From 9e737cbadcdc89c23b119701815275e7c209ff00 Mon Sep 17 00:00:00 2001
From: Alexandre Simard <as.simard@outlook.com>
Date: Mon, 26 Sep 2022 17:18:57 -0400
Subject: Solve issue #962

Fix by @MrAcademy
---
 .gitignore       | 3 ++-
 javascript/ui.js | 5 ++---
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/.gitignore b/.gitignore
index 9d78853a..fa1ab43e 100644
--- a/.gitignore
+++ b/.gitignore
@@ -19,4 +19,5 @@ __pycache__
 /webui-user.sh
 /interrogate
 /user.css
-/.idea
\ No newline at end of file
+/.idea
+/SwinIR
diff --git a/javascript/ui.js b/javascript/ui.js
index 076e9436..7db4db48 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -1,9 +1,8 @@
 // various functions for interation with ui.py not large enough to warrant putting them in separate files
 
 function selected_gallery_index(){
-    var gr = gradioApp()
-    var buttons = gradioApp().querySelectorAll(".gallery-item")
-    var button = gr.querySelector(".gallery-item.\\!ring-2")
+    var buttons = gradioApp().querySelectorAll('[style="display: block;"].tabitem .gallery-item')
+    var button = gradioApp().querySelector('[style="display: block;"].tabitem .gallery-item.\\!ring-2')
 
     var result = -1
     buttons.forEach(function(v, i){ if(v==button) { result = i } })
-- 
cgit v1.2.3


From 03ee67bfd34b9e872b33eb05fef5db83410b16f3 Mon Sep 17 00:00:00 2001
From: WDevelopsWebApps <97454358+WDevelopsWebApps@users.noreply.github.com>
Date: Wed, 28 Sep 2022 10:53:40 +0200
Subject: add advanced saving for save button

---
 modules/images.py |  5 ++++-
 modules/ui.py     | 37 +++++++++++++++++++++++++++++--------
 2 files changed, 33 insertions(+), 9 deletions(-)

diff --git a/modules/images.py b/modules/images.py
index 9458bf8d..923f81df 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -290,7 +290,10 @@ def apply_filename_pattern(x, p, seed, prompt):
         x = x.replace("[cfg]", str(p.cfg_scale))
         x = x.replace("[width]", str(p.width))
         x = x.replace("[height]", str(p.height))
-        x = x.replace("[styles]", sanitize_filename_part(", ".join(p.styles), replace_spaces=False))
+        #currently disabled if using the save button, will work otherwise 
+        # if enabled it will cause a bug because styles is not included in the save_files data dictionary
+        if hasattr(p, "styles"):
+            x = x.replace("[styles]", sanitize_filename_part(", ".join(p.styles), replace_spaces=False))
         x = x.replace("[sampler]", sanitize_filename_part(sd_samplers.samplers[p.sampler_index].name, replace_spaces=False))
 
     x = x.replace("[model_hash]", shared.sd_model.sd_model_hash)
diff --git a/modules/ui.py b/modules/ui.py
index 7db8edbd..87a86a45 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -28,6 +28,7 @@ import modules.gfpgan_model
 import modules.codeformer_model
 import modules.styles
 import modules.generation_parameters_copypaste
+from modules.images import apply_filename_pattern, get_next_sequence_number
 
 # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the bowser will not show any UI
 mimetypes.init()
@@ -90,13 +91,26 @@ def send_gradio_gallery_to_image(x):
 
 
 def save_files(js_data, images, index):
-    import csv
-
-    os.makedirs(opts.outdir_save, exist_ok=True)
-
+    import csv    
     filenames = []
 
+    #quick dictionary to class object conversion. Its neccesary due apply_filename_pattern requiring it
+    class MyObject:
+        def __init__(self, d=None):
+            if d is not None:
+                for key, value in d.items():
+                    setattr(self, key, value)
+
     data = json.loads(js_data)
+    p = MyObject(data)
+    path = opts.outdir_save
+    save_to_dirs = opts.save_to_dirs
+
+    if save_to_dirs:
+        dirname = apply_filename_pattern(opts.directories_filename_pattern or "[prompt_words]", p, p.seed, p.prompt)
+        path = os.path.join(opts.outdir_save, dirname)
+
+    os.makedirs(path, exist_ok=True)
     
     if index > -1 and opts.save_selected_only and (index > 0 or not opts.return_grid): # ensures we are looking at a specific non-grid picture, and we have save_selected_only
         images = [images[index]]
@@ -107,11 +121,18 @@ def save_files(js_data, images, index):
         writer = csv.writer(file)
         if at_start:
             writer.writerow(["prompt", "seed", "width", "height", "sampler", "cfgs", "steps", "filename", "negative_prompt"])
-
-        filename_base = str(int(time.time() * 1000))
+        file_decoration = opts.samples_filename_pattern or "[seed]-[prompt_spaces]"
+        if file_decoration != "":
+            file_decoration = "-" + file_decoration.lower()
+        file_decoration = apply_filename_pattern(file_decoration, p, p.seed, p.prompt)
+        truncated = (file_decoration[:240] + '..') if len(file_decoration) > 240 else file_decoration
+        filename_base = truncated
+
+        basecount = get_next_sequence_number(path, "")
         for i, filedata in enumerate(images):
-            filename = filename_base + ("" if len(images) == 1 else "-" + str(i + 1)) + ".png"
-            filepath = os.path.join(opts.outdir_save, filename)
+            file_number = f"{basecount+i:05}"
+            filename = file_number + filename_base + ".png"
+            filepath = os.path.join(path, filename)
 
             if filedata.startswith("data:image/png;base64,"):
                 filedata = filedata[len("data:image/png;base64,"):]
-- 
cgit v1.2.3


From c938679de7b87b4f14894d9f57fe0f40dd6e3c06 Mon Sep 17 00:00:00 2001
From: Jairo Correa <jn.j41r0@gmail.com>
Date: Wed, 28 Sep 2022 22:14:13 -0300
Subject: Fix memory leak and reduce memory usage

---
 modules/codeformer_model.py |  6 ++++--
 modules/devices.py          |  3 ++-
 modules/extras.py           |  2 ++
 modules/gfpgan_model.py     | 11 +++++------
 modules/processing.py       | 33 ++++++++++++++++++++++++++-------
 webui.py                    |  3 +++
 6 files changed, 42 insertions(+), 16 deletions(-)

diff --git a/modules/codeformer_model.py b/modules/codeformer_model.py
index 8fbdea24..2177291a 100644
--- a/modules/codeformer_model.py
+++ b/modules/codeformer_model.py
@@ -89,7 +89,7 @@ def setup_codeformer():
                             output = self.net(cropped_face_t, w=w if w is not None else shared.opts.code_former_weight, adain=True)[0]
                             restored_face = tensor2img(output, rgb2bgr=True, min_max=(-1, 1))
                         del output
-                        torch.cuda.empty_cache()
+                        devices.torch_gc()
                     except Exception as error:
                         print(f'\tFailed inference for CodeFormer: {error}', file=sys.stderr)
                         restored_face = tensor2img(cropped_face_t, rgb2bgr=True, min_max=(-1, 1))
@@ -106,7 +106,9 @@ def setup_codeformer():
                     restored_img = cv2.resize(restored_img, (0, 0), fx=original_resolution[1]/restored_img.shape[1], fy=original_resolution[0]/restored_img.shape[0], interpolation=cv2.INTER_LINEAR)
 
                 if shared.opts.face_restoration_unload:
-                    self.net.to(devices.cpu)
+                    self.net = None
+                    self.face_helper = None
+                    devices.torch_gc()
 
                 return restored_img
 
diff --git a/modules/devices.py b/modules/devices.py
index 07bb2339..df63dd88 100644
--- a/modules/devices.py
+++ b/modules/devices.py
@@ -1,4 +1,5 @@
 import torch
+import gc
 
 # has_mps is only available in nightly pytorch (for now), `getattr` for compatibility
 from modules import errors
@@ -17,8 +18,8 @@ def get_optimal_device():
 
     return cpu
 
-
 def torch_gc():
+    gc.collect()
     if torch.cuda.is_available():
         torch.cuda.empty_cache()
         torch.cuda.ipc_collect()
diff --git a/modules/extras.py b/modules/extras.py
index 9a825530..38b86167 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -98,6 +98,8 @@ def run_extras(extras_mode, image, image_folder, gfpgan_visibility, codeformer_v
 
         outputs.append(image)
 
+    devices.torch_gc()
+
     return outputs, plaintext_to_html(info), ''
 
 
diff --git a/modules/gfpgan_model.py b/modules/gfpgan_model.py
index 44c5dc6c..b1288f0c 100644
--- a/modules/gfpgan_model.py
+++ b/modules/gfpgan_model.py
@@ -49,6 +49,7 @@ def gfpgan():
 
 
 def gfpgan_fix_faces(np_image):
+    global loaded_gfpgan_model
     model = gfpgan()
 
     np_image_bgr = np_image[:, :, ::-1]
@@ -56,7 +57,9 @@ def gfpgan_fix_faces(np_image):
     np_image = gfpgan_output_bgr[:, :, ::-1]
 
     if shared.opts.face_restoration_unload:
-        model.gfpgan.to(devices.cpu)
+        del model
+        loaded_gfpgan_model = None
+        devices.torch_gc()
 
     return np_image
 
@@ -83,11 +86,7 @@ def setup_gfpgan():
                 return "GFPGAN"
 
             def restore(self, np_image):
-                np_image_bgr = np_image[:, :, ::-1]
-                cropped_faces, restored_faces, gfpgan_output_bgr = gfpgan().enhance(np_image_bgr, has_aligned=False, only_center_face=False, paste_back=True)
-                np_image = gfpgan_output_bgr[:, :, ::-1]
-
-                return np_image
+                return gfpgan_fix_faces(np_image)
 
         shared.face_restorers.append(FaceRestorerGFPGAN())
     except Exception:
diff --git a/modules/processing.py b/modules/processing.py
index 4ecdfcd2..de5cda79 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -12,7 +12,7 @@ import cv2
 from skimage import exposure
 
 import modules.sd_hijack
-from modules import devices, prompt_parser, masking
+from modules import devices, prompt_parser, masking, lowvram
 from modules.sd_hijack import model_hijack
 from modules.sd_samplers import samplers, samplers_for_img2img
 from modules.shared import opts, cmd_opts, state
@@ -335,7 +335,8 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
         if state.job_count == -1:
             state.job_count = p.n_iter
 
-        for n in range(p.n_iter):
+    for n in range(p.n_iter):
+        with torch.no_grad(), precision_scope("cuda"), ema_scope():
             if state.interrupted:
                 break
 
@@ -368,22 +369,32 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
             x_samples_ddim = p.sd_model.decode_first_stage(samples_ddim)
             x_samples_ddim = torch.clamp((x_samples_ddim + 1.0) / 2.0, min=0.0, max=1.0)
 
+            del samples_ddim
+
+            if shared.cmd_opts.lowvram or shared.cmd_opts.medvram:
+                lowvram.send_everything_to_cpu()
+
+            devices.torch_gc()
+
             if opts.filter_nsfw:
                 import modules.safety as safety
                 x_samples_ddim = modules.safety.censor_batch(x_samples_ddim)
 
-            for i, x_sample in enumerate(x_samples_ddim):
+        for i, x_sample in enumerate(x_samples_ddim):
+            with torch.no_grad(), precision_scope("cuda"), ema_scope():
                 x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2)
                 x_sample = x_sample.astype(np.uint8)
 
-                if p.restore_faces:
+            if p.restore_faces:
+                with torch.no_grad(), precision_scope("cuda"), ema_scope():
                     if opts.save and not p.do_not_save_samples and opts.save_images_before_face_restoration:
                         images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-face-restoration")
 
-                    devices.torch_gc()
-
                     x_sample = modules.face_restoration.restore_faces(x_sample)
 
+                devices.torch_gc()
+
+            with torch.no_grad(), precision_scope("cuda"), ema_scope():
                 image = Image.fromarray(x_sample)
 
                 if p.color_corrections is not None and i < len(p.color_corrections):
@@ -411,8 +422,13 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
                 infotexts.append(infotext(n, i))
                 output_images.append(image)
 
-            state.nextjob()
+        del x_samples_ddim 
 
+        devices.torch_gc()
+
+        state.nextjob()
+
+    with torch.no_grad(), precision_scope("cuda"), ema_scope():
         p.color_corrections = None
 
         index_of_first_image = 0
@@ -648,4 +664,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
         if self.mask is not None:
             samples = samples * self.nmask + self.init_latent * self.mask
 
+        del x
+        devices.torch_gc()
+
         return samples
diff --git a/webui.py b/webui.py
index c70a11c7..b61a318d 100644
--- a/webui.py
+++ b/webui.py
@@ -22,7 +22,10 @@ import modules.txt2img
 import modules.img2img
 import modules.swinir as swinir
 import modules.sd_models
+from torch.nn.functional import silu
+import ldm
 
+ldm.modules.diffusionmodules.model.nonlinearity = silu
 
 modules.codeformer_model.setup_codeformer()
 modules.gfpgan_model.setup_gfpgan()
-- 
cgit v1.2.3


From c2d5b29040132c171bc4d77f1f63da972306f22c Mon Sep 17 00:00:00 2001
From: Jairo Correa <jn.j41r0@gmail.com>
Date: Thu, 29 Sep 2022 01:14:54 -0300
Subject: Move silu to sd_hijack

---
 modules/sd_hijack.py | 12 +++---------
 webui.py             |  3 ---
 2 files changed, 3 insertions(+), 12 deletions(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index bfbd07f9..4bc58fa2 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -12,6 +12,7 @@ from ldm.util import default
 from einops import rearrange
 import ldm.modules.attention
 import ldm.modules.diffusionmodules.model
+from torch.nn.functional import silu
 
 
 # see https://github.com/basujindal/stable-diffusion/pull/117 for discussion
@@ -100,14 +101,6 @@ def split_cross_attention_forward(self, x, context=None, mask=None):
 
     return self.to_out(r2)
 
-def nonlinearity_hijack(x):
-    # swish
-    t = torch.sigmoid(x)
-    x *= t
-    del t
-
-    return x
-
 def cross_attention_attnblock_forward(self, x):
         h_ = x
         h_ = self.norm(h_)
@@ -245,11 +238,12 @@ class StableDiffusionModelHijack:
         m.cond_stage_model = FrozenCLIPEmbedderWithCustomWords(m.cond_stage_model, self)
         self.clip = m.cond_stage_model
 
+        ldm.modules.diffusionmodules.model.nonlinearity = silu
+
         if cmd_opts.opt_split_attention_v1:
             ldm.modules.attention.CrossAttention.forward = split_cross_attention_forward_v1
         elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention or torch.cuda.is_available()):
             ldm.modules.attention.CrossAttention.forward = split_cross_attention_forward
-            ldm.modules.diffusionmodules.model.nonlinearity = nonlinearity_hijack
             ldm.modules.diffusionmodules.model.AttnBlock.forward = cross_attention_attnblock_forward
 
         def flatten(el):
diff --git a/webui.py b/webui.py
index b61a318d..c70a11c7 100644
--- a/webui.py
+++ b/webui.py
@@ -22,10 +22,7 @@ import modules.txt2img
 import modules.img2img
 import modules.swinir as swinir
 import modules.sd_models
-from torch.nn.functional import silu
-import ldm
 
-ldm.modules.diffusionmodules.model.nonlinearity = silu
 
 modules.codeformer_model.setup_codeformer()
 modules.gfpgan_model.setup_gfpgan()
-- 
cgit v1.2.3


From e82ea202997cbcd2ab72891cd075d9ba270eb67d Mon Sep 17 00:00:00 2001
From: d8ahazard <d8ahazard@gmail.com>
Date: Fri, 30 Sep 2022 15:26:18 -0500
Subject: Optimize model loader

Child classes only get populated to __subclassess__ when they are imported. We don't actually need to import any of them to webui any more, so clean up webUI imports and make sure loader imports children.

Also, fix command line paths not actually being passed to the scalers.
---
 modules/modelloader.py | 19 ++++++++++++++++---
 webui.py               | 13 +++----------
 2 files changed, 19 insertions(+), 13 deletions(-)

diff --git a/modules/modelloader.py b/modules/modelloader.py
index 1106aeb7..b1721671 100644
--- a/modules/modelloader.py
+++ b/modules/modelloader.py
@@ -4,7 +4,6 @@ import importlib
 from urllib.parse import urlparse
 
 from basicsr.utils.download_util import load_file_from_url
-
 from modules import shared
 from modules.upscaler import Upscaler
 from modules.paths import script_path, models_path
@@ -120,16 +119,30 @@ def move_files(src_path: str, dest_path: str, ext_filter: str = None):
 
 
 def load_upscalers():
+    sd = shared.script_path
+    # We can only do this 'magic' method to dynamically load upscalers if they are referenced,
+    # so we'll try to import any _model.py files before looking in __subclasses__
+    modules_dir = os.path.join(sd, "modules")
+    for file in os.listdir(modules_dir):
+        if "_model.py" in file:
+            model_name = file.replace("_model.py", "")
+            full_model = f"modules.{model_name}_model"
+            try:
+                importlib.import_module(full_model)
+            except:
+                pass
     datas = []
+    c_o = vars(shared.cmd_opts)
     for cls in Upscaler.__subclasses__():
         name = cls.__name__
         module_name = cls.__module__
         module = importlib.import_module(module_name)
         class_ = getattr(module, name)
-        cmd_name = f"{name.lower().replace('upscaler', '')}-models-path"
+        cmd_name = f"{name.lower().replace('upscaler', '')}_models_path"
         opt_string = None
         try:
-            opt_string = shared.opts.__getattr__(cmd_name)
+            if cmd_name in c_o:
+                opt_string = c_o[cmd_name]
         except:
             pass
         scaler = class_(opt_string)
diff --git a/webui.py b/webui.py
index b8cccd54..ebe39a17 100644
--- a/webui.py
+++ b/webui.py
@@ -1,28 +1,21 @@
 import os
-import threading
-
-from modules import devices
-from modules.paths import script_path
 import signal
 import threading
-import modules.paths
+
 import modules.codeformer_model as codeformer
-import modules.esrgan_model as esrgan
-import modules.bsrgan_model as bsrgan
 import modules.extras
 import modules.face_restoration
 import modules.gfpgan_model as gfpgan
 import modules.img2img
-import modules.ldsr_model as ldsr
 import modules.lowvram
-import modules.realesrgan_model as realesrgan
+import modules.paths
 import modules.scripts
 import modules.sd_hijack
 import modules.sd_models
 import modules.shared as shared
-import modules.swinir_model as swinir
 import modules.txt2img
 import modules.ui
+from modules import devices
 from modules import modelloader
 from modules.paths import script_path
 from modules.shared import cmd_opts
-- 
cgit v1.2.3


From 8deae077004f0332ca607fc3a5d568b1a4705bec Mon Sep 17 00:00:00 2001
From: d8ahazard <d8ahazard@gmail.com>
Date: Fri, 30 Sep 2022 15:28:37 -0500
Subject: Add ScuNET DeNoiser/Upscaler

Q&D Implementation of ScuNET, thanks to our handy model loader. :P

https://github.com/cszn/SCUNet
---
 modules/scunet_model.py      |  90 +++++++++++++++
 modules/scunet_model_arch.py | 265 +++++++++++++++++++++++++++++++++++++++++++
 modules/shared.py            |   1 +
 3 files changed, 356 insertions(+)
 create mode 100644 modules/scunet_model.py
 create mode 100644 modules/scunet_model_arch.py

diff --git a/modules/scunet_model.py b/modules/scunet_model.py
new file mode 100644
index 00000000..7987ac14
--- /dev/null
+++ b/modules/scunet_model.py
@@ -0,0 +1,90 @@
+import os.path
+import sys
+import traceback
+
+import PIL.Image
+import numpy as np
+import torch
+from basicsr.utils.download_util import load_file_from_url
+
+import modules.upscaler
+from modules import shared, modelloader
+from modules.paths import models_path
+from modules.scunet_model_arch import SCUNet as net
+
+
+class UpscalerScuNET(modules.upscaler.Upscaler):
+    def __init__(self, dirname):
+        self.name = "ScuNET"
+        self.model_path = os.path.join(models_path, self.name)
+        self.model_name = "ScuNET GAN"
+        self.model_name2 = "ScuNET PSNR"
+        self.model_url = "https://github.com/cszn/KAIR/releases/download/v1.0/scunet_color_real_gan.pth"
+        self.model_url2 = "https://github.com/cszn/KAIR/releases/download/v1.0/scunet_color_real_psnr.pth"
+        self.user_path = dirname
+        super().__init__()
+        model_paths = self.find_models(ext_filter=[".pth"])
+        scalers = []
+        add_model2 = True
+        for file in model_paths:
+            if "http" in file:
+                name = self.model_name
+            else:
+                name = modelloader.friendly_name(file)
+            if name == self.model_name2 or file == self.model_url2:
+                add_model2 = False
+            try:
+                scaler_data = modules.upscaler.UpscalerData(name, file, self, 4)
+                scalers.append(scaler_data)
+            except Exception:
+                print(f"Error loading ScuNET model: {file}", file=sys.stderr)
+                print(traceback.format_exc(), file=sys.stderr)
+        if add_model2:
+            scaler_data2 = modules.upscaler.UpscalerData(self.model_name2, self.model_url2, self)
+            scalers.append(scaler_data2)
+        self.scalers = scalers
+
+    def do_upscale(self, img: PIL.Image, selected_file):
+        torch.cuda.empty_cache()
+
+        model = self.load_model(selected_file)
+        if model is None:
+            return img
+
+        device = shared.device
+        img = np.array(img)
+        img = img[:, :, ::-1]
+        img = np.moveaxis(img, 2, 0) / 255
+        img = torch.from_numpy(img).float()
+        img = img.unsqueeze(0).to(shared.device)
+
+        img = img.to(device)
+        with torch.no_grad():
+            output = model(img)
+        output = output.squeeze().float().cpu().clamp_(0, 1).numpy()
+        output = 255. * np.moveaxis(output, 0, 2)
+        output = output.astype(np.uint8)
+        output = output[:, :, ::-1]
+        torch.cuda.empty_cache()
+        return PIL.Image.fromarray(output, 'RGB')
+
+    def load_model(self, path: str):
+        device = shared.device
+        if "http" in path:
+            filename = load_file_from_url(url=self.model_url, model_dir=self.model_path, file_name="%s.pth" % self.name,
+                                          progress=True)
+        else:
+            filename = path
+        if not os.path.exists(os.path.join(self.model_path, filename)) or filename is None:
+            print(f"ScuNET: Unable to load model from {filename}", file=sys.stderr)
+            return None
+
+        model = net(in_nc=3, config=[4, 4, 4, 4, 4, 4, 4], dim=64)
+        model.load_state_dict(torch.load(filename), strict=True)
+        model.eval()
+        for k, v in model.named_parameters():
+            v.requires_grad = False
+        model = model.to(device)
+
+        return model
+
diff --git a/modules/scunet_model_arch.py b/modules/scunet_model_arch.py
new file mode 100644
index 00000000..972a2639
--- /dev/null
+++ b/modules/scunet_model_arch.py
@@ -0,0 +1,265 @@
+# -*- coding: utf-8 -*-
+import numpy as np
+import torch
+import torch.nn as nn
+from einops import rearrange
+from einops.layers.torch import Rearrange
+from timm.models.layers import trunc_normal_, DropPath
+
+
+class WMSA(nn.Module):
+    """ Self-attention module in Swin Transformer
+    """
+
+    def __init__(self, input_dim, output_dim, head_dim, window_size, type):
+        super(WMSA, self).__init__()
+        self.input_dim = input_dim
+        self.output_dim = output_dim
+        self.head_dim = head_dim
+        self.scale = self.head_dim ** -0.5
+        self.n_heads = input_dim // head_dim
+        self.window_size = window_size
+        self.type = type
+        self.embedding_layer = nn.Linear(self.input_dim, 3 * self.input_dim, bias=True)
+
+        self.relative_position_params = nn.Parameter(
+            torch.zeros((2 * window_size - 1) * (2 * window_size - 1), self.n_heads))
+
+        self.linear = nn.Linear(self.input_dim, self.output_dim)
+
+        trunc_normal_(self.relative_position_params, std=.02)
+        self.relative_position_params = torch.nn.Parameter(
+            self.relative_position_params.view(2 * window_size - 1, 2 * window_size - 1, self.n_heads).transpose(1,
+                                                                                                                 2).transpose(
+                0, 1))
+
+    def generate_mask(self, h, w, p, shift):
+        """ generating the mask of SW-MSA
+        Args:
+            shift: shift parameters in CyclicShift.
+        Returns:
+            attn_mask: should be (1 1 w p p),
+        """
+        # supporting sqaure.
+        attn_mask = torch.zeros(h, w, p, p, p, p, dtype=torch.bool, device=self.relative_position_params.device)
+        if self.type == 'W':
+            return attn_mask
+
+        s = p - shift
+        attn_mask[-1, :, :s, :, s:, :] = True
+        attn_mask[-1, :, s:, :, :s, :] = True
+        attn_mask[:, -1, :, :s, :, s:] = True
+        attn_mask[:, -1, :, s:, :, :s] = True
+        attn_mask = rearrange(attn_mask, 'w1 w2 p1 p2 p3 p4 -> 1 1 (w1 w2) (p1 p2) (p3 p4)')
+        return attn_mask
+
+    def forward(self, x):
+        """ Forward pass of Window Multi-head Self-attention module.
+        Args:
+            x: input tensor with shape of [b h w c];
+            attn_mask: attention mask, fill -inf where the value is True;
+        Returns:
+            output: tensor shape [b h w c]
+        """
+        if self.type != 'W': x = torch.roll(x, shifts=(-(self.window_size // 2), -(self.window_size // 2)), dims=(1, 2))
+        x = rearrange(x, 'b (w1 p1) (w2 p2) c -> b w1 w2 p1 p2 c', p1=self.window_size, p2=self.window_size)
+        h_windows = x.size(1)
+        w_windows = x.size(2)
+        # sqaure validation
+        # assert h_windows == w_windows
+
+        x = rearrange(x, 'b w1 w2 p1 p2 c -> b (w1 w2) (p1 p2) c', p1=self.window_size, p2=self.window_size)
+        qkv = self.embedding_layer(x)
+        q, k, v = rearrange(qkv, 'b nw np (threeh c) -> threeh b nw np c', c=self.head_dim).chunk(3, dim=0)
+        sim = torch.einsum('hbwpc,hbwqc->hbwpq', q, k) * self.scale
+        # Adding learnable relative embedding
+        sim = sim + rearrange(self.relative_embedding(), 'h p q -> h 1 1 p q')
+        # Using Attn Mask to distinguish different subwindows.
+        if self.type != 'W':
+            attn_mask = self.generate_mask(h_windows, w_windows, self.window_size, shift=self.window_size // 2)
+            sim = sim.masked_fill_(attn_mask, float("-inf"))
+
+        probs = nn.functional.softmax(sim, dim=-1)
+        output = torch.einsum('hbwij,hbwjc->hbwic', probs, v)
+        output = rearrange(output, 'h b w p c -> b w p (h c)')
+        output = self.linear(output)
+        output = rearrange(output, 'b (w1 w2) (p1 p2) c -> b (w1 p1) (w2 p2) c', w1=h_windows, p1=self.window_size)
+
+        if self.type != 'W': output = torch.roll(output, shifts=(self.window_size // 2, self.window_size // 2),
+                                                 dims=(1, 2))
+        return output
+
+    def relative_embedding(self):
+        cord = torch.tensor(np.array([[i, j] for i in range(self.window_size) for j in range(self.window_size)]))
+        relation = cord[:, None, :] - cord[None, :, :] + self.window_size - 1
+        # negative is allowed
+        return self.relative_position_params[:, relation[:, :, 0].long(), relation[:, :, 1].long()]
+
+
+class Block(nn.Module):
+    def __init__(self, input_dim, output_dim, head_dim, window_size, drop_path, type='W', input_resolution=None):
+        """ SwinTransformer Block
+        """
+        super(Block, self).__init__()
+        self.input_dim = input_dim
+        self.output_dim = output_dim
+        assert type in ['W', 'SW']
+        self.type = type
+        if input_resolution <= window_size:
+            self.type = 'W'
+
+        self.ln1 = nn.LayerNorm(input_dim)
+        self.msa = WMSA(input_dim, input_dim, head_dim, window_size, self.type)
+        self.drop_path = DropPath(drop_path) if drop_path > 0. else nn.Identity()
+        self.ln2 = nn.LayerNorm(input_dim)
+        self.mlp = nn.Sequential(
+            nn.Linear(input_dim, 4 * input_dim),
+            nn.GELU(),
+            nn.Linear(4 * input_dim, output_dim),
+        )
+
+    def forward(self, x):
+        x = x + self.drop_path(self.msa(self.ln1(x)))
+        x = x + self.drop_path(self.mlp(self.ln2(x)))
+        return x
+
+
+class ConvTransBlock(nn.Module):
+    def __init__(self, conv_dim, trans_dim, head_dim, window_size, drop_path, type='W', input_resolution=None):
+        """ SwinTransformer and Conv Block
+        """
+        super(ConvTransBlock, self).__init__()
+        self.conv_dim = conv_dim
+        self.trans_dim = trans_dim
+        self.head_dim = head_dim
+        self.window_size = window_size
+        self.drop_path = drop_path
+        self.type = type
+        self.input_resolution = input_resolution
+
+        assert self.type in ['W', 'SW']
+        if self.input_resolution <= self.window_size:
+            self.type = 'W'
+
+        self.trans_block = Block(self.trans_dim, self.trans_dim, self.head_dim, self.window_size, self.drop_path,
+                                 self.type, self.input_resolution)
+        self.conv1_1 = nn.Conv2d(self.conv_dim + self.trans_dim, self.conv_dim + self.trans_dim, 1, 1, 0, bias=True)
+        self.conv1_2 = nn.Conv2d(self.conv_dim + self.trans_dim, self.conv_dim + self.trans_dim, 1, 1, 0, bias=True)
+
+        self.conv_block = nn.Sequential(
+            nn.Conv2d(self.conv_dim, self.conv_dim, 3, 1, 1, bias=False),
+            nn.ReLU(True),
+            nn.Conv2d(self.conv_dim, self.conv_dim, 3, 1, 1, bias=False)
+        )
+
+    def forward(self, x):
+        conv_x, trans_x = torch.split(self.conv1_1(x), (self.conv_dim, self.trans_dim), dim=1)
+        conv_x = self.conv_block(conv_x) + conv_x
+        trans_x = Rearrange('b c h w -> b h w c')(trans_x)
+        trans_x = self.trans_block(trans_x)
+        trans_x = Rearrange('b h w c -> b c h w')(trans_x)
+        res = self.conv1_2(torch.cat((conv_x, trans_x), dim=1))
+        x = x + res
+
+        return x
+
+
+class SCUNet(nn.Module):
+    # def __init__(self, in_nc=3, config=[2, 2, 2, 2, 2, 2, 2], dim=64, drop_path_rate=0.0, input_resolution=256):
+    def __init__(self, in_nc=3, config=None, dim=64, drop_path_rate=0.0, input_resolution=256):
+        super(SCUNet, self).__init__()
+        if config is None:
+            config = [2, 2, 2, 2, 2, 2, 2]
+        self.config = config
+        self.dim = dim
+        self.head_dim = 32
+        self.window_size = 8
+
+        # drop path rate for each layer
+        dpr = [x.item() for x in torch.linspace(0, drop_path_rate, sum(config))]
+
+        self.m_head = [nn.Conv2d(in_nc, dim, 3, 1, 1, bias=False)]
+
+        begin = 0
+        self.m_down1 = [ConvTransBlock(dim // 2, dim // 2, self.head_dim, self.window_size, dpr[i + begin],
+                                       'W' if not i % 2 else 'SW', input_resolution)
+                        for i in range(config[0])] + \
+                       [nn.Conv2d(dim, 2 * dim, 2, 2, 0, bias=False)]
+
+        begin += config[0]
+        self.m_down2 = [ConvTransBlock(dim, dim, self.head_dim, self.window_size, dpr[i + begin],
+                                       'W' if not i % 2 else 'SW', input_resolution // 2)
+                        for i in range(config[1])] + \
+                       [nn.Conv2d(2 * dim, 4 * dim, 2, 2, 0, bias=False)]
+
+        begin += config[1]
+        self.m_down3 = [ConvTransBlock(2 * dim, 2 * dim, self.head_dim, self.window_size, dpr[i + begin],
+                                       'W' if not i % 2 else 'SW', input_resolution // 4)
+                        for i in range(config[2])] + \
+                       [nn.Conv2d(4 * dim, 8 * dim, 2, 2, 0, bias=False)]
+
+        begin += config[2]
+        self.m_body = [ConvTransBlock(4 * dim, 4 * dim, self.head_dim, self.window_size, dpr[i + begin],
+                                      'W' if not i % 2 else 'SW', input_resolution // 8)
+                       for i in range(config[3])]
+
+        begin += config[3]
+        self.m_up3 = [nn.ConvTranspose2d(8 * dim, 4 * dim, 2, 2, 0, bias=False), ] + \
+                     [ConvTransBlock(2 * dim, 2 * dim, self.head_dim, self.window_size, dpr[i + begin],
+                                     'W' if not i % 2 else 'SW', input_resolution // 4)
+                      for i in range(config[4])]
+
+        begin += config[4]
+        self.m_up2 = [nn.ConvTranspose2d(4 * dim, 2 * dim, 2, 2, 0, bias=False), ] + \
+                     [ConvTransBlock(dim, dim, self.head_dim, self.window_size, dpr[i + begin],
+                                     'W' if not i % 2 else 'SW', input_resolution // 2)
+                      for i in range(config[5])]
+
+        begin += config[5]
+        self.m_up1 = [nn.ConvTranspose2d(2 * dim, dim, 2, 2, 0, bias=False), ] + \
+                     [ConvTransBlock(dim // 2, dim // 2, self.head_dim, self.window_size, dpr[i + begin],
+                                     'W' if not i % 2 else 'SW', input_resolution)
+                      for i in range(config[6])]
+
+        self.m_tail = [nn.Conv2d(dim, in_nc, 3, 1, 1, bias=False)]
+
+        self.m_head = nn.Sequential(*self.m_head)
+        self.m_down1 = nn.Sequential(*self.m_down1)
+        self.m_down2 = nn.Sequential(*self.m_down2)
+        self.m_down3 = nn.Sequential(*self.m_down3)
+        self.m_body = nn.Sequential(*self.m_body)
+        self.m_up3 = nn.Sequential(*self.m_up3)
+        self.m_up2 = nn.Sequential(*self.m_up2)
+        self.m_up1 = nn.Sequential(*self.m_up1)
+        self.m_tail = nn.Sequential(*self.m_tail)
+        # self.apply(self._init_weights)
+
+    def forward(self, x0):
+
+        h, w = x0.size()[-2:]
+        paddingBottom = int(np.ceil(h / 64) * 64 - h)
+        paddingRight = int(np.ceil(w / 64) * 64 - w)
+        x0 = nn.ReplicationPad2d((0, paddingRight, 0, paddingBottom))(x0)
+
+        x1 = self.m_head(x0)
+        x2 = self.m_down1(x1)
+        x3 = self.m_down2(x2)
+        x4 = self.m_down3(x3)
+        x = self.m_body(x4)
+        x = self.m_up3(x + x4)
+        x = self.m_up2(x + x3)
+        x = self.m_up1(x + x2)
+        x = self.m_tail(x + x1)
+
+        x = x[..., :h, :w]
+
+        return x
+
+    def _init_weights(self, m):
+        if isinstance(m, nn.Linear):
+            trunc_normal_(m.weight, std=.02)
+            if m.bias is not None:
+                nn.init.constant_(m.bias, 0)
+        elif isinstance(m, nn.LayerNorm):
+            nn.init.constant_(m.bias, 0)
+            nn.init.constant_(m.weight, 1.0)
\ No newline at end of file
diff --git a/modules/shared.py b/modules/shared.py
index 8428c7a3..a48b995a 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -40,6 +40,7 @@ parser.add_argument("--gfpgan-models-path", type=str, help="Path to directory wi
 parser.add_argument("--esrgan-models-path", type=str, help="Path to directory with ESRGAN model file(s).", default=os.path.join(model_path, 'ESRGAN'))
 parser.add_argument("--bsrgan-models-path", type=str, help="Path to directory with BSRGAN model file(s).", default=os.path.join(model_path, 'BSRGAN'))
 parser.add_argument("--realesrgan-models-path", type=str, help="Path to directory with RealESRGAN model file(s).", default=os.path.join(model_path, 'RealESRGAN'))
+parser.add_argument("--scunet-models-path", type=str, help="Path to directory with ScuNET model file(s).", default=os.path.join(model_path, 'ScuNET'))
 parser.add_argument("--swinir-models-path", type=str, help="Path to directory with SwinIR model file(s).", default=os.path.join(model_path, 'SwinIR'))
 parser.add_argument("--ldsr-models-path", type=str, help="Path to directory with LDSR model file(s).", default=os.path.join(model_path, 'LDSR'))
 parser.add_argument("--opt-split-attention", action='store_true', help="force-enables cross-attention layer optimization. By default, it's on for torch.cuda and off for other torch devices.")
-- 
cgit v1.2.3


From abdbf1de646f007b6d76cfb3f416fdfaadb57903 Mon Sep 17 00:00:00 2001
From: Liam <liamthekerr@gmail.com>
Date: Thu, 29 Sep 2022 14:40:47 -0400
Subject: token counters now update when roll artist and style buttons are
 pressed
 https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/1194#issuecomment-1261203893

---
 javascript/ui.js | 28 ++++++++++++++++++++++------
 modules/ui.py    |  6 +++++-
 2 files changed, 27 insertions(+), 7 deletions(-)

diff --git a/javascript/ui.js b/javascript/ui.js
index bfe02410..88fd45ae 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -199,12 +199,21 @@ let txt2img_textarea, img2img_textarea = undefined;
 let wait_time = 800
 let token_timeout;
 
-function submit_prompt(event, generate_button_id) {
-    if (event.altKey && event.keyCode === 13) {
-        event.preventDefault();
-        gradioApp().getElementById(generate_button_id).click();
-        return;
-    }
+function roll_artist_txt2img(prompt_text) {
+	update_token_counter("txt2img_token_button")
+	return prompt_text;
+}
+function roll_artist_img2img(prompt_text) {
+	update_token_counter("img2img_token_button")
+	return prompt_text;
+}
+function update_style_txt2img(prompt_text, negative_prompt, style1, style2) {
+	update_token_counter("txt2img_token_button")
+	return [prompt_text, negative_prompt, style1, style2]
+}
+function update_style_img2img(prompt_text, negative_prompt, style1, style2) {
+	update_token_counter("img2img_token_button")
+	return [prompt_text, negative_prompt, style1, style2]
 }
 
 function update_token_counter(button_id) {
@@ -212,3 +221,10 @@ function update_token_counter(button_id) {
 		clearTimeout(token_timeout);
 	token_timeout = setTimeout(() => gradioApp().getElementById(button_id)?.click(), wait_time);
 }
+function submit_prompt(event, generate_button_id) {
+    if (event.altKey && event.keyCode === 13) {
+        event.preventDefault();
+        gradioApp().getElementById(generate_button_id).click();
+        return;
+    }
+}
\ No newline at end of file
diff --git a/modules/ui.py b/modules/ui.py
index 15572bb0..5eea1860 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -539,6 +539,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
 
             roll.click(
                 fn=roll_artist,
+                _js="roll_artist_txt2img",
                 inputs=[
                     txt2img_prompt,
                 ],
@@ -743,6 +744,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
 
             roll.click(
                 fn=roll_artist,
+                _js="roll_artist_img2img",
                 inputs=[
                     img2img_prompt,
                 ],
@@ -753,6 +755,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
 
             prompts = [(txt2img_prompt, txt2img_negative_prompt), (img2img_prompt, img2img_negative_prompt)]
             style_dropdowns = [(txt2img_prompt_style, txt2img_prompt_style2), (img2img_prompt_style, img2img_prompt_style2)]
+            style_js_funcs = ["update_style_txt2img", "update_style_img2img"]
 
             for button, (prompt, negative_prompt) in zip([txt2img_save_style, img2img_save_style], prompts):
                 button.click(
@@ -764,9 +767,10 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
                     outputs=[txt2img_prompt_style, img2img_prompt_style, txt2img_prompt_style2, img2img_prompt_style2],
                 )
 
-            for button, (prompt, negative_prompt), (style1, style2) in zip([txt2img_prompt_style_apply, img2img_prompt_style_apply], prompts, style_dropdowns):
+            for button, (prompt, negative_prompt), (style1, style2), js_func in zip([txt2img_prompt_style_apply, img2img_prompt_style_apply], prompts, style_dropdowns, style_js_funcs):
                 button.click(
                     fn=apply_styles,
+                    _js=js_func,
                     inputs=[prompt, negative_prompt, style1, style2],
                     outputs=[prompt, negative_prompt, style1, style2],
                 )
-- 
cgit v1.2.3


From ff8dc1908af088d0ed43fb85baad662733c5ca9c Mon Sep 17 00:00:00 2001
From: Liam <liamthekerr@gmail.com>
Date: Thu, 29 Sep 2022 15:47:06 -0400
Subject: fixed token counter for prompt editing

---
 modules/ui.py | 20 +++++++++++++-------
 1 file changed, 13 insertions(+), 7 deletions(-)

diff --git a/modules/ui.py b/modules/ui.py
index 5eea1860..6bf28562 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -11,6 +11,7 @@ import time
 import traceback
 import platform
 import subprocess as sp
+from functools import reduce
 
 import numpy as np
 import torch
@@ -32,6 +33,7 @@ import modules.gfpgan_model
 import modules.codeformer_model
 import modules.styles
 import modules.generation_parameters_copypaste
+from modules.prompt_parser import get_learned_conditioning_prompt_schedules
 
 # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the bowser will not show any UI
 mimetypes.init()
@@ -345,8 +347,11 @@ def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info:
         outputs=[seed, dummy_component]
     )
 
-def update_token_counter(text):
-    tokens, token_count, max_length = model_hijack.tokenize(text)
+def update_token_counter(text, steps):
+    prompt_schedules = get_learned_conditioning_prompt_schedules([text], steps)
+    flat_prompts = reduce(lambda list1, list2: list1+list2, prompt_schedules)
+    prompts = [prompt_text for step,prompt_text in flat_prompts]
+    tokens, token_count, max_length = max([model_hijack.tokenize(prompt) for prompt in prompts], key=lambda args: args[1])
     style_class = ' class="red"' if (token_count > max_length) else ""
     return f"<span {style_class}>{token_count}/{max_length}</span>"
 
@@ -364,8 +369,7 @@ def create_toprow(is_img2img):
                     roll = gr.Button(value=art_symbol, elem_id="roll", visible=len(shared.artist_db.artists) > 0)
                     paste = gr.Button(value=paste_symbol, elem_id="paste")
                     token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_token_counter")
-                    hidden_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button")
-                    hidden_button.click(fn=update_token_counter, inputs=[prompt], outputs=[token_counter])
+                    token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button")
 
                 with gr.Column(scale=10, elem_id="style_pos_col"):
                     prompt_style = gr.Dropdown(label="Style 1", elem_id=f"{id_part}_style_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())), visible=len(shared.prompt_styles.styles) > 1)
@@ -396,7 +400,7 @@ def create_toprow(is_img2img):
                 prompt_style_apply = gr.Button('Apply style', elem_id="style_apply")
                 save_style = gr.Button('Create style', elem_id="style_create")
 
-    return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, interrogate, prompt_style_apply, save_style, paste
+    return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, interrogate, prompt_style_apply, save_style, paste, token_counter, token_button
 
 
 def setup_progressbar(progressbar, preview, id_part):
@@ -419,7 +423,7 @@ def setup_progressbar(progressbar, preview, id_part):
 
 def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
     with gr.Blocks(analytics_enabled=False) as txt2img_interface:
-        txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, txt2img_prompt_style_apply, txt2img_save_style, paste = create_toprow(is_img2img=False)
+        txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, txt2img_prompt_style_apply, txt2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=False)
         dummy_component = gr.Label(visible=False)
 
         with gr.Row(elem_id='txt2img_progress_row'):
@@ -568,9 +572,10 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
                 (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)),
             ]
             modules.generation_parameters_copypaste.connect_paste(paste, txt2img_paste_fields, txt2img_prompt)
+            token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter])
 
     with gr.Blocks(analytics_enabled=False) as img2img_interface:
-        img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_prompt_style_apply, img2img_save_style, paste = create_toprow(is_img2img=True)
+        img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_prompt_style_apply, img2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=True)
 
         with gr.Row(elem_id='img2img_progress_row'):
             with gr.Column(scale=1):
@@ -793,6 +798,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
                 (denoising_strength, "Denoising strength"),
             ]
             modules.generation_parameters_copypaste.connect_paste(paste, img2img_paste_fields, img2img_prompt)
+            token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter])
 
     with gr.Blocks(analytics_enabled=False) as extras_interface:
         with gr.Row().style(equal_height=False):
-- 
cgit v1.2.3


From 3c6a049fc3c6b54ada3736710a7e86663ea7f3d9 Mon Sep 17 00:00:00 2001
From: Liam <liamthekerr@gmail.com>
Date: Fri, 30 Sep 2022 12:12:44 -0400
Subject: consolidated token counter functions

---
 javascript/ui.js | 21 +++++++++------------
 modules/ui.py    |  6 +++---
 2 files changed, 12 insertions(+), 15 deletions(-)

diff --git a/javascript/ui.js b/javascript/ui.js
index 88fd45ae..f94ed081 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -199,21 +199,18 @@ let txt2img_textarea, img2img_textarea = undefined;
 let wait_time = 800
 let token_timeout;
 
-function roll_artist_txt2img(prompt_text) {
+function update_txt2img_tokens(...args) {
 	update_token_counter("txt2img_token_button")
-	return prompt_text;
+	if (args.length == 2)
+		return args[0]
+	return args;
 }
-function roll_artist_img2img(prompt_text) {
-	update_token_counter("img2img_token_button")
-	return prompt_text;
-}
-function update_style_txt2img(prompt_text, negative_prompt, style1, style2) {
-	update_token_counter("txt2img_token_button")
-	return [prompt_text, negative_prompt, style1, style2]
-}
-function update_style_img2img(prompt_text, negative_prompt, style1, style2) {
+
+function update_img2img_tokens(...args) {
 	update_token_counter("img2img_token_button")
-	return [prompt_text, negative_prompt, style1, style2]
+	if (args.length == 2)
+		return args[0]
+	return args;
 }
 
 function update_token_counter(button_id) {
diff --git a/modules/ui.py b/modules/ui.py
index 6bf28562..40c08984 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -543,7 +543,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
 
             roll.click(
                 fn=roll_artist,
-                _js="roll_artist_txt2img",
+                _js="update_txt2img_tokens",
                 inputs=[
                     txt2img_prompt,
                 ],
@@ -749,7 +749,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
 
             roll.click(
                 fn=roll_artist,
-                _js="roll_artist_img2img",
+                _js="update_img2img_tokens",
                 inputs=[
                     img2img_prompt,
                 ],
@@ -760,7 +760,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
 
             prompts = [(txt2img_prompt, txt2img_negative_prompt), (img2img_prompt, img2img_negative_prompt)]
             style_dropdowns = [(txt2img_prompt_style, txt2img_prompt_style2), (img2img_prompt_style, img2img_prompt_style2)]
-            style_js_funcs = ["update_style_txt2img", "update_style_img2img"]
+            style_js_funcs = ["update_txt2img_tokens", "update_img2img_tokens"]
 
             for button, (prompt, negative_prompt) in zip([txt2img_save_style, img2img_save_style], prompts):
                 button.click(
-- 
cgit v1.2.3


From bdaa36c84470adbdce3e98c01a69af5e95adfb02 Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Fri, 30 Sep 2022 23:53:25 -0400
Subject: When device is MPS, use CPU for GFPGAN instead

GFPGAN will not work if the device is MPS, so default to CPU instead.
---
 modules/devices.py      | 2 +-
 modules/gfpgan_model.py | 6 +++---
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/modules/devices.py b/modules/devices.py
index 07bb2339..08bb26d6 100644
--- a/modules/devices.py
+++ b/modules/devices.py
@@ -34,7 +34,7 @@ errors.run(enable_tf32, "Enabling TF32")
 
 
 device = get_optimal_device()
-device_codeformer = cpu if has_mps else device
+device_gfpgan = device_codeformer = cpu if device.type == 'mps' else device
 
 
 def randn(seed, shape):
diff --git a/modules/gfpgan_model.py b/modules/gfpgan_model.py
index bb30d733..fcd8544a 100644
--- a/modules/gfpgan_model.py
+++ b/modules/gfpgan_model.py
@@ -21,7 +21,7 @@ def gfpgann():
     global loaded_gfpgan_model
     global model_path
     if loaded_gfpgan_model is not None:
-        loaded_gfpgan_model.gfpgan.to(shared.device)
+        loaded_gfpgan_model.gfpgan.to(devices.device_gfpgan)
         return loaded_gfpgan_model
 
     if gfpgan_constructor is None:
@@ -36,8 +36,8 @@ def gfpgann():
     else:
         print("Unable to load gfpgan model!")
         return None
-    model = gfpgan_constructor(model_path=model_file, upscale=1, arch='clean', channel_multiplier=2, bg_upsampler=None)
-    model.gfpgan.to(shared.device)
+    model = gfpgan_constructor(model_path=model_file, upscale=1, arch='clean', channel_multiplier=2, bg_upsampler=None, device=devices.device_gfpgan)
+    model.gfpgan.to(devices.device_gfpgan)
     loaded_gfpgan_model = model
 
     return model
-- 
cgit v1.2.3


From 4c2478a68a4f11959fe4887d38e0436eac19f97e Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sat, 1 Oct 2022 18:30:53 +0100
Subject: add script reload method

---
 modules/scripts.py | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/modules/scripts.py b/modules/scripts.py
index 7c3bd5e7..3c14b9e3 100644
--- a/modules/scripts.py
+++ b/modules/scripts.py
@@ -165,3 +165,12 @@ class ScriptRunner:
 
 scripts_txt2img = ScriptRunner()
 scripts_img2img = ScriptRunner()
+
+def reload_scripts(basedir):
+  global scripts_txt2img,scripts_img2img
+
+  scripts_data.clear()
+  load_scripts(basedir)
+
+  scripts_txt2img = ScriptRunner()
+  scripts_img2img = ScriptRunner()
-- 
cgit v1.2.3


From 95f35d04ab1636e08f69ca9c0ae2446714870e80 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sat, 1 Oct 2022 18:31:58 +0100
Subject: Host busy thread, check for reload

---
 webui.py | 48 ++++++++++++++++++++++++++++++++----------------
 1 file changed, 32 insertions(+), 16 deletions(-)

diff --git a/webui.py b/webui.py
index b8cccd54..4948c394 100644
--- a/webui.py
+++ b/webui.py
@@ -86,22 +86,38 @@ def webui():
 
     signal.signal(signal.SIGINT, sigint_handler)
 
-    demo = modules.ui.create_ui(
-        txt2img=wrap_gradio_gpu_call(modules.txt2img.txt2img),
-        img2img=wrap_gradio_gpu_call(modules.img2img.img2img),
-        run_extras=wrap_gradio_gpu_call(modules.extras.run_extras),
-        run_pnginfo=modules.extras.run_pnginfo,
-        run_modelmerger=modules.extras.run_modelmerger
-    )
-
-    demo.launch(
-        share=cmd_opts.share,
-        server_name="0.0.0.0" if cmd_opts.listen else None,
-        server_port=cmd_opts.port,
-        debug=cmd_opts.gradio_debug,
-        auth=[tuple(cred.split(':')) for cred in cmd_opts.gradio_auth.strip('"').split(',')] if cmd_opts.gradio_auth else None,
-        inbrowser=cmd_opts.autolaunch,
-    )
+    while 1:
+
+      demo = modules.ui.create_ui(
+          txt2img=wrap_gradio_gpu_call(modules.txt2img.txt2img),
+          img2img=wrap_gradio_gpu_call(modules.img2img.img2img),
+          run_extras=wrap_gradio_gpu_call(modules.extras.run_extras),
+          run_pnginfo=modules.extras.run_pnginfo,
+          run_modelmerger=modules.extras.run_modelmerger
+      )
+
+
+      demo.launch(
+          share=cmd_opts.share,
+          server_name="0.0.0.0" if cmd_opts.listen else None,
+          server_port=cmd_opts.port,
+          debug=cmd_opts.gradio_debug,
+          auth=[tuple(cred.split(':')) for cred in cmd_opts.gradio_auth.strip('"').split(',')] if cmd_opts.gradio_auth else None,
+          inbrowser=cmd_opts.autolaunch,
+          prevent_thread_lock=True
+      )
+
+      while 1:
+        time.sleep(0.5)
+        if getattr(demo,'do_restart',False):
+          time.sleep(0.5)
+          demo.close()
+          time.sleep(0.5)
+          break
+
+      print('Reloading Scripts')
+      modules.scripts.reload_scripts(os.path.join(script_path, "scripts"))
+      print('Restarting Gradio')
 
 
 if __name__ == "__main__":
-- 
cgit v1.2.3


From 4f8490cd5630823ac44de8b5c5e4325bdbbea7fa Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sat, 1 Oct 2022 18:33:31 +0100
Subject: add restart button

---
 modules/ui.py | 15 ++++++++++++++-
 1 file changed, 14 insertions(+), 1 deletion(-)

diff --git a/modules/ui.py b/modules/ui.py
index 15572bb0..ec6aaa28 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1002,6 +1002,17 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
             _js='function(){}'
         )
 
+        def request_restart():
+          settings_interface.gradio_ref.do_restart = True
+
+        restart_gradio = gr.Button(value='Restart Gradio and Refresh Scripts')
+        restart_gradio.click(
+            fn=request_restart,
+            inputs=[],
+            outputs=[],
+            _js='function(){document.body.innerHTML=\'<h1 style="color:white;text-align: center;">Reloading</h1>\';setTimeout(function(){location.reload()},2000)}'
+        )
+        
         if column is not None:
             column.__exit__()
 
@@ -1026,7 +1037,9 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
         css += css_hide_progressbar
 
     with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion") as demo:
-
+        
+        settings_interface.gradio_ref = demo
+        
         with gr.Tabs() as tabs:
             for interface, label, ifid in interfaces:
                 with gr.TabItem(label, id=ifid):
-- 
cgit v1.2.3


From 121ed7d36febe94995774973b5edc1ba2ba84aad Mon Sep 17 00:00:00 2001
From: Alexandre Simard <as.simard@outlook.com>
Date: Sat, 1 Oct 2022 14:04:20 -0400
Subject: Add progress bar for SwinIR in cmd

I do not know how to add them to the UI...
---
 modules/swinir_model.py | 27 +++++++++++++++------------
 webui-user.bat          |  2 +-
 2 files changed, 16 insertions(+), 13 deletions(-)

diff --git a/modules/swinir_model.py b/modules/swinir_model.py
index 41fda5a7..9bd454c6 100644
--- a/modules/swinir_model.py
+++ b/modules/swinir_model.py
@@ -5,6 +5,7 @@ import numpy as np
 import torch
 from PIL import Image
 from basicsr.utils.download_util import load_file_from_url
+from tqdm import tqdm
 
 from modules import modelloader
 from modules.paths import models_path
@@ -122,18 +123,20 @@ def inference(img, model, tile, tile_overlap, window_size, scale):
     E = torch.zeros(b, c, h * sf, w * sf, dtype=torch.half, device=device).type_as(img)
     W = torch.zeros_like(E, dtype=torch.half, device=device)
 
-    for h_idx in h_idx_list:
-        for w_idx in w_idx_list:
-            in_patch = img[..., h_idx: h_idx + tile, w_idx: w_idx + tile]
-            out_patch = model(in_patch)
-            out_patch_mask = torch.ones_like(out_patch)
-
-            E[
-            ..., h_idx * sf: (h_idx + tile) * sf, w_idx * sf: (w_idx + tile) * sf
-            ].add_(out_patch)
-            W[
-            ..., h_idx * sf: (h_idx + tile) * sf, w_idx * sf: (w_idx + tile) * sf
-            ].add_(out_patch_mask)
+    with tqdm(total=len(h_idx_list) * len(w_idx_list), desc="SwinIR tiles") as pbar:
+        for h_idx in h_idx_list:
+            for w_idx in w_idx_list:
+                in_patch = img[..., h_idx: h_idx + tile, w_idx: w_idx + tile]
+                out_patch = model(in_patch)
+                out_patch_mask = torch.ones_like(out_patch)
+
+                E[
+                ..., h_idx * sf: (h_idx + tile) * sf, w_idx * sf: (w_idx + tile) * sf
+                ].add_(out_patch)
+                W[
+                ..., h_idx * sf: (h_idx + tile) * sf, w_idx * sf: (w_idx + tile) * sf
+                ].add_(out_patch_mask)
+                pbar.update(1)
     output = E.div_(W)
 
     return output
diff --git a/webui-user.bat b/webui-user.bat
index e5a257be..5c778953 100644
--- a/webui-user.bat
+++ b/webui-user.bat
@@ -3,6 +3,6 @@
 set PYTHON=
 set GIT=
 set VENV_DIR=
-set COMMANDLINE_ARGS=
+set COMMANDLINE_ARGS=--autolaunch
 
 call webui.bat
-- 
cgit v1.2.3


From b8a2b0453b62e4e99d0e5c049313402bc79056b5 Mon Sep 17 00:00:00 2001
From: Alexandre Simard <as.simard@outlook.com>
Date: Sat, 1 Oct 2022 14:07:20 -0400
Subject: Set launch options to default

---
 webui-user.bat | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/webui-user.bat b/webui-user.bat
index 5c778953..e5a257be 100644
--- a/webui-user.bat
+++ b/webui-user.bat
@@ -3,6 +3,6 @@
 set PYTHON=
 set GIT=
 set VENV_DIR=
-set COMMANDLINE_ARGS=--autolaunch
+set COMMANDLINE_ARGS=
 
 call webui.bat
-- 
cgit v1.2.3


From a9044475c06204deb886d2a69467d0d3a9f5c9be Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sat, 1 Oct 2022 21:47:42 +0100
Subject: add time import

---
 webui.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/webui.py b/webui.py
index 4948c394..e2c4c2ba 100644
--- a/webui.py
+++ b/webui.py
@@ -1,5 +1,6 @@
 import os
 import threading
+import time
 
 from modules import devices
 from modules.paths import script_path
-- 
cgit v1.2.3


From afaa03c5fd05f48ed9c9f15558ea6f0bc4f61628 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sat, 1 Oct 2022 22:43:45 +0100
Subject: add redefinition guard to gradio_routes_templates_response

---
 modules/ui.py | 15 ++++++++-------
 1 file changed, 8 insertions(+), 7 deletions(-)

diff --git a/modules/ui.py b/modules/ui.py
index ec6aaa28..fd057916 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1219,12 +1219,13 @@ for filename in sorted(os.listdir(jsdir)):
         javascript += f"\n<script>{jsfile.read()}</script>"
 
 
-def template_response(*args, **kwargs):
-    res = gradio_routes_templates_response(*args, **kwargs)
-    res.body = res.body.replace(b'</head>', f'{javascript}</head>'.encode("utf8"))
-    res.init_headers()
-    return res
+if 'gradio_routes_templates_response' not in globals():
+  def template_response(*args, **kwargs):
+      res = gradio_routes_templates_response(*args, **kwargs)
+      res.body = res.body.replace(b'</head>', f'{javascript}</head>'.encode("utf8"))
+      res.init_headers()
+      return res
 
+  gradio_routes_templates_response = gradio.routes.templates.TemplateResponse
+  gradio.routes.templates.TemplateResponse = template_response
 
-gradio_routes_templates_response = gradio.routes.templates.TemplateResponse
-gradio.routes.templates.TemplateResponse = template_response
-- 
cgit v1.2.3


From 30f2e3565840544dd66470c6ef216ec664db6432 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sat, 1 Oct 2022 22:50:03 +0100
Subject: add importlib.reload

---
 webui.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/webui.py b/webui.py
index e2c4c2ba..ab200045 100644
--- a/webui.py
+++ b/webui.py
@@ -1,7 +1,7 @@
 import os
 import threading
 import time
-
+import importlib
 from modules import devices
 from modules.paths import script_path
 import signal
@@ -116,8 +116,10 @@ def webui():
           time.sleep(0.5)
           break
 
-      print('Reloading Scripts')
+      print('Reloading Custom Scripts')
       modules.scripts.reload_scripts(os.path.join(script_path, "scripts"))
+      print('Reloading modules: modules.ui')
+      importlib.reload(modules.ui)
       print('Restarting Gradio')
 
 
-- 
cgit v1.2.3


From 6048002dade91b82b1ce9fea3c6ff5b5c1f8c990 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sat, 1 Oct 2022 23:10:07 +0100
Subject: Add scope warning to refresh button

---
 modules/ui.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/ui.py b/modules/ui.py
index fd057916..72846a12 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1005,7 +1005,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
         def request_restart():
           settings_interface.gradio_ref.do_restart = True
 
-        restart_gradio = gr.Button(value='Restart Gradio and Refresh Scripts')
+        restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary')
         restart_gradio.click(
             fn=request_restart,
             inputs=[],
-- 
cgit v1.2.3


From 027c5aae5546ff3650347cb3c2b87df4415ab900 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sat, 1 Oct 2022 23:29:26 +0100
Subject: update reloading message style

---
 modules/ui.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/ui.py b/modules/ui.py
index 72846a12..7b2359c2 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1010,7 +1010,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
             fn=request_restart,
             inputs=[],
             outputs=[],
-            _js='function(){document.body.innerHTML=\'<h1 style="color:white;text-align: center;">Reloading</h1>\';setTimeout(function(){location.reload()},2000)}'
+            _js='function(){document.body.innerHTML=\'<h1 style="font-family:monospace;margin-top:20%;color:lightgray;text-align:center;">Reloading...</h1>\';setTimeout(function(){location.reload()},2000)}'
         )
         
         if column is not None:
-- 
cgit v1.2.3


From 55b046312c51bb7b2329d3b5b7f1c05956f821bf Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sun, 2 Oct 2022 00:12:49 +0100
Subject: move JavaScript into ui.js

---
 javascript/ui.js | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/javascript/ui.js b/javascript/ui.js
index bfe02410..e8f289b4 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -212,3 +212,8 @@ function update_token_counter(button_id) {
 		clearTimeout(token_timeout);
 	token_timeout = setTimeout(() => gradioApp().getElementById(button_id)?.click(), wait_time);
 }
+
+function restart_reload(){
+    document.body.innerHTML='<h1 style="font-family:monospace;margin-top:20%;color:lightgray;text-align:center;">Reloading...</h1>';
+    setTimeout(function(){location.reload()},2000)
+}
-- 
cgit v1.2.3


From 0aa354bd5e811e2b41b17a3052cf5d4c8190d533 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sun, 2 Oct 2022 00:13:47 +0100
Subject: remove styling from python side

---
 modules/ui.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/ui.py b/modules/ui.py
index 7b2359c2..cb859ac4 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1010,7 +1010,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
             fn=request_restart,
             inputs=[],
             outputs=[],
-            _js='function(){document.body.innerHTML=\'<h1 style="font-family:monospace;margin-top:20%;color:lightgray;text-align:center;">Reloading...</h1>\';setTimeout(function(){location.reload()},2000)}'
+            _js='function(){restart_reload()}'
         )
         
         if column is not None:
-- 
cgit v1.2.3


From cf33268d686986a24f2e04eb615f01ed53bfe308 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sun, 2 Oct 2022 01:18:42 +0100
Subject: add script body only refresh

---
 modules/scripts.py | 23 +++++++++++++++++++++++
 1 file changed, 23 insertions(+)

diff --git a/modules/scripts.py b/modules/scripts.py
index 3c14b9e3..788397f5 100644
--- a/modules/scripts.py
+++ b/modules/scripts.py
@@ -162,10 +162,33 @@ class ScriptRunner:
 
         return processed
 
+    def reload_sources(self):
+      for si,script in list(enumerate(self.scripts)):
+        with open(script.filename, "r", encoding="utf8") as file:
+            args_from = script.args_from
+            args_to   = script.args_to 
+            filename  = script.filename
+            text = file.read()
+
+            from types import ModuleType
+            compiled = compile(text, filename, 'exec')
+            module = ModuleType(script.filename)
+            exec(compiled, module.__dict__)
+
+            for key, script_class in module.__dict__.items():
+                if type(script_class) == type and issubclass(script_class, Script):
+                    self.scripts[si] = script_class()
+                    self.scripts[si].filename = filename
+                    self.scripts[si].args_from = args_from
+                    self.scripts[si].args_to = args_to
 
 scripts_txt2img = ScriptRunner()
 scripts_img2img = ScriptRunner()
 
+def reload_script_body_only():
+  scripts_txt2img.reload_sources()
+  scripts_img2img.reload_sources()
+
 def reload_scripts(basedir):
   global scripts_txt2img,scripts_img2img
 
-- 
cgit v1.2.3


From 07e40ad7f23472fc1c781fe1cc6c1ee403413918 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sun, 2 Oct 2022 01:19:55 +0100
Subject: add custom script body only refresh option

---
 modules/ui.py | 11 +++++++++++
 1 file changed, 11 insertions(+)

diff --git a/modules/ui.py b/modules/ui.py
index cb859ac4..eb7c0585 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1012,6 +1012,17 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
             outputs=[],
             _js='function(){restart_reload()}'
         )
+
+        def reload_scripts():
+          modules.scripts.reload_script_body_only()
+
+        reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='primary')
+        reload_script_bodies.click(
+            fn=reload_scripts,
+            inputs=[],
+            outputs=[],
+            _js='function(){}'
+        )
         
         if column is not None:
             column.__exit__()
-- 
cgit v1.2.3


From 2deea867814272f1f089b60e9ba8d587c16b2fb1 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sun, 2 Oct 2022 01:36:30 +0100
Subject: Put reload buttons in row and add secondary style

---
 modules/ui.py | 23 +++++++++++++----------
 1 file changed, 13 insertions(+), 10 deletions(-)

diff --git a/modules/ui.py b/modules/ui.py
index eb7c0585..963a2c61 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1002,27 +1002,30 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
             _js='function(){}'
         )
 
-        def request_restart():
-          settings_interface.gradio_ref.do_restart = True
+        with gr.Row():
+          reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary')
+          restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary')
 
-        restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary')
-        restart_gradio.click(
-            fn=request_restart,
-            inputs=[],
-            outputs=[],
-            _js='function(){restart_reload()}'
-        )
 
         def reload_scripts():
           modules.scripts.reload_script_body_only()
 
-        reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='primary')
         reload_script_bodies.click(
             fn=reload_scripts,
             inputs=[],
             outputs=[],
             _js='function(){}'
         )
+
+        def request_restart():
+          settings_interface.gradio_ref.do_restart = True
+
+        restart_gradio.click(
+            fn=request_restart,
+            inputs=[],
+            outputs=[],
+            _js='function(){restart_reload()}'
+        )
         
         if column is not None:
             column.__exit__()
-- 
cgit v1.2.3


From 3cf1a96006daffedb8ecd0ae142eca4c4da06105 Mon Sep 17 00:00:00 2001
From: RnDMonkey <ryandrutledge@gmail.com>
Date: Sat, 1 Oct 2022 21:11:03 -0700
Subject: added safety for blank directory naming patterns

---
 modules/images.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/modules/images.py b/modules/images.py
index f1aed5d6..e7894b4c 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -311,7 +311,7 @@ def apply_filename_pattern(x, p, seed, prompt):
         x = x.replace("[cfg]", str(p.cfg_scale))
         x = x.replace("[width]", str(p.width))
         x = x.replace("[height]", str(p.height))
-        x = x.replace("[styles]", sanitize_filename_part(", ".join([x for x in p.styles if not x == "None"]), replace_spaces=False))
+        x = x.replace("[styles]", sanitize_filename_part(", ".join([x for x in p.styles if not x == "None"]) or "No styles", replace_spaces=False))
         x = x.replace("[sampler]", sanitize_filename_part(sd_samplers.samplers[p.sampler_index].name, replace_spaces=False))
 
     x = x.replace("[model_hash]", shared.sd_model.sd_model_hash)
@@ -374,7 +374,7 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i
     save_to_dirs = (grid and opts.grid_save_to_dirs) or (not grid and opts.save_to_dirs and not no_prompt)
 
     if save_to_dirs:
-        dirname = apply_filename_pattern(opts.directories_filename_pattern or "[prompt_words]", p, seed, prompt)
+        dirname = apply_filename_pattern(opts.directories_filename_pattern or "[prompt_words]", p, seed, prompt).strip('\\ ')
         path = os.path.join(path, dirname)
 
     os.makedirs(path, exist_ok=True)
-- 
cgit v1.2.3


From 70f526704721a303ae045f6406439dcceee4302e Mon Sep 17 00:00:00 2001
From: RnDMonkey <ryandrutledge@gmail.com>
Date: Sat, 1 Oct 2022 21:18:15 -0700
Subject: use os.path.normpath for better safety checking

---
 modules/images.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/modules/images.py b/modules/images.py
index e7894b4c..5ef7eb92 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -374,8 +374,8 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i
     save_to_dirs = (grid and opts.grid_save_to_dirs) or (not grid and opts.save_to_dirs and not no_prompt)
 
     if save_to_dirs:
-        dirname = apply_filename_pattern(opts.directories_filename_pattern or "[prompt_words]", p, seed, prompt).strip('\\ ')
-        path = os.path.join(path, dirname)
+        dirname = apply_filename_pattern(opts.directories_filename_pattern or "[prompt_words]", p, seed, prompt)
+        path = os.path.normpath(os.path.join(path, dirname))
 
     os.makedirs(path, exist_ok=True)
 
-- 
cgit v1.2.3


From 32edf1732f27a1fad5133667c22b948adda1b070 Mon Sep 17 00:00:00 2001
From: RnDMonkey <ryandrutledge@gmail.com>
Date: Sat, 1 Oct 2022 21:37:14 -0700
Subject: os.path.normpath wasn't working, reverting to manual strip

---
 modules/images.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/modules/images.py b/modules/images.py
index 5ef7eb92..4998e92c 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -374,8 +374,8 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i
     save_to_dirs = (grid and opts.grid_save_to_dirs) or (not grid and opts.save_to_dirs and not no_prompt)
 
     if save_to_dirs:
-        dirname = apply_filename_pattern(opts.directories_filename_pattern or "[prompt_words]", p, seed, prompt)
-        path = os.path.normpath(os.path.join(path, dirname))
+        dirname = apply_filename_pattern(opts.directories_filename_pattern or "[prompt_words]", p, seed, prompt).strip('\\ /')
+        path = os.path.join(path, dirname)
 
     os.makedirs(path, exist_ok=True)
 
-- 
cgit v1.2.3


From 820f1dc96b1979d7e92170c161db281ee8bd988b Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 2 Oct 2022 15:03:39 +0300
Subject: initial support for training textual inversion

---
 .gitignore                                        |   1 +
 javascript/progressbar.js                         |   1 +
 javascript/textualInversion.js                    |   8 +
 modules/devices.py                                |   3 +-
 modules/processing.py                             |  13 +-
 modules/sd_hijack.py                              | 324 ++++------------------
 modules/sd_hijack_optimizations.py                | 164 +++++++++++
 modules/sd_models.py                              |   4 +-
 modules/shared.py                                 |   3 +-
 modules/textual_inversion/dataset.py              |  76 +++++
 modules/textual_inversion/textual_inversion.py    | 258 +++++++++++++++++
 modules/textual_inversion/ui.py                   |  32 +++
 modules/ui.py                                     | 139 ++++++++--
 style.css                                         |  10 +-
 textual_inversion_templates/style.txt             |  19 ++
 textual_inversion_templates/style_filewords.txt   |  19 ++
 textual_inversion_templates/subject.txt           |  27 ++
 textual_inversion_templates/subject_filewords.txt |  27 ++
 webui.py                                          |  15 +-
 19 files changed, 828 insertions(+), 315 deletions(-)
 create mode 100644 javascript/textualInversion.js
 create mode 100644 modules/sd_hijack_optimizations.py
 create mode 100644 modules/textual_inversion/dataset.py
 create mode 100644 modules/textual_inversion/textual_inversion.py
 create mode 100644 modules/textual_inversion/ui.py
 create mode 100644 textual_inversion_templates/style.txt
 create mode 100644 textual_inversion_templates/style_filewords.txt
 create mode 100644 textual_inversion_templates/subject.txt
 create mode 100644 textual_inversion_templates/subject_filewords.txt

diff --git a/.gitignore b/.gitignore
index 3532dab3..7afc9395 100644
--- a/.gitignore
+++ b/.gitignore
@@ -25,3 +25,4 @@ __pycache__
 /.idea
 notification.mp3
 /SwinIR
+/textual_inversion
diff --git a/javascript/progressbar.js b/javascript/progressbar.js
index 21f25b38..1e297abb 100644
--- a/javascript/progressbar.js
+++ b/javascript/progressbar.js
@@ -30,6 +30,7 @@ function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_inte
 onUiUpdate(function(){
     check_progressbar('txt2img', 'txt2img_progressbar', 'txt2img_progress_span', 'txt2img_interrupt', 'txt2img_preview', 'txt2img_gallery')
     check_progressbar('img2img', 'img2img_progressbar', 'img2img_progress_span', 'img2img_interrupt', 'img2img_preview', 'img2img_gallery')
+    check_progressbar('ti', 'ti_progressbar', 'ti_progress_span', 'ti_interrupt', 'ti_preview', 'ti_gallery')
 })
 
 function requestMoreProgress(id_part, id_progressbar_span, id_interrupt){
diff --git a/javascript/textualInversion.js b/javascript/textualInversion.js
new file mode 100644
index 00000000..8061be08
--- /dev/null
+++ b/javascript/textualInversion.js
@@ -0,0 +1,8 @@
+
+
+function start_training_textual_inversion(){
+    requestProgress('ti')
+    gradioApp().querySelector('#ti_error').innerHTML=''
+
+    return args_to_array(arguments)
+}
diff --git a/modules/devices.py b/modules/devices.py
index 07bb2339..ff82f2f6 100644
--- a/modules/devices.py
+++ b/modules/devices.py
@@ -32,10 +32,9 @@ def enable_tf32():
 
 errors.run(enable_tf32, "Enabling TF32")
 
-
 device = get_optimal_device()
 device_codeformer = cpu if has_mps else device
-
+dtype = torch.float16
 
 def randn(seed, shape):
     # Pytorch currently doesn't handle setting randomness correctly when the metal backend is used.
diff --git a/modules/processing.py b/modules/processing.py
index 7eeb5191..8223423a 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -56,7 +56,7 @@ class StableDiffusionProcessing:
         self.prompt: str = prompt
         self.prompt_for_display: str = None
         self.negative_prompt: str = (negative_prompt or "")
-        self.styles: str = styles
+        self.styles: list = styles or []
         self.seed: int = seed
         self.subseed: int = subseed
         self.subseed_strength: float = subseed_strength
@@ -271,7 +271,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration
         "Variation seed strength": (None if p.subseed_strength == 0 else p.subseed_strength),
         "Seed resize from": (None if p.seed_resize_from_w == 0 or p.seed_resize_from_h == 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"),
         "Denoising strength": getattr(p, 'denoising_strength', None),
-        "Eta": (None if p.sampler.eta == p.sampler.default_eta else p.sampler.eta),
+        "Eta": (None if p.sampler is None or p.sampler.eta == p.sampler.default_eta else p.sampler.eta),
     }
 
     generation_params.update(p.extra_generation_params)
@@ -295,8 +295,11 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
 
     fix_seed(p)
 
-    os.makedirs(p.outpath_samples, exist_ok=True)
-    os.makedirs(p.outpath_grids, exist_ok=True)
+    if p.outpath_samples is not None:
+        os.makedirs(p.outpath_samples, exist_ok=True)
+
+    if p.outpath_grids is not None:
+        os.makedirs(p.outpath_grids, exist_ok=True)
 
     modules.sd_hijack.model_hijack.apply_circular(p.tiling)
 
@@ -323,7 +326,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
         return create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration, position_in_batch)
 
     if os.path.exists(cmd_opts.embeddings_dir):
-        model_hijack.load_textual_inversion_embeddings(cmd_opts.embeddings_dir, p.sd_model)
+        model_hijack.embedding_db.load_textual_inversion_embeddings()
 
     infotexts = []
     output_images = []
diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index fa7eaeb8..fd57e5c5 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -6,244 +6,41 @@ import torch
 import numpy as np
 from torch import einsum
 
-from modules import prompt_parser
+import modules.textual_inversion.textual_inversion
+from modules import prompt_parser, devices, sd_hijack_optimizations, shared
 from modules.shared import opts, device, cmd_opts
 
-from ldm.util import default
-from einops import rearrange
 import ldm.modules.attention
 import ldm.modules.diffusionmodules.model
 
+attention_CrossAttention_forward = ldm.modules.attention.CrossAttention.forward
+diffusionmodules_model_nonlinearity = ldm.modules.diffusionmodules.model.nonlinearity
+diffusionmodules_model_AttnBlock_forward = ldm.modules.diffusionmodules.model.AttnBlock.forward
 
-# see https://github.com/basujindal/stable-diffusion/pull/117 for discussion
-def split_cross_attention_forward_v1(self, x, context=None, mask=None):
-    h = self.heads
 
-    q = self.to_q(x)
-    context = default(context, x)
-    k = self.to_k(context)
-    v = self.to_v(context)
-    del context, x
+def apply_optimizations():
+    if cmd_opts.opt_split_attention_v1:
+        ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1
+    elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention or torch.cuda.is_available()):
+        ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward
+        ldm.modules.diffusionmodules.model.nonlinearity = sd_hijack_optimizations.nonlinearity_hijack
+        ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.cross_attention_attnblock_forward
 
-    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
 
-    r1 = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device)
-    for i in range(0, q.shape[0], 2):
-        end = i + 2
-        s1 = einsum('b i d, b j d -> b i j', q[i:end], k[i:end])
-        s1 *= self.scale
+def undo_optimizations():
+    ldm.modules.attention.CrossAttention.forward = attention_CrossAttention_forward
+    ldm.modules.diffusionmodules.model.nonlinearity = diffusionmodules_model_nonlinearity
+    ldm.modules.diffusionmodules.model.AttnBlock.forward = diffusionmodules_model_AttnBlock_forward
 
-        s2 = s1.softmax(dim=-1)
-        del s1
-
-        r1[i:end] = einsum('b i j, b j d -> b i d', s2, v[i:end])
-        del s2
-
-    r2 = rearrange(r1, '(b h) n d -> b n (h d)', h=h)
-    del r1
-
-    return self.to_out(r2)
-
-
-# taken from https://github.com/Doggettx/stable-diffusion
-def split_cross_attention_forward(self, x, context=None, mask=None):
-    h = self.heads
-
-    q_in = self.to_q(x)
-    context = default(context, x)
-    k_in = self.to_k(context) * self.scale
-    v_in = self.to_v(context)
-    del context, x
-
-    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q_in, k_in, v_in))
-    del q_in, k_in, v_in
-
-    r1 = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device, dtype=q.dtype)
-
-    stats = torch.cuda.memory_stats(q.device)
-    mem_active = stats['active_bytes.all.current']
-    mem_reserved = stats['reserved_bytes.all.current']
-    mem_free_cuda, _ = torch.cuda.mem_get_info(torch.cuda.current_device())
-    mem_free_torch = mem_reserved - mem_active
-    mem_free_total = mem_free_cuda + mem_free_torch
-
-    gb = 1024 ** 3
-    tensor_size = q.shape[0] * q.shape[1] * k.shape[1] * q.element_size()
-    modifier = 3 if q.element_size() == 2 else 2.5
-    mem_required = tensor_size * modifier
-    steps = 1
-
-    if mem_required > mem_free_total:
-        steps = 2 ** (math.ceil(math.log(mem_required / mem_free_total, 2)))
-        # print(f"Expected tensor size:{tensor_size/gb:0.1f}GB, cuda free:{mem_free_cuda/gb:0.1f}GB "
-        #       f"torch free:{mem_free_torch/gb:0.1f} total:{mem_free_total/gb:0.1f} steps:{steps}")
-
-    if steps > 64:
-        max_res = math.floor(math.sqrt(math.sqrt(mem_free_total / 2.5)) / 8) * 64
-        raise RuntimeError(f'Not enough memory, use lower resolution (max approx. {max_res}x{max_res}). '
-                           f'Need: {mem_required / 64 / gb:0.1f}GB free, Have:{mem_free_total / gb:0.1f}GB free')
-
-    slice_size = q.shape[1] // steps if (q.shape[1] % steps) == 0 else q.shape[1]
-    for i in range(0, q.shape[1], slice_size):
-        end = i + slice_size
-        s1 = einsum('b i d, b j d -> b i j', q[:, i:end], k)
-
-        s2 = s1.softmax(dim=-1, dtype=q.dtype)
-        del s1
-
-        r1[:, i:end] = einsum('b i j, b j d -> b i d', s2, v)
-        del s2
-
-    del q, k, v
-
-    r2 = rearrange(r1, '(b h) n d -> b n (h d)', h=h)
-    del r1
-
-    return self.to_out(r2)
-
-def nonlinearity_hijack(x):
-    # swish
-    t = torch.sigmoid(x)
-    x *= t
-    del t
-
-    return x
-
-def cross_attention_attnblock_forward(self, x):
-        h_ = x
-        h_ = self.norm(h_)
-        q1 = self.q(h_)
-        k1 = self.k(h_)
-        v = self.v(h_)
-
-        # compute attention
-        b, c, h, w = q1.shape
-
-        q2 = q1.reshape(b, c, h*w)
-        del q1
-
-        q = q2.permute(0, 2, 1)   # b,hw,c
-        del q2
-
-        k = k1.reshape(b, c, h*w) # b,c,hw
-        del k1
-
-        h_ = torch.zeros_like(k, device=q.device)
-
-        stats = torch.cuda.memory_stats(q.device)
-        mem_active = stats['active_bytes.all.current']
-        mem_reserved = stats['reserved_bytes.all.current']
-        mem_free_cuda, _ = torch.cuda.mem_get_info(torch.cuda.current_device())
-        mem_free_torch = mem_reserved - mem_active
-        mem_free_total = mem_free_cuda + mem_free_torch
-
-        tensor_size = q.shape[0] * q.shape[1] * k.shape[2] * q.element_size()
-        mem_required = tensor_size * 2.5
-        steps = 1
-
-        if mem_required > mem_free_total:
-            steps = 2**(math.ceil(math.log(mem_required / mem_free_total, 2)))
-
-        slice_size = q.shape[1] // steps if (q.shape[1] % steps) == 0 else q.shape[1]
-        for i in range(0, q.shape[1], slice_size):
-            end = i + slice_size
-
-            w1 = torch.bmm(q[:, i:end], k)     # b,hw,hw    w[b,i,j]=sum_c q[b,i,c]k[b,c,j]
-            w2 = w1 * (int(c)**(-0.5))
-            del w1
-            w3 = torch.nn.functional.softmax(w2, dim=2, dtype=q.dtype)
-            del w2
-
-            # attend to values
-            v1 = v.reshape(b, c, h*w)
-            w4 = w3.permute(0, 2, 1)   # b,hw,hw (first hw of k, second of q)
-            del w3
-
-            h_[:, :, i:end] = torch.bmm(v1, w4)     # b, c,hw (hw of q) h_[b,c,j] = sum_i v[b,c,i] w_[b,i,j]
-            del v1, w4
-
-        h2 = h_.reshape(b, c, h, w)
-        del h_
-
-        h3 = self.proj_out(h2)
-        del h2
-
-        h3 += x
-
-        return h3
 
 class StableDiffusionModelHijack:
-    ids_lookup = {}
-    word_embeddings = {}
-    word_embeddings_checksums = {}
     fixes = None
     comments = []
-    dir_mtime = None
     layers = None
     circular_enabled = False
     clip = None
 
-    def load_textual_inversion_embeddings(self, dirname, model):
-        mt = os.path.getmtime(dirname)
-        if self.dir_mtime is not None and mt <= self.dir_mtime:
-            return
-
-        self.dir_mtime = mt
-        self.ids_lookup.clear()
-        self.word_embeddings.clear()
-
-        tokenizer = model.cond_stage_model.tokenizer
-
-        def const_hash(a):
-            r = 0
-            for v in a:
-                r = (r * 281 ^ int(v) * 997) & 0xFFFFFFFF
-            return r
-
-        def process_file(path, filename):
-            name = os.path.splitext(filename)[0]
-
-            data = torch.load(path, map_location="cpu")
-
-            # textual inversion embeddings
-            if 'string_to_param' in data:
-                param_dict = data['string_to_param']
-                if hasattr(param_dict, '_parameters'):
-                    param_dict = getattr(param_dict, '_parameters')  # fix for torch 1.12.1 loading saved file from torch 1.11
-                assert len(param_dict) == 1, 'embedding file has multiple terms in it'
-                emb = next(iter(param_dict.items()))[1]
-            # diffuser concepts
-            elif type(data) == dict and type(next(iter(data.values()))) == torch.Tensor:
-                assert len(data.keys()) == 1, 'embedding file has multiple terms in it'
-
-                emb = next(iter(data.values()))
-                if len(emb.shape) == 1:
-                    emb = emb.unsqueeze(0)
-
-            self.word_embeddings[name] = emb.detach().to(device)
-            self.word_embeddings_checksums[name] = f'{const_hash(emb.reshape(-1)*100)&0xffff:04x}'
-
-            ids = tokenizer([name], add_special_tokens=False)['input_ids'][0]
-
-            first_id = ids[0]
-            if first_id not in self.ids_lookup:
-                self.ids_lookup[first_id] = []
-            self.ids_lookup[first_id].append((ids, name))
-
-        for fn in os.listdir(dirname):
-            try:
-                fullfn = os.path.join(dirname, fn)
-
-                if os.stat(fullfn).st_size == 0:
-                    continue
-
-                process_file(fullfn, fn)
-            except Exception:
-                print(f"Error loading emedding {fn}:", file=sys.stderr)
-                print(traceback.format_exc(), file=sys.stderr)
-                continue
-
-        print(f"Loaded a total of {len(self.word_embeddings)} textual inversion embeddings.")
+    embedding_db = modules.textual_inversion.textual_inversion.EmbeddingDatabase(cmd_opts.embeddings_dir)
 
     def hijack(self, m):
         model_embeddings = m.cond_stage_model.transformer.text_model.embeddings
@@ -253,12 +50,7 @@ class StableDiffusionModelHijack:
 
         self.clip = m.cond_stage_model
 
-        if cmd_opts.opt_split_attention_v1:
-            ldm.modules.attention.CrossAttention.forward = split_cross_attention_forward_v1
-        elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention or torch.cuda.is_available()):
-            ldm.modules.attention.CrossAttention.forward = split_cross_attention_forward
-            ldm.modules.diffusionmodules.model.nonlinearity = nonlinearity_hijack
-            ldm.modules.diffusionmodules.model.AttnBlock.forward = cross_attention_attnblock_forward
+        apply_optimizations()
 
         def flatten(el):
             flattened = [flatten(children) for children in el.children()]
@@ -296,7 +88,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
     def __init__(self, wrapped, hijack):
         super().__init__()
         self.wrapped = wrapped
-        self.hijack = hijack
+        self.hijack: StableDiffusionModelHijack = hijack
         self.tokenizer = wrapped.tokenizer
         self.max_length = wrapped.max_length
         self.token_mults = {}
@@ -317,7 +109,6 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
             if mult != 1.0:
                 self.token_mults[ident] = mult
 
-
     def tokenize_line(self, line, used_custom_terms, hijack_comments):
         id_start = self.wrapped.tokenizer.bos_token_id
         id_end = self.wrapped.tokenizer.eos_token_id
@@ -339,28 +130,19 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
             while i < len(tokens):
                 token = tokens[i]
 
-                possible_matches = self.hijack.ids_lookup.get(token, None)
+                embedding = self.hijack.embedding_db.find_embedding_at_position(tokens, i)
 
-                if possible_matches is None:
+                if embedding is None:
                     remade_tokens.append(token)
                     multipliers.append(weight)
+                    i += 1
                 else:
-                    found = False
-                    for ids, word in possible_matches:
-                        if tokens[i:i + len(ids)] == ids:
-                            emb_len = int(self.hijack.word_embeddings[word].shape[0])
-                            fixes.append((len(remade_tokens), word))
-                            remade_tokens += [0] * emb_len
-                            multipliers += [weight] * emb_len
-                            i += len(ids) - 1
-                            found = True
-                            used_custom_terms.append((word, self.hijack.word_embeddings_checksums[word]))
-                            break
-
-                    if not found:
-                        remade_tokens.append(token)
-                        multipliers.append(weight)
-                i += 1
+                    emb_len = int(embedding.vec.shape[0])
+                    fixes.append((len(remade_tokens), embedding))
+                    remade_tokens += [0] * emb_len
+                    multipliers += [weight] * emb_len
+                    used_custom_terms.append((embedding.name, embedding.checksum()))
+                    i += emb_len
 
         if len(remade_tokens) > maxlen - 2:
             vocab = {v: k for k, v in self.wrapped.tokenizer.get_vocab().items()}
@@ -431,32 +213,23 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
                 while i < len(tokens):
                     token = tokens[i]
 
-                    possible_matches = self.hijack.ids_lookup.get(token, None)
+                    embedding = self.hijack.embedding_db.find_embedding_at_position(tokens, i)
 
                     mult_change = self.token_mults.get(token) if opts.enable_emphasis else None
                     if mult_change is not None:
                         mult *= mult_change
-                    elif possible_matches is None:
+                        i += 1
+                    elif embedding is None:
                         remade_tokens.append(token)
                         multipliers.append(mult)
+                        i += 1
                     else:
-                        found = False
-                        for ids, word in possible_matches:
-                            if tokens[i:i+len(ids)] == ids:
-                                emb_len = int(self.hijack.word_embeddings[word].shape[0])
-                                fixes.append((len(remade_tokens), word))
-                                remade_tokens += [0] * emb_len
-                                multipliers += [mult] * emb_len
-                                i += len(ids) - 1
-                                found = True
-                                used_custom_terms.append((word, self.hijack.word_embeddings_checksums[word]))
-                                break
-
-                        if not found:
-                            remade_tokens.append(token)
-                            multipliers.append(mult)
-
-                    i += 1
+                        emb_len = int(embedding.vec.shape[0])
+                        fixes.append((len(remade_tokens), embedding))
+                        remade_tokens += [0] * emb_len
+                        multipliers += [mult] * emb_len
+                        used_custom_terms.append((embedding.name, embedding.checksum()))
+                        i += emb_len
 
                 if len(remade_tokens) > maxlen - 2:
                     vocab = {v: k for k, v in self.wrapped.tokenizer.get_vocab().items()}
@@ -464,6 +237,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
                     overflowing_words = [vocab.get(int(x), "") for x in ovf]
                     overflowing_text = self.wrapped.tokenizer.convert_tokens_to_string(''.join(overflowing_words))
                     hijack_comments.append(f"Warning: too many input tokens; some ({len(overflowing_words)}) have been truncated:\n{overflowing_text}\n")
+
                 token_count = len(remade_tokens)
                 remade_tokens = remade_tokens + [id_end] * (maxlen - 2 - len(remade_tokens))
                 remade_tokens = [id_start] + remade_tokens[0:maxlen-2] + [id_end]
@@ -484,7 +258,6 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
         else:
             batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = self.process_text(text)
 
-
         self.hijack.fixes = hijack_fixes
         self.hijack.comments = hijack_comments
 
@@ -517,14 +290,19 @@ class EmbeddingsWithFixes(torch.nn.Module):
 
         inputs_embeds = self.wrapped(input_ids)
 
-        if batch_fixes is not None:
-            for fixes, tensor in zip(batch_fixes, inputs_embeds):
-                for offset, word in fixes:
-                    emb = self.embeddings.word_embeddings[word]
-                    emb_len = min(tensor.shape[0]-offset-1, emb.shape[0])
-                    tensor[offset+1:offset+1+emb_len] = self.embeddings.word_embeddings[word][0:emb_len]
+        if batch_fixes is None or len(batch_fixes) == 0 or max([len(x) for x in batch_fixes]) == 0:
+            return inputs_embeds
+
+        vecs = []
+        for fixes, tensor in zip(batch_fixes, inputs_embeds):
+            for offset, embedding in fixes:
+                emb = embedding.vec
+                emb_len = min(tensor.shape[0]-offset-1, emb.shape[0])
+                tensor = torch.cat([tensor[0:offset+1], emb[0:emb_len], tensor[offset+1+emb_len:]])
+
+            vecs.append(tensor)
 
-        return inputs_embeds
+        return torch.stack(vecs)
 
 
 def add_circular_option_to_conv_2d():
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
new file mode 100644
index 00000000..9c079e57
--- /dev/null
+++ b/modules/sd_hijack_optimizations.py
@@ -0,0 +1,164 @@
+import math
+import torch
+from torch import einsum
+
+from ldm.util import default
+from einops import rearrange
+
+
+# see https://github.com/basujindal/stable-diffusion/pull/117 for discussion
+def split_cross_attention_forward_v1(self, x, context=None, mask=None):
+    h = self.heads
+
+    q = self.to_q(x)
+    context = default(context, x)
+    k = self.to_k(context)
+    v = self.to_v(context)
+    del context, x
+
+    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
+
+    r1 = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device)
+    for i in range(0, q.shape[0], 2):
+        end = i + 2
+        s1 = einsum('b i d, b j d -> b i j', q[i:end], k[i:end])
+        s1 *= self.scale
+
+        s2 = s1.softmax(dim=-1)
+        del s1
+
+        r1[i:end] = einsum('b i j, b j d -> b i d', s2, v[i:end])
+        del s2
+
+    r2 = rearrange(r1, '(b h) n d -> b n (h d)', h=h)
+    del r1
+
+    return self.to_out(r2)
+
+
+# taken from https://github.com/Doggettx/stable-diffusion
+def split_cross_attention_forward(self, x, context=None, mask=None):
+    h = self.heads
+
+    q_in = self.to_q(x)
+    context = default(context, x)
+    k_in = self.to_k(context) * self.scale
+    v_in = self.to_v(context)
+    del context, x
+
+    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q_in, k_in, v_in))
+    del q_in, k_in, v_in
+
+    r1 = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device, dtype=q.dtype)
+
+    stats = torch.cuda.memory_stats(q.device)
+    mem_active = stats['active_bytes.all.current']
+    mem_reserved = stats['reserved_bytes.all.current']
+    mem_free_cuda, _ = torch.cuda.mem_get_info(torch.cuda.current_device())
+    mem_free_torch = mem_reserved - mem_active
+    mem_free_total = mem_free_cuda + mem_free_torch
+
+    gb = 1024 ** 3
+    tensor_size = q.shape[0] * q.shape[1] * k.shape[1] * q.element_size()
+    modifier = 3 if q.element_size() == 2 else 2.5
+    mem_required = tensor_size * modifier
+    steps = 1
+
+    if mem_required > mem_free_total:
+        steps = 2 ** (math.ceil(math.log(mem_required / mem_free_total, 2)))
+        # print(f"Expected tensor size:{tensor_size/gb:0.1f}GB, cuda free:{mem_free_cuda/gb:0.1f}GB "
+        #       f"torch free:{mem_free_torch/gb:0.1f} total:{mem_free_total/gb:0.1f} steps:{steps}")
+
+    if steps > 64:
+        max_res = math.floor(math.sqrt(math.sqrt(mem_free_total / 2.5)) / 8) * 64
+        raise RuntimeError(f'Not enough memory, use lower resolution (max approx. {max_res}x{max_res}). '
+                           f'Need: {mem_required / 64 / gb:0.1f}GB free, Have:{mem_free_total / gb:0.1f}GB free')
+
+    slice_size = q.shape[1] // steps if (q.shape[1] % steps) == 0 else q.shape[1]
+    for i in range(0, q.shape[1], slice_size):
+        end = i + slice_size
+        s1 = einsum('b i d, b j d -> b i j', q[:, i:end], k)
+
+        s2 = s1.softmax(dim=-1, dtype=q.dtype)
+        del s1
+
+        r1[:, i:end] = einsum('b i j, b j d -> b i d', s2, v)
+        del s2
+
+    del q, k, v
+
+    r2 = rearrange(r1, '(b h) n d -> b n (h d)', h=h)
+    del r1
+
+    return self.to_out(r2)
+
+def nonlinearity_hijack(x):
+    # swish
+    t = torch.sigmoid(x)
+    x *= t
+    del t
+
+    return x
+
+def cross_attention_attnblock_forward(self, x):
+        h_ = x
+        h_ = self.norm(h_)
+        q1 = self.q(h_)
+        k1 = self.k(h_)
+        v = self.v(h_)
+
+        # compute attention
+        b, c, h, w = q1.shape
+
+        q2 = q1.reshape(b, c, h*w)
+        del q1
+
+        q = q2.permute(0, 2, 1)   # b,hw,c
+        del q2
+
+        k = k1.reshape(b, c, h*w) # b,c,hw
+        del k1
+
+        h_ = torch.zeros_like(k, device=q.device)
+
+        stats = torch.cuda.memory_stats(q.device)
+        mem_active = stats['active_bytes.all.current']
+        mem_reserved = stats['reserved_bytes.all.current']
+        mem_free_cuda, _ = torch.cuda.mem_get_info(torch.cuda.current_device())
+        mem_free_torch = mem_reserved - mem_active
+        mem_free_total = mem_free_cuda + mem_free_torch
+
+        tensor_size = q.shape[0] * q.shape[1] * k.shape[2] * q.element_size()
+        mem_required = tensor_size * 2.5
+        steps = 1
+
+        if mem_required > mem_free_total:
+            steps = 2**(math.ceil(math.log(mem_required / mem_free_total, 2)))
+
+        slice_size = q.shape[1] // steps if (q.shape[1] % steps) == 0 else q.shape[1]
+        for i in range(0, q.shape[1], slice_size):
+            end = i + slice_size
+
+            w1 = torch.bmm(q[:, i:end], k)     # b,hw,hw    w[b,i,j]=sum_c q[b,i,c]k[b,c,j]
+            w2 = w1 * (int(c)**(-0.5))
+            del w1
+            w3 = torch.nn.functional.softmax(w2, dim=2, dtype=q.dtype)
+            del w2
+
+            # attend to values
+            v1 = v.reshape(b, c, h*w)
+            w4 = w3.permute(0, 2, 1)   # b,hw,hw (first hw of k, second of q)
+            del w3
+
+            h_[:, :, i:end] = torch.bmm(v1, w4)     # b, c,hw (hw of q) h_[b,c,j] = sum_i v[b,c,i] w_[b,i,j]
+            del v1, w4
+
+        h2 = h_.reshape(b, c, h, w)
+        del h_
+
+        h3 = self.proj_out(h2)
+        del h2
+
+        h3 += x
+
+        return h3
diff --git a/modules/sd_models.py b/modules/sd_models.py
index 2539f14c..5b3dbdc7 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -8,7 +8,7 @@ from omegaconf import OmegaConf
 
 from ldm.util import instantiate_from_config
 
-from modules import shared, modelloader
+from modules import shared, modelloader, devices
 from modules.paths import models_path
 
 model_dir = "Stable-diffusion"
@@ -134,6 +134,8 @@ def load_model_weights(model, checkpoint_file, sd_model_hash):
     if not shared.cmd_opts.no_half:
         model.half()
 
+    devices.dtype = torch.float32 if shared.cmd_opts.no_half else torch.float16
+
     model.sd_model_hash = sd_model_hash
     model.sd_model_checkpint = checkpoint_file
 
diff --git a/modules/shared.py b/modules/shared.py
index ac968b2d..ac0bc480 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -78,6 +78,7 @@ class State:
     current_latent = None
     current_image = None
     current_image_sampling_step = 0
+    textinfo = None
 
     def interrupt(self):
         self.interrupted = True
@@ -88,7 +89,7 @@ class State:
         self.current_image_sampling_step = 0
         
     def get_job_timestamp(self):
-        return datetime.datetime.now().strftime("%Y%m%d%H%M%S")
+        return datetime.datetime.now().strftime("%Y%m%d%H%M%S")  # shouldn't this return job_timestamp?
 
 
 state = State()
diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
new file mode 100644
index 00000000..7e134a08
--- /dev/null
+++ b/modules/textual_inversion/dataset.py
@@ -0,0 +1,76 @@
+import os
+import numpy as np
+import PIL
+import torch
+from PIL import Image
+from torch.utils.data import Dataset
+from torchvision import transforms
+
+import random
+import tqdm
+
+
+class PersonalizedBase(Dataset):
+    def __init__(self, data_root, size=None, repeats=100, flip_p=0.5, placeholder_token="*", width=512, height=512, model=None, device=None, template_file=None):
+
+        self.placeholder_token = placeholder_token
+
+        self.size = size
+        self.width = width
+        self.height = height
+        self.flip = transforms.RandomHorizontalFlip(p=flip_p)
+
+        self.dataset = []
+
+        with open(template_file, "r") as file:
+            lines = [x.strip() for x in file.readlines()]
+
+        self.lines = lines
+
+        assert data_root, 'dataset directory not specified'
+
+        self.image_paths = [os.path.join(data_root, file_path) for file_path in os.listdir(data_root)]
+        print("Preparing dataset...")
+        for path in tqdm.tqdm(self.image_paths):
+            image = Image.open(path)
+            image = image.convert('RGB')
+            image = image.resize((self.width, self.height), PIL.Image.BICUBIC)
+
+            filename = os.path.basename(path)
+            filename_tokens = os.path.splitext(filename)[0].replace('_', '-').replace(' ', '-').split('-')
+            filename_tokens = [token for token in filename_tokens if token.isalpha()]
+
+            npimage = np.array(image).astype(np.uint8)
+            npimage = (npimage / 127.5 - 1.0).astype(np.float32)
+
+            torchdata = torch.from_numpy(npimage).to(device=device, dtype=torch.float32)
+            torchdata = torch.moveaxis(torchdata, 2, 0)
+
+            init_latent = model.get_first_stage_encoding(model.encode_first_stage(torchdata.unsqueeze(dim=0))).squeeze()
+
+            self.dataset.append((init_latent, filename_tokens))
+
+        self.length = len(self.dataset) * repeats
+
+        self.initial_indexes = np.arange(self.length) % len(self.dataset)
+        self.indexes = None
+        self.shuffle()
+
+    def shuffle(self):
+        self.indexes = self.initial_indexes[torch.randperm(self.initial_indexes.shape[0])]
+
+    def __len__(self):
+        return self.length
+
+    def __getitem__(self, i):
+        if i % len(self.dataset) == 0:
+            self.shuffle()
+
+        index = self.indexes[i % len(self.indexes)]
+        x, filename_tokens = self.dataset[index]
+
+        text = random.choice(self.lines)
+        text = text.replace("[name]", self.placeholder_token)
+        text = text.replace("[filewords]", ' '.join(filename_tokens))
+
+        return x, text
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
new file mode 100644
index 00000000..c0baaace
--- /dev/null
+++ b/modules/textual_inversion/textual_inversion.py
@@ -0,0 +1,258 @@
+import os
+import sys
+import traceback
+
+import torch
+import tqdm
+import html
+import datetime
+
+from modules import shared, devices, sd_hijack, processing
+import modules.textual_inversion.dataset
+
+
+class Embedding:
+    def __init__(self, vec, name, step=None):
+        self.vec = vec
+        self.name = name
+        self.step = step
+        self.cached_checksum = None
+
+    def save(self, filename):
+        embedding_data = {
+            "string_to_token": {"*": 265},
+            "string_to_param": {"*": self.vec},
+            "name": self.name,
+            "step": self.step,
+        }
+
+        torch.save(embedding_data, filename)
+
+    def checksum(self):
+        if self.cached_checksum is not None:
+            return self.cached_checksum
+
+        def const_hash(a):
+            r = 0
+            for v in a:
+                r = (r * 281 ^ int(v) * 997) & 0xFFFFFFFF
+            return r
+
+        self.cached_checksum = f'{const_hash(self.vec.reshape(-1) * 100) & 0xffff:04x}'
+        return self.cached_checksum
+
+class EmbeddingDatabase:
+    def __init__(self, embeddings_dir):
+        self.ids_lookup = {}
+        self.word_embeddings = {}
+        self.dir_mtime = None
+        self.embeddings_dir = embeddings_dir
+
+    def register_embedding(self, embedding, model):
+
+        self.word_embeddings[embedding.name] = embedding
+
+        ids = model.cond_stage_model.tokenizer([embedding.name], add_special_tokens=False)['input_ids'][0]
+
+        first_id = ids[0]
+        if first_id not in self.ids_lookup:
+            self.ids_lookup[first_id] = []
+        self.ids_lookup[first_id].append((ids, embedding))
+
+        return embedding
+
+    def load_textual_inversion_embeddings(self):
+        mt = os.path.getmtime(self.embeddings_dir)
+        if self.dir_mtime is not None and mt <= self.dir_mtime:
+            return
+
+        self.dir_mtime = mt
+        self.ids_lookup.clear()
+        self.word_embeddings.clear()
+
+        def process_file(path, filename):
+            name = os.path.splitext(filename)[0]
+
+            data = torch.load(path, map_location="cpu")
+
+            # textual inversion embeddings
+            if 'string_to_param' in data:
+                param_dict = data['string_to_param']
+                if hasattr(param_dict, '_parameters'):
+                    param_dict = getattr(param_dict, '_parameters')  # fix for torch 1.12.1 loading saved file from torch 1.11
+                assert len(param_dict) == 1, 'embedding file has multiple terms in it'
+                emb = next(iter(param_dict.items()))[1]
+            # diffuser concepts
+            elif type(data) == dict and type(next(iter(data.values()))) == torch.Tensor:
+                assert len(data.keys()) == 1, 'embedding file has multiple terms in it'
+
+                emb = next(iter(data.values()))
+                if len(emb.shape) == 1:
+                    emb = emb.unsqueeze(0)
+            else:
+                raise Exception(f"Couldn't identify {filename} as neither textual inversion embedding nor diffuser concept.")
+
+            vec = emb.detach().to(devices.device, dtype=torch.float32)
+            embedding = Embedding(vec, name)
+            embedding.step = data.get('step', None)
+            self.register_embedding(embedding, shared.sd_model)
+
+        for fn in os.listdir(self.embeddings_dir):
+            try:
+                fullfn = os.path.join(self.embeddings_dir, fn)
+
+                if os.stat(fullfn).st_size == 0:
+                    continue
+
+                process_file(fullfn, fn)
+            except Exception:
+                print(f"Error loading emedding {fn}:", file=sys.stderr)
+                print(traceback.format_exc(), file=sys.stderr)
+                continue
+
+        print(f"Loaded a total of {len(self.word_embeddings)} textual inversion embeddings.")
+
+    def find_embedding_at_position(self, tokens, offset):
+        token = tokens[offset]
+        possible_matches = self.ids_lookup.get(token, None)
+
+        if possible_matches is None:
+            return None
+
+        for ids, embedding in possible_matches:
+            if tokens[offset:offset + len(ids)] == ids:
+                return embedding
+
+        return None
+
+
+
+def create_embedding(name, num_vectors_per_token):
+    init_text = '*'
+
+    cond_model = shared.sd_model.cond_stage_model
+    embedding_layer = cond_model.wrapped.transformer.text_model.embeddings
+
+    ids = cond_model.tokenizer(init_text, max_length=num_vectors_per_token, return_tensors="pt", add_special_tokens=False)["input_ids"]
+    embedded = embedding_layer(ids.to(devices.device)).squeeze(0)
+    vec = torch.zeros((num_vectors_per_token, embedded.shape[1]), device=devices.device)
+
+    for i in range(num_vectors_per_token):
+        vec[i] = embedded[i * int(embedded.shape[0]) // num_vectors_per_token]
+
+    fn = os.path.join(shared.cmd_opts.embeddings_dir, f"{name}.pt")
+    assert not os.path.exists(fn), f"file {fn} already exists"
+
+    embedding = Embedding(vec, name)
+    embedding.step = 0
+    embedding.save(fn)
+
+    return fn
+
+
+def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps, create_image_every, save_embedding_every, template_file):
+    assert embedding_name, 'embedding not selected'
+
+    shared.state.textinfo = "Initializing textual inversion training..."
+    shared.state.job_count = steps
+
+    filename = os.path.join(shared.cmd_opts.embeddings_dir, f'{embedding_name}.pt')
+
+    log_directory = os.path.join(log_directory, datetime.datetime.now().strftime("%Y-%d-%m"), embedding_name)
+
+    if save_embedding_every > 0:
+        embedding_dir = os.path.join(log_directory, "embeddings")
+        os.makedirs(embedding_dir, exist_ok=True)
+    else:
+        embedding_dir = None
+
+    if create_image_every > 0:
+        images_dir = os.path.join(log_directory, "images")
+        os.makedirs(images_dir, exist_ok=True)
+    else:
+        images_dir = None
+
+    cond_model = shared.sd_model.cond_stage_model
+
+    shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
+    with torch.autocast("cuda"):
+        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, size=512, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file)
+
+    hijack = sd_hijack.model_hijack
+
+    embedding = hijack.embedding_db.word_embeddings[embedding_name]
+    embedding.vec.requires_grad = True
+
+    optimizer = torch.optim.AdamW([embedding.vec], lr=learn_rate)
+
+    losses = torch.zeros((32,))
+
+    last_saved_file = "<none>"
+    last_saved_image = "<none>"
+
+    ititial_step = embedding.step or 0
+    if ititial_step > steps:
+        return embedding, filename
+
+    pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step)
+    for i, (x, text) in pbar:
+        embedding.step = i + ititial_step
+
+        if embedding.step > steps:
+            break
+
+        if shared.state.interrupted:
+            break
+
+        with torch.autocast("cuda"):
+            c = cond_model([text])
+            loss = shared.sd_model(x.unsqueeze(0), c)[0]
+
+            losses[embedding.step % losses.shape[0]] = loss.item()
+
+            optimizer.zero_grad()
+            loss.backward()
+            optimizer.step()
+
+        pbar.set_description(f"loss: {losses.mean():.7f}")
+
+        if embedding.step > 0 and embedding_dir is not None and embedding.step % save_embedding_every == 0:
+            last_saved_file = os.path.join(embedding_dir, f'{embedding_name}-{embedding.step}.pt')
+            embedding.save(last_saved_file)
+
+        if embedding.step > 0 and images_dir is not None and embedding.step % create_image_every == 0:
+            last_saved_image = os.path.join(images_dir, f'{embedding_name}-{embedding.step}.png')
+
+            p = processing.StableDiffusionProcessingTxt2Img(
+                sd_model=shared.sd_model,
+                prompt=text,
+                steps=20,
+                do_not_save_grid=True,
+                do_not_save_samples=True,
+            )
+
+            processed = processing.process_images(p)
+            image = processed.images[0]
+
+            shared.state.current_image = image
+            image.save(last_saved_image)
+
+            last_saved_image += f", prompt: {text}"
+
+        shared.state.job_no = embedding.step
+
+        shared.state.textinfo = f"""
+<p>
+Loss: {losses.mean():.7f}<br/>
+Step: {embedding.step}<br/>
+Last prompt: {html.escape(text)}<br/>
+Last saved embedding: {html.escape(last_saved_file)}<br/>
+Last saved image: {html.escape(last_saved_image)}<br/>
+</p>
+"""
+
+    embedding.cached_checksum = None
+    embedding.save(filename)
+
+    return embedding, filename
+
diff --git a/modules/textual_inversion/ui.py b/modules/textual_inversion/ui.py
new file mode 100644
index 00000000..ce3677a9
--- /dev/null
+++ b/modules/textual_inversion/ui.py
@@ -0,0 +1,32 @@
+import html
+
+import gradio as gr
+
+import modules.textual_inversion.textual_inversion as ti
+from modules import sd_hijack, shared
+
+
+def create_embedding(name, nvpt):
+    filename = ti.create_embedding(name, nvpt)
+
+    sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings()
+
+    return gr.Dropdown.update(choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())), f"Created: {filename}", ""
+
+
+def train_embedding(*args):
+
+    try:
+        sd_hijack.undo_optimizations()
+
+        embedding, filename = ti.train_embedding(*args)
+
+        res = f"""
+Training {'interrupted' if shared.state.interrupted else 'finished'} after {embedding.step} steps.
+Embedding saved to {html.escape(filename)}
+"""
+        return res, ""
+    except Exception:
+        raise
+    finally:
+        sd_hijack.apply_optimizations()
diff --git a/modules/ui.py b/modules/ui.py
index 15572bb0..57aef6ff 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -21,6 +21,7 @@ import gradio as gr
 import gradio.utils
 import gradio.routes
 
+from modules import sd_hijack
 from modules.paths import script_path
 from modules.shared import opts, cmd_opts
 import modules.shared as shared
@@ -32,6 +33,7 @@ import modules.gfpgan_model
 import modules.codeformer_model
 import modules.styles
 import modules.generation_parameters_copypaste
+import modules.textual_inversion.ui
 
 # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the bowser will not show any UI
 mimetypes.init()
@@ -142,8 +144,8 @@ def save_files(js_data, images, index):
     return '', '', plaintext_to_html(f"Saved: {filenames[0]}")
 
 
-def wrap_gradio_call(func):
-    def f(*args, **kwargs):
+def wrap_gradio_call(func, extra_outputs=None):
+    def f(*args, extra_outputs_array=extra_outputs, **kwargs):
         run_memmon = opts.memmon_poll_rate > 0 and not shared.mem_mon.disabled
         if run_memmon:
             shared.mem_mon.monitor()
@@ -159,7 +161,10 @@ def wrap_gradio_call(func):
             shared.state.job = ""
             shared.state.job_count = 0
 
-            res = [None, '', f"<div class='error'>{plaintext_to_html(type(e).__name__+': '+str(e))}</div>"]
+            if extra_outputs_array is None:
+                extra_outputs_array = [None, '']
+
+            res = extra_outputs_array + [f"<div class='error'>{plaintext_to_html(type(e).__name__+': '+str(e))}</div>"]
 
         elapsed = time.perf_counter() - t
 
@@ -179,6 +184,7 @@ def wrap_gradio_call(func):
         res[-1] += f"<div class='performance'><p class='time'>Time taken: <wbr>{elapsed:.2f}s</p>{vram_html}</div>"
 
         shared.state.interrupted = False
+        shared.state.job_count = 0
 
         return tuple(res)
 
@@ -187,7 +193,7 @@ def wrap_gradio_call(func):
 
 def check_progress_call(id_part):
     if shared.state.job_count == 0:
-        return "", gr_show(False), gr_show(False)
+        return "", gr_show(False), gr_show(False), gr_show(False)
 
     progress = 0
 
@@ -219,13 +225,19 @@ def check_progress_call(id_part):
         else:
             preview_visibility = gr_show(True)
 
-    return f"<span id='{id_part}_progress_span' style='display: none'>{time.time()}</span><p>{progressbar}</p>", preview_visibility, image
+    if shared.state.textinfo is not None:
+        textinfo_result = gr.HTML.update(value=shared.state.textinfo, visible=True)
+    else:
+        textinfo_result = gr_show(False)
+
+    return f"<span id='{id_part}_progress_span' style='display: none'>{time.time()}</span><p>{progressbar}</p>", preview_visibility, image, textinfo_result
 
 
 def check_progress_call_initial(id_part):
     shared.state.job_count = -1
     shared.state.current_latent = None
     shared.state.current_image = None
+    shared.state.textinfo = None
 
     return check_progress_call(id_part)
 
@@ -399,13 +411,16 @@ def create_toprow(is_img2img):
     return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, interrogate, prompt_style_apply, save_style, paste
 
 
-def setup_progressbar(progressbar, preview, id_part):
+def setup_progressbar(progressbar, preview, id_part, textinfo=None):
+    if textinfo is None:
+        textinfo = gr.HTML(visible=False)
+
     check_progress = gr.Button('Check progress', elem_id=f"{id_part}_check_progress", visible=False)
     check_progress.click(
         fn=lambda: check_progress_call(id_part),
         show_progress=False,
         inputs=[],
-        outputs=[progressbar, preview, preview],
+        outputs=[progressbar, preview, preview, textinfo],
     )
 
     check_progress_initial = gr.Button('Check progress (first)', elem_id=f"{id_part}_check_progress_initial", visible=False)
@@ -413,11 +428,14 @@ def setup_progressbar(progressbar, preview, id_part):
         fn=lambda: check_progress_call_initial(id_part),
         show_progress=False,
         inputs=[],
-        outputs=[progressbar, preview, preview],
+        outputs=[progressbar, preview, preview, textinfo],
     )
 
 
-def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
+def create_ui(wrap_gradio_gpu_call):
+    import modules.img2img
+    import modules.txt2img
+
     with gr.Blocks(analytics_enabled=False) as txt2img_interface:
         txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, txt2img_prompt_style_apply, txt2img_save_style, paste = create_toprow(is_img2img=False)
         dummy_component = gr.Label(visible=False)
@@ -483,7 +501,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
             connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
 
             txt2img_args = dict(
-                fn=txt2img,
+                fn=wrap_gradio_gpu_call(modules.txt2img.txt2img),
                 _js="submit",
                 inputs=[
                     txt2img_prompt,
@@ -675,7 +693,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
             )
 
             img2img_args = dict(
-                fn=img2img,
+                fn=wrap_gradio_gpu_call(modules.img2img.img2img),
                 _js="submit_img2img",
                 inputs=[
                     dummy_component,
@@ -828,7 +846,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
                 open_extras_folder = gr.Button('Open output directory', elem_id=button_id)
 
         submit.click(
-            fn=run_extras,
+            fn=wrap_gradio_gpu_call(modules.extras.run_extras),
             _js="get_extras_tab_index",
             inputs=[
                 dummy_component,
@@ -878,7 +896,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
                     pnginfo_send_to_img2img = gr.Button('Send to img2img')
 
         image.change(
-            fn=wrap_gradio_call(run_pnginfo),
+            fn=wrap_gradio_call(modules.extras.run_pnginfo),
             inputs=[image],
             outputs=[html, generation_info, html2],
         )
@@ -887,7 +905,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
         with gr.Row().style(equal_height=False):
             with gr.Column(variant='panel'):
                 gr.HTML(value="<p>A merger of the two checkpoints will be generated in your <b>checkpoint</b> directory.</p>")
-                
+
                 with gr.Row():
                     primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary Model Name")
                     secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary Model Name")
@@ -896,10 +914,96 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
                 interp_method = gr.Radio(choices=["Weighted Sum", "Sigmoid", "Inverse Sigmoid"], value="Weighted Sum", label="Interpolation Method")
                 save_as_half = gr.Checkbox(value=False, label="Safe as float16")
                 modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary')
-            
+
             with gr.Column(variant='panel'):
                 submit_result = gr.Textbox(elem_id="modelmerger_result", show_label=False)
 
+    sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings()
+
+    with gr.Blocks() as textual_inversion_interface:
+        with gr.Row().style(equal_height=False):
+            with gr.Column():
+                with gr.Group():
+                    gr.HTML(value="<p style='margin-bottom: 0.7em'>Create a new embedding</p>")
+
+                    new_embedding_name = gr.Textbox(label="Name")
+                    nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1)
+
+                    with gr.Row():
+                        with gr.Column(scale=3):
+                            gr.HTML(value="")
+
+                        with gr.Column():
+                            create_embedding = gr.Button(value="Create", variant='primary')
+
+                with gr.Group():
+                    gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding; must specify a directory with a set of 512x512 images</p>")
+                    train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
+                    learn_rate = gr.Number(label='Learning rate', value=5.0e-03)
+                    dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images")
+                    log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")
+                    template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"))
+                    steps = gr.Number(label='Max steps', value=100000, precision=0)
+                    create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=1000, precision=0)
+                    save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=1000, precision=0)
+
+                    with gr.Row():
+                        with gr.Column(scale=2):
+                            gr.HTML(value="")
+
+                        with gr.Column():
+                            with gr.Row():
+                                interrupt_training = gr.Button(value="Interrupt")
+                                train_embedding = gr.Button(value="Train", variant='primary')
+
+            with gr.Column():
+                progressbar = gr.HTML(elem_id="ti_progressbar")
+                ti_output = gr.Text(elem_id="ti_output", value="", show_label=False)
+
+                ti_gallery = gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(grid=4)
+                ti_preview = gr.Image(elem_id='ti_preview', visible=False)
+                ti_progress = gr.HTML(elem_id="ti_progress", value="")
+                ti_outcome = gr.HTML(elem_id="ti_error", value="")
+                setup_progressbar(progressbar, ti_preview, 'ti', textinfo=ti_progress)
+
+        create_embedding.click(
+            fn=modules.textual_inversion.ui.create_embedding,
+            inputs=[
+                new_embedding_name,
+                nvpt,
+            ],
+            outputs=[
+                train_embedding_name,
+                ti_output,
+                ti_outcome,
+            ]
+        )
+
+        train_embedding.click(
+            fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.train_embedding, extra_outputs=[gr.update()]),
+            _js="start_training_textual_inversion",
+            inputs=[
+                train_embedding_name,
+                learn_rate,
+                dataset_directory,
+                log_directory,
+                steps,
+                create_image_every,
+                save_embedding_every,
+                template_file,
+            ],
+            outputs=[
+                ti_output,
+                ti_outcome,
+            ]
+        )
+
+        interrupt_training.click(
+            fn=lambda: shared.state.interrupt(),
+            inputs=[],
+            outputs=[],
+        )
+
     def create_setting_component(key):
         def fun():
             return opts.data[key] if key in opts.data else opts.data_labels[key].default
@@ -1011,6 +1115,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
         (extras_interface, "Extras", "extras"),
         (pnginfo_interface, "PNG Info", "pnginfo"),
         (modelmerger_interface, "Checkpoint Merger", "modelmerger"),
+        (textual_inversion_interface, "Textual inversion", "ti"),
         (settings_interface, "Settings", "settings"),
     ]
 
@@ -1044,11 +1149,11 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
         
         def modelmerger(*args):
             try:
-                results = run_modelmerger(*args)
+                results = modules.extras.run_modelmerger(*args)
             except Exception as e:
                 print("Error loading/saving model file:", file=sys.stderr)
                 print(traceback.format_exc(), file=sys.stderr)
-                modules.sd_models.list_models() #To remove the potentially missing models from the list
+                modules.sd_models.list_models()  # to remove the potentially missing models from the list
                 return ["Error loading/saving model file. It doesn't exist or the name contains illegal characters"] + [gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(3)]
             return results
 
diff --git a/style.css b/style.css
index 79d6bb0d..39586bf1 100644
--- a/style.css
+++ b/style.css
@@ -157,7 +157,7 @@ button{
     max-width: 10em;
 }
 
-#txt2img_preview, #img2img_preview{
+#txt2img_preview, #img2img_preview, #ti_preview{
     position: absolute;
     width: 320px;
     left: 0;
@@ -172,18 +172,18 @@ button{
 }
 
 @media screen and (min-width: 768px) {
-    #txt2img_preview, #img2img_preview {
+    #txt2img_preview, #img2img_preview, #ti_preview {
         position: absolute;
     }
 }
 
 @media screen and (max-width: 767px) {
-    #txt2img_preview, #img2img_preview {
+    #txt2img_preview, #img2img_preview, #ti_preview {
         position: relative;
     }
 }
 
-#txt2img_preview div.left-0.top-0, #img2img_preview div.left-0.top-0{
+#txt2img_preview div.left-0.top-0, #img2img_preview div.left-0.top-0, #ti_preview div.left-0.top-0{
     display: none;
 }
 
@@ -247,7 +247,7 @@ input[type="range"]{
 #txt2img_negative_prompt, #img2img_negative_prompt{
 }
 
-#txt2img_progressbar, #img2img_progressbar{
+#txt2img_progressbar, #img2img_progressbar, #ti_progressbar{
   position: absolute;
   z-index: 1000;
   right: 0;
diff --git a/textual_inversion_templates/style.txt b/textual_inversion_templates/style.txt
new file mode 100644
index 00000000..15af2d6b
--- /dev/null
+++ b/textual_inversion_templates/style.txt
@@ -0,0 +1,19 @@
+a painting, art by [name]
+a rendering, art by [name]
+a cropped painting, art by [name]
+the painting, art by [name]
+a clean painting, art by [name]
+a dirty painting, art by [name]
+a dark painting, art by [name]
+a picture, art by [name]
+a cool painting, art by [name]
+a close-up painting, art by [name]
+a bright painting, art by [name]
+a cropped painting, art by [name]
+a good painting, art by [name]
+a close-up painting, art by [name]
+a rendition, art by [name]
+a nice painting, art by [name]
+a small painting, art by [name]
+a weird painting, art by [name]
+a large painting, art by [name]
diff --git a/textual_inversion_templates/style_filewords.txt b/textual_inversion_templates/style_filewords.txt
new file mode 100644
index 00000000..b3a8159a
--- /dev/null
+++ b/textual_inversion_templates/style_filewords.txt
@@ -0,0 +1,19 @@
+a painting of [filewords], art by [name]
+a rendering of [filewords], art by [name]
+a cropped painting of [filewords], art by [name]
+the painting of [filewords], art by [name]
+a clean painting of [filewords], art by [name]
+a dirty painting of [filewords], art by [name]
+a dark painting of [filewords], art by [name]
+a picture of [filewords], art by [name]
+a cool painting of [filewords], art by [name]
+a close-up painting of [filewords], art by [name]
+a bright painting of [filewords], art by [name]
+a cropped painting of [filewords], art by [name]
+a good painting of [filewords], art by [name]
+a close-up painting of [filewords], art by [name]
+a rendition of [filewords], art by [name]
+a nice painting of [filewords], art by [name]
+a small painting of [filewords], art by [name]
+a weird painting of [filewords], art by [name]
+a large painting of [filewords], art by [name]
diff --git a/textual_inversion_templates/subject.txt b/textual_inversion_templates/subject.txt
new file mode 100644
index 00000000..79f36aa0
--- /dev/null
+++ b/textual_inversion_templates/subject.txt
@@ -0,0 +1,27 @@
+a photo of a [name]
+a rendering of a [name]
+a cropped photo of the [name]
+the photo of a [name]
+a photo of a clean [name]
+a photo of a dirty [name]
+a dark photo of the [name]
+a photo of my [name]
+a photo of the cool [name]
+a close-up photo of a [name]
+a bright photo of the [name]
+a cropped photo of a [name]
+a photo of the [name]
+a good photo of the [name]
+a photo of one [name]
+a close-up photo of the [name]
+a rendition of the [name]
+a photo of the clean [name]
+a rendition of a [name]
+a photo of a nice [name]
+a good photo of a [name]
+a photo of the nice [name]
+a photo of the small [name]
+a photo of the weird [name]
+a photo of the large [name]
+a photo of a cool [name]
+a photo of a small [name]
diff --git a/textual_inversion_templates/subject_filewords.txt b/textual_inversion_templates/subject_filewords.txt
new file mode 100644
index 00000000..008652a6
--- /dev/null
+++ b/textual_inversion_templates/subject_filewords.txt
@@ -0,0 +1,27 @@
+a photo of a [name], [filewords]
+a rendering of a [name], [filewords]
+a cropped photo of the [name], [filewords]
+the photo of a [name], [filewords]
+a photo of a clean [name], [filewords]
+a photo of a dirty [name], [filewords]
+a dark photo of the [name], [filewords]
+a photo of my [name], [filewords]
+a photo of the cool [name], [filewords]
+a close-up photo of a [name], [filewords]
+a bright photo of the [name], [filewords]
+a cropped photo of a [name], [filewords]
+a photo of the [name], [filewords]
+a good photo of the [name], [filewords]
+a photo of one [name], [filewords]
+a close-up photo of the [name], [filewords]
+a rendition of the [name], [filewords]
+a photo of the clean [name], [filewords]
+a rendition of a [name], [filewords]
+a photo of a nice [name], [filewords]
+a good photo of a [name], [filewords]
+a photo of the nice [name], [filewords]
+a photo of the small [name], [filewords]
+a photo of the weird [name], [filewords]
+a photo of the large [name], [filewords]
+a photo of a cool [name], [filewords]
+a photo of a small [name], [filewords]
diff --git a/webui.py b/webui.py
index b8cccd54..19fdcdd4 100644
--- a/webui.py
+++ b/webui.py
@@ -12,7 +12,6 @@ import modules.bsrgan_model as bsrgan
 import modules.extras
 import modules.face_restoration
 import modules.gfpgan_model as gfpgan
-import modules.img2img
 import modules.ldsr_model as ldsr
 import modules.lowvram
 import modules.realesrgan_model as realesrgan
@@ -21,7 +20,6 @@ import modules.sd_hijack
 import modules.sd_models
 import modules.shared as shared
 import modules.swinir_model as swinir
-import modules.txt2img
 import modules.ui
 from modules import modelloader
 from modules.paths import script_path
@@ -46,7 +44,7 @@ def wrap_queued_call(func):
     return f
 
 
-def wrap_gradio_gpu_call(func):
+def wrap_gradio_gpu_call(func, extra_outputs=None):
     def f(*args, **kwargs):
         devices.torch_gc()
 
@@ -58,6 +56,7 @@ def wrap_gradio_gpu_call(func):
         shared.state.current_image = None
         shared.state.current_image_sampling_step = 0
         shared.state.interrupted = False
+        shared.state.textinfo = None
 
         with queue_lock:
             res = func(*args, **kwargs)
@@ -69,7 +68,7 @@ def wrap_gradio_gpu_call(func):
 
         return res
 
-    return modules.ui.wrap_gradio_call(f)
+    return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs)
 
 
 modules.scripts.load_scripts(os.path.join(script_path, "scripts"))
@@ -86,13 +85,7 @@ def webui():
 
     signal.signal(signal.SIGINT, sigint_handler)
 
-    demo = modules.ui.create_ui(
-        txt2img=wrap_gradio_gpu_call(modules.txt2img.txt2img),
-        img2img=wrap_gradio_gpu_call(modules.img2img.img2img),
-        run_extras=wrap_gradio_gpu_call(modules.extras.run_extras),
-        run_pnginfo=modules.extras.run_pnginfo,
-        run_modelmerger=modules.extras.run_modelmerger
-    )
+    demo = modules.ui.create_ui(wrap_gradio_gpu_call=wrap_gradio_gpu_call)
 
     demo.launch(
         share=cmd_opts.share,
-- 
cgit v1.2.3


From 0114057ad672a581bd0b598870b58b674b1a3624 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 2 Oct 2022 15:49:42 +0300
Subject: fix incorrect use of glob in modelloader for #1410

---
 modules/modelloader.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/modelloader.py b/modules/modelloader.py
index 8c862b42..015aeafa 100644
--- a/modules/modelloader.py
+++ b/modules/modelloader.py
@@ -43,7 +43,7 @@ def load_models(model_path: str, model_url: str = None, command_path: str = None
         for place in places:
             if os.path.exists(place):
                 for file in glob.iglob(place + '**/**', recursive=True):
-                    full_path = os.path.join(place, file)
+                    full_path = file
                     if os.path.isdir(full_path):
                         continue
                     if len(ext_filter) != 0:
-- 
cgit v1.2.3


From 4e72a1aab6d1b3a8d8c09fadc81843a07c05cc18 Mon Sep 17 00:00:00 2001
From: ClashSAN <98228077+ClashSAN@users.noreply.github.com>
Date: Sat, 1 Oct 2022 00:15:43 +0000
Subject: Grammar Fix

---
 README.md | 16 ++++++++--------
 1 file changed, 8 insertions(+), 8 deletions(-)

diff --git a/README.md b/README.md
index 5ded94f9..15e224e8 100644
--- a/README.md
+++ b/README.md
@@ -11,12 +11,12 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
 - One click install and run script (but you still must install python and git)
 - Outpainting
 - Inpainting
-- Prompt
-- Stable Diffusion upscale
+- Prompt Matrix
+- Stable Diffusion Upscale
 - Attention, specify parts of text that the model should pay more attention to
-    - a man in a ((txuedo)) - will pay more attentinoto tuxedo
-    - a man in a (txuedo:1.21) - alternative syntax
-- Loopback, run img2img procvessing multiple times
+    - a man in a ((tuxedo)) - will pay more attention to tuxedo
+    - a man in a (tuxedo:1.21) - alternative syntax
+- Loopback, run img2img processing multiple times
 - X/Y plot, a way to draw a 2 dimensional plot of images with different parameters
 - Textual Inversion
     - have as many embeddings as you want and use any names you like for them
@@ -35,15 +35,15 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
 - 4GB video card support (also reports of 2GB working)
 - Correct seeds for batches 
 - Prompt length validation
-     - get length of prompt in tokensas you type
-     - get a warning after geenration if some text was truncated
+     - get length of prompt in tokens as you type
+     - get a warning after generation if some text was truncated
 - Generation parameters
      - parameters you used to generate images are saved with that image
      - in PNG chunks for PNG, in EXIF for JPEG
      - can drag the image to PNG info tab to restore generation parameters and automatically copy them into UI
      - can be disabled in settings
 - Settings page
-- Running arbitrary python code from UI (must run with commandline flag to enable)
+- Running arbitrary python code from UI (must run with --allow-code to enable)
 - Mouseover hints for most UI elements
 - Possible to change defaults/mix/max/step values for UI elements via text config
 - Random artist button
-- 
cgit v1.2.3


From 0758f6e641b5790ce566a998d43e0ea74a627766 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 2 Oct 2022 17:24:50 +0300
Subject: fix --ckpt option breaking model selection

---
 modules/sd_models.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/sd_models.py b/modules/sd_models.py
index 5b3dbdc7..9259d69e 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -69,7 +69,7 @@ def list_models():
         h = model_hash(cmd_ckpt)
         title, short_model_name = modeltitle(cmd_ckpt, h)
         checkpoints_list[title] = CheckpointInfo(cmd_ckpt, title, h, short_model_name)
-        shared.opts.sd_model_checkpoint = title
+        shared.opts.data['sd_model_checkpoint'] = title
     elif cmd_ckpt is not None and cmd_ckpt != shared.default_sd_model_file:
         print(f"Checkpoint in --ckpt argument not found (Possible it was moved to {model_path}: {cmd_ckpt}", file=sys.stderr)
     for filename in model_list:
-- 
cgit v1.2.3


From 53a3dc601fb734ce433505b1ca68770919106bad Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 2 Oct 2022 18:21:56 +0300
Subject: move CLIP out of requirements and into launcher to make it possible
 to launch the program offline

---
 launch.py                 | 4 ++++
 requirements.txt          | 2 --
 requirements_versions.txt | 1 -
 3 files changed, 4 insertions(+), 3 deletions(-)

diff --git a/launch.py b/launch.py
index d2793ed2..57405fea 100644
--- a/launch.py
+++ b/launch.py
@@ -15,6 +15,7 @@ requirements_file = os.environ.get('REQS_FILE', "requirements_versions.txt")
 commandline_args = os.environ.get('COMMANDLINE_ARGS', "")
 
 gfpgan_package = os.environ.get('GFPGAN_PACKAGE', "git+https://github.com/TencentARC/GFPGAN.git@8d2447a2d918f8eba5a4a01463fd48e45126a379")
+clip_package = os.environ.get('CLIP_PACKAGE', "git+https://github.com/openai/CLIP.git@d50d76daa670286dd6cacf3bcd80b5e4823fc8e1")
 
 stable_diffusion_commit_hash = os.environ.get('STABLE_DIFFUSION_COMMIT_HASH', "69ae4b35e0a0f6ee1af8bb9a5d0016ccb27e36dc")
 taming_transformers_commit_hash = os.environ.get('TAMING_TRANSFORMERS_COMMIT_HASH', "24268930bf1dce879235a7fddd0b2355b84d7ea6")
@@ -111,6 +112,9 @@ if not skip_torch_cuda_test:
 if not is_installed("gfpgan"):
     run_pip(f"install {gfpgan_package}", "gfpgan")
 
+if not is_installed("clip"):
+    run_pip(f"install {clip_package}", "clip")
+
 os.makedirs(dir_repos, exist_ok=True)
 
 git_clone("https://github.com/CompVis/stable-diffusion.git", repo_dir('stable-diffusion'), "Stable Diffusion", stable_diffusion_commit_hash)
diff --git a/requirements.txt b/requirements.txt
index 7cb9d329..d4b337fc 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -13,14 +13,12 @@ Pillow
 pytorch_lightning
 realesrgan
 scikit-image>=0.19
-git+https://github.com/TencentARC/GFPGAN.git@8d2447a2d918f8eba5a4a01463fd48e45126a379
 timm==0.4.12
 transformers==4.19.2
 torch
 einops
 jsonmerge
 clean-fid
-git+https://github.com/openai/CLIP@d50d76daa670286dd6cacf3bcd80b5e4823fc8e1
 resize-right
 torchdiffeq
 kornia
diff --git a/requirements_versions.txt b/requirements_versions.txt
index 1e8006e0..8a9acf20 100644
--- a/requirements_versions.txt
+++ b/requirements_versions.txt
@@ -18,7 +18,6 @@ piexif==1.1.3
 einops==0.4.1
 jsonmerge==1.8.0
 clean-fid==0.1.29
-git+https://github.com/openai/CLIP@d50d76daa670286dd6cacf3bcd80b5e4823fc8e1
 resize-right==0.0.2
 torchdiffeq==0.2.3
 kornia==0.6.7
-- 
cgit v1.2.3


From 88ec0cf5571883d84abd09196652b3679e359f2e Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 2 Oct 2022 19:40:51 +0300
Subject: fix for incorrect embedding token length calculation (will break
 seeds that use embeddings, you're welcome!) add option to input
 initialization text for embeddings

---
 modules/sd_hijack.py                           |  8 ++++----
 modules/textual_inversion/textual_inversion.py | 13 +++++--------
 modules/textual_inversion/ui.py                |  4 ++--
 modules/ui.py                                  |  2 ++
 4 files changed, 13 insertions(+), 14 deletions(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index fd57e5c5..3fa06242 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -130,7 +130,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
             while i < len(tokens):
                 token = tokens[i]
 
-                embedding = self.hijack.embedding_db.find_embedding_at_position(tokens, i)
+                embedding, embedding_length_in_tokens = self.hijack.embedding_db.find_embedding_at_position(tokens, i)
 
                 if embedding is None:
                     remade_tokens.append(token)
@@ -142,7 +142,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
                     remade_tokens += [0] * emb_len
                     multipliers += [weight] * emb_len
                     used_custom_terms.append((embedding.name, embedding.checksum()))
-                    i += emb_len
+                    i += embedding_length_in_tokens
 
         if len(remade_tokens) > maxlen - 2:
             vocab = {v: k for k, v in self.wrapped.tokenizer.get_vocab().items()}
@@ -213,7 +213,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
                 while i < len(tokens):
                     token = tokens[i]
 
-                    embedding = self.hijack.embedding_db.find_embedding_at_position(tokens, i)
+                    embedding, embedding_length_in_tokens = self.hijack.embedding_db.find_embedding_at_position(tokens, i)
 
                     mult_change = self.token_mults.get(token) if opts.enable_emphasis else None
                     if mult_change is not None:
@@ -229,7 +229,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
                         remade_tokens += [0] * emb_len
                         multipliers += [mult] * emb_len
                         used_custom_terms.append((embedding.name, embedding.checksum()))
-                        i += emb_len
+                        i += embedding_length_in_tokens
 
                 if len(remade_tokens) > maxlen - 2:
                     vocab = {v: k for k, v in self.wrapped.tokenizer.get_vocab().items()}
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index c0baaace..0c50161d 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -117,24 +117,21 @@ class EmbeddingDatabase:
         possible_matches = self.ids_lookup.get(token, None)
 
         if possible_matches is None:
-            return None
+            return None, None
 
         for ids, embedding in possible_matches:
             if tokens[offset:offset + len(ids)] == ids:
-                return embedding
+                return embedding, len(ids)
 
-        return None
+        return None, None
 
 
-
-def create_embedding(name, num_vectors_per_token):
-    init_text = '*'
-
+def create_embedding(name, num_vectors_per_token, init_text='*'):
     cond_model = shared.sd_model.cond_stage_model
     embedding_layer = cond_model.wrapped.transformer.text_model.embeddings
 
     ids = cond_model.tokenizer(init_text, max_length=num_vectors_per_token, return_tensors="pt", add_special_tokens=False)["input_ids"]
-    embedded = embedding_layer(ids.to(devices.device)).squeeze(0)
+    embedded = embedding_layer.token_embedding.wrapped(ids.to(devices.device)).squeeze(0)
     vec = torch.zeros((num_vectors_per_token, embedded.shape[1]), device=devices.device)
 
     for i in range(num_vectors_per_token):
diff --git a/modules/textual_inversion/ui.py b/modules/textual_inversion/ui.py
index ce3677a9..66c43ffb 100644
--- a/modules/textual_inversion/ui.py
+++ b/modules/textual_inversion/ui.py
@@ -6,8 +6,8 @@ import modules.textual_inversion.textual_inversion as ti
 from modules import sd_hijack, shared
 
 
-def create_embedding(name, nvpt):
-    filename = ti.create_embedding(name, nvpt)
+def create_embedding(name, initialization_text, nvpt):
+    filename = ti.create_embedding(name, nvpt, init_text=initialization_text)
 
     sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings()
 
diff --git a/modules/ui.py b/modules/ui.py
index 3b81a4f7..eca50df0 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -954,6 +954,7 @@ def create_ui(wrap_gradio_gpu_call):
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Create a new embedding</p>")
 
                     new_embedding_name = gr.Textbox(label="Name")
+                    initialization_text = gr.Textbox(label="Initialization text", value="*")
                     nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1)
 
                     with gr.Row():
@@ -997,6 +998,7 @@ def create_ui(wrap_gradio_gpu_call):
             fn=modules.textual_inversion.ui.create_embedding,
             inputs=[
                 new_embedding_name,
+                initialization_text,
                 nvpt,
             ],
             outputs=[
-- 
cgit v1.2.3


From 71fe7fa49f5eb1a2c89932a9d217ed153c12fc8b Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 2 Oct 2022 19:56:37 +0300
Subject: fix using aaaa-100 embedding when the prompt has aaaa-10000 and you
 have both aaaa-100 and aaaa-10000 in the directory with embeddings.

---
 modules/textual_inversion/textual_inversion.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 0c50161d..9d2241ce 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -57,7 +57,8 @@ class EmbeddingDatabase:
         first_id = ids[0]
         if first_id not in self.ids_lookup:
             self.ids_lookup[first_id] = []
-        self.ids_lookup[first_id].append((ids, embedding))
+
+        self.ids_lookup[first_id] = sorted(self.ids_lookup[first_id] + [(ids, embedding)], key=lambda x: len(x[0]), reverse=True)
 
         return embedding
 
-- 
cgit v1.2.3


From 4ec4af6e0b7addeee5221a03f32d117ccdc875d9 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 2 Oct 2022 20:15:25 +0300
Subject: add checkpoint info to saved embeddings

---
 modules/textual_inversion/textual_inversion.py | 13 ++++++++++++-
 1 file changed, 12 insertions(+), 1 deletion(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 9d2241ce..1183aab7 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -7,7 +7,7 @@ import tqdm
 import html
 import datetime
 
-from modules import shared, devices, sd_hijack, processing
+from modules import shared, devices, sd_hijack, processing, sd_models
 import modules.textual_inversion.dataset
 
 
@@ -17,6 +17,8 @@ class Embedding:
         self.name = name
         self.step = step
         self.cached_checksum = None
+        self.sd_checkpoint = None
+        self.sd_checkpoint_name = None
 
     def save(self, filename):
         embedding_data = {
@@ -24,6 +26,8 @@ class Embedding:
             "string_to_param": {"*": self.vec},
             "name": self.name,
             "step": self.step,
+            "sd_checkpoint": self.sd_checkpoint,
+            "sd_checkpoint_name": self.sd_checkpoint_name,
         }
 
         torch.save(embedding_data, filename)
@@ -41,6 +45,7 @@ class Embedding:
         self.cached_checksum = f'{const_hash(self.vec.reshape(-1) * 100) & 0xffff:04x}'
         return self.cached_checksum
 
+
 class EmbeddingDatabase:
     def __init__(self, embeddings_dir):
         self.ids_lookup = {}
@@ -96,6 +101,8 @@ class EmbeddingDatabase:
             vec = emb.detach().to(devices.device, dtype=torch.float32)
             embedding = Embedding(vec, name)
             embedding.step = data.get('step', None)
+            embedding.sd_checkpoint = data.get('hash', None)
+            embedding.sd_checkpoint_name = data.get('sd_checkpoint_name', None)
             self.register_embedding(embedding, shared.sd_model)
 
         for fn in os.listdir(self.embeddings_dir):
@@ -249,6 +256,10 @@ Last saved image: {html.escape(last_saved_image)}<br/>
 </p>
 """
 
+    checkpoint = sd_models.select_checkpoint()
+
+    embedding.sd_checkpoint = checkpoint.hash
+    embedding.sd_checkpoint_name = checkpoint.model_name
     embedding.cached_checksum = None
     embedding.save(filename)
 
-- 
cgit v1.2.3


From 3ff0de2c594b786ef948a89efb1814c59bb42117 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 2 Oct 2022 20:23:40 +0300
Subject: added --disable-console-progressbars to disable progressbars in
 console disabled printing prompts to console by default, enabled by
 --enable-console-prompts

---
 modules/img2img.py     | 4 +++-
 modules/sd_samplers.py | 8 ++++++--
 modules/shared.py      | 7 +++++--
 modules/txt2img.py     | 4 +++-
 4 files changed, 17 insertions(+), 6 deletions(-)

diff --git a/modules/img2img.py b/modules/img2img.py
index 03e934e9..f4455c90 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -103,7 +103,9 @@ def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, pro
         inpaint_full_res_padding=inpaint_full_res_padding,
         inpainting_mask_invert=inpainting_mask_invert,
     )
-    print(f"\nimg2img: {prompt}", file=shared.progress_print_out)
+
+    if shared.cmd_opts.enable_console_prompts:
+        print(f"\nimg2img: {prompt}", file=shared.progress_print_out)
 
     p.extra_generation_params["Mask blur"] = mask_blur
 
diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index 92522214..9316875a 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -77,7 +77,9 @@ def extended_tdqm(sequence, *args, desc=None, **kwargs):
     state.sampling_steps = len(sequence)
     state.sampling_step = 0
 
-    for x in tqdm.tqdm(sequence, *args, desc=state.job, file=shared.progress_print_out, **kwargs):
+    seq = sequence if cmd_opts.disable_console_progressbars else tqdm.tqdm(sequence, *args, desc=state.job, file=shared.progress_print_out, **kwargs)
+
+    for x in seq:
         if state.interrupted:
             break
 
@@ -207,7 +209,9 @@ def extended_trange(sampler, count, *args, **kwargs):
     state.sampling_steps = count
     state.sampling_step = 0
 
-    for x in tqdm.trange(count, *args, desc=state.job, file=shared.progress_print_out, **kwargs):
+    seq = range(count) if cmd_opts.disable_console_progressbars else tqdm.trange(count, *args, desc=state.job, file=shared.progress_print_out, **kwargs)
+
+    for x in seq:
         if state.interrupted:
             break
 
diff --git a/modules/shared.py b/modules/shared.py
index 5a591dc9..1bf7a6c1 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -58,6 +58,9 @@ parser.add_argument("--opt-channelslast", action='store_true', help="change memo
 parser.add_argument("--styles-file", type=str, help="filename to use for styles", default=os.path.join(script_path, 'styles.csv'))
 parser.add_argument("--autolaunch", action='store_true', help="open the webui URL in the system's default browser upon launch", default=False)
 parser.add_argument("--use-textbox-seed", action='store_true', help="use textbox for seeds in UI (no up/down, but possible to input long seeds)", default=False)
+parser.add_argument("--disable-console-progressbars", action='store_true', help="do not output progressbars to console", default=False)
+parser.add_argument("--enable-console-prompts", action='store_true', help="print prompts to console when generating with txt2img and img2img", default=False)
+
 
 cmd_opts = parser.parse_args()
 device = get_optimal_device()
@@ -320,14 +323,14 @@ class TotalTQDM:
         )
 
     def update(self):
-        if not opts.multiple_tqdm:
+        if not opts.multiple_tqdm or cmd_opts.disable_console_progressbars:
             return
         if self._tqdm is None:
             self.reset()
         self._tqdm.update()
 
     def updateTotal(self, new_total):
-        if not opts.multiple_tqdm:
+        if not opts.multiple_tqdm or cmd_opts.disable_console_progressbars:
             return
         if self._tqdm is None:
             self.reset()
diff --git a/modules/txt2img.py b/modules/txt2img.py
index 5368e4d0..d4406c3c 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -34,7 +34,9 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2:
         denoising_strength=denoising_strength if enable_hr else None,
     )
 
-    print(f"\ntxt2img: {prompt}", file=shared.progress_print_out)
+    if cmd_opts.enable_console_prompts:
+        print(f"\ntxt2img: {prompt}", file=shared.progress_print_out)
+
     processed = modules.scripts.scripts_txt2img.run(p, *args)
 
     if processed is None:
-- 
cgit v1.2.3


From 6365a41f5981efa506dfe4e8fa878b43ca2d8d0c Mon Sep 17 00:00:00 2001
From: d8ahazard <d8ahazard@gmail.com>
Date: Sun, 2 Oct 2022 12:58:17 -0500
Subject: Update esrgan_model.py

Use alternate ESRGAN Model download path.
---
 modules/esrgan_model.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py
index ea91abfe..4aed9283 100644
--- a/modules/esrgan_model.py
+++ b/modules/esrgan_model.py
@@ -73,8 +73,8 @@ def fix_model_layers(crt_model, pretrained_net):
 class UpscalerESRGAN(Upscaler):
     def __init__(self, dirname):
         self.name = "ESRGAN"
-        self.model_url = "https://drive.google.com/u/0/uc?id=1TPrz5QKd8DHHt1k8SRtm6tMiPjz_Qene&export=download"
-        self.model_name = "ESRGAN 4x"
+        self.model_url = "https://github.com/cszn/KAIR/releases/download/v1.0/ESRGAN.pth"
+        self.model_name = "ESRGAN_4x"
         self.scalers = []
         self.user_path = dirname
         self.model_path = os.path.join(models_path, self.name)
-- 
cgit v1.2.3


From a1cde7e6468f80584030525a1b07cbf0f4ee42eb Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 2 Oct 2022 21:09:10 +0300
Subject: disabled SD model download after multiple complaints

---
 modules/sd_models.py            | 18 ++++++++----------
 modules/textual_inversion/ui.py |  2 +-
 webui.py                        |  2 +-
 3 files changed, 10 insertions(+), 12 deletions(-)

diff --git a/modules/sd_models.py b/modules/sd_models.py
index 9259d69e..9a6b568f 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -13,9 +13,6 @@ from modules.paths import models_path
 
 model_dir = "Stable-diffusion"
 model_path = os.path.abspath(os.path.join(models_path, model_dir))
-model_name = "sd-v1-4.ckpt"
-model_url = "https://drive.yerf.org/wl/?id=EBfTrmcCCUAGaQBXVIj5lJmEhjoP1tgl&mode=grid&download=1"
-user_dir = None
 
 CheckpointInfo = namedtuple("CheckpointInfo", ['filename', 'title', 'hash', 'model_name'])
 checkpoints_list = {}
@@ -30,12 +27,10 @@ except Exception:
     pass
 
 
-def setup_model(dirname):
-    global user_dir
-    user_dir = dirname
+def setup_model():
     if not os.path.exists(model_path):
         os.makedirs(model_path)
-    checkpoints_list.clear()
+
     list_models()
 
 
@@ -45,7 +40,7 @@ def checkpoint_tiles():
 
 def list_models():
     checkpoints_list.clear()
-    model_list = modelloader.load_models(model_path=model_path, model_url=model_url, command_path=user_dir, ext_filter=[".ckpt"], download_name=model_name)
+    model_list = modelloader.load_models(model_path=model_path, command_path=shared.cmd_opts.ckpt_dir, ext_filter=[".ckpt"])
 
     def modeltitle(path, shorthash):
         abspath = os.path.abspath(path)
@@ -106,8 +101,11 @@ def select_checkpoint():
 
     if len(checkpoints_list) == 0:
         print(f"No checkpoints found. When searching for checkpoints, looked at:", file=sys.stderr)
-        print(f" - file {os.path.abspath(shared.cmd_opts.ckpt)}", file=sys.stderr)
-        print(f" - directory {os.path.abspath(shared.cmd_opts.ckpt_dir)}", file=sys.stderr)
+        if shared.cmd_opts.ckpt is not None:
+            print(f" - file {os.path.abspath(shared.cmd_opts.ckpt)}", file=sys.stderr)
+        print(f" - directory {model_path}", file=sys.stderr)
+        if shared.cmd_opts.ckpt_dir is not None:
+            print(f" - directory {os.path.abspath(shared.cmd_opts.ckpt_dir)}", file=sys.stderr)
         print(f"Can't run without a checkpoint. Find and place a .ckpt file into any of those locations. The program will exit.", file=sys.stderr)
         exit(1)
 
diff --git a/modules/textual_inversion/ui.py b/modules/textual_inversion/ui.py
index 66c43ffb..633037d8 100644
--- a/modules/textual_inversion/ui.py
+++ b/modules/textual_inversion/ui.py
@@ -22,7 +22,7 @@ def train_embedding(*args):
         embedding, filename = ti.train_embedding(*args)
 
         res = f"""
-Training {'interrupted' if shared.state.interrupted else 'finished'} after {embedding.step} steps.
+Training {'interrupted' if shared.state.interrupted else 'finished'} at {embedding.step} steps.
 Embedding saved to {html.escape(filename)}
 """
         return res, ""
diff --git a/webui.py b/webui.py
index 424ab975..dc72ceb8 100644
--- a/webui.py
+++ b/webui.py
@@ -23,7 +23,7 @@ from modules.paths import script_path
 from modules.shared import cmd_opts
 
 modelloader.cleanup_models()
-modules.sd_models.setup_model(cmd_opts.ckpt_dir)
+modules.sd_models.setup_model()
 codeformer.setup_model(cmd_opts.codeformer_models_path)
 gfpgan.setup_model(cmd_opts.gfpgan_models_path)
 shared.face_restorers.append(modules.face_restoration.FaceRestoration())
-- 
cgit v1.2.3


From 852fd90c0dcda9cb5fbbfdf0c7308ce58034935c Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 2 Oct 2022 21:22:20 +0300
Subject: emergency fix for disabling SD model download after multiple
 complaints

---
 modules/sd_models.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/modules/sd_models.py b/modules/sd_models.py
index 9a6b568f..5f992064 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -45,8 +45,8 @@ def list_models():
     def modeltitle(path, shorthash):
         abspath = os.path.abspath(path)
 
-        if user_dir is not None and abspath.startswith(user_dir):
-            name = abspath.replace(user_dir, '')
+        if shared.cmd_opts.ckpt_dir is not None and abspath.startswith(shared.cmd_opts.ckpt_dir):
+            name = abspath.replace(shared.cmd_opts.ckpt_dir, '')
         elif abspath.startswith(model_path):
             name = abspath.replace(model_path, '')
         else:
-- 
cgit v1.2.3


From e808096cf641d868f88465515d70d40fc46125d4 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sun, 2 Oct 2022 19:26:06 +0100
Subject: correct indent

---
 modules/scripts.py | 48 +++++++++++++++++++++++++-----------------------
 modules/ui.py      | 25 ++++++++++++-------------
 2 files changed, 37 insertions(+), 36 deletions(-)

diff --git a/modules/scripts.py b/modules/scripts.py
index 788397f5..45230f9a 100644
--- a/modules/scripts.py
+++ b/modules/scripts.py
@@ -163,37 +163,39 @@ class ScriptRunner:
         return processed
 
     def reload_sources(self):
-      for si,script in list(enumerate(self.scripts)):
-        with open(script.filename, "r", encoding="utf8") as file:
-            args_from = script.args_from
-            args_to   = script.args_to 
-            filename  = script.filename
-            text = file.read()
+        for si, script in list(enumerate(self.scripts)):
+            with open(script.filename, "r", encoding="utf8") as file:
+                args_from = script.args_from
+                args_to = script.args_to
+                filename = script.filename
+                text = file.read()
 
-            from types import ModuleType
-            compiled = compile(text, filename, 'exec')
-            module = ModuleType(script.filename)
-            exec(compiled, module.__dict__)
+                from types import ModuleType
 
-            for key, script_class in module.__dict__.items():
-                if type(script_class) == type and issubclass(script_class, Script):
-                    self.scripts[si] = script_class()
-                    self.scripts[si].filename = filename
-                    self.scripts[si].args_from = args_from
-                    self.scripts[si].args_to = args_to
+                compiled = compile(text, filename, 'exec')
+                module = ModuleType(script.filename)
+                exec(compiled, module.__dict__)
+
+                for key, script_class in module.__dict__.items():
+                    if type(script_class) == type and issubclass(script_class, Script):
+                        self.scripts[si] = script_class()
+                        self.scripts[si].filename = filename
+                        self.scripts[si].args_from = args_from
+                        self.scripts[si].args_to = args_to
 
 scripts_txt2img = ScriptRunner()
 scripts_img2img = ScriptRunner()
 
 def reload_script_body_only():
-  scripts_txt2img.reload_sources()
-  scripts_img2img.reload_sources()
+    scripts_txt2img.reload_sources()
+    scripts_img2img.reload_sources()
+
 
 def reload_scripts(basedir):
-  global scripts_txt2img,scripts_img2img
+    global scripts_txt2img, scripts_img2img
 
-  scripts_data.clear()
-  load_scripts(basedir)
+    scripts_data.clear()
+    load_scripts(basedir)
 
-  scripts_txt2img = ScriptRunner()
-  scripts_img2img = ScriptRunner()
+    scripts_txt2img = ScriptRunner()
+    scripts_img2img = ScriptRunner()
diff --git a/modules/ui.py b/modules/ui.py
index 963a2c61..6b30f84b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1003,12 +1003,12 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
         )
 
         with gr.Row():
-          reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary')
-          restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary')
+            reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary')
+            restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary')
 
 
         def reload_scripts():
-          modules.scripts.reload_script_body_only()
+            modules.scripts.reload_script_body_only()
 
         reload_script_bodies.click(
             fn=reload_scripts,
@@ -1018,7 +1018,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
         )
 
         def request_restart():
-          settings_interface.gradio_ref.do_restart = True
+            settings_interface.gradio_ref.do_restart = True
 
         restart_gradio.click(
             fn=request_restart,
@@ -1234,12 +1234,11 @@ for filename in sorted(os.listdir(jsdir)):
 
 
 if 'gradio_routes_templates_response' not in globals():
-  def template_response(*args, **kwargs):
-      res = gradio_routes_templates_response(*args, **kwargs)
-      res.body = res.body.replace(b'</head>', f'{javascript}</head>'.encode("utf8"))
-      res.init_headers()
-      return res
-
-  gradio_routes_templates_response = gradio.routes.templates.TemplateResponse
-  gradio.routes.templates.TemplateResponse = template_response
-
+    def template_response(*args, **kwargs):
+        res = gradio_routes_templates_response(*args, **kwargs)
+        res.body = res.body.replace(b'</head>', f'{javascript}</head>'.encode("utf8"))
+        res.init_headers()
+        return res
+
+    gradio_routes_templates_response = gradio.routes.templates.TemplateResponse
+    gradio.routes.templates.TemplateResponse = template_response
-- 
cgit v1.2.3


From a634c3226fd69486ce96df56f95f3fd63172305c Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sun, 2 Oct 2022 19:26:38 +0100
Subject: correct indent

---
 webui.py | 64 ++++++++++++++++++++++++++++++++--------------------------------
 1 file changed, 32 insertions(+), 32 deletions(-)

diff --git a/webui.py b/webui.py
index ab200045..140040ca 100644
--- a/webui.py
+++ b/webui.py
@@ -89,38 +89,38 @@ def webui():
 
     while 1:
 
-      demo = modules.ui.create_ui(
-          txt2img=wrap_gradio_gpu_call(modules.txt2img.txt2img),
-          img2img=wrap_gradio_gpu_call(modules.img2img.img2img),
-          run_extras=wrap_gradio_gpu_call(modules.extras.run_extras),
-          run_pnginfo=modules.extras.run_pnginfo,
-          run_modelmerger=modules.extras.run_modelmerger
-      )
-
-
-      demo.launch(
-          share=cmd_opts.share,
-          server_name="0.0.0.0" if cmd_opts.listen else None,
-          server_port=cmd_opts.port,
-          debug=cmd_opts.gradio_debug,
-          auth=[tuple(cred.split(':')) for cred in cmd_opts.gradio_auth.strip('"').split(',')] if cmd_opts.gradio_auth else None,
-          inbrowser=cmd_opts.autolaunch,
-          prevent_thread_lock=True
-      )
-
-      while 1:
-        time.sleep(0.5)
-        if getattr(demo,'do_restart',False):
-          time.sleep(0.5)
-          demo.close()
-          time.sleep(0.5)
-          break
-
-      print('Reloading Custom Scripts')
-      modules.scripts.reload_scripts(os.path.join(script_path, "scripts"))
-      print('Reloading modules: modules.ui')
-      importlib.reload(modules.ui)
-      print('Restarting Gradio')
+        demo = modules.ui.create_ui(
+            txt2img=wrap_gradio_gpu_call(modules.txt2img.txt2img),
+            img2img=wrap_gradio_gpu_call(modules.img2img.img2img),
+            run_extras=wrap_gradio_gpu_call(modules.extras.run_extras),
+            run_pnginfo=modules.extras.run_pnginfo,
+            run_modelmerger=modules.extras.run_modelmerger
+        )
+
+
+        demo.launch(
+            share=cmd_opts.share,
+            server_name="0.0.0.0" if cmd_opts.listen else None,
+            server_port=cmd_opts.port,
+            debug=cmd_opts.gradio_debug,
+            auth=[tuple(cred.split(':')) for cred in cmd_opts.gradio_auth.strip('"').split(',')] if cmd_opts.gradio_auth else None,
+            inbrowser=cmd_opts.autolaunch,
+            prevent_thread_lock=True
+        )
+
+        while 1:
+            time.sleep(0.5)
+                if getattr(demo,'do_restart',False):
+                    time.sleep(0.5)
+                    demo.close()
+                    time.sleep(0.5)
+                    break
+
+        print('Reloading Custom Scripts')
+        modules.scripts.reload_scripts(os.path.join(script_path, "scripts"))
+        print('Reloading modules: modules.ui')
+        importlib.reload(modules.ui)
+        print('Restarting Gradio')
 
 
 if __name__ == "__main__":
-- 
cgit v1.2.3


From c0389eb3071870240bc158263e5dfb4351ec8eba Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 2 Oct 2022 21:35:29 +0300
Subject: hello

---
 webui.py | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/webui.py b/webui.py
index 63495697..47848ba5 100644
--- a/webui.py
+++ b/webui.py
@@ -103,11 +103,11 @@ def webui():
 
         while 1:
             time.sleep(0.5)
-                if getattr(demo,'do_restart',False):
-                    time.sleep(0.5)
-                    demo.close()
-                    time.sleep(0.5)
-                    break
+            if getattr(demo, 'do_restart', False):
+                time.sleep(0.5)
+                demo.close()
+                time.sleep(0.5)
+                break
 
         print('Reloading Custom Scripts')
         modules.scripts.reload_scripts(os.path.join(script_path, "scripts"))
-- 
cgit v1.2.3


From 2ef69df9a7c7b6793401f29ced71fb8a781fad4c Mon Sep 17 00:00:00 2001
From: Jocke <joakim.lovgren@protonmail.com>
Date: Sun, 2 Oct 2022 16:10:41 +0200
Subject: Prevent upscaling when None is selected for SD upscale

---
 scripts/sd_upscale.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/scripts/sd_upscale.py b/scripts/sd_upscale.py
index 2653e2d4..cb37ff7e 100644
--- a/scripts/sd_upscale.py
+++ b/scripts/sd_upscale.py
@@ -34,7 +34,11 @@ class Script(scripts.Script):
         seed = p.seed
 
         init_img = p.init_images[0]
-        img = upscaler.scaler.upscale(init_img, 2, upscaler.data_path)
+        
+        if(upscaler.name != "None"): 
+            img = upscaler.scaler.upscale(init_img, 2, upscaler.data_path)
+        else:
+            img = init_img
 
         devices.torch_gc()
 
-- 
cgit v1.2.3


From 91f327f22bb2feb780c424c74723cc0629dc34a1 Mon Sep 17 00:00:00 2001
From: Lopyter <git@lopyter.dev>
Date: Sun, 2 Oct 2022 18:15:31 +0200
Subject: make save to dirs optional for imgs saved from ui

---
 modules/shared.py | 1 +
 modules/ui.py     | 2 +-
 2 files changed, 2 insertions(+), 1 deletion(-)

diff --git a/modules/shared.py b/modules/shared.py
index 1bf7a6c1..785e7af6 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -173,6 +173,7 @@ options_templates.update(options_section(('saving-to-dirs', "Saving to a directo
     "grid_save_to_dirs": OptionInfo(False, "Save grids to subdirectory"),
     "directories_filename_pattern": OptionInfo("", "Directory name pattern"),
     "directories_max_prompt_words": OptionInfo(8, "Max prompt words", gr.Slider, {"minimum": 1, "maximum": 20, "step": 1}),
+    "use_save_to_dirs_for_ui": OptionInfo(False, "Use \"Save images to a subdirectory\" option for images saved from UI"),
 }))
 
 options_templates.update(options_section(('upscaling', "Upscaling"), {
diff --git a/modules/ui.py b/modules/ui.py
index 78a15d83..8912deff 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -113,7 +113,7 @@ def save_files(js_data, images, index):
 
     p = MyObject(data)
     path = opts.outdir_save
-    save_to_dirs = opts.save_to_dirs
+    save_to_dirs = opts.use_save_to_dirs_for_ui
 
     if save_to_dirs:
         dirname = apply_filename_pattern(opts.directories_filename_pattern or "[prompt_words]", p, p.seed, p.prompt)
-- 
cgit v1.2.3


From c4445225f79f1c57afe52358ff4b205864eb7aac Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 2 Oct 2022 21:50:14 +0300
Subject: change wording for options

---
 modules/shared.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/modules/shared.py b/modules/shared.py
index 785e7af6..7246eadc 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -170,10 +170,10 @@ options_templates.update(options_section(('saving-paths', "Paths for saving"), {
 
 options_templates.update(options_section(('saving-to-dirs', "Saving to a directory"), {
     "save_to_dirs": OptionInfo(False, "Save images to a subdirectory"),
-    "grid_save_to_dirs": OptionInfo(False, "Save grids to subdirectory"),
+    "grid_save_to_dirs": OptionInfo(False, "Save grids to a subdirectory"),
+    "use_save_to_dirs_for_ui": OptionInfo(False, "When using \"Save\" button, save images to a subdirectory"),
     "directories_filename_pattern": OptionInfo("", "Directory name pattern"),
-    "directories_max_prompt_words": OptionInfo(8, "Max prompt words", gr.Slider, {"minimum": 1, "maximum": 20, "step": 1}),
-    "use_save_to_dirs_for_ui": OptionInfo(False, "Use \"Save images to a subdirectory\" option for images saved from UI"),
+    "directories_max_prompt_words": OptionInfo(8, "Max prompt words for [prompt_words] pattern", gr.Slider, {"minimum": 1, "maximum": 20, "step": 1}),
 }))
 
 options_templates.update(options_section(('upscaling', "Upscaling"), {
-- 
cgit v1.2.3


From c7543d4940da672d970124ae8f2fec9de7bdc1da Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 2 Oct 2022 22:41:21 +0300
Subject: preprocessing for textual inversion added

---
 modules/interrogate.py                         |  1 +
 modules/textual_inversion/preprocess.py        | 75 ++++++++++++++++++++++++++
 modules/textual_inversion/textual_inversion.py |  1 +
 modules/textual_inversion/ui.py                | 14 +++--
 modules/ui.py                                  | 36 +++++++++++++
 5 files changed, 124 insertions(+), 3 deletions(-)
 create mode 100644 modules/textual_inversion/preprocess.py

diff --git a/modules/interrogate.py b/modules/interrogate.py
index f62a4745..eed87144 100644
--- a/modules/interrogate.py
+++ b/modules/interrogate.py
@@ -21,6 +21,7 @@ Category = namedtuple("Category", ["name", "topn", "items"])
 
 re_topn = re.compile(r"\.top(\d+)\.")
 
+
 class InterrogateModels:
     blip_model = None
     clip_model = None
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
new file mode 100644
index 00000000..209e928f
--- /dev/null
+++ b/modules/textual_inversion/preprocess.py
@@ -0,0 +1,75 @@
+import os
+from PIL import Image, ImageOps
+import tqdm
+
+from modules import shared, images
+
+
+def preprocess(process_src, process_dst, process_flip, process_split, process_caption):
+    size = 512
+    src = os.path.abspath(process_src)
+    dst = os.path.abspath(process_dst)
+
+    assert src != dst, 'same directory specified as source and desitnation'
+
+    os.makedirs(dst, exist_ok=True)
+
+    files = os.listdir(src)
+
+    shared.state.textinfo = "Preprocessing..."
+    shared.state.job_count = len(files)
+
+    if process_caption:
+        shared.interrogator.load()
+
+    def save_pic_with_caption(image, index):
+        if process_caption:
+            caption = "-" + shared.interrogator.generate_caption(image)
+        else:
+            caption = ""
+
+        image.save(os.path.join(dst, f"{index:05}-{subindex[0]}{caption}.png"))
+        subindex[0] += 1
+
+    def save_pic(image, index):
+        save_pic_with_caption(image, index)
+
+        if process_flip:
+            save_pic_with_caption(ImageOps.mirror(image), index)
+
+    for index, imagefile in enumerate(tqdm.tqdm(files)):
+        subindex = [0]
+        filename = os.path.join(src, imagefile)
+        img = Image.open(filename).convert("RGB")
+
+        if shared.state.interrupted:
+            break
+
+        ratio = img.height / img.width
+        is_tall = ratio > 1.35
+        is_wide = ratio < 1 / 1.35
+
+        if process_split and is_tall:
+            img = img.resize((size, size * img.height // img.width))
+
+            top = img.crop((0, 0, size, size))
+            save_pic(top, index)
+
+            bot = img.crop((0, img.height - size, size, img.height))
+            save_pic(bot, index)
+        elif process_split and is_wide:
+            img = img.resize((size * img.width // img.height, size))
+
+            left = img.crop((0, 0, size, size))
+            save_pic(left, index)
+
+            right = img.crop((img.width - size, 0, img.width, size))
+            save_pic(right, index)
+        else:
+            img = images.resize_image(1, img, size, size)
+            save_pic(img, index)
+
+        shared.state.nextjob()
+
+    if process_caption:
+        shared.interrogator.send_blip_to_ram()
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 1183aab7..d4e250d8 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -7,6 +7,7 @@ import tqdm
 import html
 import datetime
 
+
 from modules import shared, devices, sd_hijack, processing, sd_models
 import modules.textual_inversion.dataset
 
diff --git a/modules/textual_inversion/ui.py b/modules/textual_inversion/ui.py
index 633037d8..f19ac5e0 100644
--- a/modules/textual_inversion/ui.py
+++ b/modules/textual_inversion/ui.py
@@ -2,24 +2,31 @@ import html
 
 import gradio as gr
 
-import modules.textual_inversion.textual_inversion as ti
+import modules.textual_inversion.textual_inversion
+import modules.textual_inversion.preprocess
 from modules import sd_hijack, shared
 
 
 def create_embedding(name, initialization_text, nvpt):
-    filename = ti.create_embedding(name, nvpt, init_text=initialization_text)
+    filename = modules.textual_inversion.textual_inversion.create_embedding(name, nvpt, init_text=initialization_text)
 
     sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings()
 
     return gr.Dropdown.update(choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())), f"Created: {filename}", ""
 
 
+def preprocess(*args):
+    modules.textual_inversion.preprocess.preprocess(*args)
+
+    return "Preprocessing finished.", ""
+
+
 def train_embedding(*args):
 
     try:
         sd_hijack.undo_optimizations()
 
-        embedding, filename = ti.train_embedding(*args)
+        embedding, filename = modules.textual_inversion.textual_inversion.train_embedding(*args)
 
         res = f"""
 Training {'interrupted' if shared.state.interrupted else 'finished'} at {embedding.step} steps.
@@ -30,3 +37,4 @@ Embedding saved to {html.escape(filename)}
         raise
     finally:
         sd_hijack.apply_optimizations()
+
diff --git a/modules/ui.py b/modules/ui.py
index 8912deff..e7bde53b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -961,6 +961,8 @@ def create_ui(wrap_gradio_gpu_call):
         with gr.Row().style(equal_height=False):
             with gr.Column():
                 with gr.Group():
+                    gr.HTML(value="<p style='margin-bottom: 0.7em'>See <b><a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\">wiki</a></b> for detailed explanation.</p>")
+
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Create a new embedding</p>")
 
                     new_embedding_name = gr.Textbox(label="Name")
@@ -974,6 +976,24 @@ def create_ui(wrap_gradio_gpu_call):
                         with gr.Column():
                             create_embedding = gr.Button(value="Create", variant='primary')
 
+                with gr.Group():
+                    gr.HTML(value="<p style='margin-bottom: 0.7em'>Preprocess images</p>")
+
+                    process_src = gr.Textbox(label='Source directory')
+                    process_dst = gr.Textbox(label='Destination directory')
+
+                    with gr.Row():
+                        process_flip = gr.Checkbox(label='Flip')
+                        process_split = gr.Checkbox(label='Split into two')
+                        process_caption = gr.Checkbox(label='Add caption')
+
+                    with gr.Row():
+                        with gr.Column(scale=3):
+                            gr.HTML(value="")
+
+                        with gr.Column():
+                            run_preprocess = gr.Button(value="Preprocess", variant='primary')
+
                 with gr.Group():
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding; must specify a directory with a set of 512x512 images</p>")
                     train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
@@ -1018,6 +1038,22 @@ def create_ui(wrap_gradio_gpu_call):
             ]
         )
 
+        run_preprocess.click(
+            fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]),
+            _js="start_training_textual_inversion",
+            inputs=[
+                process_src,
+                process_dst,
+                process_flip,
+                process_split,
+                process_caption,
+            ],
+            outputs=[
+                ti_output,
+                ti_outcome,
+            ],
+        )
+
         train_embedding.click(
             fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.train_embedding, extra_outputs=[gr.update()]),
             _js="start_training_textual_inversion",
-- 
cgit v1.2.3


From 6785331e22d6a488fbf5905fab56d7fec867e038 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 2 Oct 2022 22:59:01 +0300
Subject: keep textual inversion dataset latents in CPU memory to save a bit of
 VRAM

---
 modules/textual_inversion/dataset.py           | 2 ++
 modules/textual_inversion/textual_inversion.py | 3 +++
 modules/ui.py                                  | 4 ++--
 3 files changed, 7 insertions(+), 2 deletions(-)

diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index 7e134a08..e8394ff6 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -8,6 +8,7 @@ from torchvision import transforms
 
 import random
 import tqdm
+from modules import devices
 
 
 class PersonalizedBase(Dataset):
@@ -47,6 +48,7 @@ class PersonalizedBase(Dataset):
             torchdata = torch.moveaxis(torchdata, 2, 0)
 
             init_latent = model.get_first_stage_encoding(model.encode_first_stage(torchdata.unsqueeze(dim=0))).squeeze()
+            init_latent = init_latent.to(devices.cpu)
 
             self.dataset.append((init_latent, filename_tokens))
 
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index d4e250d8..8686f534 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -212,7 +212,10 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
 
         with torch.autocast("cuda"):
             c = cond_model([text])
+
+            x = x.to(devices.device)
             loss = shared.sd_model(x.unsqueeze(0), c)[0]
+            del x
 
             losses[embedding.step % losses.shape[0]] = loss.item()
 
diff --git a/modules/ui.py b/modules/ui.py
index e7bde53b..d9d02ece 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1002,8 +1002,8 @@ def create_ui(wrap_gradio_gpu_call):
                     log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")
                     template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"))
                     steps = gr.Number(label='Max steps', value=100000, precision=0)
-                    create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=1000, precision=0)
-                    save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=1000, precision=0)
+                    create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0)
+                    save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0)
 
                     with gr.Row():
                         with gr.Column(scale=2):
-- 
cgit v1.2.3


From 166283653cfe7521a422c91e8fb801f3ecb4adc8 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 2 Oct 2022 23:18:13 +0300
Subject: remove LDSR warning

---
 modules/paths.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/modules/paths.py b/modules/paths.py
index ceb80417..606f7d66 100644
--- a/modules/paths.py
+++ b/modules/paths.py
@@ -20,7 +20,6 @@ path_dirs = [
     (os.path.join(sd_path, '../taming-transformers'), 'taming', 'Taming Transformers', []),
     (os.path.join(sd_path, '../CodeFormer'), 'inference_codeformer.py', 'CodeFormer', []),
     (os.path.join(sd_path, '../BLIP'), 'models/blip.py', 'BLIP', []),
-    (os.path.join(sd_path, '../latent-diffusion'), 'LDSR.py', 'LDSR', []),
     (os.path.join(sd_path, '../k-diffusion'), 'k_diffusion/sampling.py', 'k_diffusion', ["atstart"]),
 ]
 
-- 
cgit v1.2.3


From 4c2eccf8e96825333ed400f8a8a2be78141ed8ec Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 2 Oct 2022 23:22:48 +0300
Subject: credit Rinon Gal

---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index 15e224e8..ec3d7532 100644
--- a/README.md
+++ b/README.md
@@ -113,6 +113,7 @@ The documentation was moved from this README over to the project's [wiki](https:
 - LDSR - https://github.com/Hafiidz/latent-diffusion
 - Ideas for optimizations - https://github.com/basujindal/stable-diffusion
 - Doggettx - Cross Attention layer optimization - https://github.com/Doggettx/stable-diffusion, original idea for prompt editing.
+- Rinon Gal - Textual Inversion - https://github.com/rinongal/textual_inversion (we're not using his code, but we are using his ideas).
 - Idea for SD upscale - https://github.com/jquesnelle/txt2imghd
 - Noise generation for outpainting mk2 - https://github.com/parlance-zz/g-diffuser-bot
 - CLIP interrogator idea and borrowing some code - https://github.com/pharmapsychotic/clip-interrogator
-- 
cgit v1.2.3


From 138662734c25dab4e73e632b7eaff9ad9c0ce2b4 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 3 Oct 2022 07:57:59 +0300
Subject: use dropdown instead of radio for img2img upscaler selection

---
 modules/shared.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/shared.py b/modules/shared.py
index 7246eadc..2a599e9c 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -183,7 +183,7 @@ options_templates.update(options_section(('upscaling', "Upscaling"), {
     "SWIN_tile": OptionInfo(192, "Tile size for all SwinIR.", gr.Slider, {"minimum": 16, "maximum": 512, "step": 16}),
     "SWIN_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for SwinIR. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}),
     "ldsr_steps": OptionInfo(100, "LDSR processing steps. Lower = faster", gr.Slider, {"minimum": 1, "maximum": 200, "step": 1}),
-    "upscaler_for_img2img": OptionInfo(None, "Upscaler for img2img", gr.Radio, lambda: {"choices": [x.name for x in sd_upscalers]}),
+    "upscaler_for_img2img": OptionInfo(None, "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in sd_upscalers]}),
 }))
 
 options_templates.update(options_section(('face-restoration', "Face restoration"), {
-- 
cgit v1.2.3


From e615d4f9d101e2712c7c2d0e3e8feb19cb430c74 Mon Sep 17 00:00:00 2001
From: Hanusz Leszek <leszek.hanusz@gmail.com>
Date: Sun, 2 Oct 2022 21:08:23 +0200
Subject: Convert folder icon surrogate pair to valid utf8

---
 javascript/hints.js | 2 +-
 modules/ui.py       | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/javascript/hints.js b/javascript/hints.js
index 84694eeb..e72e9338 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -15,7 +15,7 @@ titles = {
     "\u267b\ufe0f": "Reuse seed from last generation, mostly useful if it was randomed",
     "\u{1f3a8}": "Add a random artist to the prompt.",
     "\u2199\ufe0f": "Read generation parameters from prompt into user interface.",
-    "\uD83D\uDCC2": "Open images output directory",
+    "\u{1f4c2}": "Open images output directory",
 
     "Inpaint a part of image": "Draw a mask over an image, and the script will regenerate the masked area with content according to prompt",
     "SD upscale": "Upscale image normally, split result into tiles, improve each tile using img2img, merge whole image back",
diff --git a/modules/ui.py b/modules/ui.py
index d9d02ece..16432151 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -69,7 +69,7 @@ random_symbol = '\U0001f3b2\ufe0f'  # 🎲️
 reuse_symbol = '\u267b\ufe0f'  # ♻️
 art_symbol = '\U0001f3a8'  # 🎨
 paste_symbol = '\u2199\ufe0f'  # ↙
-folder_symbol = '\uD83D\uDCC2'
+folder_symbol = '\U0001f4c2'  # 📂
 
 def plaintext_to_html(text):
     text = "<p>" + "<br>\n".join([f"{html.escape(x)}" for x in text.split('\n')]) + "</p>"
-- 
cgit v1.2.3


From 34c638142eaa57f89b86545ba3c72085036398bb Mon Sep 17 00:00:00 2001
From: hentailord85ez <112723046+hentailord85ez@users.noreply.github.com>
Date: Fri, 30 Sep 2022 22:38:14 +0100
Subject: Fixed when eta = 0

Unexpected behavior when using eta = 0 in something like XY, but your default eta was set to something not 0.
---
 modules/sd_samplers.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index 9316875a..dbf570d2 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -127,7 +127,7 @@ class VanillaStableDiffusionSampler:
         return res
 
     def initialize(self, p):
-        self.eta = p.eta or opts.eta_ddim
+        self.eta = p.eta if p.eta is not None else opts.eta_ddim
 
         for fieldname in ['p_sample_ddim', 'p_sample_plms']:
             if hasattr(self.sampler, fieldname):
-- 
cgit v1.2.3


From 36ea4ac0f5844e5c8dec124edbdb714ccdd6013c Mon Sep 17 00:00:00 2001
From: RnDMonkey <ryandrutledge@gmail.com>
Date: Sun, 2 Oct 2022 22:21:16 -0700
Subject: moved no-style return outside join function

---
 modules/images.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/images.py b/modules/images.py
index bba55158..1a046aca 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -315,7 +315,7 @@ def apply_filename_pattern(x, p, seed, prompt):
         #currently disabled if using the save button, will work otherwise 
         # if enabled it will cause a bug because styles is not included in the save_files data dictionary
         if hasattr(p, "styles"):
-            x = x.replace("[styles]", sanitize_filename_part(", ".join([x for x in p.styles if not x == "None"] or "None"), replace_spaces=False))
+            x = x.replace("[styles]", sanitize_filename_part(", ".join([x for x in p.styles if not x == "None"]) or "None", replace_spaces=False))
 
         x = x.replace("[sampler]", sanitize_filename_part(sd_samplers.samplers[p.sampler_index].name, replace_spaces=False))
 
-- 
cgit v1.2.3


From 6491b09c24ea77f1f69990ea80a216f9ce319589 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 3 Oct 2022 08:53:52 +0300
Subject: use existing function for gfpgan

---
 modules/gfpgan_model.py | 6 +-----
 1 file changed, 1 insertion(+), 5 deletions(-)

diff --git a/modules/gfpgan_model.py b/modules/gfpgan_model.py
index bb30d733..dd3fbcab 100644
--- a/modules/gfpgan_model.py
+++ b/modules/gfpgan_model.py
@@ -97,11 +97,7 @@ def setup_model(dirname):
                 return "GFPGAN"
 
             def restore(self, np_image):
-                np_image_bgr = np_image[:, :, ::-1]
-                cropped_faces, restored_faces, gfpgan_output_bgr = gfpgann().enhance(np_image_bgr, has_aligned=False, only_center_face=False, paste_back=True)
-                np_image = gfpgan_output_bgr[:, :, ::-1]
-
-                return np_image
+                return gfpgan_fix_faces(np_image)
 
         shared.face_restorers.append(FaceRestorerGFPGAN())
     except Exception:
-- 
cgit v1.2.3


From 43a74fa595003321200a40bd2431e56c245e75ed Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 3 Oct 2022 11:48:19 +0300
Subject: batch processing for img2img with an empty output directory, by
 request

---
 modules/img2img.py | 7 +++++--
 modules/ui.py      | 2 +-
 2 files changed, 6 insertions(+), 3 deletions(-)

diff --git a/modules/img2img.py b/modules/img2img.py
index f4455c90..2ff8e261 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -23,8 +23,10 @@ def process_batch(p, input_dir, output_dir, args):
 
     print(f"Will process {len(images)} images, creating {p.n_iter * p.batch_size} new images for each.")
 
+    save_normally = output_dir == ''
+
     p.do_not_save_grid = True
-    p.do_not_save_samples = True
+    p.do_not_save_samples = not save_normally
 
     state.job_count = len(images) * p.n_iter
 
@@ -48,7 +50,8 @@ def process_batch(p, input_dir, output_dir, args):
                 left, right = os.path.splitext(filename)
                 filename = f"{left}-{n}{right}"
 
-            processed_image.save(os.path.join(output_dir, filename))
+            if not save_normally:
+                processed_image.save(os.path.join(output_dir, filename))
 
 
 def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, init_img, init_img_with_mask, init_img_inpaint, init_mask_inpaint, mask_mode, steps: int, sampler_index: int, mask_blur: int, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, *args):
diff --git a/modules/ui.py b/modules/ui.py
index 16432151..55f7aa95 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -658,7 +658,7 @@ def create_ui(wrap_gradio_gpu_call):
 
                     with gr.TabItem('Batch img2img', id='batch'):
                         hidden = '<br>Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else ''
-                        gr.HTML(f"<p class=\"text-gray-500\">Process images in a directory on the same machine where the server is running.{hidden}</p>")
+                        gr.HTML(f"<p class=\"text-gray-500\">Process images in a directory on the same machine where the server is running.<br>Use an empty output directory to save pictures normally instead of writing to the output directory.{hidden}</p>")
                         img2img_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs)
                         img2img_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs)
 
-- 
cgit v1.2.3


From 2865ef4b9ab16d56326cc805541bebcf01d099bc Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 3 Oct 2022 13:10:03 +0300
Subject: fix broken date in TI

---
 modules/textual_inversion/textual_inversion.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 8686f534..cd9f3498 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -164,7 +164,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
 
     filename = os.path.join(shared.cmd_opts.embeddings_dir, f'{embedding_name}.pt')
 
-    log_directory = os.path.join(log_directory, datetime.datetime.now().strftime("%Y-%d-%m"), embedding_name)
+    log_directory = os.path.join(log_directory, datetime.datetime.now().strftime("%Y-%m-%d"), embedding_name)
 
     if save_embedding_every > 0:
         embedding_dir = os.path.join(log_directory, "embeddings")
-- 
cgit v1.2.3


From 2a7f48cdb8dcf9acb02610cccae0d1ee5d260bc2 Mon Sep 17 00:00:00 2001
From: fuzzytent <fuzzy.tent6960@fastmail.com>
Date: Fri, 30 Sep 2022 16:02:16 +0200
Subject: Improve styling of gallery items, particularly in dark mode

---
 style.css | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/style.css b/style.css
index 9709c4ee..e11316b9 100644
--- a/style.css
+++ b/style.css
@@ -403,3 +403,7 @@ input[type="range"]{
 .red {
 	color: red;
 }
+
+.gallery-item {
+    --tw-bg-opacity: 0 !important;
+}
-- 
cgit v1.2.3


From 5ef0baf5eaec7f21a1666af424405cbee19f3764 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 4 Oct 2022 08:52:11 +0300
Subject: add support for gelbooru tags in filenames for textual inversion

---
 modules/textual_inversion/dataset.py    | 7 +++++--
 modules/textual_inversion/preprocess.py | 4 +++-
 2 files changed, 8 insertions(+), 3 deletions(-)

diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index e8394ff6..7c44ea5b 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -9,6 +9,9 @@ from torchvision import transforms
 import random
 import tqdm
 from modules import devices
+import re
+
+re_tag = re.compile(r"[a-zA-Z][_\w\d()]+")
 
 
 class PersonalizedBase(Dataset):
@@ -38,8 +41,8 @@ class PersonalizedBase(Dataset):
             image = image.resize((self.width, self.height), PIL.Image.BICUBIC)
 
             filename = os.path.basename(path)
-            filename_tokens = os.path.splitext(filename)[0].replace('_', '-').replace(' ', '-').split('-')
-            filename_tokens = [token for token in filename_tokens if token.isalpha()]
+            filename_tokens = os.path.splitext(filename)[0]
+            filename_tokens = re_tag.findall(filename_tokens)
 
             npimage = np.array(image).astype(np.uint8)
             npimage = (npimage / 127.5 - 1.0).astype(np.float32)
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index 209e928f..f545a993 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -26,7 +26,9 @@ def preprocess(process_src, process_dst, process_flip, process_split, process_ca
         if process_caption:
             caption = "-" + shared.interrogator.generate_caption(image)
         else:
-            caption = ""
+            caption = filename
+            caption = os.path.splitext(caption)[0]
+            caption = os.path.basename(caption)
 
         image.save(os.path.join(dst, f"{index:05}-{subindex[0]}{caption}.png"))
         subindex[0] += 1
-- 
cgit v1.2.3


From 1c5604791da7e57f40880698666b6617a1754c65 Mon Sep 17 00:00:00 2001
From: DoTheSneedful <DoTheSneedful@outlook.com>
Date: Mon, 3 Oct 2022 22:20:09 -0400
Subject: Add a prompt order option to XY plot script

---
 scripts/xy_grid.py | 40 ++++++++++++++++++++++++++++++++++++++--
 1 file changed, 38 insertions(+), 2 deletions(-)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 146663b0..044c30e6 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -1,5 +1,6 @@
 from collections import namedtuple
 from copy import copy
+from itertools import permutations
 import random
 
 from PIL import Image
@@ -28,6 +29,27 @@ def apply_prompt(p, x, xs):
     p.prompt = p.prompt.replace(xs[0], x)
     p.negative_prompt = p.negative_prompt.replace(xs[0], x)
 
+def apply_order(p, x, xs):
+    token_order = []
+
+    # Initally grab the tokens from the prompt so they can be later be replaced in order of earliest seen in the prompt
+    for token in x:
+        token_order.append((p.prompt.find(token), token))
+
+    token_order.sort(key=lambda t: t[0])
+
+    search_from_pos = 0
+    for idx, token in enumerate(x):
+        original_pos, old_token = token_order[idx]
+
+        # Get position of the token again as it will likely change as tokens are being replaced
+        pos = p.prompt.find(old_token)
+        if original_pos >= 0:
+            # Avoid trying to replace what was just replaced by searching later in the prompt string
+            p.prompt = p.prompt[0:search_from_pos] + p.prompt[search_from_pos:].replace(old_token, token, 1)
+
+        search_from_pos = pos + len(token)
+
 
 samplers_dict = {}
 for i, sampler in enumerate(modules.sd_samplers.samplers):
@@ -60,7 +82,8 @@ def format_value_add_label(p, opt, x):
 def format_value(p, opt, x):
     if type(x) == float:
         x = round(x, 8)
-
+    if type(x) == type(list()):
+        x = str(x)
     return x
 
 def do_nothing(p, x, xs):
@@ -89,6 +112,7 @@ axis_options = [
     AxisOption("Sigma max", float, apply_field("s_tmax"), format_value_add_label),
     AxisOption("Sigma noise", float, apply_field("s_noise"), format_value_add_label),
     AxisOption("Eta", float, apply_field("eta"), format_value_add_label),
+    AxisOption("Prompt order", type(list()), apply_order, format_value),
     AxisOptionImg2Img("Denoising", float, apply_field("denoising_strength"), format_value_add_label),  # as it is now all AxisOptionImg2Img items must go after AxisOption ones
 ]
 
@@ -159,7 +183,11 @@ class Script(scripts.Script):
             if opt.label == 'Nothing':
                 return [0]
 
-            valslist = [x.strip() for x in vals.split(",")]
+            if opt.type == type(list()):
+                valslist = [x for x in vals]
+            else:
+                valslist = [x.strip() for x in vals.split(",")]
+
 
             if opt.type == int:
                 valslist_ext = []
@@ -212,9 +240,17 @@ class Script(scripts.Script):
             return valslist
 
         x_opt = axis_options[x_type]
+
+        if x_opt.label == "Prompt order":
+            x_values = list(permutations([x.strip() for x in x_values.split(",")]))
+
         xs = process_axis(x_opt, x_values)
 
         y_opt = axis_options[y_type]
+
+        if y_opt.label == "Prompt order":
+            y_values = list(permutations([y.strip() for y in y_values.split(",")]))
+
         ys = process_axis(y_opt, y_values)
 
         def fix_axis_seeds(axis_opt, axis_list):
-- 
cgit v1.2.3


From 1a6d40db35656083d5bf9d3a3430b45fda4e85eb Mon Sep 17 00:00:00 2001
From: DoTheSneedful <DoTheSneedful@outlook.com>
Date: Tue, 4 Oct 2022 00:18:15 -0400
Subject: Fix token ordering in prompt order XY plot

---
 scripts/xy_grid.py | 13 +++++--------
 1 file changed, 5 insertions(+), 8 deletions(-)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 044c30e6..5bcd3921 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -32,24 +32,21 @@ def apply_prompt(p, x, xs):
 def apply_order(p, x, xs):
     token_order = []
 
-    # Initally grab the tokens from the prompt so they can be later be replaced in order of earliest seen in the prompt
+    # Initally grab the tokens from the prompt so they can be be replaced in order of earliest seen
     for token in x:
         token_order.append((p.prompt.find(token), token))
 
     token_order.sort(key=lambda t: t[0])
 
     search_from_pos = 0
-    for idx, token in enumerate(x):
-        original_pos, old_token = token_order[idx]
-
+    for idx, (original_pos, old_token) in enumerate(token_order):
         # Get position of the token again as it will likely change as tokens are being replaced
-        pos = p.prompt.find(old_token)
+        pos = search_from_pos + p.prompt[search_from_pos:].find(old_token)
         if original_pos >= 0:
             # Avoid trying to replace what was just replaced by searching later in the prompt string
-            p.prompt = p.prompt[0:search_from_pos] + p.prompt[search_from_pos:].replace(old_token, token, 1)
-
-        search_from_pos = pos + len(token)
+            p.prompt = p.prompt[0:search_from_pos] + p.prompt[search_from_pos:].replace(old_token, x[idx], 1)
 
+        search_from_pos = pos + len(x[idx])
 
 samplers_dict = {}
 for i, sampler in enumerate(modules.sd_samplers.samplers):
-- 
cgit v1.2.3


From 56371153b545e3a43c3a5f206264019af361f3af Mon Sep 17 00:00:00 2001
From: DoTheSneedful <DoTheSneedful@outlook.com>
Date: Tue, 4 Oct 2022 01:07:36 -0400
Subject: XY plot prompt order simplify logic

---
 scripts/xy_grid.py | 24 +++++++++++++++---------
 1 file changed, 15 insertions(+), 9 deletions(-)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 5bcd3921..7def47f5 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -38,15 +38,21 @@ def apply_order(p, x, xs):
 
     token_order.sort(key=lambda t: t[0])
 
-    search_from_pos = 0
-    for idx, (original_pos, old_token) in enumerate(token_order):
-        # Get position of the token again as it will likely change as tokens are being replaced
-        pos = search_from_pos + p.prompt[search_from_pos:].find(old_token)
-        if original_pos >= 0:
-            # Avoid trying to replace what was just replaced by searching later in the prompt string
-            p.prompt = p.prompt[0:search_from_pos] + p.prompt[search_from_pos:].replace(old_token, x[idx], 1)
-
-        search_from_pos = pos + len(x[idx])
+    prompt_parts = []
+
+    # Split the prompt up, taking out the tokens
+    for _, token in token_order:
+        n = p.prompt.find(token)
+        prompt_parts.append(p.prompt[0:n])
+        p.prompt = p.prompt[n + len(token):]
+
+    # Rebuild the prompt with the tokens in the order we want
+    prompt_tmp = ""
+    for idx, part in enumerate(prompt_parts):
+        prompt_tmp += part
+        prompt_tmp += x[idx]
+    p.prompt = prompt_tmp + p.prompt
+    
 
 samplers_dict = {}
 for i, sampler in enumerate(modules.sd_samplers.samplers):
-- 
cgit v1.2.3


From 556c36b9607e3f4eacdddc85f8e7a78b29476ea7 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 4 Oct 2022 09:18:00 +0300
Subject: add hint, refactor code for #1607

---
 javascript/hints.js |  1 +
 scripts/xy_grid.py  | 35 ++++++++++++++++++-----------------
 2 files changed, 19 insertions(+), 17 deletions(-)

diff --git a/javascript/hints.js b/javascript/hints.js
index e72e9338..8adcd983 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -47,6 +47,7 @@ titles = {
     "Custom code": "Run Python code. Advanced user only. Must run program with --allow-code for this to work",
 
     "Prompt S/R": "Separate a list of words with commas, and the first word will be used as a keyword: script will search for this word in the prompt, and replace it with others",
+    "Prompt order": "Separate a list of words with commas, and the script will make a variation of prompt with those words for their every possible order",
 
     "Tiling": "Produce an image that can be tiled.",
     "Tile overlap": "For SD upscale, how much overlap in pixels should there be between tiles. Tiles overlap so that when they are merged back into one picture, there is no clearly visible seam.",
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 7def47f5..1237e754 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -29,10 +29,11 @@ def apply_prompt(p, x, xs):
     p.prompt = p.prompt.replace(xs[0], x)
     p.negative_prompt = p.negative_prompt.replace(xs[0], x)
 
+
 def apply_order(p, x, xs):
     token_order = []
 
-    # Initally grab the tokens from the prompt so they can be be replaced in order of earliest seen
+    # Initally grab the tokens from the prompt, so they can be replaced in order of earliest seen
     for token in x:
         token_order.append((p.prompt.find(token), token))
 
@@ -85,17 +86,26 @@ def format_value_add_label(p, opt, x):
 def format_value(p, opt, x):
     if type(x) == float:
         x = round(x, 8)
-    if type(x) == type(list()):
-        x = str(x)
     return x
 
+
+def format_value_join_list(p, opt, x):
+    return ", ".join(x)
+
+
 def do_nothing(p, x, xs):
     pass
 
+
 def format_nothing(p, opt, x):
     return ""
 
 
+def str_permutations(x):
+    """dummy function for specifying it in AxisOption's type when you want to get a list of permutations"""
+    return x
+
+
 AxisOption = namedtuple("AxisOption", ["label", "type", "apply", "format_value"])
 AxisOptionImg2Img = namedtuple("AxisOptionImg2Img", ["label", "type", "apply", "format_value"])
 
@@ -108,6 +118,7 @@ axis_options = [
     AxisOption("Steps", int, apply_field("steps"), format_value_add_label),
     AxisOption("CFG Scale", float, apply_field("cfg_scale"), format_value_add_label),
     AxisOption("Prompt S/R", str, apply_prompt, format_value),
+    AxisOption("Prompt order", str_permutations, apply_order, format_value_join_list),
     AxisOption("Sampler", str, apply_sampler, format_value),
     AxisOption("Checkpoint name", str, apply_checkpoint, format_value),
     AxisOption("Sigma Churn", float, apply_field("s_churn"), format_value_add_label),
@@ -115,7 +126,6 @@ axis_options = [
     AxisOption("Sigma max", float, apply_field("s_tmax"), format_value_add_label),
     AxisOption("Sigma noise", float, apply_field("s_noise"), format_value_add_label),
     AxisOption("Eta", float, apply_field("eta"), format_value_add_label),
-    AxisOption("Prompt order", type(list()), apply_order, format_value),
     AxisOptionImg2Img("Denoising", float, apply_field("denoising_strength"), format_value_add_label),  # as it is now all AxisOptionImg2Img items must go after AxisOption ones
 ]
 
@@ -158,6 +168,7 @@ re_range_float = re.compile(r"\s*([+-]?\s*\d+(?:.\d*)?)\s*-\s*([+-]?\s*\d+(?:.\d
 re_range_count = re.compile(r"\s*([+-]?\s*\d+)\s*-\s*([+-]?\s*\d+)(?:\s*\[(\d+)\s*\])?\s*")
 re_range_count_float = re.compile(r"\s*([+-]?\s*\d+(?:.\d*)?)\s*-\s*([+-]?\s*\d+(?:.\d*)?)(?:\s*\[(\d+(?:.\d*)?)\s*\])?\s*")
 
+
 class Script(scripts.Script):
     def title(self):
         return "X/Y plot"
@@ -186,11 +197,7 @@ class Script(scripts.Script):
             if opt.label == 'Nothing':
                 return [0]
 
-            if opt.type == type(list()):
-                valslist = [x for x in vals]
-            else:
-                valslist = [x.strip() for x in vals.split(",")]
-
+            valslist = [x.strip() for x in vals.split(",")]
 
             if opt.type == int:
                 valslist_ext = []
@@ -237,23 +244,17 @@ class Script(scripts.Script):
                         valslist_ext.append(val)
 
                 valslist = valslist_ext
+            elif opt.type == str_permutations:
+                valslist = list(permutations(valslist))
 
             valslist = [opt.type(x) for x in valslist]
 
             return valslist
 
         x_opt = axis_options[x_type]
-
-        if x_opt.label == "Prompt order":
-            x_values = list(permutations([x.strip() for x in x_values.split(",")]))
-
         xs = process_axis(x_opt, x_values)
 
         y_opt = axis_options[y_type]
-
-        if y_opt.label == "Prompt order":
-            y_values = list(permutations([y.strip() for y in y_values.split(",")]))
-
         ys = process_axis(y_opt, y_values)
 
         def fix_axis_seeds(axis_opt, axis_list):
-- 
cgit v1.2.3


From eeab7aedf532680a6ae9058ee272450bb07e41eb Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Tue, 4 Oct 2022 04:24:35 -0400
Subject: Add --use-cpu command line option

Remove MPS detection to use CPU for GFPGAN / CodeFormer and add a --use-cpu command line option.
---
 modules/devices.py      | 5 ++---
 modules/esrgan_model.py | 9 ++++-----
 modules/scunet_model.py | 8 ++++----
 modules/shared.py       | 9 +++++++--
 4 files changed, 17 insertions(+), 14 deletions(-)

diff --git a/modules/devices.py b/modules/devices.py
index 5d9c7a07..b5a0cd29 100644
--- a/modules/devices.py
+++ b/modules/devices.py
@@ -1,8 +1,8 @@
 import torch
 
-# has_mps is only available in nightly pytorch (for now), `getattr` for compatibility
 from modules import errors
 
+# has_mps is only available in nightly pytorch (for now), `getattr` for compatibility
 has_mps = getattr(torch, 'has_mps', False)
 
 cpu = torch.device("cpu")
@@ -32,8 +32,7 @@ def enable_tf32():
 
 errors.run(enable_tf32, "Enabling TF32")
 
-device = get_optimal_device()
-device_gfpgan = device_codeformer = cpu if device.type == 'mps' else device
+device = device_gfpgan = device_esrgan = device_scunet = device_codeformer = get_optimal_device()
 dtype = torch.float16
 
 def randn(seed, shape):
diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py
index 4aed9283..d17e730f 100644
--- a/modules/esrgan_model.py
+++ b/modules/esrgan_model.py
@@ -6,8 +6,7 @@ from PIL import Image
 from basicsr.utils.download_util import load_file_from_url
 
 import modules.esrgam_model_arch as arch
-from modules import shared, modelloader, images
-from modules.devices import has_mps
+from modules import shared, modelloader, images, devices
 from modules.paths import models_path
 from modules.upscaler import Upscaler, UpscalerData
 from modules.shared import opts
@@ -97,7 +96,7 @@ class UpscalerESRGAN(Upscaler):
         model = self.load_model(selected_model)
         if model is None:
             return img
-        model.to(shared.device)
+        model.to(devices.device_esrgan)
         img = esrgan_upscale(model, img)
         return img
 
@@ -112,7 +111,7 @@ class UpscalerESRGAN(Upscaler):
             print("Unable to load %s from %s" % (self.model_path, filename))
             return None
 
-        pretrained_net = torch.load(filename, map_location='cpu' if has_mps else None)
+        pretrained_net = torch.load(filename, map_location='cpu' if shared.device.type == 'mps' else None)
         crt_model = arch.RRDBNet(3, 3, 64, 23, gc=32)
 
         pretrained_net = fix_model_layers(crt_model, pretrained_net)
@@ -127,7 +126,7 @@ def upscale_without_tiling(model, img):
     img = img[:, :, ::-1]
     img = np.moveaxis(img, 2, 0) / 255
     img = torch.from_numpy(img).float()
-    img = img.unsqueeze(0).to(shared.device)
+    img = img.unsqueeze(0).to(devices.device_esrgan)
     with torch.no_grad():
         output = model(img)
     output = output.squeeze().float().cpu().clamp_(0, 1).numpy()
diff --git a/modules/scunet_model.py b/modules/scunet_model.py
index 7987ac14..fb64b740 100644
--- a/modules/scunet_model.py
+++ b/modules/scunet_model.py
@@ -8,7 +8,7 @@ import torch
 from basicsr.utils.download_util import load_file_from_url
 
 import modules.upscaler
-from modules import shared, modelloader
+from modules import devices, modelloader
 from modules.paths import models_path
 from modules.scunet_model_arch import SCUNet as net
 
@@ -51,12 +51,12 @@ class UpscalerScuNET(modules.upscaler.Upscaler):
         if model is None:
             return img
 
-        device = shared.device
+        device = devices.device_scunet
         img = np.array(img)
         img = img[:, :, ::-1]
         img = np.moveaxis(img, 2, 0) / 255
         img = torch.from_numpy(img).float()
-        img = img.unsqueeze(0).to(shared.device)
+        img = img.unsqueeze(0).to(device)
 
         img = img.to(device)
         with torch.no_grad():
@@ -69,7 +69,7 @@ class UpscalerScuNET(modules.upscaler.Upscaler):
         return PIL.Image.fromarray(output, 'RGB')
 
     def load_model(self, path: str):
-        device = shared.device
+        device = devices.device_scunet
         if "http" in path:
             filename = load_file_from_url(url=self.model_url, model_dir=self.model_path, file_name="%s.pth" % self.name,
                                           progress=True)
diff --git a/modules/shared.py b/modules/shared.py
index 2a599e9c..7899ab8d 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -12,7 +12,7 @@ import modules.interrogate
 import modules.memmon
 import modules.sd_models
 import modules.styles
-from modules.devices import get_optimal_device
+import modules.devices as devices
 from modules.paths import script_path, sd_path
 
 sd_model_file = os.path.join(script_path, 'model.ckpt')
@@ -46,6 +46,7 @@ parser.add_argument("--ldsr-models-path", type=str, help="Path to directory with
 parser.add_argument("--opt-split-attention", action='store_true', help="force-enables cross-attention layer optimization. By default, it's on for torch.cuda and off for other torch devices.")
 parser.add_argument("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization")
 parser.add_argument("--opt-split-attention-v1", action='store_true', help="enable older version of split attention optimization that does not consume all the VRAM it can find")
+parser.add_argument("--use-cpu", nargs='+',choices=['SD', 'GFPGAN', 'ESRGAN', 'SCUNet', 'CodeFormer'], help="use CPU for specified modules", default=[])
 parser.add_argument("--listen", action='store_true', help="launch gradio with 0.0.0.0 as server name, allowing to respond to network requests")
 parser.add_argument("--port", type=int, help="launch gradio with given server port, you need root/admin rights for ports < 1024, defaults to 7860 if available", default=None)
 parser.add_argument("--show-negative-prompt", action='store_true', help="does not do anything", default=False)
@@ -63,7 +64,11 @@ parser.add_argument("--enable-console-prompts", action='store_true', help="print
 
 
 cmd_opts = parser.parse_args()
-device = get_optimal_device()
+
+devices.device, devices.device_gfpgan, devices.device_esrgan, devices.device_scunet, devices.device_codeformer = \
+(devices.cpu if x in cmd_opts.use_cpu else devices.get_optimal_device() for x in ['SD', 'GFPGAN', 'ESRGAN', 'SCUNet', 'CodeFormer'])
+
+device = devices.device
 
 batch_cond_uncond = cmd_opts.always_batch_cond_uncond or not (cmd_opts.lowvram or cmd_opts.medvram)
 parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram
-- 
cgit v1.2.3


From 27ddc24fdee1fbe709054a43235ab7f9c51b3e9f Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Tue, 4 Oct 2022 05:18:17 -0400
Subject: Add BSRGAN to --add-cpu

---
 modules/bsrgan_model.py | 6 +++---
 modules/devices.py      | 2 +-
 modules/shared.py       | 6 +++---
 3 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/modules/bsrgan_model.py b/modules/bsrgan_model.py
index e62c6657..3bd80791 100644
--- a/modules/bsrgan_model.py
+++ b/modules/bsrgan_model.py
@@ -8,7 +8,7 @@ import torch
 from basicsr.utils.download_util import load_file_from_url
 
 import modules.upscaler
-from modules import shared, modelloader
+from modules import devices, modelloader
 from modules.bsrgan_model_arch import RRDBNet
 from modules.paths import models_path
 
@@ -44,13 +44,13 @@ class UpscalerBSRGAN(modules.upscaler.Upscaler):
         model = self.load_model(selected_file)
         if model is None:
             return img
-        model.to(shared.device)
+        model.to(devices.device_bsrgan)
         torch.cuda.empty_cache()
         img = np.array(img)
         img = img[:, :, ::-1]
         img = np.moveaxis(img, 2, 0) / 255
         img = torch.from_numpy(img).float()
-        img = img.unsqueeze(0).to(shared.device)
+        img = img.unsqueeze(0).to(devices.device_bsrgan)
         with torch.no_grad():
             output = model(img)
         output = output.squeeze().float().cpu().clamp_(0, 1).numpy()
diff --git a/modules/devices.py b/modules/devices.py
index b5a0cd29..b7899632 100644
--- a/modules/devices.py
+++ b/modules/devices.py
@@ -32,7 +32,7 @@ def enable_tf32():
 
 errors.run(enable_tf32, "Enabling TF32")
 
-device = device_gfpgan = device_esrgan = device_scunet = device_codeformer = get_optimal_device()
+device = device_gfpgan = device_bsrgan = device_esrgan = device_scunet = device_codeformer = get_optimal_device()
 dtype = torch.float16
 
 def randn(seed, shape):
diff --git a/modules/shared.py b/modules/shared.py
index 7899ab8d..95b98a06 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -46,7 +46,7 @@ parser.add_argument("--ldsr-models-path", type=str, help="Path to directory with
 parser.add_argument("--opt-split-attention", action='store_true', help="force-enables cross-attention layer optimization. By default, it's on for torch.cuda and off for other torch devices.")
 parser.add_argument("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization")
 parser.add_argument("--opt-split-attention-v1", action='store_true', help="enable older version of split attention optimization that does not consume all the VRAM it can find")
-parser.add_argument("--use-cpu", nargs='+',choices=['SD', 'GFPGAN', 'ESRGAN', 'SCUNet', 'CodeFormer'], help="use CPU for specified modules", default=[])
+parser.add_argument("--use-cpu", nargs='+',choices=['SD', 'GFPGAN', 'BSRGAN', 'ESRGAN', 'SCUNet', 'CodeFormer'], help="use CPU for specified modules", default=[])
 parser.add_argument("--listen", action='store_true', help="launch gradio with 0.0.0.0 as server name, allowing to respond to network requests")
 parser.add_argument("--port", type=int, help="launch gradio with given server port, you need root/admin rights for ports < 1024, defaults to 7860 if available", default=None)
 parser.add_argument("--show-negative-prompt", action='store_true', help="does not do anything", default=False)
@@ -65,8 +65,8 @@ parser.add_argument("--enable-console-prompts", action='store_true', help="print
 
 cmd_opts = parser.parse_args()
 
-devices.device, devices.device_gfpgan, devices.device_esrgan, devices.device_scunet, devices.device_codeformer = \
-(devices.cpu if x in cmd_opts.use_cpu else devices.get_optimal_device() for x in ['SD', 'GFPGAN', 'ESRGAN', 'SCUNet', 'CodeFormer'])
+devices.device, devices.device_gfpgan, devices.device_bsrgan, devices.device_esrgan, devices.device_scunet, devices.device_codeformer = \
+(devices.cpu if x in cmd_opts.use_cpu else devices.get_optimal_device() for x in ['SD', 'GFPGAN', 'BSRGAN', 'ESRGAN', 'SCUNet', 'CodeFormer'])
 
 device = devices.device
 
-- 
cgit v1.2.3


From dc9c5a97742e3a34d37da7108642d8adc0dc5858 Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Tue, 4 Oct 2022 05:22:50 -0400
Subject: Modify --add-cpu description

---
 modules/shared.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/shared.py b/modules/shared.py
index 95b98a06..25aff5b0 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -46,7 +46,7 @@ parser.add_argument("--ldsr-models-path", type=str, help="Path to directory with
 parser.add_argument("--opt-split-attention", action='store_true', help="force-enables cross-attention layer optimization. By default, it's on for torch.cuda and off for other torch devices.")
 parser.add_argument("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization")
 parser.add_argument("--opt-split-attention-v1", action='store_true', help="enable older version of split attention optimization that does not consume all the VRAM it can find")
-parser.add_argument("--use-cpu", nargs='+',choices=['SD', 'GFPGAN', 'BSRGAN', 'ESRGAN', 'SCUNet', 'CodeFormer'], help="use CPU for specified modules", default=[])
+parser.add_argument("--use-cpu", nargs='+',choices=['SD', 'GFPGAN', 'BSRGAN', 'ESRGAN', 'SCUNet', 'CodeFormer'], help="use CPU as torch device for specified modules", default=[])
 parser.add_argument("--listen", action='store_true', help="launch gradio with 0.0.0.0 as server name, allowing to respond to network requests")
 parser.add_argument("--port", type=int, help="launch gradio with given server port, you need root/admin rights for ports < 1024, defaults to 7860 if available", default=None)
 parser.add_argument("--show-negative-prompt", action='store_true', help="does not do anything", default=False)
-- 
cgit v1.2.3


From 6c6ae28bf5fd1e8bc3e8f64a3430b6f29f338f77 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 4 Oct 2022 12:32:22 +0300
Subject: send all three of GFPGAN's and codeformer's models to CPU memory
 instead of just one for #1283

---
 modules/codeformer_model.py | 12 ++++++++++--
 modules/devices.py          | 10 ++++++++++
 modules/gfpgan_model.py     | 14 ++++++++++++--
 modules/processing.py       | 16 +++++++++-------
 4 files changed, 41 insertions(+), 11 deletions(-)

diff --git a/modules/codeformer_model.py b/modules/codeformer_model.py
index a29f3855..e6d9fa4f 100644
--- a/modules/codeformer_model.py
+++ b/modules/codeformer_model.py
@@ -69,10 +69,14 @@ def setup_model(dirname):
 
                 self.net = net
                 self.face_helper = face_helper
-                self.net.to(devices.device_codeformer)
 
                 return net, face_helper
 
+            def send_model_to(self, device):
+                self.net.to(device)
+                self.face_helper.face_det.to(device)
+                self.face_helper.face_parse.to(device)
+
             def restore(self, np_image, w=None):
                 np_image = np_image[:, :, ::-1]
 
@@ -82,6 +86,8 @@ def setup_model(dirname):
                 if self.net is None or self.face_helper is None:
                     return np_image
 
+                self.send_model_to(devices.device_codeformer)
+
                 self.face_helper.clean_all()
                 self.face_helper.read_image(np_image)
                 self.face_helper.get_face_landmarks_5(only_center_face=False, resize=640, eye_dist_threshold=5)
@@ -113,8 +119,10 @@ def setup_model(dirname):
                 if original_resolution != restored_img.shape[0:2]:
                     restored_img = cv2.resize(restored_img, (0, 0), fx=original_resolution[1]/restored_img.shape[1], fy=original_resolution[0]/restored_img.shape[0], interpolation=cv2.INTER_LINEAR)
 
+                self.face_helper.clean_all()
+
                 if shared.opts.face_restoration_unload:
-                    self.net.to(devices.cpu)
+                    self.send_model_to(devices.cpu)
 
                 return restored_img
 
diff --git a/modules/devices.py b/modules/devices.py
index ff82f2f6..12aab665 100644
--- a/modules/devices.py
+++ b/modules/devices.py
@@ -1,3 +1,5 @@
+import contextlib
+
 import torch
 
 # has_mps is only available in nightly pytorch (for now), `getattr` for compatibility
@@ -57,3 +59,11 @@ def randn_without_seed(shape):
 
     return torch.randn(shape, device=device)
 
+
+def autocast():
+    from modules import shared
+
+    if dtype == torch.float32 or shared.cmd_opts.precision == "full":
+        return contextlib.nullcontext()
+
+    return torch.autocast("cuda")
diff --git a/modules/gfpgan_model.py b/modules/gfpgan_model.py
index dd3fbcab..5586b554 100644
--- a/modules/gfpgan_model.py
+++ b/modules/gfpgan_model.py
@@ -37,22 +37,32 @@ def gfpgann():
         print("Unable to load gfpgan model!")
         return None
     model = gfpgan_constructor(model_path=model_file, upscale=1, arch='clean', channel_multiplier=2, bg_upsampler=None)
-    model.gfpgan.to(shared.device)
     loaded_gfpgan_model = model
 
     return model
 
 
+def send_model_to(model, device):
+    model.gfpgan.to(device)
+    model.face_helper.face_det.to(device)
+    model.face_helper.face_parse.to(device)
+
+
 def gfpgan_fix_faces(np_image):
     model = gfpgann()
     if model is None:
         return np_image
+
+    send_model_to(model, devices.device)
+
     np_image_bgr = np_image[:, :, ::-1]
     cropped_faces, restored_faces, gfpgan_output_bgr = model.enhance(np_image_bgr, has_aligned=False, only_center_face=False, paste_back=True)
     np_image = gfpgan_output_bgr[:, :, ::-1]
 
+    model.face_helper.clean_all()
+
     if shared.opts.face_restoration_unload:
-        model.gfpgan.to(devices.cpu)
+        send_model_to(model, devices.cpu)
 
     return np_image
 
diff --git a/modules/processing.py b/modules/processing.py
index 0a4b6198..9cbecdd8 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -1,4 +1,3 @@
-import contextlib
 import json
 import math
 import os
@@ -330,9 +329,8 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
 
     infotexts = []
     output_images = []
-    precision_scope = torch.autocast if cmd_opts.precision == "autocast" else contextlib.nullcontext
-    ema_scope = (contextlib.nullcontext if cmd_opts.lowvram else p.sd_model.ema_scope)
-    with torch.no_grad(), precision_scope("cuda"), ema_scope():
+
+    with torch.no_grad():
         p.init(all_prompts, all_seeds, all_subseeds)
 
         if state.job_count == -1:
@@ -351,8 +349,9 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
 
             #uc = p.sd_model.get_learned_conditioning(len(prompts) * [p.negative_prompt])
             #c = p.sd_model.get_learned_conditioning(prompts)
-            uc = prompt_parser.get_learned_conditioning(len(prompts) * [p.negative_prompt], p.steps)
-            c = prompt_parser.get_learned_conditioning(prompts, p.steps)
+            with devices.autocast():
+                uc = prompt_parser.get_learned_conditioning(len(prompts) * [p.negative_prompt], p.steps)
+                c = prompt_parser.get_learned_conditioning(prompts, p.steps)
 
             if len(model_hijack.comments) > 0:
                 for comment in model_hijack.comments:
@@ -361,7 +360,9 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
             if p.n_iter > 1:
                 shared.state.job = f"Batch {n+1} out of {p.n_iter}"
 
-            samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength)
+            with devices.autocast():
+                samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength).to(devices.dtype)
+
             if state.interrupted:
 
                 # if we are interruped, sample returns just noise
@@ -386,6 +387,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
                     devices.torch_gc()
 
                     x_sample = modules.face_restoration.restore_faces(x_sample)
+                    devices.torch_gc()
 
                 image = Image.fromarray(x_sample)
 
-- 
cgit v1.2.3


From 2f1b61d97987ae0a52a7dfc6bc99c68928bdb594 Mon Sep 17 00:00:00 2001
From: dan <guaneec@gmail.com>
Date: Mon, 3 Oct 2022 19:25:36 +0800
Subject: Allow nested structures inside schedules

---
 modules/prompt_parser.py  | 119 +++++++++++++++++++++-------------------------
 requirements.txt          |   1 +
 requirements_versions.txt |   1 +
 3 files changed, 55 insertions(+), 66 deletions(-)

diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py
index e811eb9e..99c8ed99 100644
--- a/modules/prompt_parser.py
+++ b/modules/prompt_parser.py
@@ -1,20 +1,11 @@
 import re
 from collections import namedtuple
 import torch
+from lark import Lark, Transformer, Visitor
+import functools
 
 import modules.shared as shared
 
-re_prompt = re.compile(r'''
-(.*?)
-\[
-    ([^]:]+):
-    (?:([^]:]*):)?
-    ([0-9]*\.?[0-9]+)
-]
-|
-(.+)
-''', re.X)
-
 # a prompt like this: "fantasy landscape with a [mountain:lake:0.25] and [an oak:a christmas tree:0.75][ in foreground::0.6][ in background:0.25] [shoddy:masterful:0.5]"
 # will be represented with prompt_schedule like this (assuming steps=100):
 # [25, 'fantasy landscape with a mountain and an oak in foreground shoddy']
@@ -25,61 +16,57 @@ re_prompt = re.compile(r'''
 
 
 def get_learned_conditioning_prompt_schedules(prompts, steps):
-    res = []
-    cache = {}
-
-    for prompt in prompts:
-        prompt_schedule: list[list[str | int]] = [[steps, ""]]
-
-        cached = cache.get(prompt, None)
-        if cached is not None:
-            res.append(cached)
-            continue
-
-        for m in re_prompt.finditer(prompt):
-            plaintext = m.group(1) if m.group(5) is None else m.group(5)
-            concept_from = m.group(2)
-            concept_to = m.group(3)
-            if concept_to is None:
-                concept_to = concept_from
-                concept_from = ""
-            swap_position = float(m.group(4)) if m.group(4) is not None else None
-
-            if swap_position is not None:
-                if swap_position < 1:
-                    swap_position = swap_position * steps
-                swap_position = int(min(swap_position, steps))
-
-            swap_index = None
-            found_exact_index = False
-            for i in range(len(prompt_schedule)):
-                end_step = prompt_schedule[i][0]
-                prompt_schedule[i][1] += plaintext
-
-                if swap_position is not None and swap_index is None:
-                    if swap_position == end_step:
-                        swap_index = i
-                        found_exact_index = True
-
-                    if swap_position < end_step:
-                        swap_index = i
-
-            if swap_index is not None:
-                if not found_exact_index:
-                    prompt_schedule.insert(swap_index, [swap_position, prompt_schedule[swap_index][1]])
-
-                for i in range(len(prompt_schedule)):
-                    end_step = prompt_schedule[i][0]
-                    must_replace = swap_position < end_step
-
-                    prompt_schedule[i][1] += concept_to if must_replace else concept_from
-
-        res.append(prompt_schedule)
-        cache[prompt] = prompt_schedule
-        #for t in prompt_schedule:
-        #    print(t)
-
-    return res
+    grammar = r"""
+    start: prompt
+    prompt: (emphasized | scheduled | weighted | plain)*
+    !emphasized: "(" prompt ")"
+            | "(" prompt ":" prompt ")"
+            | "[" prompt "]"
+    scheduled: "[" (prompt ":")? prompt ":" NUMBER "]"
+    !weighted: "{" weighted_item ("|" weighted_item)* "}"
+    !weighted_item: prompt (":" prompt)?
+    plain: /([^\\\[\](){}:|]|\\.)+/
+    %import common.SIGNED_NUMBER -> NUMBER
+    """
+    parser = Lark(grammar, parser='lalr')
+    def collect_steps(steps, tree):
+        l = [steps]
+        class CollectSteps(Visitor):
+            def scheduled(self, tree):
+                tree.children[-1] = float(tree.children[-1])
+                if tree.children[-1] < 1:
+                    tree.children[-1] *= steps
+                tree.children[-1] = min(steps, int(tree.children[-1]))
+                l.append(tree.children[-1])
+        CollectSteps().visit(tree)
+        return sorted(set(l))
+    def at_step(step, tree):
+        class AtStep(Transformer):
+            def scheduled(self, args):
+                if len(args) == 2:
+                    before, after, when = (), *args
+                else:
+                    before, after, when = args
+                yield before if step <= when else after
+            def start(self, args):
+                def flatten(x):
+                    if type(x) == str:
+                        yield x
+                    else:
+                        for gen in x:
+                            yield from flatten(gen)
+                return ''.join(flatten(args[0]))
+            def plain(self, args):
+                yield args[0].value
+            def __default__(self, data, children, meta):
+                for child in children:
+                    yield from child
+        return AtStep().transform(tree)
+    @functools.cache
+    def get_schedule(prompt):
+        tree = parser.parse(prompt)
+        return [[t, at_step(t, tree)] for t in collect_steps(steps, tree)]
+    return [get_schedule(prompt) for prompt in prompts]
 
 
 ScheduledPromptConditioning = namedtuple("ScheduledPromptConditioning", ["end_at_step", "cond"])
diff --git a/requirements.txt b/requirements.txt
index d4b337fc..631fe616 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -22,3 +22,4 @@ clean-fid
 resize-right
 torchdiffeq
 kornia
+lark
diff --git a/requirements_versions.txt b/requirements_versions.txt
index 8a9acf20..fdff2687 100644
--- a/requirements_versions.txt
+++ b/requirements_versions.txt
@@ -21,3 +21,4 @@ clean-fid==0.1.29
 resize-right==0.0.2
 torchdiffeq==0.2.3
 kornia==0.6.7
+lark==1.1.2
-- 
cgit v1.2.3


From 61652461242951966e5b4cee83ce359cefa91c17 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 4 Oct 2022 14:23:22 +0300
Subject: support interrupting after the previous change

---
 modules/processing.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/modules/processing.py b/modules/processing.py
index 9cbecdd8..6f5599c7 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -361,7 +361,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
                 shared.state.job = f"Batch {n+1} out of {p.n_iter}"
 
             with devices.autocast():
-                samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength).to(devices.dtype)
+                samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength)
 
             if state.interrupted:
 
@@ -369,6 +369,8 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
                 # use the image collected previously in sampler loop
                 samples_ddim = shared.state.current_latent
 
+            samples_ddim = samples_ddim.to(devices.dtype)
+
             x_samples_ddim = p.sd_model.decode_first_stage(samples_ddim)
             x_samples_ddim = torch.clamp((x_samples_ddim + 1.0) / 2.0, min=0.0, max=1.0)
 
-- 
cgit v1.2.3


From d5bba20a58f43a9f984bb67b4e17f48661f6b818 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 4 Oct 2022 14:35:12 +0300
Subject: ignore errors in parse for purposes of token counting for #1564

---
 modules/ui.py | 12 ++++++++++--
 1 file changed, 10 insertions(+), 2 deletions(-)

diff --git a/modules/ui.py b/modules/ui.py
index 55f7aa95..20dc8c37 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -386,14 +386,22 @@ def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info:
         outputs=[seed, dummy_component]
     )
 
+
 def update_token_counter(text, steps):
-    prompt_schedules = get_learned_conditioning_prompt_schedules([text], steps)
+    try:
+        prompt_schedules = get_learned_conditioning_prompt_schedules([text], steps)
+    except Exception:
+        # a parsing error can happen here during typing, and we don't want to bother the user with
+        # messages related to it in console
+        prompt_schedules = [[[steps, text]]]
+
     flat_prompts = reduce(lambda list1, list2: list1+list2, prompt_schedules)
-    prompts = [prompt_text for step,prompt_text in flat_prompts]
+    prompts = [prompt_text for step, prompt_text in flat_prompts]
     tokens, token_count, max_length = max([model_hijack.tokenize(prompt) for prompt in prompts], key=lambda args: args[1])
     style_class = ' class="red"' if (token_count > max_length) else ""
     return f"<span {style_class}>{token_count}/{max_length}</span>"
 
+
 def create_toprow(is_img2img):
     id_part = "img2img" if is_img2img else "txt2img"
 
-- 
cgit v1.2.3


From accd00d6b8258c12b5168918a4c546b02357924a Mon Sep 17 00:00:00 2001
From: Justin Riddiough <jriddiough@gmail.com>
Date: Tue, 4 Oct 2022 01:14:28 -0500
Subject: Explain how to use second progress bar in pycharm

---
 modules/shared.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/shared.py b/modules/shared.py
index 25aff5b0..11bdf01a 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -200,7 +200,7 @@ options_templates.update(options_section(('face-restoration', "Face restoration"
 options_templates.update(options_section(('system', "System"), {
     "memmon_poll_rate": OptionInfo(8, "VRAM usage polls per second during generation. Set to 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}),
     "samples_log_stdout": OptionInfo(False, "Always print all generation info to standard output"),
-    "multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job. Broken in PyCharm console."),
+    "multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job. In PyCharm select 'emulate terminal in console output'."),
 }))
 
 options_templates.update(options_section(('sd', "Stable Diffusion"), {
-- 
cgit v1.2.3


From ea6b0d98a64290a0305e27126ea59ce1da7959a2 Mon Sep 17 00:00:00 2001
From: Justin Riddiough <jriddiough@gmail.com>
Date: Tue, 4 Oct 2022 06:38:45 -0500
Subject: Remove pycharm note, fix typo

---
 modules/shared.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/modules/shared.py b/modules/shared.py
index 11bdf01a..a7d13b2d 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -200,7 +200,7 @@ options_templates.update(options_section(('face-restoration', "Face restoration"
 options_templates.update(options_section(('system', "System"), {
     "memmon_poll_rate": OptionInfo(8, "VRAM usage polls per second during generation. Set to 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}),
     "samples_log_stdout": OptionInfo(False, "Always print all generation info to standard output"),
-    "multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job. In PyCharm select 'emulate terminal in console output'."),
+    "multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job."),
 }))
 
 options_templates.update(options_section(('sd', "Stable Diffusion"), {
@@ -209,7 +209,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"),
     "img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies (normally you'd do less with less denoising)."),
     "enable_quantization": OptionInfo(False, "Enable quantization in K samplers for sharper and cleaner results. This may change existing seeds. Requires restart to apply."),
-    "enable_emphasis": OptionInfo(True, "Eemphasis: use (text) to make model pay more attention to text and [text] to make it pay less attention"),
+    "enable_emphasis": OptionInfo(True, "Emphasis: use (text) to make model pay more attention to text and [text] to make it pay less attention"),
     "use_old_emphasis_implementation": OptionInfo(False, "Use old emphasis implementation. Can be useful to reproduce old seeds."),
     "enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"),
     "filter_nsfw": OptionInfo(False, "Filter NSFW content"),
-- 
cgit v1.2.3


From eec1b39bd54711ca31e43022d2d6ac8c6d7281da Mon Sep 17 00:00:00 2001
From: Milly <milly.ca@gmail.com>
Date: Tue, 4 Oct 2022 20:16:52 +0900
Subject: Apply prompt pattern last

---
 modules/images.py | 39 ++++++++++++++++++++-------------------
 1 file changed, 20 insertions(+), 19 deletions(-)

diff --git a/modules/images.py b/modules/images.py
index bba55158..5b56c7e3 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -287,6 +287,25 @@ def apply_filename_pattern(x, p, seed, prompt):
     if seed is not None:
         x = x.replace("[seed]", str(seed))
 
+    if p is not None:
+        x = x.replace("[steps]", str(p.steps))
+        x = x.replace("[cfg]", str(p.cfg_scale))
+        x = x.replace("[width]", str(p.width))
+        x = x.replace("[height]", str(p.height))
+
+        #currently disabled if using the save button, will work otherwise
+        # if enabled it will cause a bug because styles is not included in the save_files data dictionary
+        if hasattr(p, "styles"):
+            x = x.replace("[styles]", sanitize_filename_part(", ".join([x for x in p.styles if not x == "None"] or "None"), replace_spaces=False))
+
+        x = x.replace("[sampler]", sanitize_filename_part(sd_samplers.samplers[p.sampler_index].name, replace_spaces=False))
+
+    x = x.replace("[model_hash]", shared.sd_model.sd_model_hash)
+    x = x.replace("[date]", datetime.date.today().isoformat())
+    x = x.replace("[datetime]", datetime.datetime.now().strftime("%Y%m%d%H%M%S"))
+    x = x.replace("[job_timestamp]", shared.state.job_timestamp)
+
+    # Apply [prompt] at last. Because it may contain any replacement word.^M
     if prompt is not None:
         x = x.replace("[prompt]", sanitize_filename_part(prompt))
         if "[prompt_no_styles]" in x:
@@ -295,7 +314,7 @@ def apply_filename_pattern(x, p, seed, prompt):
                 if len(style) > 0:
                     style_parts = [y for y in style.split("{prompt}")]
                     for part in style_parts:
-                        prompt_no_style = prompt_no_style.replace(part, "").replace(", ,", ",").strip().strip(',')                        
+                        prompt_no_style = prompt_no_style.replace(part, "").replace(", ,", ",").strip().strip(',')
             prompt_no_style = prompt_no_style.replace(style, "").strip().strip(',').strip()
             x = x.replace("[prompt_no_styles]", sanitize_filename_part(prompt_no_style, replace_spaces=False))
 
@@ -306,24 +325,6 @@ def apply_filename_pattern(x, p, seed, prompt):
                 words = ["empty"]
             x = x.replace("[prompt_words]", sanitize_filename_part(" ".join(words[0:max_prompt_words]), replace_spaces=False))
 
-    if p is not None:
-        x = x.replace("[steps]", str(p.steps))
-        x = x.replace("[cfg]", str(p.cfg_scale))
-        x = x.replace("[width]", str(p.width))
-        x = x.replace("[height]", str(p.height))
-        
-        #currently disabled if using the save button, will work otherwise 
-        # if enabled it will cause a bug because styles is not included in the save_files data dictionary
-        if hasattr(p, "styles"):
-            x = x.replace("[styles]", sanitize_filename_part(", ".join([x for x in p.styles if not x == "None"] or "None"), replace_spaces=False))
-
-        x = x.replace("[sampler]", sanitize_filename_part(sd_samplers.samplers[p.sampler_index].name, replace_spaces=False))
-
-    x = x.replace("[model_hash]", shared.sd_model.sd_model_hash)
-    x = x.replace("[date]", datetime.date.today().isoformat())
-    x = x.replace("[datetime]", datetime.datetime.now().strftime("%Y%m%d%H%M%S"))
-    x = x.replace("[job_timestamp]", shared.state.job_timestamp)
-
     if cmd_opts.hide_ui_dir_config:
         x = re.sub(r'^[\\/]+|\.{2,}[\\/]+|[\\/]+\.{2,}', '', x)
 
-- 
cgit v1.2.3


From 52cef36f6ba169a8e606ecdcaed73d47378f0e8e Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 4 Oct 2022 16:54:31 +0300
Subject: emergency fix for img2img

---
 modules/processing.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/modules/processing.py b/modules/processing.py
index 6f5599c7..e9c45394 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -331,7 +331,8 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
     output_images = []
 
     with torch.no_grad():
-        p.init(all_prompts, all_seeds, all_subseeds)
+        with devices.autocast():
+            p.init(all_prompts, all_seeds, all_subseeds)
 
         if state.job_count == -1:
             state.job_count = p.n_iter
-- 
cgit v1.2.3


From 957e29a8e9cb8ca069799ec69263e188c89ed6a6 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 4 Oct 2022 17:23:48 +0300
Subject: option to not show images in web ui

---
 modules/img2img.py | 3 +++
 modules/shared.py  | 1 +
 modules/txt2img.py | 3 +++
 3 files changed, 7 insertions(+)

diff --git a/modules/img2img.py b/modules/img2img.py
index 2ff8e261..da212d72 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -129,4 +129,7 @@ def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, pro
     if opts.samples_log_stdout:
         print(generation_info_js)
 
+    if opts.do_not_show_images:
+        processed.images = []
+
     return processed.images, generation_info_js, plaintext_to_html(processed.info)
diff --git a/modules/shared.py b/modules/shared.py
index a7d13b2d..ff4e5fa3 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -229,6 +229,7 @@ options_templates.update(options_section(('ui', "User interface"), {
     "show_progressbar": OptionInfo(True, "Show progressbar"),
     "show_progress_every_n_steps": OptionInfo(0, "Show show image creation progress every N sampling steps. Set 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 32, "step": 1}),
     "return_grid": OptionInfo(True, "Show grid in results for web"),
+    "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"),
     "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"),
     "font": OptionInfo("", "Font for image grids that have text"),
     "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"),
diff --git a/modules/txt2img.py b/modules/txt2img.py
index d4406c3c..e985242b 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -48,5 +48,8 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2:
     if opts.samples_log_stdout:
         print(generation_info_js)
 
+    if opts.do_not_show_images:
+        processed.images = []
+
     return processed.images, generation_info_js, plaintext_to_html(processed.info)
 
-- 
cgit v1.2.3


From e1b128d8e46bddb9c0b2fd3ee0eefd57e0527ee0 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 4 Oct 2022 17:36:39 +0300
Subject: do not touch p.seed/p.subseed during processing #1181

---
 modules/processing.py | 26 +++++++++++++++++---------
 1 file changed, 17 insertions(+), 9 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index e9c45394..8180c63d 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -248,9 +248,16 @@ def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, see
     return x
 
 
+def get_fixed_seed(seed):
+    if seed is None or seed == '' or seed == -1:
+        return int(random.randrange(4294967294))
+
+    return seed
+
+
 def fix_seed(p):
-    p.seed = int(random.randrange(4294967294)) if p.seed is None or p.seed == '' or p.seed == -1 else p.seed
-    p.subseed = int(random.randrange(4294967294)) if p.subseed is None or p.subseed == '' or p.subseed == -1 else p.subseed
+    p.seed = get_fixed_seed(p.seed)
+    p.subseed = get_fixed_seed(p.subseed)
 
 
 def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration=0, position_in_batch=0):
@@ -292,7 +299,8 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
         
     devices.torch_gc()
 
-    fix_seed(p)
+    seed = get_fixed_seed(p.seed)
+    subseed = get_fixed_seed(p.subseed)
 
     if p.outpath_samples is not None:
         os.makedirs(p.outpath_samples, exist_ok=True)
@@ -311,15 +319,15 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
     else:
         all_prompts = p.batch_size * p.n_iter * [p.prompt]
 
-    if type(p.seed) == list:
-        all_seeds = p.seed
+    if type(seed) == list:
+        all_seeds = seed
     else:
-        all_seeds = [int(p.seed) + (x if p.subseed_strength == 0 else 0) for x in range(len(all_prompts))]
+        all_seeds = [int(seed) + (x if p.subseed_strength == 0 else 0) for x in range(len(all_prompts))]
 
-    if type(p.subseed) == list:
-        all_subseeds = p.subseed
+    if type(subseed) == list:
+        all_subseeds = subseed
     else:
-        all_subseeds = [int(p.subseed) + x for x in range(len(all_prompts))]
+        all_subseeds = [int(subseed) + x for x in range(len(all_prompts))]
 
     def infotext(iteration=0, position_in_batch=0):
         return create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration, position_in_batch)
-- 
cgit v1.2.3


From 1eb588cbf19924333b88beaa1ac0041904966640 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 4 Oct 2022 18:02:01 +0300
Subject: remove functools.cache as some people are having issues with it

---
 modules/prompt_parser.py | 8 ++++++--
 1 file changed, 6 insertions(+), 2 deletions(-)

diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py
index 99c8ed99..5d58c4ed 100644
--- a/modules/prompt_parser.py
+++ b/modules/prompt_parser.py
@@ -29,6 +29,7 @@ def get_learned_conditioning_prompt_schedules(prompts, steps):
     %import common.SIGNED_NUMBER -> NUMBER
     """
     parser = Lark(grammar, parser='lalr')
+
     def collect_steps(steps, tree):
         l = [steps]
         class CollectSteps(Visitor):
@@ -40,6 +41,7 @@ def get_learned_conditioning_prompt_schedules(prompts, steps):
                 l.append(tree.children[-1])
         CollectSteps().visit(tree)
         return sorted(set(l))
+
     def at_step(step, tree):
         class AtStep(Transformer):
             def scheduled(self, args):
@@ -62,11 +64,13 @@ def get_learned_conditioning_prompt_schedules(prompts, steps):
                 for child in children:
                     yield from child
         return AtStep().transform(tree)
-    @functools.cache
+    
     def get_schedule(prompt):
         tree = parser.parse(prompt)
         return [[t, at_step(t, tree)] for t in collect_steps(steps, tree)]
-    return [get_schedule(prompt) for prompt in prompts]
+
+    promptdict = {prompt: get_schedule(prompt) for prompt in set(prompts)}
+    return [promptdict[prompt] for prompt in prompts]
 
 
 ScheduledPromptConditioning = namedtuple("ScheduledPromptConditioning", ["end_at_step", "cond"])
-- 
cgit v1.2.3


From 90e911fd546e76f879b38a764473569911a0f845 Mon Sep 17 00:00:00 2001
From: Rae Fu <rraefu@gmail.com>
Date: Tue, 4 Oct 2022 09:49:51 -0600
Subject: prompt_parser: allow spaces in schedules, add test, log/ignore errors

Only build the parser once (at import time) instead of for each step.

doctest is run by simply executing modules/prompt_parser.py
---
 modules/processing.py    |  10 ++--
 modules/prompt_parser.py | 139 ++++++++++++++++++++++++++++++-----------------
 2 files changed, 95 insertions(+), 54 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index 8180c63d..bb94033b 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -84,7 +84,7 @@ class StableDiffusionProcessing:
         self.s_tmin = opts.s_tmin
         self.s_tmax = float('inf')  # not representable as a standard ui option
         self.s_noise = opts.s_noise
-        
+
         if not seed_enable_extras:
             self.subseed = -1
             self.subseed_strength = 0
@@ -296,7 +296,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
         assert(len(p.prompt) > 0)
     else:
         assert p.prompt is not None
-        
+
     devices.torch_gc()
 
     seed = get_fixed_seed(p.seed)
@@ -359,8 +359,8 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
             #uc = p.sd_model.get_learned_conditioning(len(prompts) * [p.negative_prompt])
             #c = p.sd_model.get_learned_conditioning(prompts)
             with devices.autocast():
-                uc = prompt_parser.get_learned_conditioning(len(prompts) * [p.negative_prompt], p.steps)
-                c = prompt_parser.get_learned_conditioning(prompts, p.steps)
+                uc = prompt_parser.get_learned_conditioning(shared.sd_model, len(prompts) * [p.negative_prompt], p.steps)
+                c = prompt_parser.get_learned_conditioning(shared.sd_model, prompts, p.steps)
 
             if len(model_hijack.comments) > 0:
                 for comment in model_hijack.comments:
@@ -527,7 +527,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
         # GC now before running the next img2img to prevent running out of memory
         x = None
         devices.torch_gc()
-        
+
         samples = self.sampler.sample_img2img(self, samples, noise, conditioning, unconditional_conditioning, steps=self.steps)
 
         return samples
diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py
index 5d58c4ed..a3b12421 100644
--- a/modules/prompt_parser.py
+++ b/modules/prompt_parser.py
@@ -1,10 +1,7 @@
 import re
 from collections import namedtuple
-import torch
-from lark import Lark, Transformer, Visitor
-import functools
 
-import modules.shared as shared
+import lark
 
 # a prompt like this: "fantasy landscape with a [mountain:lake:0.25] and [an oak:a christmas tree:0.75][ in foreground::0.6][ in background:0.25] [shoddy:masterful:0.5]"
 # will be represented with prompt_schedule like this (assuming steps=100):
@@ -14,25 +11,48 @@ import modules.shared as shared
 # [75, 'fantasy landscape with a lake and an oak in background masterful']
 # [100, 'fantasy landscape with a lake and a christmas tree in background masterful']
 
+schedule_parser = lark.Lark(r"""
+!start: (prompt | /[][():]/+)*
+prompt: (emphasized | scheduled | plain | WHITESPACE)*
+!emphasized: "(" prompt ")"
+        | "(" prompt ":" prompt ")"
+        | "[" prompt "]"
+scheduled: "[" [prompt ":"] prompt ":" [WHITESPACE] NUMBER "]"
+WHITESPACE: /\s+/
+plain: /([^\\\[\]():]|\\.)+/
+%import common.SIGNED_NUMBER -> NUMBER
+""")
 
 def get_learned_conditioning_prompt_schedules(prompts, steps):
-    grammar = r"""
-    start: prompt
-    prompt: (emphasized | scheduled | weighted | plain)*
-    !emphasized: "(" prompt ")"
-            | "(" prompt ":" prompt ")"
-            | "[" prompt "]"
-    scheduled: "[" (prompt ":")? prompt ":" NUMBER "]"
-    !weighted: "{" weighted_item ("|" weighted_item)* "}"
-    !weighted_item: prompt (":" prompt)?
-    plain: /([^\\\[\](){}:|]|\\.)+/
-    %import common.SIGNED_NUMBER -> NUMBER
     """
-    parser = Lark(grammar, parser='lalr')
+    >>> g = lambda p: get_learned_conditioning_prompt_schedules([p], 10)[0]
+    >>> g("test")
+    [[10, 'test']]
+    >>> g("a [b:3]")
+    [[3, 'a '], [10, 'a b']]
+    >>> g("a [b: 3]")
+    [[3, 'a '], [10, 'a b']]
+    >>> g("a [[[b]]:2]")
+    [[2, 'a '], [10, 'a [[b]]']]
+    >>> g("[(a:2):3]")
+    [[3, ''], [10, '(a:2)']]
+    >>> g("a [b : c : 1] d")
+    [[1, 'a b  d'], [10, 'a  c  d']]
+    >>> g("a[b:[c:d:2]:1]e")
+    [[1, 'abe'], [2, 'ace'], [10, 'ade']]
+    >>> g("a [unbalanced")
+    [[10, 'a [unbalanced']]
+    >>> g("a [b:.5] c")
+    [[5, 'a  c'], [10, 'a b c']]
+    >>> g("a [{b|d{:.5] c")  # not handling this right now
+    [[5, 'a  c'], [10, 'a {b|d{ c']]
+    >>> g("((a][:b:c [d:3]")
+    [[3, '((a][:b:c '], [10, '((a][:b:c d']]
+    """
 
     def collect_steps(steps, tree):
         l = [steps]
-        class CollectSteps(Visitor):
+        class CollectSteps(lark.Visitor):
             def scheduled(self, tree):
                 tree.children[-1] = float(tree.children[-1])
                 if tree.children[-1] < 1:
@@ -43,13 +63,10 @@ def get_learned_conditioning_prompt_schedules(prompts, steps):
         return sorted(set(l))
 
     def at_step(step, tree):
-        class AtStep(Transformer):
+        class AtStep(lark.Transformer):
             def scheduled(self, args):
-                if len(args) == 2:
-                    before, after, when = (), *args
-                else:
-                    before, after, when = args
-                yield before if step <= when else after
+                before, after, _, when = args
+                yield before or () if step <= when else after
             def start(self, args):
                 def flatten(x):
                     if type(x) == str:
@@ -57,16 +74,22 @@ def get_learned_conditioning_prompt_schedules(prompts, steps):
                     else:
                         for gen in x:
                             yield from flatten(gen)
-                return ''.join(flatten(args[0]))
+                return ''.join(flatten(args))
             def plain(self, args):
                 yield args[0].value
             def __default__(self, data, children, meta):
                 for child in children:
                     yield from child
         return AtStep().transform(tree)
-    
+
     def get_schedule(prompt):
-        tree = parser.parse(prompt)
+        try:
+            tree = schedule_parser.parse(prompt)
+        except lark.exceptions.LarkError as e:
+            if 0:
+                import traceback
+                traceback.print_exc()
+            return [[steps, prompt]]
         return [[t, at_step(t, tree)] for t in collect_steps(steps, tree)]
 
     promptdict = {prompt: get_schedule(prompt) for prompt in set(prompts)}
@@ -77,8 +100,7 @@ ScheduledPromptConditioning = namedtuple("ScheduledPromptConditioning", ["end_at
 ScheduledPromptBatch = namedtuple("ScheduledPromptBatch", ["shape", "schedules"])
 
 
-def get_learned_conditioning(prompts, steps):
-
+def get_learned_conditioning(model, prompts, steps):
     res = []
 
     prompt_schedules = get_learned_conditioning_prompt_schedules(prompts, steps)
@@ -92,7 +114,7 @@ def get_learned_conditioning(prompts, steps):
             continue
 
         texts = [x[1] for x in prompt_schedule]
-        conds = shared.sd_model.get_learned_conditioning(texts)
+        conds = model.get_learned_conditioning(texts)
 
         cond_schedule = []
         for i, (end_at_step, text) in enumerate(prompt_schedule):
@@ -105,12 +127,13 @@ def get_learned_conditioning(prompts, steps):
 
 
 def reconstruct_cond_batch(c: ScheduledPromptBatch, current_step):
-    res = torch.zeros(c.shape, device=shared.device, dtype=next(shared.sd_model.parameters()).dtype)
+    param = c.schedules[0][0].cond
+    res = torch.zeros(c.shape, device=param.device, dtype=param.dtype)
     for i, cond_schedule in enumerate(c.schedules):
         target_index = 0
-        for curret_index, (end_at, cond) in enumerate(cond_schedule):
+        for current, (end_at, cond) in enumerate(cond_schedule):
             if current_step <= end_at:
-                target_index = curret_index
+                target_index = current
                 break
         res[i] = cond_schedule[target_index].cond
 
@@ -148,23 +171,26 @@ def parse_prompt_attention(text):
       \\ - literal character '\'
       anything else - just text
 
-    Example:
-
-        'a (((house:1.3)) [on] a (hill:0.5), sun, (((sky))).'
-
-    produces:
-
-    [
-        ['a ', 1.0],
-        ['house', 1.5730000000000004],
-        [' ', 1.1],
-        ['on', 1.0],
-        [' a ', 1.1],
-        ['hill', 0.55],
-        [', sun, ', 1.1],
-        ['sky', 1.4641000000000006],
-        ['.', 1.1]
-    ]
+    >>> parse_prompt_attention('normal text')
+    [['normal text', 1.0]]
+    >>> parse_prompt_attention('an (important) word')
+    [['an ', 1.0], ['important', 1.1], [' word', 1.0]]
+    >>> parse_prompt_attention('(unbalanced')
+    [['unbalanced', 1.1]]
+    >>> parse_prompt_attention('\(literal\]')
+    [['(literal]', 1.0]]
+    >>> parse_prompt_attention('(unnecessary)(parens)')
+    [['unnecessaryparens', 1.1]]
+    >>> parse_prompt_attention('a (((house:1.3)) [on] a (hill:0.5), sun, (((sky))).')
+    [['a ', 1.0],
+     ['house', 1.5730000000000004],
+     [' ', 1.1],
+     ['on', 1.0],
+     [' a ', 1.1],
+     ['hill', 0.55],
+     [', sun, ', 1.1],
+     ['sky', 1.4641000000000006],
+     ['.', 1.1]]
     """
 
     res = []
@@ -206,4 +232,19 @@ def parse_prompt_attention(text):
     if len(res) == 0:
         res = [["", 1.0]]
 
+    # merge runs of identical weights
+    i = 0
+    while i + 1 < len(res):
+        if res[i][1] == res[i + 1][1]:
+            res[i][0] += res[i + 1][0]
+            res.pop(i + 1)
+        else:
+            i += 1
+
     return res
+
+if __name__ == "__main__":
+    import doctest
+    doctest.testmod(optionflags=doctest.NORMALIZE_WHITESPACE)
+else:
+    import torch  # doctest faster
-- 
cgit v1.2.3


From b32852ef037251eb3d846af76e2965594e1ac7a5 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 4 Oct 2022 20:49:54 +0300
Subject: add editor to img2img

---
 modules/shared.py | 1 +
 modules/ui.py     | 2 +-
 style.css         | 4 ++++
 3 files changed, 6 insertions(+), 1 deletion(-)

diff --git a/modules/shared.py b/modules/shared.py
index ff4e5fa3..e52c9b1d 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -55,6 +55,7 @@ parser.add_argument("--hide-ui-dir-config", action='store_true', help="hide dire
 parser.add_argument("--ui-settings-file", type=str, help="filename to use for ui settings", default=os.path.join(script_path, 'config.json'))
 parser.add_argument("--gradio-debug",  action='store_true', help="launch gradio with --debug option")
 parser.add_argument("--gradio-auth", type=str, help='set gradio authentication like "username:password"; or comma-delimit multiple like "u1:p1,u2:p2,u3:p3"', default=None)
+parser.add_argument("--gradio-img2img-tool", type=str, help='gradio image uploader tool: can be either editor for ctopping, or color-sketch for drawing', choices=["color-sketch", "editor"], default="color-sketch")
 parser.add_argument("--opt-channelslast", action='store_true', help="change memory type for stable diffusion to channels last")
 parser.add_argument("--styles-file", type=str, help="filename to use for styles", default=os.path.join(script_path, 'styles.csv'))
 parser.add_argument("--autolaunch", action='store_true', help="open the webui URL in the system's default browser upon launch", default=False)
diff --git a/modules/ui.py b/modules/ui.py
index 20dc8c37..6cd6761b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -644,7 +644,7 @@ def create_ui(wrap_gradio_gpu_call):
 
                 with gr.Tabs(elem_id="mode_img2img") as tabs_img2img_mode:
                     with gr.TabItem('img2img', id='img2img'):
-                        init_img = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil")
+                        init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_img2img_tool)
 
                     with gr.TabItem('Inpaint', id='inpaint'):
                         init_img_with_mask = gr.Image(label="Image for inpainting with mask",  show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", image_mode="RGBA")
diff --git a/style.css b/style.css
index 39586bf1..e8f4cb75 100644
--- a/style.css
+++ b/style.css
@@ -403,3 +403,7 @@ input[type="range"]{
 .red {
 	color: red;
 }
+
+#img2img_image div.h-60{
+    height: 480px;
+}
\ No newline at end of file
-- 
cgit v1.2.3


From ef40e4cd4d383a3405e03f1da3f5b5a1820a8f53 Mon Sep 17 00:00:00 2001
From: xpscyho <xpsychonauticonx@gmail.com>
Date: Tue, 4 Oct 2022 15:12:38 -0400
Subject: Display time taken in mins, secs when relevant Fixes #1656

---
 modules/ui.py | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/modules/ui.py b/modules/ui.py
index 6cd6761b..de6342a4 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -196,6 +196,11 @@ def wrap_gradio_call(func, extra_outputs=None):
             res = extra_outputs_array + [f"<div class='error'>{plaintext_to_html(type(e).__name__+': '+str(e))}</div>"]
 
         elapsed = time.perf_counter() - t
+        elapsed_m = int(elapsed // 60)
+        elapsed_s = elapsed % 60
+        elapsed_text = f"{elapsed_s:.2f}s"
+        if (elapsed_m > 0):
+            elapsed_text = f"{elapsed_m}m "+elapsed_text
 
         if run_memmon:
             mem_stats = {k: -(v//-(1024*1024)) for k, v in shared.mem_mon.stop().items()}
@@ -210,7 +215,7 @@ def wrap_gradio_call(func, extra_outputs=None):
             vram_html = ''
 
         # last item is always HTML
-        res[-1] += f"<div class='performance'><p class='time'>Time taken: <wbr>{elapsed:.2f}s</p>{vram_html}</div>"
+        res[-1] += f"<div class='performance'><p class='time'>Time taken: <wbr>{elapsed_text}</p>{vram_html}</div>"
 
         shared.state.interrupted = False
         shared.state.job_count = 0
-- 
cgit v1.2.3


From 82380d9ac18614c87bebba1b4cfd4b147cc76a18 Mon Sep 17 00:00:00 2001
From: Jairo Correa <jn.j41r0@gmail.com>
Date: Tue, 4 Oct 2022 22:28:50 -0300
Subject: Removing parts no longer needed to fix vram

---
 modules/devices.py    |  3 +--
 modules/processing.py | 21 ++++++++-------------
 2 files changed, 9 insertions(+), 15 deletions(-)

diff --git a/modules/devices.py b/modules/devices.py
index 6db4e57c..0158b11f 100644
--- a/modules/devices.py
+++ b/modules/devices.py
@@ -1,7 +1,6 @@
 import contextlib
 
 import torch
-import gc
 
 from modules import errors
 
@@ -20,8 +19,8 @@ def get_optimal_device():
 
     return cpu
 
+
 def torch_gc():
-    gc.collect()
     if torch.cuda.is_available():
         torch.cuda.empty_cache()
         torch.cuda.ipc_collect()
diff --git a/modules/processing.py b/modules/processing.py
index e7f9c85e..f666ba81 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -345,8 +345,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
         if state.job_count == -1:
             state.job_count = p.n_iter
 
-    for n in range(p.n_iter):
-        with torch.no_grad(), precision_scope("cuda"), ema_scope():
+        for n in range(p.n_iter):
             if state.interrupted:
                 break
 
@@ -395,22 +394,19 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
                 import modules.safety as safety
                 x_samples_ddim = modules.safety.censor_batch(x_samples_ddim)
 
-        for i, x_sample in enumerate(x_samples_ddim):
-            with torch.no_grad(), precision_scope("cuda"), ema_scope():
+            for i, x_sample in enumerate(x_samples_ddim):
                 x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2)
                 x_sample = x_sample.astype(np.uint8)
 
-            if p.restore_faces:
-                with torch.no_grad(), precision_scope("cuda"), ema_scope():
+                if p.restore_faces:
                     if opts.save and not p.do_not_save_samples and opts.save_images_before_face_restoration:
                         images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-face-restoration")
 
-                    x_sample = modules.face_restoration.restore_faces(x_sample)
                     devices.torch_gc()
 
-                devices.torch_gc()
+                    x_sample = modules.face_restoration.restore_faces(x_sample)
+                    devices.torch_gc()
 
-            with torch.no_grad(), precision_scope("cuda"), ema_scope():
                 image = Image.fromarray(x_sample)
 
                 if p.color_corrections is not None and i < len(p.color_corrections):
@@ -438,13 +434,12 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
                 infotexts.append(infotext(n, i))
                 output_images.append(image)
 
-        del x_samples_ddim 
+            del x_samples_ddim 
 
-        devices.torch_gc()
+            devices.torch_gc()
 
-        state.nextjob()
+            state.nextjob()
 
-    with torch.no_grad(), precision_scope("cuda"), ema_scope():
         p.color_corrections = None
 
         index_of_first_image = 0
-- 
cgit v1.2.3


From bbdbbd36eda870cf0bd49fdf28476c78919a123e Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Wed, 5 Oct 2022 04:43:05 +0100
Subject: shared.state.interrupt when restart is requested

---
 modules/ui.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/modules/ui.py b/modules/ui.py
index de6342a4..523ab25b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1210,6 +1210,7 @@ def create_ui(wrap_gradio_gpu_call):
         )
 
         def request_restart():
+            shared.state.interrupt()
             settings_interface.gradio_ref.do_restart = True
 
         restart_gradio.click(
-- 
cgit v1.2.3


From 67d011b02eddc20202b654dfea56528de3d5edf7 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Wed, 5 Oct 2022 04:44:22 +0100
Subject: Show generation progress in window title

---
 javascript/progressbar.js | 15 +++++++++++++++
 1 file changed, 15 insertions(+)

diff --git a/javascript/progressbar.js b/javascript/progressbar.js
index 1e297abb..3e3220c3 100644
--- a/javascript/progressbar.js
+++ b/javascript/progressbar.js
@@ -4,6 +4,21 @@ global_progressbars = {}
 function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_interrupt, id_preview, id_gallery){
     var progressbar = gradioApp().getElementById(id_progressbar)
     var interrupt = gradioApp().getElementById(id_interrupt)
+    
+    if(progressbar && progressbar.offsetParent){
+        if(progressbar.innerText){
+            let newtitle = 'Stable Diffusion - ' + progressbar.innerText
+            if(document.title != newtitle){
+                document.title =  newtitle;          
+            }
+        }else{
+            let newtitle = 'Stable Diffusion'
+            if(document.title != newtitle){
+                document.title =  newtitle;          
+            }
+        }
+    }
+    
 	if(progressbar!= null && progressbar != global_progressbars[id_progressbar]){
 	    global_progressbars[id_progressbar] = progressbar
 
-- 
cgit v1.2.3


From 59a2b9e5afc27d2fda72069ca0635070535d18fe Mon Sep 17 00:00:00 2001
From: Greendayle <Greendayle>
Date: Wed, 5 Oct 2022 20:50:10 +0200
Subject: deepdanbooru interrogator

---
 ... your deepbooru release project folder here.txt |  0
 modules/deepbooru.py                               | 60 ++++++++++++++++++++++
 modules/ui.py                                      | 24 +++++++--
 requirements.txt                                   |  3 ++
 requirements_versions.txt                          |  3 ++
 style.css                                          |  7 ++-
 6 files changed, 91 insertions(+), 6 deletions(-)
 create mode 100644 models/deepbooru/Put your deepbooru release project folder here.txt
 create mode 100644 modules/deepbooru.py

diff --git a/models/deepbooru/Put your deepbooru release project folder here.txt b/models/deepbooru/Put your deepbooru release project folder here.txt
new file mode 100644
index 00000000..e69de29b
diff --git a/modules/deepbooru.py b/modules/deepbooru.py
new file mode 100644
index 00000000..958b1c3d
--- /dev/null
+++ b/modules/deepbooru.py
@@ -0,0 +1,60 @@
+import os.path
+from concurrent.futures import ProcessPoolExecutor
+
+import numpy as np
+import deepdanbooru as dd
+import tensorflow as tf
+
+
+def _load_tf_and_return_tags(pil_image, threshold):
+    this_folder = os.path.dirname(__file__)
+    model_path = os.path.join(this_folder, '..', 'models', 'deepbooru', 'deepdanbooru-v3-20211112-sgd-e28')
+    if not os.path.exists(model_path):
+        return "Download https://github.com/KichangKim/DeepDanbooru/releases/download/v3-20211112-sgd-e28/deepdanbooru-v3-20211112-sgd-e28.zip unpack and put into models/deepbooru"
+
+    tags = dd.project.load_tags_from_project(model_path)
+    model = dd.project.load_model_from_project(
+        model_path, compile_model=True
+    )
+
+    width = model.input_shape[2]
+    height = model.input_shape[1]
+    image = np.array(pil_image)
+    image = tf.image.resize(
+        image,
+        size=(height, width),
+        method=tf.image.ResizeMethod.AREA,
+        preserve_aspect_ratio=True,
+    )
+    image = image.numpy()  # EagerTensor to np.array
+    image = dd.image.transform_and_pad_image(image, width, height)
+    image = image / 255.0
+    image_shape = image.shape
+    image = image.reshape((1, image_shape[0], image_shape[1], image_shape[2]))
+
+    y = model.predict(image)[0]
+
+    result_dict = {}
+
+    for i, tag in enumerate(tags):
+        result_dict[tag] = y[i]
+
+
+
+    result_tags_out = []
+    result_tags_print = []
+    for tag in tags:
+        if result_dict[tag] >= threshold:
+            result_tags_out.append(tag)
+            result_tags_print.append(f'{result_dict[tag]} {tag}')
+
+    print('\n'.join(sorted(result_tags_print, reverse=True)))
+
+    return ', '.join(result_tags_out)
+
+
+def get_deepbooru_tags(pil_image, threshold=0.5):
+    with ProcessPoolExecutor() as executor:
+        f = executor.submit(_load_tf_and_return_tags, pil_image, threshold)
+        ret = f.result()  # will rethrow any exceptions
+    return ret
\ No newline at end of file
diff --git a/modules/ui.py b/modules/ui.py
index 20dc8c37..ae98219a 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -23,6 +23,7 @@ import gradio.utils
 import gradio.routes
 
 from modules import sd_hijack
+from modules.deepbooru import get_deepbooru_tags
 from modules.paths import script_path
 from modules.shared import opts, cmd_opts
 import modules.shared as shared
@@ -312,6 +313,11 @@ def interrogate(image):
     return gr_show(True) if prompt is None else prompt
 
 
+def interrogate_deepbooru(image):
+    prompt = get_deepbooru_tags(image)
+    return gr_show(True) if prompt is None else prompt
+
+
 def create_seed_inputs():
     with gr.Row():
         with gr.Box():
@@ -439,15 +445,17 @@ def create_toprow(is_img2img):
                     outputs=[],
                 )
 
-            with gr.Row():
+            with gr.Row(scale=1):
                 if is_img2img:
-                    interrogate = gr.Button('Interrogate', elem_id="interrogate")
+                    interrogate = gr.Button('Interrogate\nCLIP', elem_id="interrogate")
+                    deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru")
                 else:
                     interrogate = None
+                    deepbooru = None
                 prompt_style_apply = gr.Button('Apply style', elem_id="style_apply")
                 save_style = gr.Button('Create style', elem_id="style_create")
 
-    return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, interrogate, prompt_style_apply, save_style, paste, token_counter, token_button
+    return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, interrogate, deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button
 
 
 def setup_progressbar(progressbar, preview, id_part, textinfo=None):
@@ -476,7 +484,7 @@ def create_ui(wrap_gradio_gpu_call):
     import modules.txt2img
 
     with gr.Blocks(analytics_enabled=False) as txt2img_interface:
-        txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, txt2img_prompt_style_apply, txt2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=False)
+        txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=False)
         dummy_component = gr.Label(visible=False)
 
         with gr.Row(elem_id='txt2img_progress_row'):
@@ -628,7 +636,7 @@ def create_ui(wrap_gradio_gpu_call):
             token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter])
 
     with gr.Blocks(analytics_enabled=False) as img2img_interface:
-        img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_prompt_style_apply, img2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=True)
+        img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=True)
 
         with gr.Row(elem_id='img2img_progress_row'):
             with gr.Column(scale=1):
@@ -785,6 +793,12 @@ def create_ui(wrap_gradio_gpu_call):
                 outputs=[img2img_prompt],
             )
 
+            img2img_deepbooru.click(
+                fn=interrogate_deepbooru,
+                inputs=[init_img],
+                outputs=[img2img_prompt],
+            )
+
             save.click(
                 fn=wrap_gradio_call(save_files),
                 _js="(x, y, z) => [x, y, selected_gallery_index()]",
diff --git a/requirements.txt b/requirements.txt
index 631fe616..cab101f8 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -23,3 +23,6 @@ resize-right
 torchdiffeq
 kornia
 lark
+deepdanbooru
+tensorflow
+tensorflow-io
diff --git a/requirements_versions.txt b/requirements_versions.txt
index fdff2687..811953c6 100644
--- a/requirements_versions.txt
+++ b/requirements_versions.txt
@@ -22,3 +22,6 @@ resize-right==0.0.2
 torchdiffeq==0.2.3
 kornia==0.6.7
 lark==1.1.2
+git+https://github.com/KichangKim/DeepDanbooru.git@edf73df4cdaeea2cf00e9ac08bd8a9026b7a7b26#egg=deepdanbooru[tensorflow]
+tensorflow==2.10.0
+tensorflow-io==0.27.0
diff --git a/style.css b/style.css
index 39586bf1..2fd351f9 100644
--- a/style.css
+++ b/style.css
@@ -103,7 +103,12 @@
 
 #style_apply, #style_create, #interrogate{
     margin: 0.75em 0.25em 0.25em 0.25em;
-    min-width: 3em;
+    min-width: 5em;
+}
+
+#style_apply, #style_create, #deepbooru{
+    margin: 0.75em 0.25em 0.25em 0.25em;
+    min-width: 5em;
 }
 
 #style_pos_col, #style_neg_col{
-- 
cgit v1.2.3


From 1506fab29ad54beb9f52236912abc432209c8089 Mon Sep 17 00:00:00 2001
From: Greendayle <Greendayle>
Date: Wed, 5 Oct 2022 21:15:08 +0200
Subject: removing problematic tag

---
 modules/deepbooru.py | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index 958b1c3d..841cb9c5 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -38,13 +38,12 @@ def _load_tf_and_return_tags(pil_image, threshold):
 
     for i, tag in enumerate(tags):
         result_dict[tag] = y[i]
-
-
-
     result_tags_out = []
     result_tags_print = []
     for tag in tags:
         if result_dict[tag] >= threshold:
+            if tag.startswith("rating:"):
+                continue
             result_tags_out.append(tag)
             result_tags_print.append(f'{result_dict[tag]} {tag}')
 
-- 
cgit v1.2.3


From 17a99baf0c929e5df4dfc4b2a96aa3890a141112 Mon Sep 17 00:00:00 2001
From: Greendayle <Greendayle>
Date: Wed, 5 Oct 2022 22:05:24 +0200
Subject: better model search

---
 modules/deepbooru.py | 11 +++++++++--
 1 file changed, 9 insertions(+), 2 deletions(-)

diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index 841cb9c5..a64fd9cd 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -9,8 +9,15 @@ import tensorflow as tf
 def _load_tf_and_return_tags(pil_image, threshold):
     this_folder = os.path.dirname(__file__)
     model_path = os.path.join(this_folder, '..', 'models', 'deepbooru', 'deepdanbooru-v3-20211112-sgd-e28')
-    if not os.path.exists(model_path):
-        return "Download https://github.com/KichangKim/DeepDanbooru/releases/download/v3-20211112-sgd-e28/deepdanbooru-v3-20211112-sgd-e28.zip unpack and put into models/deepbooru"
+
+    model_good = False
+    for path_candidate in [model_path, os.path.dirname(model_path)]:
+        if os.path.exists(os.path.join(path_candidate, 'project.json')):
+            model_path = path_candidate
+            model_good = True
+    if not model_good:
+        return ("Download https://github.com/KichangKim/DeepDanbooru/releases/download/v3-20211112-sgd-e28/"
+                "deepdanbooru-v3-20211112-sgd-e28.zip unpack and put into models/deepbooru")
 
     tags = dd.project.load_tags_from_project(model_path)
     model = dd.project.load_model_from_project(
-- 
cgit v1.2.3


From c26732fbee2a57e621ac22bf70decf7496daa4cd Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 5 Oct 2022 23:16:27 +0300
Subject: added support for AND from
 https://energy-based-model.github.io/Compositional-Visual-Generation-with-Composable-Diffusion-Models/

---
 modules/processing.py    |   2 +-
 modules/prompt_parser.py | 114 ++++++++++++++++++++++++++++++++++++++++++++---
 modules/sd_samplers.py   |  35 ++++++++++-----
 modules/ui.py            |   6 ++-
 4 files changed, 138 insertions(+), 19 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index bb94033b..d8c6b8d5 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -360,7 +360,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
             #c = p.sd_model.get_learned_conditioning(prompts)
             with devices.autocast():
                 uc = prompt_parser.get_learned_conditioning(shared.sd_model, len(prompts) * [p.negative_prompt], p.steps)
-                c = prompt_parser.get_learned_conditioning(shared.sd_model, prompts, p.steps)
+                c = prompt_parser.get_multicond_learned_conditioning(shared.sd_model, prompts, p.steps)
 
             if len(model_hijack.comments) > 0:
                 for comment in model_hijack.comments:
diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py
index a3b12421..f7420daf 100644
--- a/modules/prompt_parser.py
+++ b/modules/prompt_parser.py
@@ -97,10 +97,26 @@ def get_learned_conditioning_prompt_schedules(prompts, steps):
 
 
 ScheduledPromptConditioning = namedtuple("ScheduledPromptConditioning", ["end_at_step", "cond"])
-ScheduledPromptBatch = namedtuple("ScheduledPromptBatch", ["shape", "schedules"])
 
 
 def get_learned_conditioning(model, prompts, steps):
+    """converts a list of prompts into a list of prompt schedules - each schedule is a list of ScheduledPromptConditioning, specifying the comdition (cond),
+    and the sampling step at which this condition is to be replaced by the next one.
+
+    Input:
+    (model, ['a red crown', 'a [blue:green:5] jeweled crown'], 20)
+
+    Output:
+    [
+        [
+            ScheduledPromptConditioning(end_at_step=20, cond=tensor([[-0.3886,  0.0229, -0.0523,  ..., -0.4901, -0.3066,  0.0674], ..., [ 0.3317, -0.5102, -0.4066,  ...,  0.4119, -0.7647, -1.0160]], device='cuda:0'))
+        ],
+        [
+            ScheduledPromptConditioning(end_at_step=5, cond=tensor([[-0.3886,  0.0229, -0.0522,  ..., -0.4901, -0.3067,  0.0673], ..., [-0.0192,  0.3867, -0.4644,  ...,  0.1135, -0.3696, -0.4625]], device='cuda:0')),
+            ScheduledPromptConditioning(end_at_step=20, cond=tensor([[-0.3886,  0.0229, -0.0522,  ..., -0.4901, -0.3067,  0.0673], ..., [-0.7352, -0.4356, -0.7888,  ...,  0.6994, -0.4312, -1.2593]], device='cuda:0'))
+        ]
+    ]
+    """
     res = []
 
     prompt_schedules = get_learned_conditioning_prompt_schedules(prompts, steps)
@@ -123,13 +139,75 @@ def get_learned_conditioning(model, prompts, steps):
         cache[prompt] = cond_schedule
         res.append(cond_schedule)
 
-    return ScheduledPromptBatch((len(prompts),) + res[0][0].cond.shape, res)
+    return res
+
+
+re_AND = re.compile(r"\bAND\b")
+re_weight = re.compile(r"^(.*?)(?:\s*:\s*([-+]?\s*(?:\d+|\d*\.\d+)?))?\s*$")
+
+
+def get_multicond_prompt_list(prompts):
+    res_indexes = []
+
+    prompt_flat_list = []
+    prompt_indexes = {}
+
+    for prompt in prompts:
+        subprompts = re_AND.split(prompt)
+
+        indexes = []
+        for subprompt in subprompts:
+            text, weight = re_weight.search(subprompt).groups()
+
+            weight = float(weight) if weight is not None else 1.0
+
+            index = prompt_indexes.get(text, None)
+            if index is None:
+                index = len(prompt_flat_list)
+                prompt_flat_list.append(text)
+                prompt_indexes[text] = index
+
+            indexes.append((index, weight))
+
+        res_indexes.append(indexes)
+
+    return res_indexes, prompt_flat_list, prompt_indexes
+
+
+class ComposableScheduledPromptConditioning:
+    def __init__(self, schedules, weight=1.0):
+        self.schedules: list[ScheduledPromptConditioning] = schedules
+        self.weight: float = weight
+
+
+class MulticondLearnedConditioning:
+    def __init__(self, shape, batch):
+        self.shape: tuple = shape  # the shape field is needed to send this object to DDIM/PLMS
+        self.batch: list[list[ComposableScheduledPromptConditioning]] = batch
 
 
-def reconstruct_cond_batch(c: ScheduledPromptBatch, current_step):
-    param = c.schedules[0][0].cond
-    res = torch.zeros(c.shape, device=param.device, dtype=param.dtype)
-    for i, cond_schedule in enumerate(c.schedules):
+def get_multicond_learned_conditioning(model, prompts, steps) -> MulticondLearnedConditioning:
+    """same as get_learned_conditioning, but returns a list of ScheduledPromptConditioning along with the weight objects for each prompt.
+    For each prompt, the list is obtained by splitting the prompt using the AND separator.
+
+    https://energy-based-model.github.io/Compositional-Visual-Generation-with-Composable-Diffusion-Models/
+    """
+
+    res_indexes, prompt_flat_list, prompt_indexes = get_multicond_prompt_list(prompts)
+
+    learned_conditioning = get_learned_conditioning(model, prompt_flat_list, steps)
+
+    res = []
+    for indexes in res_indexes:
+        res.append([ComposableScheduledPromptConditioning(learned_conditioning[i], weight) for i, weight in indexes])
+
+    return MulticondLearnedConditioning(shape=(len(prompts),), batch=res)
+
+
+def reconstruct_cond_batch(c: list[list[ScheduledPromptConditioning]], current_step):
+    param = c[0][0].cond
+    res = torch.zeros((len(c),) + param.shape, device=param.device, dtype=param.dtype)
+    for i, cond_schedule in enumerate(c):
         target_index = 0
         for current, (end_at, cond) in enumerate(cond_schedule):
             if current_step <= end_at:
@@ -140,6 +218,30 @@ def reconstruct_cond_batch(c: ScheduledPromptBatch, current_step):
     return res
 
 
+def reconstruct_multicond_batch(c: MulticondLearnedConditioning, current_step):
+    param = c.batch[0][0].schedules[0].cond
+
+    tensors = []
+    conds_list = []
+
+    for batch_no, composable_prompts in enumerate(c.batch):
+        conds_for_batch = []
+
+        for cond_index, composable_prompt in enumerate(composable_prompts):
+            target_index = 0
+            for current, (end_at, cond) in enumerate(composable_prompt.schedules):
+                if current_step <= end_at:
+                    target_index = current
+                    break
+
+            conds_for_batch.append((len(tensors), composable_prompt.weight))
+            tensors.append(composable_prompt.schedules[target_index].cond)
+
+        conds_list.append(conds_for_batch)
+
+    return conds_list, torch.stack(tensors).to(device=param.device, dtype=param.dtype)
+
+
 re_attention = re.compile(r"""
 \\\(|
 \\\)|
diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index dbf570d2..d27c547b 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -109,9 +109,12 @@ class VanillaStableDiffusionSampler:
         return 0
 
     def p_sample_ddim_hook(self, x_dec, cond, ts, unconditional_conditioning, *args, **kwargs):
-        cond = prompt_parser.reconstruct_cond_batch(cond, self.step)
+        conds_list, tensor = prompt_parser.reconstruct_multicond_batch(cond, self.step)
         unconditional_conditioning = prompt_parser.reconstruct_cond_batch(unconditional_conditioning, self.step)
 
+        assert all([len(conds) == 1 for conds in conds_list]), 'composition via AND is not supported for DDIM/PLMS samplers'
+        cond = tensor
+
         if self.mask is not None:
             img_orig = self.sampler.model.q_sample(self.init_latent, ts)
             x_dec = img_orig * self.mask + self.nmask * x_dec
@@ -183,19 +186,31 @@ class CFGDenoiser(torch.nn.Module):
         self.step = 0
 
     def forward(self, x, sigma, uncond, cond, cond_scale):
-        cond = prompt_parser.reconstruct_cond_batch(cond, self.step)
+        conds_list, tensor = prompt_parser.reconstruct_multicond_batch(cond, self.step)
         uncond = prompt_parser.reconstruct_cond_batch(uncond, self.step)
 
+        batch_size = len(conds_list)
+        repeats = [len(conds_list[i]) for i in range(batch_size)]
+
+        x_in = torch.cat([torch.stack([x[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [x])
+        sigma_in = torch.cat([torch.stack([sigma[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [sigma])
+        cond_in = torch.cat([tensor, uncond])
+
         if shared.batch_cond_uncond:
-            x_in = torch.cat([x] * 2)
-            sigma_in = torch.cat([sigma] * 2)
-            cond_in = torch.cat([uncond, cond])
-            uncond, cond = self.inner_model(x_in, sigma_in, cond=cond_in).chunk(2)
-            denoised = uncond + (cond - uncond) * cond_scale
+            x_out = self.inner_model(x_in, sigma_in, cond=cond_in)
         else:
-            uncond = self.inner_model(x, sigma, cond=uncond)
-            cond = self.inner_model(x, sigma, cond=cond)
-            denoised = uncond + (cond - uncond) * cond_scale
+            x_out = torch.zeros_like(x_in)
+            for batch_offset in range(0, x_out.shape[0], batch_size):
+                a = batch_offset
+                b = a + batch_size
+                x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond=cond_in[a:b])
+
+        denoised_uncond = x_out[-batch_size:]
+        denoised = torch.clone(denoised_uncond)
+
+        for i, conds in enumerate(conds_list):
+            for cond_index, weight in conds:
+                denoised[i] += (x_out[cond_index] - denoised_uncond[i]) * (weight * cond_scale)
 
         if self.mask is not None:
             denoised = self.init_latent * self.mask + self.nmask * denoised
diff --git a/modules/ui.py b/modules/ui.py
index 523ab25b..9620350f 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -34,7 +34,7 @@ import modules.gfpgan_model
 import modules.codeformer_model
 import modules.styles
 import modules.generation_parameters_copypaste
-from modules.prompt_parser import get_learned_conditioning_prompt_schedules
+from modules import prompt_parser
 from modules.images import apply_filename_pattern, get_next_sequence_number
 import modules.textual_inversion.ui
 
@@ -394,7 +394,9 @@ def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info:
 
 def update_token_counter(text, steps):
     try:
-        prompt_schedules = get_learned_conditioning_prompt_schedules([text], steps)
+        _, prompt_flat_list, _ = prompt_parser.get_multicond_prompt_list([text])
+        prompt_schedules = prompt_parser.get_learned_conditioning_prompt_schedules(prompt_flat_list, steps)
+
     except Exception:
         # a parsing error can happen here during typing, and we don't want to bother the user with
         # messages related to it in console
-- 
cgit v1.2.3


From 4320f386d9641c7c234589c4cb0c0c6cbeb156ad Mon Sep 17 00:00:00 2001
From: Greendayle <Greendayle>
Date: Wed, 5 Oct 2022 22:39:32 +0200
Subject: removing underscores and colons

---
 modules/deepbooru.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index a64fd9cd..fb5018a6 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -56,7 +56,7 @@ def _load_tf_and_return_tags(pil_image, threshold):
 
     print('\n'.join(sorted(result_tags_print, reverse=True)))
 
-    return ', '.join(result_tags_out)
+    return ', '.join(result_tags_out).replace('_', ' ').replace(':', ' ')
 
 
 def get_deepbooru_tags(pil_image, threshold=0.5):
-- 
cgit v1.2.3


From f8e41a96bb30a04dd5e294c7e1178c1c3b09d481 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 5 Oct 2022 23:52:05 +0300
Subject: fix various float parsing errors

---
 modules/prompt_parser.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py
index f7420daf..800b12c7 100644
--- a/modules/prompt_parser.py
+++ b/modules/prompt_parser.py
@@ -143,8 +143,7 @@ def get_learned_conditioning(model, prompts, steps):
 
 
 re_AND = re.compile(r"\bAND\b")
-re_weight = re.compile(r"^(.*?)(?:\s*:\s*([-+]?\s*(?:\d+|\d*\.\d+)?))?\s*$")
-
+re_weight = re.compile(r"^(.*?)(?:\s*:\s*([-+]?(?:\d+\.?|\d*\.\d+)))?\s*$")
 
 def get_multicond_prompt_list(prompts):
     res_indexes = []
-- 
cgit v1.2.3


From 20f8ec877a99ce2ebf193cb1e2e773cfc77b7c41 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 6 Oct 2022 00:09:32 +0300
Subject: remove type annotations in new code because presumably they don't
 work in 3.7

---
 modules/prompt_parser.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py
index 800b12c7..ee4c5d02 100644
--- a/modules/prompt_parser.py
+++ b/modules/prompt_parser.py
@@ -175,14 +175,14 @@ def get_multicond_prompt_list(prompts):
 
 class ComposableScheduledPromptConditioning:
     def __init__(self, schedules, weight=1.0):
-        self.schedules: list[ScheduledPromptConditioning] = schedules
+        self.schedules = schedules  # : list[ScheduledPromptConditioning]
         self.weight: float = weight
 
 
 class MulticondLearnedConditioning:
     def __init__(self, shape, batch):
         self.shape: tuple = shape  # the shape field is needed to send this object to DDIM/PLMS
-        self.batch: list[list[ComposableScheduledPromptConditioning]] = batch
+        self.batch = batch  # : list[list[ComposableScheduledPromptConditioning]]
 
 
 def get_multicond_learned_conditioning(model, prompts, steps) -> MulticondLearnedConditioning:
@@ -203,7 +203,7 @@ def get_multicond_learned_conditioning(model, prompts, steps) -> MulticondLearne
     return MulticondLearnedConditioning(shape=(len(prompts),), batch=res)
 
 
-def reconstruct_cond_batch(c: list[list[ScheduledPromptConditioning]], current_step):
+def reconstruct_cond_batch(c, current_step):  # c: list[list[ScheduledPromptConditioning]]
     param = c[0][0].cond
     res = torch.zeros((len(c),) + param.shape, device=param.device, dtype=param.dtype)
     for i, cond_schedule in enumerate(c):
-- 
cgit v1.2.3


From 34c358d10d52817f7a889ae4c52096ee654f3fe6 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Wed, 5 Oct 2022 22:11:30 +0100
Subject: use typing.list in prompt_parser.py for wider python version support

---
 modules/prompt_parser.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py
index 800b12c7..fdfa21ae 100644
--- a/modules/prompt_parser.py
+++ b/modules/prompt_parser.py
@@ -1,6 +1,6 @@
 import re
 from collections import namedtuple
-
+from typing import List
 import lark
 
 # a prompt like this: "fantasy landscape with a [mountain:lake:0.25] and [an oak:a christmas tree:0.75][ in foreground::0.6][ in background:0.25] [shoddy:masterful:0.5]"
@@ -175,14 +175,14 @@ def get_multicond_prompt_list(prompts):
 
 class ComposableScheduledPromptConditioning:
     def __init__(self, schedules, weight=1.0):
-        self.schedules: list[ScheduledPromptConditioning] = schedules
+        self.schedules: List[ScheduledPromptConditioning] = schedules
         self.weight: float = weight
 
 
 class MulticondLearnedConditioning:
     def __init__(self, shape, batch):
         self.shape: tuple = shape  # the shape field is needed to send this object to DDIM/PLMS
-        self.batch: list[list[ComposableScheduledPromptConditioning]] = batch
+        self.batch: List[List[ComposableScheduledPromptConditioning]] = batch
 
 
 def get_multicond_learned_conditioning(model, prompts, steps) -> MulticondLearnedConditioning:
@@ -203,7 +203,7 @@ def get_multicond_learned_conditioning(model, prompts, steps) -> MulticondLearne
     return MulticondLearnedConditioning(shape=(len(prompts),), batch=res)
 
 
-def reconstruct_cond_batch(c: list[list[ScheduledPromptConditioning]], current_step):
+def reconstruct_cond_batch(c: List[List[ScheduledPromptConditioning]], current_step):
     param = c[0][0].cond
     res = torch.zeros((len(c),) + param.shape, device=param.device, dtype=param.dtype)
     for i, cond_schedule in enumerate(c):
-- 
cgit v1.2.3


From 55400c981b7c1389482057a35ed6ea11f08da194 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Thu, 6 Oct 2022 03:11:15 +0100
Subject: Set gradio-img2img-tool default to 'editor'

---
 modules/shared.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/shared.py b/modules/shared.py
index e52c9b1d..bab0fe6e 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -55,7 +55,7 @@ parser.add_argument("--hide-ui-dir-config", action='store_true', help="hide dire
 parser.add_argument("--ui-settings-file", type=str, help="filename to use for ui settings", default=os.path.join(script_path, 'config.json'))
 parser.add_argument("--gradio-debug",  action='store_true', help="launch gradio with --debug option")
 parser.add_argument("--gradio-auth", type=str, help='set gradio authentication like "username:password"; or comma-delimit multiple like "u1:p1,u2:p2,u3:p3"', default=None)
-parser.add_argument("--gradio-img2img-tool", type=str, help='gradio image uploader tool: can be either editor for ctopping, or color-sketch for drawing', choices=["color-sketch", "editor"], default="color-sketch")
+parser.add_argument("--gradio-img2img-tool", type=str, help='gradio image uploader tool: can be either editor for ctopping, or color-sketch for drawing', choices=["color-sketch", "editor"], default="editor")
 parser.add_argument("--opt-channelslast", action='store_true', help="change memory type for stable diffusion to channels last")
 parser.add_argument("--styles-file", type=str, help="filename to use for styles", default=os.path.join(script_path, 'styles.csv'))
 parser.add_argument("--autolaunch", action='store_true', help="open the webui URL in the system's default browser upon launch", default=False)
-- 
cgit v1.2.3


From 2499fb4e1910d31ff12c24110f161b20641b8835 Mon Sep 17 00:00:00 2001
From: Raphael Stoeckli <github@rabanti.ch>
Date: Wed, 5 Oct 2022 21:57:18 +0200
Subject: Add sanitizer for captions in Textual inversion

---
 modules/textual_inversion/preprocess.py | 28 ++++++++++++++++++++++++++++
 1 file changed, 28 insertions(+)

diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index f545a993..4f3df4bd 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -1,5 +1,8 @@
+from cmath import log
 import os
 from PIL import Image, ImageOps
+import platform
+import sys
 import tqdm
 
 from modules import shared, images
@@ -25,6 +28,7 @@ def preprocess(process_src, process_dst, process_flip, process_split, process_ca
     def save_pic_with_caption(image, index):
         if process_caption:
             caption = "-" + shared.interrogator.generate_caption(image)
+            caption = sanitize_caption(os.path.join(dst, f"{index:05}-{subindex[0]}"), caption, ".png")
         else:
             caption = filename
             caption = os.path.splitext(caption)[0]
@@ -75,3 +79,27 @@ def preprocess(process_src, process_dst, process_flip, process_split, process_ca
 
     if process_caption:
         shared.interrogator.send_blip_to_ram()
+
+def sanitize_caption(base_path, original_caption, suffix):
+    operating_system = platform.system().lower()
+    if (operating_system == "windows"):
+        invalid_path_characters = "\\/:*?\"<>|"
+        max_path_length = 259
+    else:
+        invalid_path_characters = "/" #linux/macos
+        max_path_length = 1023
+    caption = original_caption
+    for invalid_character in invalid_path_characters:
+        caption = caption.replace(invalid_character, "")
+    fixed_path_length = len(base_path) + len(suffix) 
+    if fixed_path_length + len(caption) <= max_path_length:
+        return caption
+    caption_tokens = caption.split()
+    new_caption = ""
+    for token in caption_tokens:
+        last_caption = new_caption
+        new_caption = new_caption + token + " "
+        if (len(new_caption) + fixed_path_length - 1  > max_path_length):
+            break
+    print(f"\nPath will be too long. Truncated caption: {original_caption}\nto: {last_caption}", file=sys.stderr)
+    return last_caption.strip()
-- 
cgit v1.2.3


From 4288e53fc2ea25fa49715bf5b7f14603553c9e38 Mon Sep 17 00:00:00 2001
From: Raphael Stoeckli <github@rabanti.ch>
Date: Wed, 5 Oct 2022 23:11:32 +0200
Subject: removed unused import, fixed typo

---
 modules/textual_inversion/preprocess.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index 4f3df4bd..f1c002a2 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -1,4 +1,3 @@
-from cmath import log
 import os
 from PIL import Image, ImageOps
 import platform
@@ -13,7 +12,7 @@ def preprocess(process_src, process_dst, process_flip, process_split, process_ca
     src = os.path.abspath(process_src)
     dst = os.path.abspath(process_dst)
 
-    assert src != dst, 'same directory specified as source and desitnation'
+    assert src != dst, 'same directory specified as source and destination'
 
     os.makedirs(dst, exist_ok=True)
 
-- 
cgit v1.2.3


From a93c3ffbfd264ed6b5d989922352300c9d3efbe4 Mon Sep 17 00:00:00 2001
From: Jocke <joakim.lovgren@protonmail.com>
Date: Wed, 5 Oct 2022 16:31:48 +0200
Subject: Outpainting mk2, prevent generation of a completely random image
 every time even when global seed is static

---
 scripts/outpainting_mk_2.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/scripts/outpainting_mk_2.py b/scripts/outpainting_mk_2.py
index 11613ca3..a6468e09 100644
--- a/scripts/outpainting_mk_2.py
+++ b/scripts/outpainting_mk_2.py
@@ -85,8 +85,11 @@ def get_matched_noise(_np_src_image, np_mask_rgb, noise_q=1, color_variation=0.0
     src_dist = np.absolute(src_fft)
     src_phase = src_fft / src_dist
 
+    # create a generator with a static seed to make outpainting deterministic / only follow global seed
+    rng = np.random.default_rng(0)
+
     noise_window = _get_gaussian_window(width, height, mode=1)  # start with simple gaussian noise
-    noise_rgb = np.random.random_sample((width, height, num_channels))
+    noise_rgb = rng.random((width, height, num_channels))
     noise_grey = (np.sum(noise_rgb, axis=2) / 3.)
     noise_rgb *= color_variation  # the colorfulness of the starting noise is blended to greyscale with a parameter
     for c in range(num_channels):
-- 
cgit v1.2.3


From 6e7057b31b9762a9720282c7da486e4f264dee28 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 6 Oct 2022 12:08:06 +0300
Subject: support for downloading new commit hash for git repos

---
 launch.py | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/launch.py b/launch.py
index 57405fea..2f91f586 100644
--- a/launch.py
+++ b/launch.py
@@ -86,6 +86,15 @@ def git_clone(url, dir, name, commithash=None):
     # TODO clone into temporary dir and move if successful
 
     if os.path.exists(dir):
+        if commithash is None:
+            return
+
+        current_hash = run(f'"{git}" -C {dir} rev-parse HEAD', None, "Couldn't determine {name}'s hash: {commithash}").strip()
+        if current_hash == commithash:
+            return
+
+        run(f'"{git}" -C {dir} fetch', f"Fetching updates for {name}...", f"Couldn't fetch {name}")
+        run(f'"{git}" -C {dir} checkout {commithash}', f"Checking out commint for {name} with hash: {commithash}...", f"Couldn't checkout commit {commithash} for {name}")
         return
 
     run(f'"{git}" clone "{url}" "{dir}"', f"Cloning {name} into {dir}...", f"Couldn't clone {name}")
-- 
cgit v1.2.3


From 5f24b7bcf4a074fbdec757617fcd1bc82e76551b Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 6 Oct 2022 12:08:48 +0300
Subject: option to let users select which samplers they want to hide

---
 modules/processing.py  | 13 ++++++-------
 modules/sd_samplers.py | 19 +++++++++++++++++--
 modules/shared.py      | 15 +++++++++------
 webui.py               |  4 +++-
 4 files changed, 35 insertions(+), 16 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index d8c6b8d5..e01c8b3f 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -11,9 +11,8 @@ import cv2
 from skimage import exposure
 
 import modules.sd_hijack
-from modules import devices, prompt_parser, masking
+from modules import devices, prompt_parser, masking, sd_samplers
 from modules.sd_hijack import model_hijack
-from modules.sd_samplers import samplers, samplers_for_img2img
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
 import modules.face_restoration
@@ -110,7 +109,7 @@ class Processed:
         self.width = p.width
         self.height = p.height
         self.sampler_index = p.sampler_index
-        self.sampler = samplers[p.sampler_index].name
+        self.sampler = sd_samplers.samplers[p.sampler_index].name
         self.cfg_scale = p.cfg_scale
         self.steps = p.steps
         self.batch_size = p.batch_size
@@ -265,7 +264,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration
 
     generation_params = {
         "Steps": p.steps,
-        "Sampler": samplers[p.sampler_index].name,
+        "Sampler": sd_samplers.samplers[p.sampler_index].name,
         "CFG scale": p.cfg_scale,
         "Seed": all_seeds[index],
         "Face restoration": (opts.face_restoration_model if p.restore_faces else None),
@@ -478,7 +477,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
             self.firstphase_height_truncated = int(scale * self.height)
 
     def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength):
-        self.sampler = samplers[self.sampler_index].constructor(self.sd_model)
+        self.sampler = sd_samplers.samplers[self.sampler_index].constructor(self.sd_model)
 
         if not self.enable_hr:
             x = create_random_tensors([opt_C, self.height // opt_f, self.width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self)
@@ -521,7 +520,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
 
         shared.state.nextjob()
 
-        self.sampler = samplers[self.sampler_index].constructor(self.sd_model)
+        self.sampler = sd_samplers.samplers[self.sampler_index].constructor(self.sd_model)
         noise = create_random_tensors(samples.shape[1:], seeds=seeds, subseeds=subseeds, subseed_strength=subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self)
 
         # GC now before running the next img2img to prevent running out of memory
@@ -556,7 +555,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
         self.nmask = None
 
     def init(self, all_prompts, all_seeds, all_subseeds):
-        self.sampler = samplers_for_img2img[self.sampler_index].constructor(self.sd_model)
+        self.sampler = sd_samplers.samplers_for_img2img[self.sampler_index].constructor(self.sd_model)
         crop_region = None
 
         if self.image_mask is not None:
diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index d27c547b..2e1f7715 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -32,12 +32,27 @@ samplers_data_k_diffusion = [
     if hasattr(k_diffusion.sampling, funcname)
 ]
 
-samplers = [
+all_samplers = [
     *samplers_data_k_diffusion,
     SamplerData('DDIM', lambda model: VanillaStableDiffusionSampler(ldm.models.diffusion.ddim.DDIMSampler, model), []),
     SamplerData('PLMS', lambda model: VanillaStableDiffusionSampler(ldm.models.diffusion.plms.PLMSSampler, model), []),
 ]
-samplers_for_img2img = [x for x in samplers if x.name not in ['PLMS', 'DPM fast', 'DPM adaptive']]
+
+samplers = []
+samplers_for_img2img = []
+
+
+def set_samplers():
+    global samplers, samplers_for_img2img
+
+    hidden = set(opts.hide_samplers)
+    hidden_img2img = set(opts.hide_samplers + ['PLMS', 'DPM fast', 'DPM adaptive'])
+
+    samplers = [x for x in all_samplers if x.name not in hidden]
+    samplers_for_img2img = [x for x in all_samplers if x.name not in hidden_img2img]
+
+
+set_samplers()
 
 sampler_extra_params = {
     'sample_euler': ['s_churn', 's_tmin', 's_tmax', 's_noise'],
diff --git a/modules/shared.py b/modules/shared.py
index bab0fe6e..ca2e4c74 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -13,6 +13,7 @@ import modules.memmon
 import modules.sd_models
 import modules.styles
 import modules.devices as devices
+from modules import sd_samplers
 from modules.paths import script_path, sd_path
 
 sd_model_file = os.path.join(script_path, 'model.ckpt')
@@ -238,14 +239,16 @@ options_templates.update(options_section(('ui', "User interface"), {
 }))
 
 options_templates.update(options_section(('sampler-params', "Sampler parameters"), {
-  "eta_ddim": OptionInfo(0.0, "eta (noise multiplier) for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
-  "eta_ancestral": OptionInfo(1.0, "eta (noise multiplier) for ancestral samplers", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
-  "ddim_discretize": OptionInfo('uniform', "img2img DDIM discretize", gr.Radio, {"choices": ['uniform', 'quad']}),
-  's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
-  's_tmin':  OptionInfo(0.0, "sigma tmin",  gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
-  's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
+    "hide_samplers": OptionInfo([], "Hide samplers in user interface (requires restart)", gr.CheckboxGroup, lambda: {"choices": [x.name for x in sd_samplers.all_samplers]}),
+    "eta_ddim": OptionInfo(0.0, "eta (noise multiplier) for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
+    "eta_ancestral": OptionInfo(1.0, "eta (noise multiplier) for ancestral samplers", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
+    "ddim_discretize": OptionInfo('uniform', "img2img DDIM discretize", gr.Radio, {"choices": ['uniform', 'quad']}),
+    's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
+    's_tmin':  OptionInfo(0.0, "sigma tmin",  gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
+    's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
 }))
 
+
 class Options:
     data = None
     data_labels = options_templates
diff --git a/webui.py b/webui.py
index 47848ba5..9ef12427 100644
--- a/webui.py
+++ b/webui.py
@@ -2,7 +2,7 @@ import os
 import threading
 import time
 import importlib
-from modules import devices
+from modules import devices, sd_samplers
 from modules.paths import script_path
 import signal
 import threading
@@ -109,6 +109,8 @@ def webui():
                 time.sleep(0.5)
                 break
 
+        sd_samplers.set_samplers()
+
         print('Reloading Custom Scripts')
         modules.scripts.reload_scripts(os.path.join(script_path, "scripts"))
         print('Reloading modules: modules.ui')
-- 
cgit v1.2.3


From 2d3ea42a2d1e909bbccdb6b49561b187c60a9402 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 6 Oct 2022 13:21:12 +0300
Subject: workaround for a mysterious bug where prompt weights can't be matched

---
 modules/prompt_parser.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py
index a7a6aa31..f00256f2 100644
--- a/modules/prompt_parser.py
+++ b/modules/prompt_parser.py
@@ -156,7 +156,9 @@ def get_multicond_prompt_list(prompts):
 
         indexes = []
         for subprompt in subprompts:
-            text, weight = re_weight.search(subprompt).groups()
+            match = re_weight.search(subprompt)
+
+            text, weight = match.groups() if match is not None else (subprompt, 1.0)
 
             weight = float(weight) if weight is not None else 1.0
 
-- 
cgit v1.2.3


From 2a532804957e47bc36c67c8f5b104dcfa8e8f3f0 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 6 Oct 2022 13:21:32 +0300
Subject: reorder imports to fix the bug with k-diffusion on some version

---
 webui.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/webui.py b/webui.py
index 9ef12427..480360fe 100644
--- a/webui.py
+++ b/webui.py
@@ -2,11 +2,12 @@ import os
 import threading
 import time
 import importlib
-from modules import devices, sd_samplers
-from modules.paths import script_path
 import signal
 import threading
 
+from modules.paths import script_path
+
+from modules import devices, sd_samplers
 import modules.codeformer_model as codeformer
 import modules.extras
 import modules.face_restoration
-- 
cgit v1.2.3


From c30c06db207a580d76544fd10fc1e03cd58ce85e Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Mon, 3 Oct 2022 12:48:16 +0300
Subject: update k-diffusion

---
 launch.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/launch.py b/launch.py
index 2f91f586..c2713c64 100644
--- a/launch.py
+++ b/launch.py
@@ -19,7 +19,7 @@ clip_package = os.environ.get('CLIP_PACKAGE', "git+https://github.com/openai/CLI
 
 stable_diffusion_commit_hash = os.environ.get('STABLE_DIFFUSION_COMMIT_HASH', "69ae4b35e0a0f6ee1af8bb9a5d0016ccb27e36dc")
 taming_transformers_commit_hash = os.environ.get('TAMING_TRANSFORMERS_COMMIT_HASH', "24268930bf1dce879235a7fddd0b2355b84d7ea6")
-k_diffusion_commit_hash = os.environ.get('K_DIFFUSION_COMMIT_HASH', "a7ec1974d4ccb394c2dca275f42cd97490618924")
+k_diffusion_commit_hash = os.environ.get('K_DIFFUSION_COMMIT_HASH', "567e11f7062ba20ae32b5a8cd07fb0fc4b9410cf")
 codeformer_commit_hash = os.environ.get('CODEFORMER_COMMIT_HASH', "c5b4593074ba6214284d6acd5f1719b6c5d739af")
 blip_commit_hash = os.environ.get('BLIP_COMMIT_HASH', "48211a1594f1321b00f14c9f7a5b4813144b2fb9")
 
-- 
cgit v1.2.3


From c1a068ed0acc788774afc1541ca69342fd1d94ad Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Mon, 3 Oct 2022 12:49:17 +0300
Subject: Create alternate_sampler_noise_schedules.py

---
 scripts/alternate_sampler_noise_schedules.py | 53 ++++++++++++++++++++++++++++
 1 file changed, 53 insertions(+)
 create mode 100644 scripts/alternate_sampler_noise_schedules.py

diff --git a/scripts/alternate_sampler_noise_schedules.py b/scripts/alternate_sampler_noise_schedules.py
new file mode 100644
index 00000000..4f3ed8fb
--- /dev/null
+++ b/scripts/alternate_sampler_noise_schedules.py
@@ -0,0 +1,53 @@
+import inspect
+from modules.processing import Processed, process_images
+import gradio as gr
+import modules.scripts as scripts
+import k_diffusion.sampling
+import torch
+
+
+class Script(scripts.Script):
+
+    def title(self):
+        return "Alternate Sampler Noise Schedules"
+
+    def ui(self, is_img2img):
+      noise_scheduler = gr.Dropdown(label="Noise Scheduler", choices=['Default','Karras','Exponential', 'Variance Preserving'], value='Default', type="index")
+      sched_smin     = gr.Slider(value=0.1,   label="Sigma min",                  minimum=0.0,   maximum=100.0, step=0.5,)
+      sched_smax     = gr.Slider(value=10.0,  label="Sigma max",                  minimum=0.0,   maximum=100.0, step=0.5)
+      sched_rho      = gr.Slider(value=7.0,   label="Sigma rho (Karras only)",    minimum=7.0,   maximum=100.0, step=0.5)
+      sched_beta_d   = gr.Slider(value=19.9,  label="Beta distribution (VP only)",minimum=0.0,   maximum=40.0, step=0.5)
+      sched_beta_min = gr.Slider(value=0.1,   label="Beta min (VP only)",         minimum=0.0,   maximum=40.0, step=0.1)
+      sched_eps_s    = gr.Slider(value=0.001, label="Epsilon (VP only)",          minimum=0.001, maximum=1.0,   step=0.001)
+
+      return [noise_scheduler, sched_smin, sched_smax, sched_rho, sched_beta_d, sched_beta_min, sched_eps_s]
+
+    def run(self, p, noise_scheduler, sched_smin, sched_smax, sched_rho, sched_beta_d, sched_beta_min, sched_eps_s):
+
+      noise_scheduler_func_name = ['-','get_sigmas_karras','get_sigmas_exponential','get_sigmas_vp'][noise_scheduler]
+
+      base_params = {
+        "sigma_min":sched_smin, 
+        "sigma_max":sched_smax, 
+        "rho":sched_rho, 
+        "beta_d":sched_beta_d, 
+        "beta_min":sched_beta_min, 
+        "eps_s":sched_eps_s,
+        "device":"cuda" if torch.cuda.is_available() else "cpu"
+      }
+
+      if hasattr(k_diffusion.sampling,noise_scheduler_func_name):
+
+        sigma_func  = getattr(k_diffusion.sampling,noise_scheduler_func_name)
+        sigma_func_kwargs = {}
+
+        for k,v in base_params.items():
+          if k in inspect.signature(sigma_func).parameters:
+            sigma_func_kwargs[k] = v
+
+        def substitute_noise_scheduler(n):
+          return sigma_func(n,**sigma_func_kwargs)
+
+        p.sampler_noise_scheduler_override = substitute_noise_scheduler
+
+      return process_images(p)
-- 
cgit v1.2.3


From 71901b3d3bea1d035bf4a7229d19356b4b062151 Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Wed, 5 Oct 2022 14:30:57 +0300
Subject: add karras scheduling variants

---
 modules/sd_samplers.py | 13 +++++++++++++
 1 file changed, 13 insertions(+)

diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index 2e1f7715..8d6eb762 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -26,6 +26,17 @@ samplers_k_diffusion = [
     ('DPM adaptive', 'sample_dpm_adaptive', ['k_dpm_ad']),
 ]
 
+if opts.show_karras_scheduler_variants:
+    k_diffusion.sampling.sample_dpm_2_ka = k_diffusion.sampling.sample_dpm_2
+    k_diffusion.sampling.sample_dpm_2_ancestral_ka = k_diffusion.sampling.sample_dpm_2_ancestral
+    k_diffusion.sampling.sample_lms_ka = k_diffusion.sampling.sample_lms
+    samplers_k_diffusion_ka = [
+        ('LMS K Scheduling', 'sample_lms_ka', ['k_lms_ka']),
+        ('DPM2 K Scheduling', 'sample_dpm_2_ka', ['k_dpm_2_ka']),
+        ('DPM2 a K Scheduling', 'sample_dpm_2_ancestral_ka', ['k_dpm_2_a_ka']),
+    ]
+    samplers_k_diffusion.extend(samplers_k_diffusion_ka)
+
 samplers_data_k_diffusion = [
     SamplerData(label, lambda model, funcname=funcname: KDiffusionSampler(funcname, model), aliases)
     for label, funcname, aliases in samplers_k_diffusion
@@ -345,6 +356,8 @@ class KDiffusionSampler:
 
         if p.sampler_noise_scheduler_override:
           sigmas = p.sampler_noise_scheduler_override(steps)
+        elif self.funcname.endswith('ka'):
+          sigmas = k_diffusion.sampling.get_sigmas_karras(n=steps, sigma_min=0.1, sigma_max=10, device=shared.device)
         else:
           sigmas = self.model_wrap.get_sigmas(steps)
         x = x * sigmas[0]
-- 
cgit v1.2.3


From 3ddf80a9db8793188e2fe9488233d2b272cceb33 Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Wed, 5 Oct 2022 14:31:51 +0300
Subject: add variant setting

---
 modules/shared.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/modules/shared.py b/modules/shared.py
index ca2e4c74..9e4860a2 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -236,6 +236,7 @@ options_templates.update(options_section(('ui', "User interface"), {
     "font": OptionInfo("", "Font for image grids that have text"),
     "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"),
     "js_modal_lightbox_initialy_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),
+    "show_karras_scheduler_variants": OptionInfo(True, "Show Karras scheduling variants for select samplers. Try these variants if your K sampled images suffer from excessive noise."),
 }))
 
 options_templates.update(options_section(('sampler-params', "Sampler parameters"), {
-- 
cgit v1.2.3


From a971e4a767118ec41ec0f129770122babfb16a16 Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Thu, 6 Oct 2022 13:34:42 +0300
Subject: update k-diff once again

---
 launch.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/launch.py b/launch.py
index c2713c64..9fe0fd67 100644
--- a/launch.py
+++ b/launch.py
@@ -19,7 +19,7 @@ clip_package = os.environ.get('CLIP_PACKAGE', "git+https://github.com/openai/CLI
 
 stable_diffusion_commit_hash = os.environ.get('STABLE_DIFFUSION_COMMIT_HASH', "69ae4b35e0a0f6ee1af8bb9a5d0016ccb27e36dc")
 taming_transformers_commit_hash = os.environ.get('TAMING_TRANSFORMERS_COMMIT_HASH', "24268930bf1dce879235a7fddd0b2355b84d7ea6")
-k_diffusion_commit_hash = os.environ.get('K_DIFFUSION_COMMIT_HASH', "567e11f7062ba20ae32b5a8cd07fb0fc4b9410cf")
+k_diffusion_commit_hash = os.environ.get('K_DIFFUSION_COMMIT_HASH', "f4e99857772fc3a126ba886aadf795a332774878")
 codeformer_commit_hash = os.environ.get('CODEFORMER_COMMIT_HASH', "c5b4593074ba6214284d6acd5f1719b6c5d739af")
 blip_commit_hash = os.environ.get('BLIP_COMMIT_HASH', "48211a1594f1321b00f14c9f7a5b4813144b2fb9")
 
-- 
cgit v1.2.3


From 5993df24a1026225cb8af89237547c1d9101ce69 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 6 Oct 2022 14:12:52 +0300
Subject: integrate the new samplers PR

---
 modules/processing.py                        |  7 ++--
 modules/sd_samplers.py                       | 59 +++++++++++++++-------------
 modules/shared.py                            |  1 -
 scripts/alternate_sampler_noise_schedules.py | 53 -------------------------
 scripts/img2imgalt.py                        |  3 +-
 5 files changed, 36 insertions(+), 87 deletions(-)
 delete mode 100644 scripts/alternate_sampler_noise_schedules.py

diff --git a/modules/processing.py b/modules/processing.py
index e01c8b3f..e567956c 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -477,7 +477,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
             self.firstphase_height_truncated = int(scale * self.height)
 
     def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength):
-        self.sampler = sd_samplers.samplers[self.sampler_index].constructor(self.sd_model)
+        self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers, self.sampler_index, self.sd_model)
 
         if not self.enable_hr:
             x = create_random_tensors([opt_C, self.height // opt_f, self.width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self)
@@ -520,7 +520,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
 
         shared.state.nextjob()
 
-        self.sampler = sd_samplers.samplers[self.sampler_index].constructor(self.sd_model)
+        self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers, self.sampler_index, self.sd_model)
+
         noise = create_random_tensors(samples.shape[1:], seeds=seeds, subseeds=subseeds, subseed_strength=subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self)
 
         # GC now before running the next img2img to prevent running out of memory
@@ -555,7 +556,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
         self.nmask = None
 
     def init(self, all_prompts, all_seeds, all_subseeds):
-        self.sampler = sd_samplers.samplers_for_img2img[self.sampler_index].constructor(self.sd_model)
+        self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers_for_img2img, self.sampler_index, self.sd_model)
         crop_region = None
 
         if self.image_mask is not None:
diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index 8d6eb762..497df943 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -13,46 +13,46 @@ from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
 
 
-SamplerData = namedtuple('SamplerData', ['name', 'constructor', 'aliases'])
+SamplerData = namedtuple('SamplerData', ['name', 'constructor', 'aliases', 'options'])
 
 samplers_k_diffusion = [
-    ('Euler a', 'sample_euler_ancestral', ['k_euler_a']),
-    ('Euler', 'sample_euler', ['k_euler']),
-    ('LMS', 'sample_lms', ['k_lms']),
-    ('Heun', 'sample_heun', ['k_heun']),
-    ('DPM2', 'sample_dpm_2', ['k_dpm_2']),
-    ('DPM2 a', 'sample_dpm_2_ancestral', ['k_dpm_2_a']),
-    ('DPM fast', 'sample_dpm_fast', ['k_dpm_fast']),
-    ('DPM adaptive', 'sample_dpm_adaptive', ['k_dpm_ad']),
+    ('Euler a', 'sample_euler_ancestral', ['k_euler_a'], {}),
+    ('Euler', 'sample_euler', ['k_euler'], {}),
+    ('LMS', 'sample_lms', ['k_lms'], {}),
+    ('Heun', 'sample_heun', ['k_heun'], {}),
+    ('DPM2', 'sample_dpm_2', ['k_dpm_2'], {}),
+    ('DPM2 a', 'sample_dpm_2_ancestral', ['k_dpm_2_a'], {}),
+    ('DPM fast', 'sample_dpm_fast', ['k_dpm_fast'], {}),
+    ('DPM adaptive', 'sample_dpm_adaptive', ['k_dpm_ad'], {}),
+    ('LMS Karras', 'sample_lms', ['k_lms_ka'], {'scheduler': 'karras'}),
+    ('DPM2 Karras', 'sample_dpm_2', ['k_dpm_2_ka'], {'scheduler': 'karras'}),
+    ('DPM2 a Karras', 'sample_dpm_2_ancestral', ['k_dpm_2_a_ka'], {'scheduler': 'karras'}),
 ]
 
-if opts.show_karras_scheduler_variants:
-    k_diffusion.sampling.sample_dpm_2_ka = k_diffusion.sampling.sample_dpm_2
-    k_diffusion.sampling.sample_dpm_2_ancestral_ka = k_diffusion.sampling.sample_dpm_2_ancestral
-    k_diffusion.sampling.sample_lms_ka = k_diffusion.sampling.sample_lms
-    samplers_k_diffusion_ka = [
-        ('LMS K Scheduling', 'sample_lms_ka', ['k_lms_ka']),
-        ('DPM2 K Scheduling', 'sample_dpm_2_ka', ['k_dpm_2_ka']),
-        ('DPM2 a K Scheduling', 'sample_dpm_2_ancestral_ka', ['k_dpm_2_a_ka']),
-    ]
-    samplers_k_diffusion.extend(samplers_k_diffusion_ka)
-
 samplers_data_k_diffusion = [
-    SamplerData(label, lambda model, funcname=funcname: KDiffusionSampler(funcname, model), aliases)
-    for label, funcname, aliases in samplers_k_diffusion
+    SamplerData(label, lambda model, funcname=funcname: KDiffusionSampler(funcname, model), aliases, options)
+    for label, funcname, aliases, options in samplers_k_diffusion
     if hasattr(k_diffusion.sampling, funcname)
 ]
 
 all_samplers = [
     *samplers_data_k_diffusion,
-    SamplerData('DDIM', lambda model: VanillaStableDiffusionSampler(ldm.models.diffusion.ddim.DDIMSampler, model), []),
-    SamplerData('PLMS', lambda model: VanillaStableDiffusionSampler(ldm.models.diffusion.plms.PLMSSampler, model), []),
+    SamplerData('DDIM', lambda model: VanillaStableDiffusionSampler(ldm.models.diffusion.ddim.DDIMSampler, model), [], {}),
+    SamplerData('PLMS', lambda model: VanillaStableDiffusionSampler(ldm.models.diffusion.plms.PLMSSampler, model), [], {}),
 ]
 
 samplers = []
 samplers_for_img2img = []
 
 
+def create_sampler_with_index(list_of_configs, index, model):
+    config = list_of_configs[index]
+    sampler = config.constructor(model)
+    sampler.config = config
+    
+    return sampler
+
+
 def set_samplers():
     global samplers, samplers_for_img2img
 
@@ -130,6 +130,7 @@ class VanillaStableDiffusionSampler:
         self.step = 0
         self.eta = None
         self.default_eta = 0.0
+        self.config = None
 
     def number_of_needed_noises(self, p):
         return 0
@@ -291,6 +292,7 @@ class KDiffusionSampler:
         self.stop_at = None
         self.eta = None
         self.default_eta = 1.0
+        self.config = None
 
     def callback_state(self, d):
         store_latent(d["denoised"])
@@ -355,11 +357,12 @@ class KDiffusionSampler:
         steps = steps or p.steps
 
         if p.sampler_noise_scheduler_override:
-          sigmas = p.sampler_noise_scheduler_override(steps)
-        elif self.funcname.endswith('ka'):
-          sigmas = k_diffusion.sampling.get_sigmas_karras(n=steps, sigma_min=0.1, sigma_max=10, device=shared.device)
+            sigmas = p.sampler_noise_scheduler_override(steps)
+        elif self.config is not None and self.config.options.get('scheduler', None) == 'karras':
+            sigmas = k_diffusion.sampling.get_sigmas_karras(n=steps, sigma_min=0.1, sigma_max=10, device=shared.device)
         else:
-          sigmas = self.model_wrap.get_sigmas(steps)
+            sigmas = self.model_wrap.get_sigmas(steps)
+
         x = x * sigmas[0]
 
         extra_params_kwargs = self.initialize(p)
diff --git a/modules/shared.py b/modules/shared.py
index 9e4860a2..ca2e4c74 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -236,7 +236,6 @@ options_templates.update(options_section(('ui', "User interface"), {
     "font": OptionInfo("", "Font for image grids that have text"),
     "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"),
     "js_modal_lightbox_initialy_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),
-    "show_karras_scheduler_variants": OptionInfo(True, "Show Karras scheduling variants for select samplers. Try these variants if your K sampled images suffer from excessive noise."),
 }))
 
 options_templates.update(options_section(('sampler-params', "Sampler parameters"), {
diff --git a/scripts/alternate_sampler_noise_schedules.py b/scripts/alternate_sampler_noise_schedules.py
deleted file mode 100644
index 4f3ed8fb..00000000
--- a/scripts/alternate_sampler_noise_schedules.py
+++ /dev/null
@@ -1,53 +0,0 @@
-import inspect
-from modules.processing import Processed, process_images
-import gradio as gr
-import modules.scripts as scripts
-import k_diffusion.sampling
-import torch
-
-
-class Script(scripts.Script):
-
-    def title(self):
-        return "Alternate Sampler Noise Schedules"
-
-    def ui(self, is_img2img):
-      noise_scheduler = gr.Dropdown(label="Noise Scheduler", choices=['Default','Karras','Exponential', 'Variance Preserving'], value='Default', type="index")
-      sched_smin     = gr.Slider(value=0.1,   label="Sigma min",                  minimum=0.0,   maximum=100.0, step=0.5,)
-      sched_smax     = gr.Slider(value=10.0,  label="Sigma max",                  minimum=0.0,   maximum=100.0, step=0.5)
-      sched_rho      = gr.Slider(value=7.0,   label="Sigma rho (Karras only)",    minimum=7.0,   maximum=100.0, step=0.5)
-      sched_beta_d   = gr.Slider(value=19.9,  label="Beta distribution (VP only)",minimum=0.0,   maximum=40.0, step=0.5)
-      sched_beta_min = gr.Slider(value=0.1,   label="Beta min (VP only)",         minimum=0.0,   maximum=40.0, step=0.1)
-      sched_eps_s    = gr.Slider(value=0.001, label="Epsilon (VP only)",          minimum=0.001, maximum=1.0,   step=0.001)
-
-      return [noise_scheduler, sched_smin, sched_smax, sched_rho, sched_beta_d, sched_beta_min, sched_eps_s]
-
-    def run(self, p, noise_scheduler, sched_smin, sched_smax, sched_rho, sched_beta_d, sched_beta_min, sched_eps_s):
-
-      noise_scheduler_func_name = ['-','get_sigmas_karras','get_sigmas_exponential','get_sigmas_vp'][noise_scheduler]
-
-      base_params = {
-        "sigma_min":sched_smin, 
-        "sigma_max":sched_smax, 
-        "rho":sched_rho, 
-        "beta_d":sched_beta_d, 
-        "beta_min":sched_beta_min, 
-        "eps_s":sched_eps_s,
-        "device":"cuda" if torch.cuda.is_available() else "cpu"
-      }
-
-      if hasattr(k_diffusion.sampling,noise_scheduler_func_name):
-
-        sigma_func  = getattr(k_diffusion.sampling,noise_scheduler_func_name)
-        sigma_func_kwargs = {}
-
-        for k,v in base_params.items():
-          if k in inspect.signature(sigma_func).parameters:
-            sigma_func_kwargs[k] = v
-
-        def substitute_noise_scheduler(n):
-          return sigma_func(n,**sigma_func_kwargs)
-
-        p.sampler_noise_scheduler_override = substitute_noise_scheduler
-
-      return process_images(p)
diff --git a/scripts/img2imgalt.py b/scripts/img2imgalt.py
index 0ef137f7..f9894cb0 100644
--- a/scripts/img2imgalt.py
+++ b/scripts/img2imgalt.py
@@ -8,7 +8,6 @@ import gradio as gr
 
 from modules import processing, shared, sd_samplers, prompt_parser
 from modules.processing import Processed
-from modules.sd_samplers import samplers
 from modules.shared import opts, cmd_opts, state
 
 import torch
@@ -159,7 +158,7 @@ class Script(scripts.Script):
             
             combined_noise = ((1 - randomness) * rec_noise + randomness * rand_noise) / ((randomness**2 + (1-randomness)**2) ** 0.5)
             
-            sampler = samplers[p.sampler_index].constructor(p.sd_model)
+            sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers, p.sampler_index, p.sd_model)
 
             sigmas = sampler.model_wrap.get_sigmas(p.steps)
             
-- 
cgit v1.2.3


From f5490674a8fd84162b4e80c045e675633afb9ee7 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 6 Oct 2022 17:41:49 +0300
Subject: fix bad output for error when updating a git repo

---
 launch.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/launch.py b/launch.py
index 9fe0fd67..75edb66a 100644
--- a/launch.py
+++ b/launch.py
@@ -89,7 +89,7 @@ def git_clone(url, dir, name, commithash=None):
         if commithash is None:
             return
 
-        current_hash = run(f'"{git}" -C {dir} rev-parse HEAD', None, "Couldn't determine {name}'s hash: {commithash}").strip()
+        current_hash = run(f'"{git}" -C {dir} rev-parse HEAD', None, f"Couldn't determine {name}'s hash: {commithash}").strip()
         if current_hash == commithash:
             return
 
-- 
cgit v1.2.3


From be71115b1a1201d04f0e2a11e718fb31cbd26474 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Thu, 6 Oct 2022 01:09:44 +0100
Subject: Update shared.py

---
 modules/shared.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/modules/shared.py b/modules/shared.py
index ca2e4c74..9f7c6efe 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -236,6 +236,7 @@ options_templates.update(options_section(('ui', "User interface"), {
     "font": OptionInfo("", "Font for image grids that have text"),
     "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"),
     "js_modal_lightbox_initialy_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),
+    "show_progress_in_title": OptionInfo(False, "Show generation progress in window title."),
 }))
 
 options_templates.update(options_section(('sampler-params', "Sampler parameters"), {
-- 
cgit v1.2.3


From c06298d1d003aa034007978ee7508af636c18124 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Thu, 6 Oct 2022 01:10:38 +0100
Subject: add check for progress in title setting

---
 javascript/progressbar.js | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/javascript/progressbar.js b/javascript/progressbar.js
index 3e3220c3..f9e9290e 100644
--- a/javascript/progressbar.js
+++ b/javascript/progressbar.js
@@ -5,7 +5,7 @@ function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_inte
     var progressbar = gradioApp().getElementById(id_progressbar)
     var interrupt = gradioApp().getElementById(id_interrupt)
     
-    if(progressbar && progressbar.offsetParent){
+    if(opts.show_progress_in_title && progressbar && progressbar.offsetParent){
         if(progressbar.innerText){
             let newtitle = 'Stable Diffusion - ' + progressbar.innerText
             if(document.title != newtitle){
-- 
cgit v1.2.3


From fec71e4de24b65b0f205a3c071b71651bbcb0dfc Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Thu, 6 Oct 2022 01:35:07 +0100
Subject: Default window title progress updates on

---
 modules/shared.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/shared.py b/modules/shared.py
index 9f7c6efe..5c16f025 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -236,7 +236,7 @@ options_templates.update(options_section(('ui', "User interface"), {
     "font": OptionInfo("", "Font for image grids that have text"),
     "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"),
     "js_modal_lightbox_initialy_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),
-    "show_progress_in_title": OptionInfo(False, "Show generation progress in window title."),
+    "show_progress_in_title": OptionInfo(True, "Show generation progress in window title."),
 }))
 
 options_templates.update(options_section(('sampler-params', "Sampler parameters"), {
-- 
cgit v1.2.3


From 5d0e6ab8567bda2ee8f5ed31f332ca07c1b84b98 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Thu, 6 Oct 2022 04:04:50 +0100
Subject: Allow escaping of commas in xy_grid

---
 scripts/xy_grid.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 1237e754..210829a7 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -168,6 +168,7 @@ re_range_float = re.compile(r"\s*([+-]?\s*\d+(?:.\d*)?)\s*-\s*([+-]?\s*\d+(?:.\d
 re_range_count = re.compile(r"\s*([+-]?\s*\d+)\s*-\s*([+-]?\s*\d+)(?:\s*\[(\d+)\s*\])?\s*")
 re_range_count_float = re.compile(r"\s*([+-]?\s*\d+(?:.\d*)?)\s*-\s*([+-]?\s*\d+(?:.\d*)?)(?:\s*\[(\d+(?:.\d*)?)\s*\])?\s*")
 
+re_non_escaped_comma = re.compile(r"(?<!\\),")
 
 class Script(scripts.Script):
     def title(self):
@@ -197,7 +198,7 @@ class Script(scripts.Script):
             if opt.label == 'Nothing':
                 return [0]
 
-            valslist = [x.strip() for x in vals.split(",")]
+            valslist = [x.replace('\\,',',').strip() for x in re_non_escaped_comma.split(vals)]
 
             if opt.type == int:
                 valslist_ext = []
-- 
cgit v1.2.3


From efa61d31682fb589956cbffa60243d68d9a0daa7 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Thu, 6 Oct 2022 11:55:21 +0100
Subject: use csv.reader

---
 scripts/xy_grid.py | 9 ++++-----
 1 file changed, 4 insertions(+), 5 deletions(-)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 210829a7..1a625898 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -1,8 +1,9 @@
 from collections import namedtuple
 from copy import copy
-from itertools import permutations
+from itertools import permutations, chain
 import random
-
+import csv
+from io import StringIO
 from PIL import Image
 import numpy as np
 
@@ -168,8 +169,6 @@ re_range_float = re.compile(r"\s*([+-]?\s*\d+(?:.\d*)?)\s*-\s*([+-]?\s*\d+(?:.\d
 re_range_count = re.compile(r"\s*([+-]?\s*\d+)\s*-\s*([+-]?\s*\d+)(?:\s*\[(\d+)\s*\])?\s*")
 re_range_count_float = re.compile(r"\s*([+-]?\s*\d+(?:.\d*)?)\s*-\s*([+-]?\s*\d+(?:.\d*)?)(?:\s*\[(\d+(?:.\d*)?)\s*\])?\s*")
 
-re_non_escaped_comma = re.compile(r"(?<!\\),")
-
 class Script(scripts.Script):
     def title(self):
         return "X/Y plot"
@@ -198,7 +197,7 @@ class Script(scripts.Script):
             if opt.label == 'Nothing':
                 return [0]
 
-            valslist = [x.replace('\\,',',').strip() for x in re_non_escaped_comma.split(vals)]
+            valslist = list(chain.from_iterable(csv.reader(StringIO(s))))
 
             if opt.type == int:
                 valslist_ext = []
-- 
cgit v1.2.3


From fd9e0491681c027bd62267fef4b632d12af7af3b Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Thu, 6 Oct 2022 12:32:17 +0100
Subject: strip() split comma delimited lines

---
 scripts/xy_grid.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 1a625898..ec27e58b 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -197,7 +197,7 @@ class Script(scripts.Script):
             if opt.label == 'Nothing':
                 return [0]
 
-            valslist = list(chain.from_iterable(csv.reader(StringIO(s))))
+            valslist = list(map(str.strip,chain.from_iterable(csv.reader(StringIO(s)))))
 
             if opt.type == int:
                 valslist_ext = []
-- 
cgit v1.2.3


From 82eb8ea452b1e63535c58d15ec6db2ad2342faa8 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Thu, 6 Oct 2022 15:22:51 +0100
Subject: Update xy_grid.py

split vals not 's' from tests
---
 scripts/xy_grid.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index ec27e58b..210c7b6e 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -197,7 +197,7 @@ class Script(scripts.Script):
             if opt.label == 'Nothing':
                 return [0]
 
-            valslist = list(map(str.strip,chain.from_iterable(csv.reader(StringIO(s)))))
+            valslist = list(map(str.strip,chain.from_iterable(csv.reader(StringIO(vals)))))
 
             if opt.type == int:
                 valslist_ext = []
-- 
cgit v1.2.3


From 0bb458f0ca06a7be27cf1a1003c536d1f06a5bd3 Mon Sep 17 00:00:00 2001
From: Milly <milly.ca@gmail.com>
Date: Wed, 5 Oct 2022 01:19:50 +0900
Subject: Removed duplicate image saving codes

Use `modules.images.save_image()` instead.
---
 modules/images.py |  7 ++++---
 modules/ui.py     | 46 ++++++++++------------------------------------
 2 files changed, 14 insertions(+), 39 deletions(-)

diff --git a/modules/images.py b/modules/images.py
index c2fadab9..810f1446 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -353,7 +353,7 @@ def get_next_sequence_number(path, basename):
     return result + 1
 
 
-def save_image(image, path, basename, seed=None, prompt=None, extension='png', info=None, short_filename=False, no_prompt=False, grid=False, pnginfo_section_name='parameters', p=None, existing_info=None, forced_filename=None, suffix=""):
+def save_image(image, path, basename, seed=None, prompt=None, extension='png', info=None, short_filename=False, no_prompt=False, grid=False, pnginfo_section_name='parameters', p=None, existing_info=None, forced_filename=None, suffix="", save_to_dirs=None):
     if short_filename or prompt is None or seed is None:
         file_decoration = ""
     elif opts.save_to_dirs:
@@ -377,7 +377,8 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i
     else:
         pnginfo = None
 
-    save_to_dirs = (grid and opts.grid_save_to_dirs) or (not grid and opts.save_to_dirs and not no_prompt)
+    if save_to_dirs is None:
+        save_to_dirs = (grid and opts.grid_save_to_dirs) or (not grid and opts.save_to_dirs and not no_prompt)
 
     if save_to_dirs:
         dirname = apply_filename_pattern(opts.directories_filename_pattern or "[prompt_words]", p, seed, prompt).strip('\\ /')
@@ -431,4 +432,4 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i
         with open(f"{fullfn_without_extension}.txt", "w", encoding="utf8") as file:
             file.write(info + "\n")
 
-
+    return fullfn
diff --git a/modules/ui.py b/modules/ui.py
index 9620350f..4f18126f 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -35,7 +35,7 @@ import modules.codeformer_model
 import modules.styles
 import modules.generation_parameters_copypaste
 from modules import prompt_parser
-from modules.images import apply_filename_pattern, get_next_sequence_number
+from modules.images import save_image
 import modules.textual_inversion.ui
 
 # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the bowser will not show any UI
@@ -114,20 +114,13 @@ def save_files(js_data, images, index):
     p = MyObject(data)
     path = opts.outdir_save
     save_to_dirs = opts.use_save_to_dirs_for_ui
-
-    if save_to_dirs:
-        dirname = apply_filename_pattern(opts.directories_filename_pattern or "[prompt_words]", p, p.seed, p.prompt)
-        path = os.path.join(opts.outdir_save, dirname)
-
-    os.makedirs(path, exist_ok=True)
-  
+    extension: str = opts.samples_format
+    start_index = 0
 
     if index > -1 and opts.save_selected_only and (index >= data["index_of_first_image"]):  # ensures we are looking at a specific non-grid picture, and we have save_selected_only
 
         images = [images[index]]
-        infotexts = [data["infotexts"][index]]
-    else:
-        infotexts = data["infotexts"]
+        start_index = index
 
     with open(os.path.join(opts.outdir_save, "log.csv"), "a", encoding="utf8", newline='') as file:
         at_start = file.tell() == 0
@@ -135,37 +128,18 @@ def save_files(js_data, images, index):
         if at_start:
             writer.writerow(["prompt", "seed", "width", "height", "sampler", "cfgs", "steps", "filename", "negative_prompt"])
 
-        file_decoration = opts.samples_filename_pattern or "[seed]-[prompt_spaces]"
-        if file_decoration != "":
-            file_decoration = "-" + file_decoration.lower()
-        file_decoration = apply_filename_pattern(file_decoration, p, p.seed, p.prompt)
-        truncated = (file_decoration[:240] + '..') if len(file_decoration) > 240 else file_decoration
-        filename_base = truncated
-        extension = opts.samples_format.lower()
-
-        basecount = get_next_sequence_number(path, "")
-        for i, filedata in enumerate(images):
-            file_number = f"{basecount+i:05}"
-            filename = file_number + filename_base + f".{extension}"
-            filepath = os.path.join(path, filename)
-
-
+        for image_index, filedata in enumerate(images, start_index):
             if filedata.startswith("data:image/png;base64,"):
                 filedata = filedata[len("data:image/png;base64,"):]
 
             image = Image.open(io.BytesIO(base64.decodebytes(filedata.encode('utf-8'))))
-            if opts.enable_pnginfo and extension == 'png':
-                pnginfo = PngImagePlugin.PngInfo()
-                pnginfo.add_text('parameters', infotexts[i])
-                image.save(filepath, pnginfo=pnginfo)
-            else:
-                image.save(filepath, quality=opts.jpeg_quality)
 
-            if opts.enable_pnginfo and extension in ("jpg", "jpeg", "webp"):
-                piexif.insert(piexif.dump({"Exif": {
-                    piexif.ExifIFD.UserComment: piexif.helper.UserComment.dump(infotexts[i], encoding="unicode")
-                }}), filepath)
+            is_grid = image_index < p.index_of_first_image
+            i = 0 if is_grid else (image_index - p.index_of_first_image)
+
+            fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
 
+            filename = os.path.relpath(fullfn, path)
             filenames.append(filename)
 
         writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]])
-- 
cgit v1.2.3


From 1069ec49a35d04c1e85c92534e92a2d6aa59cb75 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 6 Oct 2022 20:16:21 +0300
Subject: revert back to using list comprehension rather than list and map

---
 scripts/xy_grid.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 210c7b6e..6344e612 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -197,7 +197,7 @@ class Script(scripts.Script):
             if opt.label == 'Nothing':
                 return [0]
 
-            valslist = list(map(str.strip,chain.from_iterable(csv.reader(StringIO(vals)))))
+            valslist = [x.strip() for x in chain.from_iterable(csv.reader(StringIO(vals)))]
 
             if opt.type == int:
                 valslist_ext = []
-- 
cgit v1.2.3


From dbc8a4d35129b08eab30776bbbaf3a2e7ac10a6c Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 6 Oct 2022 20:27:50 +0300
Subject: add generation parameters to images shown in web ui

---
 modules/processing.py | 8 ++++++--
 1 file changed, 6 insertions(+), 2 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index de818d5b..8faf9095 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -430,7 +430,9 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
                 if opts.samples_save and not p.do_not_save_samples:
                     images.save_image(image, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p)
 
-                infotexts.append(infotext(n, i))
+                text = infotext(n, i)
+                infotexts.append(text)
+                image.info["parameters"] = text
                 output_images.append(image)
 
             del x_samples_ddim 
@@ -447,7 +449,9 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
             grid = images.image_grid(output_images, p.batch_size)
 
             if opts.return_grid:
-                infotexts.insert(0, infotext())
+                text = infotext()
+                infotexts.insert(0, text)
+                grid.info["parameters"] = text
                 output_images.insert(0, grid)
                 index_of_first_image = 1
 
-- 
cgit v1.2.3


From cf7c784fcc0c84a8a4edd8d3aca4dda4c7025c43 Mon Sep 17 00:00:00 2001
From: Milly <milly.ca@gmail.com>
Date: Fri, 7 Oct 2022 00:19:52 +0900
Subject: Removed duplicate defined models_path

Use `modules.paths.models_path` instead `modules.shared.model_path`.
---
 modules/shared.py | 19 +++++++++----------
 1 file changed, 9 insertions(+), 10 deletions(-)

diff --git a/modules/shared.py b/modules/shared.py
index 5c16f025..25bb6e6c 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -14,11 +14,10 @@ import modules.sd_models
 import modules.styles
 import modules.devices as devices
 from modules import sd_samplers
-from modules.paths import script_path, sd_path
+from modules.paths import models_path, script_path, sd_path
 
 sd_model_file = os.path.join(script_path, 'model.ckpt')
 default_sd_model_file = sd_model_file
-model_path = os.path.join(script_path, 'models')
 parser = argparse.ArgumentParser()
 parser.add_argument("--config", type=str, default=os.path.join(sd_path, "configs/stable-diffusion/v1-inference.yaml"), help="path to config which constructs model",)
 parser.add_argument("--ckpt", type=str, default=sd_model_file, help="path to checkpoint of stable diffusion model; if specified, this checkpoint will be added to the list of checkpoints and loaded",)
@@ -36,14 +35,14 @@ parser.add_argument("--always-batch-cond-uncond", action='store_true', help="dis
 parser.add_argument("--unload-gfpgan", action='store_true', help="does not do anything.")
 parser.add_argument("--precision", type=str, help="evaluate at this precision", choices=["full", "autocast"], default="autocast")
 parser.add_argument("--share", action='store_true', help="use share=True for gradio and make the UI accessible through their site (doesn't work for me but you might have better luck)")
-parser.add_argument("--codeformer-models-path", type=str, help="Path to directory with codeformer model file(s).", default=os.path.join(model_path, 'Codeformer'))
-parser.add_argument("--gfpgan-models-path", type=str, help="Path to directory with GFPGAN model file(s).", default=os.path.join(model_path, 'GFPGAN'))
-parser.add_argument("--esrgan-models-path", type=str, help="Path to directory with ESRGAN model file(s).", default=os.path.join(model_path, 'ESRGAN'))
-parser.add_argument("--bsrgan-models-path", type=str, help="Path to directory with BSRGAN model file(s).", default=os.path.join(model_path, 'BSRGAN'))
-parser.add_argument("--realesrgan-models-path", type=str, help="Path to directory with RealESRGAN model file(s).", default=os.path.join(model_path, 'RealESRGAN'))
-parser.add_argument("--scunet-models-path", type=str, help="Path to directory with ScuNET model file(s).", default=os.path.join(model_path, 'ScuNET'))
-parser.add_argument("--swinir-models-path", type=str, help="Path to directory with SwinIR model file(s).", default=os.path.join(model_path, 'SwinIR'))
-parser.add_argument("--ldsr-models-path", type=str, help="Path to directory with LDSR model file(s).", default=os.path.join(model_path, 'LDSR'))
+parser.add_argument("--codeformer-models-path", type=str, help="Path to directory with codeformer model file(s).", default=os.path.join(models_path, 'Codeformer'))
+parser.add_argument("--gfpgan-models-path", type=str, help="Path to directory with GFPGAN model file(s).", default=os.path.join(models_path, 'GFPGAN'))
+parser.add_argument("--esrgan-models-path", type=str, help="Path to directory with ESRGAN model file(s).", default=os.path.join(models_path, 'ESRGAN'))
+parser.add_argument("--bsrgan-models-path", type=str, help="Path to directory with BSRGAN model file(s).", default=os.path.join(models_path, 'BSRGAN'))
+parser.add_argument("--realesrgan-models-path", type=str, help="Path to directory with RealESRGAN model file(s).", default=os.path.join(models_path, 'RealESRGAN'))
+parser.add_argument("--scunet-models-path", type=str, help="Path to directory with ScuNET model file(s).", default=os.path.join(models_path, 'ScuNET'))
+parser.add_argument("--swinir-models-path", type=str, help="Path to directory with SwinIR model file(s).", default=os.path.join(models_path, 'SwinIR'))
+parser.add_argument("--ldsr-models-path", type=str, help="Path to directory with LDSR model file(s).", default=os.path.join(models_path, 'LDSR'))
 parser.add_argument("--opt-split-attention", action='store_true', help="force-enables cross-attention layer optimization. By default, it's on for torch.cuda and off for other torch devices.")
 parser.add_argument("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization")
 parser.add_argument("--opt-split-attention-v1", action='store_true', help="enable older version of split attention optimization that does not consume all the VRAM it can find")
-- 
cgit v1.2.3


From 070b7d60cf5dac6387b3bfc8f3b3977b620e4fd5 Mon Sep 17 00:00:00 2001
From: Milly <milly.ca@gmail.com>
Date: Wed, 5 Oct 2022 02:13:09 +0900
Subject: Added styles to Processed

So `[styles]` pattern can use in saving image UI.
---
 modules/images.py     | 7 +------
 modules/processing.py | 2 ++
 2 files changed, 3 insertions(+), 6 deletions(-)

diff --git a/modules/images.py b/modules/images.py
index 810f1446..fa0714fd 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -292,12 +292,7 @@ def apply_filename_pattern(x, p, seed, prompt):
         x = x.replace("[cfg]", str(p.cfg_scale))
         x = x.replace("[width]", str(p.width))
         x = x.replace("[height]", str(p.height))
-
-        #currently disabled if using the save button, will work otherwise
-        # if enabled it will cause a bug because styles is not included in the save_files data dictionary
-        if hasattr(p, "styles"):
-            x = x.replace("[styles]", sanitize_filename_part(", ".join([x for x in p.styles if not x == "None"]) or "None", replace_spaces=False))
-
+        x = x.replace("[styles]", sanitize_filename_part(", ".join([x for x in p.styles if not x == "None"]) or "None", replace_spaces=False))
         x = x.replace("[sampler]", sanitize_filename_part(sd_samplers.samplers[p.sampler_index].name, replace_spaces=False))
 
     x = x.replace("[model_hash]", shared.sd_model.sd_model_hash)
diff --git a/modules/processing.py b/modules/processing.py
index 8faf9095..706dbfa8 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -121,6 +121,7 @@ class Processed:
         self.denoising_strength = getattr(p, 'denoising_strength', None)
         self.extra_generation_params = p.extra_generation_params
         self.index_of_first_image = index_of_first_image
+        self.styles = p.styles
 
         self.eta = p.eta
         self.ddim_discretize = p.ddim_discretize
@@ -165,6 +166,7 @@ class Processed:
             "extra_generation_params": self.extra_generation_params,
             "index_of_first_image": self.index_of_first_image,
             "infotexts": self.infotexts,
+            "styles": self.styles,
         }
 
         return json.dumps(obj)
-- 
cgit v1.2.3


From 1cc36d170ac15e7f04208df32db27af1b10c867c Mon Sep 17 00:00:00 2001
From: Milly <milly.ca@gmail.com>
Date: Wed, 5 Oct 2022 02:17:15 +0900
Subject: Added job_timestamp to Processed

So `[job_timestamp]` pattern can use in saving image UI.
---
 modules/images.py     | 2 +-
 modules/processing.py | 2 ++
 2 files changed, 3 insertions(+), 1 deletion(-)

diff --git a/modules/images.py b/modules/images.py
index fa0714fd..669d76af 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -298,7 +298,7 @@ def apply_filename_pattern(x, p, seed, prompt):
     x = x.replace("[model_hash]", shared.sd_model.sd_model_hash)
     x = x.replace("[date]", datetime.date.today().isoformat())
     x = x.replace("[datetime]", datetime.datetime.now().strftime("%Y%m%d%H%M%S"))
-    x = x.replace("[job_timestamp]", shared.state.job_timestamp)
+    x = x.replace("[job_timestamp]", getattr(p, "job_timestamp", shared.state.job_timestamp))
 
     # Apply [prompt] at last. Because it may contain any replacement word.^M
     if prompt is not None:
diff --git a/modules/processing.py b/modules/processing.py
index 706dbfa8..f773a30e 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -122,6 +122,7 @@ class Processed:
         self.extra_generation_params = p.extra_generation_params
         self.index_of_first_image = index_of_first_image
         self.styles = p.styles
+        self.job_timestamp = state.job_timestamp
 
         self.eta = p.eta
         self.ddim_discretize = p.ddim_discretize
@@ -167,6 +168,7 @@ class Processed:
             "index_of_first_image": self.index_of_first_image,
             "infotexts": self.infotexts,
             "styles": self.styles,
+            "job_timestamp": self.job_timestamp,
         }
 
         return json.dumps(obj)
-- 
cgit v1.2.3


From 405c8171d1acbb994084d98770bbcb97d01d9406 Mon Sep 17 00:00:00 2001
From: Milly <milly.ca@gmail.com>
Date: Thu, 6 Oct 2022 00:59:04 +0900
Subject: Prefer using `Processed.sd_model_hash` attribute when filename
 pattern

---
 modules/images.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/images.py b/modules/images.py
index 669d76af..29c5ee24 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -295,7 +295,7 @@ def apply_filename_pattern(x, p, seed, prompt):
         x = x.replace("[styles]", sanitize_filename_part(", ".join([x for x in p.styles if not x == "None"]) or "None", replace_spaces=False))
         x = x.replace("[sampler]", sanitize_filename_part(sd_samplers.samplers[p.sampler_index].name, replace_spaces=False))
 
-    x = x.replace("[model_hash]", shared.sd_model.sd_model_hash)
+    x = x.replace("[model_hash]", getattr(p, "sd_model_hash", shared.sd_model.sd_model_hash))
     x = x.replace("[date]", datetime.date.today().isoformat())
     x = x.replace("[datetime]", datetime.datetime.now().strftime("%Y%m%d%H%M%S"))
     x = x.replace("[job_timestamp]", getattr(p, "job_timestamp", shared.state.job_timestamp))
-- 
cgit v1.2.3


From b34b25b4c941819d34f29be6c4c1ec01e64585b4 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 6 Oct 2022 23:27:01 +0300
Subject: karras samplers for img2img?

---
 modules/sd_samplers.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index 497df943..df17e93c 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -338,9 +338,11 @@ class KDiffusionSampler:
         steps, t_enc = setup_img2img_steps(p, steps)
 
         if p.sampler_noise_scheduler_override:
-          sigmas = p.sampler_noise_scheduler_override(steps)
+            sigmas = p.sampler_noise_scheduler_override(steps)
+        elif self.config is not None and self.config.options.get('scheduler', None) == 'karras':
+            sigmas = k_diffusion.sampling.get_sigmas_karras(n=steps, sigma_min=0.1, sigma_max=10, device=shared.device)
         else:
-          sigmas = self.model_wrap.get_sigmas(steps)
+            sigmas = self.model_wrap.get_sigmas(steps)
 
         noise = noise * sigmas[steps - t_enc - 1]
         xi = x + noise
-- 
cgit v1.2.3


From 2995107fa24cfd72b0a991e18271dcde148c2807 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 6 Oct 2022 23:44:54 +0300
Subject: added ctrl+up or ctrl+down hotkeys for attention

---
 README.md                    |  4 ++++
 javascript/edit-attention.js | 41 +++++++++++++++++++++++++++++++++++++++++
 2 files changed, 45 insertions(+)
 create mode 100644 javascript/edit-attention.js

diff --git a/README.md b/README.md
index ec3d7532..a14a6330 100644
--- a/README.md
+++ b/README.md
@@ -16,6 +16,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
 - Attention, specify parts of text that the model should pay more attention to
     - a man in a ((tuxedo)) - will pay more attention to tuxedo
     - a man in a (tuxedo:1.21) - alternative syntax
+    - select text and press ctrl+up or ctrl+down to aduotmatically adjust attention to selected text
 - Loopback, run img2img processing multiple times
 - X/Y plot, a way to draw a 2 dimensional plot of images with different parameters
 - Textual Inversion
@@ -61,6 +62,9 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
 - Reloading checkpoints on the fly
 - Checkpoint Merger, a tab that allows you to merge two checkpoints into one
 - [Custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Scripts) with many extensions from community
+- [Composable-Diffusion](https://energy-based-model.github.io/Compositional-Visual-Generation-with-Composable-Diffusion-Models/), a way to use multiple prompts at once
+     - separate prompts using uppercase `AND`
+     - also supports weights for prompts: `a cat :1.2 AND a dog AND a penguin :2.2`
 
 ## Installation and Running
 Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for both [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended) and [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs.
diff --git a/javascript/edit-attention.js b/javascript/edit-attention.js
new file mode 100644
index 00000000..c67ed579
--- /dev/null
+++ b/javascript/edit-attention.js
@@ -0,0 +1,41 @@
+addEventListener('keydown', (event) => {
+	let target = event.originalTarget;
+	if (!target.hasAttribute("placeholder")) return;
+	if (!target.placeholder.toLowerCase().includes("prompt")) return;
+
+	let plus = "ArrowUp"
+	let minus = "ArrowDown"
+	if (event.key != plus && event.key != minus) return;
+
+	selectionStart = target.selectionStart;
+	selectionEnd = target.selectionEnd;
+	if(selectionStart == selectionEnd) return;
+
+	event.preventDefault();
+
+	if (selectionStart == 0 || target.value[selectionStart - 1] != "(") {
+		target.value = target.value.slice(0, selectionStart) +
+			"(" + target.value.slice(selectionStart, selectionEnd) + ":1.0)" +
+			target.value.slice(selectionEnd);
+
+		target.focus();
+		target.selectionStart = selectionStart + 1;
+		target.selectionEnd = selectionEnd + 1;
+
+	} else {
+		end = target.value.slice(selectionEnd + 1).indexOf(")") + 1;
+		weight = parseFloat(target.value.slice(selectionEnd + 1, selectionEnd + 1 + end));
+		if (event.key == minus) weight -= 0.1;
+		if (event.key == plus) weight += 0.1;
+
+		weight = parseFloat(weight.toPrecision(12));
+
+		target.value = target.value.slice(0, selectionEnd + 1) +
+			weight +
+			target.value.slice(selectionEnd + 1 + end - 1);
+
+		target.focus();
+		target.selectionStart = selectionStart;
+		target.selectionEnd = selectionEnd;
+	}
+});
-- 
cgit v1.2.3


From f174fb29228a04955fb951b32b0bab79e33ec2b8 Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Fri, 7 Oct 2022 05:21:49 +0300
Subject: add xformers attention

---
 modules/sd_hijack_optimizations.py | 39 +++++++++++++++++++++++++++++++++++++-
 1 file changed, 38 insertions(+), 1 deletion(-)

diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index ea4cfdfc..da1b76e1 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -1,7 +1,9 @@
 import math
 import torch
 from torch import einsum
-
+import xformers.ops
+import functorch
+xformers._is_functorch_available=True
 from ldm.util import default
 from einops import rearrange
 
@@ -92,6 +94,41 @@ def split_cross_attention_forward(self, x, context=None, mask=None):
 
     return self.to_out(r2)
 
+def _maybe_init(self, x):
+    """
+    Initialize the attention operator, if required We expect the head dimension to be exposed here, meaning that x
+    : B, Head, Length
+    """
+    if self.attention_op is not None:
+        return
+    _, M, K = x.shape
+    try:
+        self.attention_op = xformers.ops.AttentionOpDispatch(
+            dtype=x.dtype,
+            device=x.device,
+            k=K,
+            attn_bias_type=type(None),
+            has_dropout=False,
+            kv_len=M,
+            q_len=M,
+        ).op
+    except NotImplementedError as err:
+        raise NotImplementedError(f"Please install xformers with the flash attention / cutlass components.\n{err}")
+
+def xformers_attention_forward(self, x, context=None, mask=None):
+    h = self.heads
+    q_in = self.to_q(x)
+    context = default(context, x)
+    k_in = self.to_k(context)
+    v_in = self.to_v(context)
+    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q_in, k_in, v_in))
+    del q_in, k_in, v_in
+    self._maybe_init(q)
+    out = xformers.ops.memory_efficient_attention(q, k, v, attn_bias=None, op=self.attention_op)
+
+    out = rearrange(out, '(b h) n d -> b n (h d)', h=h)
+    return self.to_out(out)
+
 def cross_attention_attnblock_forward(self, x):
         h_ = x
         h_ = self.norm(h_)
-- 
cgit v1.2.3


From 2eb911b056ce6ff4434f673366782ed34f2b2f12 Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Fri, 7 Oct 2022 05:22:28 +0300
Subject: Update sd_hijack.py

---
 modules/sd_hijack.py | 13 +++++++++----
 1 file changed, 9 insertions(+), 4 deletions(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index a6fa890c..6221ed5a 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -20,12 +20,17 @@ diffusionmodules_model_AttnBlock_forward = ldm.modules.diffusionmodules.model.At
 
 
 def apply_optimizations():
-    ldm.modules.diffusionmodules.model.nonlinearity = silu
-
     if cmd_opts.opt_split_attention_v1:
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1
-    elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention or torch.cuda.is_available()):
-        ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward
+    if cmd_opts.opt_split_attention:
+        ldm.modules.attention_CrossAttention_forward = sd_hijack_optimizations.split_cross_attention_forward
+        ldm.modules.diffusionmodules.model.nonlinearity = sd_hijack_optimizations.nonlinearity_hijack
+        ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.cross_attention_attnblock_forward
+    elif not cmd_opts.disable_opt_xformers_attention:
+        ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward
+        ldm.modules.attention.CrossAttention._maybe_init = sd_hijack_optimizations._maybe_init
+        ldm.modules.attention.CrossAttention.attention_op = None
+        ldm.modules.diffusionmodules.model.nonlinearity = sd_hijack_optimizations.nonlinearity_hijack
         ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.cross_attention_attnblock_forward
 
 
-- 
cgit v1.2.3


From da4ab2707b4cb0611cf181ba248a271d1937433e Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Fri, 7 Oct 2022 05:23:06 +0300
Subject: Update shared.py

---
 modules/shared.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/modules/shared.py b/modules/shared.py
index 25bb6e6c..8cc3b2fe 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -43,6 +43,7 @@ parser.add_argument("--realesrgan-models-path", type=str, help="Path to director
 parser.add_argument("--scunet-models-path", type=str, help="Path to directory with ScuNET model file(s).", default=os.path.join(models_path, 'ScuNET'))
 parser.add_argument("--swinir-models-path", type=str, help="Path to directory with SwinIR model file(s).", default=os.path.join(models_path, 'SwinIR'))
 parser.add_argument("--ldsr-models-path", type=str, help="Path to directory with LDSR model file(s).", default=os.path.join(models_path, 'LDSR'))
+parser.add_argument("--disable-opt-xformers-attention", action='store_true', help="force-disables xformers attention optimization")
 parser.add_argument("--opt-split-attention", action='store_true', help="force-enables cross-attention layer optimization. By default, it's on for torch.cuda and off for other torch devices.")
 parser.add_argument("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization")
 parser.add_argument("--opt-split-attention-v1", action='store_true', help="enable older version of split attention optimization that does not consume all the VRAM it can find")
-- 
cgit v1.2.3


From cd8bb597c6bcb6c59b538b7a1ab8f2face764fc5 Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Fri, 7 Oct 2022 05:23:25 +0300
Subject: Update requirements.txt

---
 requirements.txt | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/requirements.txt b/requirements.txt
index 631fe616..304a066a 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -23,3 +23,5 @@ resize-right
 torchdiffeq
 kornia
 lark
+functorch
+#xformers?
-- 
cgit v1.2.3


From 35d6b231628d18d53d166c3a92fea1523e88d51e Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Fri, 7 Oct 2022 05:31:53 +0300
Subject: Update sd_hijack.py

---
 modules/sd_hijack.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 6221ed5a..a006c0a3 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -20,17 +20,16 @@ diffusionmodules_model_AttnBlock_forward = ldm.modules.diffusionmodules.model.At
 
 
 def apply_optimizations():
+    ldm.modules.diffusionmodules.model.nonlinearity = silu
     if cmd_opts.opt_split_attention_v1:
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1
     if cmd_opts.opt_split_attention:
         ldm.modules.attention_CrossAttention_forward = sd_hijack_optimizations.split_cross_attention_forward
-        ldm.modules.diffusionmodules.model.nonlinearity = sd_hijack_optimizations.nonlinearity_hijack
         ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.cross_attention_attnblock_forward
     elif not cmd_opts.disable_opt_xformers_attention:
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward
         ldm.modules.attention.CrossAttention._maybe_init = sd_hijack_optimizations._maybe_init
         ldm.modules.attention.CrossAttention.attention_op = None
-        ldm.modules.diffusionmodules.model.nonlinearity = sd_hijack_optimizations.nonlinearity_hijack
         ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.cross_attention_attnblock_forward
 
 
-- 
cgit v1.2.3


From 5303df24282ba06abb34a423f2967354d37d078e Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Fri, 7 Oct 2022 06:01:14 +0300
Subject: Update sd_hijack.py

---
 modules/sd_hijack.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index a006c0a3..ddacb0ad 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -23,10 +23,10 @@ def apply_optimizations():
     ldm.modules.diffusionmodules.model.nonlinearity = silu
     if cmd_opts.opt_split_attention_v1:
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1
-    if cmd_opts.opt_split_attention:
+    elif cmd_opts.opt_split_attention:
         ldm.modules.attention_CrossAttention_forward = sd_hijack_optimizations.split_cross_attention_forward
         ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.cross_attention_attnblock_forward
-    elif not cmd_opts.disable_opt_xformers_attention:
+    elif not cmd_opts.disable_opt_xformers_attention and not cmd_opts.opt_split_attention:
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward
         ldm.modules.attention.CrossAttention._maybe_init = sd_hijack_optimizations._maybe_init
         ldm.modules.attention.CrossAttention.attention_op = None
-- 
cgit v1.2.3


From 5e3ff846c56dc8e1d5c76ea04a8f2f74d7da07fc Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Fri, 7 Oct 2022 06:38:01 +0300
Subject: Update sd_hijack.py

---
 modules/sd_hijack.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index ddacb0ad..cbdb9d3c 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -26,7 +26,7 @@ def apply_optimizations():
     elif cmd_opts.opt_split_attention:
         ldm.modules.attention_CrossAttention_forward = sd_hijack_optimizations.split_cross_attention_forward
         ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.cross_attention_attnblock_forward
-    elif not cmd_opts.disable_opt_xformers_attention and not cmd_opts.opt_split_attention:
+    elif not cmd_opts.disable_opt_xformers_attention and not (cmd_opts.opt_split_attention or torch.version.hip):
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward
         ldm.modules.attention.CrossAttention._maybe_init = sd_hijack_optimizations._maybe_init
         ldm.modules.attention.CrossAttention.attention_op = None
-- 
cgit v1.2.3


From bad7cb29cecac51c5c0f39afec332b007ed73133 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 7 Oct 2022 10:17:52 +0300
Subject: added support for hypernetworks (???)

---
 modules/hypernetwork.py            | 55 ++++++++++++++++++++++++++++++++++++++
 modules/sd_hijack_optimizations.py | 17 ++++++++++--
 modules/shared.py                  |  9 ++++++-
 scripts/xy_grid.py                 | 10 +++++++
 4 files changed, 88 insertions(+), 3 deletions(-)
 create mode 100644 modules/hypernetwork.py

diff --git a/modules/hypernetwork.py b/modules/hypernetwork.py
new file mode 100644
index 00000000..9ed1eed9
--- /dev/null
+++ b/modules/hypernetwork.py
@@ -0,0 +1,55 @@
+import glob
+import os
+import torch
+from modules import devices
+
+
+class HypernetworkModule(torch.nn.Module):
+    def __init__(self, dim, state_dict):
+        super().__init__()
+
+        self.linear1 = torch.nn.Linear(dim, dim * 2)
+        self.linear2 = torch.nn.Linear(dim * 2, dim)
+
+        self.load_state_dict(state_dict, strict=True)
+        self.to(devices.device)
+
+    def forward(self, x):
+        return x + (self.linear2(self.linear1(x)))
+
+
+class Hypernetwork:
+    filename = None
+    name = None
+
+    def __init__(self, filename):
+        self.filename = filename
+        self.name = os.path.splitext(os.path.basename(filename))[0]
+        self.layers = {}
+
+        state_dict = torch.load(filename, map_location='cpu')
+        for size, sd in state_dict.items():
+            self.layers[size] = (HypernetworkModule(size, sd[0]), HypernetworkModule(size, sd[1]))
+
+
+def load_hypernetworks(path):
+    res = {}
+
+    for filename in glob.iglob(path + '**/*.pt', recursive=True):
+        hn = Hypernetwork(filename)
+        res[hn.name] = hn
+
+    return res
+
+def apply(self, x, context=None, mask=None, original=None):
+
+
+    if CrossAttention.hypernetwork is not None and context.shape[2] in CrossAttention.hypernetwork:
+        if context.shape[1] == 77 and CrossAttention.noise_cond:
+            context = context + (torch.randn_like(context) * 0.1)
+        h_k, h_v = CrossAttention.hypernetwork[context.shape[2]]
+        k = self.to_k(h_k(context))
+        v = self.to_v(h_v(context))
+    else:
+        k = self.to_k(context)
+        v = self.to_v(context)
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index ea4cfdfc..d9cca485 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -5,6 +5,8 @@ from torch import einsum
 from ldm.util import default
 from einops import rearrange
 
+from modules import shared
+
 
 # see https://github.com/basujindal/stable-diffusion/pull/117 for discussion
 def split_cross_attention_forward_v1(self, x, context=None, mask=None):
@@ -42,8 +44,19 @@ def split_cross_attention_forward(self, x, context=None, mask=None):
 
     q_in = self.to_q(x)
     context = default(context, x)
-    k_in = self.to_k(context) * self.scale
-    v_in = self.to_v(context)
+
+    hypernetwork = shared.selected_hypernetwork()
+    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
+
+    if hypernetwork_layers is not None:
+        k_in = self.to_k(hypernetwork_layers[0](context))
+        v_in = self.to_v(hypernetwork_layers[1](context))
+    else:
+        k_in = self.to_k(context)
+        v_in = self.to_v(context)
+
+    k_in *= self.scale
+
     del context, x
 
     q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q_in, k_in, v_in))
diff --git a/modules/shared.py b/modules/shared.py
index 25bb6e6c..879d8424 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -13,7 +13,7 @@ import modules.memmon
 import modules.sd_models
 import modules.styles
 import modules.devices as devices
-from modules import sd_samplers
+from modules import sd_samplers, hypernetwork
 from modules.paths import models_path, script_path, sd_path
 
 sd_model_file = os.path.join(script_path, 'model.ckpt')
@@ -76,6 +76,12 @@ parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram
 
 config_filename = cmd_opts.ui_settings_file
 
+hypernetworks = hypernetwork.load_hypernetworks(os.path.join(models_path, 'hypernetworks'))
+
+
+def selected_hypernetwork():
+    return hypernetworks.get(opts.sd_hypernetwork, None)
+
 
 class State:
     interrupted = False
@@ -206,6 +212,7 @@ options_templates.update(options_section(('system', "System"), {
 
 options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}),
+    "sd_hypernetwork": OptionInfo("None", "Stable Diffusion finetune hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}),
     "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."),
     "save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"),
     "img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies (normally you'd do less with less denoising)."),
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 6344e612..c0c364df 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -77,6 +77,11 @@ def apply_checkpoint(p, x, xs):
     modules.sd_models.reload_model_weights(shared.sd_model, info)
 
 
+def apply_hypernetwork(p, x, xs):
+    hn = shared.hypernetworks.get(x, None)
+    opts.data["sd_hypernetwork"] = hn.name if hn is not None else 'None'
+
+
 def format_value_add_label(p, opt, x):
     if type(x) == float:
         x = round(x, 8)
@@ -122,6 +127,7 @@ axis_options = [
     AxisOption("Prompt order", str_permutations, apply_order, format_value_join_list),
     AxisOption("Sampler", str, apply_sampler, format_value),
     AxisOption("Checkpoint name", str, apply_checkpoint, format_value),
+    AxisOption("Hypernetwork", str, apply_hypernetwork, format_value),
     AxisOption("Sigma Churn", float, apply_field("s_churn"), format_value_add_label),
     AxisOption("Sigma min", float, apply_field("s_tmin"), format_value_add_label),
     AxisOption("Sigma max", float, apply_field("s_tmax"), format_value_add_label),
@@ -193,6 +199,8 @@ class Script(scripts.Script):
         modules.processing.fix_seed(p)
         p.batch_size = 1
 
+        initial_hn = opts.sd_hypernetwork
+
         def process_axis(opt, vals):
             if opt.label == 'Nothing':
                 return [0]
@@ -300,4 +308,6 @@ class Script(scripts.Script):
         # restore checkpoint in case it was changed by axes
         modules.sd_models.reload_model_weights(shared.sd_model)
 
+        opts.data["sd_hypernetwork"] = initial_hn
+
         return processed
-- 
cgit v1.2.3


From d15b3ec0013c10f02f0fb80e8448bac8872a151f Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 7 Oct 2022 10:40:22 +0300
Subject: support loading VAE

---
 modules/sd_models.py | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/modules/sd_models.py b/modules/sd_models.py
index 5f992064..8f794b47 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -134,6 +134,14 @@ def load_model_weights(model, checkpoint_file, sd_model_hash):
 
     devices.dtype = torch.float32 if shared.cmd_opts.no_half else torch.float16
 
+    vae_file = os.path.splitext(checkpoint_file)[0] + ".vae.pt"
+    if os.path.exists(vae_file):
+        print(f"Loading VAE weights from: {vae_file}")
+        vae_ckpt = torch.load(vae_file, map_location="cpu")
+        vae_dict = {k: v for k, v in vae_ckpt["state_dict"].items() if k[0:4] != "loss"}
+
+        model.first_stage_model.load_state_dict(vae_dict)
+
     model.sd_model_hash = sd_model_hash
     model.sd_model_checkpint = checkpoint_file
 
-- 
cgit v1.2.3


From 97bc0b9504572d2df80598d0b694703bcd626de6 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 7 Oct 2022 13:22:50 +0300
Subject: do not stop working on failed hypernetwork load

---
 modules/hypernetwork.py | 11 +++++++++--
 1 file changed, 9 insertions(+), 2 deletions(-)

diff --git a/modules/hypernetwork.py b/modules/hypernetwork.py
index 9ed1eed9..c5cf4afa 100644
--- a/modules/hypernetwork.py
+++ b/modules/hypernetwork.py
@@ -1,5 +1,8 @@
 import glob
 import os
+import sys
+import traceback
+
 import torch
 from modules import devices
 
@@ -36,8 +39,12 @@ def load_hypernetworks(path):
     res = {}
 
     for filename in glob.iglob(path + '**/*.pt', recursive=True):
-        hn = Hypernetwork(filename)
-        res[hn.name] = hn
+        try:
+            hn = Hypernetwork(filename)
+            res[hn.name] = hn
+        except Exception:
+            print(f"Error loading hypernetwork {filename}", file=sys.stderr)
+            print(traceback.format_exc(), file=sys.stderr)
 
     return res
 
-- 
cgit v1.2.3


From f7c787eb7c295c27439f4fbdf78c26b8389560be Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 7 Oct 2022 16:39:51 +0300
Subject: make it possible to use hypernetworks without opt split attention

---
 modules/hypernetwork.py | 42 ++++++++++++++++++++++++++++++++++--------
 modules/sd_hijack.py    |  6 ++++--
 2 files changed, 38 insertions(+), 10 deletions(-)

diff --git a/modules/hypernetwork.py b/modules/hypernetwork.py
index c5cf4afa..c7b86682 100644
--- a/modules/hypernetwork.py
+++ b/modules/hypernetwork.py
@@ -4,7 +4,12 @@ import sys
 import traceback
 
 import torch
-from modules import devices
+
+from ldm.util import default
+from modules import devices, shared
+import torch
+from torch import einsum
+from einops import rearrange, repeat
 
 
 class HypernetworkModule(torch.nn.Module):
@@ -48,15 +53,36 @@ def load_hypernetworks(path):
 
     return res
 
-def apply(self, x, context=None, mask=None, original=None):
 
+def attention_CrossAttention_forward(self, x, context=None, mask=None):
+    h = self.heads
+
+    q = self.to_q(x)
+    context = default(context, x)
 
-    if CrossAttention.hypernetwork is not None and context.shape[2] in CrossAttention.hypernetwork:
-        if context.shape[1] == 77 and CrossAttention.noise_cond:
-            context = context + (torch.randn_like(context) * 0.1)
-        h_k, h_v = CrossAttention.hypernetwork[context.shape[2]]
-        k = self.to_k(h_k(context))
-        v = self.to_v(h_v(context))
+    hypernetwork = shared.selected_hypernetwork()
+    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
+
+    if hypernetwork_layers is not None:
+        k = self.to_k(hypernetwork_layers[0](context))
+        v = self.to_v(hypernetwork_layers[1](context))
     else:
         k = self.to_k(context)
         v = self.to_v(context)
+
+    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
+
+    sim = einsum('b i d, b j d -> b i j', q, k) * self.scale
+
+    if mask is not None:
+        mask = rearrange(mask, 'b ... -> b (...)')
+        max_neg_value = -torch.finfo(sim.dtype).max
+        mask = repeat(mask, 'b j -> (b h) () j', h=h)
+        sim.masked_fill_(~mask, max_neg_value)
+
+    # attention, what we cannot get enough of
+    attn = sim.softmax(dim=-1)
+
+    out = einsum('b i j, b j d -> b i d', attn, v)
+    out = rearrange(out, '(b h) n d -> b n (h d)', h=h)
+    return self.to_out(out)
diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index a6fa890c..d68f89cc 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -8,7 +8,7 @@ from torch import einsum
 from torch.nn.functional import silu
 
 import modules.textual_inversion.textual_inversion
-from modules import prompt_parser, devices, sd_hijack_optimizations, shared
+from modules import prompt_parser, devices, sd_hijack_optimizations, shared, hypernetwork
 from modules.shared import opts, device, cmd_opts
 
 import ldm.modules.attention
@@ -20,6 +20,8 @@ diffusionmodules_model_AttnBlock_forward = ldm.modules.diffusionmodules.model.At
 
 
 def apply_optimizations():
+    undo_optimizations()
+
     ldm.modules.diffusionmodules.model.nonlinearity = silu
 
     if cmd_opts.opt_split_attention_v1:
@@ -30,7 +32,7 @@ def apply_optimizations():
 
 
 def undo_optimizations():
-    ldm.modules.attention.CrossAttention.forward = attention_CrossAttention_forward
+    ldm.modules.attention.CrossAttention.forward = hypernetwork.attention_CrossAttention_forward
     ldm.modules.diffusionmodules.model.nonlinearity = diffusionmodules_model_nonlinearity
     ldm.modules.diffusionmodules.model.AttnBlock.forward = diffusionmodules_model_AttnBlock_forward
 
-- 
cgit v1.2.3


From 54fa613c8391e3973cca9d94cdf539061932508b Mon Sep 17 00:00:00 2001
From: Greendayle <Greendayle>
Date: Fri, 7 Oct 2022 20:37:43 +0200
Subject: loading tf only in interrogation process

---
 modules/deepbooru.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index fb5018a6..79dc59bd 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -1,12 +1,13 @@
 import os.path
 from concurrent.futures import ProcessPoolExecutor
 
-import numpy as np
-import deepdanbooru as dd
-import tensorflow as tf
 
 
 def _load_tf_and_return_tags(pil_image, threshold):
+    import deepdanbooru as dd
+    import tensorflow as tf
+    import numpy as np
+
     this_folder = os.path.dirname(__file__)
     model_path = os.path.join(this_folder, '..', 'models', 'deepbooru', 'deepdanbooru-v3-20211112-sgd-e28')
 
-- 
cgit v1.2.3


From fa2ea648db81f5723bb5d722f2fe0ebd7dfc319a Mon Sep 17 00:00:00 2001
From: Greendayle <Greendayle>
Date: Fri, 7 Oct 2022 20:46:38 +0200
Subject: even more powerfull fix

---
 modules/deepbooru.py | 9 +++++++--
 1 file changed, 7 insertions(+), 2 deletions(-)

diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index 79dc59bd..60094336 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -60,8 +60,13 @@ def _load_tf_and_return_tags(pil_image, threshold):
     return ', '.join(result_tags_out).replace('_', ' ').replace(':', ' ')
 
 
+def subprocess_init_no_cuda():
+    import os
+    os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
+
+
 def get_deepbooru_tags(pil_image, threshold=0.5):
-    with ProcessPoolExecutor() as executor:
-        f = executor.submit(_load_tf_and_return_tags, pil_image, threshold)
+    with ProcessPoolExecutor(initializer=subprocess_init_no_cuda) as executor:
+        f = executor.submit(_load_tf_and_return_tags, pil_image, threshold, )
         ret = f.result()  # will rethrow any exceptions
     return ret
\ No newline at end of file
-- 
cgit v1.2.3


From 5f12e7efd92ad802742f96788b4be3249ad02829 Mon Sep 17 00:00:00 2001
From: Greendayle <Greendayle>
Date: Fri, 7 Oct 2022 20:58:30 +0200
Subject: linux test

---
 modules/deepbooru.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index 60094336..781b2249 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -1,6 +1,6 @@
 import os.path
 from concurrent.futures import ProcessPoolExecutor
-
+from multiprocessing import get_context
 
 
 def _load_tf_and_return_tags(pil_image, threshold):
@@ -66,7 +66,8 @@ def subprocess_init_no_cuda():
 
 
 def get_deepbooru_tags(pil_image, threshold=0.5):
-    with ProcessPoolExecutor(initializer=subprocess_init_no_cuda) as executor:
+    context = get_context('spawn')
+    with ProcessPoolExecutor(initializer=subprocess_init_no_cuda, mp_context=context) as executor:
         f = executor.submit(_load_tf_and_return_tags, pil_image, threshold, )
         ret = f.result()  # will rethrow any exceptions
     return ret
\ No newline at end of file
-- 
cgit v1.2.3


From 12c4d5c6b5bf9dd50d0601c36af4f99b65316d58 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 7 Oct 2022 23:22:22 +0300
Subject: hypernetwork training mk1

---
 modules/hypernetwork.py                      |  88 ---------
 modules/hypernetwork/hypernetwork.py         | 267 +++++++++++++++++++++++++++
 modules/hypernetwork/ui.py                   |  43 +++++
 modules/sd_hijack.py                         |   4 +-
 modules/sd_hijack_optimizations.py           |   3 +-
 modules/shared.py                            |  13 +-
 modules/textual_inversion/ui.py              |   1 -
 modules/ui.py                                |  58 +++++-
 scripts/xy_grid.py                           |   7 +-
 textual_inversion_templates/hypernetwork.txt |  27 +++
 textual_inversion_templates/none.txt         |   1 +
 webui.py                                     |   9 +
 12 files changed, 414 insertions(+), 107 deletions(-)
 delete mode 100644 modules/hypernetwork.py
 create mode 100644 modules/hypernetwork/hypernetwork.py
 create mode 100644 modules/hypernetwork/ui.py
 create mode 100644 textual_inversion_templates/hypernetwork.txt
 create mode 100644 textual_inversion_templates/none.txt

diff --git a/modules/hypernetwork.py b/modules/hypernetwork.py
deleted file mode 100644
index c7b86682..00000000
--- a/modules/hypernetwork.py
+++ /dev/null
@@ -1,88 +0,0 @@
-import glob
-import os
-import sys
-import traceback
-
-import torch
-
-from ldm.util import default
-from modules import devices, shared
-import torch
-from torch import einsum
-from einops import rearrange, repeat
-
-
-class HypernetworkModule(torch.nn.Module):
-    def __init__(self, dim, state_dict):
-        super().__init__()
-
-        self.linear1 = torch.nn.Linear(dim, dim * 2)
-        self.linear2 = torch.nn.Linear(dim * 2, dim)
-
-        self.load_state_dict(state_dict, strict=True)
-        self.to(devices.device)
-
-    def forward(self, x):
-        return x + (self.linear2(self.linear1(x)))
-
-
-class Hypernetwork:
-    filename = None
-    name = None
-
-    def __init__(self, filename):
-        self.filename = filename
-        self.name = os.path.splitext(os.path.basename(filename))[0]
-        self.layers = {}
-
-        state_dict = torch.load(filename, map_location='cpu')
-        for size, sd in state_dict.items():
-            self.layers[size] = (HypernetworkModule(size, sd[0]), HypernetworkModule(size, sd[1]))
-
-
-def load_hypernetworks(path):
-    res = {}
-
-    for filename in glob.iglob(path + '**/*.pt', recursive=True):
-        try:
-            hn = Hypernetwork(filename)
-            res[hn.name] = hn
-        except Exception:
-            print(f"Error loading hypernetwork {filename}", file=sys.stderr)
-            print(traceback.format_exc(), file=sys.stderr)
-
-    return res
-
-
-def attention_CrossAttention_forward(self, x, context=None, mask=None):
-    h = self.heads
-
-    q = self.to_q(x)
-    context = default(context, x)
-
-    hypernetwork = shared.selected_hypernetwork()
-    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
-
-    if hypernetwork_layers is not None:
-        k = self.to_k(hypernetwork_layers[0](context))
-        v = self.to_v(hypernetwork_layers[1](context))
-    else:
-        k = self.to_k(context)
-        v = self.to_v(context)
-
-    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
-
-    sim = einsum('b i d, b j d -> b i j', q, k) * self.scale
-
-    if mask is not None:
-        mask = rearrange(mask, 'b ... -> b (...)')
-        max_neg_value = -torch.finfo(sim.dtype).max
-        mask = repeat(mask, 'b j -> (b h) () j', h=h)
-        sim.masked_fill_(~mask, max_neg_value)
-
-    # attention, what we cannot get enough of
-    attn = sim.softmax(dim=-1)
-
-    out = einsum('b i j, b j d -> b i d', attn, v)
-    out = rearrange(out, '(b h) n d -> b n (h d)', h=h)
-    return self.to_out(out)
diff --git a/modules/hypernetwork/hypernetwork.py b/modules/hypernetwork/hypernetwork.py
new file mode 100644
index 00000000..a3d6a47e
--- /dev/null
+++ b/modules/hypernetwork/hypernetwork.py
@@ -0,0 +1,267 @@
+import datetime
+import glob
+import html
+import os
+import sys
+import traceback
+import tqdm
+
+import torch
+
+from ldm.util import default
+from modules import devices, shared, processing, sd_models
+import torch
+from torch import einsum
+from einops import rearrange, repeat
+import modules.textual_inversion.dataset
+
+
+class HypernetworkModule(torch.nn.Module):
+    def __init__(self, dim, state_dict=None):
+        super().__init__()
+
+        self.linear1 = torch.nn.Linear(dim, dim * 2)
+        self.linear2 = torch.nn.Linear(dim * 2, dim)
+
+        if state_dict is not None:
+            self.load_state_dict(state_dict, strict=True)
+        else:
+            self.linear1.weight.data.fill_(0.0001)
+            self.linear1.bias.data.fill_(0.0001)
+            self.linear2.weight.data.fill_(0.0001)
+            self.linear2.bias.data.fill_(0.0001)
+
+        self.to(devices.device)
+
+    def forward(self, x):
+        return x + (self.linear2(self.linear1(x)))
+
+
+class Hypernetwork:
+    filename = None
+    name = None
+
+    def __init__(self, name=None):
+        self.filename = None
+        self.name = name
+        self.layers = {}
+        self.step = 0
+        self.sd_checkpoint = None
+        self.sd_checkpoint_name = None
+
+        for size in [320, 640, 768, 1280]:
+            self.layers[size] = (HypernetworkModule(size), HypernetworkModule(size))
+
+    def weights(self):
+        res = []
+
+        for k, layers in self.layers.items():
+            for layer in layers:
+                layer.train()
+                res += [layer.linear1.weight, layer.linear1.bias, layer.linear2.weight, layer.linear2.bias]
+
+        return res
+
+    def save(self, filename):
+        state_dict = {}
+
+        for k, v in self.layers.items():
+            state_dict[k] = (v[0].state_dict(), v[1].state_dict())
+
+        state_dict['step'] = self.step
+        state_dict['name'] = self.name
+        state_dict['sd_checkpoint'] = self.sd_checkpoint
+        state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name
+
+        torch.save(state_dict, filename)
+
+    def load(self, filename):
+        self.filename = filename
+        if self.name is None:
+            self.name = os.path.splitext(os.path.basename(filename))[0]
+
+        state_dict = torch.load(filename, map_location='cpu')
+
+        for size, sd in state_dict.items():
+            if type(size) == int:
+                self.layers[size] = (HypernetworkModule(size, sd[0]), HypernetworkModule(size, sd[1]))
+
+        self.name = state_dict.get('name', self.name)
+        self.step = state_dict.get('step', 0)
+        self.sd_checkpoint = state_dict.get('sd_checkpoint', None)
+        self.sd_checkpoint_name = state_dict.get('sd_checkpoint_name', None)
+
+
+def load_hypernetworks(path):
+    res = {}
+
+    for filename in glob.iglob(path + '**/*.pt', recursive=True):
+        try:
+            hn = Hypernetwork()
+            hn.load(filename)
+            res[hn.name] = hn
+        except Exception:
+            print(f"Error loading hypernetwork {filename}", file=sys.stderr)
+            print(traceback.format_exc(), file=sys.stderr)
+
+    return res
+
+
+def attention_CrossAttention_forward(self, x, context=None, mask=None):
+    h = self.heads
+
+    q = self.to_q(x)
+    context = default(context, x)
+
+    hypernetwork_layers = (shared.hypernetwork.layers if shared.hypernetwork is not None else {}).get(context.shape[2], None)
+
+    if hypernetwork_layers is not None:
+        hypernetwork_k, hypernetwork_v = hypernetwork_layers
+
+        self.hypernetwork_k = hypernetwork_k
+        self.hypernetwork_v = hypernetwork_v
+
+        context_k = hypernetwork_k(context)
+        context_v = hypernetwork_v(context)
+    else:
+        context_k = context
+        context_v = context
+
+    k = self.to_k(context_k)
+    v = self.to_v(context_v)
+
+    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
+
+    sim = einsum('b i d, b j d -> b i j', q, k) * self.scale
+
+    if mask is not None:
+        mask = rearrange(mask, 'b ... -> b (...)')
+        max_neg_value = -torch.finfo(sim.dtype).max
+        mask = repeat(mask, 'b j -> (b h) () j', h=h)
+        sim.masked_fill_(~mask, max_neg_value)
+
+    # attention, what we cannot get enough of
+    attn = sim.softmax(dim=-1)
+
+    out = einsum('b i j, b j d -> b i d', attn, v)
+    out = rearrange(out, '(b h) n d -> b n (h d)', h=h)
+    return self.to_out(out)
+
+
+def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_image_prompt):
+    assert hypernetwork_name, 'embedding not selected'
+
+    shared.hypernetwork = shared.hypernetworks[hypernetwork_name]
+
+    shared.state.textinfo = "Initializing hypernetwork training..."
+    shared.state.job_count = steps
+
+    filename = os.path.join(shared.cmd_opts.hypernetwork_dir, f'{hypernetwork_name}.pt')
+
+    log_directory = os.path.join(log_directory, datetime.datetime.now().strftime("%Y-%m-%d"), hypernetwork_name)
+
+    if save_hypernetwork_every > 0:
+        hypernetwork_dir = os.path.join(log_directory, "hypernetworks")
+        os.makedirs(hypernetwork_dir, exist_ok=True)
+    else:
+        hypernetwork_dir = None
+
+    if create_image_every > 0:
+        images_dir = os.path.join(log_directory, "images")
+        os.makedirs(images_dir, exist_ok=True)
+    else:
+        images_dir = None
+
+    cond_model = shared.sd_model.cond_stage_model
+
+    shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
+    with torch.autocast("cuda"):
+        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, size=512, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file)
+
+    hypernetwork = shared.hypernetworks[hypernetwork_name]
+    weights = hypernetwork.weights()
+    for weight in weights:
+        weight.requires_grad = True
+
+    optimizer = torch.optim.AdamW(weights, lr=learn_rate)
+
+    losses = torch.zeros((32,))
+
+    last_saved_file = "<none>"
+    last_saved_image = "<none>"
+
+    ititial_step = hypernetwork.step or 0
+    if ititial_step > steps:
+        return hypernetwork, filename
+
+    pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step)
+    for i, (x, text) in pbar:
+        hypernetwork.step = i + ititial_step
+
+        if hypernetwork.step > steps:
+            break
+
+        if shared.state.interrupted:
+            break
+
+        with torch.autocast("cuda"):
+            c = cond_model([text])
+
+            x = x.to(devices.device)
+            loss = shared.sd_model(x.unsqueeze(0), c)[0]
+            del x
+
+            losses[hypernetwork.step % losses.shape[0]] = loss.item()
+
+            optimizer.zero_grad()
+            loss.backward()
+            optimizer.step()
+
+        pbar.set_description(f"loss: {losses.mean():.7f}")
+
+        if hypernetwork.step > 0 and hypernetwork_dir is not None and hypernetwork.step % save_hypernetwork_every == 0:
+            last_saved_file = os.path.join(hypernetwork_dir, f'{hypernetwork_name}-{hypernetwork.step}.pt')
+            hypernetwork.save(last_saved_file)
+
+        if hypernetwork.step > 0 and images_dir is not None and hypernetwork.step % create_image_every == 0:
+            last_saved_image = os.path.join(images_dir, f'{hypernetwork_name}-{hypernetwork.step}.png')
+
+            preview_text = text if preview_image_prompt == "" else preview_image_prompt
+
+            p = processing.StableDiffusionProcessingTxt2Img(
+                sd_model=shared.sd_model,
+                prompt=preview_text,
+                steps=20,
+                do_not_save_grid=True,
+                do_not_save_samples=True,
+            )
+
+            processed = processing.process_images(p)
+            image = processed.images[0]
+
+            shared.state.current_image = image
+            image.save(last_saved_image)
+
+            last_saved_image += f", prompt: {preview_text}"
+
+        shared.state.job_no = hypernetwork.step
+
+        shared.state.textinfo = f"""
+<p>
+Loss: {losses.mean():.7f}<br/>
+Step: {hypernetwork.step}<br/>
+Last prompt: {html.escape(text)}<br/>
+Last saved embedding: {html.escape(last_saved_file)}<br/>
+Last saved image: {html.escape(last_saved_image)}<br/>
+</p>
+"""
+
+    checkpoint = sd_models.select_checkpoint()
+
+    hypernetwork.sd_checkpoint = checkpoint.hash
+    hypernetwork.sd_checkpoint_name = checkpoint.model_name
+    hypernetwork.save(filename)
+
+    return hypernetwork, filename
+
+
diff --git a/modules/hypernetwork/ui.py b/modules/hypernetwork/ui.py
new file mode 100644
index 00000000..525f978c
--- /dev/null
+++ b/modules/hypernetwork/ui.py
@@ -0,0 +1,43 @@
+import html
+import os
+
+import gradio as gr
+
+import modules.textual_inversion.textual_inversion
+import modules.textual_inversion.preprocess
+from modules import sd_hijack, shared
+
+
+def create_hypernetwork(name):
+    fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt")
+    assert not os.path.exists(fn), f"file {fn} already exists"
+
+    hypernetwork = modules.hypernetwork.hypernetwork.Hypernetwork(name=name)
+    hypernetwork.save(fn)
+
+    shared.reload_hypernetworks()
+    shared.hypernetwork = shared.hypernetworks.get(shared.opts.sd_hypernetwork, None)
+
+    return gr.Dropdown.update(choices=sorted([x for x in shared.hypernetworks.keys()])), f"Created: {fn}", ""
+
+
+def train_hypernetwork(*args):
+
+    initial_hypernetwork = shared.hypernetwork
+
+    try:
+        sd_hijack.undo_optimizations()
+
+        hypernetwork, filename = modules.hypernetwork.hypernetwork.train_hypernetwork(*args)
+
+        res = f"""
+Training {'interrupted' if shared.state.interrupted else 'finished'} at {hypernetwork.step} steps.
+Hypernetwork saved to {html.escape(filename)}
+"""
+        return res, ""
+    except Exception:
+        raise
+    finally:
+        shared.hypernetwork = initial_hypernetwork
+        sd_hijack.apply_optimizations()
+
diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index d68f89cc..ec8c9d4b 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -8,7 +8,7 @@ from torch import einsum
 from torch.nn.functional import silu
 
 import modules.textual_inversion.textual_inversion
-from modules import prompt_parser, devices, sd_hijack_optimizations, shared, hypernetwork
+from modules import prompt_parser, devices, sd_hijack_optimizations, shared
 from modules.shared import opts, device, cmd_opts
 
 import ldm.modules.attention
@@ -32,6 +32,8 @@ def apply_optimizations():
 
 
 def undo_optimizations():
+    from modules.hypernetwork import hypernetwork
+
     ldm.modules.attention.CrossAttention.forward = hypernetwork.attention_CrossAttention_forward
     ldm.modules.diffusionmodules.model.nonlinearity = diffusionmodules_model_nonlinearity
     ldm.modules.diffusionmodules.model.AttnBlock.forward = diffusionmodules_model_AttnBlock_forward
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index d9cca485..3f32e020 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -45,8 +45,7 @@ def split_cross_attention_forward(self, x, context=None, mask=None):
     q_in = self.to_q(x)
     context = default(context, x)
 
-    hypernetwork = shared.selected_hypernetwork()
-    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
+    hypernetwork_layers = (shared.hypernetwork.layers if shared.hypernetwork is not None else {}).get(context.shape[2], None)
 
     if hypernetwork_layers is not None:
         k_in = self.to_k(hypernetwork_layers[0](context))
diff --git a/modules/shared.py b/modules/shared.py
index 879d8424..c5a893e8 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -13,7 +13,7 @@ import modules.memmon
 import modules.sd_models
 import modules.styles
 import modules.devices as devices
-from modules import sd_samplers, hypernetwork
+from modules import sd_samplers
 from modules.paths import models_path, script_path, sd_path
 
 sd_model_file = os.path.join(script_path, 'model.ckpt')
@@ -28,6 +28,7 @@ parser.add_argument("--no-half", action='store_true', help="do not switch the mo
 parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware acceleration in browser)")
 parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI")
 parser.add_argument("--embeddings-dir", type=str, default=os.path.join(script_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)")
+parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_path, 'hypernetworks'), help="hypernetwork directory")
 parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui")
 parser.add_argument("--medvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a little speed for low VRM usage")
 parser.add_argument("--lowvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a lot of speed for very low VRM usage")
@@ -76,11 +77,15 @@ parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram
 
 config_filename = cmd_opts.ui_settings_file
 
-hypernetworks = hypernetwork.load_hypernetworks(os.path.join(models_path, 'hypernetworks'))
 
+def reload_hypernetworks():
+    from modules.hypernetwork import hypernetwork
+    hypernetworks.clear()
+    hypernetworks.update(hypernetwork.load_hypernetworks(cmd_opts.hypernetwork_dir))
 
-def selected_hypernetwork():
-    return hypernetworks.get(opts.sd_hypernetwork, None)
+
+hypernetworks = {}
+hypernetwork = None
 
 
 class State:
diff --git a/modules/textual_inversion/ui.py b/modules/textual_inversion/ui.py
index f19ac5e0..c57de1f9 100644
--- a/modules/textual_inversion/ui.py
+++ b/modules/textual_inversion/ui.py
@@ -22,7 +22,6 @@ def preprocess(*args):
 
 
 def train_embedding(*args):
-
     try:
         sd_hijack.undo_optimizations()
 
diff --git a/modules/ui.py b/modules/ui.py
index 4f18126f..051908c1 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -37,6 +37,7 @@ import modules.generation_parameters_copypaste
 from modules import prompt_parser
 from modules.images import save_image
 import modules.textual_inversion.ui
+import modules.hypernetwork.ui
 
 # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the bowser will not show any UI
 mimetypes.init()
@@ -965,6 +966,18 @@ def create_ui(wrap_gradio_gpu_call):
                         with gr.Column():
                             create_embedding = gr.Button(value="Create", variant='primary')
 
+                with gr.Group():
+                    gr.HTML(value="<p style='margin-bottom: 0.7em'>Create a new hypernetwork</p>")
+
+                    new_hypernetwork_name = gr.Textbox(label="Name")
+
+                    with gr.Row():
+                        with gr.Column(scale=3):
+                            gr.HTML(value="")
+
+                        with gr.Column():
+                            create_hypernetwork = gr.Button(value="Create", variant='primary')
+
                 with gr.Group():
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Preprocess images</p>")
 
@@ -986,6 +999,7 @@ def create_ui(wrap_gradio_gpu_call):
                 with gr.Group():
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding; must specify a directory with a set of 512x512 images</p>")
                     train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
+                    train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', choices=[x for x in shared.hypernetworks.keys()])
                     learn_rate = gr.Number(label='Learning rate', value=5.0e-03)
                     dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images")
                     log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")
@@ -993,15 +1007,12 @@ def create_ui(wrap_gradio_gpu_call):
                     steps = gr.Number(label='Max steps', value=100000, precision=0)
                     create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0)
                     save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0)
+                    preview_image_prompt = gr.Textbox(label='Preview prompt', value="")
 
                     with gr.Row():
-                        with gr.Column(scale=2):
-                            gr.HTML(value="")
-
-                        with gr.Column():
-                            with gr.Row():
-                                interrupt_training = gr.Button(value="Interrupt")
-                                train_embedding = gr.Button(value="Train", variant='primary')
+                        interrupt_training = gr.Button(value="Interrupt")
+                        train_hypernetwork = gr.Button(value="Train Hypernetwork", variant='primary')
+                        train_embedding = gr.Button(value="Train Embedding", variant='primary')
 
             with gr.Column():
                 progressbar = gr.HTML(elem_id="ti_progressbar")
@@ -1027,6 +1038,18 @@ def create_ui(wrap_gradio_gpu_call):
             ]
         )
 
+        create_hypernetwork.click(
+            fn=modules.hypernetwork.ui.create_hypernetwork,
+            inputs=[
+                new_hypernetwork_name,
+            ],
+            outputs=[
+                train_hypernetwork_name,
+                ti_output,
+                ti_outcome,
+            ]
+        )
+
         run_preprocess.click(
             fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]),
             _js="start_training_textual_inversion",
@@ -1062,12 +1085,33 @@ def create_ui(wrap_gradio_gpu_call):
             ]
         )
 
+        train_hypernetwork.click(
+            fn=wrap_gradio_gpu_call(modules.hypernetwork.ui.train_hypernetwork, extra_outputs=[gr.update()]),
+            _js="start_training_textual_inversion",
+            inputs=[
+                train_hypernetwork_name,
+                learn_rate,
+                dataset_directory,
+                log_directory,
+                steps,
+                create_image_every,
+                save_embedding_every,
+                template_file,
+                preview_image_prompt,
+            ],
+            outputs=[
+                ti_output,
+                ti_outcome,
+            ]
+        )
+
         interrupt_training.click(
             fn=lambda: shared.state.interrupt(),
             inputs=[],
             outputs=[],
         )
 
+
     def create_setting_component(key):
         def fun():
             return opts.data[key] if key in opts.data else opts.data_labels[key].default
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index c0c364df..5b504de6 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -78,8 +78,7 @@ def apply_checkpoint(p, x, xs):
 
 
 def apply_hypernetwork(p, x, xs):
-    hn = shared.hypernetworks.get(x, None)
-    opts.data["sd_hypernetwork"] = hn.name if hn is not None else 'None'
+    shared.hypernetwork = shared.hypernetworks.get(x, None)
 
 
 def format_value_add_label(p, opt, x):
@@ -199,7 +198,7 @@ class Script(scripts.Script):
         modules.processing.fix_seed(p)
         p.batch_size = 1
 
-        initial_hn = opts.sd_hypernetwork
+        initial_hn = shared.hypernetwork
 
         def process_axis(opt, vals):
             if opt.label == 'Nothing':
@@ -308,6 +307,6 @@ class Script(scripts.Script):
         # restore checkpoint in case it was changed by axes
         modules.sd_models.reload_model_weights(shared.sd_model)
 
-        opts.data["sd_hypernetwork"] = initial_hn
+        shared.hypernetwork = initial_hn
 
         return processed
diff --git a/textual_inversion_templates/hypernetwork.txt b/textual_inversion_templates/hypernetwork.txt
new file mode 100644
index 00000000..91e06890
--- /dev/null
+++ b/textual_inversion_templates/hypernetwork.txt
@@ -0,0 +1,27 @@
+a photo of a [filewords]
+a rendering of a [filewords]
+a cropped photo of the [filewords]
+the photo of a [filewords]
+a photo of a clean [filewords]
+a photo of a dirty [filewords]
+a dark photo of the [filewords]
+a photo of my [filewords]
+a photo of the cool [filewords]
+a close-up photo of a [filewords]
+a bright photo of the [filewords]
+a cropped photo of a [filewords]
+a photo of the [filewords]
+a good photo of the [filewords]
+a photo of one [filewords]
+a close-up photo of the [filewords]
+a rendition of the [filewords]
+a photo of the clean [filewords]
+a rendition of a [filewords]
+a photo of a nice [filewords]
+a good photo of a [filewords]
+a photo of the nice [filewords]
+a photo of the small [filewords]
+a photo of the weird [filewords]
+a photo of the large [filewords]
+a photo of a cool [filewords]
+a photo of a small [filewords]
diff --git a/textual_inversion_templates/none.txt b/textual_inversion_templates/none.txt
new file mode 100644
index 00000000..f77af461
--- /dev/null
+++ b/textual_inversion_templates/none.txt
@@ -0,0 +1 @@
+picture
diff --git a/webui.py b/webui.py
index 480360fe..60f9061f 100644
--- a/webui.py
+++ b/webui.py
@@ -74,6 +74,15 @@ def wrap_gradio_gpu_call(func, extra_outputs=None):
     return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs)
 
 
+def set_hypernetwork():
+    shared.hypernetwork = shared.hypernetworks.get(shared.opts.sd_hypernetwork, None)
+
+
+shared.reload_hypernetworks()
+shared.opts.onchange("sd_hypernetwork", set_hypernetwork)
+set_hypernetwork()
+
+
 modules.scripts.load_scripts(os.path.join(script_path, "scripts"))
 
 shared.sd_model = modules.sd_models.load_model()
-- 
cgit v1.2.3


From c9cc65b201679ea43c763b0d85e749d40bbc5433 Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Sat, 8 Oct 2022 04:09:18 +0300
Subject: switch to the proper way of calling xformers

---
 modules/sd_hijack_optimizations.py | 28 +++-------------------------
 1 file changed, 3 insertions(+), 25 deletions(-)

diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index da1b76e1..7fb4a45e 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -94,39 +94,17 @@ def split_cross_attention_forward(self, x, context=None, mask=None):
 
     return self.to_out(r2)
 
-def _maybe_init(self, x):
-    """
-    Initialize the attention operator, if required We expect the head dimension to be exposed here, meaning that x
-    : B, Head, Length
-    """
-    if self.attention_op is not None:
-        return
-    _, M, K = x.shape
-    try:
-        self.attention_op = xformers.ops.AttentionOpDispatch(
-            dtype=x.dtype,
-            device=x.device,
-            k=K,
-            attn_bias_type=type(None),
-            has_dropout=False,
-            kv_len=M,
-            q_len=M,
-        ).op
-    except NotImplementedError as err:
-        raise NotImplementedError(f"Please install xformers with the flash attention / cutlass components.\n{err}")
-
 def xformers_attention_forward(self, x, context=None, mask=None):
     h = self.heads
     q_in = self.to_q(x)
     context = default(context, x)
     k_in = self.to_k(context)
     v_in = self.to_v(context)
-    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q_in, k_in, v_in))
+    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> b n h d', h=h), (q_in, k_in, v_in))
     del q_in, k_in, v_in
-    self._maybe_init(q)
-    out = xformers.ops.memory_efficient_attention(q, k, v, attn_bias=None, op=self.attention_op)
+    out = xformers.ops.memory_efficient_attention(q, k, v, attn_bias=None)
 
-    out = rearrange(out, '(b h) n d -> b n (h d)', h=h)
+    out = rearrange(out, 'b n h d -> b n (h d)', h=h)
     return self.to_out(out)
 
 def cross_attention_attnblock_forward(self, x):
-- 
cgit v1.2.3


From b70eaeb2005a5a9593119e7fd32b8072c2a208d5 Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Sat, 8 Oct 2022 04:10:35 +0300
Subject: delete broken and unnecessary aliases

---
 modules/sd_hijack.py | 10 ++++------
 1 file changed, 4 insertions(+), 6 deletions(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index cbdb9d3c..0e99c319 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -21,16 +21,14 @@ diffusionmodules_model_AttnBlock_forward = ldm.modules.diffusionmodules.model.At
 
 def apply_optimizations():
     ldm.modules.diffusionmodules.model.nonlinearity = silu
-    if cmd_opts.opt_split_attention_v1:
+    if not cmd_opts.disable_opt_xformers_attention and not (cmd_opts.opt_split_attention or torch.version.hip):
+        ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward
+        ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.cross_attention_attnblock_forward
+    elif cmd_opts.opt_split_attention_v1:
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1
     elif cmd_opts.opt_split_attention:
         ldm.modules.attention_CrossAttention_forward = sd_hijack_optimizations.split_cross_attention_forward
         ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.cross_attention_attnblock_forward
-    elif not cmd_opts.disable_opt_xformers_attention and not (cmd_opts.opt_split_attention or torch.version.hip):
-        ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward
-        ldm.modules.attention.CrossAttention._maybe_init = sd_hijack_optimizations._maybe_init
-        ldm.modules.attention.CrossAttention.attention_op = None
-        ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.cross_attention_attnblock_forward
 
 
 def undo_optimizations():
-- 
cgit v1.2.3


From a958f9b3fdea95c01d360aba1b6fe0ce3ea6b349 Mon Sep 17 00:00:00 2001
From: Jairo Correa <jn.j41r0@gmail.com>
Date: Fri, 7 Oct 2022 20:05:47 -0300
Subject: edit-attention browser compatibility and readme typo

---
 README.md                    | 2 +-
 javascript/edit-attention.js | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index a14a6330..0516c2cd 100644
--- a/README.md
+++ b/README.md
@@ -16,7 +16,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
 - Attention, specify parts of text that the model should pay more attention to
     - a man in a ((tuxedo)) - will pay more attention to tuxedo
     - a man in a (tuxedo:1.21) - alternative syntax
-    - select text and press ctrl+up or ctrl+down to aduotmatically adjust attention to selected text
+    - select text and press ctrl+up or ctrl+down to automatically adjust attention to selected text
 - Loopback, run img2img processing multiple times
 - X/Y plot, a way to draw a 2 dimensional plot of images with different parameters
 - Textual Inversion
diff --git a/javascript/edit-attention.js b/javascript/edit-attention.js
index c67ed579..0280c603 100644
--- a/javascript/edit-attention.js
+++ b/javascript/edit-attention.js
@@ -1,5 +1,5 @@
 addEventListener('keydown', (event) => {
-	let target = event.originalTarget;
+	let target = event.originalTarget || event.composedPath()[0];
 	if (!target.hasAttribute("placeholder")) return;
 	if (!target.placeholder.toLowerCase().includes("prompt")) return;
 
-- 
cgit v1.2.3


From f2055cb1d4ce45d7aaacc49d8ab5bec7791a8f47 Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Sat, 8 Oct 2022 01:47:02 -0400
Subject: Add hypernetwork support to split cross attention v1

* Add hypernetwork support to split_cross_attention_forward_v1
* Fix device check in esrgan_model.py to use devices.device_esrgan instead of shared.device
---
 modules/esrgan_model.py            |  2 +-
 modules/sd_hijack_optimizations.py | 18 ++++++++++++++----
 2 files changed, 15 insertions(+), 5 deletions(-)

diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py
index d17e730f..28548124 100644
--- a/modules/esrgan_model.py
+++ b/modules/esrgan_model.py
@@ -111,7 +111,7 @@ class UpscalerESRGAN(Upscaler):
             print("Unable to load %s from %s" % (self.model_path, filename))
             return None
 
-        pretrained_net = torch.load(filename, map_location='cpu' if shared.device.type == 'mps' else None)
+        pretrained_net = torch.load(filename, map_location='cpu' if devices.device_esrgan.type == 'mps' else None)
         crt_model = arch.RRDBNet(3, 3, 64, 23, gc=32)
 
         pretrained_net = fix_model_layers(crt_model, pretrained_net)
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index d9cca485..3351c740 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -12,13 +12,22 @@ from modules import shared
 def split_cross_attention_forward_v1(self, x, context=None, mask=None):
     h = self.heads
 
-    q = self.to_q(x)
+    q_in = self.to_q(x)
     context = default(context, x)
-    k = self.to_k(context)
-    v = self.to_v(context)
+
+    hypernetwork = shared.selected_hypernetwork()
+    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
+
+    if hypernetwork_layers is not None:
+        k_in = self.to_k(hypernetwork_layers[0](context))
+        v_in = self.to_v(hypernetwork_layers[1](context))
+    else:
+        k_in = self.to_k(context)
+        v_in = self.to_v(context)
     del context, x
 
-    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
+    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q_in, k_in, v_in))
+    del q_in, k_in, v_in
 
     r1 = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device)
     for i in range(0, q.shape[0], 2):
@@ -31,6 +40,7 @@ def split_cross_attention_forward_v1(self, x, context=None, mask=None):
 
         r1[i:end] = einsum('b i j, b j d -> b i d', s2, v[i:end])
         del s2
+    del q, k, v
 
     r2 = rearrange(r1, '(b h) n d -> b n (h d)', h=h)
     del r1
-- 
cgit v1.2.3


From e21e4732531299ef4895baccdb7a6493a3886924 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sat, 8 Oct 2022 05:34:17 +0100
Subject: Context Menus

---
 javascript/contextMenus.js | 165 +++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 165 insertions(+)
 create mode 100644 javascript/contextMenus.js

diff --git a/javascript/contextMenus.js b/javascript/contextMenus.js
new file mode 100644
index 00000000..99d1d3f7
--- /dev/null
+++ b/javascript/contextMenus.js
@@ -0,0 +1,165 @@
+
+contextMenuInit = function(){
+  let eventListenerApplied=false;
+  let menuSpecs = new Map();
+
+  const uid = function(){
+    return Date.now().toString(36) + Math.random().toString(36).substr(2);
+  }
+
+  function showContextMenu(event,element,menuEntries){
+    let posx = event.clientX + document.body.scrollLeft + document.documentElement.scrollLeft;
+    let posy = event.clientY + document.body.scrollTop + document.documentElement.scrollTop; 
+
+    let oldMenu = gradioApp().querySelector('#context-menu')
+    if(oldMenu){
+      oldMenu.remove()
+    }
+
+    let tabButton = gradioApp().querySelector('button')
+    let baseStyle = window.getComputedStyle(tabButton)
+
+    const contextMenu = document.createElement('nav')
+    contextMenu.id = "context-menu"
+    contextMenu.style.background = baseStyle.background
+    contextMenu.style.color = baseStyle.color
+    contextMenu.style.fontFamily = baseStyle.fontFamily
+    contextMenu.style.top = posy+'px'
+    contextMenu.style.left = posx+'px'
+
+
+
+    const contextMenuList = document.createElement('ul')
+    contextMenuList.className = 'context-menu-items';
+    contextMenu.append(contextMenuList);
+
+    menuEntries.forEach(function(entry){
+      let contextMenuEntry = document.createElement('a')
+      contextMenuEntry.innerHTML = entry['name']
+      contextMenuEntry.addEventListener("click", function(e) {
+        entry['func']();
+      })
+      contextMenuList.append(contextMenuEntry);
+
+    })
+
+    gradioApp().getRootNode().appendChild(contextMenu)
+
+    let menuWidth = contextMenu.offsetWidth + 4;
+    let menuHeight = contextMenu.offsetHeight + 4;
+
+    let windowWidth = window.innerWidth;
+    let windowHeight = window.innerHeight;
+
+    if ( (windowWidth - posx) < menuWidth ) {
+      contextMenu.style.left = windowWidth - menuWidth + "px";
+    }
+
+    if ( (windowHeight - posy) < menuHeight ) {
+      contextMenu.style.top = windowHeight - menuHeight + "px";
+    }
+
+  }
+
+  function appendContextMenuOption(targetEmementSelector,entryName,entryFunction){
+    
+    currentItems = menuSpecs.get(targetEmementSelector)
+    
+    if(!currentItems){
+      currentItems = []
+      menuSpecs.set(targetEmementSelector,currentItems);
+    }
+    let newItem = {'id':targetEmementSelector+'_'+uid(), 
+                   'name':entryName,
+                   'func':entryFunction,
+                   'isNew':true}
+
+    currentItems.push(newItem)
+    return newItem['id']
+  }
+
+  function removeContextMenuOption(uid){
+
+  }
+
+  function addContextMenuEventListener(){
+    if(eventListenerApplied){
+      return;
+    }
+    gradioApp().addEventListener("click", function(e) {
+      let source = e.composedPath()[0]
+      if(source.id && source.indexOf('check_progress')>-1){
+        return
+      }
+      
+      let oldMenu = gradioApp().querySelector('#context-menu')
+      if(oldMenu){
+        oldMenu.remove()
+      }
+    });
+    gradioApp().addEventListener("contextmenu", function(e) {
+      let oldMenu = gradioApp().querySelector('#context-menu')
+      if(oldMenu){
+        oldMenu.remove()
+      }
+      menuSpecs.forEach(function(v,k) {
+        if(e.composedPath()[0].matches(k)){
+          showContextMenu(e,e.composedPath()[0],v)
+          e.preventDefault()
+          return
+        }
+      })
+    });
+    eventListenerApplied=true
+  
+  }
+
+  return [appendContextMenuOption, removeContextMenuOption, addContextMenuEventListener]
+}
+
+initResponse = contextMenuInit()
+appendContextMenuOption     = initResponse[0]
+removeContextMenuOption     = initResponse[1]
+addContextMenuEventListener = initResponse[2]
+
+
+//Start example Context Menu Items
+generateOnRepeatId = appendContextMenuOption('#txt2img_generate','Generate forever',function(){
+  let genbutton = gradioApp().querySelector('#txt2img_generate');
+  let interruptbutton = gradioApp().querySelector('#txt2img_interrupt');
+  if(!interruptbutton.offsetParent){
+    genbutton.click();
+  }
+  clearInterval(window.generateOnRepeatInterval)
+  window.generateOnRepeatInterval = setInterval(function(){
+    if(!interruptbutton.offsetParent){
+      genbutton.click();
+    }
+  },
+  500)}
+)
+
+cancelGenerateForever = function(){ 
+  clearInterval(window.generateOnRepeatInterval) 
+  let interruptbutton = gradioApp().querySelector('#txt2img_interrupt');
+  if(interruptbutton.offsetParent){
+      interruptbutton.click();
+  }
+}
+
+appendContextMenuOption('#txt2img_interrupt','Cancel generate forever',cancelGenerateForever)
+appendContextMenuOption('#txt2img_generate','Cancel generate forever',cancelGenerateForever)
+
+appendContextMenuOption('#roll','Roll three',
+  function(){ 
+    let rollbutton = gradioApp().querySelector('#roll');
+    setTimeout(function(){rollbutton.click()},100)
+    setTimeout(function(){rollbutton.click()},200)
+    setTimeout(function(){rollbutton.click()},300)
+  }
+)
+//End example Context Menu Items
+
+onUiUpdate(function(){
+  addContextMenuEventListener()
+});
\ No newline at end of file
-- 
cgit v1.2.3


From 83749bfc72923b946abb825ebf4fdcc8b6035c8e Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sat, 8 Oct 2022 05:35:03 +0100
Subject: context menu styling

---
 style.css | 29 ++++++++++++++++++++++++++++-
 1 file changed, 28 insertions(+), 1 deletion(-)

diff --git a/style.css b/style.css
index da0729a2..50c5e557 100644
--- a/style.css
+++ b/style.css
@@ -410,4 +410,31 @@ input[type="range"]{
 
 #img2img_image div.h-60{
     height: 480px;
-}
\ No newline at end of file
+}
+
+#context-menu{
+    z-index:9999;
+    position:absolute;
+    display:block;
+    padding:0px 0;
+    border:2px solid #a55000;
+    border-radius:8px;
+    box-shadow:1px 1px 2px #CE6400;
+    width: 200px;
+}
+
+.context-menu-items{
+    list-style: none;
+    margin: 0;
+    padding: 0;
+}
+
+.context-menu-items a{
+    display:block;
+    padding:5px;
+    cursor:pointer;
+}
+
+.context-menu-items a:hover{
+    background: #a55000;
+}
-- 
cgit v1.2.3


From 21679435e531e729a4aea494e6cb9b7152ecdf75 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sat, 8 Oct 2022 05:46:42 +0100
Subject: implement removal

---
 javascript/contextMenus.js | 13 ++++++++++---
 1 file changed, 10 insertions(+), 3 deletions(-)

diff --git a/javascript/contextMenus.js b/javascript/contextMenus.js
index 99d1d3f7..2d82269f 100644
--- a/javascript/contextMenus.js
+++ b/javascript/contextMenus.js
@@ -79,7 +79,13 @@ contextMenuInit = function(){
   }
 
   function removeContextMenuOption(uid){
-
+    menuSpecs.forEach(function(v,k) {
+      let index = -1
+      v.forEach(function(e,ei){if(e['id']==uid){index=ei}})
+      if(index>=0){
+        v.splice(index, 1);
+      }
+    })
   }
 
   function addContextMenuEventListener(){
@@ -148,7 +154,8 @@ cancelGenerateForever = function(){
 }
 
 appendContextMenuOption('#txt2img_interrupt','Cancel generate forever',cancelGenerateForever)
-appendContextMenuOption('#txt2img_generate','Cancel generate forever',cancelGenerateForever)
+appendContextMenuOption('#txt2img_generate', 'Cancel generate forever',cancelGenerateForever)
+
 
 appendContextMenuOption('#roll','Roll three',
   function(){ 
@@ -162,4 +169,4 @@ appendContextMenuOption('#roll','Roll three',
 
 onUiUpdate(function(){
   addContextMenuEventListener()
-});
\ No newline at end of file
+});
-- 
cgit v1.2.3


From 87db6f01cc6b118fe0c82c36c6686d72d060c417 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 8 Oct 2022 10:15:29 +0300
Subject: add info about cross attention javascript shortcut code

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 0516c2cd..d6e1d50b 100644
--- a/README.md
+++ b/README.md
@@ -16,7 +16,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
 - Attention, specify parts of text that the model should pay more attention to
     - a man in a ((tuxedo)) - will pay more attention to tuxedo
     - a man in a (tuxedo:1.21) - alternative syntax
-    - select text and press ctrl+up or ctrl+down to automatically adjust attention to selected text
+    - select text and press ctrl+up or ctrl+down to automatically adjust attention to selected text (code contributed by anonymous user)
 - Loopback, run img2img processing multiple times
 - X/Y plot, a way to draw a 2 dimensional plot of images with different parameters
 - Textual Inversion
-- 
cgit v1.2.3


From 5d54f35c583bd5a3b0ee271a862827f1ca81ef09 Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Sat, 8 Oct 2022 11:55:02 +0300
Subject: add xformers attnblock and hypernetwork support

---
 modules/sd_hijack_optimizations.py | 20 ++++++++++++++++++--
 1 file changed, 18 insertions(+), 2 deletions(-)

diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index 7fb4a45e..c78d5838 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -98,8 +98,14 @@ def xformers_attention_forward(self, x, context=None, mask=None):
     h = self.heads
     q_in = self.to_q(x)
     context = default(context, x)
-    k_in = self.to_k(context)
-    v_in = self.to_v(context)
+    hypernetwork = shared.selected_hypernetwork()
+    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
+    if hypernetwork_layers is not None:
+        k_in = self.to_k(hypernetwork_layers[0](context))
+        v_in = self.to_v(hypernetwork_layers[1](context))
+    else:
+        k_in = self.to_k(context)
+        v_in = self.to_v(context)
     q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> b n h d', h=h), (q_in, k_in, v_in))
     del q_in, k_in, v_in
     out = xformers.ops.memory_efficient_attention(q, k, v, attn_bias=None)
@@ -169,3 +175,13 @@ def cross_attention_attnblock_forward(self, x):
         h3 += x
 
         return h3
+    
+    def xformers_attnblock_forward(self, x):
+        h_ = x
+        h_ = self.norm(h_)
+        q1 = self.q(h_).contiguous()
+        k1 = self.k(h_).contiguous()
+        v = self.v(h_).contiguous()
+        out = xformers.ops.memory_efficient_attention(q1, k1, v)
+        out = self.proj_out(out)
+        return x+out
-- 
cgit v1.2.3


From 76a616fa6b814c681eaf6edc87eb3001b8c2b6be Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Sat, 8 Oct 2022 11:55:38 +0300
Subject: Update sd_hijack_optimizations.py

---
 modules/sd_hijack_optimizations.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index c78d5838..ee58c7e4 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -176,7 +176,7 @@ def cross_attention_attnblock_forward(self, x):
 
         return h3
     
-    def xformers_attnblock_forward(self, x):
+def xformers_attnblock_forward(self, x):
         h_ = x
         h_ = self.norm(h_)
         q1 = self.q(h_).contiguous()
-- 
cgit v1.2.3


From 91d66f5520df416db718103d460550ad495e952d Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Sat, 8 Oct 2022 11:56:01 +0300
Subject: use new attnblock for xformers path

---
 modules/sd_hijack.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 0e99c319..3da8c8ce 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -23,7 +23,7 @@ def apply_optimizations():
     ldm.modules.diffusionmodules.model.nonlinearity = silu
     if not cmd_opts.disable_opt_xformers_attention and not (cmd_opts.opt_split_attention or torch.version.hip):
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward
-        ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.cross_attention_attnblock_forward
+        ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.xformers_attnblock_forward
     elif cmd_opts.opt_split_attention_v1:
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1
     elif cmd_opts.opt_split_attention:
-- 
cgit v1.2.3


From 616b7218f7c469d25c138634472017a7e18e742e Mon Sep 17 00:00:00 2001
From: leko <rexx0520@gmail.com>
Date: Fri, 7 Oct 2022 23:09:21 +0800
Subject: fix: handles when state_dict does not exist

---
 modules/sd_models.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/modules/sd_models.py b/modules/sd_models.py
index 8f794b47..9409d070 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -122,7 +122,11 @@ def load_model_weights(model, checkpoint_file, sd_model_hash):
     pl_sd = torch.load(checkpoint_file, map_location="cpu")
     if "global_step" in pl_sd:
         print(f"Global Step: {pl_sd['global_step']}")
-    sd = pl_sd["state_dict"]
+    
+    if "state_dict" in pl_sd:
+        sd = pl_sd["state_dict"]
+    else:
+        sd = pl_sd
 
     model.load_state_dict(sd, strict=False)
 
-- 
cgit v1.2.3


From 706d5944a075a6523ea7f00165d630efc085ca22 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 8 Oct 2022 13:38:57 +0300
Subject: let user choose his own prompt token count limit

---
 modules/processing.py |  6 ++++++
 modules/sd_hijack.py  | 13 +++++++------
 modules/shared.py     |  5 +++--
 3 files changed, 16 insertions(+), 8 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index f773a30e..d814d5ac 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -123,6 +123,7 @@ class Processed:
         self.index_of_first_image = index_of_first_image
         self.styles = p.styles
         self.job_timestamp = state.job_timestamp
+        self.max_prompt_tokens = opts.max_prompt_tokens
 
         self.eta = p.eta
         self.ddim_discretize = p.ddim_discretize
@@ -141,6 +142,7 @@ class Processed:
         self.all_subseeds = all_subseeds or [self.subseed]
         self.infotexts = infotexts or [info]
 
+
     def js(self):
         obj = {
             "prompt": self.prompt,
@@ -169,6 +171,7 @@ class Processed:
             "infotexts": self.infotexts,
             "styles": self.styles,
             "job_timestamp": self.job_timestamp,
+            "max_prompt_tokens": self.max_prompt_tokens,
         }
 
         return json.dumps(obj)
@@ -266,6 +269,8 @@ def fix_seed(p):
 def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration=0, position_in_batch=0):
     index = position_in_batch + iteration * p.batch_size
 
+    max_tokens = getattr(p, 'max_prompt_tokens', opts.max_prompt_tokens)
+
     generation_params = {
         "Steps": p.steps,
         "Sampler": sd_samplers.samplers[p.sampler_index].name,
@@ -281,6 +286,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration
         "Seed resize from": (None if p.seed_resize_from_w == 0 or p.seed_resize_from_h == 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"),
         "Denoising strength": getattr(p, 'denoising_strength', None),
         "Eta": (None if p.sampler is None or p.sampler.eta == p.sampler.default_eta else p.sampler.eta),
+        "Max tokens": (None if max_tokens == shared.vanilla_max_prompt_tokens else max_tokens)
     }
 
     generation_params.update(p.extra_generation_params)
diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index d68f89cc..340329c0 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -18,7 +18,6 @@ attention_CrossAttention_forward = ldm.modules.attention.CrossAttention.forward
 diffusionmodules_model_nonlinearity = ldm.modules.diffusionmodules.model.nonlinearity
 diffusionmodules_model_AttnBlock_forward = ldm.modules.diffusionmodules.model.AttnBlock.forward
 
-
 def apply_optimizations():
     undo_optimizations()
 
@@ -83,7 +82,7 @@ class StableDiffusionModelHijack:
             layer.padding_mode = 'circular' if enable else 'zeros'
 
     def tokenize(self, text):
-        max_length = self.clip.max_length - 2
+        max_length = opts.max_prompt_tokens - 2
         _, remade_batch_tokens, _, _, _, token_count = self.clip.process_text([text])
         return remade_batch_tokens[0], token_count, max_length
 
@@ -94,7 +93,6 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
         self.wrapped = wrapped
         self.hijack: StableDiffusionModelHijack = hijack
         self.tokenizer = wrapped.tokenizer
-        self.max_length = wrapped.max_length
         self.token_mults = {}
 
         tokens_with_parens = [(k, v) for k, v in self.tokenizer.get_vocab().items() if '(' in k or ')' in k or '[' in k or ']' in k]
@@ -116,7 +114,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
     def tokenize_line(self, line, used_custom_terms, hijack_comments):
         id_start = self.wrapped.tokenizer.bos_token_id
         id_end = self.wrapped.tokenizer.eos_token_id
-        maxlen = self.wrapped.max_length
+        maxlen = opts.max_prompt_tokens
 
         if opts.enable_emphasis:
             parsed = prompt_parser.parse_prompt_attention(line)
@@ -191,7 +189,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
     def process_text_old(self, text):
         id_start = self.wrapped.tokenizer.bos_token_id
         id_end = self.wrapped.tokenizer.eos_token_id
-        maxlen = self.wrapped.max_length
+        maxlen = self.wrapped.max_length  # you get to stay at 77
         used_custom_terms = []
         remade_batch_tokens = []
         overflowing_words = []
@@ -268,8 +266,11 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
         if len(used_custom_terms) > 0:
             self.hijack.comments.append("Used embeddings: " + ", ".join([f'{word} [{checksum}]' for word, checksum in used_custom_terms]))
 
+        position_ids_array = [min(x, 75) for x in range(len(remade_batch_tokens[0])-1)] + [76]
+        position_ids = torch.asarray(position_ids_array, device=devices.device).expand((1, -1))
+
         tokens = torch.asarray(remade_batch_tokens).to(device)
-        outputs = self.wrapped.transformer(input_ids=tokens)
+        outputs = self.wrapped.transformer(input_ids=tokens, position_ids=position_ids)
         z = outputs.last_hidden_state
 
         # restoring original mean is likely not correct, but it seems to work well to prevent artifacts that happen otherwise
diff --git a/modules/shared.py b/modules/shared.py
index 879d8424..864e772c 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -118,8 +118,8 @@ prompt_styles = modules.styles.StyleDatabase(styles_filename)
 interrogator = modules.interrogate.InterrogateModels("interrogate")
 
 face_restorers = []
-# This was moved to webui.py with the other model "setup" calls.
-# modules.sd_models.list_models()
+
+vanilla_max_prompt_tokens = 77
 
 
 def realesrgan_models_names():
@@ -221,6 +221,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "use_old_emphasis_implementation": OptionInfo(False, "Use old emphasis implementation. Can be useful to reproduce old seeds."),
     "enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"),
     "filter_nsfw": OptionInfo(False, "Filter NSFW content"),
+    "max_prompt_tokens": OptionInfo(vanilla_max_prompt_tokens, f"Max prompt token count. Two tokens are reserved for for start and end. Default is {vanilla_max_prompt_tokens}. Setting this to a different value will result in different pictures for same seed.", gr.Number, {"precision": 0}),
     "random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}),
 }))
 
-- 
cgit v1.2.3


From 786d9f63aaa4515df82eb2cf357ea92f3dae1e29 Mon Sep 17 00:00:00 2001
From: Trung Ngo <codem01@gmail.com>
Date: Tue, 4 Oct 2022 22:56:30 -0500
Subject: Add button to skip the current iteration

---
 javascript/hints.js       |  1 +
 javascript/progressbar.js | 20 ++++++++++++++------
 modules/img2img.py        |  4 ++++
 modules/processing.py     |  4 ++++
 modules/shared.py         |  5 +++++
 modules/ui.py             |  8 ++++++++
 style.css                 | 14 ++++++++++++--
 webui.py                  |  1 +
 8 files changed, 49 insertions(+), 8 deletions(-)

diff --git a/javascript/hints.js b/javascript/hints.js
index 8adcd983..8e352e94 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -35,6 +35,7 @@ titles = {
     "Denoising strength": "Determines how little respect the algorithm should have for image's content. At 0, nothing will change, and at 1 you'll get an unrelated image. With values below 1.0, processing will take less steps than the Sampling Steps slider specifies.",
     "Denoising strength change factor": "In loopback mode, on each loop the denoising strength is multiplied by this value. <1 means decreasing variety so your sequence will converge on a fixed picture. >1 means increasing variety so your sequence will become more and more chaotic.",
 
+    "Skip": "Stop processing current image and continue processing.",
     "Interrupt": "Stop processing images and return any results accumulated so far.",
     "Save": "Write image to a directory (default - log/images) and generation parameters into csv file.",
 
diff --git a/javascript/progressbar.js b/javascript/progressbar.js
index f9e9290e..4395a215 100644
--- a/javascript/progressbar.js
+++ b/javascript/progressbar.js
@@ -1,8 +1,9 @@
 // code related to showing and updating progressbar shown as the image is being made
 global_progressbars = {}
 
-function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_interrupt, id_preview, id_gallery){
+function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_skip, id_interrupt, id_preview, id_gallery){
     var progressbar = gradioApp().getElementById(id_progressbar)
+    var skip = id_skip ? gradioApp().getElementById(id_skip) : null
     var interrupt = gradioApp().getElementById(id_interrupt)
     
     if(opts.show_progress_in_title && progressbar && progressbar.offsetParent){
@@ -32,30 +33,37 @@ function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_inte
 
                 var progressDiv = gradioApp().querySelectorAll('#' + id_progressbar_span).length > 0;
                 if(!progressDiv){
+                    if (skip) {
+                        skip.style.display = "none"
+                    }
                     interrupt.style.display = "none"
                 }
             }
 
-            window.setTimeout(function(){ requestMoreProgress(id_part, id_progressbar_span, id_interrupt) }, 500)
+            window.setTimeout(function() { requestMoreProgress(id_part, id_progressbar_span, id_skip, id_interrupt) }, 500)
         });
         mutationObserver.observe( progressbar, { childList:true, subtree:true })
 	}
 }
 
 onUiUpdate(function(){
-    check_progressbar('txt2img', 'txt2img_progressbar', 'txt2img_progress_span', 'txt2img_interrupt', 'txt2img_preview', 'txt2img_gallery')
-    check_progressbar('img2img', 'img2img_progressbar', 'img2img_progress_span', 'img2img_interrupt', 'img2img_preview', 'img2img_gallery')
-    check_progressbar('ti', 'ti_progressbar', 'ti_progress_span', 'ti_interrupt', 'ti_preview', 'ti_gallery')
+    check_progressbar('txt2img', 'txt2img_progressbar', 'txt2img_progress_span', 'txt2img_skip', 'txt2img_interrupt', 'txt2img_preview', 'txt2img_gallery')
+    check_progressbar('img2img', 'img2img_progressbar', 'img2img_progress_span', 'img2img_skip', 'img2img_interrupt', 'img2img_preview', 'img2img_gallery')
+    check_progressbar('ti', 'ti_progressbar', 'ti_progress_span', '', 'ti_interrupt', 'ti_preview', 'ti_gallery')
 })
 
-function requestMoreProgress(id_part, id_progressbar_span, id_interrupt){
+function requestMoreProgress(id_part, id_progressbar_span, id_skip, id_interrupt){
     btn = gradioApp().getElementById(id_part+"_check_progress");
     if(btn==null) return;
 
     btn.click();
     var progressDiv = gradioApp().querySelectorAll('#' + id_progressbar_span).length > 0;
+    var skip = id_skip ? gradioApp().getElementById(id_skip) : null
     var interrupt = gradioApp().getElementById(id_interrupt)
     if(progressDiv && interrupt){
+        if (skip) {
+            skip.style.display = "block"
+        }
         interrupt.style.display = "block"
     }
 }
diff --git a/modules/img2img.py b/modules/img2img.py
index da212d72..e60b7e0f 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -32,6 +32,10 @@ def process_batch(p, input_dir, output_dir, args):
 
     for i, image in enumerate(images):
         state.job = f"{i+1} out of {len(images)}"
+        if state.skipped:
+            state.skipped = False
+            state.interrupted = False
+            continue
 
         if state.interrupted:
             break
diff --git a/modules/processing.py b/modules/processing.py
index d814d5ac..6805039c 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -355,6 +355,10 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
             state.job_count = p.n_iter
 
         for n in range(p.n_iter):
+            if state.skipped:
+                state.skipped = False
+                state.interrupted = False
+            
             if state.interrupted:
                 break
 
diff --git a/modules/shared.py b/modules/shared.py
index 864e772c..7f802bd9 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -84,6 +84,7 @@ def selected_hypernetwork():
 
 
 class State:
+    skipped = False
     interrupted = False
     job = ""
     job_no = 0
@@ -96,6 +97,10 @@ class State:
     current_image_sampling_step = 0
     textinfo = None
 
+    def skip(self):
+        self.skipped = True
+        self.interrupted = True
+
     def interrupt(self):
         self.interrupted = True
 
diff --git a/modules/ui.py b/modules/ui.py
index 4f18126f..e3e62fdd 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -191,6 +191,7 @@ def wrap_gradio_call(func, extra_outputs=None):
         # last item is always HTML
         res[-1] += f"<div class='performance'><p class='time'>Time taken: <wbr>{elapsed_text}</p>{vram_html}</div>"
 
+        shared.state.skipped = False
         shared.state.interrupted = False
         shared.state.job_count = 0
 
@@ -411,9 +412,16 @@ def create_toprow(is_img2img):
 
         with gr.Column(scale=1):
             with gr.Row():
+                skip = gr.Button('Skip', elem_id=f"{id_part}_skip")
                 interrupt = gr.Button('Interrupt', elem_id=f"{id_part}_interrupt")
                 submit = gr.Button('Generate', elem_id=f"{id_part}_generate", variant='primary')
 
+                skip.click(
+                    fn=lambda: shared.state.skip(),
+                    inputs=[],
+                    outputs=[],
+                )
+
                 interrupt.click(
                     fn=lambda: shared.state.interrupt(),
                     inputs=[],
diff --git a/style.css b/style.css
index 50c5e557..6904fc50 100644
--- a/style.css
+++ b/style.css
@@ -393,10 +393,20 @@ input[type="range"]{
 
 #txt2img_interrupt, #img2img_interrupt{
   position: absolute;
-  width: 100%;
+  width: 50%;
   height: 72px;
   background: #b4c0cc;
-  border-radius: 8px;
+  border-radius: 0px;
+  display: none;
+}
+
+#txt2img_skip, #img2img_skip{
+  position: absolute;
+  width: 50%;
+  right: 0px;
+  height: 72px;
+  background: #b4c0cc;
+  border-radius: 0px;
   display: none;
 }
 
diff --git a/webui.py b/webui.py
index 480360fe..3b4cf5e9 100644
--- a/webui.py
+++ b/webui.py
@@ -58,6 +58,7 @@ def wrap_gradio_gpu_call(func, extra_outputs=None):
         shared.state.current_latent = None
         shared.state.current_image = None
         shared.state.current_image_sampling_step = 0
+        shared.state.skipped = False
         shared.state.interrupted = False
         shared.state.textinfo = None
 
-- 
cgit v1.2.3


From 00117a07efbbe8482add12262a179326541467de Mon Sep 17 00:00:00 2001
From: Trung Ngo <codem01@gmail.com>
Date: Sat, 8 Oct 2022 05:33:21 -0500
Subject: check specifically for skipped

---
 modules/img2img.py     | 2 --
 modules/processing.py  | 3 +--
 modules/sd_samplers.py | 4 ++--
 modules/shared.py      | 1 -
 4 files changed, 3 insertions(+), 7 deletions(-)

diff --git a/modules/img2img.py b/modules/img2img.py
index e60b7e0f..24126774 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -34,8 +34,6 @@ def process_batch(p, input_dir, output_dir, args):
         state.job = f"{i+1} out of {len(images)}"
         if state.skipped:
             state.skipped = False
-            state.interrupted = False
-            continue
 
         if state.interrupted:
             break
diff --git a/modules/processing.py b/modules/processing.py
index 6805039c..3657fe69 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -357,7 +357,6 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
         for n in range(p.n_iter):
             if state.skipped:
                 state.skipped = False
-                state.interrupted = False
             
             if state.interrupted:
                 break
@@ -385,7 +384,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
             with devices.autocast():
                 samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength)
 
-            if state.interrupted:
+            if state.interrupted or state.skipped:
 
                 # if we are interruped, sample returns just noise
                 # use the image collected previously in sampler loop
diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index df17e93c..13a8b322 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -106,7 +106,7 @@ def extended_tdqm(sequence, *args, desc=None, **kwargs):
     seq = sequence if cmd_opts.disable_console_progressbars else tqdm.tqdm(sequence, *args, desc=state.job, file=shared.progress_print_out, **kwargs)
 
     for x in seq:
-        if state.interrupted:
+        if state.interrupted or state.skipped:
             break
 
         yield x
@@ -254,7 +254,7 @@ def extended_trange(sampler, count, *args, **kwargs):
     seq = range(count) if cmd_opts.disable_console_progressbars else tqdm.trange(count, *args, desc=state.job, file=shared.progress_print_out, **kwargs)
 
     for x in seq:
-        if state.interrupted:
+        if state.interrupted or state.skipped:
             break
 
         if sampler.stop_at is not None and x > sampler.stop_at:
diff --git a/modules/shared.py b/modules/shared.py
index 7f802bd9..ca462628 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -99,7 +99,6 @@ class State:
 
     def skip(self):
         self.skipped = True
-        self.interrupted = True
 
     def interrupt(self):
         self.interrupted = True
-- 
cgit v1.2.3


From 4999eb2ef9b30e8c42ca7e4a94d4bbffe4d1f015 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 8 Oct 2022 14:25:47 +0300
Subject: do not let user choose his own prompt token count limit

---
 README.md             |  1 +
 modules/processing.py |  5 -----
 modules/sd_hijack.py  | 25 ++++++++++++-------------
 modules/shared.py     |  3 ---
 4 files changed, 13 insertions(+), 21 deletions(-)

diff --git a/README.md b/README.md
index d6e1d50b..ef9b5e31 100644
--- a/README.md
+++ b/README.md
@@ -65,6 +65,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
 - [Composable-Diffusion](https://energy-based-model.github.io/Compositional-Visual-Generation-with-Composable-Diffusion-Models/), a way to use multiple prompts at once
      - separate prompts using uppercase `AND`
      - also supports weights for prompts: `a cat :1.2 AND a dog AND a penguin :2.2`
+- No token limit for prompts (original stable diffusion lets you use up to 75 tokens)
 
 ## Installation and Running
 Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for both [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended) and [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs.
diff --git a/modules/processing.py b/modules/processing.py
index 3657fe69..d5162ddc 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -123,7 +123,6 @@ class Processed:
         self.index_of_first_image = index_of_first_image
         self.styles = p.styles
         self.job_timestamp = state.job_timestamp
-        self.max_prompt_tokens = opts.max_prompt_tokens
 
         self.eta = p.eta
         self.ddim_discretize = p.ddim_discretize
@@ -171,7 +170,6 @@ class Processed:
             "infotexts": self.infotexts,
             "styles": self.styles,
             "job_timestamp": self.job_timestamp,
-            "max_prompt_tokens": self.max_prompt_tokens,
         }
 
         return json.dumps(obj)
@@ -269,8 +267,6 @@ def fix_seed(p):
 def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration=0, position_in_batch=0):
     index = position_in_batch + iteration * p.batch_size
 
-    max_tokens = getattr(p, 'max_prompt_tokens', opts.max_prompt_tokens)
-
     generation_params = {
         "Steps": p.steps,
         "Sampler": sd_samplers.samplers[p.sampler_index].name,
@@ -286,7 +282,6 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration
         "Seed resize from": (None if p.seed_resize_from_w == 0 or p.seed_resize_from_h == 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"),
         "Denoising strength": getattr(p, 'denoising_strength', None),
         "Eta": (None if p.sampler is None or p.sampler.eta == p.sampler.default_eta else p.sampler.eta),
-        "Max tokens": (None if max_tokens == shared.vanilla_max_prompt_tokens else max_tokens)
     }
 
     generation_params.update(p.extra_generation_params)
diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 340329c0..2c1332c9 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -36,6 +36,13 @@ def undo_optimizations():
     ldm.modules.diffusionmodules.model.AttnBlock.forward = diffusionmodules_model_AttnBlock_forward
 
 
+def get_target_prompt_token_count(token_count):
+    if token_count < 75:
+        return 75
+
+    return math.ceil(token_count / 10) * 10
+
+
 class StableDiffusionModelHijack:
     fixes = None
     comments = []
@@ -84,7 +91,7 @@ class StableDiffusionModelHijack:
     def tokenize(self, text):
         max_length = opts.max_prompt_tokens - 2
         _, remade_batch_tokens, _, _, _, token_count = self.clip.process_text([text])
-        return remade_batch_tokens[0], token_count, max_length
+        return remade_batch_tokens[0], token_count, get_target_prompt_token_count(token_count)
 
 
 class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
@@ -114,7 +121,6 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
     def tokenize_line(self, line, used_custom_terms, hijack_comments):
         id_start = self.wrapped.tokenizer.bos_token_id
         id_end = self.wrapped.tokenizer.eos_token_id
-        maxlen = opts.max_prompt_tokens
 
         if opts.enable_emphasis:
             parsed = prompt_parser.parse_prompt_attention(line)
@@ -146,19 +152,12 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
                     used_custom_terms.append((embedding.name, embedding.checksum()))
                     i += embedding_length_in_tokens
 
-        if len(remade_tokens) > maxlen - 2:
-            vocab = {v: k for k, v in self.wrapped.tokenizer.get_vocab().items()}
-            ovf = remade_tokens[maxlen - 2:]
-            overflowing_words = [vocab.get(int(x), "") for x in ovf]
-            overflowing_text = self.wrapped.tokenizer.convert_tokens_to_string(''.join(overflowing_words))
-            hijack_comments.append(f"Warning: too many input tokens; some ({len(overflowing_words)}) have been truncated:\n{overflowing_text}\n")
-
         token_count = len(remade_tokens)
-        remade_tokens = remade_tokens + [id_end] * (maxlen - 2 - len(remade_tokens))
-        remade_tokens = [id_start] + remade_tokens[0:maxlen - 2] + [id_end]
+        prompt_target_length = get_target_prompt_token_count(token_count)
+        tokens_to_add = prompt_target_length - len(remade_tokens) + 1
 
-        multipliers = multipliers + [1.0] * (maxlen - 2 - len(multipliers))
-        multipliers = [1.0] + multipliers[0:maxlen - 2] + [1.0]
+        remade_tokens = [id_start] + remade_tokens + [id_end] * tokens_to_add
+        multipliers = [1.0] + multipliers + [1.0] * tokens_to_add
 
         return remade_tokens, fixes, multipliers, token_count
 
diff --git a/modules/shared.py b/modules/shared.py
index ca462628..475d7e52 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -123,8 +123,6 @@ interrogator = modules.interrogate.InterrogateModels("interrogate")
 
 face_restorers = []
 
-vanilla_max_prompt_tokens = 77
-
 
 def realesrgan_models_names():
     import modules.realesrgan_model
@@ -225,7 +223,6 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "use_old_emphasis_implementation": OptionInfo(False, "Use old emphasis implementation. Can be useful to reproduce old seeds."),
     "enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"),
     "filter_nsfw": OptionInfo(False, "Filter NSFW content"),
-    "max_prompt_tokens": OptionInfo(vanilla_max_prompt_tokens, f"Max prompt token count. Two tokens are reserved for for start and end. Default is {vanilla_max_prompt_tokens}. Setting this to a different value will result in different pictures for same seed.", gr.Number, {"precision": 0}),
     "random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}),
 }))
 
-- 
cgit v1.2.3


From 4201fd14f5769a4cf6723d2bc5495c3c84a2cd00 Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Sat, 8 Oct 2022 14:42:34 +0300
Subject: install xformers

---
 launch.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/launch.py b/launch.py
index 75edb66a..f3fbe16a 100644
--- a/launch.py
+++ b/launch.py
@@ -124,6 +124,9 @@ if not is_installed("gfpgan"):
 if not is_installed("clip"):
     run_pip(f"install {clip_package}", "clip")
 
+if not is_installed("xformers"):
+    run_pip("install https://github.com/C43H66N12O12S2/stable-diffusion-webui/releases/download/a/xformers-0.0.14.dev0-cp310-cp310-win_amd64.whl", "xformers")
+
 os.makedirs(dir_repos, exist_ok=True)
 
 git_clone("https://github.com/CompVis/stable-diffusion.git", repo_dir('stable-diffusion'), "Stable Diffusion", stable_diffusion_commit_hash)
-- 
cgit v1.2.3


From 3f166be1b60ff2ab33a6d2646809ec3f48796303 Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Sat, 8 Oct 2022 14:42:50 +0300
Subject: Update requirements.txt

---
 requirements.txt | 1 -
 1 file changed, 1 deletion(-)

diff --git a/requirements.txt b/requirements.txt
index 304a066a..81641d68 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -24,4 +24,3 @@ torchdiffeq
 kornia
 lark
 functorch
-#xformers?
-- 
cgit v1.2.3


From 77f4237d1c3af1756e7dab2699e3dcebad5619d6 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 8 Oct 2022 15:25:59 +0300
Subject: fix bugs related to variable prompt lengths

---
 modules/sd_hijack.py   | 14 +++++++++-----
 modules/sd_samplers.py | 35 ++++++++++++++++++++++++++++-------
 2 files changed, 37 insertions(+), 12 deletions(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 2c1332c9..7e7fde0f 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -89,7 +89,6 @@ class StableDiffusionModelHijack:
             layer.padding_mode = 'circular' if enable else 'zeros'
 
     def tokenize(self, text):
-        max_length = opts.max_prompt_tokens - 2
         _, remade_batch_tokens, _, _, _, token_count = self.clip.process_text([text])
         return remade_batch_tokens[0], token_count, get_target_prompt_token_count(token_count)
 
@@ -174,7 +173,8 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
             if line in cache:
                 remade_tokens, fixes, multipliers = cache[line]
             else:
-                remade_tokens, fixes, multipliers, token_count = self.tokenize_line(line, used_custom_terms, hijack_comments)
+                remade_tokens, fixes, multipliers, current_token_count = self.tokenize_line(line, used_custom_terms, hijack_comments)
+                token_count = max(current_token_count, token_count)
 
                 cache[line] = (remade_tokens, fixes, multipliers)
 
@@ -265,15 +265,19 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
         if len(used_custom_terms) > 0:
             self.hijack.comments.append("Used embeddings: " + ", ".join([f'{word} [{checksum}]' for word, checksum in used_custom_terms]))
 
-        position_ids_array = [min(x, 75) for x in range(len(remade_batch_tokens[0])-1)] + [76]
+        target_token_count = get_target_prompt_token_count(token_count) + 2
+
+        position_ids_array = [min(x, 75) for x in range(target_token_count-1)] + [76]
         position_ids = torch.asarray(position_ids_array, device=devices.device).expand((1, -1))
 
-        tokens = torch.asarray(remade_batch_tokens).to(device)
+        remade_batch_tokens_of_same_length = [x + [self.wrapped.tokenizer.eos_token_id] * (target_token_count - len(x)) for x in remade_batch_tokens]
+        tokens = torch.asarray(remade_batch_tokens_of_same_length).to(device)
         outputs = self.wrapped.transformer(input_ids=tokens, position_ids=position_ids)
         z = outputs.last_hidden_state
 
         # restoring original mean is likely not correct, but it seems to work well to prevent artifacts that happen otherwise
-        batch_multipliers = torch.asarray(batch_multipliers).to(device)
+        batch_multipliers_of_same_length = [x + [1.0] * (target_token_count - len(x)) for x in batch_multipliers]
+        batch_multipliers = torch.asarray(batch_multipliers_of_same_length).to(device)
         original_mean = z.mean()
         z *= batch_multipliers.reshape(batch_multipliers.shape + (1,)).expand(z.shape)
         new_mean = z.mean()
diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index 13a8b322..eade0dbb 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -142,6 +142,16 @@ class VanillaStableDiffusionSampler:
         assert all([len(conds) == 1 for conds in conds_list]), 'composition via AND is not supported for DDIM/PLMS samplers'
         cond = tensor
 
+        # for DDIM, shapes must match, we can't just process cond and uncond independently;
+        # filling unconditional_conditioning with repeats of the last vector to match length is
+        # not 100% correct but should work well enough
+        if unconditional_conditioning.shape[1] < cond.shape[1]:
+            last_vector = unconditional_conditioning[:, -1:]
+            last_vector_repeated = last_vector.repeat([1, cond.shape[1] - unconditional_conditioning.shape[1], 1])
+            unconditional_conditioning = torch.hstack([unconditional_conditioning, last_vector_repeated])
+        elif unconditional_conditioning.shape[1] > cond.shape[1]:
+            unconditional_conditioning = unconditional_conditioning[:, :cond.shape[1]]
+
         if self.mask is not None:
             img_orig = self.sampler.model.q_sample(self.init_latent, ts)
             x_dec = img_orig * self.mask + self.nmask * x_dec
@@ -221,18 +231,29 @@ class CFGDenoiser(torch.nn.Module):
 
         x_in = torch.cat([torch.stack([x[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [x])
         sigma_in = torch.cat([torch.stack([sigma[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [sigma])
-        cond_in = torch.cat([tensor, uncond])
 
-        if shared.batch_cond_uncond:
-            x_out = self.inner_model(x_in, sigma_in, cond=cond_in)
+        if tensor.shape[1] == uncond.shape[1]:
+            cond_in = torch.cat([tensor, uncond])
+
+            if shared.batch_cond_uncond:
+                x_out = self.inner_model(x_in, sigma_in, cond=cond_in)
+            else:
+                x_out = torch.zeros_like(x_in)
+                for batch_offset in range(0, x_out.shape[0], batch_size):
+                    a = batch_offset
+                    b = a + batch_size
+                    x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond=cond_in[a:b])
         else:
             x_out = torch.zeros_like(x_in)
-            for batch_offset in range(0, x_out.shape[0], batch_size):
+            batch_size = batch_size*2 if shared.batch_cond_uncond else batch_size
+            for batch_offset in range(0, tensor.shape[0], batch_size):
                 a = batch_offset
-                b = a + batch_size
-                x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond=cond_in[a:b])
+                b = min(a + batch_size, tensor.shape[0])
+                x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond=tensor[a:b])
+
+            x_out[-uncond.shape[0]:] = self.inner_model(x_in[-uncond.shape[0]:], sigma_in[-uncond.shape[0]:], cond=uncond)
 
-        denoised_uncond = x_out[-batch_size:]
+        denoised_uncond = x_out[-uncond.shape[0]:]
         denoised = torch.clone(denoised_uncond)
 
         for i, conds in enumerate(conds_list):
-- 
cgit v1.2.3


From 7001bffe0247804793dfabb69ac96d832572ccd0 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 8 Oct 2022 15:43:25 +0300
Subject: fix AND broken for long prompts

---
 modules/prompt_parser.py | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py
index f00256f2..15666073 100644
--- a/modules/prompt_parser.py
+++ b/modules/prompt_parser.py
@@ -239,6 +239,15 @@ def reconstruct_multicond_batch(c: MulticondLearnedConditioning, current_step):
 
         conds_list.append(conds_for_batch)
 
+    # if prompts have wildly different lengths above the limit we'll get tensors fo different shapes
+    # and won't be able to torch.stack them. So this fixes that.
+    token_count = max([x.shape[0] for x in tensors])
+    for i in range(len(tensors)):
+        if tensors[i].shape[0] != token_count:
+            last_vector = tensors[i][-1:]
+            last_vector_repeated = last_vector.repeat([token_count - tensors[i].shape[0], 1])
+            tensors[i] = torch.vstack([tensors[i], last_vector_repeated])
+
     return conds_list, torch.stack(tensors).to(device=param.device, dtype=param.dtype)
 
 
-- 
cgit v1.2.3


From 772db721a52da374d627b60994222051f26c27a7 Mon Sep 17 00:00:00 2001
From: ddPn08 <pyn.g.1125@gmail.com>
Date: Fri, 7 Oct 2022 23:02:07 +0900
Subject: fix glob path in hypernetwork.py

---
 modules/hypernetwork.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/hypernetwork.py b/modules/hypernetwork.py
index c7b86682..7f062242 100644
--- a/modules/hypernetwork.py
+++ b/modules/hypernetwork.py
@@ -43,7 +43,7 @@ class Hypernetwork:
 def load_hypernetworks(path):
     res = {}
 
-    for filename in glob.iglob(path + '**/*.pt', recursive=True):
+    for filename in glob.iglob(os.path.join(path, '**/*.pt'), recursive=True):
         try:
             hn = Hypernetwork(filename)
             res[hn.name] = hn
-- 
cgit v1.2.3


From 32e428ff19c28c87bb2ed362316b928b372e3a70 Mon Sep 17 00:00:00 2001
From: guaneec <guaneec@users.noreply.github.com>
Date: Sat, 8 Oct 2022 16:01:34 +0800
Subject: Remove duplicate event listeners

---
 javascript/imageviewer.js | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/javascript/imageviewer.js b/javascript/imageviewer.js
index 3a0baac8..4c0e8f4b 100644
--- a/javascript/imageviewer.js
+++ b/javascript/imageviewer.js
@@ -86,6 +86,9 @@ function showGalleryImage(){
         
         if(fullImg_preview != null){
             fullImg_preview.forEach(function function_name(e) {
+                if (e.dataset.modded)
+                    return;
+                e.dataset.modded = true;
                 if(e && e.parentElement.tagName == 'DIV'){
 
                     e.style.cursor='pointer'
-- 
cgit v1.2.3


From 5f85a74b00c0154bfd559dc67edfa7e30342b7c9 Mon Sep 17 00:00:00 2001
From: MrCheeze <fishycheeze@yahoo.ca>
Date: Fri, 7 Oct 2022 17:48:34 -0400
Subject: fix bug where when using prompt composition, hijack_comments
 generated before the final AND will be dropped

---
 modules/processing.py | 1 +
 modules/sd_hijack.py  | 5 ++++-
 2 files changed, 5 insertions(+), 1 deletion(-)

diff --git a/modules/processing.py b/modules/processing.py
index d5162ddc..8240ee27 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -313,6 +313,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
         os.makedirs(p.outpath_grids, exist_ok=True)
 
     modules.sd_hijack.model_hijack.apply_circular(p.tiling)
+    modules.sd_hijack.model_hijack.clear_comments()
 
     comments = {}
 
diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 7e7fde0f..ba808a39 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -88,6 +88,9 @@ class StableDiffusionModelHijack:
         for layer in [layer for layer in self.layers if type(layer) == torch.nn.Conv2d]:
             layer.padding_mode = 'circular' if enable else 'zeros'
 
+    def clear_comments(self):
+        self.comments = []
+
     def tokenize(self, text):
         _, remade_batch_tokens, _, _, _, token_count = self.clip.process_text([text])
         return remade_batch_tokens[0], token_count, get_target_prompt_token_count(token_count)
@@ -260,7 +263,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
             batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = self.process_text(text)
 
         self.hijack.fixes = hijack_fixes
-        self.hijack.comments = hijack_comments
+        self.hijack.comments += hijack_comments
 
         if len(used_custom_terms) > 0:
             self.hijack.comments.append("Used embeddings: " + ", ".join([f'{word} [{checksum}]' for word, checksum in used_custom_terms]))
-- 
cgit v1.2.3


From d0e85873ac72416d32dee8720dc9e93ab3d3e236 Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Sat, 8 Oct 2022 16:13:26 +0300
Subject: check for OS and env variable

---
 launch.py | 9 +++++++--
 1 file changed, 7 insertions(+), 2 deletions(-)

diff --git a/launch.py b/launch.py
index f3fbe16a..a2089b3b 100644
--- a/launch.py
+++ b/launch.py
@@ -4,6 +4,7 @@ import os
 import sys
 import importlib.util
 import shlex
+import platform
 
 dir_repos = "repositories"
 dir_tmp = "tmp"
@@ -31,6 +32,7 @@ def extract_arg(args, name):
 
 
 args, skip_torch_cuda_test = extract_arg(args, '--skip-torch-cuda-test')
+args, xformers = extract_arg(args, '--xformers')
 
 
 def repo_dir(name):
@@ -124,8 +126,11 @@ if not is_installed("gfpgan"):
 if not is_installed("clip"):
     run_pip(f"install {clip_package}", "clip")
 
-if not is_installed("xformers"):
-    run_pip("install https://github.com/C43H66N12O12S2/stable-diffusion-webui/releases/download/a/xformers-0.0.14.dev0-cp310-cp310-win_amd64.whl", "xformers")
+if not is_installed("xformers") and xformers:
+    if platform.system() == "Windows":
+        run_pip("install https://github.com/C43H66N12O12S2/stable-diffusion-webui/releases/download/a/xformers-0.0.14.dev0-cp310-cp310-win_amd64.whl", "xformers")
+    elif:
+        run_pip("install xformers", "xformers")
 
 os.makedirs(dir_repos, exist_ok=True)
 
-- 
cgit v1.2.3


From 26b459a3799c5cdf71ca8ed5315a99f69c69f02c Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Sat, 8 Oct 2022 16:20:04 +0300
Subject: default to split attention if cuda is available and xformers is not

---
 modules/sd_hijack.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 3da8c8ce..04adcf03 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -21,12 +21,12 @@ diffusionmodules_model_AttnBlock_forward = ldm.modules.diffusionmodules.model.At
 
 def apply_optimizations():
     ldm.modules.diffusionmodules.model.nonlinearity = silu
-    if not cmd_opts.disable_opt_xformers_attention and not (cmd_opts.opt_split_attention or torch.version.hip):
+    if not cmd_opts.disable_opt_xformers_attention and not (cmd_opts.opt_split_attention or torch.version.hip or shared.xformers_available):
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward
         ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.xformers_attnblock_forward
     elif cmd_opts.opt_split_attention_v1:
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1
-    elif cmd_opts.opt_split_attention:
+    elif cmd_opts.opt_split_attention or torch.cuda.is_available():
         ldm.modules.attention_CrossAttention_forward = sd_hijack_optimizations.split_cross_attention_forward
         ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.cross_attention_attnblock_forward
 
-- 
cgit v1.2.3


From ddfa9a97865c732193023a71521c5b7b53d8571b Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Sat, 8 Oct 2022 16:20:41 +0300
Subject: add xformers_available shared variable

---
 modules/shared.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/shared.py b/modules/shared.py
index 8cc3b2fe..6ed4b802 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -74,7 +74,7 @@ device = devices.device
 
 batch_cond_uncond = cmd_opts.always_batch_cond_uncond or not (cmd_opts.lowvram or cmd_opts.medvram)
 parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram
-
+xformers_available = False
 config_filename = cmd_opts.ui_settings_file
 
 
-- 
cgit v1.2.3


From 69d0053583757ce2942d62de81e8b89e6be07840 Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Sat, 8 Oct 2022 16:21:40 +0300
Subject: update sd_hijack_opt to respect new env variables

---
 modules/sd_hijack_optimizations.py | 11 ++++++++---
 1 file changed, 8 insertions(+), 3 deletions(-)

diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index ee58c7e4..be09ec8f 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -1,9 +1,14 @@
 import math
 import torch
 from torch import einsum
-import xformers.ops
-import functorch
-xformers._is_functorch_available=True
+try:
+    import xformers.ops
+    import functorch
+    xformers._is_functorch_available = True
+    shared.xformers_available = True
+except:
+    print('Cannot find xformers, defaulting to split attention. Try setting --xformers in your webui-user file if you wish to install it.')
+    continue
 from ldm.util import default
 from einops import rearrange
 
-- 
cgit v1.2.3


From ca5f0f149c29c344a6badd055b15b5e5fcd6e938 Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Sat, 8 Oct 2022 16:22:38 +0300
Subject: Update launch.py

---
 launch.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/launch.py b/launch.py
index a2089b3b..a592e1ba 100644
--- a/launch.py
+++ b/launch.py
@@ -129,7 +129,7 @@ if not is_installed("clip"):
 if not is_installed("xformers") and xformers:
     if platform.system() == "Windows":
         run_pip("install https://github.com/C43H66N12O12S2/stable-diffusion-webui/releases/download/a/xformers-0.0.14.dev0-cp310-cp310-win_amd64.whl", "xformers")
-    elif:
+    elif platform.system() == "Linux":
         run_pip("install xformers", "xformers")
 
 os.makedirs(dir_repos, exist_ok=True)
-- 
cgit v1.2.3


From 7ffea1507813540b8cd9e73feb7bf23de1ac4e27 Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Sat, 8 Oct 2022 16:24:06 +0300
Subject: Update requirements_versions.txt

---
 requirements_versions.txt | 1 +
 1 file changed, 1 insertion(+)

diff --git a/requirements_versions.txt b/requirements_versions.txt
index fdff2687..fec3e9d5 100644
--- a/requirements_versions.txt
+++ b/requirements_versions.txt
@@ -22,3 +22,4 @@ resize-right==0.0.2
 torchdiffeq==0.2.3
 kornia==0.6.7
 lark==1.1.2
+functorch==0.2.1
-- 
cgit v1.2.3


From 970de9ee6891ff586821d0d80dde01c2f6c681b3 Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Sat, 8 Oct 2022 16:29:43 +0300
Subject: Update sd_hijack.py

---
 modules/sd_hijack.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 04adcf03..5b30539f 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -21,7 +21,7 @@ diffusionmodules_model_AttnBlock_forward = ldm.modules.diffusionmodules.model.At
 
 def apply_optimizations():
     ldm.modules.diffusionmodules.model.nonlinearity = silu
-    if not cmd_opts.disable_opt_xformers_attention and not (cmd_opts.opt_split_attention or torch.version.hip or shared.xformers_available):
+    if not cmd_opts.disable_opt_xformers_attention and not (cmd_opts.opt_split_attention or torch.version.hip) and shared.xformers_available:
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward
         ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.xformers_attnblock_forward
     elif cmd_opts.opt_split_attention_v1:
-- 
cgit v1.2.3


From 7ff1170a2e11b6f00f587407326db0b9f8f51adf Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 8 Oct 2022 16:33:39 +0300
Subject: emergency fix for xformers (continue + shared)

---
 modules/sd_hijack_optimizations.py | 16 ++++++++--------
 1 file changed, 8 insertions(+), 8 deletions(-)

diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index e43e2c7a..05023b6f 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -1,19 +1,19 @@
 import math
 import torch
 from torch import einsum
-try:
-    import xformers.ops
-    import functorch
-    xformers._is_functorch_available = True
-    shared.xformers_available = True
-except:
-    print('Cannot find xformers, defaulting to split attention. Try setting --xformers in your webui-user file if you wish to install it.')
-    continue
+
 from ldm.util import default
 from einops import rearrange
 
 from modules import shared
 
+try:
+    import xformers.ops
+    import functorch
+    xformers._is_functorch_available = True
+    shared.xformers_available = True
+except Exception:
+    print('Cannot find xformers, defaulting to split attention. Try adding --xformers commandline argument to your webui-user file if you wish to install it.')
 
 # see https://github.com/basujindal/stable-diffusion/pull/117 for discussion
 def split_cross_attention_forward_v1(self, x, context=None, mask=None):
-- 
cgit v1.2.3


From dc1117233ef8f9b25ff1ac40b158f20b70ba2fcb Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 8 Oct 2022 17:02:18 +0300
Subject: simplify xfrmers options: --xformers to enable and that's it

---
 launch.py                          |  2 +-
 modules/sd_hijack.py               |  2 +-
 modules/sd_hijack_optimizations.py | 20 +++++++++++++-------
 modules/shared.py                  |  2 +-
 4 files changed, 16 insertions(+), 10 deletions(-)

diff --git a/launch.py b/launch.py
index a592e1ba..61f62096 100644
--- a/launch.py
+++ b/launch.py
@@ -32,7 +32,7 @@ def extract_arg(args, name):
 
 
 args, skip_torch_cuda_test = extract_arg(args, '--skip-torch-cuda-test')
-args, xformers = extract_arg(args, '--xformers')
+xformers = '--xformers' in args
 
 
 def repo_dir(name):
diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 5d93f7f6..91e98c16 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -22,7 +22,7 @@ def apply_optimizations():
     undo_optimizations()
 
     ldm.modules.diffusionmodules.model.nonlinearity = silu
-    if not cmd_opts.disable_opt_xformers_attention and not (cmd_opts.opt_split_attention or torch.version.hip) and shared.xformers_available:
+    if cmd_opts.xformers and shared.xformers_available and not torch.version.hip:
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward
         ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.xformers_attnblock_forward
     elif cmd_opts.opt_split_attention_v1:
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index 05023b6f..d23d733b 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -1,4 +1,7 @@
 import math
+import sys
+import traceback
+
 import torch
 from torch import einsum
 
@@ -7,13 +10,16 @@ from einops import rearrange
 
 from modules import shared
 
-try:
-    import xformers.ops
-    import functorch
-    xformers._is_functorch_available = True
-    shared.xformers_available = True
-except Exception:
-    print('Cannot find xformers, defaulting to split attention. Try adding --xformers commandline argument to your webui-user file if you wish to install it.')
+if shared.cmd_opts.xformers:
+    try:
+        import xformers.ops
+        import functorch
+        xformers._is_functorch_available = True
+        shared.xformers_available = True
+    except Exception:
+        print("Cannot import xformers", file=sys.stderr)
+        print(traceback.format_exc(), file=sys.stderr)
+
 
 # see https://github.com/basujindal/stable-diffusion/pull/117 for discussion
 def split_cross_attention_forward_v1(self, x, context=None, mask=None):
diff --git a/modules/shared.py b/modules/shared.py
index d68df751..02cb2722 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -43,7 +43,7 @@ parser.add_argument("--realesrgan-models-path", type=str, help="Path to director
 parser.add_argument("--scunet-models-path", type=str, help="Path to directory with ScuNET model file(s).", default=os.path.join(models_path, 'ScuNET'))
 parser.add_argument("--swinir-models-path", type=str, help="Path to directory with SwinIR model file(s).", default=os.path.join(models_path, 'SwinIR'))
 parser.add_argument("--ldsr-models-path", type=str, help="Path to directory with LDSR model file(s).", default=os.path.join(models_path, 'LDSR'))
-parser.add_argument("--disable-opt-xformers-attention", action='store_true', help="force-disables xformers attention optimization")
+parser.add_argument("--xformers", action='store_true', help="enable xformers for cross attention layers")
 parser.add_argument("--opt-split-attention", action='store_true', help="force-enables cross-attention layer optimization. By default, it's on for torch.cuda and off for other torch devices.")
 parser.add_argument("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization")
 parser.add_argument("--opt-split-attention-v1", action='store_true', help="enable older version of split attention optimization that does not consume all the VRAM it can find")
-- 
cgit v1.2.3


From 27032c47df9c07ac21dd5b89fa7dc247bb8705b6 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 8 Oct 2022 17:10:05 +0300
Subject: restore old opt_split_attention/disable_opt_split_attention logic

---
 modules/sd_hijack.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 91e98c16..335a2bcf 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -27,7 +27,7 @@ def apply_optimizations():
         ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.xformers_attnblock_forward
     elif cmd_opts.opt_split_attention_v1:
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1
-    elif cmd_opts.opt_split_attention or torch.cuda.is_available():
+    elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention or torch.cuda.is_available()):
         ldm.modules.attention_CrossAttention_forward = sd_hijack_optimizations.split_cross_attention_forward
         ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.cross_attention_attnblock_forward
 
-- 
cgit v1.2.3


From 4f33289d0fc5aa3a197f4a4c926d03d44f0d597e Mon Sep 17 00:00:00 2001
From: Milly <milly.ca@gmail.com>
Date: Sat, 8 Oct 2022 22:48:15 +0900
Subject: Fixed typo

---
 modules/ui.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/ui.py b/modules/ui.py
index e3e62fdd..ffd75f6a 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -946,7 +946,7 @@ def create_ui(wrap_gradio_gpu_call):
                 custom_name = gr.Textbox(label="Custom Name (Optional)")
                 interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Interpolation Amount', value=0.3)
                 interp_method = gr.Radio(choices=["Weighted Sum", "Sigmoid", "Inverse Sigmoid"], value="Weighted Sum", label="Interpolation Method")
-                save_as_half = gr.Checkbox(value=False, label="Safe as float16")
+                save_as_half = gr.Checkbox(value=False, label="Save as float16")
                 modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary')
 
             with gr.Column(variant='panel'):
-- 
cgit v1.2.3


From cfc33f99d47d1f45af15499e5965834089d11858 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 8 Oct 2022 17:28:58 +0300
Subject: why did you do this

---
 modules/sd_hijack.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 335a2bcf..ed271976 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -28,7 +28,7 @@ def apply_optimizations():
     elif cmd_opts.opt_split_attention_v1:
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1
     elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention or torch.cuda.is_available()):
-        ldm.modules.attention_CrossAttention_forward = sd_hijack_optimizations.split_cross_attention_forward
+        ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward
         ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.cross_attention_attnblock_forward
 
 
-- 
cgit v1.2.3


From 7e639cd49855ef59e087ae9a9122756a937007eb Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Sat, 8 Oct 2022 17:22:20 +0300
Subject: check for 3.10

---
 launch.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/launch.py b/launch.py
index 61f62096..1d65a779 100644
--- a/launch.py
+++ b/launch.py
@@ -126,7 +126,7 @@ if not is_installed("gfpgan"):
 if not is_installed("clip"):
     run_pip(f"install {clip_package}", "clip")
 
-if not is_installed("xformers") and xformers:
+if not is_installed("xformers") and xformers and platform.python_version().startswith("3.10"):
     if platform.system() == "Windows":
         run_pip("install https://github.com/C43H66N12O12S2/stable-diffusion-webui/releases/download/a/xformers-0.0.14.dev0-cp310-cp310-win_amd64.whl", "xformers")
     elif platform.system() == "Linux":
-- 
cgit v1.2.3


From 017b6b8744f0771e498656ec043e12d5cc6969a7 Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Sat, 8 Oct 2022 17:27:21 +0300
Subject: check for ampere

---
 modules/sd_hijack.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index ed271976..5e266d5e 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -22,9 +22,10 @@ def apply_optimizations():
     undo_optimizations()
 
     ldm.modules.diffusionmodules.model.nonlinearity = silu
-    if cmd_opts.xformers and shared.xformers_available and not torch.version.hip:
-        ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward
-        ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.xformers_attnblock_forward
+    if cmd_opts.xformers and shared.xformers_available and torch.version.cuda:
+        if torch.cuda.get_device_capability(shared.device) == (8, 6):
+            ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward
+            ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.xformers_attnblock_forward
     elif cmd_opts.opt_split_attention_v1:
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1
     elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention or torch.cuda.is_available()):
-- 
cgit v1.2.3


From cc0258aea7b6605be3648900063cfa96ed7c5ffa Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Sat, 8 Oct 2022 17:44:53 +0300
Subject: check for ampere without destroying the optimizations. again.

---
 modules/sd_hijack.py | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 5e266d5e..a3e374f0 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -22,10 +22,9 @@ def apply_optimizations():
     undo_optimizations()
 
     ldm.modules.diffusionmodules.model.nonlinearity = silu
-    if cmd_opts.xformers and shared.xformers_available and torch.version.cuda:
-        if torch.cuda.get_device_capability(shared.device) == (8, 6):
-            ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward
-            ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.xformers_attnblock_forward
+    if cmd_opts.xformers and shared.xformers_available and torch.version.cuda and torch.cuda.get_device_capability(shared.device) == (8, 6):
+        ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward
+        ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.xformers_attnblock_forward
     elif cmd_opts.opt_split_attention_v1:
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1
     elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention or torch.cuda.is_available()):
-- 
cgit v1.2.3


From 34acad1628e98a5e0cbd459fa69ded915864f53d Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Fri, 7 Oct 2022 22:56:00 +0100
Subject: Add GZipMiddleware to root demo

---
 webui.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/webui.py b/webui.py
index 3b4cf5e9..18de8e16 100644
--- a/webui.py
+++ b/webui.py
@@ -5,6 +5,8 @@ import importlib
 import signal
 import threading
 
+from fastapi.middleware.gzip import GZipMiddleware
+
 from modules.paths import script_path
 
 from modules import devices, sd_samplers
@@ -93,7 +95,7 @@ def webui():
 
         demo = modules.ui.create_ui(wrap_gradio_gpu_call=wrap_gradio_gpu_call)
         
-        demo.launch(
+        app,local_url,share_url = demo.launch(
             share=cmd_opts.share,
             server_name="0.0.0.0" if cmd_opts.listen else None,
             server_port=cmd_opts.port,
@@ -102,6 +104,8 @@ def webui():
             inbrowser=cmd_opts.autolaunch,
             prevent_thread_lock=True
         )
+        
+        app.add_middleware(GZipMiddleware,minimum_size=1000)
 
         while 1:
             time.sleep(0.5)
-- 
cgit v1.2.3


From a5550f0213c3f145b1c984816ebcef92c48853ee Mon Sep 17 00:00:00 2001
From: Artem Zagidulin <p0chta@yandex.ru>
Date: Wed, 5 Oct 2022 19:10:39 +0300
Subject: alternate prompt

---
 modules/prompt_parser.py | 9 +++++++--
 1 file changed, 7 insertions(+), 2 deletions(-)

diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py
index 15666073..919d5d31 100644
--- a/modules/prompt_parser.py
+++ b/modules/prompt_parser.py
@@ -13,13 +13,14 @@ import lark
 
 schedule_parser = lark.Lark(r"""
 !start: (prompt | /[][():]/+)*
-prompt: (emphasized | scheduled | plain | WHITESPACE)*
+prompt: (emphasized | scheduled | alternate | plain | WHITESPACE)*
 !emphasized: "(" prompt ")"
         | "(" prompt ":" prompt ")"
         | "[" prompt "]"
 scheduled: "[" [prompt ":"] prompt ":" [WHITESPACE] NUMBER "]"
+alternate: "[" prompt ("|" prompt)+ "]"
 WHITESPACE: /\s+/
-plain: /([^\\\[\]():]|\\.)+/
+plain: /([^\\\[\]():|]|\\.)+/
 %import common.SIGNED_NUMBER -> NUMBER
 """)
 
@@ -59,6 +60,8 @@ def get_learned_conditioning_prompt_schedules(prompts, steps):
                     tree.children[-1] *= steps
                 tree.children[-1] = min(steps, int(tree.children[-1]))
                 l.append(tree.children[-1])
+            def alternate(self, tree):
+                l.extend(range(1, steps+1))
         CollectSteps().visit(tree)
         return sorted(set(l))
 
@@ -67,6 +70,8 @@ def get_learned_conditioning_prompt_schedules(prompts, steps):
             def scheduled(self, args):
                 before, after, _, when = args
                 yield before or () if step <= when else after
+            def alternate(self, args):
+                yield next(args[(step - 1)%len(args)])
             def start(self, args):
                 def flatten(x):
                     if type(x) == str:
-- 
cgit v1.2.3


From 01f8cb44474e454903c11718e6a4f33dbde34bb8 Mon Sep 17 00:00:00 2001
From: Greendayle <Greendayle>
Date: Sat, 8 Oct 2022 18:02:56 +0200
Subject: made deepdanbooru optional, added to readme, automatic download of
 deepbooru model

---
 README.md                 |  2 ++
 launch.py                 |  4 ++++
 modules/deepbooru.py      | 20 ++++++++++----------
 modules/shared.py         |  1 +
 modules/ui.py             | 19 ++++++++++++-------
 requirements.txt          |  3 ---
 requirements_versions.txt |  3 ---
 7 files changed, 29 insertions(+), 23 deletions(-)

diff --git a/README.md b/README.md
index ef9b5e31..6cd7a1f9 100644
--- a/README.md
+++ b/README.md
@@ -66,6 +66,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
      - separate prompts using uppercase `AND`
      - also supports weights for prompts: `a cat :1.2 AND a dog AND a penguin :2.2`
 - No token limit for prompts (original stable diffusion lets you use up to 75 tokens)
+- DeepDanbooru integration, creates danbooru style tags for anime prompts (add --deepdanbooru to commandline args)
 
 ## Installation and Running
 Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for both [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended) and [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs.
@@ -123,4 +124,5 @@ The documentation was moved from this README over to the project's [wiki](https:
 - Noise generation for outpainting mk2 - https://github.com/parlance-zz/g-diffuser-bot
 - CLIP interrogator idea and borrowing some code - https://github.com/pharmapsychotic/clip-interrogator
 - Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user.
+- DeepDanbooru - interrogator for anime diffusors https://github.com/KichangKim/DeepDanbooru
 - (You)
diff --git a/launch.py b/launch.py
index 61f62096..d46426eb 100644
--- a/launch.py
+++ b/launch.py
@@ -33,6 +33,7 @@ def extract_arg(args, name):
 
 args, skip_torch_cuda_test = extract_arg(args, '--skip-torch-cuda-test')
 xformers = '--xformers' in args
+deepdanbooru = '--deepdanbooru' in args
 
 
 def repo_dir(name):
@@ -132,6 +133,9 @@ if not is_installed("xformers") and xformers:
     elif platform.system() == "Linux":
         run_pip("install xformers", "xformers")
 
+if not is_installed("deepdanbooru") and deepdanbooru:
+    run_pip("install git+https://github.com/KichangKim/DeepDanbooru.git@edf73df4cdaeea2cf00e9ac08bd8a9026b7a7b26#egg=deepdanbooru[tensorflow] tensorflow==2.10.0 tensorflow-io==0.27.0", "deepdanbooru")
+
 os.makedirs(dir_repos, exist_ok=True)
 
 git_clone("https://github.com/CompVis/stable-diffusion.git", repo_dir('stable-diffusion'), "Stable Diffusion", stable_diffusion_commit_hash)
diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index 781b2249..7e3c0618 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -9,16 +9,16 @@ def _load_tf_and_return_tags(pil_image, threshold):
     import numpy as np
 
     this_folder = os.path.dirname(__file__)
-    model_path = os.path.join(this_folder, '..', 'models', 'deepbooru', 'deepdanbooru-v3-20211112-sgd-e28')
-
-    model_good = False
-    for path_candidate in [model_path, os.path.dirname(model_path)]:
-        if os.path.exists(os.path.join(path_candidate, 'project.json')):
-            model_path = path_candidate
-            model_good = True
-    if not model_good:
-        return ("Download https://github.com/KichangKim/DeepDanbooru/releases/download/v3-20211112-sgd-e28/"
-                "deepdanbooru-v3-20211112-sgd-e28.zip unpack and put into models/deepbooru")
+    model_path = os.path.abspath(os.path.join(this_folder, '..', 'models', 'deepbooru'))
+    if not os.path.exists(os.path.join(model_path, 'project.json')):
+        # there is no point importing these every time
+        import zipfile
+        from basicsr.utils.download_util import load_file_from_url
+        load_file_from_url(r"https://github.com/KichangKim/DeepDanbooru/releases/download/v3-20211112-sgd-e28/deepdanbooru-v3-20211112-sgd-e28.zip",
+                           model_path)
+        with zipfile.ZipFile(os.path.join(model_path, "deepdanbooru-v3-20211112-sgd-e28.zip"), "r") as zip_ref:
+            zip_ref.extractall(model_path)
+        os.remove(os.path.join(model_path, "deepdanbooru-v3-20211112-sgd-e28.zip"))
 
     tags = dd.project.load_tags_from_project(model_path)
     model = dd.project.load_model_from_project(
diff --git a/modules/shared.py b/modules/shared.py
index 02cb2722..c87b726e 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -44,6 +44,7 @@ parser.add_argument("--scunet-models-path", type=str, help="Path to directory wi
 parser.add_argument("--swinir-models-path", type=str, help="Path to directory with SwinIR model file(s).", default=os.path.join(models_path, 'SwinIR'))
 parser.add_argument("--ldsr-models-path", type=str, help="Path to directory with LDSR model file(s).", default=os.path.join(models_path, 'LDSR'))
 parser.add_argument("--xformers", action='store_true', help="enable xformers for cross attention layers")
+parser.add_argument("--deepdanbooru", action='store_true', help="enable deepdanbooru interrogator")
 parser.add_argument("--opt-split-attention", action='store_true', help="force-enables cross-attention layer optimization. By default, it's on for torch.cuda and off for other torch devices.")
 parser.add_argument("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization")
 parser.add_argument("--opt-split-attention-v1", action='store_true', help="enable older version of split attention optimization that does not consume all the VRAM it can find")
diff --git a/modules/ui.py b/modules/ui.py
index 30583fe9..c5c11c3c 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -23,9 +23,10 @@ import gradio.utils
 import gradio.routes
 
 from modules import sd_hijack
-from modules.deepbooru import get_deepbooru_tags
 from modules.paths import script_path
 from modules.shared import opts, cmd_opts
+if cmd_opts.deepdanbooru:
+    from modules.deepbooru import get_deepbooru_tags
 import modules.shared as shared
 from modules.sd_samplers import samplers, samplers_for_img2img
 from modules.sd_hijack import model_hijack
@@ -437,7 +438,10 @@ def create_toprow(is_img2img):
             with gr.Row(scale=1):
                 if is_img2img:
                     interrogate = gr.Button('Interrogate\nCLIP', elem_id="interrogate")
-                    deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru")
+                    if cmd_opts.deepdanbooru:
+                        deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru")
+                    else:
+                        deepbooru = None
                 else:
                     interrogate = None
                     deepbooru = None
@@ -782,11 +786,12 @@ def create_ui(wrap_gradio_gpu_call):
                 outputs=[img2img_prompt],
             )
 
-            img2img_deepbooru.click(
-                fn=interrogate_deepbooru,
-                inputs=[init_img],
-                outputs=[img2img_prompt],
-            )
+            if cmd_opts.deepdanbooru:
+                img2img_deepbooru.click(
+                    fn=interrogate_deepbooru,
+                    inputs=[init_img],
+                    outputs=[img2img_prompt],
+                )
 
             save.click(
                 fn=wrap_gradio_call(save_files),
diff --git a/requirements.txt b/requirements.txt
index cd3953c6..81641d68 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -23,7 +23,4 @@ resize-right
 torchdiffeq
 kornia
 lark
-deepdanbooru
-tensorflow
-tensorflow-io
 functorch
diff --git a/requirements_versions.txt b/requirements_versions.txt
index 2d256a54..fec3e9d5 100644
--- a/requirements_versions.txt
+++ b/requirements_versions.txt
@@ -22,7 +22,4 @@ resize-right==0.0.2
 torchdiffeq==0.2.3
 kornia==0.6.7
 lark==1.1.2
-git+https://github.com/KichangKim/DeepDanbooru.git@edf73df4cdaeea2cf00e9ac08bd8a9026b7a7b26#egg=deepdanbooru[tensorflow]
-tensorflow==2.10.0
-tensorflow-io==0.27.0
 functorch==0.2.1
-- 
cgit v1.2.3


From f9c5da159245bb1e7603b3c8b9e0703bcb1c2ff5 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 8 Oct 2022 19:05:19 +0300
Subject: add fallback for xformers_attnblock_forward

---
 modules/sd_hijack_optimizations.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index d23d733b..dba21192 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -211,6 +211,7 @@ def cross_attention_attnblock_forward(self, x):
         return h3
     
 def xformers_attnblock_forward(self, x):
+    try:
         h_ = x
         h_ = self.norm(h_)
         q1 = self.q(h_).contiguous()
@@ -218,4 +219,6 @@ def xformers_attnblock_forward(self, x):
         v = self.v(h_).contiguous()
         out = xformers.ops.memory_efficient_attention(q1, k1, v)
         out = self.proj_out(out)
-        return x+out
+        return x + out
+    except NotImplementedError:
+        return cross_attention_attnblock_forward(self, x)
-- 
cgit v1.2.3


From 3061cdb7b610d4ba7f1ea695d9d6364b591e5bc7 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 8 Oct 2022 19:22:15 +0300
Subject: add --force-enable-xformers option and also add messages to console
 regarding cross attention optimizations

---
 modules/sd_hijack.py | 6 +++++-
 modules/shared.py    | 1 +
 2 files changed, 6 insertions(+), 1 deletion(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index a3e374f0..307cc67d 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -22,12 +22,16 @@ def apply_optimizations():
     undo_optimizations()
 
     ldm.modules.diffusionmodules.model.nonlinearity = silu
-    if cmd_opts.xformers and shared.xformers_available and torch.version.cuda and torch.cuda.get_device_capability(shared.device) == (8, 6):
+
+    if cmd_opts.force_enable_xformers or (cmd_opts.xformers and shared.xformers_available and torch.version.cuda and torch.cuda.get_device_capability(shared.device) == (8, 6)):
+        print("Applying xformers cross attention optimization.")
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward
         ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.xformers_attnblock_forward
     elif cmd_opts.opt_split_attention_v1:
+        print("Applying v1 cross attention optimization.")
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1
     elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention or torch.cuda.is_available()):
+        print("Applying cross attention optimization.")
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward
         ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.cross_attention_attnblock_forward
 
diff --git a/modules/shared.py b/modules/shared.py
index 02cb2722..8f941226 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -44,6 +44,7 @@ parser.add_argument("--scunet-models-path", type=str, help="Path to directory wi
 parser.add_argument("--swinir-models-path", type=str, help="Path to directory with SwinIR model file(s).", default=os.path.join(models_path, 'SwinIR'))
 parser.add_argument("--ldsr-models-path", type=str, help="Path to directory with LDSR model file(s).", default=os.path.join(models_path, 'LDSR'))
 parser.add_argument("--xformers", action='store_true', help="enable xformers for cross attention layers")
+parser.add_argument("--force-enable-xformers", action='store_true', help="enable xformers for cross attention layers regardless of whether the checking code thinks you can run it; do not make bug reports if this fails to work")
 parser.add_argument("--opt-split-attention", action='store_true', help="force-enables cross-attention layer optimization. By default, it's on for torch.cuda and off for other torch devices.")
 parser.add_argument("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization")
 parser.add_argument("--opt-split-attention-v1", action='store_true', help="enable older version of split attention optimization that does not consume all the VRAM it can find")
-- 
cgit v1.2.3


From 15c4278f1a18b8104e135dd82690d10cff39a2e7 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sat, 8 Oct 2022 17:50:01 +0100
Subject: TI preprocess wording
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

I had to check the code to work out what splitting was 🤷🏿
---
 modules/ui.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/modules/ui.py b/modules/ui.py
index ffd75f6a..d52d74c6 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -980,9 +980,9 @@ def create_ui(wrap_gradio_gpu_call):
                     process_dst = gr.Textbox(label='Destination directory')
 
                     with gr.Row():
-                        process_flip = gr.Checkbox(label='Flip')
-                        process_split = gr.Checkbox(label='Split into two')
-                        process_caption = gr.Checkbox(label='Add caption')
+                        process_flip = gr.Checkbox(label='Create flipped copies')
+                        process_split = gr.Checkbox(label='Split oversized images into two')
+                        process_caption = gr.Checkbox(label='Use CLIP caption as filename')
 
                     with gr.Row():
                         with gr.Column(scale=3):
-- 
cgit v1.2.3


From b458fa48fe5734a872bca83061d702609cb52940 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sat, 8 Oct 2022 17:56:28 +0100
Subject: Update ui.py

---
 modules/ui.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/ui.py b/modules/ui.py
index d52d74c6..b09359aa 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -982,7 +982,7 @@ def create_ui(wrap_gradio_gpu_call):
                     with gr.Row():
                         process_flip = gr.Checkbox(label='Create flipped copies')
                         process_split = gr.Checkbox(label='Split oversized images into two')
-                        process_caption = gr.Checkbox(label='Use CLIP caption as filename')
+                        process_caption = gr.Checkbox(label='Use BLIP caption as filename')
 
                     with gr.Row():
                         with gr.Column(scale=3):
-- 
cgit v1.2.3


From 1371d7608b402d6f15c200ec2f5fde4579836a05 Mon Sep 17 00:00:00 2001
From: Fampai <unknown>
Date: Sat, 8 Oct 2022 14:28:22 -0400
Subject: Added ability to ignore last n layers in FrozenCLIPEmbedder

---
 modules/sd_hijack.py | 11 +++++++++--
 modules/shared.py    |  1 +
 2 files changed, 10 insertions(+), 2 deletions(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 307cc67d..f12a9696 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -281,8 +281,15 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
 
         remade_batch_tokens_of_same_length = [x + [self.wrapped.tokenizer.eos_token_id] * (target_token_count - len(x)) for x in remade_batch_tokens]
         tokens = torch.asarray(remade_batch_tokens_of_same_length).to(device)
-        outputs = self.wrapped.transformer(input_ids=tokens, position_ids=position_ids)
-        z = outputs.last_hidden_state
+
+        tmp = -opts.CLIP_ignore_last_layers
+        if (opts.CLIP_ignore_last_layers == 0):
+            outputs = self.wrapped.transformer(input_ids=tokens, position_ids=position_ids)
+            z = outputs.last_hidden_state
+        else:
+            outputs = self.wrapped.transformer(input_ids=tokens, position_ids=position_ids, output_hidden_states=tmp)
+            z = outputs.hidden_states[tmp]
+            z = self.wrapped.transformer.text_model.final_layer_norm(z)
 
         # restoring original mean is likely not correct, but it seems to work well to prevent artifacts that happen otherwise
         batch_multipliers_of_same_length = [x + [1.0] * (target_token_count - len(x)) for x in batch_multipliers]
diff --git a/modules/shared.py b/modules/shared.py
index 8f941226..af8dc744 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -225,6 +225,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "use_old_emphasis_implementation": OptionInfo(False, "Use old emphasis implementation. Can be useful to reproduce old seeds."),
     "enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"),
     "filter_nsfw": OptionInfo(False, "Filter NSFW content"),
+    'CLIP_ignore_last_layers': OptionInfo(0, "Ignore last layers of CLIP model", gr.Slider, {"minimum": 0, "maximum": 5, "step": 1}),
     "random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}),
 }))
 
-- 
cgit v1.2.3


From e6e42f98df2c928c4f49351ad6b466387ce87d42 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 8 Oct 2022 19:25:10 +0300
Subject: make --force-enable-xformers work without needing --xformers

---
 modules/sd_hijack_optimizations.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index dba21192..c4396bb9 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -10,7 +10,7 @@ from einops import rearrange
 
 from modules import shared
 
-if shared.cmd_opts.xformers:
+if shared.cmd_opts.xformers or shared.cmd_opts.force_enable_xformers:
     try:
         import xformers.ops
         import functorch
-- 
cgit v1.2.3


From 3b2141c5fb6a3c2b8ab4b1e759a97ead77260129 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 8 Oct 2022 22:21:15 +0300
Subject: add 'Ignore last layers of CLIP model' option as a parameter to the
 infotext

---
 modules/processing.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/modules/processing.py b/modules/processing.py
index 8240ee27..515fc91a 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -123,6 +123,7 @@ class Processed:
         self.index_of_first_image = index_of_first_image
         self.styles = p.styles
         self.job_timestamp = state.job_timestamp
+        self.clip_skip = opts.CLIP_ignore_last_layers
 
         self.eta = p.eta
         self.ddim_discretize = p.ddim_discretize
@@ -141,7 +142,6 @@ class Processed:
         self.all_subseeds = all_subseeds or [self.subseed]
         self.infotexts = infotexts or [info]
 
-
     def js(self):
         obj = {
             "prompt": self.prompt,
@@ -170,6 +170,7 @@ class Processed:
             "infotexts": self.infotexts,
             "styles": self.styles,
             "job_timestamp": self.job_timestamp,
+            "clip_skip": self.clip_skip,
         }
 
         return json.dumps(obj)
@@ -267,6 +268,8 @@ def fix_seed(p):
 def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration=0, position_in_batch=0):
     index = position_in_batch + iteration * p.batch_size
 
+    clip_skip = getattr(p, 'clip_skip', opts.CLIP_ignore_last_layers)
+
     generation_params = {
         "Steps": p.steps,
         "Sampler": sd_samplers.samplers[p.sampler_index].name,
@@ -282,6 +285,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration
         "Seed resize from": (None if p.seed_resize_from_w == 0 or p.seed_resize_from_h == 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"),
         "Denoising strength": getattr(p, 'denoising_strength', None),
         "Eta": (None if p.sampler is None or p.sampler.eta == p.sampler.default_eta else p.sampler.eta),
+        "Clip skip": None if clip_skip==0 else clip_skip,
     }
 
     generation_params.update(p.extra_generation_params)
-- 
cgit v1.2.3


From 610a7f4e1480c0ffeedb2a07dc27ae86bf03c3a8 Mon Sep 17 00:00:00 2001
From: Edouard Leurent <eleurent@gmail.com>
Date: Sat, 8 Oct 2022 16:49:43 +0100
Subject: Break after finding the local directory of stable diffusion

Otherwise, we may override it with one of the next two path (. or ..) if it is present there, and then the local paths of other modules (taming transformers, codeformers, etc.) wont be found in sd_path/../.

Fix https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/1085
---
 modules/paths.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/modules/paths.py b/modules/paths.py
index 606f7d66..0519caa0 100644
--- a/modules/paths.py
+++ b/modules/paths.py
@@ -12,6 +12,7 @@ possible_sd_paths = [os.path.join(script_path, 'repositories/stable-diffusion'),
 for possible_sd_path in possible_sd_paths:
     if os.path.exists(os.path.join(possible_sd_path, 'ldm/models/diffusion/ddpm.py')):
         sd_path = os.path.abspath(possible_sd_path)
+        break
 
 assert sd_path is not None, "Couldn't find Stable Diffusion in any of: " + str(possible_sd_paths)
 
-- 
cgit v1.2.3


From 432782163ae53e605470bcefc9a6f796c4556912 Mon Sep 17 00:00:00 2001
From: Aidan Holland <thehappydinoa@gmail.com>
Date: Sat, 8 Oct 2022 15:12:24 -0400
Subject: chore: Fix typos

---
 README.md                    | 2 +-
 javascript/imageviewer.js    | 2 +-
 modules/interrogate.py       | 4 ++--
 modules/processing.py        | 2 +-
 modules/scunet_model_arch.py | 4 ++--
 modules/sd_models.py         | 4 ++--
 modules/sd_samplers.py       | 4 ++--
 modules/shared.py            | 6 +++---
 modules/swinir_model_arch.py | 2 +-
 modules/ui.py                | 4 ++--
 10 files changed, 17 insertions(+), 17 deletions(-)

diff --git a/README.md b/README.md
index ef9b5e31..63dd0c18 100644
--- a/README.md
+++ b/README.md
@@ -34,7 +34,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
 - Sampling method selection
 - Interrupt processing at any time
 - 4GB video card support (also reports of 2GB working)
-- Correct seeds for batches 
+- Correct seeds for batches
 - Prompt length validation
      - get length of prompt in tokens as you type
      - get a warning after generation if some text was truncated
diff --git a/javascript/imageviewer.js b/javascript/imageviewer.js
index 4c0e8f4b..6a00c0da 100644
--- a/javascript/imageviewer.js
+++ b/javascript/imageviewer.js
@@ -95,7 +95,7 @@ function showGalleryImage(){
 
                     e.addEventListener('click', function (evt) {
                         if(!opts.js_modal_lightbox) return;
-                        modalZoomSet(gradioApp().getElementById('modalImage'), opts.js_modal_lightbox_initialy_zoomed)
+                        modalZoomSet(gradioApp().getElementById('modalImage'), opts.js_modal_lightbox_initially_zoomed)
                         showModal(evt)
                     },true);
                 }
diff --git a/modules/interrogate.py b/modules/interrogate.py
index eed87144..635e266e 100644
--- a/modules/interrogate.py
+++ b/modules/interrogate.py
@@ -140,11 +140,11 @@ class InterrogateModels:
 
             res = caption
 
-            cilp_image = self.clip_preprocess(pil_image).unsqueeze(0).type(self.dtype).to(shared.device)
+            clip_image = self.clip_preprocess(pil_image).unsqueeze(0).type(self.dtype).to(shared.device)
 
             precision_scope = torch.autocast if shared.cmd_opts.precision == "autocast" else contextlib.nullcontext
             with torch.no_grad(), precision_scope("cuda"):
-                image_features = self.clip_model.encode_image(cilp_image).type(self.dtype)
+                image_features = self.clip_model.encode_image(clip_image).type(self.dtype)
 
                 image_features /= image_features.norm(dim=-1, keepdim=True)
 
diff --git a/modules/processing.py b/modules/processing.py
index 515fc91a..31220881 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -386,7 +386,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
 
             if state.interrupted or state.skipped:
 
-                # if we are interruped, sample returns just noise
+                # if we are interrupted, sample returns just noise
                 # use the image collected previously in sampler loop
                 samples_ddim = shared.state.current_latent
 
diff --git a/modules/scunet_model_arch.py b/modules/scunet_model_arch.py
index 972a2639..43ca8d36 100644
--- a/modules/scunet_model_arch.py
+++ b/modules/scunet_model_arch.py
@@ -40,7 +40,7 @@ class WMSA(nn.Module):
         Returns:
             attn_mask: should be (1 1 w p p),
         """
-        # supporting sqaure.
+        # supporting square.
         attn_mask = torch.zeros(h, w, p, p, p, p, dtype=torch.bool, device=self.relative_position_params.device)
         if self.type == 'W':
             return attn_mask
@@ -65,7 +65,7 @@ class WMSA(nn.Module):
         x = rearrange(x, 'b (w1 p1) (w2 p2) c -> b w1 w2 p1 p2 c', p1=self.window_size, p2=self.window_size)
         h_windows = x.size(1)
         w_windows = x.size(2)
-        # sqaure validation
+        # square validation
         # assert h_windows == w_windows
 
         x = rearrange(x, 'b w1 w2 p1 p2 c -> b (w1 w2) (p1 p2) c', p1=self.window_size, p2=self.window_size)
diff --git a/modules/sd_models.py b/modules/sd_models.py
index 9409d070..a09866ce 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -147,7 +147,7 @@ def load_model_weights(model, checkpoint_file, sd_model_hash):
         model.first_stage_model.load_state_dict(vae_dict)
 
     model.sd_model_hash = sd_model_hash
-    model.sd_model_checkpint = checkpoint_file
+    model.sd_model_checkpoint = checkpoint_file
 
 
 def load_model():
@@ -175,7 +175,7 @@ def reload_model_weights(sd_model, info=None):
     from modules import lowvram, devices, sd_hijack
     checkpoint_info = info or select_checkpoint()
 
-    if sd_model.sd_model_checkpint == checkpoint_info.filename:
+    if sd_model.sd_model_checkpoint == checkpoint_info.filename:
         return
 
     if shared.cmd_opts.lowvram or shared.cmd_opts.medvram:
diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index eade0dbb..6e743f7e 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -181,7 +181,7 @@ class VanillaStableDiffusionSampler:
 
         self.initialize(p)
 
-        # existing code fails with cetain step counts, like 9
+        # existing code fails with certain step counts, like 9
         try:
             self.sampler.make_schedule(ddim_num_steps=steps,  ddim_eta=self.eta, ddim_discretize=p.ddim_discretize, verbose=False)
         except Exception:
@@ -204,7 +204,7 @@ class VanillaStableDiffusionSampler:
 
         steps = steps or p.steps
 
-        # existing code fails with cetin step counts, like 9
+        # existing code fails with certain step counts, like 9
         try:
             samples_ddim, _ = self.sampler.sample(S=steps, conditioning=conditioning, batch_size=int(x.shape[0]), shape=x[0].shape, verbose=False, unconditional_guidance_scale=p.cfg_scale, unconditional_conditioning=unconditional_conditioning, x_T=x, eta=self.eta)
         except Exception:
diff --git a/modules/shared.py b/modules/shared.py
index af8dc744..2dc092d6 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -141,9 +141,9 @@ class OptionInfo:
         self.section = None
 
 
-def options_section(section_identifer, options_dict):
+def options_section(section_identifier, options_dict):
     for k, v in options_dict.items():
-        v.section = section_identifer
+        v.section = section_identifier
 
     return options_dict
 
@@ -246,7 +246,7 @@ options_templates.update(options_section(('ui', "User interface"), {
     "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"),
     "font": OptionInfo("", "Font for image grids that have text"),
     "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"),
-    "js_modal_lightbox_initialy_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),
+    "js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),
     "show_progress_in_title": OptionInfo(True, "Show generation progress in window title."),
 }))
 
diff --git a/modules/swinir_model_arch.py b/modules/swinir_model_arch.py
index 461fb354..863f42db 100644
--- a/modules/swinir_model_arch.py
+++ b/modules/swinir_model_arch.py
@@ -166,7 +166,7 @@ class SwinTransformerBlock(nn.Module):
 
     Args:
         dim (int): Number of input channels.
-        input_resolution (tuple[int]): Input resulotion.
+        input_resolution (tuple[int]): Input resolution.
         num_heads (int): Number of attention heads.
         window_size (int): Window size.
         shift_size (int): Shift size for SW-MSA.
diff --git a/modules/ui.py b/modules/ui.py
index b09359aa..b51af121 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -38,7 +38,7 @@ from modules import prompt_parser
 from modules.images import save_image
 import modules.textual_inversion.ui
 
-# this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the bowser will not show any UI
+# this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI
 mimetypes.init()
 mimetypes.add_type('application/javascript', '.js')
 
@@ -102,7 +102,7 @@ def save_files(js_data, images, index):
     import csv    
     filenames = []
 
-    #quick dictionary to class object conversion. Its neccesary due apply_filename_pattern requiring it
+    #quick dictionary to class object conversion. Its necessary due apply_filename_pattern requiring it
     class MyObject:
         def __init__(self, d=None):
             if d is not None:
-- 
cgit v1.2.3


From 050a6a798cec90ae2f881c2ddd3f0221e69907dc Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 8 Oct 2022 23:26:48 +0300
Subject: support loading .yaml config with same name as model support EMA
 weights in processing (????)

---
 modules/processing.py |  2 +-
 modules/sd_models.py  | 30 +++++++++++++++++++++++-------
 2 files changed, 24 insertions(+), 8 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index 31220881..4fea6d56 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -347,7 +347,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
     infotexts = []
     output_images = []
 
-    with torch.no_grad():
+    with torch.no_grad(), p.sd_model.ema_scope():
         with devices.autocast():
             p.init(all_prompts, all_seeds, all_subseeds)
 
diff --git a/modules/sd_models.py b/modules/sd_models.py
index a09866ce..cb3982b1 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -14,7 +14,7 @@ from modules.paths import models_path
 model_dir = "Stable-diffusion"
 model_path = os.path.abspath(os.path.join(models_path, model_dir))
 
-CheckpointInfo = namedtuple("CheckpointInfo", ['filename', 'title', 'hash', 'model_name'])
+CheckpointInfo = namedtuple("CheckpointInfo", ['filename', 'title', 'hash', 'model_name', 'config'])
 checkpoints_list = {}
 
 try:
@@ -63,14 +63,20 @@ def list_models():
     if os.path.exists(cmd_ckpt):
         h = model_hash(cmd_ckpt)
         title, short_model_name = modeltitle(cmd_ckpt, h)
-        checkpoints_list[title] = CheckpointInfo(cmd_ckpt, title, h, short_model_name)
+        checkpoints_list[title] = CheckpointInfo(cmd_ckpt, title, h, short_model_name, shared.cmd_opts.config)
         shared.opts.data['sd_model_checkpoint'] = title
     elif cmd_ckpt is not None and cmd_ckpt != shared.default_sd_model_file:
         print(f"Checkpoint in --ckpt argument not found (Possible it was moved to {model_path}: {cmd_ckpt}", file=sys.stderr)
     for filename in model_list:
         h = model_hash(filename)
         title, short_model_name = modeltitle(filename, h)
-        checkpoints_list[title] = CheckpointInfo(filename, title, h, short_model_name)
+
+        basename, _ = os.path.splitext(filename)
+        config = basename + ".yaml"
+        if not os.path.exists(config):
+            config = shared.cmd_opts.config
+
+        checkpoints_list[title] = CheckpointInfo(filename, title, h, short_model_name, config)
 
 
 def get_closet_checkpoint_match(searchString):
@@ -116,7 +122,10 @@ def select_checkpoint():
     return checkpoint_info
 
 
-def load_model_weights(model, checkpoint_file, sd_model_hash):
+def load_model_weights(model, checkpoint_info):
+    checkpoint_file = checkpoint_info.filename
+    sd_model_hash = checkpoint_info.hash
+
     print(f"Loading weights [{sd_model_hash}] from {checkpoint_file}")
 
     pl_sd = torch.load(checkpoint_file, map_location="cpu")
@@ -148,15 +157,19 @@ def load_model_weights(model, checkpoint_file, sd_model_hash):
 
     model.sd_model_hash = sd_model_hash
     model.sd_model_checkpoint = checkpoint_file
+    model.sd_checkpoint_info = checkpoint_info
 
 
 def load_model():
     from modules import lowvram, sd_hijack
     checkpoint_info = select_checkpoint()
 
-    sd_config = OmegaConf.load(shared.cmd_opts.config)
+    if checkpoint_info.config != shared.cmd_opts.config:
+        print(f"Loading config from: {shared.cmd_opts.config}")
+
+    sd_config = OmegaConf.load(checkpoint_info.config)
     sd_model = instantiate_from_config(sd_config.model)
-    load_model_weights(sd_model, checkpoint_info.filename, checkpoint_info.hash)
+    load_model_weights(sd_model, checkpoint_info)
 
     if shared.cmd_opts.lowvram or shared.cmd_opts.medvram:
         lowvram.setup_for_low_vram(sd_model, shared.cmd_opts.medvram)
@@ -178,6 +191,9 @@ def reload_model_weights(sd_model, info=None):
     if sd_model.sd_model_checkpoint == checkpoint_info.filename:
         return
 
+    if sd_model.sd_checkpoint_info.config != checkpoint_info.config:
+        return load_model()
+
     if shared.cmd_opts.lowvram or shared.cmd_opts.medvram:
         lowvram.send_everything_to_cpu()
     else:
@@ -185,7 +201,7 @@ def reload_model_weights(sd_model, info=None):
 
     sd_hijack.model_hijack.undo_hijack(sd_model)
 
-    load_model_weights(sd_model, checkpoint_info.filename, checkpoint_info.hash)
+    load_model_weights(sd_model, checkpoint_info)
 
     sd_hijack.model_hijack.hijack(sd_model)
 
-- 
cgit v1.2.3


From 5841990b0df04906da7321beef6f7f7902b7d57b Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sun, 9 Oct 2022 05:38:38 +0100
Subject: Update textual_inversion.py

---
 modules/textual_inversion/textual_inversion.py | 25 ++++++++++++++++++++++---
 1 file changed, 22 insertions(+), 3 deletions(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index cd9f3498..f6316020 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -7,6 +7,9 @@ import tqdm
 import html
 import datetime
 
+from PIL import Image, PngImagePlugin
+import base64
+from io import BytesIO
 
 from modules import shared, devices, sd_hijack, processing, sd_models
 import modules.textual_inversion.dataset
@@ -80,7 +83,15 @@ class EmbeddingDatabase:
         def process_file(path, filename):
             name = os.path.splitext(filename)[0]
 
-            data = torch.load(path, map_location="cpu")
+            data = []
+
+            if filename.upper().endswith('.PNG'):
+                embed_image = Image.open(path)
+                if 'sd-embedding' in embed_image.text:
+                    embeddingData = base64.b64decode(embed_image.text['sd-embedding'])
+                    data = torch.load(BytesIO(embeddingData), map_location="cpu")
+            else:
+                data = torch.load(path, map_location="cpu")
 
             # textual inversion embeddings
             if 'string_to_param' in data:
@@ -156,7 +167,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'):
     return fn
 
 
-def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps, create_image_every, save_embedding_every, template_file):
+def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding):
     assert embedding_name, 'embedding not selected'
 
     shared.state.textinfo = "Initializing textual inversion training..."
@@ -244,7 +255,15 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
             image = processed.images[0]
 
             shared.state.current_image = image
-            image.save(last_saved_image)
+
+            if save_image_with_stored_embedding:
+                info = PngImagePlugin.PngInfo()
+                info.add_text("sd-embedding", base64.b64encode(open(last_saved_file,'rb').read()))
+                image.save(last_saved_image, "PNG", pnginfo=info)
+            else:
+                image.save(last_saved_image)
+
+
 
             last_saved_image += f", prompt: {text}"
 
-- 
cgit v1.2.3


From cd8673bd9b2e59bddefee8d307340d643695fe11 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sun, 9 Oct 2022 05:40:57 +0100
Subject: add embed embedding to ui

---
 modules/ui.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/modules/ui.py b/modules/ui.py
index b51af121..a5983204 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1001,7 +1001,8 @@ def create_ui(wrap_gradio_gpu_call):
                     steps = gr.Number(label='Max steps', value=100000, precision=0)
                     create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0)
                     save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0)
-
+                    save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True)
+                    
                     with gr.Row():
                         with gr.Column(scale=2):
                             gr.HTML(value="")
@@ -1063,6 +1064,7 @@ def create_ui(wrap_gradio_gpu_call):
                 create_image_every,
                 save_embedding_every,
                 template_file,
+                save_image_with_stored_embedding,
             ],
             outputs=[
                 ti_output,
-- 
cgit v1.2.3


From c77c89cc83c618472ad352cf8a28fde28c3a1377 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 9 Oct 2022 10:23:31 +0300
Subject: make main model loading and model merger use the same code

---
 modules/extras.py    |  6 +++---
 modules/sd_models.py | 14 +++++++++-----
 2 files changed, 12 insertions(+), 8 deletions(-)

diff --git a/modules/extras.py b/modules/extras.py
index 1d9e64e5..ef6e6de7 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -169,9 +169,9 @@ def run_modelmerger(primary_model_name, secondary_model_name, interp_method, int
 
     print(f"Loading {secondary_model_info.filename}...")
     secondary_model = torch.load(secondary_model_info.filename, map_location='cpu')
-   
-    theta_0 = primary_model['state_dict']
-    theta_1 = secondary_model['state_dict']
+
+    theta_0 = sd_models.get_state_dict_from_checkpoint(primary_model)
+    theta_1 = sd_models.get_state_dict_from_checkpoint(secondary_model)
 
     theta_funcs = {
         "Weighted Sum": weighted_sum,
diff --git a/modules/sd_models.py b/modules/sd_models.py
index cb3982b1..18fb8c2e 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -122,6 +122,13 @@ def select_checkpoint():
     return checkpoint_info
 
 
+def get_state_dict_from_checkpoint(pl_sd):
+    if "state_dict" in pl_sd:
+        return pl_sd["state_dict"]
+
+    return pl_sd
+
+
 def load_model_weights(model, checkpoint_info):
     checkpoint_file = checkpoint_info.filename
     sd_model_hash = checkpoint_info.hash
@@ -131,11 +138,8 @@ def load_model_weights(model, checkpoint_info):
     pl_sd = torch.load(checkpoint_file, map_location="cpu")
     if "global_step" in pl_sd:
         print(f"Global Step: {pl_sd['global_step']}")
-    
-    if "state_dict" in pl_sd:
-        sd = pl_sd["state_dict"]
-    else:
-        sd = pl_sd
+
+    sd = get_state_dict_from_checkpoint(pl_sd)
 
     model.load_state_dict(sd, strict=False)
 
-- 
cgit v1.2.3


From 4e569fd888f8e3c5632a072d51abbb6e4d17abd6 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 9 Oct 2022 10:31:47 +0300
Subject: fixed incorrect message about loading config; thanks anon!

---
 modules/sd_models.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/sd_models.py b/modules/sd_models.py
index 18fb8c2e..2101b18d 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -169,7 +169,7 @@ def load_model():
     checkpoint_info = select_checkpoint()
 
     if checkpoint_info.config != shared.cmd_opts.config:
-        print(f"Loading config from: {shared.cmd_opts.config}")
+        print(f"Loading config from: {checkpoint_info.config}")
 
     sd_config = OmegaConf.load(checkpoint_info.config)
     sd_model = instantiate_from_config(sd_config.model)
-- 
cgit v1.2.3


From 5ab7e88d9b0bb0125af9f7237242a00a93360ce5 Mon Sep 17 00:00:00 2001
From: aoirusann <82883326+aoirusann@users.noreply.github.com>
Date: Sat, 8 Oct 2022 13:09:29 +0800
Subject: Add `Download` & `Download as zip`

---
 modules/ui.py | 39 ++++++++++++++++++++++++++++++++++-----
 1 file changed, 34 insertions(+), 5 deletions(-)

diff --git a/modules/ui.py b/modules/ui.py
index b51af121..fe7f10a7 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -98,9 +98,10 @@ def send_gradio_gallery_to_image(x):
     return image_from_url_text(x[0])
 
 
-def save_files(js_data, images, index):
+def save_files(js_data, images, do_make_zip, index):
     import csv    
     filenames = []
+    fullfns = []
 
     #quick dictionary to class object conversion. Its necessary due apply_filename_pattern requiring it
     class MyObject:
@@ -141,10 +142,22 @@ def save_files(js_data, images, index):
 
             filename = os.path.relpath(fullfn, path)
             filenames.append(filename)
+            fullfns.append(fullfn)
 
         writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]])
 
-    return '', '', plaintext_to_html(f"Saved: {filenames[0]}")
+    # Make Zip
+    if do_make_zip:
+        zip_filepath = os.path.join(path, "images.zip")
+
+        from zipfile import ZipFile
+        with ZipFile(zip_filepath, "w") as zip_file:
+            for i in range(len(fullfns)):
+                with open(fullfns[i], mode="rb") as f:
+                    zip_file.writestr(filenames[i], f.read())
+        fullfns.insert(0, zip_filepath)
+
+    return fullfns, '', '', plaintext_to_html(f"Saved: {filenames[0]}")
 
 
 def wrap_gradio_call(func, extra_outputs=None):
@@ -521,6 +534,12 @@ def create_ui(wrap_gradio_gpu_call):
                         button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder'
                         open_txt2img_folder = gr.Button(folder_symbol, elem_id=button_id)
 
+                    with gr.Row():
+                        do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
+                    
+                    with gr.Row():
+                        download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False)
+
                 with gr.Group():
                     html_info = gr.HTML()
                     generation_info = gr.Textbox(visible=False)
@@ -570,13 +589,15 @@ def create_ui(wrap_gradio_gpu_call):
 
             save.click(
                 fn=wrap_gradio_call(save_files),
-                _js="(x, y, z) => [x, y, selected_gallery_index()]",
+                _js="(x, y, z, w) => [x, y, z, selected_gallery_index()]",
                 inputs=[
                     generation_info,
                     txt2img_gallery,
+                    do_make_zip,
                     html_info,
                 ],
                 outputs=[
+                    download_files,
                     html_info,
                     html_info,
                     html_info,
@@ -701,6 +722,12 @@ def create_ui(wrap_gradio_gpu_call):
                         button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder'
                         open_img2img_folder = gr.Button(folder_symbol, elem_id=button_id)
 
+                    with gr.Row():
+                        do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
+                    
+                    with gr.Row():
+                        download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False)
+
                 with gr.Group():
                     html_info = gr.HTML()
                     generation_info = gr.Textbox(visible=False)
@@ -776,13 +803,15 @@ def create_ui(wrap_gradio_gpu_call):
 
             save.click(
                 fn=wrap_gradio_call(save_files),
-                _js="(x, y, z) => [x, y, selected_gallery_index()]",
+                _js="(x, y, z, w) => [x, y, z, selected_gallery_index()]",
                 inputs=[
                     generation_info,
                     img2img_gallery,
-                    html_info
+                    do_make_zip,
+                    html_info,
                 ],
                 outputs=[
+                    download_files,
                     html_info,
                     html_info,
                     html_info,
-- 
cgit v1.2.3


From 14192c5b207b16b1ec7a4c9c4ea538d1a6811a4d Mon Sep 17 00:00:00 2001
From: aoirusann <yimodo.siki@gmail.com>
Date: Sun, 9 Oct 2022 13:01:10 +0800
Subject: Support `Download` for txt files.

---
 modules/images.py | 39 +++++++++++++++++++++++++++++++++++++--
 modules/ui.py     |  5 ++++-
 2 files changed, 41 insertions(+), 3 deletions(-)

diff --git a/modules/images.py b/modules/images.py
index 29c5ee24..c0a90676 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -349,6 +349,38 @@ def get_next_sequence_number(path, basename):
 
 
 def save_image(image, path, basename, seed=None, prompt=None, extension='png', info=None, short_filename=False, no_prompt=False, grid=False, pnginfo_section_name='parameters', p=None, existing_info=None, forced_filename=None, suffix="", save_to_dirs=None):
+    '''Save an image.
+
+    Args:
+        image (`PIL.Image`):
+            The image to be saved.
+        path (`str`):
+            The directory to save the image. Note, the option `save_to_dirs` will make the image to be saved into a sub directory.
+        basename (`str`):
+            The base filename which will be applied to `filename pattern`.
+        seed, prompt, short_filename, 
+        extension (`str`):
+            Image file extension, default is `png`.
+        pngsectionname (`str`):
+            Specify the name of the section which `info` will be saved in.
+        info (`str` or `PngImagePlugin.iTXt`):
+            PNG info chunks.
+        existing_info (`dict`):
+            Additional PNG info. `existing_info == {pngsectionname: info, ...}`
+        no_prompt:
+            TODO I don't know its meaning.
+        p (`StableDiffusionProcessing`)
+        forced_filename (`str`):
+            If specified, `basename` and filename pattern will be ignored.
+        save_to_dirs (bool):
+            If true, the image will be saved into a subdirectory of `path`.
+
+    Returns: (fullfn, txt_fullfn)
+        fullfn (`str`):
+            The full path of the saved imaged.
+        txt_fullfn (`str` or None):
+            If a text file is saved for this image, this will be its full path. Otherwise None.
+    '''
     if short_filename or prompt is None or seed is None:
         file_decoration = ""
     elif opts.save_to_dirs:
@@ -424,7 +456,10 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i
             piexif.insert(exif_bytes(), fullfn_without_extension + ".jpg")
 
     if opts.save_txt and info is not None:
-        with open(f"{fullfn_without_extension}.txt", "w", encoding="utf8") as file:
+        txt_fullfn = f"{fullfn_without_extension}.txt"
+        with open(txt_fullfn, "w", encoding="utf8") as file:
             file.write(info + "\n")
+    else:
+        txt_fullfn = None
 
-    return fullfn
+    return fullfn, txt_fullfn
diff --git a/modules/ui.py b/modules/ui.py
index fe7f10a7..debd8873 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -138,11 +138,14 @@ def save_files(js_data, images, do_make_zip, index):
             is_grid = image_index < p.index_of_first_image
             i = 0 if is_grid else (image_index - p.index_of_first_image)
 
-            fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
+            fullfn, txt_fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
 
             filename = os.path.relpath(fullfn, path)
             filenames.append(filename)
             fullfns.append(fullfn)
+            if txt_fullfn:
+                filenames.append(os.path.basename(txt_fullfn))
+                fullfns.append(txt_fullfn)
 
         writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]])
 
-- 
cgit v1.2.3


From 122d42687b97ec4df4c2a8c335d2de385cd1f1a1 Mon Sep 17 00:00:00 2001
From: Fampai <unknown>
Date: Sat, 8 Oct 2022 22:37:35 -0400
Subject: Fix VRAM Issue by only loading in hypernetwork when selected in
 settings

---
 modules/hypernetwork.py            | 23 +++++++++++++++--------
 modules/sd_hijack_optimizations.py |  6 +++---
 modules/shared.py                  |  7 ++-----
 webui.py                           |  3 +++
 4 files changed, 23 insertions(+), 16 deletions(-)

diff --git a/modules/hypernetwork.py b/modules/hypernetwork.py
index 7f062242..19f1c227 100644
--- a/modules/hypernetwork.py
+++ b/modules/hypernetwork.py
@@ -40,18 +40,25 @@ class Hypernetwork:
             self.layers[size] = (HypernetworkModule(size, sd[0]), HypernetworkModule(size, sd[1]))
 
 
-def load_hypernetworks(path):
+def list_hypernetworks(path):
     res = {}
-
     for filename in glob.iglob(os.path.join(path, '**/*.pt'), recursive=True):
+        name = os.path.splitext(os.path.basename(filename))[0]
+        res[name] = filename
+    return res
+
+
+def load_hypernetwork(filename):
+    print(f"Loading hypernetwork {filename}")
+    path = shared.hypernetworks.get(filename, None)
+    if (path is not None):
         try:
-            hn = Hypernetwork(filename)
-            res[hn.name] = hn
+            shared.loaded_hypernetwork = Hypernetwork(path)
         except Exception:
-            print(f"Error loading hypernetwork {filename}", file=sys.stderr)
+            print(f"Error loading hypernetwork {path}", file=sys.stderr)
             print(traceback.format_exc(), file=sys.stderr)
-
-    return res
+    else:
+        shared.loaded_hypernetwork = None
 
 
 def attention_CrossAttention_forward(self, x, context=None, mask=None):
@@ -60,7 +67,7 @@ def attention_CrossAttention_forward(self, x, context=None, mask=None):
     q = self.to_q(x)
     context = default(context, x)
 
-    hypernetwork = shared.selected_hypernetwork()
+    hypernetwork = shared.loaded_hypernetwork
     hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
 
     if hypernetwork_layers is not None:
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index c4396bb9..634fb4b2 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -28,7 +28,7 @@ def split_cross_attention_forward_v1(self, x, context=None, mask=None):
     q_in = self.to_q(x)
     context = default(context, x)
 
-    hypernetwork = shared.selected_hypernetwork()
+    hypernetwork = shared.loaded_hypernetwork
     hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
 
     if hypernetwork_layers is not None:
@@ -68,7 +68,7 @@ def split_cross_attention_forward(self, x, context=None, mask=None):
     q_in = self.to_q(x)
     context = default(context, x)
 
-    hypernetwork = shared.selected_hypernetwork()
+    hypernetwork = shared.loaded_hypernetwork
     hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
 
     if hypernetwork_layers is not None:
@@ -132,7 +132,7 @@ def xformers_attention_forward(self, x, context=None, mask=None):
     h = self.heads
     q_in = self.to_q(x)
     context = default(context, x)
-    hypernetwork = shared.selected_hypernetwork()
+    hypernetwork = shared.loaded_hypernetwork
     hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
     if hypernetwork_layers is not None:
         k_in = self.to_k(hypernetwork_layers[0](context))
diff --git a/modules/shared.py b/modules/shared.py
index b2c76a32..9dce6cb7 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -79,11 +79,8 @@ parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram
 xformers_available = False
 config_filename = cmd_opts.ui_settings_file
 
-hypernetworks = hypernetwork.load_hypernetworks(os.path.join(models_path, 'hypernetworks'))
-
-
-def selected_hypernetwork():
-    return hypernetworks.get(opts.sd_hypernetwork, None)
+hypernetworks = hypernetwork.list_hypernetworks(os.path.join(models_path, 'hypernetworks'))
+loaded_hypernetwork = None
 
 
 class State:
diff --git a/webui.py b/webui.py
index 18de8e16..270584f7 100644
--- a/webui.py
+++ b/webui.py
@@ -82,6 +82,9 @@ modules.scripts.load_scripts(os.path.join(script_path, "scripts"))
 shared.sd_model = modules.sd_models.load_model()
 shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model)))
 
+loaded_hypernetwork = modules.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)
+shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)))
+
 
 def webui():
     # make the program just exit at ctrl+c without waiting for anything
-- 
cgit v1.2.3


From 03e570886f430f39020e504aba057a95f2e62484 Mon Sep 17 00:00:00 2001
From: frostydad <64224601+Cyberes@users.noreply.github.com>
Date: Sat, 8 Oct 2022 18:13:13 -0600
Subject: Fix incorrect sampler name in output

---
 modules/processing.py |  9 ++++++++-
 scripts/xy_grid.py    | 16 +++++++++-------
 2 files changed, 17 insertions(+), 8 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index 4fea6d56..6b8664a0 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -1,3 +1,4 @@
+
 import json
 import math
 import os
@@ -46,6 +47,12 @@ def apply_color_correction(correction, image):
     return image
 
 
+def get_correct_sampler(p):
+    if isinstance(p, modules.processing.StableDiffusionProcessingTxt2Img):
+        return sd_samplers.samplers
+    elif isinstance(p, modules.processing.StableDiffusionProcessingImg2Img):
+        return sd_samplers.samplers_for_img2img
+
 class StableDiffusionProcessing:
     def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt="", styles=None, seed=-1, subseed=-1, subseed_strength=0, seed_resize_from_h=-1, seed_resize_from_w=-1, seed_enable_extras=True, sampler_index=0, batch_size=1, n_iter=1, steps=50, cfg_scale=7.0, width=512, height=512, restore_faces=False, tiling=False, do_not_save_samples=False, do_not_save_grid=False, extra_generation_params=None, overlay_images=None, negative_prompt=None, eta=None):
         self.sd_model = sd_model
@@ -272,7 +279,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration
 
     generation_params = {
         "Steps": p.steps,
-        "Sampler": sd_samplers.samplers[p.sampler_index].name,
+        "Sampler": get_correct_sampler(p)[p.sampler_index].name,
         "CFG scale": p.cfg_scale,
         "Seed": all_seeds[index],
         "Face restoration": (opts.face_restoration_model if p.restore_faces else None),
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index c0c364df..26ae2199 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -11,7 +11,7 @@ import modules.scripts as scripts
 import gradio as gr
 
 from modules import images
-from modules.processing import process_images, Processed
+from modules.processing import process_images, Processed, get_correct_sampler
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
 import modules.sd_samplers
@@ -56,15 +56,17 @@ def apply_order(p, x, xs):
     p.prompt = prompt_tmp + p.prompt
     
 
-samplers_dict = {}
-for i, sampler in enumerate(modules.sd_samplers.samplers):
-    samplers_dict[sampler.name.lower()] = i
-    for alias in sampler.aliases:
-        samplers_dict[alias.lower()] = i
+def build_samplers_dict(p):
+    samplers_dict = {}
+    for i, sampler in enumerate(get_correct_sampler(p)):
+        samplers_dict[sampler.name.lower()] = i
+        for alias in sampler.aliases:
+            samplers_dict[alias.lower()] = i
+    return samplers_dict
 
 
 def apply_sampler(p, x, xs):
-    sampler_index = samplers_dict.get(x.lower(), None)
+    sampler_index = build_samplers_dict(p).get(x.lower(), None)
     if sampler_index is None:
         raise RuntimeError(f"Unknown sampler: {x}")
 
-- 
cgit v1.2.3


From ef93acdc731b7a2b3c13651b6de1bce58af989d4 Mon Sep 17 00:00:00 2001
From: frostydad <64224601+Cyberes@users.noreply.github.com>
Date: Sat, 8 Oct 2022 18:15:35 -0600
Subject: remove line break

---
 modules/processing.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/modules/processing.py b/modules/processing.py
index 6b8664a0..7fa1144e 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -1,4 +1,3 @@
-
 import json
 import math
 import os
-- 
cgit v1.2.3


From 1ffeb42d38d9276dc28918189d32f60d593a162c Mon Sep 17 00:00:00 2001
From: Nicolas Noullet <nicolas.noullet@gmail.com>
Date: Sun, 9 Oct 2022 00:18:45 +0200
Subject: Fix typo

---
 modules/shared.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/shared.py b/modules/shared.py
index 9dce6cb7..dffa0094 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -238,7 +238,7 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"),
 
 options_templates.update(options_section(('ui', "User interface"), {
     "show_progressbar": OptionInfo(True, "Show progressbar"),
-    "show_progress_every_n_steps": OptionInfo(0, "Show show image creation progress every N sampling steps. Set 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 32, "step": 1}),
+    "show_progress_every_n_steps": OptionInfo(0, "Show image creation progress every N sampling steps. Set 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 32, "step": 1}),
     "return_grid": OptionInfo(True, "Show grid in results for web"),
     "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"),
     "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"),
-- 
cgit v1.2.3


From e2930f9821c197da94e208b5ae73711002844efc Mon Sep 17 00:00:00 2001
From: Tony Beeman <beeman@gmail.com>
Date: Fri, 7 Oct 2022 17:46:39 -0700
Subject: Fix for Prompts_from_file showing extra textbox.

---
 modules/scripts.py           | 30 ++++++++++++++++++++++++++----
 scripts/prompts_from_file.py |  4 ++++
 2 files changed, 30 insertions(+), 4 deletions(-)

diff --git a/modules/scripts.py b/modules/scripts.py
index 45230f9a..d8f87927 100644
--- a/modules/scripts.py
+++ b/modules/scripts.py
@@ -1,4 +1,5 @@
 import os
+from pydoc import visiblename
 import sys
 import traceback
 
@@ -31,6 +32,15 @@ class Script:
     def show(self, is_img2img):
         return True
 
+
+    # Called when the ui for this script has been shown.
+    # Useful for hiding some controls, since the scripts module sets visibility to
+    # everything to true. The parameters will be the parameters returned by the ui method
+    # The return value should be gradio updates, similar to what you would return
+    # from a Gradio event handler.
+    def on_show(self, *args):
+        return [ui.gr_show(True)] * len(args)
+
     # This is where the additional processing is implemented. The parameters include
     # self, the model object "p" (a StableDiffusionProcessing class, see
     # processing.py), and the parameters returned by the ui method.
@@ -125,20 +135,32 @@ class ScriptRunner:
             inputs += controls
             script.args_to = len(inputs)
 
-        def select_script(script_index):
+        def select_script(*args):
+            script_index = args[0]
+            on_show_updates = []
             if 0 < script_index <= len(self.scripts):
                 script = self.scripts[script_index-1]
                 args_from = script.args_from
                 args_to = script.args_to
+                script_args = args[args_from:args_to]
+                on_show_updates = wrap_call(script.on_show, script.filename, "on_show", *script_args)
             else:
                 args_from = 0
                 args_to = 0
 
-            return [ui.gr_show(True if i == 0 else args_from <= i < args_to) for i in range(len(inputs))]
+            ret = [ ui.gr_show(True)] # always show the dropdown
+            for i in range(1, len(inputs)):
+                if (args_from <= i < args_to):
+                    ret.append( on_show_updates[i - args_from] )
+                else:
+                    ret.append(ui.gr_show(False))
+            return ret
+
+            # return [ui.gr_show(True if (i == 0) else on_show_updates[i - args_from] if args_from <= i < args_to else False) for i in range(len(inputs))]
 
         dropdown.change(
             fn=select_script,
-            inputs=[dropdown],
+            inputs=inputs,
             outputs=inputs
         )
 
@@ -198,4 +220,4 @@ def reload_scripts(basedir):
     load_scripts(basedir)
 
     scripts_txt2img = ScriptRunner()
-    scripts_img2img = ScriptRunner()
+    scripts_img2img = ScriptRunner()
\ No newline at end of file
diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py
index 513d9a1c..110889a6 100644
--- a/scripts/prompts_from_file.py
+++ b/scripts/prompts_from_file.py
@@ -10,6 +10,7 @@ from modules.processing import Processed, process_images
 from PIL import Image
 from modules.shared import opts, cmd_opts, state
 
+g_txt_mode = False
 
 class Script(scripts.Script):
     def title(self):
@@ -29,6 +30,9 @@ class Script(scripts.Script):
         checkbox_txt.change(fn=lambda x: [gr.File.update(visible = not x), gr.TextArea.update(visible = x)], inputs=[checkbox_txt], outputs=[file, prompt_txt])
         return [checkbox_txt, file, prompt_txt]
 
+    def on_show(self, checkbox_txt, file, prompt_txt):
+        return [ gr.Checkbox.update(visible = True), gr.File.update(visible = not checkbox_txt), gr.TextArea.update(visible = checkbox_txt) ]
+
     def run(self, p, checkbox_txt, data: bytes, prompt_txt: str):
         if (checkbox_txt):
             lines = [x.strip() for x in prompt_txt.splitlines()]
-- 
cgit v1.2.3


From 86cb16886f8f48169cee4658ad0c5e5443beed2a Mon Sep 17 00:00:00 2001
From: Tony Beeman <beeman@gmail.com>
Date: Fri, 7 Oct 2022 23:51:50 -0700
Subject: Pull Request Code Review Fixes

---
 modules/scripts.py           | 1 -
 scripts/prompts_from_file.py | 2 --
 2 files changed, 3 deletions(-)

diff --git a/modules/scripts.py b/modules/scripts.py
index d8f87927..8dfd4de9 100644
--- a/modules/scripts.py
+++ b/modules/scripts.py
@@ -1,5 +1,4 @@
 import os
-from pydoc import visiblename
 import sys
 import traceback
 
diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py
index 110889a6..b24f1a80 100644
--- a/scripts/prompts_from_file.py
+++ b/scripts/prompts_from_file.py
@@ -10,8 +10,6 @@ from modules.processing import Processed, process_images
 from PIL import Image
 from modules.shared import opts, cmd_opts, state
 
-g_txt_mode = False
-
 class Script(scripts.Script):
     def title(self):
         return "Prompts from file or textbox"
-- 
cgit v1.2.3


From cbf6dad02d04d98e5a2d5e870777ab99b5796b2d Mon Sep 17 00:00:00 2001
From: Tony Beeman <beeman@gmail.com>
Date: Sat, 8 Oct 2022 10:40:30 -0700
Subject: Handle case where on_show returns the wrong number of arguments

---
 modules/scripts.py | 9 ++++++---
 1 file changed, 6 insertions(+), 3 deletions(-)

diff --git a/modules/scripts.py b/modules/scripts.py
index 8dfd4de9..7d89979d 100644
--- a/modules/scripts.py
+++ b/modules/scripts.py
@@ -143,6 +143,8 @@ class ScriptRunner:
                 args_to = script.args_to
                 script_args = args[args_from:args_to]
                 on_show_updates = wrap_call(script.on_show, script.filename, "on_show", *script_args)
+                if (len(on_show_updates) != (args_to - args_from)):
+                    print("Error in custom script (" + script.filename + "): on_show() method should return the same number of arguments as ui().", file=sys.stderr)
             else:
                 args_from = 0
                 args_to = 0
@@ -150,13 +152,14 @@ class ScriptRunner:
             ret = [ ui.gr_show(True)] # always show the dropdown
             for i in range(1, len(inputs)):
                 if (args_from <= i < args_to):
-                    ret.append( on_show_updates[i - args_from] )
+                    if (i - args_from) < len(on_show_updates):
+                        ret.append( on_show_updates[i - args_from] )
+                    else:
+                        ret.append(ui.gr_show(True))
                 else:
                     ret.append(ui.gr_show(False))
             return ret
 
-            # return [ui.gr_show(True if (i == 0) else on_show_updates[i - args_from] if args_from <= i < args_to else False) for i in range(len(inputs))]
-
         dropdown.change(
             fn=select_script,
             inputs=inputs,
-- 
cgit v1.2.3


From ab4fe4f44c3d2675a351269fe2ff1ddeac557aa6 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 9 Oct 2022 11:59:41 +0300
Subject: hide filenames for save button by default

---
 modules/ui.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/modules/ui.py b/modules/ui.py
index 8071b1cb..e1ab2665 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -162,7 +162,7 @@ def save_files(js_data, images, do_make_zip, index):
                     zip_file.writestr(filenames[i], f.read())
         fullfns.insert(0, zip_filepath)
 
-    return fullfns, '', '', plaintext_to_html(f"Saved: {filenames[0]}")
+    return gr.File.update(value=fullfns, visible=True), '', '', plaintext_to_html(f"Saved: {filenames[0]}")
 
 
 def wrap_gradio_call(func, extra_outputs=None):
@@ -553,7 +553,7 @@ def create_ui(wrap_gradio_gpu_call):
                         do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
                     
                     with gr.Row():
-                        download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False)
+                        download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
 
                 with gr.Group():
                     html_info = gr.HTML()
@@ -741,7 +741,7 @@ def create_ui(wrap_gradio_gpu_call):
                         do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
                     
                     with gr.Row():
-                        download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False)
+                        download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
 
                 with gr.Group():
                     html_info = gr.HTML()
-- 
cgit v1.2.3


From 0241d811d23427b99f6b1eda1540bdf8d87963d5 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 9 Oct 2022 12:04:44 +0300
Subject: Revert "Fix for Prompts_from_file showing extra textbox."

This reverts commit e2930f9821c197da94e208b5ae73711002844efc.
---
 modules/scripts.py | 32 ++++----------------------------
 1 file changed, 4 insertions(+), 28 deletions(-)

diff --git a/modules/scripts.py b/modules/scripts.py
index 7d89979d..45230f9a 100644
--- a/modules/scripts.py
+++ b/modules/scripts.py
@@ -31,15 +31,6 @@ class Script:
     def show(self, is_img2img):
         return True
 
-
-    # Called when the ui for this script has been shown.
-    # Useful for hiding some controls, since the scripts module sets visibility to
-    # everything to true. The parameters will be the parameters returned by the ui method
-    # The return value should be gradio updates, similar to what you would return
-    # from a Gradio event handler.
-    def on_show(self, *args):
-        return [ui.gr_show(True)] * len(args)
-
     # This is where the additional processing is implemented. The parameters include
     # self, the model object "p" (a StableDiffusionProcessing class, see
     # processing.py), and the parameters returned by the ui method.
@@ -134,35 +125,20 @@ class ScriptRunner:
             inputs += controls
             script.args_to = len(inputs)
 
-        def select_script(*args):
-            script_index = args[0]
-            on_show_updates = []
+        def select_script(script_index):
             if 0 < script_index <= len(self.scripts):
                 script = self.scripts[script_index-1]
                 args_from = script.args_from
                 args_to = script.args_to
-                script_args = args[args_from:args_to]
-                on_show_updates = wrap_call(script.on_show, script.filename, "on_show", *script_args)
-                if (len(on_show_updates) != (args_to - args_from)):
-                    print("Error in custom script (" + script.filename + "): on_show() method should return the same number of arguments as ui().", file=sys.stderr)
             else:
                 args_from = 0
                 args_to = 0
 
-            ret = [ ui.gr_show(True)] # always show the dropdown
-            for i in range(1, len(inputs)):
-                if (args_from <= i < args_to):
-                    if (i - args_from) < len(on_show_updates):
-                        ret.append( on_show_updates[i - args_from] )
-                    else:
-                        ret.append(ui.gr_show(True))
-                else:
-                    ret.append(ui.gr_show(False))
-            return ret
+            return [ui.gr_show(True if i == 0 else args_from <= i < args_to) for i in range(len(inputs))]
 
         dropdown.change(
             fn=select_script,
-            inputs=inputs,
+            inputs=[dropdown],
             outputs=inputs
         )
 
@@ -222,4 +198,4 @@ def reload_scripts(basedir):
     load_scripts(basedir)
 
     scripts_txt2img = ScriptRunner()
-    scripts_img2img = ScriptRunner()
\ No newline at end of file
+    scripts_img2img = ScriptRunner()
-- 
cgit v1.2.3


From 6f6798ddabe10d320fe8ea05edf0fdcef0c51a8e Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 9 Oct 2022 12:33:37 +0300
Subject: prevent a possible code execution error (thanks, RyotaK)

---
 modules/ui.py | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/modules/ui.py b/modules/ui.py
index e1ab2665..dad509f3 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1153,6 +1153,15 @@ def create_ui(wrap_gradio_gpu_call):
     component_dict = {}
 
     def open_folder(f):
+        if not os.path.isdir(f):
+            print(f"""
+WARNING
+An open_folder request was made with an argument that is not a folder.
+This could be an error or a malicious attempt to run code on your computer.
+Requested path was: {f}
+""", file=sys.stderr)
+            return
+
         if not shared.cmd_opts.hide_ui_dir_config:
             path = os.path.normpath(f)
             if platform.system() == "Windows":
-- 
cgit v1.2.3


From d74c38108f95e44d83a1706ee5ab218124972868 Mon Sep 17 00:00:00 2001
From: Jesse Williams <33797815+xram64@users.noreply.github.com>
Date: Sat, 8 Oct 2022 01:30:49 -0400
Subject: Confirm that options are valid before starting

When using the 'Sampler' or 'Checkpoint' options, if one of the entered
names has a typo, an error will only be thrown once the `draw_xy_grid`
loop reaches that name. This can waste a lot of time for large grids
with a typo near the end of a list, since the script needs to start over
and re-generate any earlier images to finish making the grid.

Also fixing typo in variable name in `draw_xy_grid`.
---
 scripts/xy_grid.py | 21 +++++++++++++++------
 1 file changed, 15 insertions(+), 6 deletions(-)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 26ae2199..07040886 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -145,7 +145,7 @@ def draw_xy_grid(p, xs, ys, x_labels, y_labels, cell, draw_legend):
     ver_texts = [[images.GridAnnotation(y)] for y in y_labels]
     hor_texts = [[images.GridAnnotation(x)] for x in x_labels]
 
-    first_pocessed = None
+    first_processed = None
 
     state.job_count = len(xs) * len(ys) * p.n_iter
 
@@ -154,8 +154,8 @@ def draw_xy_grid(p, xs, ys, x_labels, y_labels, cell, draw_legend):
             state.job = f"{ix + iy * len(xs) + 1} out of {len(xs) * len(ys)}"
 
             processed = cell(x, y)
-            if first_pocessed is None:
-                first_pocessed = processed
+            if first_processed is None:
+                first_processed = processed
 
             try:
               res.append(processed.images[0])
@@ -166,9 +166,9 @@ def draw_xy_grid(p, xs, ys, x_labels, y_labels, cell, draw_legend):
     if draw_legend:
         grid = images.draw_grid_annotations(grid, res[0].width, res[0].height, hor_texts, ver_texts)
 
-    first_pocessed.images = [grid]
+    first_processed.images = [grid]
 
-    return first_pocessed
+    return first_processed
 
 
 re_range = re.compile(r"\s*([+-]?\s*\d+)\s*-\s*([+-]?\s*\d+)(?:\s*\(([+-]\d+)\s*\))?\s*")
@@ -216,7 +216,6 @@ class Script(scripts.Script):
                     m = re_range.fullmatch(val)
                     mc = re_range_count.fullmatch(val)
                     if m is not None:
-
                         start = int(m.group(1))
                         end = int(m.group(2))+1
                         step = int(m.group(3)) if m.group(3) is not None else 1
@@ -258,6 +257,16 @@ class Script(scripts.Script):
                 valslist = list(permutations(valslist))
 
             valslist = [opt.type(x) for x in valslist]
+            
+            # Confirm options are valid before starting
+            if opt.label == "Sampler":
+                for sampler_val in valslist:
+                    if sampler_val.lower() not in samplers_dict.keys():
+                        raise RuntimeError(f"Unknown sampler: {sampler_val}")
+            elif opt.label == "Checkpoint name":
+                for ckpt_val in valslist:
+                    if modules.sd_models.get_closet_checkpoint_match(ckpt_val) is None:
+                        raise RuntimeError(f"Checkpoint for {ckpt_val} not found")
 
             return valslist
 
-- 
cgit v1.2.3


From a65a45272e8f26ee3bc52a5300b396266508a9a5 Mon Sep 17 00:00:00 2001
From: Brendan Byrd <GitHub@ResonatorSoft.org>
Date: Thu, 6 Oct 2022 19:31:36 -0400
Subject: Don't change the seed initially if "Keep -1 for seeds" is checked

Fixes #1049
---
 scripts/xy_grid.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 07040886..a8f53bef 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -198,7 +198,9 @@ class Script(scripts.Script):
         return [x_type, x_values, y_type, y_values, draw_legend, no_fixed_seeds]
 
     def run(self, p, x_type, x_values, y_type, y_values, draw_legend, no_fixed_seeds):
-        modules.processing.fix_seed(p)
+        if not no_fixed_seeds:
+            modules.processing.fix_seed(p)
+
         p.batch_size = 1
 
         initial_hn = opts.sd_hypernetwork
-- 
cgit v1.2.3


From 0609ce06c0778536cb368ac3867292f87c6d9fc7 Mon Sep 17 00:00:00 2001
From: Milly <milly.ca@gmail.com>
Date: Fri, 7 Oct 2022 03:36:08 +0900
Subject: Removed duplicate definition model_path

---
 modules/bsrgan_model.py     | 2 --
 modules/esrgan_model.py     | 2 --
 modules/ldsr_model.py       | 2 --
 modules/realesrgan_model.py | 2 --
 modules/scunet_model.py     | 2 --
 modules/swinir_model.py     | 2 --
 modules/upscaler.py         | 7 ++++---
 7 files changed, 4 insertions(+), 15 deletions(-)

diff --git a/modules/bsrgan_model.py b/modules/bsrgan_model.py
index 3bd80791..737e1a76 100644
--- a/modules/bsrgan_model.py
+++ b/modules/bsrgan_model.py
@@ -10,13 +10,11 @@ from basicsr.utils.download_util import load_file_from_url
 import modules.upscaler
 from modules import devices, modelloader
 from modules.bsrgan_model_arch import RRDBNet
-from modules.paths import models_path
 
 
 class UpscalerBSRGAN(modules.upscaler.Upscaler):
     def __init__(self, dirname):
         self.name = "BSRGAN"
-        self.model_path = os.path.join(models_path, self.name)
         self.model_name = "BSRGAN 4x"
         self.model_url = "https://github.com/cszn/KAIR/releases/download/v1.0/BSRGAN.pth"
         self.user_path = dirname
diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py
index 28548124..3970e6e4 100644
--- a/modules/esrgan_model.py
+++ b/modules/esrgan_model.py
@@ -7,7 +7,6 @@ from basicsr.utils.download_util import load_file_from_url
 
 import modules.esrgam_model_arch as arch
 from modules import shared, modelloader, images, devices
-from modules.paths import models_path
 from modules.upscaler import Upscaler, UpscalerData
 from modules.shared import opts
 
@@ -76,7 +75,6 @@ class UpscalerESRGAN(Upscaler):
         self.model_name = "ESRGAN_4x"
         self.scalers = []
         self.user_path = dirname
-        self.model_path = os.path.join(models_path, self.name)
         super().__init__()
         model_paths = self.find_models(ext_filter=[".pt", ".pth"])
         scalers = []
diff --git a/modules/ldsr_model.py b/modules/ldsr_model.py
index 1c1070fc..8c4db44a 100644
--- a/modules/ldsr_model.py
+++ b/modules/ldsr_model.py
@@ -7,13 +7,11 @@ from basicsr.utils.download_util import load_file_from_url
 from modules.upscaler import Upscaler, UpscalerData
 from modules.ldsr_model_arch import LDSR
 from modules import shared
-from modules.paths import models_path
 
 
 class UpscalerLDSR(Upscaler):
     def __init__(self, user_path):
         self.name = "LDSR"
-        self.model_path = os.path.join(models_path, self.name)
         self.user_path = user_path
         self.model_url = "https://heibox.uni-heidelberg.de/f/578df07c8fc04ffbadf3/?dl=1"
         self.yaml_url = "https://heibox.uni-heidelberg.de/f/31a76b13ea27482981b4/?dl=1"
diff --git a/modules/realesrgan_model.py b/modules/realesrgan_model.py
index dc0123e0..3ac0b97a 100644
--- a/modules/realesrgan_model.py
+++ b/modules/realesrgan_model.py
@@ -8,14 +8,12 @@ from basicsr.utils.download_util import load_file_from_url
 from realesrgan import RealESRGANer
 
 from modules.upscaler import Upscaler, UpscalerData
-from modules.paths import models_path
 from modules.shared import cmd_opts, opts
 
 
 class UpscalerRealESRGAN(Upscaler):
     def __init__(self, path):
         self.name = "RealESRGAN"
-        self.model_path = os.path.join(models_path, self.name)
         self.user_path = path
         super().__init__()
         try:
diff --git a/modules/scunet_model.py b/modules/scunet_model.py
index fb64b740..36a996bf 100644
--- a/modules/scunet_model.py
+++ b/modules/scunet_model.py
@@ -9,14 +9,12 @@ from basicsr.utils.download_util import load_file_from_url
 
 import modules.upscaler
 from modules import devices, modelloader
-from modules.paths import models_path
 from modules.scunet_model_arch import SCUNet as net
 
 
 class UpscalerScuNET(modules.upscaler.Upscaler):
     def __init__(self, dirname):
         self.name = "ScuNET"
-        self.model_path = os.path.join(models_path, self.name)
         self.model_name = "ScuNET GAN"
         self.model_name2 = "ScuNET PSNR"
         self.model_url = "https://github.com/cszn/KAIR/releases/download/v1.0/scunet_color_real_gan.pth"
diff --git a/modules/swinir_model.py b/modules/swinir_model.py
index 9bd454c6..fbd11f84 100644
--- a/modules/swinir_model.py
+++ b/modules/swinir_model.py
@@ -8,7 +8,6 @@ from basicsr.utils.download_util import load_file_from_url
 from tqdm import tqdm
 
 from modules import modelloader
-from modules.paths import models_path
 from modules.shared import cmd_opts, opts, device
 from modules.swinir_model_arch import SwinIR as net
 from modules.upscaler import Upscaler, UpscalerData
@@ -25,7 +24,6 @@ class UpscalerSwinIR(Upscaler):
                          "/003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR" \
                          "-L_x4_GAN.pth "
         self.model_name = "SwinIR 4x"
-        self.model_path = os.path.join(models_path, self.name)
         self.user_path = dirname
         super().__init__()
         scalers = []
diff --git a/modules/upscaler.py b/modules/upscaler.py
index d9d7c5e2..34672be7 100644
--- a/modules/upscaler.py
+++ b/modules/upscaler.py
@@ -36,10 +36,11 @@ class Upscaler:
         self.half = not modules.shared.cmd_opts.no_half
         self.pre_pad = 0
         self.mod_scale = None
-        if self.name is not None and create_dirs:
+
+        if self.model_path is not None and self.name:
             self.model_path = os.path.join(models_path, self.name)
-            if not os.path.exists(self.model_path):
-                os.makedirs(self.model_path)
+        if self.model_path and create_dirs:
+            os.makedirs(self.model_path, exist_ok=True)
 
         try:
             import cv2
-- 
cgit v1.2.3


From bd833409ac7b8337040d521f6b65ced51e1b2ea8 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 9 Oct 2022 13:10:15 +0300
Subject: additional changes for saving pnginfo for #1803

---
 modules/extras.py     | 4 ++++
 modules/processing.py | 6 ++++--
 2 files changed, 8 insertions(+), 2 deletions(-)

diff --git a/modules/extras.py b/modules/extras.py
index ef6e6de7..39dd3806 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -98,6 +98,10 @@ def run_extras(extras_mode, image, image_folder, gfpgan_visibility, codeformer_v
                           no_prompt=True, grid=False, pnginfo_section_name="extras", existing_info=existing_pnginfo,
                           forced_filename=image_name if opts.use_original_name_batch else None)
 
+        if opts.enable_pnginfo:
+            image.info = existing_pnginfo
+            image.info["extras"] = info
+
         outputs.append(image)
 
     devices.torch_gc()
diff --git a/modules/processing.py b/modules/processing.py
index 7fa1144e..2c991317 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -451,7 +451,8 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
 
                 text = infotext(n, i)
                 infotexts.append(text)
-                image.info["parameters"] = text
+                if opts.enable_pnginfo:
+                    image.info["parameters"] = text
                 output_images.append(image)
 
             del x_samples_ddim 
@@ -470,7 +471,8 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
             if opts.return_grid:
                 text = infotext()
                 infotexts.insert(0, text)
-                grid.info["parameters"] = text
+                if opts.enable_pnginfo:
+                    grid.info["parameters"] = text
                 output_images.insert(0, grid)
                 index_of_first_image = 1
 
-- 
cgit v1.2.3


From f4578b343ded3b8ccd1879ea0c0b3cdadfcc3a5f Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 9 Oct 2022 13:23:30 +0300
Subject: fix model switching not working properly if there is a different yaml
 config

---
 modules/sd_models.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/modules/sd_models.py b/modules/sd_models.py
index 2101b18d..d0c74dd8 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -196,7 +196,8 @@ def reload_model_weights(sd_model, info=None):
         return
 
     if sd_model.sd_checkpoint_info.config != checkpoint_info.config:
-        return load_model()
+        shared.sd_model = load_model()
+        return shared.sd_model
 
     if shared.cmd_opts.lowvram or shared.cmd_opts.medvram:
         lowvram.send_everything_to_cpu()
-- 
cgit v1.2.3


From 77a719648db515f10136e8b8483d5b16bda2eaeb Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 9 Oct 2022 13:48:04 +0300
Subject: fix logic error in #1832

---
 modules/upscaler.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/upscaler.py b/modules/upscaler.py
index 34672be7..6ab2fb40 100644
--- a/modules/upscaler.py
+++ b/modules/upscaler.py
@@ -37,7 +37,7 @@ class Upscaler:
         self.pre_pad = 0
         self.mod_scale = None
 
-        if self.model_path is not None and self.name:
+        if self.model_path is None and self.name:
             self.model_path = os.path.join(models_path, self.name)
         if self.model_path and create_dirs:
             os.makedirs(self.model_path, exist_ok=True)
-- 
cgit v1.2.3


From 542a3d3a4a00c1383fbdaf938ceefef87cf834bb Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 9 Oct 2022 14:33:22 +0300
Subject: fix btoken hypernetworks in XY plot

---
 modules/hypernetwork.py | 7 +++++--
 scripts/xy_grid.py      | 9 +++------
 2 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/modules/hypernetwork.py b/modules/hypernetwork.py
index 19f1c227..498bc9d8 100644
--- a/modules/hypernetwork.py
+++ b/modules/hypernetwork.py
@@ -49,15 +49,18 @@ def list_hypernetworks(path):
 
 
 def load_hypernetwork(filename):
-    print(f"Loading hypernetwork {filename}")
     path = shared.hypernetworks.get(filename, None)
-    if (path is not None):
+    if path is not None:
+        print(f"Loading hypernetwork {filename}")
         try:
             shared.loaded_hypernetwork = Hypernetwork(path)
         except Exception:
             print(f"Error loading hypernetwork {path}", file=sys.stderr)
             print(traceback.format_exc(), file=sys.stderr)
     else:
+        if shared.loaded_hypernetwork is not None:
+            print(f"Unloading hypernetwork")
+
         shared.loaded_hypernetwork = None
 
 
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index a8f53bef..fe949067 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -10,7 +10,7 @@ import numpy as np
 import modules.scripts as scripts
 import gradio as gr
 
-from modules import images
+from modules import images, hypernetwork
 from modules.processing import process_images, Processed, get_correct_sampler
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
@@ -80,8 +80,7 @@ def apply_checkpoint(p, x, xs):
 
 
 def apply_hypernetwork(p, x, xs):
-    hn = shared.hypernetworks.get(x, None)
-    opts.data["sd_hypernetwork"] = hn.name if hn is not None else 'None'
+    hypernetwork.load_hypernetwork(x)
 
 
 def format_value_add_label(p, opt, x):
@@ -203,8 +202,6 @@ class Script(scripts.Script):
 
         p.batch_size = 1
 
-        initial_hn = opts.sd_hypernetwork
-
         def process_axis(opt, vals):
             if opt.label == 'Nothing':
                 return [0]
@@ -321,6 +318,6 @@ class Script(scripts.Script):
         # restore checkpoint in case it was changed by axes
         modules.sd_models.reload_model_weights(shared.sd_model)
 
-        opts.data["sd_hypernetwork"] = initial_hn
+        hypernetwork.load_hypernetwork(opts.sd_hypernetwork)
 
         return processed
-- 
cgit v1.2.3


From d6d10a37bfd21568e74efb46137f906da96d5fdb Mon Sep 17 00:00:00 2001
From: William Moorehouse <moorehousew@gmail.com>
Date: Sun, 9 Oct 2022 04:58:40 -0400
Subject: Added extended model details to infotext

---
 modules/processing.py | 3 +++
 modules/sd_models.py  | 3 ++-
 modules/shared.py     | 1 +
 3 files changed, 6 insertions(+), 1 deletion(-)

diff --git a/modules/processing.py b/modules/processing.py
index 2c991317..d1bcee4a 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -284,6 +284,9 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration
         "Face restoration": (opts.face_restoration_model if p.restore_faces else None),
         "Size": f"{p.width}x{p.height}",
         "Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash),
+        "Model": (None if not opts.add_extended_model_details_to_info or not shared.sd_model.sd_model_name else shared.sd_model.sd_model_name),
+        "Model VAE": (None if not opts.add_extended_model_details_to_info or not shared.sd_model.sd_model_vae_name else shared.sd_model.sd_model_vae_name),
+        "Model hypernetwork": (None if not opts.add_extended_model_details_to_info or not opts.sd_hypernetwork else opts.sd_hypernetwork),
         "Batch size": (None if p.batch_size < 2 else p.batch_size),
         "Batch pos": (None if p.batch_size < 2 else position_in_batch),
         "Variation seed": (None if p.subseed_strength == 0 else all_subseeds[index]),
diff --git a/modules/sd_models.py b/modules/sd_models.py
index d0c74dd8..3fa42329 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -4,7 +4,7 @@ import sys
 from collections import namedtuple
 import torch
 from omegaconf import OmegaConf
-
+from pathlib import Path
 
 from ldm.util import instantiate_from_config
 
@@ -158,6 +158,7 @@ def load_model_weights(model, checkpoint_info):
         vae_dict = {k: v for k, v in vae_ckpt["state_dict"].items() if k[0:4] != "loss"}
 
         model.first_stage_model.load_state_dict(vae_dict)
+        model.sd_model_vae_name = Path(vae_file).stem
 
     model.sd_model_hash = sd_model_hash
     model.sd_model_checkpoint = checkpoint_file
diff --git a/modules/shared.py b/modules/shared.py
index dffa0094..ca63f7d8 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -242,6 +242,7 @@ options_templates.update(options_section(('ui', "User interface"), {
     "return_grid": OptionInfo(True, "Show grid in results for web"),
     "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"),
     "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"),
+    "add_extended_model_details_to_info": OptionInfo(False, "Add extended model details to generation information (model name, VAE, hypernetwork)"),
     "font": OptionInfo("", "Font for image grids that have text"),
     "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"),
     "js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),
-- 
cgit v1.2.3


From 006791c13d70e582eee766b7d0499e9821a86bf9 Mon Sep 17 00:00:00 2001
From: William Moorehouse <moorehousew@gmail.com>
Date: Sun, 9 Oct 2022 05:09:18 -0400
Subject: Fix grabbing the model name for infotext

---
 modules/processing.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/processing.py b/modules/processing.py
index d1bcee4a..c035c990 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -284,7 +284,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration
         "Face restoration": (opts.face_restoration_model if p.restore_faces else None),
         "Size": f"{p.width}x{p.height}",
         "Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash),
-        "Model": (None if not opts.add_extended_model_details_to_info or not shared.sd_model.sd_model_name else shared.sd_model.sd_model_name),
+        "Model": (None if not opts.add_extended_model_details_to_info or not shared.sd_model.sd_checkpoint_info.model_name else shared.sd_model.sd_checkpoint_info.model_name),
         "Model VAE": (None if not opts.add_extended_model_details_to_info or not shared.sd_model.sd_model_vae_name else shared.sd_model.sd_model_vae_name),
         "Model hypernetwork": (None if not opts.add_extended_model_details_to_info or not opts.sd_hypernetwork else opts.sd_hypernetwork),
         "Batch size": (None if p.batch_size < 2 else p.batch_size),
-- 
cgit v1.2.3


From 594cbfd8fbe4078b43ceccf01509eeef3d6790c6 Mon Sep 17 00:00:00 2001
From: William Moorehouse <moorehousew@gmail.com>
Date: Sun, 9 Oct 2022 07:27:11 -0400
Subject: Sanitize infotext output (for now)

---
 modules/processing.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index c035c990..049f3769 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -284,9 +284,9 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration
         "Face restoration": (opts.face_restoration_model if p.restore_faces else None),
         "Size": f"{p.width}x{p.height}",
         "Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash),
-        "Model": (None if not opts.add_extended_model_details_to_info or not shared.sd_model.sd_checkpoint_info.model_name else shared.sd_model.sd_checkpoint_info.model_name),
-        "Model VAE": (None if not opts.add_extended_model_details_to_info or not shared.sd_model.sd_model_vae_name else shared.sd_model.sd_model_vae_name),
-        "Model hypernetwork": (None if not opts.add_extended_model_details_to_info or not opts.sd_hypernetwork else opts.sd_hypernetwork),
+        "Model": (None if not opts.add_extended_model_details_to_info or not shared.sd_model.sd_checkpoint_info.model_name else shared.sd_model.sd_checkpoint_info.model_name.replace(',', '').replace(':', '')),
+        "Model VAE": (None if not opts.add_extended_model_details_to_info or not shared.sd_model.sd_model_vae_name else shared.sd_model.sd_model_vae_name.replace(',', '').replace(':', '')),
+        "Model hypernetwork": (None if not opts.add_extended_model_details_to_info or not opts.sd_hypernetwork else opts.sd_hypernetwork.replace(',', '').replace(':', '')),
         "Batch size": (None if p.batch_size < 2 else p.batch_size),
         "Batch pos": (None if p.batch_size < 2 else position_in_batch),
         "Variation seed": (None if p.subseed_strength == 0 else all_subseeds[index]),
-- 
cgit v1.2.3


From e6e8cabe0c9c335e0d72345602c069b198558b53 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 9 Oct 2022 14:57:48 +0300
Subject: change up #2056 to make it work how i want it to plus make xy plot
 write correct values to images

---
 modules/processing.py | 5 ++---
 modules/sd_models.py  | 2 --
 modules/shared.py     | 2 +-
 3 files changed, 3 insertions(+), 6 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index 049f3769..04aed989 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -284,9 +284,8 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration
         "Face restoration": (opts.face_restoration_model if p.restore_faces else None),
         "Size": f"{p.width}x{p.height}",
         "Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash),
-        "Model": (None if not opts.add_extended_model_details_to_info or not shared.sd_model.sd_checkpoint_info.model_name else shared.sd_model.sd_checkpoint_info.model_name.replace(',', '').replace(':', '')),
-        "Model VAE": (None if not opts.add_extended_model_details_to_info or not shared.sd_model.sd_model_vae_name else shared.sd_model.sd_model_vae_name.replace(',', '').replace(':', '')),
-        "Model hypernetwork": (None if not opts.add_extended_model_details_to_info or not opts.sd_hypernetwork else opts.sd_hypernetwork.replace(',', '').replace(':', '')),
+        "Model": (None if not opts.add_model_name_to_info or not shared.sd_model.sd_checkpoint_info.model_name else shared.sd_model.sd_checkpoint_info.model_name.replace(',', '').replace(':', '')),
+        "Hypernet": (None if shared.loaded_hypernetwork is None else shared.loaded_hypernetwork.name.replace(',', '').replace(':', '')),
         "Batch size": (None if p.batch_size < 2 else p.batch_size),
         "Batch pos": (None if p.batch_size < 2 else position_in_batch),
         "Variation seed": (None if p.subseed_strength == 0 else all_subseeds[index]),
diff --git a/modules/sd_models.py b/modules/sd_models.py
index 3fa42329..e63d3c29 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -4,7 +4,6 @@ import sys
 from collections import namedtuple
 import torch
 from omegaconf import OmegaConf
-from pathlib import Path
 
 from ldm.util import instantiate_from_config
 
@@ -158,7 +157,6 @@ def load_model_weights(model, checkpoint_info):
         vae_dict = {k: v for k, v in vae_ckpt["state_dict"].items() if k[0:4] != "loss"}
 
         model.first_stage_model.load_state_dict(vae_dict)
-        model.sd_model_vae_name = Path(vae_file).stem
 
     model.sd_model_hash = sd_model_hash
     model.sd_model_checkpoint = checkpoint_file
diff --git a/modules/shared.py b/modules/shared.py
index ca63f7d8..6ecc2503 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -242,7 +242,7 @@ options_templates.update(options_section(('ui', "User interface"), {
     "return_grid": OptionInfo(True, "Show grid in results for web"),
     "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"),
     "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"),
-    "add_extended_model_details_to_info": OptionInfo(False, "Add extended model details to generation information (model name, VAE, hypernetwork)"),
+    "add_model_name_to_info": OptionInfo(False, "Add model name to generation information"),
     "font": OptionInfo("", "Font for image grids that have text"),
     "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"),
     "js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),
-- 
cgit v1.2.3


From 2c52f4da7ff80a3ec277105f4db6146c6379898a Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 9 Oct 2022 15:01:42 +0300
Subject: fix broken samplers in XY plot

---
 scripts/xy_grid.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index fe949067..c89ca1a9 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -259,6 +259,7 @@ class Script(scripts.Script):
             
             # Confirm options are valid before starting
             if opt.label == "Sampler":
+                samplers_dict = build_samplers_dict(p)
                 for sampler_val in valslist:
                     if sampler_val.lower() not in samplers_dict.keys():
                         raise RuntimeError(f"Unknown sampler: {sampler_val}")
-- 
cgit v1.2.3


From 9d1138e2940c4ddcd2685bcba12c7d407e9e0ec5 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 9 Oct 2022 15:08:10 +0300
Subject: fix typo in filename for ESRGAN arch

---
 modules/esrgam_model_arch.py | 80 --------------------------------------------
 modules/esrgan_model.py      |  2 +-
 modules/esrgan_model_arch.py | 80 ++++++++++++++++++++++++++++++++++++++++++++
 3 files changed, 81 insertions(+), 81 deletions(-)
 delete mode 100644 modules/esrgam_model_arch.py
 create mode 100644 modules/esrgan_model_arch.py

diff --git a/modules/esrgam_model_arch.py b/modules/esrgam_model_arch.py
deleted file mode 100644
index e413d36e..00000000
--- a/modules/esrgam_model_arch.py
+++ /dev/null
@@ -1,80 +0,0 @@
-# this file is taken from https://github.com/xinntao/ESRGAN
-
-import functools
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-
-
-def make_layer(block, n_layers):
-    layers = []
-    for _ in range(n_layers):
-        layers.append(block())
-    return nn.Sequential(*layers)
-
-
-class ResidualDenseBlock_5C(nn.Module):
-    def __init__(self, nf=64, gc=32, bias=True):
-        super(ResidualDenseBlock_5C, self).__init__()
-        # gc: growth channel, i.e. intermediate channels
-        self.conv1 = nn.Conv2d(nf, gc, 3, 1, 1, bias=bias)
-        self.conv2 = nn.Conv2d(nf + gc, gc, 3, 1, 1, bias=bias)
-        self.conv3 = nn.Conv2d(nf + 2 * gc, gc, 3, 1, 1, bias=bias)
-        self.conv4 = nn.Conv2d(nf + 3 * gc, gc, 3, 1, 1, bias=bias)
-        self.conv5 = nn.Conv2d(nf + 4 * gc, nf, 3, 1, 1, bias=bias)
-        self.lrelu = nn.LeakyReLU(negative_slope=0.2, inplace=True)
-
-        # initialization
-        # mutil.initialize_weights([self.conv1, self.conv2, self.conv3, self.conv4, self.conv5], 0.1)
-
-    def forward(self, x):
-        x1 = self.lrelu(self.conv1(x))
-        x2 = self.lrelu(self.conv2(torch.cat((x, x1), 1)))
-        x3 = self.lrelu(self.conv3(torch.cat((x, x1, x2), 1)))
-        x4 = self.lrelu(self.conv4(torch.cat((x, x1, x2, x3), 1)))
-        x5 = self.conv5(torch.cat((x, x1, x2, x3, x4), 1))
-        return x5 * 0.2 + x
-
-
-class RRDB(nn.Module):
-    '''Residual in Residual Dense Block'''
-
-    def __init__(self, nf, gc=32):
-        super(RRDB, self).__init__()
-        self.RDB1 = ResidualDenseBlock_5C(nf, gc)
-        self.RDB2 = ResidualDenseBlock_5C(nf, gc)
-        self.RDB3 = ResidualDenseBlock_5C(nf, gc)
-
-    def forward(self, x):
-        out = self.RDB1(x)
-        out = self.RDB2(out)
-        out = self.RDB3(out)
-        return out * 0.2 + x
-
-
-class RRDBNet(nn.Module):
-    def __init__(self, in_nc, out_nc, nf, nb, gc=32):
-        super(RRDBNet, self).__init__()
-        RRDB_block_f = functools.partial(RRDB, nf=nf, gc=gc)
-
-        self.conv_first = nn.Conv2d(in_nc, nf, 3, 1, 1, bias=True)
-        self.RRDB_trunk = make_layer(RRDB_block_f, nb)
-        self.trunk_conv = nn.Conv2d(nf, nf, 3, 1, 1, bias=True)
-        #### upsampling
-        self.upconv1 = nn.Conv2d(nf, nf, 3, 1, 1, bias=True)
-        self.upconv2 = nn.Conv2d(nf, nf, 3, 1, 1, bias=True)
-        self.HRconv = nn.Conv2d(nf, nf, 3, 1, 1, bias=True)
-        self.conv_last = nn.Conv2d(nf, out_nc, 3, 1, 1, bias=True)
-
-        self.lrelu = nn.LeakyReLU(negative_slope=0.2, inplace=True)
-
-    def forward(self, x):
-        fea = self.conv_first(x)
-        trunk = self.trunk_conv(self.RRDB_trunk(fea))
-        fea = fea + trunk
-
-        fea = self.lrelu(self.upconv1(F.interpolate(fea, scale_factor=2, mode='nearest')))
-        fea = self.lrelu(self.upconv2(F.interpolate(fea, scale_factor=2, mode='nearest')))
-        out = self.conv_last(self.lrelu(self.HRconv(fea)))
-
-        return out
diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py
index 3970e6e4..46ad0da3 100644
--- a/modules/esrgan_model.py
+++ b/modules/esrgan_model.py
@@ -5,7 +5,7 @@ import torch
 from PIL import Image
 from basicsr.utils.download_util import load_file_from_url
 
-import modules.esrgam_model_arch as arch
+import modules.esrgan_model_arch as arch
 from modules import shared, modelloader, images, devices
 from modules.upscaler import Upscaler, UpscalerData
 from modules.shared import opts
diff --git a/modules/esrgan_model_arch.py b/modules/esrgan_model_arch.py
new file mode 100644
index 00000000..e413d36e
--- /dev/null
+++ b/modules/esrgan_model_arch.py
@@ -0,0 +1,80 @@
+# this file is taken from https://github.com/xinntao/ESRGAN
+
+import functools
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+
+
+def make_layer(block, n_layers):
+    layers = []
+    for _ in range(n_layers):
+        layers.append(block())
+    return nn.Sequential(*layers)
+
+
+class ResidualDenseBlock_5C(nn.Module):
+    def __init__(self, nf=64, gc=32, bias=True):
+        super(ResidualDenseBlock_5C, self).__init__()
+        # gc: growth channel, i.e. intermediate channels
+        self.conv1 = nn.Conv2d(nf, gc, 3, 1, 1, bias=bias)
+        self.conv2 = nn.Conv2d(nf + gc, gc, 3, 1, 1, bias=bias)
+        self.conv3 = nn.Conv2d(nf + 2 * gc, gc, 3, 1, 1, bias=bias)
+        self.conv4 = nn.Conv2d(nf + 3 * gc, gc, 3, 1, 1, bias=bias)
+        self.conv5 = nn.Conv2d(nf + 4 * gc, nf, 3, 1, 1, bias=bias)
+        self.lrelu = nn.LeakyReLU(negative_slope=0.2, inplace=True)
+
+        # initialization
+        # mutil.initialize_weights([self.conv1, self.conv2, self.conv3, self.conv4, self.conv5], 0.1)
+
+    def forward(self, x):
+        x1 = self.lrelu(self.conv1(x))
+        x2 = self.lrelu(self.conv2(torch.cat((x, x1), 1)))
+        x3 = self.lrelu(self.conv3(torch.cat((x, x1, x2), 1)))
+        x4 = self.lrelu(self.conv4(torch.cat((x, x1, x2, x3), 1)))
+        x5 = self.conv5(torch.cat((x, x1, x2, x3, x4), 1))
+        return x5 * 0.2 + x
+
+
+class RRDB(nn.Module):
+    '''Residual in Residual Dense Block'''
+
+    def __init__(self, nf, gc=32):
+        super(RRDB, self).__init__()
+        self.RDB1 = ResidualDenseBlock_5C(nf, gc)
+        self.RDB2 = ResidualDenseBlock_5C(nf, gc)
+        self.RDB3 = ResidualDenseBlock_5C(nf, gc)
+
+    def forward(self, x):
+        out = self.RDB1(x)
+        out = self.RDB2(out)
+        out = self.RDB3(out)
+        return out * 0.2 + x
+
+
+class RRDBNet(nn.Module):
+    def __init__(self, in_nc, out_nc, nf, nb, gc=32):
+        super(RRDBNet, self).__init__()
+        RRDB_block_f = functools.partial(RRDB, nf=nf, gc=gc)
+
+        self.conv_first = nn.Conv2d(in_nc, nf, 3, 1, 1, bias=True)
+        self.RRDB_trunk = make_layer(RRDB_block_f, nb)
+        self.trunk_conv = nn.Conv2d(nf, nf, 3, 1, 1, bias=True)
+        #### upsampling
+        self.upconv1 = nn.Conv2d(nf, nf, 3, 1, 1, bias=True)
+        self.upconv2 = nn.Conv2d(nf, nf, 3, 1, 1, bias=True)
+        self.HRconv = nn.Conv2d(nf, nf, 3, 1, 1, bias=True)
+        self.conv_last = nn.Conv2d(nf, out_nc, 3, 1, 1, bias=True)
+
+        self.lrelu = nn.LeakyReLU(negative_slope=0.2, inplace=True)
+
+    def forward(self, x):
+        fea = self.conv_first(x)
+        trunk = self.trunk_conv(self.RRDB_trunk(fea))
+        fea = fea + trunk
+
+        fea = self.lrelu(self.upconv1(F.interpolate(fea, scale_factor=2, mode='nearest')))
+        fea = self.lrelu(self.upconv2(F.interpolate(fea, scale_factor=2, mode='nearest')))
+        out = self.conv_last(self.lrelu(self.HRconv(fea)))
+
+        return out
-- 
cgit v1.2.3


From f8197976ef5f0523faffb2b237e9166fb2bedecd Mon Sep 17 00:00:00 2001
From: Greendayle <Greendayle>
Date: Sun, 9 Oct 2022 13:44:13 +0200
Subject: Shielded launch enviroment creation stuff from multiprocessing

---
 launch.py | 174 ++++++++++++++++++++++++++++++--------------------------------
 1 file changed, 85 insertions(+), 89 deletions(-)

diff --git a/launch.py b/launch.py
index b0a59b6a..d1a4fd6a 100644
--- a/launch.py
+++ b/launch.py
@@ -6,40 +6,11 @@ import importlib.util
 import shlex
 import platform
 
-dir_repos = "repositories"
-dir_tmp = "tmp"
-
-python = sys.executable
-git = os.environ.get('GIT', "git")
-torch_command = os.environ.get('TORCH_COMMAND', "pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 --extra-index-url https://download.pytorch.org/whl/cu113")
-requirements_file = os.environ.get('REQS_FILE', "requirements_versions.txt")
-commandline_args = os.environ.get('COMMANDLINE_ARGS', "")
-
-gfpgan_package = os.environ.get('GFPGAN_PACKAGE', "git+https://github.com/TencentARC/GFPGAN.git@8d2447a2d918f8eba5a4a01463fd48e45126a379")
-clip_package = os.environ.get('CLIP_PACKAGE', "git+https://github.com/openai/CLIP.git@d50d76daa670286dd6cacf3bcd80b5e4823fc8e1")
-
-stable_diffusion_commit_hash = os.environ.get('STABLE_DIFFUSION_COMMIT_HASH', "69ae4b35e0a0f6ee1af8bb9a5d0016ccb27e36dc")
-taming_transformers_commit_hash = os.environ.get('TAMING_TRANSFORMERS_COMMIT_HASH', "24268930bf1dce879235a7fddd0b2355b84d7ea6")
-k_diffusion_commit_hash = os.environ.get('K_DIFFUSION_COMMIT_HASH', "f4e99857772fc3a126ba886aadf795a332774878")
-codeformer_commit_hash = os.environ.get('CODEFORMER_COMMIT_HASH', "c5b4593074ba6214284d6acd5f1719b6c5d739af")
-blip_commit_hash = os.environ.get('BLIP_COMMIT_HASH', "48211a1594f1321b00f14c9f7a5b4813144b2fb9")
-
-args = shlex.split(commandline_args)
-
 
 def extract_arg(args, name):
     return [x for x in args if x != name], name in args
 
 
-args, skip_torch_cuda_test = extract_arg(args, '--skip-torch-cuda-test')
-xformers = '--xformers' in args
-deepdanbooru = '--deepdanbooru' in args
-
-
-def repo_dir(name):
-    return os.path.join(dir_repos, name)
-
-
 def run(command, desc=None, errdesc=None):
     if desc is not None:
         print(desc)
@@ -59,23 +30,11 @@ stderr: {result.stderr.decode(encoding="utf8", errors="ignore") if len(result.st
     return result.stdout.decode(encoding="utf8", errors="ignore")
 
 
-def run_python(code, desc=None, errdesc=None):
-    return run(f'"{python}" -c "{code}"', desc, errdesc)
-
-
-def run_pip(args, desc=None):
-    return run(f'"{python}" -m pip {args} --prefer-binary', desc=f"Installing {desc}", errdesc=f"Couldn't install {desc}")
-
-
 def check_run(command):
     result = subprocess.run(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True)
     return result.returncode == 0
 
 
-def check_run_python(code):
-    return check_run(f'"{python}" -c "{code}"')
-
-
 def is_installed(package):
     try:
         spec = importlib.util.find_spec(package)
@@ -85,80 +44,117 @@ def is_installed(package):
     return spec is not None
 
 
-def git_clone(url, dir, name, commithash=None):
-    # TODO clone into temporary dir and move if successful
+def prepare_enviroment():
+    dir_repos = "repositories"
 
-    if os.path.exists(dir):
-        if commithash is None:
-            return
+    python = sys.executable
+    git = os.environ.get('GIT', "git")
+    torch_command = os.environ.get('TORCH_COMMAND', "pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 --extra-index-url https://download.pytorch.org/whl/cu113")
+    requirements_file = os.environ.get('REQS_FILE', "requirements_versions.txt")
+    commandline_args = os.environ.get('COMMANDLINE_ARGS', "")
 
-        current_hash = run(f'"{git}" -C {dir} rev-parse HEAD', None, f"Couldn't determine {name}'s hash: {commithash}").strip()
-        if current_hash == commithash:
-            return
+    gfpgan_package = os.environ.get('GFPGAN_PACKAGE', "git+https://github.com/TencentARC/GFPGAN.git@8d2447a2d918f8eba5a4a01463fd48e45126a379")
+    clip_package = os.environ.get('CLIP_PACKAGE', "git+https://github.com/openai/CLIP.git@d50d76daa670286dd6cacf3bcd80b5e4823fc8e1")
+
+    stable_diffusion_commit_hash = os.environ.get('STABLE_DIFFUSION_COMMIT_HASH', "69ae4b35e0a0f6ee1af8bb9a5d0016ccb27e36dc")
+    taming_transformers_commit_hash = os.environ.get('TAMING_TRANSFORMERS_COMMIT_HASH', "24268930bf1dce879235a7fddd0b2355b84d7ea6")
+    k_diffusion_commit_hash = os.environ.get('K_DIFFUSION_COMMIT_HASH', "f4e99857772fc3a126ba886aadf795a332774878")
+    codeformer_commit_hash = os.environ.get('CODEFORMER_COMMIT_HASH', "c5b4593074ba6214284d6acd5f1719b6c5d739af")
+    blip_commit_hash = os.environ.get('BLIP_COMMIT_HASH', "48211a1594f1321b00f14c9f7a5b4813144b2fb9")
+
+    args = shlex.split(commandline_args)
+
+    args, skip_torch_cuda_test = extract_arg(args, '--skip-torch-cuda-test')
+    xformers = '--xformers' in args
+    deepdanbooru = '--deepdanbooru' in args
+
+    def repo_dir(name):
+        return os.path.join(dir_repos, name)
+
+    def run_python(code, desc=None, errdesc=None):
+        return run(f'"{python}" -c "{code}"', desc, errdesc)
 
-        run(f'"{git}" -C {dir} fetch', f"Fetching updates for {name}...", f"Couldn't fetch {name}")
-        run(f'"{git}" -C {dir} checkout {commithash}', f"Checking out commint for {name} with hash: {commithash}...", f"Couldn't checkout commit {commithash} for {name}")
-        return
+    def run_pip(args, desc=None):
+        return run(f'"{python}" -m pip {args} --prefer-binary', desc=f"Installing {desc}", errdesc=f"Couldn't install {desc}")
 
-    run(f'"{git}" clone "{url}" "{dir}"', f"Cloning {name} into {dir}...", f"Couldn't clone {name}")
+    def check_run_python(code):
+        return check_run(f'"{python}" -c "{code}"')
 
-    if commithash is not None:
-        run(f'"{git}" -C {dir} checkout {commithash}', None, "Couldn't checkout {name}'s hash: {commithash}")
+    def git_clone(url, dir, name, commithash=None):
+        # TODO clone into temporary dir and move if successful
 
+        if os.path.exists(dir):
+            if commithash is None:
+                return
 
-try:
-    commit = run(f"{git} rev-parse HEAD").strip()
-except Exception:
-    commit = "<none>"
+            current_hash = run(f'"{git}" -C {dir} rev-parse HEAD', None, f"Couldn't determine {name}'s hash: {commithash}").strip()
+            if current_hash == commithash:
+                return
 
-print(f"Python {sys.version}")
-print(f"Commit hash: {commit}")
+            run(f'"{git}" -C {dir} fetch', f"Fetching updates for {name}...", f"Couldn't fetch {name}")
+            run(f'"{git}" -C {dir} checkout {commithash}', f"Checking out commint for {name} with hash: {commithash}...", f"Couldn't checkout commit {commithash} for {name}")
+            return
+
+        run(f'"{git}" clone "{url}" "{dir}"', f"Cloning {name} into {dir}...", f"Couldn't clone {name}")
 
+        if commithash is not None:
+            run(f'"{git}" -C {dir} checkout {commithash}', None, "Couldn't checkout {name}'s hash: {commithash}")
+
+    try:
+        commit = run(f"{git} rev-parse HEAD").strip()
+    except Exception:
+        commit = "<none>"
 
-if not is_installed("torch") or not is_installed("torchvision"):
-    run(f'"{python}" -m {torch_command}', "Installing torch and torchvision", "Couldn't install torch")
+    print(f"Python {sys.version}")
+    print(f"Commit hash: {commit}")
 
-if not skip_torch_cuda_test:
-    run_python("import torch; assert torch.cuda.is_available(), 'Torch is not able to use GPU; add --skip-torch-cuda-test to COMMANDLINE_ARGS variable to disable this check'")
+    if not is_installed("torch") or not is_installed("torchvision"):
+        run(f'"{python}" -m {torch_command}', "Installing torch and torchvision", "Couldn't install torch")
 
-if not is_installed("gfpgan"):
-    run_pip(f"install {gfpgan_package}", "gfpgan")
+    if not skip_torch_cuda_test:
+        run_python("import torch; assert torch.cuda.is_available(), 'Torch is not able to use GPU; add --skip-torch-cuda-test to COMMANDLINE_ARGS variable to disable this check'")
 
-if not is_installed("clip"):
-    run_pip(f"install {clip_package}", "clip")
+    if not is_installed("gfpgan"):
+        run_pip(f"install {gfpgan_package}", "gfpgan")
 
-if not is_installed("xformers") and xformers and platform.python_version().startswith("3.10"):
-    if platform.system() == "Windows":
-        run_pip("install https://github.com/C43H66N12O12S2/stable-diffusion-webui/releases/download/a/xformers-0.0.14.dev0-cp310-cp310-win_amd64.whl", "xformers")
-    elif platform.system() == "Linux":
-        run_pip("install xformers", "xformers")
+    if not is_installed("clip"):
+        run_pip(f"install {clip_package}", "clip")
 
-if not is_installed("deepdanbooru") and deepdanbooru:
-    run_pip("install git+https://github.com/KichangKim/DeepDanbooru.git@edf73df4cdaeea2cf00e9ac08bd8a9026b7a7b26#egg=deepdanbooru[tensorflow] tensorflow==2.10.0 tensorflow-io==0.27.0", "deepdanbooru")
+    if not is_installed("xformers") and xformers and platform.python_version().startswith("3.10"):
+        if platform.system() == "Windows":
+            run_pip("install https://github.com/C43H66N12O12S2/stable-diffusion-webui/releases/download/a/xformers-0.0.14.dev0-cp310-cp310-win_amd64.whl", "xformers")
+        elif platform.system() == "Linux":
+            run_pip("install xformers", "xformers")
 
-os.makedirs(dir_repos, exist_ok=True)
+    if not is_installed("deepdanbooru") and deepdanbooru:
+        run_pip("install git+https://github.com/KichangKim/DeepDanbooru.git@edf73df4cdaeea2cf00e9ac08bd8a9026b7a7b26#egg=deepdanbooru[tensorflow] tensorflow==2.10.0 tensorflow-io==0.27.0", "deepdanbooru")
 
-git_clone("https://github.com/CompVis/stable-diffusion.git", repo_dir('stable-diffusion'), "Stable Diffusion", stable_diffusion_commit_hash)
-git_clone("https://github.com/CompVis/taming-transformers.git", repo_dir('taming-transformers'), "Taming Transformers", taming_transformers_commit_hash)
-git_clone("https://github.com/crowsonkb/k-diffusion.git", repo_dir('k-diffusion'), "K-diffusion", k_diffusion_commit_hash)
-git_clone("https://github.com/sczhou/CodeFormer.git", repo_dir('CodeFormer'), "CodeFormer", codeformer_commit_hash)
-git_clone("https://github.com/salesforce/BLIP.git", repo_dir('BLIP'), "BLIP", blip_commit_hash)
+    os.makedirs(dir_repos, exist_ok=True)
 
-if not is_installed("lpips"):
-    run_pip(f"install -r {os.path.join(repo_dir('CodeFormer'), 'requirements.txt')}", "requirements for CodeFormer")
+    git_clone("https://github.com/CompVis/stable-diffusion.git", repo_dir('stable-diffusion'), "Stable Diffusion", stable_diffusion_commit_hash)
+    git_clone("https://github.com/CompVis/taming-transformers.git", repo_dir('taming-transformers'), "Taming Transformers", taming_transformers_commit_hash)
+    git_clone("https://github.com/crowsonkb/k-diffusion.git", repo_dir('k-diffusion'), "K-diffusion", k_diffusion_commit_hash)
+    git_clone("https://github.com/sczhou/CodeFormer.git", repo_dir('CodeFormer'), "CodeFormer", codeformer_commit_hash)
+    git_clone("https://github.com/salesforce/BLIP.git", repo_dir('BLIP'), "BLIP", blip_commit_hash)
 
-run_pip(f"install -r {requirements_file}", "requirements for Web UI")
+    if not is_installed("lpips"):
+        run_pip(f"install -r {os.path.join(repo_dir('CodeFormer'), 'requirements.txt')}", "requirements for CodeFormer")
 
-sys.argv += args
+    run_pip(f"install -r {requirements_file}", "requirements for Web UI")
+
+    sys.argv += args
+
+    if "--exit" in args:
+        print("Exiting because of --exit argument")
+        exit(0)
 
-if "--exit" in args:
-    print("Exiting because of --exit argument")
-    exit(0)
 
 def start_webui():
     print(f"Launching Web UI with arguments: {' '.join(sys.argv[1:])}")
     import webui
     webui.webui()
 
+
 if __name__ == "__main__":
+    prepare_enviroment()
     start_webui()
-- 
cgit v1.2.3


From bba2ac8324ccd1a67c78e5f59babae8323ec7dc6 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 9 Oct 2022 15:22:51 +0300
Subject: reshuffle the code a bit in launcher to keep functions in one place
 for #2069

---
 launch.py | 77 ++++++++++++++++++++++++++++++++++-----------------------------
 1 file changed, 41 insertions(+), 36 deletions(-)

diff --git a/launch.py b/launch.py
index d1a4fd6a..f42f557d 100644
--- a/launch.py
+++ b/launch.py
@@ -6,6 +6,10 @@ import importlib.util
 import shlex
 import platform
 
+dir_repos = "repositories"
+python = sys.executable
+git = os.environ.get('GIT', "git")
+
 
 def extract_arg(args, name):
     return [x for x in args if x != name], name in args
@@ -44,11 +48,44 @@ def is_installed(package):
     return spec is not None
 
 
-def prepare_enviroment():
-    dir_repos = "repositories"
+def repo_dir(name):
+    return os.path.join(dir_repos, name)
+
+
+def run_python(code, desc=None, errdesc=None):
+    return run(f'"{python}" -c "{code}"', desc, errdesc)
+
+
+def run_pip(args, desc=None):
+    return run(f'"{python}" -m pip {args} --prefer-binary', desc=f"Installing {desc}", errdesc=f"Couldn't install {desc}")
+
+
+def check_run_python(code):
+    return check_run(f'"{python}" -c "{code}"')
+
+
+def git_clone(url, dir, name, commithash=None):
+    # TODO clone into temporary dir and move if successful
+
+    if os.path.exists(dir):
+        if commithash is None:
+            return
+
+        current_hash = run(f'"{git}" -C {dir} rev-parse HEAD', None, f"Couldn't determine {name}'s hash: {commithash}").strip()
+        if current_hash == commithash:
+            return
+
+        run(f'"{git}" -C {dir} fetch', f"Fetching updates for {name}...", f"Couldn't fetch {name}")
+        run(f'"{git}" -C {dir} checkout {commithash}', f"Checking out commint for {name} with hash: {commithash}...", f"Couldn't checkout commit {commithash} for {name}")
+        return
 
-    python = sys.executable
-    git = os.environ.get('GIT', "git")
+    run(f'"{git}" clone "{url}" "{dir}"', f"Cloning {name} into {dir}...", f"Couldn't clone {name}")
+
+    if commithash is not None:
+        run(f'"{git}" -C {dir} checkout {commithash}', None, "Couldn't checkout {name}'s hash: {commithash}")
+
+
+def prepare_enviroment():
     torch_command = os.environ.get('TORCH_COMMAND', "pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 --extra-index-url https://download.pytorch.org/whl/cu113")
     requirements_file = os.environ.get('REQS_FILE', "requirements_versions.txt")
     commandline_args = os.environ.get('COMMANDLINE_ARGS', "")
@@ -68,38 +105,6 @@ def prepare_enviroment():
     xformers = '--xformers' in args
     deepdanbooru = '--deepdanbooru' in args
 
-    def repo_dir(name):
-        return os.path.join(dir_repos, name)
-
-    def run_python(code, desc=None, errdesc=None):
-        return run(f'"{python}" -c "{code}"', desc, errdesc)
-
-    def run_pip(args, desc=None):
-        return run(f'"{python}" -m pip {args} --prefer-binary', desc=f"Installing {desc}", errdesc=f"Couldn't install {desc}")
-
-    def check_run_python(code):
-        return check_run(f'"{python}" -c "{code}"')
-
-    def git_clone(url, dir, name, commithash=None):
-        # TODO clone into temporary dir and move if successful
-
-        if os.path.exists(dir):
-            if commithash is None:
-                return
-
-            current_hash = run(f'"{git}" -C {dir} rev-parse HEAD', None, f"Couldn't determine {name}'s hash: {commithash}").strip()
-            if current_hash == commithash:
-                return
-
-            run(f'"{git}" -C {dir} fetch', f"Fetching updates for {name}...", f"Couldn't fetch {name}")
-            run(f'"{git}" -C {dir} checkout {commithash}', f"Checking out commint for {name} with hash: {commithash}...", f"Couldn't checkout commit {commithash} for {name}")
-            return
-
-        run(f'"{git}" clone "{url}" "{dir}"', f"Cloning {name} into {dir}...", f"Couldn't clone {name}")
-
-        if commithash is not None:
-            run(f'"{git}" -C {dir} checkout {commithash}', None, "Couldn't checkout {name}'s hash: {commithash}")
-
     try:
         commit = run(f"{git} rev-parse HEAD").strip()
     except Exception:
-- 
cgit v1.2.3


From 875ddfeecfaffad9eee24813301637cba310337d Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 9 Oct 2022 17:58:43 +0300
Subject: added guard for torch.load to prevent loading pickles with unknown
 content

---
 modules/paths.py  |  1 +
 modules/safe.py   | 89 +++++++++++++++++++++++++++++++++++++++++++++++++++++++
 modules/shared.py |  1 +
 3 files changed, 91 insertions(+)
 create mode 100644 modules/safe.py

diff --git a/modules/paths.py b/modules/paths.py
index 0519caa0..1e7a2fbc 100644
--- a/modules/paths.py
+++ b/modules/paths.py
@@ -1,6 +1,7 @@
 import argparse
 import os
 import sys
+import modules.safe
 
 script_path = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
 models_path = os.path.join(script_path, "models")
diff --git a/modules/safe.py b/modules/safe.py
new file mode 100644
index 00000000..2d2c1371
--- /dev/null
+++ b/modules/safe.py
@@ -0,0 +1,89 @@
+# this code is adapted from the script contributed by anon from /h/
+
+import io
+import pickle
+import collections
+import sys
+import traceback
+
+import torch
+import numpy
+import _codecs
+import zipfile
+
+
+def encode(*args):
+    out = _codecs.encode(*args)
+    return out
+
+
+class RestrictedUnpickler(pickle.Unpickler):
+    def persistent_load(self, saved_id):
+        assert saved_id[0] == 'storage'
+        return torch.storage._TypedStorage()
+
+    def find_class(self, module, name):
+        if module == 'collections' and name == 'OrderedDict':
+            return getattr(collections, name)
+        if module == 'torch._utils' and name in ['_rebuild_tensor_v2', '_rebuild_parameter']:
+            return getattr(torch._utils, name)
+        if module == 'torch' and name in ['FloatStorage', 'HalfStorage', 'IntStorage', 'LongStorage']:
+            return getattr(torch, name)
+        if module == 'torch.nn.modules.container' and name in ['ParameterDict']:
+            return getattr(torch.nn.modules.container, name)
+        if module == 'numpy.core.multiarray' and name == 'scalar':
+            return numpy.core.multiarray.scalar
+        if module == 'numpy' and name == 'dtype':
+            return numpy.dtype
+        if module == '_codecs' and name == 'encode':
+            return encode
+        if module == "pytorch_lightning.callbacks" and name == 'model_checkpoint':
+            import pytorch_lightning.callbacks
+            return pytorch_lightning.callbacks.model_checkpoint
+        if module == "pytorch_lightning.callbacks.model_checkpoint" and name == 'ModelCheckpoint':
+            import pytorch_lightning.callbacks.model_checkpoint
+            return pytorch_lightning.callbacks.model_checkpoint.ModelCheckpoint
+        if module == "__builtin__" and name == 'set':
+            return set
+
+        # Forbid everything else.
+        raise pickle.UnpicklingError(f"global '{module}/{name}' is forbidden")
+
+
+def check_pt(filename):
+    try:
+
+        # new pytorch format is a zip file
+        with zipfile.ZipFile(filename) as z:
+            with z.open('archive/data.pkl') as file:
+                unpickler = RestrictedUnpickler(file)
+                unpickler.load()
+
+    except zipfile.BadZipfile:
+
+        # if it's not a zip file, it's an olf pytorch format, with five objects written to pickle
+        with open(filename, "rb") as file:
+            unpickler = RestrictedUnpickler(file)
+            for i in range(5):
+                unpickler.load()
+
+
+def load(filename, *args, **kwargs):
+    from modules import shared
+
+    try:
+        if not shared.cmd_opts.disable_safe_unpickle:
+            check_pt(filename)
+
+    except Exception:
+        print(f"Error verifying pickled file from {filename}:", file=sys.stderr)
+        print(traceback.format_exc(), file=sys.stderr)
+        print(f"\nThe file may be malicious, so the program is not going to read it.", file=sys.stderr)
+        print(f"You can skip this check with --disable-safe-unpickle commandline argument.", file=sys.stderr)
+        return None
+
+    return unsafe_torch_load(filename, *args, **kwargs)
+
+
+unsafe_torch_load = torch.load
+torch.load = load
diff --git a/modules/shared.py b/modules/shared.py
index 6ecc2503..3d7f08e1 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -65,6 +65,7 @@ parser.add_argument("--autolaunch", action='store_true', help="open the webui UR
 parser.add_argument("--use-textbox-seed", action='store_true', help="use textbox for seeds in UI (no up/down, but possible to input long seeds)", default=False)
 parser.add_argument("--disable-console-progressbars", action='store_true', help="do not output progressbars to console", default=False)
 parser.add_argument("--enable-console-prompts", action='store_true', help="print prompts to console when generating with txt2img and img2img", default=False)
+parser.add_argument("--disable-safe-unpickle", action='store_true', help="disable checking pytorch models for malicious code", default=False)
 
 
 cmd_opts = parser.parse_args()
-- 
cgit v1.2.3


From d3cd46b0388918128af203fda37fa63461c46611 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sun, 9 Oct 2022 16:19:33 +0100
Subject: Update lightbox to change displayed image as soon as generation is
 complete (#1933)

* add updateOnBackgroundChange
* typo fixes.
* reindent to 4 spaces
---
 javascript/imageviewer.js | 174 ++++++++++++++++++++++++++--------------------
 1 file changed, 99 insertions(+), 75 deletions(-)

diff --git a/javascript/imageviewer.js b/javascript/imageviewer.js
index 6a00c0da..65a33dd7 100644
--- a/javascript/imageviewer.js
+++ b/javascript/imageviewer.js
@@ -1,72 +1,97 @@
 // A full size 'lightbox' preview modal shown when left clicking on gallery previews
-
 function closeModal() {
-  gradioApp().getElementById("lightboxModal").style.display = "none";
+    gradioApp().getElementById("lightboxModal").style.display = "none";
 }
 
 function showModal(event) {
-  const source = event.target || event.srcElement;
-  const modalImage = gradioApp().getElementById("modalImage")
-  const lb = gradioApp().getElementById("lightboxModal")
-  modalImage.src = source.src
-  if (modalImage.style.display === 'none') {
-    lb.style.setProperty('background-image', 'url(' + source.src + ')');
-  }
-  lb.style.display = "block";
-  lb.focus()
-  event.stopPropagation()
+    const source = event.target || event.srcElement;
+    const modalImage = gradioApp().getElementById("modalImage")
+    const lb = gradioApp().getElementById("lightboxModal")
+    modalImage.src = source.src
+    if (modalImage.style.display === 'none') {
+        lb.style.setProperty('background-image', 'url(' + source.src + ')');
+    }
+    lb.style.display = "block";
+    lb.focus()
+    event.stopPropagation()
 }
 
 function negmod(n, m) {
-  return ((n % m) + m) % m;
+    return ((n % m) + m) % m;
 }
 
-function modalImageSwitch(offset){
-  var allgalleryButtons = gradioApp().querySelectorAll(".gallery-item.transition-all")
-  var galleryButtons = []
-  allgalleryButtons.forEach(function(elem){
-    if(elem.parentElement.offsetParent){
-        galleryButtons.push(elem);
+function updateOnBackgroundChange() {
+    const modalImage = gradioApp().getElementById("modalImage")
+    if (modalImage && modalImage.offsetParent) {
+        let allcurrentButtons = gradioApp().querySelectorAll(".gallery-item.transition-all.\\!ring-2")
+        let currentButton = null
+        allcurrentButtons.forEach(function(elem) {
+            if (elem.parentElement.offsetParent) {
+                currentButton = elem;
+            }
+        })
+
+        if (modalImage.src != currentButton.children[0].src) {
+            modalImage.src = currentButton.children[0].src;
+            if (modalImage.style.display === 'none') {
+                modal.style.setProperty('background-image', `url(${modalImage.src})`)
+            }
+        }
     }
-  })
-
-  if(galleryButtons.length>1){
-      var allcurrentButtons = gradioApp().querySelectorAll(".gallery-item.transition-all.\\!ring-2")
-      var currentButton = null
-      allcurrentButtons.forEach(function(elem){
-        if(elem.parentElement.offsetParent){
-            currentButton = elem;
+}
+
+function modalImageSwitch(offset) {
+    var allgalleryButtons = gradioApp().querySelectorAll(".gallery-item.transition-all")
+    var galleryButtons = []
+    allgalleryButtons.forEach(function(elem) {
+        if (elem.parentElement.offsetParent) {
+            galleryButtons.push(elem);
         }
-      })
-
-      var result = -1
-      galleryButtons.forEach(function(v, i){ if(v==currentButton) { result = i } })
-
-      if(result != -1){
-        nextButton = galleryButtons[negmod((result+offset),galleryButtons.length)]
-        nextButton.click()
-        const modalImage = gradioApp().getElementById("modalImage");
-        const modal = gradioApp().getElementById("lightboxModal");
-        modalImage.src = nextButton.children[0].src;
-        if (modalImage.style.display === 'none') {
-            modal.style.setProperty('background-image', `url(${modalImage.src})`)
+    })
+
+    if (galleryButtons.length > 1) {
+        var allcurrentButtons = gradioApp().querySelectorAll(".gallery-item.transition-all.\\!ring-2")
+        var currentButton = null
+        allcurrentButtons.forEach(function(elem) {
+            if (elem.parentElement.offsetParent) {
+                currentButton = elem;
+            }
+        })
+
+        var result = -1
+        galleryButtons.forEach(function(v, i) {
+            if (v == currentButton) {
+                result = i
+            }
+        })
+
+        if (result != -1) {
+            nextButton = galleryButtons[negmod((result + offset), galleryButtons.length)]
+            nextButton.click()
+            const modalImage = gradioApp().getElementById("modalImage");
+            const modal = gradioApp().getElementById("lightboxModal");
+            modalImage.src = nextButton.children[0].src;
+            if (modalImage.style.display === 'none') {
+                modal.style.setProperty('background-image', `url(${modalImage.src})`)
+            }
+            setTimeout(function() {
+                modal.focus()
+            }, 10)
         }
-        setTimeout( function(){modal.focus()},10)
-      }
-  }
+    }
 }
 
-function modalNextImage(event){
-  modalImageSwitch(1)
-  event.stopPropagation()
+function modalNextImage(event) {
+    modalImageSwitch(1)
+    event.stopPropagation()
 }
 
-function modalPrevImage(event){
-  modalImageSwitch(-1)  
-  event.stopPropagation()
+function modalPrevImage(event) {
+    modalImageSwitch(-1)
+    event.stopPropagation()
 }
 
-function modalKeyHandler(event){
+function modalKeyHandler(event) {
     switch (event.key) {
         case "ArrowLeft":
             modalPrevImage(event)
@@ -80,24 +105,22 @@ function modalKeyHandler(event){
     }
 }
 
-function showGalleryImage(){
+function showGalleryImage() {
     setTimeout(function() {
         fullImg_preview = gradioApp().querySelectorAll('img.w-full.object-contain')
-        
-        if(fullImg_preview != null){
+
+        if (fullImg_preview != null) {
             fullImg_preview.forEach(function function_name(e) {
                 if (e.dataset.modded)
                     return;
                 e.dataset.modded = true;
                 if(e && e.parentElement.tagName == 'DIV'){
-
                     e.style.cursor='pointer'
-
                     e.addEventListener('click', function (evt) {
                         if(!opts.js_modal_lightbox) return;
                         modalZoomSet(gradioApp().getElementById('modalImage'), opts.js_modal_lightbox_initially_zoomed)
                         showModal(evt)
-                    },true);
+                    }, true);
                 }
             });
         }
@@ -105,21 +128,21 @@ function showGalleryImage(){
     }, 100);
 }
 
-function modalZoomSet(modalImage, enable){
-    if( enable ){
+function modalZoomSet(modalImage, enable) {
+    if (enable) {
         modalImage.classList.add('modalImageFullscreen');
-    } else{
+    } else {
         modalImage.classList.remove('modalImageFullscreen');
     }
 }
 
-function modalZoomToggle(event){
+function modalZoomToggle(event) {
     modalImage = gradioApp().getElementById("modalImage");
     modalZoomSet(modalImage, !modalImage.classList.contains('modalImageFullscreen'))
     event.stopPropagation()
 }
 
-function modalTileImageToggle(event){
+function modalTileImageToggle(event) {
     const modalImage = gradioApp().getElementById("modalImage");
     const modal = gradioApp().getElementById("lightboxModal");
     const isTiling = modalImage.style.display === 'none';
@@ -134,17 +157,18 @@ function modalTileImageToggle(event){
     event.stopPropagation()
 }
 
-function galleryImageHandler(e){
-    if(e && e.parentElement.tagName == 'BUTTON'){
+function galleryImageHandler(e) {
+    if (e && e.parentElement.tagName == 'BUTTON') {
         e.onclick = showGalleryImage;
     }
 }
 
-onUiUpdate(function(){
+onUiUpdate(function() {
     fullImg_preview = gradioApp().querySelectorAll('img.w-full')
-        if(fullImg_preview != null){
-	    fullImg_preview.forEach(galleryImageHandler);
+    if (fullImg_preview != null) {
+        fullImg_preview.forEach(galleryImageHandler);
     }
+    updateOnBackgroundChange();
 })
 
 document.addEventListener("DOMContentLoaded", function() {
@@ -152,13 +176,13 @@ document.addEventListener("DOMContentLoaded", function() {
     const modal = document.createElement('div')
     modal.onclick = closeModal;
     modal.id = "lightboxModal";
-    modal.tabIndex=0
+    modal.tabIndex = 0
     modal.addEventListener('keydown', modalKeyHandler, true)
 
     const modalControls = document.createElement('div')
     modalControls.className = 'modalControls gradio-container';
     modal.append(modalControls);
-    
+
     const modalZoom = document.createElement('span')
     modalZoom.className = 'modalZoom cursor';
     modalZoom.innerHTML = '&#10529;'
@@ -183,30 +207,30 @@ document.addEventListener("DOMContentLoaded", function() {
     const modalImage = document.createElement('img')
     modalImage.id = 'modalImage';
     modalImage.onclick = closeModal;
-    modalImage.tabIndex=0
+    modalImage.tabIndex = 0
     modalImage.addEventListener('keydown', modalKeyHandler, true)
     modal.appendChild(modalImage)
 
     const modalPrev = document.createElement('a')
     modalPrev.className = 'modalPrev';
     modalPrev.innerHTML = '&#10094;'
-    modalPrev.tabIndex=0
-    modalPrev.addEventListener('click',modalPrevImage,true);
+    modalPrev.tabIndex = 0
+    modalPrev.addEventListener('click', modalPrevImage, true);
     modalPrev.addEventListener('keydown', modalKeyHandler, true)
     modal.appendChild(modalPrev)
 
     const modalNext = document.createElement('a')
     modalNext.className = 'modalNext';
     modalNext.innerHTML = '&#10095;'
-    modalNext.tabIndex=0
-    modalNext.addEventListener('click',modalNextImage,true);
+    modalNext.tabIndex = 0
+    modalNext.addEventListener('click', modalNextImage, true);
     modalNext.addEventListener('keydown', modalKeyHandler, true)
 
     modal.appendChild(modalNext)
 
 
     gradioApp().getRootNode().appendChild(modal)
-    
+
     document.body.appendChild(modalFragment);
-	
+
 });
-- 
cgit v1.2.3


From 9ecea0a8d6bdc434755e11128487fd62f1ff130f Mon Sep 17 00:00:00 2001
From: Artem Zagidulin <p0chta@yandex.ru>
Date: Sun, 9 Oct 2022 16:14:56 +0300
Subject: fix missing png info when Extras Batch Process

---
 modules/extras.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/extras.py b/modules/extras.py
index 39dd3806..41e8612c 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -29,7 +29,7 @@ def run_extras(extras_mode, image, image_folder, gfpgan_visibility, codeformer_v
     if extras_mode == 1:
         #convert file to pillow image
         for img in image_folder:
-            image = Image.fromarray(np.array(Image.open(img)))
+            image = Image.open(img)
             imageArr.append(image)
             imageNameArr.append(os.path.splitext(img.orig_name)[0])
     else:
-- 
cgit v1.2.3


From a2d70f25bf51264d8d68f4f36937b390f79334a7 Mon Sep 17 00:00:00 2001
From: supersteve3d <39339941+supersteve3d@users.noreply.github.com>
Date: Sun, 9 Oct 2022 23:40:18 +0800
Subject: Add files via upload

Updated txt2img screenshot (UI as of Oct 9th) for github webui / README.md
---
 txt2img_Screenshot.png | Bin 539132 -> 337094 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)

diff --git a/txt2img_Screenshot.png b/txt2img_Screenshot.png
index fedd538e..6e2759a4 100644
Binary files a/txt2img_Screenshot.png and b/txt2img_Screenshot.png differ
-- 
cgit v1.2.3


From 45bf9a6264b3507473e02cc3f9aa36559f24aca2 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 9 Oct 2022 18:58:55 +0300
Subject: added clip skip to XY plot

---
 scripts/xy_grid.py | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index c89ca1a9..7b0d9083 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -83,6 +83,10 @@ def apply_hypernetwork(p, x, xs):
     hypernetwork.load_hypernetwork(x)
 
 
+def apply_clip_skip(p, x, xs):
+    opts.data["CLIP_ignore_last_layers"] = x
+
+
 def format_value_add_label(p, opt, x):
     if type(x) == float:
         x = round(x, 8)
@@ -134,6 +138,7 @@ axis_options = [
     AxisOption("Sigma max", float, apply_field("s_tmax"), format_value_add_label),
     AxisOption("Sigma noise", float, apply_field("s_noise"), format_value_add_label),
     AxisOption("Eta", float, apply_field("eta"), format_value_add_label),
+    AxisOption("Clip skip", int, apply_clip_skip, format_value_add_label),
     AxisOptionImg2Img("Denoising", float, apply_field("denoising_strength"), format_value_add_label),  # as it is now all AxisOptionImg2Img items must go after AxisOption ones
 ]
 
@@ -201,6 +206,7 @@ class Script(scripts.Script):
             modules.processing.fix_seed(p)
 
         p.batch_size = 1
+        CLIP_ignore_last_layers = opts.CLIP_ignore_last_layers
 
         def process_axis(opt, vals):
             if opt.label == 'Nothing':
@@ -321,4 +327,6 @@ class Script(scripts.Script):
 
         hypernetwork.load_hypernetwork(opts.sd_hypernetwork)
 
+        opts.data["CLIP_ignore_last_layers"] = CLIP_ignore_last_layers
+
         return processed
-- 
cgit v1.2.3


From 6c383d2e82045fc4475d665f83bdeeac8fd844d9 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 9 Oct 2022 22:24:07 +0300
Subject: show model selection setting on top of page

---
 modules/shared.py |  5 +++--
 modules/ui.py     | 54 +++++++++++++++++++++++++++++++++++++++++++++---------
 style.css         |  9 +++++++++
 3 files changed, 57 insertions(+), 11 deletions(-)

diff --git a/modules/shared.py b/modules/shared.py
index 3d7f08e1..270fa402 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -131,13 +131,14 @@ def realesrgan_models_names():
 
 
 class OptionInfo:
-    def __init__(self, default=None, label="", component=None, component_args=None, onchange=None):
+    def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, show_on_main_page=False):
         self.default = default
         self.label = label
         self.component = component
         self.component_args = component_args
         self.onchange = onchange
         self.section = None
+        self.show_on_main_page = show_on_main_page
 
 
 def options_section(section_identifier, options_dict):
@@ -214,7 +215,7 @@ options_templates.update(options_section(('system', "System"), {
 }))
 
 options_templates.update(options_section(('sd', "Stable Diffusion"), {
-    "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}),
+    "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, show_on_main_page=True),
     "sd_hypernetwork": OptionInfo("None", "Stable Diffusion finetune hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}),
     "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."),
     "save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"),
diff --git a/modules/ui.py b/modules/ui.py
index dad509f3..2231a8ed 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1175,10 +1175,13 @@ Requested path was: {f}
         changed = 0
 
         for key, value, comp in zip(opts.data_labels.keys(), args, components):
-            if not opts.same_type(value, opts.data_labels[key].default):
-                return f"Bad value for setting {key}: {value}; expecting {type(opts.data_labels[key].default).__name__}"
+            if comp != dummy_component and not opts.same_type(value, opts.data_labels[key].default):
+                return f"Bad value for setting {key}: {value}; expecting {type(opts.data_labels[key].default).__name__}", opts.dumpjson()
 
         for key, value, comp in zip(opts.data_labels.keys(), args, components):
+            if comp == dummy_component:
+                continue
+
             comp_args = opts.data_labels[key].component_args
             if comp_args and isinstance(comp_args, dict) and comp_args.get('visible') is False:
                 continue
@@ -1196,6 +1199,21 @@ Requested path was: {f}
 
         return f'{changed} settings changed.', opts.dumpjson()
 
+    def run_settings_single(value, key):
+        if not opts.same_type(value, opts.data_labels[key].default):
+            return gr.update(visible=True), opts.dumpjson()
+
+        oldval = opts.data.get(key, None)
+        opts.data[key] = value
+
+        if oldval != value:
+            if opts.data_labels[key].onchange is not None:
+                opts.data_labels[key].onchange()
+
+        opts.save(shared.config_filename)
+
+        return gr.update(value=value), opts.dumpjson()
+
     with gr.Blocks(analytics_enabled=False) as settings_interface:
         settings_submit = gr.Button(value="Apply settings", variant='primary')
         result = gr.HTML()
@@ -1203,6 +1221,8 @@ Requested path was: {f}
         settings_cols = 3
         items_per_col = int(len(opts.data_labels) * 0.9 / settings_cols)
 
+        quicksettings_list = []
+
         cols_displayed = 0
         items_displayed = 0
         previous_section = None
@@ -1225,10 +1245,14 @@ Requested path was: {f}
 
                     gr.HTML(elem_id="settings_header_text_{}".format(item.section[0]), value='<h1 class="gr-button-lg">{}</h1>'.format(item.section[1]))
 
-                component = create_setting_component(k)
-                component_dict[k] = component
-                components.append(component)
-                items_displayed += 1
+                if item.show_on_main_page:
+                    quicksettings_list.append((i, k, item))
+                    components.append(dummy_component)
+                else:
+                    component = create_setting_component(k)
+                    component_dict[k] = component
+                    components.append(component)
+                    items_displayed += 1
 
         request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications")
         request_notifications.click(
@@ -1242,7 +1266,6 @@ Requested path was: {f}
             reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary')
             restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary')
 
-
         def reload_scripts():
             modules.scripts.reload_script_body_only()
 
@@ -1289,7 +1312,11 @@ Requested path was: {f}
         css += css_hide_progressbar
 
     with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion") as demo:
-        
+        with gr.Row(elem_id="quicksettings"):
+            for i, k, item in quicksettings_list:
+                component = create_setting_component(k)
+                component_dict[k] = component
+
         settings_interface.gradio_ref = demo
         
         with gr.Tabs() as tabs:
@@ -1306,7 +1333,16 @@ Requested path was: {f}
             inputs=components,
             outputs=[result, text_settings],
         )
-        
+
+        for i, k, item in quicksettings_list:
+            component = component_dict[k]
+
+            component.change(
+                fn=lambda value, k=k: run_settings_single(value, key=k),
+                inputs=[component],
+                outputs=[component, text_settings],
+            )
+
         def modelmerger(*args):
             try:
                 results = modules.extras.run_modelmerger(*args)
diff --git a/style.css b/style.css
index 101d2052..28160bdf 100644
--- a/style.css
+++ b/style.css
@@ -453,3 +453,12 @@ input[type="range"]{
 .context-menu-items a:hover{
     background: #a55000;
 }
+
+#quicksettings > div{
+    border: none;
+}
+
+#quicksettings > div > div{
+    max-width: 32em;
+    padding: 0;
+}
-- 
cgit v1.2.3


From e59c66c0088422b27f64b401ef42c242f836725a Mon Sep 17 00:00:00 2001
From: Fampai <unknown>
Date: Sat, 8 Oct 2022 16:32:05 -0400
Subject: Optimized code for Ignoring last CLIP layers

---
 modules/sd_hijack.py | 12 ++++--------
 1 file changed, 4 insertions(+), 8 deletions(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index f12a9696..4a2d2153 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -282,14 +282,10 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
         remade_batch_tokens_of_same_length = [x + [self.wrapped.tokenizer.eos_token_id] * (target_token_count - len(x)) for x in remade_batch_tokens]
         tokens = torch.asarray(remade_batch_tokens_of_same_length).to(device)
 
-        tmp = -opts.CLIP_ignore_last_layers
-        if (opts.CLIP_ignore_last_layers == 0):
-            outputs = self.wrapped.transformer(input_ids=tokens, position_ids=position_ids)
-            z = outputs.last_hidden_state
-        else:
-            outputs = self.wrapped.transformer(input_ids=tokens, position_ids=position_ids, output_hidden_states=tmp)
-            z = outputs.hidden_states[tmp]
-            z = self.wrapped.transformer.text_model.final_layer_norm(z)
+        tmp = -opts.CLIP_stop_at_last_layers
+        outputs = self.wrapped.transformer(input_ids=tokens, position_ids=position_ids, output_hidden_states=tmp)
+        z = outputs.hidden_states[tmp]
+        z = self.wrapped.transformer.text_model.final_layer_norm(z)
 
         # restoring original mean is likely not correct, but it seems to work well to prevent artifacts that happen otherwise
         batch_multipliers_of_same_length = [x + [1.0] * (target_token_count - len(x)) for x in batch_multipliers]
-- 
cgit v1.2.3


From a14f7bf113a2af9e06a1c4d06c2efa244f9c5730 Mon Sep 17 00:00:00 2001
From: Fampai <unknown>
Date: Sat, 8 Oct 2022 16:33:06 -0400
Subject: Corrected CLIP Layer Ignore description and updated its range to the
 max possible

---
 modules/shared.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/shared.py b/modules/shared.py
index 270fa402..1995a99a 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -225,7 +225,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "use_old_emphasis_implementation": OptionInfo(False, "Use old emphasis implementation. Can be useful to reproduce old seeds."),
     "enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"),
     "filter_nsfw": OptionInfo(False, "Filter NSFW content"),
-    'CLIP_ignore_last_layers': OptionInfo(0, "Ignore last layers of CLIP model", gr.Slider, {"minimum": 0, "maximum": 5, "step": 1}),
+    'CLIP_stop_at_last_layers': OptionInfo(1, "Stop At last layers of CLIP model", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}),
     "random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}),
 }))
 
-- 
cgit v1.2.3


From ec2bd9be75865c9f3a8c898163ab381688c03b6e Mon Sep 17 00:00:00 2001
From: Fampai <unknown>
Date: Sat, 8 Oct 2022 17:28:42 -0400
Subject: Fix issues with CLIP ignore option name change

---
 modules/processing.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index 04aed989..92a105a2 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -129,7 +129,7 @@ class Processed:
         self.index_of_first_image = index_of_first_image
         self.styles = p.styles
         self.job_timestamp = state.job_timestamp
-        self.clip_skip = opts.CLIP_ignore_last_layers
+        self.clip_skip = opts.CLIP_stop_at_last_layers
 
         self.eta = p.eta
         self.ddim_discretize = p.ddim_discretize
@@ -274,7 +274,7 @@ def fix_seed(p):
 def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration=0, position_in_batch=0):
     index = position_in_batch + iteration * p.batch_size
 
-    clip_skip = getattr(p, 'clip_skip', opts.CLIP_ignore_last_layers)
+    clip_skip = getattr(p, 'clip_skip', opts.CLIP_stop_at_last_layers)
 
     generation_params = {
         "Steps": p.steps,
-- 
cgit v1.2.3


From ad3ae441081155dcd4fde805279e5082ca264695 Mon Sep 17 00:00:00 2001
From: Fampai <unknown>
Date: Sun, 9 Oct 2022 04:32:40 -0400
Subject: Updated code for legibility

---
 modules/sd_hijack.py | 7 +++++--
 1 file changed, 5 insertions(+), 2 deletions(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 4a2d2153..7793d25b 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -284,8 +284,11 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
 
         tmp = -opts.CLIP_stop_at_last_layers
         outputs = self.wrapped.transformer(input_ids=tokens, position_ids=position_ids, output_hidden_states=tmp)
-        z = outputs.hidden_states[tmp]
-        z = self.wrapped.transformer.text_model.final_layer_norm(z)
+        if tmp < -1:
+            z = outputs.hidden_states[tmp]
+            z = self.wrapped.transformer.text_model.final_layer_norm(z)
+        else:
+            z = outputs.last_hidden_state
 
         # restoring original mean is likely not correct, but it seems to work well to prevent artifacts that happen otherwise
         batch_multipliers_of_same_length = [x + [1.0] * (target_token_count - len(x)) for x in batch_multipliers]
-- 
cgit v1.2.3


From 1824e9ee3ab4f94aee8908a62ea2569a01aeb3d7 Mon Sep 17 00:00:00 2001
From: Fampai <unknown>
Date: Sun, 9 Oct 2022 14:15:43 -0400
Subject: Removed unnecessary tmp variable

---
 modules/sd_hijack.py | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 7793d25b..437acce4 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -282,10 +282,9 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
         remade_batch_tokens_of_same_length = [x + [self.wrapped.tokenizer.eos_token_id] * (target_token_count - len(x)) for x in remade_batch_tokens]
         tokens = torch.asarray(remade_batch_tokens_of_same_length).to(device)
 
-        tmp = -opts.CLIP_stop_at_last_layers
-        outputs = self.wrapped.transformer(input_ids=tokens, position_ids=position_ids, output_hidden_states=tmp)
-        if tmp < -1:
-            z = outputs.hidden_states[tmp]
+        outputs = self.wrapped.transformer(input_ids=tokens, position_ids=position_ids, output_hidden_states=-opts.CLIP_stop_at_last_layers)
+        if opts.CLIP_stop_at_last_layers > 1:
+            z = outputs.hidden_states[-opts.CLIP_stop_at_last_layers]
             z = self.wrapped.transformer.text_model.final_layer_norm(z)
         else:
             z = outputs.last_hidden_state
-- 
cgit v1.2.3


From 84ddd44113b36062e8ba6cb2e5db0fce4f48efb8 Mon Sep 17 00:00:00 2001
From: Fampai <unknown>
Date: Sun, 9 Oct 2022 14:57:17 -0400
Subject: Clip skip variable name change breaks x/y plot script. This fixes
 that

---
 scripts/xy_grid.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 7b0d9083..771eb8e4 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -84,7 +84,7 @@ def apply_hypernetwork(p, x, xs):
 
 
 def apply_clip_skip(p, x, xs):
-    opts.data["CLIP_ignore_last_layers"] = x
+    opts.data["CLIP_stop_at_last_layers"] = x
 
 
 def format_value_add_label(p, opt, x):
@@ -206,7 +206,7 @@ class Script(scripts.Script):
             modules.processing.fix_seed(p)
 
         p.batch_size = 1
-        CLIP_ignore_last_layers = opts.CLIP_ignore_last_layers
+        CLIP_stop_at_last_layers = opts.CLIP_stop_at_last_layers
 
         def process_axis(opt, vals):
             if opt.label == 'Nothing':
@@ -327,6 +327,6 @@ class Script(scripts.Script):
 
         hypernetwork.load_hypernetwork(opts.sd_hypernetwork)
 
-        opts.data["CLIP_ignore_last_layers"] = CLIP_ignore_last_layers
+        opts.data["CLIP_stop_at_last_layers"] = CLIP_stop_at_last_layers
 
         return processed
-- 
cgit v1.2.3


From 8d340cfb884e1dbff5b6f477f4ecf7d104279115 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 9 Oct 2022 22:30:59 +0300
Subject: do not add clip skip to parameters if it's 1 or 0

---
 modules/processing.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/processing.py b/modules/processing.py
index 92a105a2..94d2dd62 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -293,7 +293,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration
         "Seed resize from": (None if p.seed_resize_from_w == 0 or p.seed_resize_from_h == 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"),
         "Denoising strength": getattr(p, 'denoising_strength', None),
         "Eta": (None if p.sampler is None or p.sampler.eta == p.sampler.default_eta else p.sampler.eta),
-        "Clip skip": None if clip_skip==0 else clip_skip,
+        "Clip skip": None if clip_skip <= 1 else clip_skip,
     }
 
     generation_params.update(p.extra_generation_params)
-- 
cgit v1.2.3


From fa0c5eb81b72bc1e562d0b9bbd92f30945d78b4e Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sun, 9 Oct 2022 20:41:22 +0100
Subject: Add pretty image captioning functions

---
 modules/images.py | 31 +++++++++++++++++++++++++++++++
 1 file changed, 31 insertions(+)

diff --git a/modules/images.py b/modules/images.py
index 29c5ee24..10963dc7 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -428,3 +428,34 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i
             file.write(info + "\n")
 
     return fullfn
+
+def addCaptionLines(lines,image,initialx,textfont):
+    draw = ImageDraw.Draw(image)
+    hstart =initialx
+    for fill,line in lines:
+        fontSize = 32
+        font = ImageFont.truetype(textfont, fontSize)
+        _,_,w, h = draw.textbbox((0,0),line,font=font)
+        fontSize =  min( int(fontSize * ((image.size[0]-35)/w) ), 28)
+        font = ImageFont.truetype(textfont, fontSize)
+        _,_,w,h = draw.textbbox((0,0),line,font=font)
+        draw.text(((image.size[0]-w)/2,hstart), line, font=font, fill=fill)
+        hstart += h
+    return hstart
+
+def captionImge(image,prelines,postlines,background=(51, 51, 51),font=None):
+    if font is None:
+        try:
+            font = ImageFont.truetype(opts.font or Roboto, fontsize)
+            font = opts.font or Roboto
+        except Exception:
+            font = Roboto
+
+    sampleImage = image
+    background = Image.new("RGBA", (sampleImage.size[0],sampleImage.size[1]+1024), background)
+    hoffset = addCaptionLines(prelines,background,5,font)+16
+    background.paste(sampleImage,(0,hoffset))
+    hoffset = hoffset+sampleImage.size[1]+8
+    hoffset = addCaptionLines(postlines,background,hoffset,font)
+    background = background.crop((0,0,sampleImage.size[0],hoffset+8))
+    return background
-- 
cgit v1.2.3


From a65476718f08a35f527b973ef731e6f488bace5e Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 9 Oct 2022 23:38:49 +0300
Subject: add DoubleStorage to list of allowed classes for pickle

---
 modules/safe.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/safe.py b/modules/safe.py
index 2d2c1371..4d06f2a5 100644
--- a/modules/safe.py
+++ b/modules/safe.py
@@ -27,7 +27,7 @@ class RestrictedUnpickler(pickle.Unpickler):
             return getattr(collections, name)
         if module == 'torch._utils' and name in ['_rebuild_tensor_v2', '_rebuild_parameter']:
             return getattr(torch._utils, name)
-        if module == 'torch' and name in ['FloatStorage', 'HalfStorage', 'IntStorage', 'LongStorage']:
+        if module == 'torch' and name in ['FloatStorage', 'HalfStorage', 'IntStorage', 'LongStorage', 'DoubleStorage']:
             return getattr(torch, name)
         if module == 'torch.nn.modules.container' and name in ['ParameterDict']:
             return getattr(torch.nn.modules.container, name)
-- 
cgit v1.2.3


From 03694e1f9915e34cf7d9a31073f1a1a9def2909f Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sun, 9 Oct 2022 21:58:14 +0100
Subject: add embedding load and save from b64 json

---
 modules/textual_inversion/textual_inversion.py | 30 ++++++++++++++++++--------
 1 file changed, 21 insertions(+), 9 deletions(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index f6316020..1b7f8906 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -7,9 +7,11 @@ import tqdm
 import html
 import datetime
 
-from PIL import Image, PngImagePlugin
+from PIL import Image,PngImagePlugin
+from ..images import captionImge
+import numpy as np
 import base64
-from io import BytesIO
+import json
 
 from modules import shared, devices, sd_hijack, processing, sd_models
 import modules.textual_inversion.dataset
@@ -87,9 +89,9 @@ class EmbeddingDatabase:
 
             if filename.upper().endswith('.PNG'):
                 embed_image = Image.open(path)
-                if 'sd-embedding' in embed_image.text:
-                    embeddingData = base64.b64decode(embed_image.text['sd-embedding'])
-                    data = torch.load(BytesIO(embeddingData), map_location="cpu")
+                if 'sd-ti-embedding' in embed_image.text:
+                    data = embeddingFromB64(embed_image.text['sd-ti-embedding'])
+                    name = data.get('name',name)
             else:
                 data = torch.load(path, map_location="cpu")
 
@@ -258,13 +260,23 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
 
             if save_image_with_stored_embedding:
                 info = PngImagePlugin.PngInfo()
-                info.add_text("sd-embedding", base64.b64encode(open(last_saved_file,'rb').read()))
-                image.save(last_saved_image, "PNG", pnginfo=info)
+                data = torch.load(last_saved_file)
+                info.add_text("sd-ti-embedding", embeddingToB64(data))
+
+                pre_lines = [((255, 207, 175),"<{}>".format(data.get('name','???')))]
+                
+                caption_checkpoint_hash = data.get('sd_checkpoint','UNK')
+                caption_checkpoint_hash = caption_checkpoint_hash.upper() if caption_checkpoint_hash else 'UNK'
+                caption_stepcount = data.get('step',0)
+                caption_stepcount = caption_stepcount if caption_stepcount else 0
+
+                post_lines = [((240, 223, 175),"Trained against checkpoint [{}] for {} steps".format(caption_checkpoint_hash,
+                                                                                                  caption_stepcount))]
+                captioned_image = captionImge(image,prelines=pre_lines,postlines=post_lines)
+                captioned_image.save(last_saved_image, "PNG", pnginfo=info)
             else:
                 image.save(last_saved_image)
 
-
-
             last_saved_image += f", prompt: {text}"
 
         shared.state.job_no = embedding.step
-- 
cgit v1.2.3


From 969bd8256e5b4f1007d3cc653723d4ad50a92528 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sun, 9 Oct 2022 22:02:28 +0100
Subject: add alternate checkpoint hash source

---
 modules/textual_inversion/textual_inversion.py | 7 +++++--
 1 file changed, 5 insertions(+), 2 deletions(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 1b7f8906..d7813084 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -265,8 +265,11 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
 
                 pre_lines = [((255, 207, 175),"<{}>".format(data.get('name','???')))]
                 
-                caption_checkpoint_hash = data.get('sd_checkpoint','UNK')
-                caption_checkpoint_hash = caption_checkpoint_hash.upper() if caption_checkpoint_hash else 'UNK'
+                caption_checkpoint_hash = data.get('sd_checkpoint')
+                if caption_checkpoint_hash is None:
+                    caption_checkpoint_hash = data.get('hash')
+                caption_checkpoint_hash = caption_checkpoint_hash.upper() if caption_checkpoint_hash else 'UNKNOWN'
+                
                 caption_stepcount = data.get('step',0)
                 caption_stepcount = caption_stepcount if caption_stepcount else 0
 
-- 
cgit v1.2.3


From 5d12ec82d3e13f5ff4c55db2930e4e10aed7015a Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sun, 9 Oct 2022 22:05:09 +0100
Subject: add encoder and decoder classes

---
 modules/textual_inversion/textual_inversion.py | 21 +++++++++++++++++++++
 1 file changed, 21 insertions(+)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index d7813084..44d4e08b 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -16,6 +16,27 @@ import json
 from modules import shared, devices, sd_hijack, processing, sd_models
 import modules.textual_inversion.dataset
 
+class EmbeddingEncoder(json.JSONEncoder):
+    def default(self, obj):
+        if isinstance(obj, torch.Tensor):
+            return {'EMBEDDINGTENSOR':obj.cpu().detach().numpy().tolist()}
+        return json.JSONEncoder.default(self, o)
+
+class EmbeddingDecoder(json.JSONDecoder):
+    def __init__(self, *args, **kwargs):
+        json.JSONDecoder.__init__(self, object_hook=self.object_hook, *args, **kwargs)
+    def object_hook(self, d):
+        if 'EMBEDDINGTENSOR' in d:
+            return torch.from_numpy(np.array(d['EMBEDDINGTENSOR']))
+        return d
+
+def embeddingToB64(data):
+    d = json.dumps(data,cls=EmbeddingEncoder)
+    return base64.b64encode(d.encode())
+
+def EmbeddingFromB64(data):
+    d = base64.b64decode(data)
+    return json.loads(d,cls=EmbeddingDecoder)
 
 class Embedding:
     def __init__(self, vec, name, step=None):
-- 
cgit v1.2.3


From d0184b8f76ce492da699f1926f34b57cd095242e Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sun, 9 Oct 2022 22:06:12 +0100
Subject: change json tensor key name

---
 modules/textual_inversion/textual_inversion.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 44d4e08b..ae8d207d 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -19,15 +19,15 @@ import modules.textual_inversion.dataset
 class EmbeddingEncoder(json.JSONEncoder):
     def default(self, obj):
         if isinstance(obj, torch.Tensor):
-            return {'EMBEDDINGTENSOR':obj.cpu().detach().numpy().tolist()}
+            return {'TORCHTENSOR':obj.cpu().detach().numpy().tolist()}
         return json.JSONEncoder.default(self, o)
 
 class EmbeddingDecoder(json.JSONDecoder):
     def __init__(self, *args, **kwargs):
         json.JSONDecoder.__init__(self, object_hook=self.object_hook, *args, **kwargs)
     def object_hook(self, d):
-        if 'EMBEDDINGTENSOR' in d:
-            return torch.from_numpy(np.array(d['EMBEDDINGTENSOR']))
+        if 'TORCHTENSOR' in d:
+            return torch.from_numpy(np.array(d['TORCHTENSOR']))
         return d
 
 def embeddingToB64(data):
-- 
cgit v1.2.3


From 66846105103cfc282434d0dc2102910160b7a633 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sun, 9 Oct 2022 22:06:42 +0100
Subject: correct case on embeddingFromB64

---
 modules/textual_inversion/textual_inversion.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index ae8d207d..d2b95fa3 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -34,7 +34,7 @@ def embeddingToB64(data):
     d = json.dumps(data,cls=EmbeddingEncoder)
     return base64.b64encode(d.encode())
 
-def EmbeddingFromB64(data):
+def embeddingFromB64(data):
     d = base64.b64decode(data)
     return json.loads(d,cls=EmbeddingDecoder)
 
-- 
cgit v1.2.3


From 96f1e6be59316ec640cab2435fa95b3688194906 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sun, 9 Oct 2022 22:14:50 +0100
Subject: source checkpoint hash from current checkpoint

---
 modules/textual_inversion/textual_inversion.py | 6 ++----
 1 file changed, 2 insertions(+), 4 deletions(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index d2b95fa3..b16fa84e 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -286,10 +286,8 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
 
                 pre_lines = [((255, 207, 175),"<{}>".format(data.get('name','???')))]
                 
-                caption_checkpoint_hash = data.get('sd_checkpoint')
-                if caption_checkpoint_hash is None:
-                    caption_checkpoint_hash = data.get('hash')
-                caption_checkpoint_hash = caption_checkpoint_hash.upper() if caption_checkpoint_hash else 'UNKNOWN'
+                checkpoint = sd_models.select_checkpoint()
+                caption_checkpoint_hash = checkpoint.hash
                 
                 caption_stepcount = data.get('step',0)
                 caption_stepcount = caption_stepcount if caption_stepcount else 0
-- 
cgit v1.2.3


From 01fd9cf0d28d8b71a113ab1aa62accfe7f0d9c51 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sun, 9 Oct 2022 22:17:02 +0100
Subject: change source of step count

---
 modules/textual_inversion/textual_inversion.py | 10 ++--------
 1 file changed, 2 insertions(+), 8 deletions(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index b16fa84e..e4f339b8 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -285,15 +285,9 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
                 info.add_text("sd-ti-embedding", embeddingToB64(data))
 
                 pre_lines = [((255, 207, 175),"<{}>".format(data.get('name','???')))]
-                
                 checkpoint = sd_models.select_checkpoint()
-                caption_checkpoint_hash = checkpoint.hash
-                
-                caption_stepcount = data.get('step',0)
-                caption_stepcount = caption_stepcount if caption_stepcount else 0
-
-                post_lines = [((240, 223, 175),"Trained against checkpoint [{}] for {} steps".format(caption_checkpoint_hash,
-                                                                                                  caption_stepcount))]
+                post_lines = [((240, 223, 175),"Trained against checkpoint [{}] for {} steps".format(checkpoint.hash,
+                                                                                                     embedding.step))]
                 captioned_image = captionImge(image,prelines=pre_lines,postlines=post_lines)
                 captioned_image.save(last_saved_image, "PNG", pnginfo=info)
             else:
-- 
cgit v1.2.3


From 45fbd1c5fec887988ab555aac75a999d4f3aff40 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 10 Oct 2022 00:42:18 +0300
Subject: remove background for quicksettings row (for dark theme)

---
 style.css | 1 +
 1 file changed, 1 insertion(+)

diff --git a/style.css b/style.css
index 28160bdf..c0c3f2bb 100644
--- a/style.css
+++ b/style.css
@@ -456,6 +456,7 @@ input[type="range"]{
 
 #quicksettings > div{
     border: none;
+    background: none;
 }
 
 #quicksettings > div > div{
-- 
cgit v1.2.3


From 0ac3a07eecbd7b98f3a19d01dc46f02dcda3443b Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Mon, 10 Oct 2022 00:05:36 +0100
Subject: add caption image with overlay

---
 modules/images.py | 46 ++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 46 insertions(+)

diff --git a/modules/images.py b/modules/images.py
index 10963dc7..4a4fc977 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -459,3 +459,49 @@ def captionImge(image,prelines,postlines,background=(51, 51, 51),font=None):
     hoffset = addCaptionLines(postlines,background,hoffset,font)
     background = background.crop((0,0,sampleImage.size[0],hoffset+8))
     return background
+
+def captionImageOverlay(srcimage,title,footerLeft,footerMid,footerRight,textfont=None):
+    from math import cos
+
+    image = srcimage.copy()
+
+    if textfont is None:
+        try:
+            textfont = ImageFont.truetype(opts.font or Roboto, fontsize)
+            textfont = opts.font or Roboto
+        except Exception:
+            textfont = Roboto
+
+    factor = 1.5
+    gradient = Image.new('RGBA', (1,image.size[1]), color=(0,0,0,0))
+    for y in range(image.size[1]):
+        mag = 1-cos(y/image.size[1]*factor)
+        mag = max(mag,1-cos((image.size[1]-y)/image.size[1]*factor*1.1))
+        gradient.putpixel((0, y), (0,0,0,int(mag*255)))
+    image = Image.alpha_composite(image.convert('RGBA'), gradient.resize(image.size))
+
+    draw = ImageDraw.Draw(image)
+    fontSize = 32
+    font = ImageFont.truetype(textfont, fontSize)
+    padding = 10
+
+    _,_,w, h = draw.textbbox((0,0),title,font=font)
+    fontSize =  min( int(fontSize * (((image.size[0]*0.75)-(padding*4))/w) ), 72)
+    font = ImageFont.truetype(textfont, fontSize)
+    _,_,w,h = draw.textbbox((0,0),title,font=font)
+    draw.text((padding,padding), title, anchor='lt', font=font, fill=(255,255,255,230))
+
+    _,_,w, h = draw.textbbox((0,0),footerLeft,font=font)
+    fontSizeleft =  min( int(fontSize * (((image.size[0]/3)-(padding))/w) ), 72)
+    _,_,w, h = draw.textbbox((0,0),footerMid,font=font)
+    fontSizemid =  min( int(fontSize * (((image.size[0]/3)-(padding))/w) ), 72)
+    _,_,w, h = draw.textbbox((0,0),footerRight,font=font)
+    fontSizeright =  min( int(fontSize * (((image.size[0]/3)-(padding))/w) ), 72)
+
+    font = ImageFont.truetype(textfont, min(fontSizeleft,fontSizemid,fontSizeright))
+
+    draw.text((padding,image.size[1]-padding),               footerLeft, anchor='ls', font=font, fill=(255,255,255,230))
+    draw.text((image.size[0]/2,image.size[1]-padding),       footerMid, anchor='ms', font=font, fill=(255,255,255,230))
+    draw.text((image.size[0]-padding,image.size[1]-padding), footerRight, anchor='rs', font=font, fill=(255,255,255,230))
+
+    return image
-- 
cgit v1.2.3


From d6a599ef9ba18a66ae79b50f2945af5788fdda8f Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Mon, 10 Oct 2022 00:07:52 +0100
Subject: change caption method

---
 modules/textual_inversion/textual_inversion.py | 30 ++++++++++++++++++--------
 1 file changed, 21 insertions(+), 9 deletions(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index e4f339b8..21596e78 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -8,7 +8,7 @@ import html
 import datetime
 
 from PIL import Image,PngImagePlugin
-from ..images import captionImge
+from ..images import captionImageOverlay
 import numpy as np
 import base64
 import json
@@ -212,6 +212,12 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
     else:
         images_dir = None
 
+    if create_image_every > 0 and save_image_with_stored_embedding:
+        images_embeds_dir = os.path.join(log_directory, "image_embeddings")
+        os.makedirs(images_embeds_dir, exist_ok=True)
+    else:
+        images_embeds_dir = None
+        
     cond_model = shared.sd_model.cond_stage_model
 
     shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
@@ -279,19 +285,25 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
 
             shared.state.current_image = image
 
-            if save_image_with_stored_embedding:
+            if save_image_with_stored_embedding and os.path.exists(last_saved_file):
+                
+                last_saved_image_chunks = os.path.join(images_embeds_dir, f'{embedding_name}-{embedding.step}.png')
+
                 info = PngImagePlugin.PngInfo()
                 data = torch.load(last_saved_file)
                 info.add_text("sd-ti-embedding", embeddingToB64(data))
 
-                pre_lines = [((255, 207, 175),"<{}>".format(data.get('name','???')))]
+                title = "<{}>".format(data.get('name','???'))
                 checkpoint = sd_models.select_checkpoint()
-                post_lines = [((240, 223, 175),"Trained against checkpoint [{}] for {} steps".format(checkpoint.hash,
-                                                                                                     embedding.step))]
-                captioned_image = captionImge(image,prelines=pre_lines,postlines=post_lines)
-                captioned_image.save(last_saved_image, "PNG", pnginfo=info)
-            else:
-                image.save(last_saved_image)
+                footer_left = checkpoint.model_name
+                footer_mid = '[{}]'.format(checkpoint.hash)
+                footer_right = '[{}]'.format(embedding.step)
+
+                captioned_image = captionImageOverlay(image,title,footer_left,footer_mid,footer_right)
+
+                captioned_image.save(last_saved_image_chunks, "PNG", pnginfo=info)
+            
+            image.save(last_saved_image)
 
             last_saved_image += f", prompt: {text}"
 
-- 
cgit v1.2.3


From e2c2925eb4d634b186de2c76798162ec56e2f869 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Mon, 10 Oct 2022 00:12:53 +0100
Subject: remove braces from steps

---
 modules/textual_inversion/textual_inversion.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 21596e78..9a18ee5c 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -297,7 +297,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
                 checkpoint = sd_models.select_checkpoint()
                 footer_left = checkpoint.model_name
                 footer_mid = '[{}]'.format(checkpoint.hash)
-                footer_right = '[{}]'.format(embedding.step)
+                footer_right = '{}'.format(embedding.step)
 
                 captioned_image = captionImageOverlay(image,title,footer_left,footer_mid,footer_right)
 
-- 
cgit v1.2.3


From 6435691bb11c5a35703720bfd2a875f24c066f86 Mon Sep 17 00:00:00 2001
From: Justin Maier <Zipp425@gmail.com>
Date: Sun, 9 Oct 2022 19:26:52 -0600
Subject: Add "Scale to" option to Extras

---
 javascript/ui.js  |  3 ++-
 modules/extras.py | 28 +++++++++++++++++++++++-----
 modules/ui.py     | 38 +++++++++++++++++++++++++-------------
 3 files changed, 50 insertions(+), 19 deletions(-)

diff --git a/javascript/ui.js b/javascript/ui.js
index b1053201..4100944e 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -101,7 +101,8 @@ function create_tab_index_args(tabId, args){
 }
 
 function get_extras_tab_index(){
-    return create_tab_index_args('mode_extras', arguments)
+    const [,,...args] = [...arguments]
+    return [get_tab_index('mode_extras'), get_tab_index('extras_resize_mode'), ...args]
 }
 
 function create_submit_args(args){
diff --git a/modules/extras.py b/modules/extras.py
index 41e8612c..83ca7049 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -1,3 +1,4 @@
+import math
 import os
 
 import numpy as np
@@ -19,7 +20,7 @@ import gradio as gr
 cached_images = {}
 
 
-def run_extras(extras_mode, image, image_folder, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility):
+def run_extras(extras_mode, resize_mode, image, image_folder, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility):
     devices.torch_gc()
 
     imageArr = []
@@ -67,8 +68,23 @@ def run_extras(extras_mode, image, image_folder, gfpgan_visibility, codeformer_v
             info += f"CodeFormer w: {round(codeformer_weight, 2)}, CodeFormer visibility:{round(codeformer_visibility, 2)}\n"
             image = res
 
+        if resize_mode == 1:
+            upscaling_resize = max(upscaling_resize_w/image.width, upscaling_resize_h/image.height)
+            crop_info = " (crop)" if upscaling_crop else ""
+            info += f"Resize to: {upscaling_resize_w:g}x{upscaling_resize_h:g}{crop_info}\n"
+
+            def crop_upscaled_center(image, resize_w, resize_h):
+                left = int(math.ceil((image.width - resize_w) / 2))
+                right = image.width - int(math.floor((image.width - resize_w) / 2))
+                top = int(math.ceil((image.height - resize_h) / 2))
+                bottom = image.height - int(math.floor((image.height - resize_h) / 2))
+
+                image = image.crop((left, top, right, bottom))
+                return image
+
+
         if upscaling_resize != 1.0:
-            def upscale(image, scaler_index, resize):
+            def upscale(image, scaler_index, resize, mode, resize_w, resize_h, crop):
                 small = image.crop((image.width // 2, image.height // 2, image.width // 2 + 10, image.height // 2 + 10))
                 pixels = tuple(np.array(small).flatten().tolist())
                 key = (resize, scaler_index, image.width, image.height, gfpgan_visibility, codeformer_visibility, codeformer_weight) + pixels
@@ -77,15 +93,17 @@ def run_extras(extras_mode, image, image_folder, gfpgan_visibility, codeformer_v
                 if c is None:
                     upscaler = shared.sd_upscalers[scaler_index]
                     c = upscaler.scaler.upscale(image, resize, upscaler.data_path)
+                    if mode == 1 and crop:
+                        c = crop_upscaled_center(c, resize_w, resize_h)
                     cached_images[key] = c
 
                 return c
 
             info += f"Upscale: {round(upscaling_resize, 3)}, model:{shared.sd_upscalers[extras_upscaler_1].name}\n"
-            res = upscale(image, extras_upscaler_1, upscaling_resize)
+            res = upscale(image, extras_upscaler_1, upscaling_resize, resize_mode, upscaling_resize_w, upscaling_resize_h, upscaling_crop)
 
             if extras_upscaler_2 != 0 and extras_upscaler_2_visibility > 0:
-                res2 = upscale(image, extras_upscaler_2, upscaling_resize)
+                res2 = upscale(image, extras_upscaler_2, upscaling_resize, resize_mode, upscaling_resize_w, upscaling_resize_h, upscaling_crop)
                 info += f"Upscale: {round(upscaling_resize, 3)}, visibility: {round(extras_upscaler_2_visibility, 3)}, model:{shared.sd_upscalers[extras_upscaler_2].name}\n"
                 res = Image.blend(res, res2, extras_upscaler_2_visibility)
 
@@ -190,7 +208,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, interp_method, int
             theta_0[key] = theta_func(theta_0[key], theta_1[key], (float(1.0) - interp_amount))  # Need to reverse the interp_amount to match the desired mix ration in the merged checkpoint
             if save_as_half:
                 theta_0[key] = theta_0[key].half()
-    
+
     for key in theta_1.keys():
         if 'model' in key and key not in theta_0:
             theta_0[key] = theta_1[key]
diff --git a/modules/ui.py b/modules/ui.py
index 2231a8ed..4bb2892b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -101,7 +101,7 @@ def send_gradio_gallery_to_image(x):
 
 
 def save_files(js_data, images, do_make_zip, index):
-    import csv    
+    import csv
     filenames = []
     fullfns = []
 
@@ -551,7 +551,7 @@ def create_ui(wrap_gradio_gpu_call):
 
                     with gr.Row():
                         do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
-                    
+
                     with gr.Row():
                         download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
 
@@ -739,7 +739,7 @@ def create_ui(wrap_gradio_gpu_call):
 
                     with gr.Row():
                         do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
-                    
+
                     with gr.Row():
                         download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
 
@@ -903,7 +903,15 @@ def create_ui(wrap_gradio_gpu_call):
                     with gr.TabItem('Batch Process'):
                         image_batch = gr.File(label="Batch Process", file_count="multiple", interactive=True, type="file")
 
-                upscaling_resize = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Resize", value=2)
+                with gr.Tabs(elem_id="extras_resize_mode"):
+                    with gr.TabItem('Scale by'):
+                        upscaling_resize = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Resize", value=2)
+                    with gr.TabItem('Scale to'):
+                        with gr.Group():
+                            with gr.Row():
+                                upscaling_resize_w = gr.Number(label="Width", value=512)
+                                upscaling_resize_h = gr.Number(label="Height", value=512)
+                            upscaling_crop = gr.Checkbox(label='Crop to fit', value=True)
 
                 with gr.Group():
                     extras_upscaler_1 = gr.Radio(label='Upscaler 1', choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
@@ -934,6 +942,7 @@ def create_ui(wrap_gradio_gpu_call):
             fn=wrap_gradio_gpu_call(modules.extras.run_extras),
             _js="get_extras_tab_index",
             inputs=[
+                dummy_component,
                 dummy_component,
                 extras_image,
                 image_batch,
@@ -941,6 +950,9 @@ def create_ui(wrap_gradio_gpu_call):
                 codeformer_visibility,
                 codeformer_weight,
                 upscaling_resize,
+                upscaling_resize_w,
+                upscaling_resize_h,
+                upscaling_crop,
                 extras_upscaler_1,
                 extras_upscaler_2,
                 extras_upscaler_2_visibility,
@@ -951,14 +963,14 @@ def create_ui(wrap_gradio_gpu_call):
                 html_info,
             ]
         )
-     
+
         extras_send_to_img2img.click(
             fn=lambda x: image_from_url_text(x),
             _js="extract_image_from_gallery_img2img",
             inputs=[result_images],
             outputs=[init_img],
         )
-        
+
         extras_send_to_inpaint.click(
             fn=lambda x: image_from_url_text(x),
             _js="extract_image_from_gallery_img2img",
@@ -1286,7 +1298,7 @@ Requested path was: {f}
             outputs=[],
             _js='function(){restart_reload()}'
         )
-        
+
         if column is not None:
             column.__exit__()
 
@@ -1318,12 +1330,12 @@ Requested path was: {f}
                 component_dict[k] = component
 
         settings_interface.gradio_ref = demo
-        
+
         with gr.Tabs() as tabs:
             for interface, label, ifid in interfaces:
                 with gr.TabItem(label, id=ifid):
                     interface.render()
-        
+
         if os.path.exists(os.path.join(script_path, "notification.mp3")):
             audio_notification = gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False)
 
@@ -1456,10 +1468,10 @@ Requested path was: {f}
 
             if getattr(obj,'custom_script_source',None) is not None:
               key = 'customscript/' + obj.custom_script_source + '/' + key
-            
+
             if getattr(obj, 'do_not_save_to_config', False):
                 return
-            
+
             saved_value = ui_settings.get(key, None)
             if saved_value is None:
                 ui_settings[key] = getattr(obj, field)
@@ -1483,10 +1495,10 @@ Requested path was: {f}
 
         if type(x) == gr.Textbox:
             apply_field(x, 'value')
-        
+
         if type(x) == gr.Number:
             apply_field(x, 'value')
-        
+
     visit(txt2img_interface, loadsave, "txt2img")
     visit(img2img_interface, loadsave, "img2img")
     visit(extras_interface, loadsave, "extras")
-- 
cgit v1.2.3


From cc92dc1f8d73dd4d574c4c8ccab78b7fc61e440b Mon Sep 17 00:00:00 2001
From: ssysm <me@theeditorstudio.com>
Date: Sun, 9 Oct 2022 23:17:29 -0400
Subject: add vae path args

---
 modules/sd_models.py | 2 +-
 modules/shared.py    | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/modules/sd_models.py b/modules/sd_models.py
index cb3982b1..b6979432 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -147,7 +147,7 @@ def load_model_weights(model, checkpoint_info):
 
     devices.dtype = torch.float32 if shared.cmd_opts.no_half else torch.float16
 
-    vae_file = os.path.splitext(checkpoint_file)[0] + ".vae.pt"
+    vae_file = shared.cmd_opts.vae_path or os.path.splitext(checkpoint_file)[0] + ".vae.pt"
     if os.path.exists(vae_file):
         print(f"Loading VAE weights from: {vae_file}")
         vae_ckpt = torch.load(vae_file, map_location="cpu")
diff --git a/modules/shared.py b/modules/shared.py
index 2dc092d6..52ccfa6e 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -64,7 +64,7 @@ parser.add_argument("--autolaunch", action='store_true', help="open the webui UR
 parser.add_argument("--use-textbox-seed", action='store_true', help="use textbox for seeds in UI (no up/down, but possible to input long seeds)", default=False)
 parser.add_argument("--disable-console-progressbars", action='store_true', help="do not output progressbars to console", default=False)
 parser.add_argument("--enable-console-prompts", action='store_true', help="print prompts to console when generating with txt2img and img2img", default=False)
-
+parser.add_argument('--vae-path', type=str, help='Path to Variational Autoencoders model', default=None)
 
 cmd_opts = parser.parse_args()
 
-- 
cgit v1.2.3


From 1f92336be768d235c18a82acb2195b7135101ae7 Mon Sep 17 00:00:00 2001
From: JC_Array <justin318@att.net>
Date: Sun, 9 Oct 2022 23:58:18 -0500
Subject: refactored the deepbooru module to improve speed on running multiple
 interogations in a row.  Added the option to generate deepbooru tags for
 textual inversion preproccessing.

---
 modules/deepbooru.py                    | 84 +++++++++++++++++++++++++--------
 modules/textual_inversion/preprocess.py | 22 ++++++++-
 modules/ui.py                           | 52 ++++++++++++++------
 3 files changed, 122 insertions(+), 36 deletions(-)

diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index 7e3c0618..cee4a3b4 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -1,21 +1,74 @@
 import os.path
 from concurrent.futures import ProcessPoolExecutor
-from multiprocessing import get_context
+import multiprocessing
 
 
-def _load_tf_and_return_tags(pil_image, threshold):
+def get_deepbooru_tags(pil_image, threshold=0.5):
+    """
+    This method is for running only one image at a time for simple use.  Used to the img2img interrogate.
+    """
+    from modules import shared  # prevents circular reference
+    create_deepbooru_process(threshold)
+    shared.deepbooru_process_return["value"] = -1
+    shared.deepbooru_process_queue.put(pil_image)
+    while shared.deepbooru_process_return["value"] == -1:
+        time.sleep(0.2)
+    release_process()
+    return ret
+
+
+def deepbooru_process(queue, deepbooru_process_return, threshold):
+    model, tags = get_deepbooru_tags_model()
+    while True: # while process is running, keep monitoring queue for new image
+        pil_image = queue.get()
+        if pil_image == "QUIT":
+            break
+        else:
+            deepbooru_process_return["value"] = get_deepbooru_tags_from_model(model, tags, pil_image, threshold)
+
+
+def create_deepbooru_process(threshold=0.5):
+    """
+    Creates deepbooru process.  A queue is created to send images into the process.  This enables multiple images
+    to be processed in a row without reloading the model or creating a new process.  To return the data, a shared
+    dictionary is created to hold the tags created.  To wait for tags to be returned, a value of -1 is assigned
+    to the dictionary and the method adding the image to the queue should wait for this value to be updated with
+    the tags.
+    """
+    from modules import shared  # prevents circular reference
+    shared.deepbooru_process_manager = multiprocessing.Manager()
+    shared.deepbooru_process_queue = shared.deepbooru_process_manager.Queue()
+    shared.deepbooru_process_return = shared.deepbooru_process_manager.dict()
+    shared.deepbooru_process_return["value"] = -1
+    shared.deepbooru_process = multiprocessing.Process(target=deepbooru_process, args=(shared.deepbooru_process_queue, shared.deepbooru_process_return, threshold))
+    shared.deepbooru_process.start()
+
+
+def release_process():
+    """
+    Stops the deepbooru process to return used memory
+    """
+    from modules import shared  # prevents circular reference
+    shared.deepbooru_process_queue.put("QUIT")
+    shared.deepbooru_process.join()
+    shared.deepbooru_process_queue = None
+    shared.deepbooru_process = None
+    shared.deepbooru_process_return = None
+    shared.deepbooru_process_manager = None
+
+def get_deepbooru_tags_model():
     import deepdanbooru as dd
     import tensorflow as tf
     import numpy as np
-
     this_folder = os.path.dirname(__file__)
     model_path = os.path.abspath(os.path.join(this_folder, '..', 'models', 'deepbooru'))
     if not os.path.exists(os.path.join(model_path, 'project.json')):
         # there is no point importing these every time
         import zipfile
         from basicsr.utils.download_util import load_file_from_url
-        load_file_from_url(r"https://github.com/KichangKim/DeepDanbooru/releases/download/v3-20211112-sgd-e28/deepdanbooru-v3-20211112-sgd-e28.zip",
-                           model_path)
+        load_file_from_url(
+            r"https://github.com/KichangKim/DeepDanbooru/releases/download/v3-20211112-sgd-e28/deepdanbooru-v3-20211112-sgd-e28.zip",
+            model_path)
         with zipfile.ZipFile(os.path.join(model_path, "deepdanbooru-v3-20211112-sgd-e28.zip"), "r") as zip_ref:
             zip_ref.extractall(model_path)
         os.remove(os.path.join(model_path, "deepdanbooru-v3-20211112-sgd-e28.zip"))
@@ -24,7 +77,13 @@ def _load_tf_and_return_tags(pil_image, threshold):
     model = dd.project.load_model_from_project(
         model_path, compile_model=True
     )
+    return model, tags
 
+
+def get_deepbooru_tags_from_model(model, tags, pil_image, threshold=0.5):
+    import deepdanbooru as dd
+    import tensorflow as tf
+    import numpy as np
     width = model.input_shape[2]
     height = model.input_shape[1]
     image = np.array(pil_image)
@@ -57,17 +116,4 @@ def _load_tf_and_return_tags(pil_image, threshold):
 
     print('\n'.join(sorted(result_tags_print, reverse=True)))
 
-    return ', '.join(result_tags_out).replace('_', ' ').replace(':', ' ')
-
-
-def subprocess_init_no_cuda():
-    import os
-    os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
-
-
-def get_deepbooru_tags(pil_image, threshold=0.5):
-    context = get_context('spawn')
-    with ProcessPoolExecutor(initializer=subprocess_init_no_cuda, mp_context=context) as executor:
-        f = executor.submit(_load_tf_and_return_tags, pil_image, threshold, )
-        ret = f.result()  # will rethrow any exceptions
-    return ret
\ No newline at end of file
+    return ', '.join(result_tags_out).replace('_', ' ').replace(':', ' ')
\ No newline at end of file
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index f1c002a2..9f63c9a4 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -3,11 +3,14 @@ from PIL import Image, ImageOps
 import platform
 import sys
 import tqdm
+import time
 
 from modules import shared, images
+from modules.shared import opts, cmd_opts
+if cmd_opts.deepdanbooru:
+    import modules.deepbooru as deepbooru
 
-
-def preprocess(process_src, process_dst, process_flip, process_split, process_caption):
+def preprocess(process_src, process_dst, process_flip, process_split, process_caption, process_caption_deepbooru=False):
     size = 512
     src = os.path.abspath(process_src)
     dst = os.path.abspath(process_dst)
@@ -24,10 +27,21 @@ def preprocess(process_src, process_dst, process_flip, process_split, process_ca
     if process_caption:
         shared.interrogator.load()
 
+    if process_caption_deepbooru:
+        deepbooru.create_deepbooru_process()
+
     def save_pic_with_caption(image, index):
         if process_caption:
             caption = "-" + shared.interrogator.generate_caption(image)
             caption = sanitize_caption(os.path.join(dst, f"{index:05}-{subindex[0]}"), caption, ".png")
+        elif process_caption_deepbooru:
+            shared.deepbooru_process_return["value"] = -1
+            shared.deepbooru_process_queue.put(image)
+            while shared.deepbooru_process_return["value"] == -1:
+                time.sleep(0.2)
+            caption = "-" + shared.deepbooru_process_return["value"]
+            caption = sanitize_caption(os.path.join(dst, f"{index:05}-{subindex[0]}"), caption, ".png")
+            shared.deepbooru_process_return["value"] = -1
         else:
             caption = filename
             caption = os.path.splitext(caption)[0]
@@ -79,6 +93,10 @@ def preprocess(process_src, process_dst, process_flip, process_split, process_ca
     if process_caption:
         shared.interrogator.send_blip_to_ram()
 
+    if process_caption_deepbooru:
+        deepbooru.release_process()
+
+
 def sanitize_caption(base_path, original_caption, suffix):
     operating_system = platform.system().lower()
     if (operating_system == "windows"):
diff --git a/modules/ui.py b/modules/ui.py
index 2231a8ed..179e3a83 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1034,6 +1034,9 @@ def create_ui(wrap_gradio_gpu_call):
                         process_flip = gr.Checkbox(label='Create flipped copies')
                         process_split = gr.Checkbox(label='Split oversized images into two')
                         process_caption = gr.Checkbox(label='Use BLIP caption as filename')
+                        if cmd_opts.deepdanbooru:
+                            process_caption_deepbooru = gr.Checkbox(label='Use deepbooru caption as filename')
+
 
                     with gr.Row():
                         with gr.Column(scale=3):
@@ -1086,21 +1089,40 @@ def create_ui(wrap_gradio_gpu_call):
             ]
         )
 
-        run_preprocess.click(
-            fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]),
-            _js="start_training_textual_inversion",
-            inputs=[
-                process_src,
-                process_dst,
-                process_flip,
-                process_split,
-                process_caption,
-            ],
-            outputs=[
-                ti_output,
-                ti_outcome,
-            ],
-        )
+        if cmd_opts.deepdanbooru:
+            # if process_caption_deepbooru is None, it will cause an error, as a result only include it if it is enabled
+            run_preprocess.click(
+                fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]),
+                _js="start_training_textual_inversion",
+                inputs=[
+                    process_src,
+                    process_dst,
+                    process_flip,
+                    process_split,
+                    process_caption,
+                    process_caption_deepbooru,
+                ],
+                outputs=[
+                    ti_output,
+                    ti_outcome,
+                ],
+            )
+        else:
+            run_preprocess.click(
+                fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]),
+                _js="start_training_textual_inversion",
+                inputs=[
+                    process_src,
+                    process_dst,
+                    process_flip,
+                    process_split,
+                    process_caption,
+                ],
+                outputs=[
+                    ti_output,
+                    ti_outcome,
+                ],
+            )
 
         train_embedding.click(
             fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.train_embedding, extra_outputs=[gr.update()]),
-- 
cgit v1.2.3


From 8acc901ba3a252dc6ab4fabcb41644cf64d1774c Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Mon, 10 Oct 2022 00:38:55 -0400
Subject: Newer versions of PyTorch use TypedStorage instead

Pytorch 1.13 and later will rename _TypedStorage to TypedStorage, so check for TypedStorage and use _TypedStorage if it is not available. Currently this is needed so that nightly builds of PyTorch work correctly.
---
 modules/safe.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/modules/safe.py b/modules/safe.py
index 4d06f2a5..05917463 100644
--- a/modules/safe.py
+++ b/modules/safe.py
@@ -12,6 +12,10 @@ import _codecs
 import zipfile
 
 
+# PyTorch 1.13 and later have _TypedStorage renamed to TypedStorage
+TypedStorage = torch.storage.TypedStorage if hasattr(torch.storage, 'TypedStorage') else torch.storage._TypedStorage
+
+
 def encode(*args):
     out = _codecs.encode(*args)
     return out
@@ -20,7 +24,7 @@ def encode(*args):
 class RestrictedUnpickler(pickle.Unpickler):
     def persistent_load(self, saved_id):
         assert saved_id[0] == 'storage'
-        return torch.storage._TypedStorage()
+        return TypedStorage()
 
     def find_class(self, module, name):
         if module == 'collections' and name == 'OrderedDict':
-- 
cgit v1.2.3


From 8a7c07a2140c98bceca858087525d77fd0352fda Mon Sep 17 00:00:00 2001
From: yfszzx <yfszzx@gmail.com>
Date: Mon, 10 Oct 2022 15:39:39 +0800
Subject: show image history

---
 javascript/images_history.js   |  66 ++++++++++++++++++++++
 javascript/jquery-3.6.0.min.js |   2 +
 modules/images_history.py      |  90 ++++++++++++++++++++++++++++++
 modules/ui.py                  |  11 +++-
 repositorieslatent-diffusion   |   1 +
 testui.py                      | 124 +++++++++++++++++++++++++++++++++++++++++
 6 files changed, 292 insertions(+), 2 deletions(-)
 create mode 100644 javascript/images_history.js
 create mode 100644 javascript/jquery-3.6.0.min.js
 create mode 100644 modules/images_history.py
 create mode 160000 repositorieslatent-diffusion
 create mode 100644 testui.py

diff --git a/javascript/images_history.js b/javascript/images_history.js
new file mode 100644
index 00000000..f30b7eff
--- /dev/null
+++ b/javascript/images_history.js
@@ -0,0 +1,66 @@
+function init_images_history(){ 
+	if (gradioApp().getElementById('txt2img_images_history_first_page') == null) {
+		setTimeout(init_images_history, 1000)
+	} else {
+		tab_list = ["txt2img", "img2img"]
+		for (i in tab_list){
+			tab = tab_list[i]
+			gradioApp().getElementById(tab + "_images_history_first_page").click()
+			$(gradioApp().getElementById(tab + '_images_history')).addClass("images_history_gallery")
+			item = $(gradioApp().getElementById(tab + '_images_history_set_index'))
+			item.addClass("images_history_set_index")
+			item.hide()
+		}		
+	}
+	
+}
+setTimeout(init_images_history, 1000)
+onUiUpdate(function(){
+    fullImg_preview = gradioApp().querySelectorAll('#txt2img_images_history img.w-full')
+        if(fullImg_preview.length > 0){
+	    	fullImg_preview.forEach(set_history_index_from_img);
+    }
+    fullImg_preview = gradioApp().querySelectorAll('#img2img_images_history img.w-full')
+        if(fullImg_preview.length > 0){
+	    	fullImg_preview.forEach(set_history_index_from_img);
+    }
+})
+
+function set_history_gallery_index(item){
+	buttons = item.find(".gallery-item")
+	// alert(item.attr("id") + " " + buttons.length)
+	index = -1
+	i = 0
+	buttons.each(function(){
+		if($(this).hasClass("!ring-2")){ index = i }
+		i += 1
+	})
+	if (index == -1){
+		setTimeout(set_history_gallery_index, 10, item)     
+	} else {
+		item = item.find(".images_history_set_index").first()
+    	item.attr("img_index", index)
+    	item.click()
+	}
+}
+function set_history_index_from_img(e){
+    if(e && e.parentElement.tagName == 'BUTTON'){
+    	bnt = $(e).parent()
+    	if (bnt.hasClass("transform")){
+    		bnt.off("click").on("click",function(){
+    		set_history_gallery_index($(this).parents(".images_history_gallery").first())  
+     		})
+    	} else {
+    		bnt.off("mousedown").on("mousedown", function(){
+    		set_history_gallery_index($(this).parents(".images_history_gallery").first())  
+    		})
+
+		}  		
+    }
+}
+function images_history_get_current_img(is_image2image){
+	head = is_image2image?"img2img":"txt2img"
+	s =  $(gradioApp().getElementById(head + '_images_history_set_index')).attr("img_index")
+	return s
+}
+
diff --git a/javascript/jquery-3.6.0.min.js b/javascript/jquery-3.6.0.min.js
new file mode 100644
index 00000000..c4c6022f
--- /dev/null
+++ b/javascript/jquery-3.6.0.min.js
@@ -0,0 +1,2 @@
+/*! jQuery v3.6.0 | (c) OpenJS Foundation and other contributors | jquery.org/license */
+!function(e,t){"use strict";"object"==typeof module&&"object"==typeof module.exports?module.exports=e.document?t(e,!0):function(e){if(!e.document)throw new Error("jQuery requires a window with a document");return t(e)}:t(e)}("undefined"!=typeof window?window:this,function(C,e){"use strict";var t=[],r=Object.getPrototypeOf,s=t.slice,g=t.flat?function(e){return t.flat.call(e)}:function(e){return t.concat.apply([],e)},u=t.push,i=t.indexOf,n={},o=n.toString,v=n.hasOwnProperty,a=v.toString,l=a.call(Object),y={},m=function(e){return"function"==typeof e&&"number"!=typeof e.nodeType&&"function"!=typeof e.item},x=function(e){return null!=e&&e===e.window},E=C.document,c={type:!0,src:!0,nonce:!0,noModule:!0};function b(e,t,n){var r,i,o=(n=n||E).createElement("script");if(o.text=e,t)for(r in c)(i=t[r]||t.getAttribute&&t.getAttribute(r))&&o.setAttribute(r,i);n.head.appendChild(o).parentNode.removeChild(o)}function w(e){return null==e?e+"":"object"==typeof e||"function"==typeof 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diff --git a/modules/images_history.py b/modules/images_history.py
new file mode 100644
index 00000000..23d83557
--- /dev/null
+++ b/modules/images_history.py
@@ -0,0 +1,90 @@
+import os
+def get_recent_images(is_img2img, dir_name, page_index, step):
+	page_index = int(page_index)
+	f_list = os.listdir(dir_name)
+	file_list = []
+	for file in f_list:
+		if file[-4:] == ".txt":
+			continue
+		file_list.append(file)	
+	file_list = sorted(file_list, key=lambda file: -os.path.getctime(os.path.join(dir_name, file)))
+	num = 24
+	max_page_index = len(file_list) // num + 1	
+	page_index = max_page_index if page_index == -1 else page_index + step
+	page_index = 1 if page_index < 1 else page_index	
+	page_index = max_page_index if page_index > max_page_index else page_index
+	idx_frm = (page_index - 1) * num
+	file_list = file_list[idx_frm:idx_frm + num]
+	print(f"Loading history page {page_index}")	
+	return [os.path.join(dir_name, file) for file in file_list], page_index, file_list
+def first_page_click(is_img2img, dir_name):
+	return get_recent_images(is_img2img, dir_name, 1, 0)
+def end_page_click(is_img2img, dir_name):
+	return get_recent_images(is_img2img, dir_name, -1, 0)
+def prev_page_click(is_img2img, dir_name, page_index):
+	return get_recent_images(is_img2img, dir_name, page_index, -1)
+def next_page_click(is_img2img, dir_name, page_index):	
+	return get_recent_images(is_img2img, dir_name, page_index, 1)
+def page_index_change(is_img2img, dir_name, page_index):	
+	return get_recent_images(is_img2img, dir_name, page_index, 0)
+def show_image_info(num, filenames):
+	return filenames[int(num)]
+def delete_image(is_img2img, dir_name, name, page_index, filenames):
+	path = os.path.join(dir_name, name)		
+	if os.path.exists(path):
+		print(f"Delete file {path}")
+		os.remove(path)	
+	i = 0
+	for f in filenames:
+		if f == name:
+			break
+		i += 1
+	images, page_index, file_list = get_recent_images(is_img2img, dir_name, page_index, 0)
+	current_file =  file_list[i] if i < len(file_list) else None
+	return images, page_index, file_list, current_file
+
+
+def show_images_history(gr, opts, is_img2img):
+		def id_name(is_img2img, name):	
+			return ("img2img" if is_img2img else "txt2img") + "_" + name
+		with gr.Row():				
+			if is_img2img:
+				dir_name = opts.outdir_img2img_samples
+			else:
+				dir_name = opts.outdir_txt2img_samples							
+			first_page = gr.Button('First Page', elem_id=id_name(is_img2img,"images_history_first_page"))
+			prev_page = gr.Button('Prev Page') 
+			page_index = gr.Number(value=1)
+			next_page = gr.Button('Next Page') 
+			end_page = gr.Button('End Page')  
+		with gr.Row():	      
+			delete = gr.Button('Delete')
+			Send = gr.Button('Send')
+		with gr.Row():	
+			with gr.Column(elem_id=id_name(is_img2img,"images_history")):	
+				history_gallery = gr.Gallery(label="Images history").style(grid=6)
+				img_file_name = gr.Textbox()	
+				img_file_info = gr.Textbox(dir_name)
+				img_path = gr.Textbox(dir_name, visible=False)					
+				set_index = gr.Button('set_index',  elem_id=id_name(is_img2img,"images_history_set_index"))
+				is_img2img_flag = gr.Checkbox(is_img2img, visible=False)
+		filenames = gr.State()
+		first_page.click(first_page_click, inputs=[is_img2img_flag, img_path], outputs=[history_gallery, page_index, filenames])
+		next_page.click(next_page_click, inputs=[is_img2img_flag, img_path, page_index], outputs=[history_gallery, page_index, filenames])
+		prev_page.click(prev_page_click, inputs=[is_img2img_flag, img_path,  page_index], outputs=[history_gallery, page_index, filenames])		
+		end_page.click(end_page_click, inputs=[is_img2img_flag, img_path], outputs=[history_gallery, page_index, filenames])
+		page_index.submit(page_index_change, inputs=[is_img2img_flag, img_path,  page_index], outputs=[history_gallery, page_index, filenames])
+		set_index.click(show_image_info, _js="images_history_get_current_img",inputs=[is_img2img_flag, filenames], outputs=img_file_name)	
+		delete.click(delete_image, inputs=[is_img2img_flag, img_path, img_file_name, page_index, filenames], outputs=[history_gallery, page_index, filenames,img_file_name]) 
+		#page_index.change(page_index_change, inputs=[is_img2img_flag, img_path,  page_index], outputs=[history_gallery, page_index])
+		
+def create_history_tabs(gr, opts):
+	with gr.Blocks(analytics_enabled=False) as images_history:
+		with gr.Tabs() as tabs:			
+			with gr.Tab("txt2img history", id="images_history_txt2img"):
+				with gr.Blocks(analytics_enabled=False) as images_history_txt2img:   
+					show_images_history(gr, opts, is_img2img=False) 
+			with gr.Tab("img2img history", id="images_history_img2img"):
+				with gr.Blocks(analytics_enabled=False) as images_history_img2img:
+					show_images_history(gr, opts, is_img2img=True)
+	return images_history
diff --git a/modules/ui.py b/modules/ui.py
index 4f18126f..8762fcf5 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -37,6 +37,7 @@ import modules.generation_parameters_copypaste
 from modules import prompt_parser
 from modules.images import save_image
 import modules.textual_inversion.ui
+import modules.images_history as img_his
 
 # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the bowser will not show any UI
 mimetypes.init()
@@ -499,7 +500,6 @@ def create_ui(wrap_gradio_gpu_call):
                     custom_inputs = modules.scripts.scripts_txt2img.setup_ui(is_img2img=False)
 
             with gr.Column(variant='panel'):
-
                 with gr.Group():
                     txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False)
                     txt2img_gallery = gr.Gallery(label='Output', show_label=False, elem_id='txt2img_gallery').style(grid=4)
@@ -516,6 +516,7 @@ def create_ui(wrap_gradio_gpu_call):
                 with gr.Group():
                     html_info = gr.HTML()
                     generation_info = gr.Textbox(visible=False)
+                
 
             connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
             connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
@@ -607,6 +608,7 @@ def create_ui(wrap_gradio_gpu_call):
             ]
             modules.generation_parameters_copypaste.connect_paste(paste, txt2img_paste_fields, txt2img_prompt)
             token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter])
+        
 
     with gr.Blocks(analytics_enabled=False) as img2img_interface:
         img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_prompt_style_apply, img2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=True)
@@ -696,6 +698,7 @@ def create_ui(wrap_gradio_gpu_call):
                 with gr.Group():
                     html_info = gr.HTML()
                     generation_info = gr.Textbox(visible=False)
+                
 
             connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
             connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
@@ -1126,8 +1129,10 @@ def create_ui(wrap_gradio_gpu_call):
 
         opts.save(shared.config_filename)
 
-        return f'{changed} settings changed.', opts.dumpjson()
+        return f'{changed} settings changed.', opts.dumpjson()    
 
+    
+    images_history = img_his.create_history_tabs(gr, opts)    
     with gr.Blocks(analytics_enabled=False) as settings_interface:
         settings_submit = gr.Button(value="Apply settings", variant='primary')
         result = gr.HTML()
@@ -1206,7 +1211,9 @@ def create_ui(wrap_gradio_gpu_call):
         (pnginfo_interface, "PNG Info", "pnginfo"),
         (modelmerger_interface, "Checkpoint Merger", "modelmerger"),
         (textual_inversion_interface, "Textual inversion", "ti"),
+        (images_history, "History", "images_history"),
         (settings_interface, "Settings", "settings"),
+
     ]
 
     with open(os.path.join(script_path, "style.css"), "r", encoding="utf8") as file:
diff --git a/repositorieslatent-diffusion b/repositorieslatent-diffusion
new file mode 160000
index 00000000..abf33e70
--- /dev/null
+++ b/repositorieslatent-diffusion
@@ -0,0 +1 @@
+Subproject commit abf33e7002d59d9085081bce93ec798dcabd49af
diff --git a/testui.py b/testui.py
new file mode 100644
index 00000000..f54e4a62
--- /dev/null
+++ b/testui.py
@@ -0,0 +1,124 @@
+import os
+import threading
+import time
+import importlib
+import signal
+import threading
+
+from modules.paths import script_path
+
+from modules import devices, sd_samplers
+import modules.codeformer_model as codeformer
+import modules.extras
+import modules.face_restoration
+import modules.gfpgan_model as gfpgan
+import modules.img2img
+
+import modules.lowvram
+import modules.paths
+import modules.scripts
+import modules.sd_hijack
+import modules.sd_models
+import modules.shared as shared
+import modules.txt2img
+
+import modules.ui
+from modules import devices
+from modules import modelloader
+from modules.paths import script_path
+from modules.shared import cmd_opts
+
+modelloader.cleanup_models()
+modules.sd_models.setup_model()
+codeformer.setup_model(cmd_opts.codeformer_models_path)
+gfpgan.setup_model(cmd_opts.gfpgan_models_path)
+shared.face_restorers.append(modules.face_restoration.FaceRestoration())
+modelloader.load_upscalers()
+queue_lock = threading.Lock()
+
+
+def wrap_queued_call(func):
+    def f(*args, **kwargs):
+        with queue_lock:
+            res = func(*args, **kwargs)
+
+        return res
+
+    return f
+
+
+def wrap_gradio_gpu_call(func, extra_outputs=None):
+    def f(*args, **kwargs):
+        devices.torch_gc()
+
+        shared.state.sampling_step = 0
+        shared.state.job_count = -1
+        shared.state.job_no = 0
+        shared.state.job_timestamp = shared.state.get_job_timestamp()
+        shared.state.current_latent = None
+        shared.state.current_image = None
+        shared.state.current_image_sampling_step = 0
+        shared.state.interrupted = False
+        shared.state.textinfo = None
+
+        with queue_lock:
+            res = func(*args, **kwargs)
+
+        shared.state.job = ""
+        shared.state.job_count = 0
+
+        devices.torch_gc()
+
+        return res
+
+    return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs)
+
+
+modules.scripts.load_scripts(os.path.join(script_path, "scripts"))
+
+shared.sd_model = None #modules.sd_models.load_model()
+#shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model)))
+
+
+def webui():
+    # make the program just exit at ctrl+c without waiting for anything
+    def sigint_handler(sig, frame):
+        print(f'Interrupted with signal {sig} in {frame}')
+        os._exit(0)
+
+    signal.signal(signal.SIGINT, sigint_handler)
+
+    while 1:
+
+        demo = modules.ui.create_ui(wrap_gradio_gpu_call=wrap_gradio_gpu_call)
+        
+        demo.launch(
+            share=cmd_opts.share,
+            server_name="0.0.0.0" if cmd_opts.listen else None,
+            server_port=cmd_opts.port,
+            debug=cmd_opts.gradio_debug,
+            auth=[tuple(cred.split(':')) for cred in cmd_opts.gradio_auth.strip('"').split(',')] if cmd_opts.gradio_auth else None,
+            inbrowser=cmd_opts.autolaunch,
+            prevent_thread_lock=True
+        )
+
+        while 1:
+            time.sleep(0.5)
+            if getattr(demo, 'do_restart', False):
+                time.sleep(0.5)
+                demo.close()
+                time.sleep(0.5)
+                break
+
+        sd_samplers.set_samplers()
+
+        print('Reloading Custom Scripts')
+        modules.scripts.reload_scripts(os.path.join(script_path, "scripts"))
+        print('Reloading modules: modules.ui')
+        importlib.reload(modules.ui)
+        print('Restarting Gradio')
+
+
+
+if __name__ == "__main__":
+    webui()
-- 
cgit v1.2.3


From 3110f895b2718a3a25aae419fdf5c87c177ec9f4 Mon Sep 17 00:00:00 2001
From: alg-wiki <alg.4chan@gmail.com>
Date: Mon, 10 Oct 2022 17:07:46 +0900
Subject: Textual Inversion: Added custom training image size and number of
 repeats per input image in a single epoch

---
 modules/textual_inversion/dataset.py           |  6 +++---
 modules/textual_inversion/preprocess.py        |  4 ++--
 modules/textual_inversion/textual_inversion.py | 15 ++++++++++++---
 modules/ui.py                                  |  8 +++++++-
 4 files changed, 24 insertions(+), 9 deletions(-)

diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index 7c44ea5b..acc4ce59 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -15,13 +15,13 @@ re_tag = re.compile(r"[a-zA-Z][_\w\d()]+")
 
 
 class PersonalizedBase(Dataset):
-    def __init__(self, data_root, size=None, repeats=100, flip_p=0.5, placeholder_token="*", width=512, height=512, model=None, device=None, template_file=None):
+    def __init__(self, data_root, size, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None):
 
         self.placeholder_token = placeholder_token
 
         self.size = size
-        self.width = width
-        self.height = height
+        self.width = size
+        self.height = size
         self.flip = transforms.RandomHorizontalFlip(p=flip_p)
 
         self.dataset = []
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index f1c002a2..b3de6fd7 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -7,8 +7,8 @@ import tqdm
 from modules import shared, images
 
 
-def preprocess(process_src, process_dst, process_flip, process_split, process_caption):
-    size = 512
+def preprocess(process_src, process_dst, process_size, process_flip, process_split, process_caption):
+    size = process_size
     src = os.path.abspath(process_src)
     dst = os.path.abspath(process_dst)
 
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index cd9f3498..e34dc2e8 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -6,6 +6,7 @@ import torch
 import tqdm
 import html
 import datetime
+import math
 
 
 from modules import shared, devices, sd_hijack, processing, sd_models
@@ -156,7 +157,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'):
     return fn
 
 
-def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps, create_image_every, save_embedding_every, template_file):
+def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_size, steps, num_repeats, create_image_every, save_embedding_every, template_file):
     assert embedding_name, 'embedding not selected'
 
     shared.state.textinfo = "Initializing textual inversion training..."
@@ -182,7 +183,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
 
     shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
     with torch.autocast("cuda"):
-        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, size=512, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file)
+        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, size=training_size, repeats=num_repeats, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file)
 
     hijack = sd_hijack.model_hijack
 
@@ -200,6 +201,9 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
     if ititial_step > steps:
         return embedding, filename
 
+    tr_img_len = len([os.path.join(data_root, file_path) for file_path in os.listdir(data_root)])
+    epoch_len = (tr_img_len * num_repeats) + tr_img_len
+
     pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step)
     for i, (x, text) in pbar:
         embedding.step = i + ititial_step
@@ -223,7 +227,10 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
             loss.backward()
             optimizer.step()
 
-        pbar.set_description(f"loss: {losses.mean():.7f}")
+        epoch_num = math.floor(embedding.step / epoch_len)
+        epoch_step = embedding.step - (epoch_num * epoch_len)
+
+        pbar.set_description(f"[Epoch {epoch_num}: {epoch_step}/{epoch_len}]loss: {losses.mean():.7f}")
 
         if embedding.step > 0 and embedding_dir is not None and embedding.step % save_embedding_every == 0:
             last_saved_file = os.path.join(embedding_dir, f'{embedding_name}-{embedding.step}.pt')
@@ -236,6 +243,8 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
                 sd_model=shared.sd_model,
                 prompt=text,
                 steps=20,
+                height=training_size,
+                width=training_size,
                 do_not_save_grid=True,
                 do_not_save_samples=True,
             )
diff --git a/modules/ui.py b/modules/ui.py
index 2231a8ed..f821fd8d 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1029,6 +1029,7 @@ def create_ui(wrap_gradio_gpu_call):
 
                     process_src = gr.Textbox(label='Source directory')
                     process_dst = gr.Textbox(label='Destination directory')
+                    process_size = gr.Slider(minimum=64, maximum=2048, step=64, label="Size (width and height)", value=512)
 
                     with gr.Row():
                         process_flip = gr.Checkbox(label='Create flipped copies')
@@ -1043,13 +1044,15 @@ def create_ui(wrap_gradio_gpu_call):
                             run_preprocess = gr.Button(value="Preprocess", variant='primary')
 
                 with gr.Group():
-                    gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding; must specify a directory with a set of 512x512 images</p>")
+                    gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding; must specify a directory with a set of 1:1 ratio images</p>")
                     train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
                     learn_rate = gr.Number(label='Learning rate', value=5.0e-03)
                     dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images")
                     log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")
                     template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"))
+                    training_size = gr.Slider(minimum=64, maximum=2048, step=64, label="Size (width and height)", value=512)
                     steps = gr.Number(label='Max steps', value=100000, precision=0)
+                    num_repeats = gr.Number(label='Number of repeats for a single input image per epoch', value=100, precision=0)
                     create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0)
                     save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0)
 
@@ -1092,6 +1095,7 @@ def create_ui(wrap_gradio_gpu_call):
             inputs=[
                 process_src,
                 process_dst,
+                process_size,
                 process_flip,
                 process_split,
                 process_caption,
@@ -1110,7 +1114,9 @@ def create_ui(wrap_gradio_gpu_call):
                 learn_rate,
                 dataset_directory,
                 log_directory,
+                training_size,
                 steps,
+                num_repeats,
                 create_image_every,
                 save_embedding_every,
                 template_file,
-- 
cgit v1.2.3


From 8ec069e64df48f8f202f8b93a08e91b69448eb39 Mon Sep 17 00:00:00 2001
From: JC_Array <justin318@att.net>
Date: Mon, 10 Oct 2022 03:23:24 -0500
Subject: removed duplicate run_preprocess.click by creating
 run_preprocess_inputs list and appending deepbooru variable to input list if
 in scope

---
 modules/ui.py | 49 +++++++++++++++++--------------------------------
 1 file changed, 17 insertions(+), 32 deletions(-)

diff --git a/modules/ui.py b/modules/ui.py
index 179e3a83..22ca74c2 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1089,40 +1089,25 @@ def create_ui(wrap_gradio_gpu_call):
             ]
         )
 
+        run_preprocess_inputs = [
+            process_src,
+            process_dst,
+            process_flip,
+            process_split,
+            process_caption,
+        ]
         if cmd_opts.deepdanbooru:
             # if process_caption_deepbooru is None, it will cause an error, as a result only include it if it is enabled
-            run_preprocess.click(
-                fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]),
-                _js="start_training_textual_inversion",
-                inputs=[
-                    process_src,
-                    process_dst,
-                    process_flip,
-                    process_split,
-                    process_caption,
-                    process_caption_deepbooru,
-                ],
-                outputs=[
-                    ti_output,
-                    ti_outcome,
-                ],
-            )
-        else:
-            run_preprocess.click(
-                fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]),
-                _js="start_training_textual_inversion",
-                inputs=[
-                    process_src,
-                    process_dst,
-                    process_flip,
-                    process_split,
-                    process_caption,
-                ],
-                outputs=[
-                    ti_output,
-                    ti_outcome,
-                ],
-            )
+            run_preprocess_inputs.append(process_caption_deepbooru)
+        run_preprocess.click(
+            fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]),
+            _js="start_training_textual_inversion",
+            inputs=run_preprocess_inputs,
+            outputs=[
+                ti_output,
+                ti_outcome,
+            ],
+        )
 
         train_embedding.click(
             fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.train_embedding, extra_outputs=[gr.update()]),
-- 
cgit v1.2.3


From 4ee7519fc2e459ce8eff1f61f1655afba393357c Mon Sep 17 00:00:00 2001
From: alg-wiki <alg.4chan@gmail.com>
Date: Mon, 10 Oct 2022 17:31:33 +0900
Subject: Fixed progress bar output for epoch

---
 modules/textual_inversion/textual_inversion.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index e34dc2e8..769682ea 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -228,7 +228,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
             optimizer.step()
 
         epoch_num = math.floor(embedding.step / epoch_len)
-        epoch_step = embedding.step - (epoch_num * epoch_len)
+        epoch_step = embedding.step - (epoch_num * epoch_len) + 1
 
         pbar.set_description(f"[Epoch {epoch_num}: {epoch_step}/{epoch_len}]loss: {losses.mean():.7f}")
 
-- 
cgit v1.2.3


From 2f94331df2cb1181439adecc28cfd758049f6501 Mon Sep 17 00:00:00 2001
From: JC_Array <justin318@att.net>
Date: Mon, 10 Oct 2022 03:34:00 -0500
Subject: removed change in last commit, simplified to adding the visible
 argument to process_caption_deepbooru and it set to False if deepdanbooru
 argument is not set

---
 modules/ui.py | 22 ++++++++++------------
 1 file changed, 10 insertions(+), 12 deletions(-)

diff --git a/modules/ui.py b/modules/ui.py
index 22ca74c2..f8adafb3 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1036,7 +1036,8 @@ def create_ui(wrap_gradio_gpu_call):
                         process_caption = gr.Checkbox(label='Use BLIP caption as filename')
                         if cmd_opts.deepdanbooru:
                             process_caption_deepbooru = gr.Checkbox(label='Use deepbooru caption as filename')
-
+                        else:
+                            process_caption_deepbooru = gr.Checkbox(label='Use deepbooru caption as filename', visible=False)
 
                     with gr.Row():
                         with gr.Column(scale=3):
@@ -1089,20 +1090,17 @@ def create_ui(wrap_gradio_gpu_call):
             ]
         )
 
-        run_preprocess_inputs = [
-            process_src,
-            process_dst,
-            process_flip,
-            process_split,
-            process_caption,
-        ]
-        if cmd_opts.deepdanbooru:
-            # if process_caption_deepbooru is None, it will cause an error, as a result only include it if it is enabled
-            run_preprocess_inputs.append(process_caption_deepbooru)
         run_preprocess.click(
             fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]),
             _js="start_training_textual_inversion",
-            inputs=run_preprocess_inputs,
+            inputs=[
+                process_src,
+                process_dst,
+                process_flip,
+                process_split,
+                process_caption,
+                process_caption_deepbooru
+            ],
             outputs=[
                 ti_output,
                 ti_outcome,
-- 
cgit v1.2.3


From 23f2989799ee3911d2959cfceb74b921f20c9a51 Mon Sep 17 00:00:00 2001
From: yfszzx <yfszzx@gmail.com>
Date: Mon, 10 Oct 2022 18:33:49 +0800
Subject: images history over

---
 javascript/images_history.js |   4 +-
 modules/images_history.py    | 141 ++++++++++++++++++++++++++-----------------
 modules/ui.py                |   9 ++-
 testui.py                    | 124 -------------------------------------
 4 files changed, 94 insertions(+), 184 deletions(-)
 delete mode 100644 testui.py

diff --git a/javascript/images_history.js b/javascript/images_history.js
index f30b7eff..93d2b89a 100644
--- a/javascript/images_history.js
+++ b/javascript/images_history.js
@@ -58,9 +58,9 @@ function set_history_index_from_img(e){
 		}  		
     }
 }
-function images_history_get_current_img(is_image2image){
+function images_history_get_current_img(is_image2image, image_path, files){
 	head = is_image2image?"img2img":"txt2img"
 	s =  $(gradioApp().getElementById(head + '_images_history_set_index')).attr("img_index")
-	return s
+	return [s, image_path, files]
 }
 
diff --git a/modules/images_history.py b/modules/images_history.py
index 23d83557..0e0a48f3 100644
--- a/modules/images_history.py
+++ b/modules/images_history.py
@@ -1,5 +1,6 @@
 import os
-def get_recent_images(is_img2img, dir_name, page_index, step):
+def get_recent_images(dir_name, page_index, step, image_index):
+	print(image_index)
 	page_index = int(page_index)
 	f_list = os.listdir(dir_name)
 	file_list = []
@@ -8,7 +9,7 @@ def get_recent_images(is_img2img, dir_name, page_index, step):
 			continue
 		file_list.append(file)	
 	file_list = sorted(file_list, key=lambda file: -os.path.getctime(os.path.join(dir_name, file)))
-	num = 24
+	num = 48
 	max_page_index = len(file_list) // num + 1	
 	page_index = max_page_index if page_index == -1 else page_index + step
 	page_index = 1 if page_index < 1 else page_index	
@@ -16,75 +17,101 @@ def get_recent_images(is_img2img, dir_name, page_index, step):
 	idx_frm = (page_index - 1) * num
 	file_list = file_list[idx_frm:idx_frm + num]
 	print(f"Loading history page {page_index}")	
-	return [os.path.join(dir_name, file) for file in file_list], page_index, file_list
-def first_page_click(is_img2img, dir_name):
-	return get_recent_images(is_img2img, dir_name, 1, 0)
-def end_page_click(is_img2img, dir_name):
-	return get_recent_images(is_img2img, dir_name, -1, 0)
-def prev_page_click(is_img2img, dir_name, page_index):
-	return get_recent_images(is_img2img, dir_name, page_index, -1)
-def next_page_click(is_img2img, dir_name, page_index):	
-	return get_recent_images(is_img2img, dir_name, page_index, 1)
-def page_index_change(is_img2img, dir_name, page_index):	
-	return get_recent_images(is_img2img, dir_name, page_index, 0)
-def show_image_info(num, filenames):
-	return filenames[int(num)]
-def delete_image(is_img2img, dir_name, name, page_index, filenames):
+	image_index = int(image_index)
+	if image_index < 0 or image_index > len(file_list)  - 1:
+		current_file = None 
+		hide_image = None
+	else:
+		current_file =  file_list[int(image_index)]
+		hide_image = os.path.join(dir_name, current_file)
+	return [os.path.join(dir_name, file) for file in file_list], page_index, file_list, current_file, hide_image
+def first_page_click(dir_name, page_index, image_index):
+	return get_recent_images(dir_name, 1, 0, image_index)
+def end_page_click(dir_name, page_index, image_index):
+	return get_recent_images(dir_name, -1, 0, image_index)
+def prev_page_click(dir_name, page_index, image_index):
+	return get_recent_images(dir_name, page_index, -1, image_index)
+def next_page_click(dir_name, page_index, image_index):	
+	return get_recent_images(dir_name, page_index, 1, image_index)
+def page_index_change(dir_name, page_index, image_index):	
+	return get_recent_images(dir_name, page_index, 0, image_index)
+
+def show_image_info(num, image_path, filenames):
+	file = filenames[int(num)]
+	return file, num, os.path.join(image_path, file)
+def delete_image(is_img2img, dir_name, name, page_index, filenames, image_index):
+	print("filename", name)
 	path = os.path.join(dir_name, name)		
 	if os.path.exists(path):
 		print(f"Delete file {path}")
 		os.remove(path)	
-	i = 0
-	for f in filenames:
-		if f == name:
-			break
-		i += 1
-	images, page_index, file_list = get_recent_images(is_img2img, dir_name, page_index, 0)
-	current_file =  file_list[i] if i < len(file_list) else None
-	return images, page_index, file_list, current_file
+	images, page_index, file_list, current_file, hide_image = get_recent_images(dir_name, page_index, 0, image_index)
+	return images, page_index, file_list, current_file, hide_image
 
 
-def show_images_history(gr, opts, is_img2img):
+def show_images_history(gr, opts, is_img2img, run_pnginfo, switch_dict):
 		def id_name(is_img2img, name):	
 			return ("img2img" if is_img2img else "txt2img") + "_" + name
-		with gr.Row():				
-			if is_img2img:
-				dir_name = opts.outdir_img2img_samples
-			else:
-				dir_name = opts.outdir_txt2img_samples							
-			first_page = gr.Button('First Page', elem_id=id_name(is_img2img,"images_history_first_page"))
-			prev_page = gr.Button('Prev Page') 
-			page_index = gr.Number(value=1)
-			next_page = gr.Button('Next Page') 
-			end_page = gr.Button('End Page')  
-		with gr.Row():	      
-			delete = gr.Button('Delete')
-			Send = gr.Button('Send')
-		with gr.Row():	
-			with gr.Column(elem_id=id_name(is_img2img,"images_history")):	
-				history_gallery = gr.Gallery(label="Images history").style(grid=6)
-				img_file_name = gr.Textbox()	
-				img_file_info = gr.Textbox(dir_name)
-				img_path = gr.Textbox(dir_name, visible=False)					
-				set_index = gr.Button('set_index',  elem_id=id_name(is_img2img,"images_history_set_index"))
-				is_img2img_flag = gr.Checkbox(is_img2img, visible=False)
-		filenames = gr.State()
-		first_page.click(first_page_click, inputs=[is_img2img_flag, img_path], outputs=[history_gallery, page_index, filenames])
-		next_page.click(next_page_click, inputs=[is_img2img_flag, img_path, page_index], outputs=[history_gallery, page_index, filenames])
-		prev_page.click(prev_page_click, inputs=[is_img2img_flag, img_path,  page_index], outputs=[history_gallery, page_index, filenames])		
-		end_page.click(end_page_click, inputs=[is_img2img_flag, img_path], outputs=[history_gallery, page_index, filenames])
-		page_index.submit(page_index_change, inputs=[is_img2img_flag, img_path,  page_index], outputs=[history_gallery, page_index, filenames])
-		set_index.click(show_image_info, _js="images_history_get_current_img",inputs=[is_img2img_flag, filenames], outputs=img_file_name)	
-		delete.click(delete_image, inputs=[is_img2img_flag, img_path, img_file_name, page_index, filenames], outputs=[history_gallery, page_index, filenames,img_file_name]) 
+		if is_img2img:
+			dir_name = opts.outdir_img2img_samples
+		else:
+			dir_name = opts.outdir_txt2img_samples
+		with gr.Row():	 
+				first_page = gr.Button('First', elem_id=id_name(is_img2img,"images_history_first_page"))
+				prev_page = gr.Button('Prev') 
+				page_index = gr.Number(value=1, label="Page Index")
+				next_page = gr.Button('Next') 
+				end_page = gr.Button('End')	
+		with gr.Row(elem_id=id_name(is_img2img,"images_history")):			
+			with gr.Row():	 
+				with gr.Column():
+					history_gallery = gr.Gallery(show_label=False).style(grid=6)
+				with gr.Column():	 
+					with gr.Row():	      
+						delete = gr.Button('Delete')
+						pnginfo_send_to_txt2img = gr.Button('Send to txt2img')
+						pnginfo_send_to_img2img = gr.Button('Send to img2img')
+					with gr.Row():
+						with gr.Column():
+							img_file_info = gr.Textbox(dir_name, label="Generate Info")
+							img_file_name = gr.Textbox(label="File Name")	
+					with gr.Row():	
+							# hiden items
+							img_path = gr.Textbox(dir_name, visible=False)				
+							is_img2img_flag = gr.Checkbox(is_img2img, visible=False)	
+							image_index = gr.Textbox(value=-1, visible=False)						
+							set_index = gr.Button('set_index',  elem_id=id_name(is_img2img,"images_history_set_index"))
+							filenames = gr.State()
+							hide_image = gr.Image(visible=False, type="pil")
+							info1 = gr.Textbox(visible=False)
+							info2 = gr.Textbox(visible=False)
+
+				
+		# turn pages
+		gallery_inputs = [img_path, page_index, image_index]
+		gallery_outputs = [history_gallery, page_index, filenames, img_file_name, hide_image]
+		first_page.click(first_page_click, inputs=gallery_inputs, outputs=gallery_outputs)
+		next_page.click(next_page_click, inputs=gallery_inputs, outputs=gallery_outputs)
+		prev_page.click(prev_page_click, inputs=gallery_inputs, outputs=gallery_outputs)		
+		end_page.click(end_page_click, inputs=gallery_inputs, outputs=gallery_outputs)
+		page_index.submit(page_index_change, inputs=gallery_inputs, outputs=gallery_outputs)
 		#page_index.change(page_index_change, inputs=[is_img2img_flag, img_path,  page_index], outputs=[history_gallery, page_index])
+
+		#other funcitons
+		set_index.click(show_image_info, _js="images_history_get_current_img", inputs=[is_img2img_flag,  img_path, filenames], outputs=[img_file_name, image_index, hide_image])
+		delete.click(delete_image, inputs=[is_img2img_flag, img_path, img_file_name, page_index, filenames, image_index], outputs=gallery_outputs) 
+		hide_image.change(fn=run_pnginfo, inputs=[hide_image], outputs=[info1, img_file_info, info2])
+		switch_dict["fn"](pnginfo_send_to_txt2img, switch_dict["t2i"], img_file_info, 'switch_to_txt2img')
+		switch_dict["fn"](pnginfo_send_to_img2img, switch_dict["i2i"], img_file_info, 'switch_to_img2img_img2img')
+	
 		
-def create_history_tabs(gr, opts):
+def create_history_tabs(gr, opts, run_pnginfo, switch_dict):
 	with gr.Blocks(analytics_enabled=False) as images_history:
 		with gr.Tabs() as tabs:			
 			with gr.Tab("txt2img history", id="images_history_txt2img"):
 				with gr.Blocks(analytics_enabled=False) as images_history_txt2img:   
-					show_images_history(gr, opts, is_img2img=False) 
+					show_images_history(gr, opts, False, run_pnginfo, switch_dict) 
 			with gr.Tab("img2img history", id="images_history_img2img"):
 				with gr.Blocks(analytics_enabled=False) as images_history_img2img:
-					show_images_history(gr, opts, is_img2img=True)
+					show_images_history(gr, opts, True, run_pnginfo, switch_dict)
 	return images_history
diff --git a/modules/ui.py b/modules/ui.py
index 8762fcf5..21c9236b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1131,8 +1131,15 @@ def create_ui(wrap_gradio_gpu_call):
 
         return f'{changed} settings changed.', opts.dumpjson()    
 
+    #images history
+    images_history_switch_dict = {
+        "fn":modules.generation_parameters_copypaste.connect_paste,
+        "t2i":txt2img_paste_fields,
+        "i2i":img2img_paste_fields
+    }
+    images_history = img_his.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict)    
     
-    images_history = img_his.create_history_tabs(gr, opts)    
+
     with gr.Blocks(analytics_enabled=False) as settings_interface:
         settings_submit = gr.Button(value="Apply settings", variant='primary')
         result = gr.HTML()
diff --git a/testui.py b/testui.py
deleted file mode 100644
index f54e4a62..00000000
--- a/testui.py
+++ /dev/null
@@ -1,124 +0,0 @@
-import os
-import threading
-import time
-import importlib
-import signal
-import threading
-
-from modules.paths import script_path
-
-from modules import devices, sd_samplers
-import modules.codeformer_model as codeformer
-import modules.extras
-import modules.face_restoration
-import modules.gfpgan_model as gfpgan
-import modules.img2img
-
-import modules.lowvram
-import modules.paths
-import modules.scripts
-import modules.sd_hijack
-import modules.sd_models
-import modules.shared as shared
-import modules.txt2img
-
-import modules.ui
-from modules import devices
-from modules import modelloader
-from modules.paths import script_path
-from modules.shared import cmd_opts
-
-modelloader.cleanup_models()
-modules.sd_models.setup_model()
-codeformer.setup_model(cmd_opts.codeformer_models_path)
-gfpgan.setup_model(cmd_opts.gfpgan_models_path)
-shared.face_restorers.append(modules.face_restoration.FaceRestoration())
-modelloader.load_upscalers()
-queue_lock = threading.Lock()
-
-
-def wrap_queued_call(func):
-    def f(*args, **kwargs):
-        with queue_lock:
-            res = func(*args, **kwargs)
-
-        return res
-
-    return f
-
-
-def wrap_gradio_gpu_call(func, extra_outputs=None):
-    def f(*args, **kwargs):
-        devices.torch_gc()
-
-        shared.state.sampling_step = 0
-        shared.state.job_count = -1
-        shared.state.job_no = 0
-        shared.state.job_timestamp = shared.state.get_job_timestamp()
-        shared.state.current_latent = None
-        shared.state.current_image = None
-        shared.state.current_image_sampling_step = 0
-        shared.state.interrupted = False
-        shared.state.textinfo = None
-
-        with queue_lock:
-            res = func(*args, **kwargs)
-
-        shared.state.job = ""
-        shared.state.job_count = 0
-
-        devices.torch_gc()
-
-        return res
-
-    return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs)
-
-
-modules.scripts.load_scripts(os.path.join(script_path, "scripts"))
-
-shared.sd_model = None #modules.sd_models.load_model()
-#shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model)))
-
-
-def webui():
-    # make the program just exit at ctrl+c without waiting for anything
-    def sigint_handler(sig, frame):
-        print(f'Interrupted with signal {sig} in {frame}')
-        os._exit(0)
-
-    signal.signal(signal.SIGINT, sigint_handler)
-
-    while 1:
-
-        demo = modules.ui.create_ui(wrap_gradio_gpu_call=wrap_gradio_gpu_call)
-        
-        demo.launch(
-            share=cmd_opts.share,
-            server_name="0.0.0.0" if cmd_opts.listen else None,
-            server_port=cmd_opts.port,
-            debug=cmd_opts.gradio_debug,
-            auth=[tuple(cred.split(':')) for cred in cmd_opts.gradio_auth.strip('"').split(',')] if cmd_opts.gradio_auth else None,
-            inbrowser=cmd_opts.autolaunch,
-            prevent_thread_lock=True
-        )
-
-        while 1:
-            time.sleep(0.5)
-            if getattr(demo, 'do_restart', False):
-                time.sleep(0.5)
-                demo.close()
-                time.sleep(0.5)
-                break
-
-        sd_samplers.set_samplers()
-
-        print('Reloading Custom Scripts')
-        modules.scripts.reload_scripts(os.path.join(script_path, "scripts"))
-        print('Reloading modules: modules.ui')
-        importlib.reload(modules.ui)
-        print('Restarting Gradio')
-
-
-
-if __name__ == "__main__":
-    webui()
-- 
cgit v1.2.3


From a3578233395e585e68c2118d3630cb2a961d4a36 Mon Sep 17 00:00:00 2001
From: Bepis <36346617+bbepis@users.noreply.github.com>
Date: Mon, 10 Oct 2022 23:12:29 +1100
Subject: Add a pull request template

---
 .../PULL_REQUEST_TEMPLATE/pull_request_template.md | 28 ++++++++++++++++++++++
 1 file changed, 28 insertions(+)
 create mode 100644 .github/PULL_REQUEST_TEMPLATE/pull_request_template.md

diff --git a/.github/PULL_REQUEST_TEMPLATE/pull_request_template.md b/.github/PULL_REQUEST_TEMPLATE/pull_request_template.md
new file mode 100644
index 00000000..86009613
--- /dev/null
+++ b/.github/PULL_REQUEST_TEMPLATE/pull_request_template.md
@@ -0,0 +1,28 @@
+# Please read the [contributing wiki page](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Contributing) before submitting a pull request!
+
+If you have a large change, pay special attention to this paragraph:
+
+> Before making changes, if you think that your feature will result in more than 100 lines changing, find me and talk to me about the feature you are proposing. It pains me to reject the hard work someone else did, but I won't add everything to the repo, and it's better if the rejection happens before you have to waste time working on the feature.
+
+Otherwise, after making sure you're following the rules described in wiki page, remove this section and continue on.
+
+**Describe what this pull request is trying to achieve.**
+
+A clear and concise description of what you're trying to accomplish with this, so your intent doesn't have to be extracted from your code.
+
+**Additional notes and description of your changes**
+
+More technical discussion about your changes go here, plus anything that a maintainer might have to specifically take a look at, or be wary of.
+
+**Environment this was tested in**
+
+List the environment you have developed / tested this on. As per the contributing page, changes should be able to work on Windows out of the box.
+ - OS: [e.g. Windows, Linux]
+ - Browser [e.g. chrome, safari]
+ - Graphics card [e.g. NVIDIA RTX 2080 8GB, AMD RX 6600 8GB]
+
+**Screenshots or videos of your changes**
+
+If applicable, screenshots or a video showing off your changes. If it edits an existing UI, it should ideally contain a comparison of what used to be there, before your changes were made.
+
+This is **required** for anything that touches the user interface.
\ No newline at end of file
-- 
cgit v1.2.3


From 7349088d32b080f64058b6e5de5f0380a71ecd09 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 10 Oct 2022 16:11:14 +0300
Subject: --no-half-vae

---
 modules/devices.py     |  6 +++++-
 modules/processing.py  | 11 +++++++++--
 modules/sd_models.py   |  3 +++
 modules/sd_samplers.py |  4 ++--
 modules/shared.py      |  1 +
 5 files changed, 20 insertions(+), 5 deletions(-)

diff --git a/modules/devices.py b/modules/devices.py
index 0158b11f..03ef58f1 100644
--- a/modules/devices.py
+++ b/modules/devices.py
@@ -36,6 +36,7 @@ errors.run(enable_tf32, "Enabling TF32")
 
 device = device_gfpgan = device_bsrgan = device_esrgan = device_scunet = device_codeformer = get_optimal_device()
 dtype = torch.float16
+dtype_vae = torch.float16
 
 def randn(seed, shape):
     # Pytorch currently doesn't handle setting randomness correctly when the metal backend is used.
@@ -59,9 +60,12 @@ def randn_without_seed(shape):
     return torch.randn(shape, device=device)
 
 
-def autocast():
+def autocast(disable=False):
     from modules import shared
 
+    if disable:
+        return contextlib.nullcontext()
+
     if dtype == torch.float32 or shared.cmd_opts.precision == "full":
         return contextlib.nullcontext()
 
diff --git a/modules/processing.py b/modules/processing.py
index 94d2dd62..ec8651ae 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -259,6 +259,13 @@ def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, see
     return x
 
 
+def decode_first_stage(model, x):
+    with devices.autocast(disable=x.dtype == devices.dtype_vae):
+        x = model.decode_first_stage(x)
+
+    return x
+
+
 def get_fixed_seed(seed):
     if seed is None or seed == '' or seed == -1:
         return int(random.randrange(4294967294))
@@ -400,7 +407,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
 
             samples_ddim = samples_ddim.to(devices.dtype)
 
-            x_samples_ddim = p.sd_model.decode_first_stage(samples_ddim)
+            x_samples_ddim = decode_first_stage(p.sd_model, samples_ddim)
             x_samples_ddim = torch.clamp((x_samples_ddim + 1.0) / 2.0, min=0.0, max=1.0)
 
             del samples_ddim
@@ -533,7 +540,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
         if self.scale_latent:
             samples = torch.nn.functional.interpolate(samples, size=(self.height // opt_f, self.width // opt_f), mode="bilinear")
         else:
-            decoded_samples = self.sd_model.decode_first_stage(samples)
+            decoded_samples = decode_first_stage(self.sd_model, samples)
 
             if opts.upscaler_for_img2img is None or opts.upscaler_for_img2img == "None":
                 decoded_samples = torch.nn.functional.interpolate(decoded_samples, size=(self.height, self.width), mode="bilinear")
diff --git a/modules/sd_models.py b/modules/sd_models.py
index e63d3c29..2cdcd84f 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -149,6 +149,7 @@ def load_model_weights(model, checkpoint_info):
         model.half()
 
     devices.dtype = torch.float32 if shared.cmd_opts.no_half else torch.float16
+    devices.dtype_vae = torch.float32 if shared.cmd_opts.no_half or shared.cmd_opts.no_half_vae else torch.float16
 
     vae_file = os.path.splitext(checkpoint_file)[0] + ".vae.pt"
     if os.path.exists(vae_file):
@@ -158,6 +159,8 @@ def load_model_weights(model, checkpoint_info):
 
         model.first_stage_model.load_state_dict(vae_dict)
 
+    model.first_stage_model.to(devices.dtype_vae)
+
     model.sd_model_hash = sd_model_hash
     model.sd_model_checkpoint = checkpoint_file
     model.sd_checkpoint_info = checkpoint_info
diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index 6e743f7e..d168b938 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -7,7 +7,7 @@ import inspect
 import k_diffusion.sampling
 import ldm.models.diffusion.ddim
 import ldm.models.diffusion.plms
-from modules import prompt_parser
+from modules import prompt_parser, devices, processing
 
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
@@ -83,7 +83,7 @@ def setup_img2img_steps(p, steps=None):
 
 
 def sample_to_image(samples):
-    x_sample = shared.sd_model.decode_first_stage(samples[0:1].type(shared.sd_model.dtype))[0]
+    x_sample = processing.decode_first_stage(shared.sd_model, samples[0:1])[0]
     x_sample = torch.clamp((x_sample + 1.0) / 2.0, min=0.0, max=1.0)
     x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2)
     x_sample = x_sample.astype(np.uint8)
diff --git a/modules/shared.py b/modules/shared.py
index 1995a99a..5dfc344c 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -25,6 +25,7 @@ parser.add_argument("--ckpt-dir", type=str, default=None, help="Path to director
 parser.add_argument("--gfpgan-dir", type=str, help="GFPGAN directory", default=('./src/gfpgan' if os.path.exists('./src/gfpgan') else './GFPGAN'))
 parser.add_argument("--gfpgan-model", type=str, help="GFPGAN model file name", default=None)
 parser.add_argument("--no-half", action='store_true', help="do not switch the model to 16-bit floats")
+parser.add_argument("--no-half-vae", action='store_true', help="do not switch the VAE model to 16-bit floats")
 parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware acceleration in browser)")
 parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI")
 parser.add_argument("--embeddings-dir", type=str, default=os.path.join(script_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)")
-- 
cgit v1.2.3


From 04c745ea4f81518999927fee5f78500560c25e29 Mon Sep 17 00:00:00 2001
From: alg-wiki <alg.4chan@gmail.com>
Date: Mon, 10 Oct 2022 22:35:35 +0900
Subject: Custom Width and Height

---
 modules/textual_inversion/dataset.py           |  7 +++----
 modules/textual_inversion/preprocess.py        | 19 ++++++++++---------
 modules/textual_inversion/textual_inversion.py | 11 +++++------
 modules/ui.py                                  | 12 ++++++++----
 4 files changed, 26 insertions(+), 23 deletions(-)

diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index acc4ce59..bcf772d2 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -15,13 +15,12 @@ re_tag = re.compile(r"[a-zA-Z][_\w\d()]+")
 
 
 class PersonalizedBase(Dataset):
-    def __init__(self, data_root, size, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None):
+    def __init__(self, data_root, width, height, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None):
 
         self.placeholder_token = placeholder_token
 
-        self.size = size
-        self.width = size
-        self.height = size
+        self.width = width
+        self.height = height
         self.flip = transforms.RandomHorizontalFlip(p=flip_p)
 
         self.dataset = []
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index b3de6fd7..d7efdef2 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -7,8 +7,9 @@ import tqdm
 from modules import shared, images
 
 
-def preprocess(process_src, process_dst, process_size, process_flip, process_split, process_caption):
-    size = process_size
+def preprocess(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption):
+    width = process_width
+    height = process_height
     src = os.path.abspath(process_src)
     dst = os.path.abspath(process_dst)
 
@@ -55,23 +56,23 @@ def preprocess(process_src, process_dst, process_size, process_flip, process_spl
         is_wide = ratio < 1 / 1.35
 
         if process_split and is_tall:
-            img = img.resize((size, size * img.height // img.width))
+            img = img.resize((width, height * img.height // img.width))
 
-            top = img.crop((0, 0, size, size))
+            top = img.crop((0, 0, width, height))
             save_pic(top, index)
 
-            bot = img.crop((0, img.height - size, size, img.height))
+            bot = img.crop((0, img.height - height, width, img.height))
             save_pic(bot, index)
         elif process_split and is_wide:
-            img = img.resize((size * img.width // img.height, size))
+            img = img.resize((width * img.width // img.height, height))
 
-            left = img.crop((0, 0, size, size))
+            left = img.crop((0, 0, width, height))
             save_pic(left, index)
 
-            right = img.crop((img.width - size, 0, img.width, size))
+            right = img.crop((img.width - width, 0, img.width, height))
             save_pic(right, index)
         else:
-            img = images.resize_image(1, img, size, size)
+            img = images.resize_image(1, img, width, height)
             save_pic(img, index)
 
         shared.state.nextjob()
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 769682ea..5965c5a0 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -6,7 +6,6 @@ import torch
 import tqdm
 import html
 import datetime
-import math
 
 
 from modules import shared, devices, sd_hijack, processing, sd_models
@@ -157,7 +156,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'):
     return fn
 
 
-def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_size, steps, num_repeats, create_image_every, save_embedding_every, template_file):
+def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, num_repeats, create_image_every, save_embedding_every, template_file):
     assert embedding_name, 'embedding not selected'
 
     shared.state.textinfo = "Initializing textual inversion training..."
@@ -183,7 +182,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
 
     shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
     with torch.autocast("cuda"):
-        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, size=training_size, repeats=num_repeats, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file)
+        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, height=training_height, repeats=num_repeats, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file)
 
     hijack = sd_hijack.model_hijack
 
@@ -227,7 +226,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
             loss.backward()
             optimizer.step()
 
-        epoch_num = math.floor(embedding.step / epoch_len)
+        epoch_num = embedding.step // epoch_len
         epoch_step = embedding.step - (epoch_num * epoch_len) + 1
 
         pbar.set_description(f"[Epoch {epoch_num}: {epoch_step}/{epoch_len}]loss: {losses.mean():.7f}")
@@ -243,8 +242,8 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
                 sd_model=shared.sd_model,
                 prompt=text,
                 steps=20,
-                height=training_size,
-                width=training_size,
+				height=training_height,
+				width=training_width,
                 do_not_save_grid=True,
                 do_not_save_samples=True,
             )
diff --git a/modules/ui.py b/modules/ui.py
index f821fd8d..8c06ad7c 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1029,7 +1029,8 @@ def create_ui(wrap_gradio_gpu_call):
 
                     process_src = gr.Textbox(label='Source directory')
                     process_dst = gr.Textbox(label='Destination directory')
-                    process_size = gr.Slider(minimum=64, maximum=2048, step=64, label="Size (width and height)", value=512)
+                    process_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
+                    process_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
 
                     with gr.Row():
                         process_flip = gr.Checkbox(label='Create flipped copies')
@@ -1050,7 +1051,8 @@ def create_ui(wrap_gradio_gpu_call):
                     dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images")
                     log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")
                     template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"))
-                    training_size = gr.Slider(minimum=64, maximum=2048, step=64, label="Size (width and height)", value=512)
+                    training_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
+                    training_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
                     steps = gr.Number(label='Max steps', value=100000, precision=0)
                     num_repeats = gr.Number(label='Number of repeats for a single input image per epoch', value=100, precision=0)
                     create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0)
@@ -1095,7 +1097,8 @@ def create_ui(wrap_gradio_gpu_call):
             inputs=[
                 process_src,
                 process_dst,
-                process_size,
+                process_width,
+                process_height,
                 process_flip,
                 process_split,
                 process_caption,
@@ -1114,7 +1117,8 @@ def create_ui(wrap_gradio_gpu_call):
                 learn_rate,
                 dataset_directory,
                 log_directory,
-                training_size,
+                training_width,
+                training_height,
                 steps,
                 num_repeats,
                 create_image_every,
-- 
cgit v1.2.3


From 8f1efdc130cf7ff47cb8d3722cdfc0dbeba3069e Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 10 Oct 2022 17:03:45 +0300
Subject: --no-half-vae pt2

---
 modules/processing.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index ec8651ae..50ba4fc5 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -405,8 +405,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
                 # use the image collected previously in sampler loop
                 samples_ddim = shared.state.current_latent
 
-            samples_ddim = samples_ddim.to(devices.dtype)
-
+            samples_ddim = samples_ddim.to(devices.dtype_vae)
             x_samples_ddim = decode_first_stage(p.sd_model, samples_ddim)
             x_samples_ddim = torch.clamp((x_samples_ddim + 1.0) / 2.0, min=0.0, max=1.0)
 
-- 
cgit v1.2.3


From ea00c1624bbb0dcb5be07f59c9509061baddf5b1 Mon Sep 17 00:00:00 2001
From: alg-wiki <alg.4chan@gmail.com>
Date: Mon, 10 Oct 2022 17:07:46 +0900
Subject: Textual Inversion: Added custom training image size and number of
 repeats per input image in a single epoch

---
 modules/textual_inversion/dataset.py           |  6 +++---
 modules/textual_inversion/preprocess.py        |  4 ++--
 modules/textual_inversion/textual_inversion.py | 15 ++++++++++++---
 modules/ui.py                                  |  8 +++++++-
 4 files changed, 24 insertions(+), 9 deletions(-)

diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index 7c44ea5b..acc4ce59 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -15,13 +15,13 @@ re_tag = re.compile(r"[a-zA-Z][_\w\d()]+")
 
 
 class PersonalizedBase(Dataset):
-    def __init__(self, data_root, size=None, repeats=100, flip_p=0.5, placeholder_token="*", width=512, height=512, model=None, device=None, template_file=None):
+    def __init__(self, data_root, size, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None):
 
         self.placeholder_token = placeholder_token
 
         self.size = size
-        self.width = width
-        self.height = height
+        self.width = size
+        self.height = size
         self.flip = transforms.RandomHorizontalFlip(p=flip_p)
 
         self.dataset = []
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index f1c002a2..b3de6fd7 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -7,8 +7,8 @@ import tqdm
 from modules import shared, images
 
 
-def preprocess(process_src, process_dst, process_flip, process_split, process_caption):
-    size = 512
+def preprocess(process_src, process_dst, process_size, process_flip, process_split, process_caption):
+    size = process_size
     src = os.path.abspath(process_src)
     dst = os.path.abspath(process_dst)
 
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index cd9f3498..e34dc2e8 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -6,6 +6,7 @@ import torch
 import tqdm
 import html
 import datetime
+import math
 
 
 from modules import shared, devices, sd_hijack, processing, sd_models
@@ -156,7 +157,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'):
     return fn
 
 
-def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps, create_image_every, save_embedding_every, template_file):
+def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_size, steps, num_repeats, create_image_every, save_embedding_every, template_file):
     assert embedding_name, 'embedding not selected'
 
     shared.state.textinfo = "Initializing textual inversion training..."
@@ -182,7 +183,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
 
     shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
     with torch.autocast("cuda"):
-        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, size=512, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file)
+        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, size=training_size, repeats=num_repeats, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file)
 
     hijack = sd_hijack.model_hijack
 
@@ -200,6 +201,9 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
     if ititial_step > steps:
         return embedding, filename
 
+    tr_img_len = len([os.path.join(data_root, file_path) for file_path in os.listdir(data_root)])
+    epoch_len = (tr_img_len * num_repeats) + tr_img_len
+
     pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step)
     for i, (x, text) in pbar:
         embedding.step = i + ititial_step
@@ -223,7 +227,10 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
             loss.backward()
             optimizer.step()
 
-        pbar.set_description(f"loss: {losses.mean():.7f}")
+        epoch_num = math.floor(embedding.step / epoch_len)
+        epoch_step = embedding.step - (epoch_num * epoch_len)
+
+        pbar.set_description(f"[Epoch {epoch_num}: {epoch_step}/{epoch_len}]loss: {losses.mean():.7f}")
 
         if embedding.step > 0 and embedding_dir is not None and embedding.step % save_embedding_every == 0:
             last_saved_file = os.path.join(embedding_dir, f'{embedding_name}-{embedding.step}.pt')
@@ -236,6 +243,8 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
                 sd_model=shared.sd_model,
                 prompt=text,
                 steps=20,
+                height=training_size,
+                width=training_size,
                 do_not_save_grid=True,
                 do_not_save_samples=True,
             )
diff --git a/modules/ui.py b/modules/ui.py
index 2231a8ed..f821fd8d 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1029,6 +1029,7 @@ def create_ui(wrap_gradio_gpu_call):
 
                     process_src = gr.Textbox(label='Source directory')
                     process_dst = gr.Textbox(label='Destination directory')
+                    process_size = gr.Slider(minimum=64, maximum=2048, step=64, label="Size (width and height)", value=512)
 
                     with gr.Row():
                         process_flip = gr.Checkbox(label='Create flipped copies')
@@ -1043,13 +1044,15 @@ def create_ui(wrap_gradio_gpu_call):
                             run_preprocess = gr.Button(value="Preprocess", variant='primary')
 
                 with gr.Group():
-                    gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding; must specify a directory with a set of 512x512 images</p>")
+                    gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding; must specify a directory with a set of 1:1 ratio images</p>")
                     train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
                     learn_rate = gr.Number(label='Learning rate', value=5.0e-03)
                     dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images")
                     log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")
                     template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"))
+                    training_size = gr.Slider(minimum=64, maximum=2048, step=64, label="Size (width and height)", value=512)
                     steps = gr.Number(label='Max steps', value=100000, precision=0)
+                    num_repeats = gr.Number(label='Number of repeats for a single input image per epoch', value=100, precision=0)
                     create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0)
                     save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0)
 
@@ -1092,6 +1095,7 @@ def create_ui(wrap_gradio_gpu_call):
             inputs=[
                 process_src,
                 process_dst,
+                process_size,
                 process_flip,
                 process_split,
                 process_caption,
@@ -1110,7 +1114,9 @@ def create_ui(wrap_gradio_gpu_call):
                 learn_rate,
                 dataset_directory,
                 log_directory,
+                training_size,
                 steps,
+                num_repeats,
                 create_image_every,
                 save_embedding_every,
                 template_file,
-- 
cgit v1.2.3


From 6ad3a53e368d36535de1a4fca73b3bb78fd40654 Mon Sep 17 00:00:00 2001
From: alg-wiki <alg.4chan@gmail.com>
Date: Mon, 10 Oct 2022 17:31:33 +0900
Subject: Fixed progress bar output for epoch

---
 modules/textual_inversion/textual_inversion.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index e34dc2e8..769682ea 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -228,7 +228,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
             optimizer.step()
 
         epoch_num = math.floor(embedding.step / epoch_len)
-        epoch_step = embedding.step - (epoch_num * epoch_len)
+        epoch_step = embedding.step - (epoch_num * epoch_len) + 1
 
         pbar.set_description(f"[Epoch {epoch_num}: {epoch_step}/{epoch_len}]loss: {losses.mean():.7f}")
 
-- 
cgit v1.2.3


From 7a20f914eddfdf09c0ccced157ec108205bc3d0f Mon Sep 17 00:00:00 2001
From: alg-wiki <alg.4chan@gmail.com>
Date: Mon, 10 Oct 2022 22:35:35 +0900
Subject: Custom Width and Height

---
 modules/textual_inversion/dataset.py           |  7 +++----
 modules/textual_inversion/preprocess.py        | 19 ++++++++++---------
 modules/textual_inversion/textual_inversion.py | 11 +++++------
 modules/ui.py                                  | 12 ++++++++----
 4 files changed, 26 insertions(+), 23 deletions(-)

diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index acc4ce59..bcf772d2 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -15,13 +15,12 @@ re_tag = re.compile(r"[a-zA-Z][_\w\d()]+")
 
 
 class PersonalizedBase(Dataset):
-    def __init__(self, data_root, size, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None):
+    def __init__(self, data_root, width, height, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None):
 
         self.placeholder_token = placeholder_token
 
-        self.size = size
-        self.width = size
-        self.height = size
+        self.width = width
+        self.height = height
         self.flip = transforms.RandomHorizontalFlip(p=flip_p)
 
         self.dataset = []
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index b3de6fd7..d7efdef2 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -7,8 +7,9 @@ import tqdm
 from modules import shared, images
 
 
-def preprocess(process_src, process_dst, process_size, process_flip, process_split, process_caption):
-    size = process_size
+def preprocess(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption):
+    width = process_width
+    height = process_height
     src = os.path.abspath(process_src)
     dst = os.path.abspath(process_dst)
 
@@ -55,23 +56,23 @@ def preprocess(process_src, process_dst, process_size, process_flip, process_spl
         is_wide = ratio < 1 / 1.35
 
         if process_split and is_tall:
-            img = img.resize((size, size * img.height // img.width))
+            img = img.resize((width, height * img.height // img.width))
 
-            top = img.crop((0, 0, size, size))
+            top = img.crop((0, 0, width, height))
             save_pic(top, index)
 
-            bot = img.crop((0, img.height - size, size, img.height))
+            bot = img.crop((0, img.height - height, width, img.height))
             save_pic(bot, index)
         elif process_split and is_wide:
-            img = img.resize((size * img.width // img.height, size))
+            img = img.resize((width * img.width // img.height, height))
 
-            left = img.crop((0, 0, size, size))
+            left = img.crop((0, 0, width, height))
             save_pic(left, index)
 
-            right = img.crop((img.width - size, 0, img.width, size))
+            right = img.crop((img.width - width, 0, img.width, height))
             save_pic(right, index)
         else:
-            img = images.resize_image(1, img, size, size)
+            img = images.resize_image(1, img, width, height)
             save_pic(img, index)
 
         shared.state.nextjob()
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 769682ea..5965c5a0 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -6,7 +6,6 @@ import torch
 import tqdm
 import html
 import datetime
-import math
 
 
 from modules import shared, devices, sd_hijack, processing, sd_models
@@ -157,7 +156,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'):
     return fn
 
 
-def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_size, steps, num_repeats, create_image_every, save_embedding_every, template_file):
+def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, num_repeats, create_image_every, save_embedding_every, template_file):
     assert embedding_name, 'embedding not selected'
 
     shared.state.textinfo = "Initializing textual inversion training..."
@@ -183,7 +182,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
 
     shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
     with torch.autocast("cuda"):
-        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, size=training_size, repeats=num_repeats, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file)
+        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, height=training_height, repeats=num_repeats, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file)
 
     hijack = sd_hijack.model_hijack
 
@@ -227,7 +226,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
             loss.backward()
             optimizer.step()
 
-        epoch_num = math.floor(embedding.step / epoch_len)
+        epoch_num = embedding.step // epoch_len
         epoch_step = embedding.step - (epoch_num * epoch_len) + 1
 
         pbar.set_description(f"[Epoch {epoch_num}: {epoch_step}/{epoch_len}]loss: {losses.mean():.7f}")
@@ -243,8 +242,8 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
                 sd_model=shared.sd_model,
                 prompt=text,
                 steps=20,
-                height=training_size,
-                width=training_size,
+				height=training_height,
+				width=training_width,
                 do_not_save_grid=True,
                 do_not_save_samples=True,
             )
diff --git a/modules/ui.py b/modules/ui.py
index f821fd8d..8c06ad7c 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1029,7 +1029,8 @@ def create_ui(wrap_gradio_gpu_call):
 
                     process_src = gr.Textbox(label='Source directory')
                     process_dst = gr.Textbox(label='Destination directory')
-                    process_size = gr.Slider(minimum=64, maximum=2048, step=64, label="Size (width and height)", value=512)
+                    process_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
+                    process_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
 
                     with gr.Row():
                         process_flip = gr.Checkbox(label='Create flipped copies')
@@ -1050,7 +1051,8 @@ def create_ui(wrap_gradio_gpu_call):
                     dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images")
                     log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")
                     template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"))
-                    training_size = gr.Slider(minimum=64, maximum=2048, step=64, label="Size (width and height)", value=512)
+                    training_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
+                    training_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
                     steps = gr.Number(label='Max steps', value=100000, precision=0)
                     num_repeats = gr.Number(label='Number of repeats for a single input image per epoch', value=100, precision=0)
                     create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0)
@@ -1095,7 +1097,8 @@ def create_ui(wrap_gradio_gpu_call):
             inputs=[
                 process_src,
                 process_dst,
-                process_size,
+                process_width,
+                process_height,
                 process_flip,
                 process_split,
                 process_caption,
@@ -1114,7 +1117,8 @@ def create_ui(wrap_gradio_gpu_call):
                 learn_rate,
                 dataset_directory,
                 log_directory,
-                training_size,
+                training_width,
+                training_height,
                 steps,
                 num_repeats,
                 create_image_every,
-- 
cgit v1.2.3


From ce37fdd30e9fc0fe0bc5805a068ce8b11b42b5a3 Mon Sep 17 00:00:00 2001
From: Ben <110583491+TheLastBen@users.noreply.github.com>
Date: Sat, 8 Oct 2022 22:03:00 +0100
Subject: maximize the view

---
 style.css | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/style.css b/style.css
index c0c3f2bb..04bb9576 100644
--- a/style.css
+++ b/style.css
@@ -1,3 +1,7 @@
+.container {
+    max-width: 100%;
+}
+
 .output-html p {margin: 0 0.5em;}
 
 .row > *,
-- 
cgit v1.2.3


From 707a431100362645e914042bb344d08439f48ac8 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Mon, 10 Oct 2022 15:34:49 +0100
Subject: add pixel data footer

---
 modules/textual_inversion/textual_inversion.py | 48 ++++++++++++++++++++++++--
 1 file changed, 46 insertions(+), 2 deletions(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 7a24192e..6fb64691 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -12,6 +12,7 @@ from ..images import captionImageOverlay
 import numpy as np
 import base64
 import json
+import zlib
 
 from modules import shared, devices, sd_hijack, processing, sd_models
 import modules.textual_inversion.dataset
@@ -20,7 +21,7 @@ class EmbeddingEncoder(json.JSONEncoder):
     def default(self, obj):
         if isinstance(obj, torch.Tensor):
             return {'TORCHTENSOR':obj.cpu().detach().numpy().tolist()}
-        return json.JSONEncoder.default(self, o)
+        return json.JSONEncoder.default(self, obj)
 
 class EmbeddingDecoder(json.JSONDecoder):
     def __init__(self, *args, **kwargs):
@@ -38,6 +39,45 @@ def embeddingFromB64(data):
     d = base64.b64decode(data)
     return json.loads(d,cls=EmbeddingDecoder)
 
+def appendImageDataFooter(image,data):
+    d = 3
+    data_compressed = zlib.compress( json.dumps(data,cls=EmbeddingEncoder).encode(),level=9)
+    dnp = np.frombuffer(data_compressed,np.uint8).copy()
+    w = image.size[0]
+    next_size = dnp.shape[0] + (w-(dnp.shape[0]%w))
+    next_size = next_size + ((w*d)-(next_size%(w*d)))
+    dnp.resize(next_size)
+    dnp = dnp.reshape((-1,w,d))
+    print(dnp.shape)
+    im = Image.fromarray(dnp,mode='RGB')
+    background = Image.new('RGB',(image.size[0],image.size[1]+im.size[1]+1),(0,0,0))
+    background.paste(image,(0,0))
+    background.paste(im,(0,image.size[1]+1))
+    return background
+
+def crop_black(img,tol=0):
+    mask = (img>tol).all(2)
+    mask0,mask1 = mask.any(0),mask.any(1)
+    col_start,col_end = mask0.argmax(),mask.shape[1]-mask0[::-1].argmax()
+    row_start,row_end = mask1.argmax(),mask.shape[0]-mask1[::-1].argmax()
+    return img[row_start:row_end,col_start:col_end]
+
+def extractImageDataFooter(image):
+    d=3
+    outarr = crop_black(np.array(image.getdata()).reshape(image.size[1],image.size[0],d ).astype(np.uint8) )
+    lastRow = np.where( np.sum(outarr, axis=(1,2))==0)
+    if lastRow[0].shape[0] == 0:
+        print('Image data block not found.')
+        return None
+    lastRow = lastRow[0]
+    
+    lastRow = lastRow.max()
+
+    dataBlock = outarr[lastRow+1::].astype(np.uint8).flatten().tobytes()
+    print(lastRow)
+    data = zlib.decompress(dataBlock)
+    return json.loads(data,cls=EmbeddingDecoder)
+
 class Embedding:
     def __init__(self, vec, name, step=None):
         self.vec = vec
@@ -113,6 +153,9 @@ class EmbeddingDatabase:
                 if 'sd-ti-embedding' in embed_image.text:
                     data = embeddingFromB64(embed_image.text['sd-ti-embedding'])
                     name = data.get('name',name)
+                else:
+                    data = extractImageDataFooter(embed_image)
+                    name = data.get('name',name)
             else:
                 data = torch.load(path, map_location="cpu")
 
@@ -190,7 +233,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'):
     return fn
 
 
-def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, num_repeats, create_image_every, save_embedding_every, template_file):
+def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, num_repeats, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding):
     assert embedding_name, 'embedding not selected'
 
     shared.state.textinfo = "Initializing textual inversion training..."
@@ -308,6 +351,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
                 footer_right = '{}'.format(embedding.step)
 
                 captioned_image = captionImageOverlay(image,title,footer_left,footer_mid,footer_right)
+                captioned_image = appendImageDataFooter(captioned_image,data)
 
                 captioned_image.save(last_saved_image_chunks, "PNG", pnginfo=info)
             
-- 
cgit v1.2.3


From df6d0d9286279c41c4c67460c3158fa268697524 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Mon, 10 Oct 2022 15:43:09 +0100
Subject: convert back to rgb as some hosts add alpha

---
 modules/textual_inversion/textual_inversion.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 6fb64691..667a7cf2 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -64,7 +64,7 @@ def crop_black(img,tol=0):
 
 def extractImageDataFooter(image):
     d=3
-    outarr = crop_black(np.array(image.getdata()).reshape(image.size[1],image.size[0],d ).astype(np.uint8) )
+    outarr = crop_black(np.array(image.convert('RGB').getdata()).reshape(image.size[1],image.size[0],d ).astype(np.uint8) )
     lastRow = np.where( np.sum(outarr, axis=(1,2))==0)
     if lastRow[0].shape[0] == 0:
         print('Image data block not found.')
-- 
cgit v1.2.3


From f347ddfd808c56bb1bacdec0c4bedf826ff85cd8 Mon Sep 17 00:00:00 2001
From: RW21 <rinze.watanabe.translation@gmail.com>
Date: Mon, 10 Oct 2022 10:44:11 +0900
Subject: Remove max_batch_count from ui.py

---
 modules/ui.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/modules/ui.py b/modules/ui.py
index 8c06ad7c..8ba84911 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -524,7 +524,7 @@ def create_ui(wrap_gradio_gpu_call):
                     denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7)
 
                 with gr.Row():
-                    batch_count = gr.Slider(minimum=1, maximum=cmd_opts.max_batch_count, step=1, label='Batch count', value=1)
+                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1)
                     batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1)
 
                 cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0)
@@ -710,7 +710,7 @@ def create_ui(wrap_gradio_gpu_call):
                     tiling = gr.Checkbox(label='Tiling', value=False)
 
                 with gr.Row():
-                    batch_count = gr.Slider(minimum=1, maximum=cmd_opts.max_batch_count, step=1, label='Batch count', value=1)
+                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1)
                     batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1)
 
                 with gr.Group():
-- 
cgit v1.2.3


From b340439586d844e76782149ca1857c8de35773ec Mon Sep 17 00:00:00 2001
From: hentailord85ez <112723046+hentailord85ez@users.noreply.github.com>
Date: Mon, 10 Oct 2022 05:28:06 +0100
Subject: Unlimited Token Works

Unlimited tokens actually work now. Works with textual inversion too. Replaces the previous not-so-much-working implementation.
---
 modules/sd_hijack.py | 69 ++++++++++++++++++++++++++++++++++------------------
 1 file changed, 46 insertions(+), 23 deletions(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 437acce4..8d5c77d8 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -43,10 +43,7 @@ def undo_optimizations():
 
 
 def get_target_prompt_token_count(token_count):
-    if token_count < 75:
-        return 75
-
-    return math.ceil(token_count / 10) * 10
+    return math.ceil(max(token_count, 1) / 75) * 75
 
 
 class StableDiffusionModelHijack:
@@ -127,7 +124,6 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
                 self.token_mults[ident] = mult
 
     def tokenize_line(self, line, used_custom_terms, hijack_comments):
-        id_start = self.wrapped.tokenizer.bos_token_id
         id_end = self.wrapped.tokenizer.eos_token_id
 
         if opts.enable_emphasis:
@@ -154,7 +150,8 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
                     i += 1
                 else:
                     emb_len = int(embedding.vec.shape[0])
-                    fixes.append((len(remade_tokens), embedding))
+                    iteration = len(remade_tokens) // 75
+                    fixes.append((iteration, (len(remade_tokens) % 75, embedding)))
                     remade_tokens += [0] * emb_len
                     multipliers += [weight] * emb_len
                     used_custom_terms.append((embedding.name, embedding.checksum()))
@@ -162,10 +159,10 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
 
         token_count = len(remade_tokens)
         prompt_target_length = get_target_prompt_token_count(token_count)
-        tokens_to_add = prompt_target_length - len(remade_tokens) + 1
+        tokens_to_add = prompt_target_length - len(remade_tokens)
 
-        remade_tokens = [id_start] + remade_tokens + [id_end] * tokens_to_add
-        multipliers = [1.0] + multipliers + [1.0] * tokens_to_add
+        remade_tokens = remade_tokens + [id_end] * tokens_to_add
+        multipliers = multipliers + [1.0] * tokens_to_add
 
         return remade_tokens, fixes, multipliers, token_count
 
@@ -260,29 +257,55 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
             hijack_fixes.append(fixes)
             batch_multipliers.append(multipliers)
         return batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count
-
+    
     def forward(self, text):
-
-        if opts.use_old_emphasis_implementation:
+        use_old = opts.use_old_emphasis_implementation
+        if use_old:
             batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = self.process_text_old(text)
         else:
             batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = self.process_text(text)
 
-        self.hijack.fixes = hijack_fixes
         self.hijack.comments += hijack_comments
 
         if len(used_custom_terms) > 0:
             self.hijack.comments.append("Used embeddings: " + ", ".join([f'{word} [{checksum}]' for word, checksum in used_custom_terms]))
+        
+        if use_old:
+            self.hijack.fixes = hijack_fixes
+            return self.process_tokens(remade_batch_tokens, batch_multipliers)
+        
+        z = None
+        i = 0
+        while max(map(len, remade_batch_tokens)) != 0:
+            rem_tokens = [x[75:] for x in remade_batch_tokens]
+            rem_multipliers = [x[75:] for x in batch_multipliers]
+            
+            self.hijack.fixes = []
+            for unfiltered in hijack_fixes:
+                fixes = []
+                for fix in unfiltered:
+                    if fix[0] == i:
+                        fixes.append(fix[1])
+                self.hijack.fixes.append(fixes)
+            
+            z1 = self.process_tokens([x[:75] for x in remade_batch_tokens], [x[:75] for x in batch_multipliers])
+            z = z1 if z is None else torch.cat((z, z1), axis=-2)
+            
+            remade_batch_tokens = rem_tokens
+            batch_multipliers = rem_multipliers
+            i += 1
+        
+        return z
+        
+    
+    def process_tokens(self, remade_batch_tokens, batch_multipliers):
+        if not opts.use_old_emphasis_implementation:
+            remade_batch_tokens = [[self.wrapped.tokenizer.bos_token_id] + x[:75] + [self.wrapped.tokenizer.eos_token_id] for x in remade_batch_tokens]
+            batch_multipliers = [[1.0] + x[:75] + [1.0] for x in batch_multipliers]
+        
+        tokens = torch.asarray(remade_batch_tokens).to(device)
+        outputs = self.wrapped.transformer(input_ids=tokens)
 
-        target_token_count = get_target_prompt_token_count(token_count) + 2
-
-        position_ids_array = [min(x, 75) for x in range(target_token_count-1)] + [76]
-        position_ids = torch.asarray(position_ids_array, device=devices.device).expand((1, -1))
-
-        remade_batch_tokens_of_same_length = [x + [self.wrapped.tokenizer.eos_token_id] * (target_token_count - len(x)) for x in remade_batch_tokens]
-        tokens = torch.asarray(remade_batch_tokens_of_same_length).to(device)
-
-        outputs = self.wrapped.transformer(input_ids=tokens, position_ids=position_ids, output_hidden_states=-opts.CLIP_stop_at_last_layers)
         if opts.CLIP_stop_at_last_layers > 1:
             z = outputs.hidden_states[-opts.CLIP_stop_at_last_layers]
             z = self.wrapped.transformer.text_model.final_layer_norm(z)
@@ -290,7 +313,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
             z = outputs.last_hidden_state
 
         # restoring original mean is likely not correct, but it seems to work well to prevent artifacts that happen otherwise
-        batch_multipliers_of_same_length = [x + [1.0] * (target_token_count - len(x)) for x in batch_multipliers]
+        batch_multipliers_of_same_length = [x + [1.0] * (75 - len(x)) for x in batch_multipliers]
         batch_multipliers = torch.asarray(batch_multipliers_of_same_length).to(device)
         original_mean = z.mean()
         z *= batch_multipliers.reshape(batch_multipliers.shape + (1,)).expand(z.shape)
-- 
cgit v1.2.3


From 460bbae58726c177beddfcddf351f27e205d3fb2 Mon Sep 17 00:00:00 2001
From: hentailord85ez <112723046+hentailord85ez@users.noreply.github.com>
Date: Mon, 10 Oct 2022 16:09:06 +0100
Subject: Pad beginning of textual inversion embedding

---
 modules/sd_hijack.py | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 8d5c77d8..3a60cd63 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -151,6 +151,11 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
                 else:
                     emb_len = int(embedding.vec.shape[0])
                     iteration = len(remade_tokens) // 75
+                    if (len(remade_tokens) + emb_len) // 75 != iteration:
+                        rem = (75 * (iteration + 1) - len(remade_tokens))
+                        remade_tokens += [id_end] * rem
+                        multipliers += [1.0] * rem
+                        iteration += 1
                     fixes.append((iteration, (len(remade_tokens) % 75, embedding)))
                     remade_tokens += [0] * emb_len
                     multipliers += [weight] * emb_len
-- 
cgit v1.2.3


From d5c14365fd468dbf89fa12a68bea5b217077273c Mon Sep 17 00:00:00 2001
From: hentailord85ez <112723046+hentailord85ez@users.noreply.github.com>
Date: Mon, 10 Oct 2022 16:13:47 +0100
Subject: Add back in output hidden states parameter

---
 modules/sd_hijack.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 3a60cd63..3edc0e9d 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -309,7 +309,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
             batch_multipliers = [[1.0] + x[:75] + [1.0] for x in batch_multipliers]
         
         tokens = torch.asarray(remade_batch_tokens).to(device)
-        outputs = self.wrapped.transformer(input_ids=tokens)
+        outputs = self.wrapped.transformer(input_ids=tokens, output_hidden_states=-opts.CLIP_stop_at_last_layers)
 
         if opts.CLIP_stop_at_last_layers > 1:
             z = outputs.hidden_states[-opts.CLIP_stop_at_last_layers]
-- 
cgit v1.2.3


From 6c36fe5719a824fa18f6ad3e02727783f095bc5f Mon Sep 17 00:00:00 2001
From: Melan <alexleander91@gmail.com>
Date: Mon, 10 Oct 2022 18:16:04 +0200
Subject: Add ctrl+enter as a shortcut to quickly start a generation.

---
 script.js | 16 ++++++++++++++++
 1 file changed, 16 insertions(+)

diff --git a/script.js b/script.js
index cf989605..a92c0f77 100644
--- a/script.js
+++ b/script.js
@@ -40,6 +40,22 @@ document.addEventListener("DOMContentLoaded", function() {
     mutationObserver.observe( gradioApp(), { childList:true, subtree:true })
 });
 
+/**
+ * Add a ctrl+enter as a shortcut to start a generation
+ */
+ document.addEventListener('keydown', function(e) {
+    var handled = false;
+    if (e.key !== undefined) {
+        if((e.key == "Enter" && (e.metaKey || e.ctrlKey))) handled = true;
+    } else if (e.keyCode !== undefined) {
+        if((e.keyCode == 13 && (e.metaKey || e.ctrlKey))) handled = true;
+    }
+    if (handled) { 
+        gradioApp().querySelector("#txt2img_generate").click(); 
+        e.preventDefault();
+    }
+})
+
 /**
  * checks that a UI element is not in another hidden element or tab content
  */
-- 
cgit v1.2.3


From 9d33baba587637815d818e5e641d8f8b74c4900d Mon Sep 17 00:00:00 2001
From: Vladimir Repin <32306715+mezotaken@users.noreply.github.com>
Date: Mon, 10 Oct 2022 18:46:48 +0300
Subject: Always show previous mask and fix extras_send dest

---
 modules/ui.py | 2 +-
 style.css     | 7 +++++++
 2 files changed, 8 insertions(+), 1 deletion(-)

diff --git a/modules/ui.py b/modules/ui.py
index 8ba84911..e8039d76 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -961,7 +961,7 @@ def create_ui(wrap_gradio_gpu_call):
         
         extras_send_to_inpaint.click(
             fn=lambda x: image_from_url_text(x),
-            _js="extract_image_from_gallery_img2img",
+            _js="extract_image_from_gallery_inpaint",
             inputs=[result_images],
             outputs=[init_img_with_mask],
         )
diff --git a/style.css b/style.css
index 04bb9576..00a3d07f 100644
--- a/style.css
+++ b/style.css
@@ -467,3 +467,10 @@ input[type="range"]{
     max-width: 32em;
     padding: 0;
 }
+
+canvas[key="mask"] {
+    z-index: 12 !important;
+    filter: invert();
+    mix-blend-mode: multiply;
+    pointer-events: none;
+}
-- 
cgit v1.2.3


From b8c38f2bbfa28904f67f0c4f9cabab4d85ebced2 Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Mon, 10 Oct 2022 17:44:58 +0300
Subject: change prebuilt wheel

---
 launch.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/launch.py b/launch.py
index f42f557d..e1000f55 100644
--- a/launch.py
+++ b/launch.py
@@ -127,7 +127,7 @@ def prepare_enviroment():
 
     if not is_installed("xformers") and xformers and platform.python_version().startswith("3.10"):
         if platform.system() == "Windows":
-            run_pip("install https://github.com/C43H66N12O12S2/stable-diffusion-webui/releases/download/a/xformers-0.0.14.dev0-cp310-cp310-win_amd64.whl", "xformers")
+            run_pip("install https://github.com/C43H66N12O12S2/stable-diffusion-webui/releases/download/c/xformers-0.0.14.dev0-cp310-cp310-win_amd64.whl", "xformers")
         elif platform.system() == "Linux":
             run_pip("install xformers", "xformers")
 
-- 
cgit v1.2.3


From 623251ce2b8d152e242011f62984a8247a14a389 Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Mon, 10 Oct 2022 17:45:38 +0300
Subject: allow pascal onwards

---
 modules/sd_hijack.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 3edc0e9d..827bf304 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -23,7 +23,7 @@ def apply_optimizations():
 
     ldm.modules.diffusionmodules.model.nonlinearity = silu
 
-    if cmd_opts.force_enable_xformers or (cmd_opts.xformers and shared.xformers_available and torch.version.cuda and torch.cuda.get_device_capability(shared.device) == (8, 6)):
+    if cmd_opts.force_enable_xformers or (cmd_opts.xformers and shared.xformers_available and torch.version.cuda and (6, 0) <= torch.cuda.get_device_capability(shared.device) <= (8, 6)):
         print("Applying xformers cross attention optimization.")
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward
         ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.xformers_attnblock_forward
-- 
cgit v1.2.3


From 3e7a981194ed9c454e951365846e4eba66fa7095 Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Mon, 10 Oct 2022 17:51:05 +0300
Subject: remove functorch

---
 modules/sd_hijack_optimizations.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index 634fb4b2..18408e62 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -13,8 +13,6 @@ from modules import shared
 if shared.cmd_opts.xformers or shared.cmd_opts.force_enable_xformers:
     try:
         import xformers.ops
-        import functorch
-        xformers._is_functorch_available = True
         shared.xformers_available = True
     except Exception:
         print("Cannot import xformers", file=sys.stderr)
-- 
cgit v1.2.3


From 5c3254b3ee62ef46cb2e3a6ed14182efeb868f30 Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Mon, 10 Oct 2022 17:51:41 +0300
Subject: Update requirements.txt

---
 requirements.txt | 1 -
 1 file changed, 1 deletion(-)

diff --git a/requirements.txt b/requirements.txt
index 81641d68..631fe616 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -23,4 +23,3 @@ resize-right
 torchdiffeq
 kornia
 lark
-functorch
-- 
cgit v1.2.3


From e37d0cdd06772c8d6edb2272c0ef25c46c74cc6d Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Mon, 10 Oct 2022 17:51:53 +0300
Subject: Update requirements_versions.txt

---
 requirements_versions.txt | 1 -
 1 file changed, 1 deletion(-)

diff --git a/requirements_versions.txt b/requirements_versions.txt
index fec3e9d5..fdff2687 100644
--- a/requirements_versions.txt
+++ b/requirements_versions.txt
@@ -22,4 +22,3 @@ resize-right==0.0.2
 torchdiffeq==0.2.3
 kornia==0.6.7
 lark==1.1.2
-functorch==0.2.1
-- 
cgit v1.2.3


From ece27fe98933eb0eda8ea94dc496dd7554f3a08f Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Sun, 9 Oct 2022 18:55:33 +0300
Subject: Add files via upload

---
 modules/swinir_model_arch_v2.py | 1017 +++++++++++++++++++++++++++++++++++++++
 1 file changed, 1017 insertions(+)
 create mode 100644 modules/swinir_model_arch_v2.py

diff --git a/modules/swinir_model_arch_v2.py b/modules/swinir_model_arch_v2.py
new file mode 100644
index 00000000..0e28ae6e
--- /dev/null
+++ b/modules/swinir_model_arch_v2.py
@@ -0,0 +1,1017 @@
+# -----------------------------------------------------------------------------------
+# Swin2SR: Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restoration, https://arxiv.org/abs/
+# Written by Conde and Choi et al.
+# -----------------------------------------------------------------------------------
+
+import math
+import numpy as np
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+import torch.utils.checkpoint as checkpoint
+from timm.models.layers import DropPath, to_2tuple, trunc_normal_
+
+
+class Mlp(nn.Module):
+    def __init__(self, in_features, hidden_features=None, out_features=None, act_layer=nn.GELU, drop=0.):
+        super().__init__()
+        out_features = out_features or in_features
+        hidden_features = hidden_features or in_features
+        self.fc1 = nn.Linear(in_features, hidden_features)
+        self.act = act_layer()
+        self.fc2 = nn.Linear(hidden_features, out_features)
+        self.drop = nn.Dropout(drop)
+
+    def forward(self, x):
+        x = self.fc1(x)
+        x = self.act(x)
+        x = self.drop(x)
+        x = self.fc2(x)
+        x = self.drop(x)
+        return x
+
+
+def window_partition(x, window_size):
+    """
+    Args:
+        x: (B, H, W, C)
+        window_size (int): window size
+    Returns:
+        windows: (num_windows*B, window_size, window_size, C)
+    """
+    B, H, W, C = x.shape
+    x = x.view(B, H // window_size, window_size, W // window_size, window_size, C)
+    windows = x.permute(0, 1, 3, 2, 4, 5).contiguous().view(-1, window_size, window_size, C)
+    return windows
+
+
+def window_reverse(windows, window_size, H, W):
+    """
+    Args:
+        windows: (num_windows*B, window_size, window_size, C)
+        window_size (int): Window size
+        H (int): Height of image
+        W (int): Width of image
+    Returns:
+        x: (B, H, W, C)
+    """
+    B = int(windows.shape[0] / (H * W / window_size / window_size))
+    x = windows.view(B, H // window_size, W // window_size, window_size, window_size, -1)
+    x = x.permute(0, 1, 3, 2, 4, 5).contiguous().view(B, H, W, -1)
+    return x
+
+class WindowAttention(nn.Module):
+    r""" Window based multi-head self attention (W-MSA) module with relative position bias.
+    It supports both of shifted and non-shifted window.
+    Args:
+        dim (int): Number of input channels.
+        window_size (tuple[int]): The height and width of the window.
+        num_heads (int): Number of attention heads.
+        qkv_bias (bool, optional):  If True, add a learnable bias to query, key, value. Default: True
+        attn_drop (float, optional): Dropout ratio of attention weight. Default: 0.0
+        proj_drop (float, optional): Dropout ratio of output. Default: 0.0
+        pretrained_window_size (tuple[int]): The height and width of the window in pre-training.
+    """
+
+    def __init__(self, dim, window_size, num_heads, qkv_bias=True, attn_drop=0., proj_drop=0.,
+                 pretrained_window_size=[0, 0]):
+
+        super().__init__()
+        self.dim = dim
+        self.window_size = window_size  # Wh, Ww
+        self.pretrained_window_size = pretrained_window_size
+        self.num_heads = num_heads
+
+        self.logit_scale = nn.Parameter(torch.log(10 * torch.ones((num_heads, 1, 1))), requires_grad=True)
+
+        # mlp to generate continuous relative position bias
+        self.cpb_mlp = nn.Sequential(nn.Linear(2, 512, bias=True),
+                                     nn.ReLU(inplace=True),
+                                     nn.Linear(512, num_heads, bias=False))
+
+        # get relative_coords_table
+        relative_coords_h = torch.arange(-(self.window_size[0] - 1), self.window_size[0], dtype=torch.float32)
+        relative_coords_w = torch.arange(-(self.window_size[1] - 1), self.window_size[1], dtype=torch.float32)
+        relative_coords_table = torch.stack(
+            torch.meshgrid([relative_coords_h,
+                            relative_coords_w])).permute(1, 2, 0).contiguous().unsqueeze(0)  # 1, 2*Wh-1, 2*Ww-1, 2
+        if pretrained_window_size[0] > 0:
+            relative_coords_table[:, :, :, 0] /= (pretrained_window_size[0] - 1)
+            relative_coords_table[:, :, :, 1] /= (pretrained_window_size[1] - 1)
+        else:
+            relative_coords_table[:, :, :, 0] /= (self.window_size[0] - 1)
+            relative_coords_table[:, :, :, 1] /= (self.window_size[1] - 1)
+        relative_coords_table *= 8  # normalize to -8, 8
+        relative_coords_table = torch.sign(relative_coords_table) * torch.log2(
+            torch.abs(relative_coords_table) + 1.0) / np.log2(8)
+
+        self.register_buffer("relative_coords_table", relative_coords_table)
+
+        # get pair-wise relative position index for each token inside the window
+        coords_h = torch.arange(self.window_size[0])
+        coords_w = torch.arange(self.window_size[1])
+        coords = torch.stack(torch.meshgrid([coords_h, coords_w]))  # 2, Wh, Ww
+        coords_flatten = torch.flatten(coords, 1)  # 2, Wh*Ww
+        relative_coords = coords_flatten[:, :, None] - coords_flatten[:, None, :]  # 2, Wh*Ww, Wh*Ww
+        relative_coords = relative_coords.permute(1, 2, 0).contiguous()  # Wh*Ww, Wh*Ww, 2
+        relative_coords[:, :, 0] += self.window_size[0] - 1  # shift to start from 0
+        relative_coords[:, :, 1] += self.window_size[1] - 1
+        relative_coords[:, :, 0] *= 2 * self.window_size[1] - 1
+        relative_position_index = relative_coords.sum(-1)  # Wh*Ww, Wh*Ww
+        self.register_buffer("relative_position_index", relative_position_index)
+
+        self.qkv = nn.Linear(dim, dim * 3, bias=False)
+        if qkv_bias:
+            self.q_bias = nn.Parameter(torch.zeros(dim))
+            self.v_bias = nn.Parameter(torch.zeros(dim))
+        else:
+            self.q_bias = None
+            self.v_bias = None
+        self.attn_drop = nn.Dropout(attn_drop)
+        self.proj = nn.Linear(dim, dim)
+        self.proj_drop = nn.Dropout(proj_drop)
+        self.softmax = nn.Softmax(dim=-1)
+
+    def forward(self, x, mask=None):
+        """
+        Args:
+            x: input features with shape of (num_windows*B, N, C)
+            mask: (0/-inf) mask with shape of (num_windows, Wh*Ww, Wh*Ww) or None
+        """
+        B_, N, C = x.shape
+        qkv_bias = None
+        if self.q_bias is not None:
+            qkv_bias = torch.cat((self.q_bias, torch.zeros_like(self.v_bias, requires_grad=False), self.v_bias))
+        qkv = F.linear(input=x, weight=self.qkv.weight, bias=qkv_bias)
+        qkv = qkv.reshape(B_, N, 3, self.num_heads, -1).permute(2, 0, 3, 1, 4)
+        q, k, v = qkv[0], qkv[1], qkv[2]  # make torchscript happy (cannot use tensor as tuple)
+
+        # cosine attention
+        attn = (F.normalize(q, dim=-1) @ F.normalize(k, dim=-1).transpose(-2, -1))
+        logit_scale = torch.clamp(self.logit_scale, max=torch.log(torch.tensor(1. / 0.01)).to(self.logit_scale.device)).exp()
+        attn = attn * logit_scale
+
+        relative_position_bias_table = self.cpb_mlp(self.relative_coords_table).view(-1, self.num_heads)
+        relative_position_bias = relative_position_bias_table[self.relative_position_index.view(-1)].view(
+            self.window_size[0] * self.window_size[1], self.window_size[0] * self.window_size[1], -1)  # Wh*Ww,Wh*Ww,nH
+        relative_position_bias = relative_position_bias.permute(2, 0, 1).contiguous()  # nH, Wh*Ww, Wh*Ww
+        relative_position_bias = 16 * torch.sigmoid(relative_position_bias)
+        attn = attn + relative_position_bias.unsqueeze(0)
+
+        if mask is not None:
+            nW = mask.shape[0]
+            attn = attn.view(B_ // nW, nW, self.num_heads, N, N) + mask.unsqueeze(1).unsqueeze(0)
+            attn = attn.view(-1, self.num_heads, N, N)
+            attn = self.softmax(attn)
+        else:
+            attn = self.softmax(attn)
+
+        attn = self.attn_drop(attn)
+
+        x = (attn @ v).transpose(1, 2).reshape(B_, N, C)
+        x = self.proj(x)
+        x = self.proj_drop(x)
+        return x
+
+    def extra_repr(self) -> str:
+        return f'dim={self.dim}, window_size={self.window_size}, ' \
+               f'pretrained_window_size={self.pretrained_window_size}, num_heads={self.num_heads}'
+
+    def flops(self, N):
+        # calculate flops for 1 window with token length of N
+        flops = 0
+        # qkv = self.qkv(x)
+        flops += N * self.dim * 3 * self.dim
+        # attn = (q @ k.transpose(-2, -1))
+        flops += self.num_heads * N * (self.dim // self.num_heads) * N
+        #  x = (attn @ v)
+        flops += self.num_heads * N * N * (self.dim // self.num_heads)
+        # x = self.proj(x)
+        flops += N * self.dim * self.dim
+        return flops
+
+class SwinTransformerBlock(nn.Module):
+    r""" Swin Transformer Block.
+    Args:
+        dim (int): Number of input channels.
+        input_resolution (tuple[int]): Input resulotion.
+        num_heads (int): Number of attention heads.
+        window_size (int): Window size.
+        shift_size (int): Shift size for SW-MSA.
+        mlp_ratio (float): Ratio of mlp hidden dim to embedding dim.
+        qkv_bias (bool, optional): If True, add a learnable bias to query, key, value. Default: True
+        drop (float, optional): Dropout rate. Default: 0.0
+        attn_drop (float, optional): Attention dropout rate. Default: 0.0
+        drop_path (float, optional): Stochastic depth rate. Default: 0.0
+        act_layer (nn.Module, optional): Activation layer. Default: nn.GELU
+        norm_layer (nn.Module, optional): Normalization layer.  Default: nn.LayerNorm
+        pretrained_window_size (int): Window size in pre-training.
+    """
+
+    def __init__(self, dim, input_resolution, num_heads, window_size=7, shift_size=0,
+                 mlp_ratio=4., qkv_bias=True, drop=0., attn_drop=0., drop_path=0.,
+                 act_layer=nn.GELU, norm_layer=nn.LayerNorm, pretrained_window_size=0):
+        super().__init__()
+        self.dim = dim
+        self.input_resolution = input_resolution
+        self.num_heads = num_heads
+        self.window_size = window_size
+        self.shift_size = shift_size
+        self.mlp_ratio = mlp_ratio
+        if min(self.input_resolution) <= self.window_size:
+            # if window size is larger than input resolution, we don't partition windows
+            self.shift_size = 0
+            self.window_size = min(self.input_resolution)
+        assert 0 <= self.shift_size < self.window_size, "shift_size must in 0-window_size"
+
+        self.norm1 = norm_layer(dim)
+        self.attn = WindowAttention(
+            dim, window_size=to_2tuple(self.window_size), num_heads=num_heads,
+            qkv_bias=qkv_bias, attn_drop=attn_drop, proj_drop=drop,
+            pretrained_window_size=to_2tuple(pretrained_window_size))
+
+        self.drop_path = DropPath(drop_path) if drop_path > 0. else nn.Identity()
+        self.norm2 = norm_layer(dim)
+        mlp_hidden_dim = int(dim * mlp_ratio)
+        self.mlp = Mlp(in_features=dim, hidden_features=mlp_hidden_dim, act_layer=act_layer, drop=drop)
+
+        if self.shift_size > 0:
+            attn_mask = self.calculate_mask(self.input_resolution)
+        else:
+            attn_mask = None
+
+        self.register_buffer("attn_mask", attn_mask)
+        
+    def calculate_mask(self, x_size):
+        # calculate attention mask for SW-MSA
+        H, W = x_size
+        img_mask = torch.zeros((1, H, W, 1))  # 1 H W 1
+        h_slices = (slice(0, -self.window_size),
+                    slice(-self.window_size, -self.shift_size),
+                    slice(-self.shift_size, None))
+        w_slices = (slice(0, -self.window_size),
+                    slice(-self.window_size, -self.shift_size),
+                    slice(-self.shift_size, None))
+        cnt = 0
+        for h in h_slices:
+            for w in w_slices:
+                img_mask[:, h, w, :] = cnt
+                cnt += 1
+
+        mask_windows = window_partition(img_mask, self.window_size)  # nW, window_size, window_size, 1
+        mask_windows = mask_windows.view(-1, self.window_size * self.window_size)
+        attn_mask = mask_windows.unsqueeze(1) - mask_windows.unsqueeze(2)
+        attn_mask = attn_mask.masked_fill(attn_mask != 0, float(-100.0)).masked_fill(attn_mask == 0, float(0.0))
+
+        return attn_mask        
+
+    def forward(self, x, x_size):
+        H, W = x_size
+        B, L, C = x.shape
+        #assert L == H * W, "input feature has wrong size"
+
+        shortcut = x
+        x = x.view(B, H, W, C)
+
+        # cyclic shift
+        if self.shift_size > 0:
+            shifted_x = torch.roll(x, shifts=(-self.shift_size, -self.shift_size), dims=(1, 2))
+        else:
+            shifted_x = x
+
+        # partition windows
+        x_windows = window_partition(shifted_x, self.window_size)  # nW*B, window_size, window_size, C
+        x_windows = x_windows.view(-1, self.window_size * self.window_size, C)  # nW*B, window_size*window_size, C
+
+        # W-MSA/SW-MSA (to be compatible for testing on images whose shapes are the multiple of window size
+        if self.input_resolution == x_size:
+            attn_windows = self.attn(x_windows, mask=self.attn_mask)  # nW*B, window_size*window_size, C
+        else:
+            attn_windows = self.attn(x_windows, mask=self.calculate_mask(x_size).to(x.device))
+            
+        # merge windows
+        attn_windows = attn_windows.view(-1, self.window_size, self.window_size, C)
+        shifted_x = window_reverse(attn_windows, self.window_size, H, W)  # B H' W' C
+
+        # reverse cyclic shift
+        if self.shift_size > 0:
+            x = torch.roll(shifted_x, shifts=(self.shift_size, self.shift_size), dims=(1, 2))
+        else:
+            x = shifted_x
+        x = x.view(B, H * W, C)
+        x = shortcut + self.drop_path(self.norm1(x))
+
+        # FFN
+        x = x + self.drop_path(self.norm2(self.mlp(x)))
+
+        return x
+
+    def extra_repr(self) -> str:
+        return f"dim={self.dim}, input_resolution={self.input_resolution}, num_heads={self.num_heads}, " \
+               f"window_size={self.window_size}, shift_size={self.shift_size}, mlp_ratio={self.mlp_ratio}"
+
+    def flops(self):
+        flops = 0
+        H, W = self.input_resolution
+        # norm1
+        flops += self.dim * H * W
+        # W-MSA/SW-MSA
+        nW = H * W / self.window_size / self.window_size
+        flops += nW * self.attn.flops(self.window_size * self.window_size)
+        # mlp
+        flops += 2 * H * W * self.dim * self.dim * self.mlp_ratio
+        # norm2
+        flops += self.dim * H * W
+        return flops
+
+class PatchMerging(nn.Module):
+    r""" Patch Merging Layer.
+    Args:
+        input_resolution (tuple[int]): Resolution of input feature.
+        dim (int): Number of input channels.
+        norm_layer (nn.Module, optional): Normalization layer.  Default: nn.LayerNorm
+    """
+
+    def __init__(self, input_resolution, dim, norm_layer=nn.LayerNorm):
+        super().__init__()
+        self.input_resolution = input_resolution
+        self.dim = dim
+        self.reduction = nn.Linear(4 * dim, 2 * dim, bias=False)
+        self.norm = norm_layer(2 * dim)
+
+    def forward(self, x):
+        """
+        x: B, H*W, C
+        """
+        H, W = self.input_resolution
+        B, L, C = x.shape
+        assert L == H * W, "input feature has wrong size"
+        assert H % 2 == 0 and W % 2 == 0, f"x size ({H}*{W}) are not even."
+
+        x = x.view(B, H, W, C)
+
+        x0 = x[:, 0::2, 0::2, :]  # B H/2 W/2 C
+        x1 = x[:, 1::2, 0::2, :]  # B H/2 W/2 C
+        x2 = x[:, 0::2, 1::2, :]  # B H/2 W/2 C
+        x3 = x[:, 1::2, 1::2, :]  # B H/2 W/2 C
+        x = torch.cat([x0, x1, x2, x3], -1)  # B H/2 W/2 4*C
+        x = x.view(B, -1, 4 * C)  # B H/2*W/2 4*C
+
+        x = self.reduction(x)
+        x = self.norm(x)
+
+        return x
+
+    def extra_repr(self) -> str:
+        return f"input_resolution={self.input_resolution}, dim={self.dim}"
+
+    def flops(self):
+        H, W = self.input_resolution
+        flops = (H // 2) * (W // 2) * 4 * self.dim * 2 * self.dim
+        flops += H * W * self.dim // 2
+        return flops    
+
+class BasicLayer(nn.Module):
+    """ A basic Swin Transformer layer for one stage.
+    Args:
+        dim (int): Number of input channels.
+        input_resolution (tuple[int]): Input resolution.
+        depth (int): Number of blocks.
+        num_heads (int): Number of attention heads.
+        window_size (int): Local window size.
+        mlp_ratio (float): Ratio of mlp hidden dim to embedding dim.
+        qkv_bias (bool, optional): If True, add a learnable bias to query, key, value. Default: True
+        drop (float, optional): Dropout rate. Default: 0.0
+        attn_drop (float, optional): Attention dropout rate. Default: 0.0
+        drop_path (float | tuple[float], optional): Stochastic depth rate. Default: 0.0
+        norm_layer (nn.Module, optional): Normalization layer. Default: nn.LayerNorm
+        downsample (nn.Module | None, optional): Downsample layer at the end of the layer. Default: None
+        use_checkpoint (bool): Whether to use checkpointing to save memory. Default: False.
+        pretrained_window_size (int): Local window size in pre-training.
+    """
+
+    def __init__(self, dim, input_resolution, depth, num_heads, window_size,
+                 mlp_ratio=4., qkv_bias=True, drop=0., attn_drop=0.,
+                 drop_path=0., norm_layer=nn.LayerNorm, downsample=None, use_checkpoint=False,
+                 pretrained_window_size=0):
+
+        super().__init__()
+        self.dim = dim
+        self.input_resolution = input_resolution
+        self.depth = depth
+        self.use_checkpoint = use_checkpoint
+
+        # build blocks
+        self.blocks = nn.ModuleList([
+            SwinTransformerBlock(dim=dim, input_resolution=input_resolution,
+                                 num_heads=num_heads, window_size=window_size,
+                                 shift_size=0 if (i % 2 == 0) else window_size // 2,
+                                 mlp_ratio=mlp_ratio,
+                                 qkv_bias=qkv_bias,
+                                 drop=drop, attn_drop=attn_drop,
+                                 drop_path=drop_path[i] if isinstance(drop_path, list) else drop_path,
+                                 norm_layer=norm_layer,
+                                 pretrained_window_size=pretrained_window_size)
+            for i in range(depth)])
+
+        # patch merging layer
+        if downsample is not None:
+            self.downsample = downsample(input_resolution, dim=dim, norm_layer=norm_layer)
+        else:
+            self.downsample = None
+
+    def forward(self, x, x_size):
+        for blk in self.blocks:
+            if self.use_checkpoint:
+                x = checkpoint.checkpoint(blk, x, x_size)
+            else:
+                x = blk(x, x_size)
+        if self.downsample is not None:
+            x = self.downsample(x)
+        return x
+
+    def extra_repr(self) -> str:
+        return f"dim={self.dim}, input_resolution={self.input_resolution}, depth={self.depth}"
+
+    def flops(self):
+        flops = 0
+        for blk in self.blocks:
+            flops += blk.flops()
+        if self.downsample is not None:
+            flops += self.downsample.flops()
+        return flops
+
+    def _init_respostnorm(self):
+        for blk in self.blocks:
+            nn.init.constant_(blk.norm1.bias, 0)
+            nn.init.constant_(blk.norm1.weight, 0)
+            nn.init.constant_(blk.norm2.bias, 0)
+            nn.init.constant_(blk.norm2.weight, 0)
+            
+class PatchEmbed(nn.Module):
+    r""" Image to Patch Embedding
+    Args:
+        img_size (int): Image size.  Default: 224.
+        patch_size (int): Patch token size. Default: 4.
+        in_chans (int): Number of input image channels. Default: 3.
+        embed_dim (int): Number of linear projection output channels. Default: 96.
+        norm_layer (nn.Module, optional): Normalization layer. Default: None
+    """
+
+    def __init__(self, img_size=224, patch_size=4, in_chans=3, embed_dim=96, norm_layer=None):
+        super().__init__()
+        img_size = to_2tuple(img_size)
+        patch_size = to_2tuple(patch_size)
+        patches_resolution = [img_size[0] // patch_size[0], img_size[1] // patch_size[1]]
+        self.img_size = img_size
+        self.patch_size = patch_size
+        self.patches_resolution = patches_resolution
+        self.num_patches = patches_resolution[0] * patches_resolution[1]
+
+        self.in_chans = in_chans
+        self.embed_dim = embed_dim
+
+        self.proj = nn.Conv2d(in_chans, embed_dim, kernel_size=patch_size, stride=patch_size)
+        if norm_layer is not None:
+            self.norm = norm_layer(embed_dim)
+        else:
+            self.norm = None
+
+    def forward(self, x):
+        B, C, H, W = x.shape
+        # FIXME look at relaxing size constraints
+        # assert H == self.img_size[0] and W == self.img_size[1],
+        #     f"Input image size ({H}*{W}) doesn't match model ({self.img_size[0]}*{self.img_size[1]})."
+        x = self.proj(x).flatten(2).transpose(1, 2)  # B Ph*Pw C
+        if self.norm is not None:
+            x = self.norm(x)
+        return x
+
+    def flops(self):
+        Ho, Wo = self.patches_resolution
+        flops = Ho * Wo * self.embed_dim * self.in_chans * (self.patch_size[0] * self.patch_size[1])
+        if self.norm is not None:
+            flops += Ho * Wo * self.embed_dim
+        return flops           
+
+class RSTB(nn.Module):
+    """Residual Swin Transformer Block (RSTB).
+
+    Args:
+        dim (int): Number of input channels.
+        input_resolution (tuple[int]): Input resolution.
+        depth (int): Number of blocks.
+        num_heads (int): Number of attention heads.
+        window_size (int): Local window size.
+        mlp_ratio (float): Ratio of mlp hidden dim to embedding dim.
+        qkv_bias (bool, optional): If True, add a learnable bias to query, key, value. Default: True
+        drop (float, optional): Dropout rate. Default: 0.0
+        attn_drop (float, optional): Attention dropout rate. Default: 0.0
+        drop_path (float | tuple[float], optional): Stochastic depth rate. Default: 0.0
+        norm_layer (nn.Module, optional): Normalization layer. Default: nn.LayerNorm
+        downsample (nn.Module | None, optional): Downsample layer at the end of the layer. Default: None
+        use_checkpoint (bool): Whether to use checkpointing to save memory. Default: False.
+        img_size: Input image size.
+        patch_size: Patch size.
+        resi_connection: The convolutional block before residual connection.
+    """
+
+    def __init__(self, dim, input_resolution, depth, num_heads, window_size,
+                 mlp_ratio=4., qkv_bias=True, drop=0., attn_drop=0.,
+                 drop_path=0., norm_layer=nn.LayerNorm, downsample=None, use_checkpoint=False,
+                 img_size=224, patch_size=4, resi_connection='1conv'):
+        super(RSTB, self).__init__()
+
+        self.dim = dim
+        self.input_resolution = input_resolution
+
+        self.residual_group = BasicLayer(dim=dim,
+                                         input_resolution=input_resolution,
+                                         depth=depth,
+                                         num_heads=num_heads,
+                                         window_size=window_size,
+                                         mlp_ratio=mlp_ratio,
+                                         qkv_bias=qkv_bias, 
+                                         drop=drop, attn_drop=attn_drop,
+                                         drop_path=drop_path,
+                                         norm_layer=norm_layer,
+                                         downsample=downsample,
+                                         use_checkpoint=use_checkpoint)
+
+        if resi_connection == '1conv':
+            self.conv = nn.Conv2d(dim, dim, 3, 1, 1)
+        elif resi_connection == '3conv':
+            # to save parameters and memory
+            self.conv = nn.Sequential(nn.Conv2d(dim, dim // 4, 3, 1, 1), nn.LeakyReLU(negative_slope=0.2, inplace=True),
+                                      nn.Conv2d(dim // 4, dim // 4, 1, 1, 0),
+                                      nn.LeakyReLU(negative_slope=0.2, inplace=True),
+                                      nn.Conv2d(dim // 4, dim, 3, 1, 1))
+
+        self.patch_embed = PatchEmbed(
+            img_size=img_size, patch_size=patch_size, in_chans=dim, embed_dim=dim,
+            norm_layer=None)
+
+        self.patch_unembed = PatchUnEmbed(
+            img_size=img_size, patch_size=patch_size, in_chans=dim, embed_dim=dim,
+            norm_layer=None)
+
+    def forward(self, x, x_size):
+        return self.patch_embed(self.conv(self.patch_unembed(self.residual_group(x, x_size), x_size))) + x
+
+    def flops(self):
+        flops = 0
+        flops += self.residual_group.flops()
+        H, W = self.input_resolution
+        flops += H * W * self.dim * self.dim * 9
+        flops += self.patch_embed.flops()
+        flops += self.patch_unembed.flops()
+
+        return flops
+
+class PatchUnEmbed(nn.Module):
+    r""" Image to Patch Unembedding
+
+    Args:
+        img_size (int): Image size.  Default: 224.
+        patch_size (int): Patch token size. Default: 4.
+        in_chans (int): Number of input image channels. Default: 3.
+        embed_dim (int): Number of linear projection output channels. Default: 96.
+        norm_layer (nn.Module, optional): Normalization layer. Default: None
+    """
+
+    def __init__(self, img_size=224, patch_size=4, in_chans=3, embed_dim=96, norm_layer=None):
+        super().__init__()
+        img_size = to_2tuple(img_size)
+        patch_size = to_2tuple(patch_size)
+        patches_resolution = [img_size[0] // patch_size[0], img_size[1] // patch_size[1]]
+        self.img_size = img_size
+        self.patch_size = patch_size
+        self.patches_resolution = patches_resolution
+        self.num_patches = patches_resolution[0] * patches_resolution[1]
+
+        self.in_chans = in_chans
+        self.embed_dim = embed_dim
+
+    def forward(self, x, x_size):
+        B, HW, C = x.shape
+        x = x.transpose(1, 2).view(B, self.embed_dim, x_size[0], x_size[1])  # B Ph*Pw C
+        return x
+
+    def flops(self):
+        flops = 0
+        return flops
+
+
+class Upsample(nn.Sequential):
+    """Upsample module.
+
+    Args:
+        scale (int): Scale factor. Supported scales: 2^n and 3.
+        num_feat (int): Channel number of intermediate features.
+    """
+
+    def __init__(self, scale, num_feat):
+        m = []
+        if (scale & (scale - 1)) == 0:  # scale = 2^n
+            for _ in range(int(math.log(scale, 2))):
+                m.append(nn.Conv2d(num_feat, 4 * num_feat, 3, 1, 1))
+                m.append(nn.PixelShuffle(2))
+        elif scale == 3:
+            m.append(nn.Conv2d(num_feat, 9 * num_feat, 3, 1, 1))
+            m.append(nn.PixelShuffle(3))
+        else:
+            raise ValueError(f'scale {scale} is not supported. ' 'Supported scales: 2^n and 3.')
+        super(Upsample, self).__init__(*m)
+        
+class Upsample_hf(nn.Sequential):
+    """Upsample module.
+
+    Args:
+        scale (int): Scale factor. Supported scales: 2^n and 3.
+        num_feat (int): Channel number of intermediate features.
+    """
+
+    def __init__(self, scale, num_feat):
+        m = []
+        if (scale & (scale - 1)) == 0:  # scale = 2^n
+            for _ in range(int(math.log(scale, 2))):
+                m.append(nn.Conv2d(num_feat, 4 * num_feat, 3, 1, 1))
+                m.append(nn.PixelShuffle(2))
+        elif scale == 3:
+            m.append(nn.Conv2d(num_feat, 9 * num_feat, 3, 1, 1))
+            m.append(nn.PixelShuffle(3))
+        else:
+            raise ValueError(f'scale {scale} is not supported. ' 'Supported scales: 2^n and 3.')
+        super(Upsample_hf, self).__init__(*m)        
+
+
+class UpsampleOneStep(nn.Sequential):
+    """UpsampleOneStep module (the difference with Upsample is that it always only has 1conv + 1pixelshuffle)
+       Used in lightweight SR to save parameters.
+
+    Args:
+        scale (int): Scale factor. Supported scales: 2^n and 3.
+        num_feat (int): Channel number of intermediate features.
+
+    """
+
+    def __init__(self, scale, num_feat, num_out_ch, input_resolution=None):
+        self.num_feat = num_feat
+        self.input_resolution = input_resolution
+        m = []
+        m.append(nn.Conv2d(num_feat, (scale ** 2) * num_out_ch, 3, 1, 1))
+        m.append(nn.PixelShuffle(scale))
+        super(UpsampleOneStep, self).__init__(*m)
+
+    def flops(self):
+        H, W = self.input_resolution
+        flops = H * W * self.num_feat * 3 * 9
+        return flops
+    
+    
+
+class Swin2SR(nn.Module):
+    r""" Swin2SR
+        A PyTorch impl of : `Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restoration`.
+
+    Args:
+        img_size (int | tuple(int)): Input image size. Default 64
+        patch_size (int | tuple(int)): Patch size. Default: 1
+        in_chans (int): Number of input image channels. Default: 3
+        embed_dim (int): Patch embedding dimension. Default: 96
+        depths (tuple(int)): Depth of each Swin Transformer layer.
+        num_heads (tuple(int)): Number of attention heads in different layers.
+        window_size (int): Window size. Default: 7
+        mlp_ratio (float): Ratio of mlp hidden dim to embedding dim. Default: 4
+        qkv_bias (bool): If True, add a learnable bias to query, key, value. Default: True
+        drop_rate (float): Dropout rate. Default: 0
+        attn_drop_rate (float): Attention dropout rate. Default: 0
+        drop_path_rate (float): Stochastic depth rate. Default: 0.1
+        norm_layer (nn.Module): Normalization layer. Default: nn.LayerNorm.
+        ape (bool): If True, add absolute position embedding to the patch embedding. Default: False
+        patch_norm (bool): If True, add normalization after patch embedding. Default: True
+        use_checkpoint (bool): Whether to use checkpointing to save memory. Default: False
+        upscale: Upscale factor. 2/3/4/8 for image SR, 1 for denoising and compress artifact reduction
+        img_range: Image range. 1. or 255.
+        upsampler: The reconstruction reconstruction module. 'pixelshuffle'/'pixelshuffledirect'/'nearest+conv'/None
+        resi_connection: The convolutional block before residual connection. '1conv'/'3conv'
+    """
+
+    def __init__(self, img_size=64, patch_size=1, in_chans=3,
+                 embed_dim=96, depths=[6, 6, 6, 6], num_heads=[6, 6, 6, 6],
+                 window_size=7, mlp_ratio=4., qkv_bias=True, 
+                 drop_rate=0., attn_drop_rate=0., drop_path_rate=0.1,
+                 norm_layer=nn.LayerNorm, ape=False, patch_norm=True,
+                 use_checkpoint=False, upscale=2, img_range=1., upsampler='', resi_connection='1conv',
+                 **kwargs):
+        super(Swin2SR, self).__init__()
+        num_in_ch = in_chans
+        num_out_ch = in_chans
+        num_feat = 64
+        self.img_range = img_range
+        if in_chans == 3:
+            rgb_mean = (0.4488, 0.4371, 0.4040)
+            self.mean = torch.Tensor(rgb_mean).view(1, 3, 1, 1)
+        else:
+            self.mean = torch.zeros(1, 1, 1, 1)
+        self.upscale = upscale
+        self.upsampler = upsampler
+        self.window_size = window_size
+
+        #####################################################################################################
+        ################################### 1, shallow feature extraction ###################################
+        self.conv_first = nn.Conv2d(num_in_ch, embed_dim, 3, 1, 1)
+
+        #####################################################################################################
+        ################################### 2, deep feature extraction ######################################
+        self.num_layers = len(depths)
+        self.embed_dim = embed_dim
+        self.ape = ape
+        self.patch_norm = patch_norm
+        self.num_features = embed_dim
+        self.mlp_ratio = mlp_ratio
+
+        # split image into non-overlapping patches
+        self.patch_embed = PatchEmbed(
+            img_size=img_size, patch_size=patch_size, in_chans=embed_dim, embed_dim=embed_dim,
+            norm_layer=norm_layer if self.patch_norm else None)
+        num_patches = self.patch_embed.num_patches
+        patches_resolution = self.patch_embed.patches_resolution
+        self.patches_resolution = patches_resolution
+
+        # merge non-overlapping patches into image
+        self.patch_unembed = PatchUnEmbed(
+            img_size=img_size, patch_size=patch_size, in_chans=embed_dim, embed_dim=embed_dim,
+            norm_layer=norm_layer if self.patch_norm else None)
+
+        # absolute position embedding
+        if self.ape:
+            self.absolute_pos_embed = nn.Parameter(torch.zeros(1, num_patches, embed_dim))
+            trunc_normal_(self.absolute_pos_embed, std=.02)
+
+        self.pos_drop = nn.Dropout(p=drop_rate)
+
+        # stochastic depth
+        dpr = [x.item() for x in torch.linspace(0, drop_path_rate, sum(depths))]  # stochastic depth decay rule
+
+        # build Residual Swin Transformer blocks (RSTB)
+        self.layers = nn.ModuleList()
+        for i_layer in range(self.num_layers):
+            layer = RSTB(dim=embed_dim,
+                         input_resolution=(patches_resolution[0],
+                                           patches_resolution[1]),
+                         depth=depths[i_layer],
+                         num_heads=num_heads[i_layer],
+                         window_size=window_size,
+                         mlp_ratio=self.mlp_ratio,
+                         qkv_bias=qkv_bias, 
+                         drop=drop_rate, attn_drop=attn_drop_rate,
+                         drop_path=dpr[sum(depths[:i_layer]):sum(depths[:i_layer + 1])],  # no impact on SR results
+                         norm_layer=norm_layer,
+                         downsample=None,
+                         use_checkpoint=use_checkpoint,
+                         img_size=img_size,
+                         patch_size=patch_size,
+                         resi_connection=resi_connection
+
+                         )
+            self.layers.append(layer)
+            
+        if self.upsampler == 'pixelshuffle_hf':
+            self.layers_hf = nn.ModuleList()
+            for i_layer in range(self.num_layers):
+                layer = RSTB(dim=embed_dim,
+                             input_resolution=(patches_resolution[0],
+                                               patches_resolution[1]),
+                             depth=depths[i_layer],
+                             num_heads=num_heads[i_layer],
+                             window_size=window_size,
+                             mlp_ratio=self.mlp_ratio,
+                             qkv_bias=qkv_bias, 
+                             drop=drop_rate, attn_drop=attn_drop_rate,
+                             drop_path=dpr[sum(depths[:i_layer]):sum(depths[:i_layer + 1])],  # no impact on SR results
+                             norm_layer=norm_layer,
+                             downsample=None,
+                             use_checkpoint=use_checkpoint,
+                             img_size=img_size,
+                             patch_size=patch_size,
+                             resi_connection=resi_connection
+
+                             )
+                self.layers_hf.append(layer)
+                        
+        self.norm = norm_layer(self.num_features)
+
+        # build the last conv layer in deep feature extraction
+        if resi_connection == '1conv':
+            self.conv_after_body = nn.Conv2d(embed_dim, embed_dim, 3, 1, 1)
+        elif resi_connection == '3conv':
+            # to save parameters and memory
+            self.conv_after_body = nn.Sequential(nn.Conv2d(embed_dim, embed_dim // 4, 3, 1, 1),
+                                                 nn.LeakyReLU(negative_slope=0.2, inplace=True),
+                                                 nn.Conv2d(embed_dim // 4, embed_dim // 4, 1, 1, 0),
+                                                 nn.LeakyReLU(negative_slope=0.2, inplace=True),
+                                                 nn.Conv2d(embed_dim // 4, embed_dim, 3, 1, 1))
+
+        #####################################################################################################
+        ################################ 3, high quality image reconstruction ################################
+        if self.upsampler == 'pixelshuffle':
+            # for classical SR
+            self.conv_before_upsample = nn.Sequential(nn.Conv2d(embed_dim, num_feat, 3, 1, 1),
+                                                      nn.LeakyReLU(inplace=True))
+            self.upsample = Upsample(upscale, num_feat)
+            self.conv_last = nn.Conv2d(num_feat, num_out_ch, 3, 1, 1)
+        elif self.upsampler == 'pixelshuffle_aux':
+            self.conv_bicubic = nn.Conv2d(num_in_ch, num_feat, 3, 1, 1)
+            self.conv_before_upsample = nn.Sequential(
+                nn.Conv2d(embed_dim, num_feat, 3, 1, 1),
+                nn.LeakyReLU(inplace=True))
+            self.conv_aux = nn.Conv2d(num_feat, num_out_ch, 3, 1, 1)
+            self.conv_after_aux = nn.Sequential(
+                nn.Conv2d(3, num_feat, 3, 1, 1),
+                nn.LeakyReLU(inplace=True))            
+            self.upsample = Upsample(upscale, num_feat)
+            self.conv_last = nn.Conv2d(num_feat, num_out_ch, 3, 1, 1)
+            
+        elif self.upsampler == 'pixelshuffle_hf':
+            self.conv_before_upsample = nn.Sequential(nn.Conv2d(embed_dim, num_feat, 3, 1, 1),
+                                                      nn.LeakyReLU(inplace=True))
+            self.upsample = Upsample(upscale, num_feat)
+            self.upsample_hf = Upsample_hf(upscale, num_feat)
+            self.conv_last = nn.Conv2d(num_feat, num_out_ch, 3, 1, 1)
+            self.conv_first_hf = nn.Sequential(nn.Conv2d(num_feat, embed_dim, 3, 1, 1),
+                                                      nn.LeakyReLU(inplace=True))
+            self.conv_after_body_hf = nn.Conv2d(embed_dim, embed_dim, 3, 1, 1)
+            self.conv_before_upsample_hf = nn.Sequential(
+                nn.Conv2d(embed_dim, num_feat, 3, 1, 1),
+                nn.LeakyReLU(inplace=True))
+            self.conv_last_hf = nn.Conv2d(num_feat, num_out_ch, 3, 1, 1)
+            
+        elif self.upsampler == 'pixelshuffledirect':
+            # for lightweight SR (to save parameters)
+            self.upsample = UpsampleOneStep(upscale, embed_dim, num_out_ch,
+                                            (patches_resolution[0], patches_resolution[1]))
+        elif self.upsampler == 'nearest+conv':
+            # for real-world SR (less artifacts)
+            assert self.upscale == 4, 'only support x4 now.'
+            self.conv_before_upsample = nn.Sequential(nn.Conv2d(embed_dim, num_feat, 3, 1, 1),
+                                                      nn.LeakyReLU(inplace=True))
+            self.conv_up1 = nn.Conv2d(num_feat, num_feat, 3, 1, 1)
+            self.conv_up2 = nn.Conv2d(num_feat, num_feat, 3, 1, 1)
+            self.conv_hr = nn.Conv2d(num_feat, num_feat, 3, 1, 1)
+            self.conv_last = nn.Conv2d(num_feat, num_out_ch, 3, 1, 1)
+            self.lrelu = nn.LeakyReLU(negative_slope=0.2, inplace=True)
+        else:
+            # for image denoising and JPEG compression artifact reduction
+            self.conv_last = nn.Conv2d(embed_dim, num_out_ch, 3, 1, 1)
+
+        self.apply(self._init_weights)
+
+    def _init_weights(self, m):
+        if isinstance(m, nn.Linear):
+            trunc_normal_(m.weight, std=.02)
+            if isinstance(m, nn.Linear) and m.bias is not None:
+                nn.init.constant_(m.bias, 0)
+        elif isinstance(m, nn.LayerNorm):
+            nn.init.constant_(m.bias, 0)
+            nn.init.constant_(m.weight, 1.0)
+
+    @torch.jit.ignore
+    def no_weight_decay(self):
+        return {'absolute_pos_embed'}
+
+    @torch.jit.ignore
+    def no_weight_decay_keywords(self):
+        return {'relative_position_bias_table'}
+
+    def check_image_size(self, x):
+        _, _, h, w = x.size()
+        mod_pad_h = (self.window_size - h % self.window_size) % self.window_size
+        mod_pad_w = (self.window_size - w % self.window_size) % self.window_size
+        x = F.pad(x, (0, mod_pad_w, 0, mod_pad_h), 'reflect')
+        return x
+
+    def forward_features(self, x):
+        x_size = (x.shape[2], x.shape[3])
+        x = self.patch_embed(x)
+        if self.ape:
+            x = x + self.absolute_pos_embed
+        x = self.pos_drop(x)
+
+        for layer in self.layers:
+            x = layer(x, x_size)
+
+        x = self.norm(x)  # B L C
+        x = self.patch_unembed(x, x_size)
+
+        return x
+    
+    def forward_features_hf(self, x):
+        x_size = (x.shape[2], x.shape[3])
+        x = self.patch_embed(x)
+        if self.ape:
+            x = x + self.absolute_pos_embed
+        x = self.pos_drop(x)
+
+        for layer in self.layers_hf:
+            x = layer(x, x_size)
+
+        x = self.norm(x)  # B L C
+        x = self.patch_unembed(x, x_size)
+
+        return x    
+
+    def forward(self, x):
+        H, W = x.shape[2:]
+        x = self.check_image_size(x)
+
+        self.mean = self.mean.type_as(x)
+        x = (x - self.mean) * self.img_range
+
+        if self.upsampler == 'pixelshuffle':
+            # for classical SR
+            x = self.conv_first(x)
+            x = self.conv_after_body(self.forward_features(x)) + x
+            x = self.conv_before_upsample(x)
+            x = self.conv_last(self.upsample(x))
+        elif self.upsampler == 'pixelshuffle_aux':
+            bicubic = F.interpolate(x, size=(H * self.upscale, W * self.upscale), mode='bicubic', align_corners=False)
+            bicubic = self.conv_bicubic(bicubic)
+            x = self.conv_first(x)
+            x = self.conv_after_body(self.forward_features(x)) + x
+            x = self.conv_before_upsample(x)
+            aux = self.conv_aux(x) # b, 3, LR_H, LR_W
+            x = self.conv_after_aux(aux)
+            x = self.upsample(x)[:, :, :H * self.upscale, :W * self.upscale] + bicubic[:, :, :H * self.upscale, :W * self.upscale]
+            x = self.conv_last(x)
+            aux = aux / self.img_range + self.mean
+        elif self.upsampler == 'pixelshuffle_hf':
+            # for classical SR with HF
+            x = self.conv_first(x)
+            x = self.conv_after_body(self.forward_features(x)) + x
+            x_before = self.conv_before_upsample(x)
+            x_out = self.conv_last(self.upsample(x_before))
+            
+            x_hf = self.conv_first_hf(x_before)
+            x_hf = self.conv_after_body_hf(self.forward_features_hf(x_hf)) + x_hf
+            x_hf = self.conv_before_upsample_hf(x_hf)
+            x_hf = self.conv_last_hf(self.upsample_hf(x_hf))
+            x = x_out + x_hf
+            x_hf = x_hf / self.img_range + self.mean
+
+        elif self.upsampler == 'pixelshuffledirect':
+            # for lightweight SR
+            x = self.conv_first(x)
+            x = self.conv_after_body(self.forward_features(x)) + x
+            x = self.upsample(x)
+        elif self.upsampler == 'nearest+conv':
+            # for real-world SR
+            x = self.conv_first(x)
+            x = self.conv_after_body(self.forward_features(x)) + x
+            x = self.conv_before_upsample(x)
+            x = self.lrelu(self.conv_up1(torch.nn.functional.interpolate(x, scale_factor=2, mode='nearest')))
+            x = self.lrelu(self.conv_up2(torch.nn.functional.interpolate(x, scale_factor=2, mode='nearest')))
+            x = self.conv_last(self.lrelu(self.conv_hr(x)))
+        else:
+            # for image denoising and JPEG compression artifact reduction
+            x_first = self.conv_first(x)
+            res = self.conv_after_body(self.forward_features(x_first)) + x_first
+            x = x + self.conv_last(res)
+        
+        x = x / self.img_range + self.mean
+        if self.upsampler == "pixelshuffle_aux":
+            return x[:, :, :H*self.upscale, :W*self.upscale], aux
+        
+        elif self.upsampler == "pixelshuffle_hf":
+            x_out = x_out / self.img_range + self.mean
+            return x_out[:, :, :H*self.upscale, :W*self.upscale], x[:, :, :H*self.upscale, :W*self.upscale], x_hf[:, :, :H*self.upscale, :W*self.upscale]
+        
+        else:
+            return x[:, :, :H*self.upscale, :W*self.upscale]
+
+    def flops(self):
+        flops = 0
+        H, W = self.patches_resolution
+        flops += H * W * 3 * self.embed_dim * 9
+        flops += self.patch_embed.flops()
+        for i, layer in enumerate(self.layers):
+            flops += layer.flops()
+        flops += H * W * 3 * self.embed_dim * self.embed_dim
+        flops += self.upsample.flops()
+        return flops
+
+
+if __name__ == '__main__':
+    upscale = 4
+    window_size = 8
+    height = (1024 // upscale // window_size + 1) * window_size
+    width = (720 // upscale // window_size + 1) * window_size
+    model = Swin2SR(upscale=2, img_size=(height, width),
+                   window_size=window_size, img_range=1., depths=[6, 6, 6, 6],
+                   embed_dim=60, num_heads=[6, 6, 6, 6], mlp_ratio=2, upsampler='pixelshuffledirect')
+    print(model)
+    print(height, width, model.flops() / 1e9)
+
+    x = torch.randn((1, 3, height, width))
+    x = model(x)
+    print(x.shape)
\ No newline at end of file
-- 
cgit v1.2.3


From ed769977f0d0f201d8e361d365102f18775fc62c Mon Sep 17 00:00:00 2001
From: C43H66N12O12S2 <36072735+C43H66N12O12S2@users.noreply.github.com>
Date: Sun, 9 Oct 2022 18:56:59 +0300
Subject: add swinir v2 support

---
 modules/swinir_model.py | 35 ++++++++++++++++++++++++++++-------
 1 file changed, 28 insertions(+), 7 deletions(-)

diff --git a/modules/swinir_model.py b/modules/swinir_model.py
index fbd11f84..baa02e3d 100644
--- a/modules/swinir_model.py
+++ b/modules/swinir_model.py
@@ -10,6 +10,7 @@ from tqdm import tqdm
 from modules import modelloader
 from modules.shared import cmd_opts, opts, device
 from modules.swinir_model_arch import SwinIR as net
+from modules.swinir_model_arch_v2 import Swin2SR as net2
 from modules.upscaler import Upscaler, UpscalerData
 
 precision_scope = (
@@ -57,22 +58,42 @@ class UpscalerSwinIR(Upscaler):
             filename = path
         if filename is None or not os.path.exists(filename):
             return None
-        model = net(
+        if filename.endswith(".v2.pth"):
+            model = net2(
             upscale=scale,
             in_chans=3,
             img_size=64,
             window_size=8,
             img_range=1.0,
-            depths=[6, 6, 6, 6, 6, 6, 6, 6, 6],
-            embed_dim=240,
-            num_heads=[8, 8, 8, 8, 8, 8, 8, 8, 8],
+            depths=[6, 6, 6, 6, 6, 6],
+            embed_dim=180,
+            num_heads=[6, 6, 6, 6, 6, 6],
             mlp_ratio=2,
             upsampler="nearest+conv",
-            resi_connection="3conv",
-        )
+            resi_connection="1conv",
+            )
+            params = None
+        else:
+            model = net(
+                upscale=scale,
+                in_chans=3,
+                img_size=64,
+                window_size=8,
+                img_range=1.0,
+                depths=[6, 6, 6, 6, 6, 6, 6, 6, 6],
+                embed_dim=240,
+                num_heads=[8, 8, 8, 8, 8, 8, 8, 8, 8],
+                mlp_ratio=2,
+                upsampler="nearest+conv",
+                resi_connection="3conv",
+            )
+            params = "params_ema"
 
         pretrained_model = torch.load(filename)
-        model.load_state_dict(pretrained_model["params_ema"], strict=True)
+        if params is not None:
+            model.load_state_dict(pretrained_model[params], strict=True)
+        else:
+            model.load_state_dict(pretrained_model, strict=True)
         if not cmd_opts.no_half:
             model = model.half()
         return model
-- 
cgit v1.2.3


From af62ad4d25dcd0454944368f4925d83101cdedbc Mon Sep 17 00:00:00 2001
From: ssysm <me@theeditorstudio.com>
Date: Mon, 10 Oct 2022 13:25:28 -0400
Subject: change vae loading method

---
 modules/sd_models.py | 11 +++++++++--
 1 file changed, 9 insertions(+), 2 deletions(-)

diff --git a/modules/sd_models.py b/modules/sd_models.py
index b0e1d8bd..7a42d924 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -150,9 +150,16 @@ def load_model_weights(model, checkpoint_info):
 
     devices.dtype = torch.float32 if shared.cmd_opts.no_half else torch.float16
 
-    vae_file = shared.cmd_opts.vae_path or os.path.splitext(checkpoint_file)[0] + ".vae.pt"
+    vae_file = os.path.splitext(checkpoint_file)[0] + ".vae.pt"
+    if os.path.exists(vae_file):
+        print(f"Found VAE Weights: {vae_file}")
+    elif shared.cmd_opts.vae_path != None:
+        vae_file = shared.cmd_opts.vae_path
+        print(f'No VAE found for inside the model folder. Using CLI specified : {vae_file}')
+    else:
+        print("No VAE found for inside the model folder. Passing.")
+
     if os.path.exists(vae_file):
-        print(f"Loading VAE weights from: {vae_file}")
         vae_ckpt = torch.load(vae_file, map_location="cpu")
         vae_dict = {k: v for k, v in vae_ckpt["state_dict"].items() if k[0:4] != "loss"}
 
-- 
cgit v1.2.3


From 39919c40dd18f5a14ae21403efea1b0f819756c7 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 10 Oct 2022 20:32:37 +0300
Subject: add eta noise seed delta option

---
 javascript/hints.js   | 1 +
 modules/processing.py | 6 +++++-
 modules/shared.py     | 1 +
 3 files changed, 7 insertions(+), 1 deletion(-)

diff --git a/javascript/hints.js b/javascript/hints.js
index 8e352e94..47b80776 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -79,6 +79,7 @@ titles = {
     "Highres. fix": "Use a two step process to partially create an image at smaller resolution, upscale, and then improve details in it without changing composition",
     "Scale latent": "Uscale the image in latent space. Alternative is to produce the full image from latent representation, upscale that, and then move it back to latent space.",
 
+    "Eta noise seed delta": "If this values is non-zero, it will be added to seed and used to initialize RNG for noises when using samplers with Eta. You can use this to produce even more variation of images, or you can use this to match images of other software if you know what you are doing.",
 }
 
 
diff --git a/modules/processing.py b/modules/processing.py
index 50ba4fc5..698b3069 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -207,7 +207,7 @@ def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, see
     # enables the generation of additional tensors with noise that the sampler will use during its processing.
     # Using those pre-generated tensors instead of simple torch.randn allows a batch with seeds [100, 101] to
     # produce the same images as with two batches [100], [101].
-    if p is not None and p.sampler is not None and len(seeds) > 1 and opts.enable_batch_seeds:
+    if p is not None and p.sampler is not None and (len(seeds) > 1 and opts.enable_batch_seeds or opts.eta_noise_seed_delta > 0):
         sampler_noises = [[] for _ in range(p.sampler.number_of_needed_noises(p))]
     else:
         sampler_noises = None
@@ -247,6 +247,9 @@ def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, see
         if sampler_noises is not None:
             cnt = p.sampler.number_of_needed_noises(p)
 
+            if opts.eta_noise_seed_delta > 0:
+                torch.manual_seed(seed + opts.eta_noise_seed_delta)
+
             for j in range(cnt):
                 sampler_noises[j].append(devices.randn_without_seed(tuple(noise_shape)))
 
@@ -301,6 +304,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration
         "Denoising strength": getattr(p, 'denoising_strength', None),
         "Eta": (None if p.sampler is None or p.sampler.eta == p.sampler.default_eta else p.sampler.eta),
         "Clip skip": None if clip_skip <= 1 else clip_skip,
+        "ENSD": None if opts.eta_noise_seed_delta == 0 else opts.eta_noise_seed_delta,
     }
 
     generation_params.update(p.extra_generation_params)
diff --git a/modules/shared.py b/modules/shared.py
index 5dfc344c..b1c65ecf 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -260,6 +260,7 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters"
     's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
     's_tmin':  OptionInfo(0.0, "sigma tmin",  gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
     's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
+    'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}),
 }))
 
 
-- 
cgit v1.2.3


From 727e4d108674dc2813507e2a973a733ef21e8d53 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 10 Oct 2022 20:46:55 +0300
Subject: no to different messages plus fix using != to compare to None

---
 modules/sd_models.py | 9 +++------
 1 file changed, 3 insertions(+), 6 deletions(-)

diff --git a/modules/sd_models.py b/modules/sd_models.py
index 4c06051e..0a55b4c3 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -152,15 +152,12 @@ def load_model_weights(model, checkpoint_info):
     devices.dtype_vae = torch.float32 if shared.cmd_opts.no_half or shared.cmd_opts.no_half_vae else torch.float16
 
     vae_file = os.path.splitext(checkpoint_file)[0] + ".vae.pt"
-    if os.path.exists(vae_file):
-        print(f"Found VAE Weights: {vae_file}")
-    elif shared.cmd_opts.vae_path != None:
+
+    if not os.path.exists(vae_file) and shared.cmd_opts.vae_path is not None:
         vae_file = shared.cmd_opts.vae_path
-        print(f'No VAE found for inside the model folder. Using CLI specified : {vae_file}')
-    else:
-        print("No VAE found for inside the model folder. Passing.")
 
     if os.path.exists(vae_file):
+        print(f"Loading VAE weights from: {vae_file}")
         vae_ckpt = torch.load(vae_file, map_location="cpu")
         vae_dict = {k: v for k, v in vae_ckpt["state_dict"].items() if k[0:4] != "loss"}
 
-- 
cgit v1.2.3


From 1d64976dbc5a0f3124567b91fadd5014a9d93c5f Mon Sep 17 00:00:00 2001
From: Justin Maier <Zipp425@gmail.com>
Date: Mon, 10 Oct 2022 12:04:21 -0600
Subject: Simplify crop logic

---
 modules/extras.py | 14 +++-----------
 modules/ui.py     |  4 ++--
 2 files changed, 5 insertions(+), 13 deletions(-)

diff --git a/modules/extras.py b/modules/extras.py
index 83ca7049..b24d7de3 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -73,16 +73,6 @@ def run_extras(extras_mode, resize_mode, image, image_folder, gfpgan_visibility,
             crop_info = " (crop)" if upscaling_crop else ""
             info += f"Resize to: {upscaling_resize_w:g}x{upscaling_resize_h:g}{crop_info}\n"
 
-            def crop_upscaled_center(image, resize_w, resize_h):
-                left = int(math.ceil((image.width - resize_w) / 2))
-                right = image.width - int(math.floor((image.width - resize_w) / 2))
-                top = int(math.ceil((image.height - resize_h) / 2))
-                bottom = image.height - int(math.floor((image.height - resize_h) / 2))
-
-                image = image.crop((left, top, right, bottom))
-                return image
-
-
         if upscaling_resize != 1.0:
             def upscale(image, scaler_index, resize, mode, resize_w, resize_h, crop):
                 small = image.crop((image.width // 2, image.height // 2, image.width // 2 + 10, image.height // 2 + 10))
@@ -94,7 +84,9 @@ def run_extras(extras_mode, resize_mode, image, image_folder, gfpgan_visibility,
                     upscaler = shared.sd_upscalers[scaler_index]
                     c = upscaler.scaler.upscale(image, resize, upscaler.data_path)
                     if mode == 1 and crop:
-                        c = crop_upscaled_center(c, resize_w, resize_h)
+                        cropped = Image.new("RGB", (resize_w, resize_h))
+                        cropped.paste(c, box=(resize_w // 2 - c.width // 2, resize_h // 2 - c.height // 2))
+                        c = cropped
                     cached_images[key] = c
 
                 return c
diff --git a/modules/ui.py b/modules/ui.py
index 4bb2892b..1aabe18d 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -909,8 +909,8 @@ def create_ui(wrap_gradio_gpu_call):
                     with gr.TabItem('Scale to'):
                         with gr.Group():
                             with gr.Row():
-                                upscaling_resize_w = gr.Number(label="Width", value=512)
-                                upscaling_resize_h = gr.Number(label="Height", value=512)
+                                upscaling_resize_w = gr.Number(label="Width", value=512, precision=0)
+                                upscaling_resize_h = gr.Number(label="Height", value=512, precision=0)
                             upscaling_crop = gr.Checkbox(label='Crop to fit', value=True)
 
                 with gr.Group():
-- 
cgit v1.2.3


From 5da1ba0e91a81804dc911d34c9a2e6956a23199c Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 10 Oct 2022 21:24:11 +0300
Subject: remove batch size restriction from X/Y plot

---
 scripts/xy_grid.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 771eb8e4..42e1489c 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -205,7 +205,10 @@ class Script(scripts.Script):
         if not no_fixed_seeds:
             modules.processing.fix_seed(p)
 
-        p.batch_size = 1
+        if not opts.return_grid:
+            p.batch_size = 1
+
+
         CLIP_stop_at_last_layers = opts.CLIP_stop_at_last_layers
 
         def process_axis(opt, vals):
-- 
cgit v1.2.3


From bc3e183b739913e7be91213a256f038b10eb71e9 Mon Sep 17 00:00:00 2001
From: alg-wiki <alg.4chan@gmail.com>
Date: Tue, 11 Oct 2022 04:30:13 +0900
Subject: Textual Inversion: Preprocess and Training will only pick-up image
 files

---
 modules/textual_inversion/dataset.py           | 3 ++-
 modules/textual_inversion/preprocess.py        | 3 ++-
 modules/textual_inversion/textual_inversion.py | 3 ++-
 3 files changed, 6 insertions(+), 3 deletions(-)

diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index bcf772d2..d4baf066 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -22,6 +22,7 @@ class PersonalizedBase(Dataset):
         self.width = width
         self.height = height
         self.flip = transforms.RandomHorizontalFlip(p=flip_p)
+        self.extns = [".jpg",".jpeg",".png"]
 
         self.dataset = []
 
@@ -32,7 +33,7 @@ class PersonalizedBase(Dataset):
 
         assert data_root, 'dataset directory not specified'
 
-        self.image_paths = [os.path.join(data_root, file_path) for file_path in os.listdir(data_root)]
+        self.image_paths = [os.path.join(data_root, file_path) for file_path in os.listdir(data_root) if os.path.splitext(file_path.casefold())[1] in self.extns]
         print("Preparing dataset...")
         for path in tqdm.tqdm(self.image_paths):
             image = Image.open(path)
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index d7efdef2..b6c78cf8 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -12,12 +12,13 @@ def preprocess(process_src, process_dst, process_width, process_height, process_
     height = process_height
     src = os.path.abspath(process_src)
     dst = os.path.abspath(process_dst)
+    extns = [".jpg",".jpeg",".png"]
 
     assert src != dst, 'same directory specified as source and destination'
 
     os.makedirs(dst, exist_ok=True)
 
-    files = os.listdir(src)
+    files = [i for i in os.listdir(src) if os.path.splitext(i.casefold())[1] in extns]
 
     shared.state.textinfo = "Preprocessing..."
     shared.state.job_count = len(files)
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 5965c5a0..45397be9 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -161,6 +161,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
 
     shared.state.textinfo = "Initializing textual inversion training..."
     shared.state.job_count = steps
+    extns = [".jpg",".jpeg",".png"]
 
     filename = os.path.join(shared.cmd_opts.embeddings_dir, f'{embedding_name}.pt')
 
@@ -200,7 +201,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
     if ititial_step > steps:
         return embedding, filename
 
-    tr_img_len = len([os.path.join(data_root, file_path) for file_path in os.listdir(data_root)])
+    tr_img_len = len([os.path.join(data_root, file_path) for file_path in os.listdir(data_root) if os.path.splitext(file_path.casefold())[1] in extns])
     epoch_len = (tr_img_len * num_repeats) + tr_img_len
 
     pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step)
-- 
cgit v1.2.3


From f98338faa84ecce503e68d8ba13d5f7bbae52730 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 10 Oct 2022 23:15:48 +0300
Subject: add an option to not add watermark to created images

---
 javascript/hints.js | 1 +
 modules/shared.py   | 1 +
 2 files changed, 2 insertions(+)

diff --git a/javascript/hints.js b/javascript/hints.js
index 47b80776..045f2d3c 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -80,6 +80,7 @@ titles = {
     "Scale latent": "Uscale the image in latent space. Alternative is to produce the full image from latent representation, upscale that, and then move it back to latent space.",
 
     "Eta noise seed delta": "If this values is non-zero, it will be added to seed and used to initialize RNG for noises when using samplers with Eta. You can use this to produce even more variation of images, or you can use this to match images of other software if you know what you are doing.",
+    "Do not add watermark to images": "If this option is enabled, watermark will not be added to created images. Warning: if you do not add watermark, you may be bevaing in an unethical manner.",
 }
 
 
diff --git a/modules/shared.py b/modules/shared.py
index da389f9c..ecd15ef5 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -173,6 +173,7 @@ options_templates.update(options_section(('saving-images', "Saving images/grids"
 
     "use_original_name_batch": OptionInfo(False, "Use original name for output filename during batch process in extras tab"),
     "save_selected_only": OptionInfo(True, "When using 'Save' button, only save a single selected image"),
+    "do_not_add_watermark": OptionInfo(False, "Do not add watermark to images"),
 }))
 
 options_templates.update(options_section(('saving-paths', "Paths for saving"), {
-- 
cgit v1.2.3


From 42bf5fa3256bff5e4640e5a626e750d4e49e01e1 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Mon, 10 Oct 2022 21:54:21 +0100
Subject: Make cancel generate forever let the current gen complete (#2206)

---
 javascript/contextMenus.js | 4 ----
 1 file changed, 4 deletions(-)

diff --git a/javascript/contextMenus.js b/javascript/contextMenus.js
index 2d82269f..7852793c 100644
--- a/javascript/contextMenus.js
+++ b/javascript/contextMenus.js
@@ -147,10 +147,6 @@ generateOnRepeatId = appendContextMenuOption('#txt2img_generate','Generate forev
 
 cancelGenerateForever = function(){ 
   clearInterval(window.generateOnRepeatInterval) 
-  let interruptbutton = gradioApp().querySelector('#txt2img_interrupt');
-  if(interruptbutton.offsetParent){
-      interruptbutton.click();
-  }
 }
 
 appendContextMenuOption('#txt2img_interrupt','Cancel generate forever',cancelGenerateForever)
-- 
cgit v1.2.3


From 2536ecbb1790da2af0d61b6a26f38732cba665cd Mon Sep 17 00:00:00 2001
From: Fampai <>
Date: Mon, 10 Oct 2022 17:10:29 -0400
Subject: Refactored learning rate code

---
 modules/textual_inversion/textual_inversion.py | 51 ++++++++++++++++++++++++--
 modules/ui.py                                  |  2 +-
 2 files changed, 48 insertions(+), 5 deletions(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 5965c5a0..c64a4598 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -189,8 +189,6 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
     embedding = hijack.embedding_db.word_embeddings[embedding_name]
     embedding.vec.requires_grad = True
 
-    optimizer = torch.optim.AdamW([embedding.vec], lr=learn_rate)
-
     losses = torch.zeros((32,))
 
     last_saved_file = "<none>"
@@ -203,12 +201,24 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
     tr_img_len = len([os.path.join(data_root, file_path) for file_path in os.listdir(data_root)])
     epoch_len = (tr_img_len * num_repeats) + tr_img_len
 
+    scheduleIter = iter(LearnSchedule(learn_rate, steps, ititial_step))
+    (learn_rate, end_step) = next(scheduleIter)
+    print(f'Training at rate of {learn_rate} until step {end_step}')
+
+    optimizer = torch.optim.AdamW([embedding.vec], lr=learn_rate)
+
     pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step)
     for i, (x, text) in pbar:
         embedding.step = i + ititial_step
 
-        if embedding.step > steps:
-            break
+        if embedding.step > end_step:
+            try:
+                (learn_rate, end_step) = next(scheduleIter)
+            except:
+                break
+            tqdm.tqdm.write(f'Training at rate of {learn_rate} until step {end_step}')
+            for pg in optimizer.param_groups:
+                pg['lr'] = learn_rate
 
         if shared.state.interrupted:
             break
@@ -277,3 +287,36 @@ Last saved image: {html.escape(last_saved_image)}<br/>
 
     return embedding, filename
 
+class LearnSchedule:
+    def __init__(self, learn_rate, max_steps, cur_step=0):
+        pairs = learn_rate.split(',')
+        self.rates = []
+        self.it = 0
+        self.maxit = 0
+        for i, pair in enumerate(pairs):
+            tmp = pair.split(':')
+            if len(tmp) == 2:
+                step = int(tmp[1])
+                if step > cur_step:
+                    self.rates.append((float(tmp[0]), min(step, max_steps)))
+                    self.maxit += 1
+                    if step > max_steps:
+                        return
+                elif step == -1:
+                    self.rates.append((float(tmp[0]), max_steps))
+                    self.maxit += 1
+                    return
+            else:
+                self.rates.append((float(tmp[0]), max_steps))
+                self.maxit += 1
+                return
+
+    def __iter__(self):
+        return self
+
+    def __next__(self):
+        if self.it < self.maxit:
+            self.it += 1
+            return self.rates[self.it - 1]
+        else:
+            raise StopIteration
diff --git a/modules/ui.py b/modules/ui.py
index 8c06ad7c..c9e8355b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1047,7 +1047,7 @@ def create_ui(wrap_gradio_gpu_call):
                 with gr.Group():
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding; must specify a directory with a set of 1:1 ratio images</p>")
                     train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
-                    learn_rate = gr.Number(label='Learning rate', value=5.0e-03)
+                    learn_rate = gr.Textbox(label='Learning rate', placeholder="Learning rate", value = "5.0e-03")
                     dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images")
                     log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")
                     template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"))
-- 
cgit v1.2.3


From 907a88b2d0be320575c2129d8d6a1d4f3a68f9eb Mon Sep 17 00:00:00 2001
From: alg-wiki <alg.4chan@gmail.com>
Date: Tue, 11 Oct 2022 06:33:08 +0900
Subject: Added .webp .bmp

---
 modules/textual_inversion/dataset.py           | 2 +-
 modules/textual_inversion/preprocess.py        | 2 +-
 modules/textual_inversion/textual_inversion.py | 2 +-
 3 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index d4baf066..0dc54fb7 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -22,7 +22,7 @@ class PersonalizedBase(Dataset):
         self.width = width
         self.height = height
         self.flip = transforms.RandomHorizontalFlip(p=flip_p)
-        self.extns = [".jpg",".jpeg",".png"]
+        self.extns = [".jpg",".jpeg",".png",".webp",".bmp"]
 
         self.dataset = []
 
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index b6c78cf8..8290abe8 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -12,7 +12,7 @@ def preprocess(process_src, process_dst, process_width, process_height, process_
     height = process_height
     src = os.path.abspath(process_src)
     dst = os.path.abspath(process_dst)
-    extns = [".jpg",".jpeg",".png"]
+    extns = [".jpg",".jpeg",".png",".webp",".bmp"]
 
     assert src != dst, 'same directory specified as source and destination'
 
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index a03b299c..33c923d1 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -161,7 +161,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
 
     shared.state.textinfo = "Initializing textual inversion training..."
     shared.state.job_count = steps
-    extns = [".jpg",".jpeg",".png"]
+    extns = [".jpg",".jpeg",".png",".webp",".bmp"]
 
     filename = os.path.join(shared.cmd_opts.embeddings_dir, f'{embedding_name}.pt')
 
-- 
cgit v1.2.3


From a1a05ad2d13d0b995dbf8ecead6315f17837ef81 Mon Sep 17 00:00:00 2001
From: JC_Array <justin318@att.net>
Date: Mon, 10 Oct 2022 16:47:58 -0500
Subject: import time missing, added to deepbooru fixxing error on
 get_deepbooru_tags

---
 modules/deepbooru.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index cee4a3b4..12555b2e 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -1,6 +1,7 @@
 import os.path
 from concurrent.futures import ProcessPoolExecutor
 import multiprocessing
+import time
 
 
 def get_deepbooru_tags(pil_image, threshold=0.5):
-- 
cgit v1.2.3


From b980e7188c671fc55b26557f097076fb5c976ba0 Mon Sep 17 00:00:00 2001
From: JC_Array <justin318@att.net>
Date: Mon, 10 Oct 2022 16:52:54 -0500
Subject: corrected tag return in get_deepbooru_tags

---
 modules/deepbooru.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index 12555b2e..ebdba5e0 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -15,7 +15,6 @@ def get_deepbooru_tags(pil_image, threshold=0.5):
     while shared.deepbooru_process_return["value"] == -1:
         time.sleep(0.2)
     release_process()
-    return ret
 
 
 def deepbooru_process(queue, deepbooru_process_return, threshold):
-- 
cgit v1.2.3


From 315d5a8ed975c88f670bc484f40a23fbf3a77b63 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Mon, 10 Oct 2022 23:14:44 +0100
Subject: update data dis[play style

---
 modules/textual_inversion/textual_inversion.py | 88 +++++++++++++++++++-------
 1 file changed, 65 insertions(+), 23 deletions(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 667a7cf2..95eebea7 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -39,20 +39,59 @@ def embeddingFromB64(data):
     d = base64.b64decode(data)
     return json.loads(d,cls=EmbeddingDecoder)
 
-def appendImageDataFooter(image,data):
+def xorBlock(block):
+    return np.bitwise_xor(block.astype(np.uint8),
+                          ((np.random.RandomState(0xDEADBEEF).random(block.shape)*255).astype(np.uint8)) & 0x0F )
+
+def styleBlock(block,sequence):
+    im = Image.new('RGB',(block.shape[1],block.shape[0]))
+    draw = ImageDraw.Draw(im)
+    i=0
+    for x in range(-6,im.size[0],8):
+        for yi,y in enumerate(range(-6,im.size[1],8)):
+            offset=0
+            if yi%2==0:
+                offset=4
+            shade = sequence[i%len(sequence)]
+            i+=1
+            draw.ellipse((x+offset, y, x+6+offset, y+6), fill =(shade,shade,shade) )
+
+    fg = np.array(im).astype(np.uint8) & 0xF0
+    return block ^ fg
+
+def insertImageDataEmbed(image,data):
     d = 3
     data_compressed = zlib.compress( json.dumps(data,cls=EmbeddingEncoder).encode(),level=9)
     dnp = np.frombuffer(data_compressed,np.uint8).copy()
-    w = image.size[0]
-    next_size = dnp.shape[0] + (w-(dnp.shape[0]%w))
-    next_size = next_size + ((w*d)-(next_size%(w*d)))
-    dnp.resize(next_size)
-    dnp = dnp.reshape((-1,w,d))
-    print(dnp.shape)
-    im = Image.fromarray(dnp,mode='RGB')
-    background = Image.new('RGB',(image.size[0],image.size[1]+im.size[1]+1),(0,0,0))
-    background.paste(image,(0,0))
-    background.paste(im,(0,image.size[1]+1))
+    dnphigh = dnp >> 4
+    dnplow  = dnp & 0x0F
+    
+    h = image.size[1]
+    next_size = dnplow.shape[0] + (h-(dnplow.shape[0]%h))
+    next_size = next_size + ((h*d)-(next_size%(h*d)))
+
+    dnplow.resize(next_size)
+    dnplow = dnplow.reshape((h,-1,d))
+
+    dnphigh.resize(next_size)
+    dnphigh = dnphigh.reshape((h,-1,d))
+
+    edgeStyleWeights = list(data['string_to_param'].values())[0].cpu().detach().numpy().tolist()[0][:1024]
+    edgeStyleWeights = (np.abs(edgeStyleWeights)/np.max(np.abs(edgeStyleWeights))*255).astype(np.uint8)
+
+    dnplow   = styleBlock(dnplow,sequence=edgeStyleWeights)
+    dnplow   = xorBlock(dnplow)    
+    dnphigh  = styleBlock(dnphigh,sequence=edgeStyleWeights[::-1])
+    dnphigh  = xorBlock(dnphigh)
+
+    imlow  = Image.fromarray(dnplow,mode='RGB')
+    imhigh = Image.fromarray(dnphigh,mode='RGB')
+
+    background = Image.new('RGB',(image.size[0]+imlow.size[0]+imhigh.size[0]+2,image.size[1]),(0,0,0))
+    background.paste(imlow,(0,0))
+    background.paste(image,(imlow.size[0]+1,0))
+    background.paste(imhigh,(imlow.size[0]+1+image.size[0]+1,0))
+
     return background
 
 def crop_black(img,tol=0):
@@ -62,19 +101,22 @@ def crop_black(img,tol=0):
     row_start,row_end = mask1.argmax(),mask.shape[0]-mask1[::-1].argmax()
     return img[row_start:row_end,col_start:col_end]
 
-def extractImageDataFooter(image):
+def extractImageDataEmbed(image):
     d=3
-    outarr = crop_black(np.array(image.convert('RGB').getdata()).reshape(image.size[1],image.size[0],d ).astype(np.uint8) )
-    lastRow = np.where( np.sum(outarr, axis=(1,2))==0)
-    if lastRow[0].shape[0] == 0:
-        print('Image data block not found.')
+    outarr = crop_black(np.array(image.getdata()).reshape(image.size[1],image.size[0],d ).astype(np.uint8) ) & 0x0F
+    blackCols = np.where( np.sum(outarr, axis=(0,2))==0)
+    if blackCols[0].shape[0] < 2:
+        print('No Image data blocks found.')
         return None
-    lastRow = lastRow[0]
-    
-    lastRow = lastRow.max()
 
-    dataBlock = outarr[lastRow+1::].astype(np.uint8).flatten().tobytes()
-    print(lastRow)
+    dataBlocklower = outarr[:,:blackCols[0].min(),:].astype(np.uint8)
+    dataBlockupper = outarr[:,blackCols[0].max()+1:,:].astype(np.uint8)
+
+    dataBlocklower = xorBlock(dataBlocklower)
+    dataBlockupper = xorBlock(dataBlockupper)
+    
+    dataBlock = (dataBlockupper << 4) | (dataBlocklower)
+    dataBlock = dataBlock.flatten().tobytes()   
     data = zlib.decompress(dataBlock)
     return json.loads(data,cls=EmbeddingDecoder)
 
@@ -154,7 +196,7 @@ class EmbeddingDatabase:
                     data = embeddingFromB64(embed_image.text['sd-ti-embedding'])
                     name = data.get('name',name)
                 else:
-                    data = extractImageDataFooter(embed_image)
+                    data = extractImageDataEmbed(embed_image)
                     name = data.get('name',name)
             else:
                 data = torch.load(path, map_location="cpu")
@@ -351,7 +393,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
                 footer_right = '{}'.format(embedding.step)
 
                 captioned_image = captionImageOverlay(image,title,footer_left,footer_mid,footer_right)
-                captioned_image = appendImageDataFooter(captioned_image,data)
+                captioned_image = insertImageDataEmbed(captioned_image,data)
 
                 captioned_image.save(last_saved_image_chunks, "PNG", pnginfo=info)
             
-- 
cgit v1.2.3


From 767202a4c324f9b49f63ab4dabbb5736fe9df6e5 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Mon, 10 Oct 2022 23:20:52 +0100
Subject: add dependency

---
 modules/textual_inversion/textual_inversion.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 95eebea7..f3cacaa0 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -7,7 +7,7 @@ import tqdm
 import html
 import datetime
 
-from PIL import Image,PngImagePlugin
+from PIL import Image,PngImagePlugin,ImageDraw
 from ..images import captionImageOverlay
 import numpy as np
 import base64
-- 
cgit v1.2.3


From e0fbe6d27e7b4505766c8cb5a4264e1114cf3721 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Mon, 10 Oct 2022 23:26:24 +0100
Subject: colour depth conversion fix

---
 modules/textual_inversion/textual_inversion.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index f3cacaa0..ae807268 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -103,7 +103,7 @@ def crop_black(img,tol=0):
 
 def extractImageDataEmbed(image):
     d=3
-    outarr = crop_black(np.array(image.getdata()).reshape(image.size[1],image.size[0],d ).astype(np.uint8) ) & 0x0F
+    outarr = crop_black(np.array(image.convert('RGB').getdata()).reshape(image.size[1],image.size[0],d ).astype(np.uint8) ) & 0x0F
     blackCols = np.where( np.sum(outarr, axis=(0,2))==0)
     if blackCols[0].shape[0] < 2:
         print('No Image data blocks found.')
-- 
cgit v1.2.3


From 76ef3d75f61253516c024553335d9083d9660a8a Mon Sep 17 00:00:00 2001
From: JC_Array <justin318@att.net>
Date: Mon, 10 Oct 2022 18:01:49 -0500
Subject: added deepbooru settings (threshold and sort by alpha or likelyhood)

---
 modules/deepbooru.py | 36 +++++++++++++++++++++++++-----------
 modules/shared.py    |  6 ++++++
 2 files changed, 31 insertions(+), 11 deletions(-)

diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index ebdba5e0..e31e92c0 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -3,31 +3,32 @@ from concurrent.futures import ProcessPoolExecutor
 import multiprocessing
 import time
 
-
-def get_deepbooru_tags(pil_image, threshold=0.5):
+def get_deepbooru_tags(pil_image):
     """
     This method is for running only one image at a time for simple use.  Used to the img2img interrogate.
     """
     from modules import shared  # prevents circular reference
-    create_deepbooru_process(threshold)
+    create_deepbooru_process(shared.opts.deepbooru_threshold, shared.opts.deepbooru_sort_alpha)
     shared.deepbooru_process_return["value"] = -1
     shared.deepbooru_process_queue.put(pil_image)
     while shared.deepbooru_process_return["value"] == -1:
         time.sleep(0.2)
+    tags = shared.deepbooru_process_return["value"]
     release_process()
+    return tags
 
 
-def deepbooru_process(queue, deepbooru_process_return, threshold):
+def deepbooru_process(queue, deepbooru_process_return, threshold, alpha_sort):
     model, tags = get_deepbooru_tags_model()
     while True: # while process is running, keep monitoring queue for new image
         pil_image = queue.get()
         if pil_image == "QUIT":
             break
         else:
-            deepbooru_process_return["value"] = get_deepbooru_tags_from_model(model, tags, pil_image, threshold)
+            deepbooru_process_return["value"] = get_deepbooru_tags_from_model(model, tags, pil_image, threshold, alpha_sort)
 
 
-def create_deepbooru_process(threshold=0.5):
+def create_deepbooru_process(threshold, alpha_sort):
     """
     Creates deepbooru process.  A queue is created to send images into the process.  This enables multiple images
     to be processed in a row without reloading the model or creating a new process.  To return the data, a shared
@@ -40,7 +41,7 @@ def create_deepbooru_process(threshold=0.5):
     shared.deepbooru_process_queue = shared.deepbooru_process_manager.Queue()
     shared.deepbooru_process_return = shared.deepbooru_process_manager.dict()
     shared.deepbooru_process_return["value"] = -1
-    shared.deepbooru_process = multiprocessing.Process(target=deepbooru_process, args=(shared.deepbooru_process_queue, shared.deepbooru_process_return, threshold))
+    shared.deepbooru_process = multiprocessing.Process(target=deepbooru_process, args=(shared.deepbooru_process_queue, shared.deepbooru_process_return, threshold, alpha_sort))
     shared.deepbooru_process.start()
 
 
@@ -80,7 +81,7 @@ def get_deepbooru_tags_model():
     return model, tags
 
 
-def get_deepbooru_tags_from_model(model, tags, pil_image, threshold=0.5):
+def get_deepbooru_tags_from_model(model, tags, pil_image, threshold, alpha_sort):
     import deepdanbooru as dd
     import tensorflow as tf
     import numpy as np
@@ -105,15 +106,28 @@ def get_deepbooru_tags_from_model(model, tags, pil_image, threshold=0.5):
 
     for i, tag in enumerate(tags):
         result_dict[tag] = y[i]
-    result_tags_out = []
+
+    unsorted_tags_in_theshold = []
     result_tags_print = []
     for tag in tags:
         if result_dict[tag] >= threshold:
             if tag.startswith("rating:"):
                 continue
-            result_tags_out.append(tag)
+            unsorted_tags_in_theshold.append((result_dict[tag], tag))
             result_tags_print.append(f'{result_dict[tag]} {tag}')
 
+    # sort tags
+    result_tags_out = []
+    sort_ndx = 0
+    print(alpha_sort)
+    if alpha_sort:
+        sort_ndx = 1
+
+    # sort by reverse by likelihood and normal for alpha
+    unsorted_tags_in_theshold.sort(key=lambda y: y[sort_ndx], reverse=(not alpha_sort))
+    for weight, tag in unsorted_tags_in_theshold:
+        result_tags_out.append(tag)
+
     print('\n'.join(sorted(result_tags_print, reverse=True)))
 
-    return ', '.join(result_tags_out).replace('_', ' ').replace(':', ' ')
\ No newline at end of file
+    return ', '.join(result_tags_out).replace('_', ' ').replace(':', ' ')
diff --git a/modules/shared.py b/modules/shared.py
index 1995a99a..2e307809 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -261,6 +261,12 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters"
     's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
 }))
 
+if cmd_opts.deepdanbooru:
+    options_templates.update(options_section(('deepbooru-params', "DeepBooru parameters"), {
+        "deepbooru_sort_alpha": OptionInfo(True, "Sort Alphabetical", gr.Checkbox),
+        'deepbooru_threshold': OptionInfo(0.5, "Threshold", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
+    }))
+
 
 class Options:
     data = None
-- 
cgit v1.2.3


From 70b50b1dfcb0ce0f87998c994f4855014bc7e26b Mon Sep 17 00:00:00 2001
From: ClashSAN <98228077+ClashSAN@users.noreply.github.com>
Date: Mon, 10 Oct 2022 23:23:12 +0000
Subject: add features, credit for Composable Diffusion

to readme

https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/2171
---
 README.md | 10 ++++++++--
 1 file changed, 8 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index 561eb03d..0e938768 100644
--- a/README.md
+++ b/README.md
@@ -28,10 +28,12 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
     - CodeFormer, face restoration tool as an alternative to GFPGAN
     - RealESRGAN, neural network upscaler
     - ESRGAN, neural network upscaler with a lot of third party models
-    - SwinIR, neural network upscaler
+    - SwinIR and Swin2SR([see here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/2092)), neural network upscalers
     - LDSR, Latent diffusion super resolution upscaling
 - Resizing aspect ratio options
 - Sampling method selection
+    - Adjust sampler eta values (noise multiplier)
+    - More advanced noise setting options
 - Interrupt processing at any time
 - 4GB video card support (also reports of 2GB working)
 - Correct seeds for batches
@@ -67,6 +69,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
      - also supports weights for prompts: `a cat :1.2 AND a dog AND a penguin :2.2`
 - No token limit for prompts (original stable diffusion lets you use up to 75 tokens)
 - DeepDanbooru integration, creates danbooru style tags for anime prompts (add --deepdanbooru to commandline args)
+- [xformers](https://github.com/mv-lab/swin2sr), major speed increase for select cards: (add --xformers to commandline args)
 
 ## Installation and Running
 Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for both [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended) and [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs.
@@ -116,6 +119,7 @@ The documentation was moved from this README over to the project's [wiki](https:
 - CodeFormer - https://github.com/sczhou/CodeFormer
 - ESRGAN - https://github.com/xinntao/ESRGAN
 - SwinIR - https://github.com/JingyunLiang/SwinIR
+- Swin2SR - https://github.com/mv-lab/swin2sr
 - LDSR - https://github.com/Hafiidz/latent-diffusion
 - Ideas for optimizations - https://github.com/basujindal/stable-diffusion
 - Doggettx - Cross Attention layer optimization - https://github.com/Doggettx/stable-diffusion, original idea for prompt editing.
@@ -123,6 +127,8 @@ The documentation was moved from this README over to the project's [wiki](https:
 - Idea for SD upscale - https://github.com/jquesnelle/txt2imghd
 - Noise generation for outpainting mk2 - https://github.com/parlance-zz/g-diffuser-bot
 - CLIP interrogator idea and borrowing some code - https://github.com/pharmapsychotic/clip-interrogator
+- Idea for Composable Diffusion - https://github.com/energy-based-model/Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch
+- xformers - https://github.com/facebookresearch/xformers
+- DeepDanbooru - interrogator for anime diffusers https://github.com/KichangKim/DeepDanbooru
 - Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user.
-- DeepDanbooru - interrogator for anime diffusors https://github.com/KichangKim/DeepDanbooru
 - (You)
-- 
cgit v1.2.3


From bb932dbf9faf43ba918daa4791873078797b2a48 Mon Sep 17 00:00:00 2001
From: JC_Array <justin318@att.net>
Date: Mon, 10 Oct 2022 18:37:52 -0500
Subject: added alpha sort and threshold variables to create process method in
 preprocessing

---
 modules/textual_inversion/preprocess.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index 4a2194da..c0af729b 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -29,7 +29,7 @@ def preprocess(process_src, process_dst, process_width, process_height, process_
         shared.interrogator.load()
 
     if process_caption_deepbooru:
-        deepbooru.create_deepbooru_process()
+        deepbooru.create_deepbooru_process(opts.deepbooru_threshold, opts.deepbooru_sort_alpha)
 
     def save_pic_with_caption(image, index):
         if process_caption:
-- 
cgit v1.2.3


From 1add3cff84b7e2436d69b1e97ae689281e4a7c33 Mon Sep 17 00:00:00 2001
From: papuSpartan <mcgpapu@gmail.com>
Date: Mon, 10 Oct 2022 19:57:43 -0500
Subject: Refresh list of models/ckpts upon hitting restart gradio in the
 settings pane

---
 modules/ui.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/modules/ui.py b/modules/ui.py
index e8039d76..06ff118f 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -39,6 +39,7 @@ import modules.generation_parameters_copypaste
 from modules import prompt_parser
 from modules.images import save_image
 import modules.textual_inversion.ui
+from modules.sd_models import list_models
 
 # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI
 mimetypes.init()
@@ -1290,6 +1291,9 @@ Requested path was: {f}
             shared.state.interrupt()
             settings_interface.gradio_ref.do_restart = True
 
+            # refresh models so that new models/.ckpt's show up on reload
+            list_models()
+
         restart_gradio.click(
             fn=request_restart,
             inputs=[],
-- 
cgit v1.2.3


From 7aa8fcac1e45c3ad9c6a40df0e44a346afcd5032 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Tue, 11 Oct 2022 04:17:36 +0100
Subject: use simple lcg in xor

---
 modules/textual_inversion/textual_inversion.py | 10 ++++++++--
 1 file changed, 8 insertions(+), 2 deletions(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index ae807268..13416a08 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -39,9 +39,15 @@ def embeddingFromB64(data):
     d = base64.b64decode(data)
     return json.loads(d,cls=EmbeddingDecoder)
 
+def lcg(m=2**32, a=1664525, c=1013904223, seed=0):
+    while True:
+        seed = (a * seed + c) % m
+        yield seed
+
 def xorBlock(block):
-    return np.bitwise_xor(block.astype(np.uint8),
-                          ((np.random.RandomState(0xDEADBEEF).random(block.shape)*255).astype(np.uint8)) & 0x0F )
+    g = lcg()
+    randblock = np.array([next(g) for _ in range(np.product(block.shape))]).astype(np.uint8).reshape(block.shape)
+    return np.bitwise_xor(block.astype(np.uint8),randblock & 0x0F) 
 
 def styleBlock(block,sequence):
     im = Image.new('RGB',(block.shape[1],block.shape[0]))
-- 
cgit v1.2.3


From 8b7d3f1bef47bbe048f644ed0d8dd3ad46554045 Mon Sep 17 00:00:00 2001
From: Jairo Correa <jn.j41r0@gmail.com>
Date: Tue, 11 Oct 2022 02:22:46 -0300
Subject: Make the ctrl+enter shortcut use the generate button on the current
 tab

---
 modules/ui.py |  2 +-
 script.js     | 11 +++++++++--
 2 files changed, 10 insertions(+), 3 deletions(-)

diff --git a/modules/ui.py b/modules/ui.py
index e8039d76..cafda884 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1331,7 +1331,7 @@ Requested path was: {f}
         
         with gr.Tabs() as tabs:
             for interface, label, ifid in interfaces:
-                with gr.TabItem(label, id=ifid):
+                with gr.TabItem(label, id=ifid, elem_id='tab_' + ifid):
                     interface.render()
         
         if os.path.exists(os.path.join(script_path, "notification.mp3")):
diff --git a/script.js b/script.js
index a92c0f77..9543cbe6 100644
--- a/script.js
+++ b/script.js
@@ -6,6 +6,10 @@ function get_uiCurrentTab() {
     return gradioApp().querySelector('.tabs button:not(.border-transparent)')
 }
 
+function get_uiCurrentTabContent() {
+    return gradioApp().querySelector('.tabitem[id^=tab_]:not([style*="display: none"])')
+}
+
 uiUpdateCallbacks = []
 uiTabChangeCallbacks = []
 let uiCurrentTab = null
@@ -50,8 +54,11 @@ document.addEventListener("DOMContentLoaded", function() {
     } else if (e.keyCode !== undefined) {
         if((e.keyCode == 13 && (e.metaKey || e.ctrlKey))) handled = true;
     }
-    if (handled) { 
-        gradioApp().querySelector("#txt2img_generate").click(); 
+    if (handled) {
+        button = get_uiCurrentTabContent().querySelector('button[id$=_generate]');
+        if (button) {
+            button.click();
+        }
         e.preventDefault();
     }
 })
-- 
cgit v1.2.3


From 8617396c6df71074c7fd3d39419802026874712a Mon Sep 17 00:00:00 2001
From: Kenneth <kenneth.mccarthy24@yahoo.com>
Date: Mon, 10 Oct 2022 17:23:07 -0600
Subject: Added slider for deepbooru score threshold in settings

---
 modules/shared.py | 1 +
 modules/ui.py     | 2 +-
 2 files changed, 2 insertions(+), 1 deletion(-)

diff --git a/modules/shared.py b/modules/shared.py
index ecd15ef5..e0830e28 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -239,6 +239,7 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"),
     "interrogate_clip_min_length": OptionInfo(24, "Interrogate: minimum description length (excluding artists, etc..)", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}),
     "interrogate_clip_max_length": OptionInfo(48, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}),
     "interrogate_clip_dict_limit": OptionInfo(1500, "Interrogate: maximum number of lines in text file (0 = No limit)"),
+    "interrogate_deepbooru_score_threshold": OptionInfo(0.5, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
 }))
 
 options_templates.update(options_section(('ui', "User interface"), {
diff --git a/modules/ui.py b/modules/ui.py
index cafda884..ca3151c4 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -311,7 +311,7 @@ def interrogate(image):
 
 
 def interrogate_deepbooru(image):
-    prompt = get_deepbooru_tags(image)
+    prompt = get_deepbooru_tags(image, opts.interrogate_deepbooru_score_threshold)
     return gr_show(True) if prompt is None else prompt
 
 
-- 
cgit v1.2.3


From 5e2627a1a63e4c9f87e6e604ecc24e9936f149de Mon Sep 17 00:00:00 2001
From: hentailord85ez <112723046+hentailord85ez@users.noreply.github.com>
Date: Tue, 11 Oct 2022 07:55:28 +0100
Subject: Comma backtrack padding (#2192)

Comma backtrack padding
---
 modules/sd_hijack.py | 19 ++++++++++++++++++-
 modules/shared.py    |  1 +
 2 files changed, 19 insertions(+), 1 deletion(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 827bf304..aa4d2cbc 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -107,6 +107,8 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
         self.tokenizer = wrapped.tokenizer
         self.token_mults = {}
 
+        self.comma_token = [v for k, v in self.tokenizer.get_vocab().items() if k == ',</w>'][0]
+
         tokens_with_parens = [(k, v) for k, v in self.tokenizer.get_vocab().items() if '(' in k or ')' in k or '[' in k or ']' in k]
         for text, ident in tokens_with_parens:
             mult = 1.0
@@ -136,6 +138,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
         fixes = []
         remade_tokens = []
         multipliers = []
+        last_comma = -1
 
         for tokens, (text, weight) in zip(tokenized, parsed):
             i = 0
@@ -144,6 +147,20 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
 
                 embedding, embedding_length_in_tokens = self.hijack.embedding_db.find_embedding_at_position(tokens, i)
 
+                if token == self.comma_token:
+                    last_comma = len(remade_tokens)
+                elif opts.comma_padding_backtrack != 0 and max(len(remade_tokens), 1) % 75 == 0 and last_comma != -1 and len(remade_tokens) - last_comma <= opts.comma_padding_backtrack:
+                    last_comma += 1
+                    reloc_tokens = remade_tokens[last_comma:]
+                    reloc_mults = multipliers[last_comma:]
+
+                    remade_tokens = remade_tokens[:last_comma]
+                    length = len(remade_tokens)
+                    
+                    rem = int(math.ceil(length / 75)) * 75 - length
+                    remade_tokens += [id_end] * rem + reloc_tokens
+                    multipliers = multipliers[:last_comma] + [1.0] * rem + reloc_mults
+                
                 if embedding is None:
                     remade_tokens.append(token)
                     multipliers.append(weight)
@@ -284,7 +301,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
         while max(map(len, remade_batch_tokens)) != 0:
             rem_tokens = [x[75:] for x in remade_batch_tokens]
             rem_multipliers = [x[75:] for x in batch_multipliers]
-            
+
             self.hijack.fixes = []
             for unfiltered in hijack_fixes:
                 fixes = []
diff --git a/modules/shared.py b/modules/shared.py
index e0830e28..14b40d70 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -227,6 +227,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "enable_emphasis": OptionInfo(True, "Emphasis: use (text) to make model pay more attention to text and [text] to make it pay less attention"),
     "use_old_emphasis_implementation": OptionInfo(False, "Use old emphasis implementation. Can be useful to reproduce old seeds."),
     "enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"),
+    "comma_padding_backtrack": OptionInfo(20, "Increase coherency by padding from the last comma within n tokens when using more than 75 tokens", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1 }),
     "filter_nsfw": OptionInfo(False, "Filter NSFW content"),
     'CLIP_stop_at_last_layers': OptionInfo(1, "Stop At last layers of CLIP model", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}),
     "random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}),
-- 
cgit v1.2.3


From 948533950c9db5069a874d925fadd50bac00fdb5 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 11:09:51 +0300
Subject: replace duplicate code with a function

---
 modules/hypernetwork.py            | 23 ++++++++++++--------
 modules/sd_hijack_optimizations.py | 44 +++++++++++++-------------------------
 2 files changed, 29 insertions(+), 38 deletions(-)

diff --git a/modules/hypernetwork.py b/modules/hypernetwork.py
index 498bc9d8..7bbc443e 100644
--- a/modules/hypernetwork.py
+++ b/modules/hypernetwork.py
@@ -64,21 +64,26 @@ def load_hypernetwork(filename):
         shared.loaded_hypernetwork = None
 
 
+def apply_hypernetwork(hypernetwork, context):
+    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
+
+    if hypernetwork_layers is None:
+        return context, context
+
+    context_k = hypernetwork_layers[0](context)
+    context_v = hypernetwork_layers[1](context)
+    return context_k, context_v
+
+
 def attention_CrossAttention_forward(self, x, context=None, mask=None):
     h = self.heads
 
     q = self.to_q(x)
     context = default(context, x)
 
-    hypernetwork = shared.loaded_hypernetwork
-    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
-
-    if hypernetwork_layers is not None:
-        k = self.to_k(hypernetwork_layers[0](context))
-        v = self.to_v(hypernetwork_layers[1](context))
-    else:
-        k = self.to_k(context)
-        v = self.to_v(context)
+    context_k, context_v = apply_hypernetwork(shared.loaded_hypernetwork, context)
+    k = self.to_k(context_k)
+    v = self.to_v(context_v)
 
     q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
 
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index 18408e62..25cb67a4 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -8,7 +8,8 @@ from torch import einsum
 from ldm.util import default
 from einops import rearrange
 
-from modules import shared
+from modules import shared, hypernetwork
+
 
 if shared.cmd_opts.xformers or shared.cmd_opts.force_enable_xformers:
     try:
@@ -26,16 +27,10 @@ def split_cross_attention_forward_v1(self, x, context=None, mask=None):
     q_in = self.to_q(x)
     context = default(context, x)
 
-    hypernetwork = shared.loaded_hypernetwork
-    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
-
-    if hypernetwork_layers is not None:
-        k_in = self.to_k(hypernetwork_layers[0](context))
-        v_in = self.to_v(hypernetwork_layers[1](context))
-    else:
-        k_in = self.to_k(context)
-        v_in = self.to_v(context)
-    del context, x
+    context_k, context_v = hypernetwork.apply_hypernetwork(shared.loaded_hypernetwork, context)
+    k_in = self.to_k(context_k)
+    v_in = self.to_v(context_v)
+    del context, context_k, context_v, x
 
     q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q_in, k_in, v_in))
     del q_in, k_in, v_in
@@ -59,22 +54,16 @@ def split_cross_attention_forward_v1(self, x, context=None, mask=None):
     return self.to_out(r2)
 
 
-# taken from https://github.com/Doggettx/stable-diffusion
+# taken from https://github.com/Doggettx/stable-diffusion and modified
 def split_cross_attention_forward(self, x, context=None, mask=None):
     h = self.heads
 
     q_in = self.to_q(x)
     context = default(context, x)
 
-    hypernetwork = shared.loaded_hypernetwork
-    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
-
-    if hypernetwork_layers is not None:
-        k_in = self.to_k(hypernetwork_layers[0](context))
-        v_in = self.to_v(hypernetwork_layers[1](context))
-    else:
-        k_in = self.to_k(context)
-        v_in = self.to_v(context)
+    context_k, context_v = hypernetwork.apply_hypernetwork(shared.loaded_hypernetwork, context)
+    k_in = self.to_k(context_k)
+    v_in = self.to_v(context_v)
 
     k_in *= self.scale
 
@@ -130,14 +119,11 @@ def xformers_attention_forward(self, x, context=None, mask=None):
     h = self.heads
     q_in = self.to_q(x)
     context = default(context, x)
-    hypernetwork = shared.loaded_hypernetwork
-    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
-    if hypernetwork_layers is not None:
-        k_in = self.to_k(hypernetwork_layers[0](context))
-        v_in = self.to_v(hypernetwork_layers[1](context))
-    else:
-        k_in = self.to_k(context)
-        v_in = self.to_v(context)
+
+    context_k, context_v = hypernetwork.apply_hypernetwork(shared.loaded_hypernetwork, context)
+    k_in = self.to_k(context_k)
+    v_in = self.to_v(context_v)
+
     q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> b n h d', h=h), (q_in, k_in, v_in))
     del q_in, k_in, v_in
     out = xformers.ops.memory_efficient_attention(q, k, v, attn_bias=None)
-- 
cgit v1.2.3


From b2368a3bce663f19a7209d9cb38617e635ca6e3c Mon Sep 17 00:00:00 2001
From: alg-wiki <alg.4chan@gmail.com>
Date: Tue, 11 Oct 2022 17:32:46 +0900
Subject: Switched to exception handling

---
 modules/textual_inversion/dataset.py           | 10 +++++-----
 modules/textual_inversion/preprocess.py        |  8 +++++---
 modules/textual_inversion/textual_inversion.py | 18 ++++++++----------
 3 files changed, 18 insertions(+), 18 deletions(-)

diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index 0dc54fb7..4d006366 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -22,7 +22,6 @@ class PersonalizedBase(Dataset):
         self.width = width
         self.height = height
         self.flip = transforms.RandomHorizontalFlip(p=flip_p)
-        self.extns = [".jpg",".jpeg",".png",".webp",".bmp"]
 
         self.dataset = []
 
@@ -33,12 +32,13 @@ class PersonalizedBase(Dataset):
 
         assert data_root, 'dataset directory not specified'
 
-        self.image_paths = [os.path.join(data_root, file_path) for file_path in os.listdir(data_root) if os.path.splitext(file_path.casefold())[1] in self.extns]
+        self.image_paths = [os.path.join(data_root, file_path) for file_path in os.listdir(data_root)]
         print("Preparing dataset...")
         for path in tqdm.tqdm(self.image_paths):
-            image = Image.open(path)
-            image = image.convert('RGB')
-            image = image.resize((self.width, self.height), PIL.Image.BICUBIC)
+            try:
+                image = Image.open(path).convert('RGB').resize((self.width, self.height), PIL.Image.BICUBIC)
+            except Exception:
+                continue
 
             filename = os.path.basename(path)
             filename_tokens = os.path.splitext(filename)[0]
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index 8290abe8..1a672725 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -12,13 +12,12 @@ def preprocess(process_src, process_dst, process_width, process_height, process_
     height = process_height
     src = os.path.abspath(process_src)
     dst = os.path.abspath(process_dst)
-    extns = [".jpg",".jpeg",".png",".webp",".bmp"]
 
     assert src != dst, 'same directory specified as source and destination'
 
     os.makedirs(dst, exist_ok=True)
 
-    files = [i for i in os.listdir(src) if os.path.splitext(i.casefold())[1] in extns]
+    files = os.listdir(src)
 
     shared.state.textinfo = "Preprocessing..."
     shared.state.job_count = len(files)
@@ -47,7 +46,10 @@ def preprocess(process_src, process_dst, process_width, process_height, process_
     for index, imagefile in enumerate(tqdm.tqdm(files)):
         subindex = [0]
         filename = os.path.join(src, imagefile)
-        img = Image.open(filename).convert("RGB")
+        try:
+            img = Image.open(filename).convert("RGB")
+        except Exception:
+            continue
 
         if shared.state.interrupted:
             break
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 33c923d1..91cde04b 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -161,7 +161,6 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
 
     shared.state.textinfo = "Initializing textual inversion training..."
     shared.state.job_count = steps
-    extns = [".jpg",".jpeg",".png",".webp",".bmp"]
 
     filename = os.path.join(shared.cmd_opts.embeddings_dir, f'{embedding_name}.pt')
 
@@ -201,10 +200,6 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
     if ititial_step > steps:
         return embedding, filename
 
-    tr_img_len = len([os.path.join(data_root, file_path) for file_path in os.listdir(data_root) if os.path.splitext(file_path.casefold())[1] in extns])
-
-    epoch_len = (tr_img_len * num_repeats) + tr_img_len
-
     pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step)
     for i, (x, text) in pbar:
         embedding.step = i + ititial_step
@@ -228,10 +223,10 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
             loss.backward()
             optimizer.step()
 
-        epoch_num = embedding.step // epoch_len
-        epoch_step = embedding.step - (epoch_num * epoch_len) + 1
+        epoch_num = embedding.step // len(ds)
+        epoch_step = embedding.step - (epoch_num * len(ds)) + 1
 
-        pbar.set_description(f"[Epoch {epoch_num}: {epoch_step}/{epoch_len}]loss: {losses.mean():.7f}")
+        pbar.set_description(f"[Epoch {epoch_num}: {epoch_step}/{len(ds)}]loss: {losses.mean():.7f}")
 
         if embedding.step > 0 and embedding_dir is not None and embedding.step % save_embedding_every == 0:
             last_saved_file = os.path.join(embedding_dir, f'{embedding_name}-{embedding.step}.pt')
@@ -243,9 +238,12 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
             p = processing.StableDiffusionProcessingTxt2Img(
                 sd_model=shared.sd_model,
                 prompt=text,
-                steps=20,
-				height=training_height,
+                steps=28,
+				height=768,
 				width=training_width,
+                negative_prompt="lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts,signature, watermark, username, blurry, artist name",
+                cfg_scale=7.0,
+                sampler_index=0,
                 do_not_save_grid=True,
                 do_not_save_samples=True,
             )
-- 
cgit v1.2.3


From 8bacbca0a1ab9aabcb0ad0cbf070e0006991e98a Mon Sep 17 00:00:00 2001
From: alg-wiki <alg.4chan@gmail.com>
Date: Tue, 11 Oct 2022 17:35:09 +0900
Subject: Removed my local edits to checkpoint image generation

---
 modules/textual_inversion/textual_inversion.py | 7 ++-----
 1 file changed, 2 insertions(+), 5 deletions(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 91cde04b..e9ff80c2 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -238,12 +238,9 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
             p = processing.StableDiffusionProcessingTxt2Img(
                 sd_model=shared.sd_model,
                 prompt=text,
-                steps=28,
-				height=768,
+                steps=20,
+				height=training_height,
 				width=training_width,
-                negative_prompt="lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts,signature, watermark, username, blurry, artist name",
-                cfg_scale=7.0,
-                sampler_index=0,
                 do_not_save_grid=True,
                 do_not_save_samples=True,
             )
-- 
cgit v1.2.3


From 255be75d30f41e089e499ec1c8462d6bf64dec24 Mon Sep 17 00:00:00 2001
From: aperullo <18688190+aperullo@users.noreply.github.com>
Date: Tue, 11 Oct 2022 06:16:57 -0400
Subject: Error if prompt missing SR token to prevent mis-gens (#2209)

---
 scripts/xy_grid.py | 7 +++++++
 1 file changed, 7 insertions(+)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 42e1489c..10a82dc9 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -27,9 +27,16 @@ def apply_field(field):
 
 
 def apply_prompt(p, x, xs):
+
+    orig_prompt = p.prompt
+    orig_negative_prompt = p.negative_prompt
+
     p.prompt = p.prompt.replace(xs[0], x)
     p.negative_prompt = p.negative_prompt.replace(xs[0], x)
 
+    if p.prompt == orig_prompt and p.negative_prompt == orig_negative_prompt:
+        raise RuntimeError(f"Prompt S/R did not find {xs[0]} in prompt or negative prompt. Did you forget to add the token?")
+
 
 def apply_order(p, x, xs):
     token_order = []
-- 
cgit v1.2.3


From 4b460fcb1a0224772949556fe0469da93245c532 Mon Sep 17 00:00:00 2001
From: Rory Grieve <rhrg500@gmail.com>
Date: Tue, 11 Oct 2022 11:23:47 +0100
Subject: Reset init img in loopback at start of each batch (#2214)

Before a new batch would use the last image from the previous batch. Now
each batch will use the original image for the init image at the start of the
batch.
---
 scripts/loopback.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/scripts/loopback.py b/scripts/loopback.py
index e90b58d4..d8c68af8 100644
--- a/scripts/loopback.py
+++ b/scripts/loopback.py
@@ -38,6 +38,7 @@ class Script(scripts.Script):
 
         grids = []
         all_images = []
+        original_init_image = p.init_images
         state.job_count = loops * batch_count
 
         initial_color_corrections = [processing.setup_color_correction(p.init_images[0])]
@@ -45,6 +46,9 @@ class Script(scripts.Script):
         for n in range(batch_count):
             history = []
 
+            # Reset to original init image at the start of each batch
+            p.init_images = original_init_image
+
             for i in range(loops):
                 p.n_iter = 1
                 p.batch_size = 1
-- 
cgit v1.2.3


From a8490e4019c359ff24824e004059744d7164361b Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Tue, 11 Oct 2022 11:42:41 +0100
Subject: revert sr warning

---
 scripts/xy_grid.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 10a82dc9..99b3c4f6 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -35,7 +35,8 @@ def apply_prompt(p, x, xs):
     p.negative_prompt = p.negative_prompt.replace(xs[0], x)
 
     if p.prompt == orig_prompt and p.negative_prompt == orig_negative_prompt:
-        raise RuntimeError(f"Prompt S/R did not find {xs[0]} in prompt or negative prompt. Did you forget to add the token?")
+        pass
+        #raise RuntimeError(f"Prompt S/R did not find {xs[0]} in prompt or negative prompt. Did you forget to add the token?")
 
 
 def apply_order(p, x, xs):
-- 
cgit v1.2.3


From 1a0a6a84c3149e236211d547471f5416cd1129f3 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Tue, 11 Oct 2022 11:59:56 +0100
Subject: add incorrect start word guard to xy_grid (#2259)

---
 scripts/xy_grid.py | 9 ++-------
 1 file changed, 2 insertions(+), 7 deletions(-)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 99b3c4f6..9d4d6187 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -27,17 +27,12 @@ def apply_field(field):
 
 
 def apply_prompt(p, x, xs):
-
-    orig_prompt = p.prompt
-    orig_negative_prompt = p.negative_prompt
+    if xs[0] not in p.prompt and xs[0] not in p.negative_prompt:
+        raise RuntimeError(f"Prompt S/R did not find {xs[0]} in prompt or negative prompt.")
 
     p.prompt = p.prompt.replace(xs[0], x)
     p.negative_prompt = p.negative_prompt.replace(xs[0], x)
 
-    if p.prompt == orig_prompt and p.negative_prompt == orig_negative_prompt:
-        pass
-        #raise RuntimeError(f"Prompt S/R did not find {xs[0]} in prompt or negative prompt. Did you forget to add the token?")
-
 
 def apply_order(p, x, xs):
     token_order = []
-- 
cgit v1.2.3


From 530103b586109c11fd068eb70ef09503ec6a4caf Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 14:53:02 +0300
Subject: fixes related to merge

---
 modules/hypernetwork.py                        | 103 -------------------------
 modules/hypernetwork/hypernetwork.py           |  74 +++++++++++-------
 modules/hypernetwork/ui.py                     |  10 +--
 modules/sd_hijack_optimizations.py             |   3 +-
 modules/shared.py                              |  13 +++-
 modules/textual_inversion/textual_inversion.py |  12 +--
 modules/ui.py                                  |   5 +-
 scripts/xy_grid.py                             |   3 +-
 webui.py                                       |  15 +---
 9 files changed, 78 insertions(+), 160 deletions(-)
 delete mode 100644 modules/hypernetwork.py

diff --git a/modules/hypernetwork.py b/modules/hypernetwork.py
deleted file mode 100644
index 7bbc443e..00000000
--- a/modules/hypernetwork.py
+++ /dev/null
@@ -1,103 +0,0 @@
-import glob
-import os
-import sys
-import traceback
-
-import torch
-
-from ldm.util import default
-from modules import devices, shared
-import torch
-from torch import einsum
-from einops import rearrange, repeat
-
-
-class HypernetworkModule(torch.nn.Module):
-    def __init__(self, dim, state_dict):
-        super().__init__()
-
-        self.linear1 = torch.nn.Linear(dim, dim * 2)
-        self.linear2 = torch.nn.Linear(dim * 2, dim)
-
-        self.load_state_dict(state_dict, strict=True)
-        self.to(devices.device)
-
-    def forward(self, x):
-        return x + (self.linear2(self.linear1(x)))
-
-
-class Hypernetwork:
-    filename = None
-    name = None
-
-    def __init__(self, filename):
-        self.filename = filename
-        self.name = os.path.splitext(os.path.basename(filename))[0]
-        self.layers = {}
-
-        state_dict = torch.load(filename, map_location='cpu')
-        for size, sd in state_dict.items():
-            self.layers[size] = (HypernetworkModule(size, sd[0]), HypernetworkModule(size, sd[1]))
-
-
-def list_hypernetworks(path):
-    res = {}
-    for filename in glob.iglob(os.path.join(path, '**/*.pt'), recursive=True):
-        name = os.path.splitext(os.path.basename(filename))[0]
-        res[name] = filename
-    return res
-
-
-def load_hypernetwork(filename):
-    path = shared.hypernetworks.get(filename, None)
-    if path is not None:
-        print(f"Loading hypernetwork {filename}")
-        try:
-            shared.loaded_hypernetwork = Hypernetwork(path)
-        except Exception:
-            print(f"Error loading hypernetwork {path}", file=sys.stderr)
-            print(traceback.format_exc(), file=sys.stderr)
-    else:
-        if shared.loaded_hypernetwork is not None:
-            print(f"Unloading hypernetwork")
-
-        shared.loaded_hypernetwork = None
-
-
-def apply_hypernetwork(hypernetwork, context):
-    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
-
-    if hypernetwork_layers is None:
-        return context, context
-
-    context_k = hypernetwork_layers[0](context)
-    context_v = hypernetwork_layers[1](context)
-    return context_k, context_v
-
-
-def attention_CrossAttention_forward(self, x, context=None, mask=None):
-    h = self.heads
-
-    q = self.to_q(x)
-    context = default(context, x)
-
-    context_k, context_v = apply_hypernetwork(shared.loaded_hypernetwork, context)
-    k = self.to_k(context_k)
-    v = self.to_v(context_v)
-
-    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
-
-    sim = einsum('b i d, b j d -> b i j', q, k) * self.scale
-
-    if mask is not None:
-        mask = rearrange(mask, 'b ... -> b (...)')
-        max_neg_value = -torch.finfo(sim.dtype).max
-        mask = repeat(mask, 'b j -> (b h) () j', h=h)
-        sim.masked_fill_(~mask, max_neg_value)
-
-    # attention, what we cannot get enough of
-    attn = sim.softmax(dim=-1)
-
-    out = einsum('b i j, b j d -> b i d', attn, v)
-    out = rearrange(out, '(b h) n d -> b n (h d)', h=h)
-    return self.to_out(out)
diff --git a/modules/hypernetwork/hypernetwork.py b/modules/hypernetwork/hypernetwork.py
index a3d6a47e..aa701bda 100644
--- a/modules/hypernetwork/hypernetwork.py
+++ b/modules/hypernetwork/hypernetwork.py
@@ -26,10 +26,11 @@ class HypernetworkModule(torch.nn.Module):
         if state_dict is not None:
             self.load_state_dict(state_dict, strict=True)
         else:
-            self.linear1.weight.data.fill_(0.0001)
-            self.linear1.bias.data.fill_(0.0001)
-            self.linear2.weight.data.fill_(0.0001)
-            self.linear2.bias.data.fill_(0.0001)
+
+            self.linear1.weight.data.normal_(mean=0.0, std=0.01)
+            self.linear1.bias.data.zero_()
+            self.linear2.weight.data.normal_(mean=0.0, std=0.01)
+            self.linear2.bias.data.zero_()
 
         self.to(devices.device)
 
@@ -92,41 +93,54 @@ class Hypernetwork:
         self.sd_checkpoint_name = state_dict.get('sd_checkpoint_name', None)
 
 
-def load_hypernetworks(path):
+def list_hypernetworks(path):
     res = {}
+    for filename in glob.iglob(os.path.join(path, '**/*.pt'), recursive=True):
+        name = os.path.splitext(os.path.basename(filename))[0]
+        res[name] = filename
+    return res
 
-    for filename in glob.iglob(path + '**/*.pt', recursive=True):
+
+def load_hypernetwork(filename):
+    path = shared.hypernetworks.get(filename, None)
+    if path is not None:
+        print(f"Loading hypernetwork {filename}")
         try:
-            hn = Hypernetwork()
-            hn.load(filename)
-            res[hn.name] = hn
+            shared.loaded_hypernetwork = Hypernetwork()
+            shared.loaded_hypernetwork.load(path)
+
         except Exception:
-            print(f"Error loading hypernetwork {filename}", file=sys.stderr)
+            print(f"Error loading hypernetwork {path}", file=sys.stderr)
             print(traceback.format_exc(), file=sys.stderr)
+    else:
+        if shared.loaded_hypernetwork is not None:
+            print(f"Unloading hypernetwork")
 
-    return res
+        shared.loaded_hypernetwork = None
 
 
-def attention_CrossAttention_forward(self, x, context=None, mask=None):
-    h = self.heads
+def apply_hypernetwork(hypernetwork, context, layer=None):
+    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
 
-    q = self.to_q(x)
-    context = default(context, x)
+    if hypernetwork_layers is None:
+        return context, context
 
-    hypernetwork_layers = (shared.hypernetwork.layers if shared.hypernetwork is not None else {}).get(context.shape[2], None)
+    if layer is not None:
+        layer.hyper_k = hypernetwork_layers[0]
+        layer.hyper_v = hypernetwork_layers[1]
 
-    if hypernetwork_layers is not None:
-        hypernetwork_k, hypernetwork_v = hypernetwork_layers
+    context_k = hypernetwork_layers[0](context)
+    context_v = hypernetwork_layers[1](context)
+    return context_k, context_v
 
-        self.hypernetwork_k = hypernetwork_k
-        self.hypernetwork_v = hypernetwork_v
 
-        context_k = hypernetwork_k(context)
-        context_v = hypernetwork_v(context)
-    else:
-        context_k = context
-        context_v = context
+def attention_CrossAttention_forward(self, x, context=None, mask=None):
+    h = self.heads
+
+    q = self.to_q(x)
+    context = default(context, x)
 
+    context_k, context_v = apply_hypernetwork(shared.loaded_hypernetwork, context, self)
     k = self.to_k(context_k)
     v = self.to_v(context_v)
 
@@ -151,7 +165,9 @@ def attention_CrossAttention_forward(self, x, context=None, mask=None):
 def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_image_prompt):
     assert hypernetwork_name, 'embedding not selected'
 
-    shared.hypernetwork = shared.hypernetworks[hypernetwork_name]
+    path = shared.hypernetworks.get(hypernetwork_name, None)
+    shared.loaded_hypernetwork = Hypernetwork()
+    shared.loaded_hypernetwork.load(path)
 
     shared.state.textinfo = "Initializing hypernetwork training..."
     shared.state.job_count = steps
@@ -176,9 +192,9 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
 
     shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
     with torch.autocast("cuda"):
-        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, size=512, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file)
+        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=512, height=512, repeats=1, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file)
 
-    hypernetwork = shared.hypernetworks[hypernetwork_name]
+    hypernetwork = shared.loaded_hypernetwork
     weights = hypernetwork.weights()
     for weight in weights:
         weight.requires_grad = True
@@ -194,7 +210,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
     if ititial_step > steps:
         return hypernetwork, filename
 
-    pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step)
+    pbar = tqdm.tqdm(enumerate(ds), total=steps - ititial_step)
     for i, (x, text) in pbar:
         hypernetwork.step = i + ititial_step
 
diff --git a/modules/hypernetwork/ui.py b/modules/hypernetwork/ui.py
index 525f978c..f6d1d0a3 100644
--- a/modules/hypernetwork/ui.py
+++ b/modules/hypernetwork/ui.py
@@ -6,24 +6,24 @@ import gradio as gr
 import modules.textual_inversion.textual_inversion
 import modules.textual_inversion.preprocess
 from modules import sd_hijack, shared
+from modules.hypernetwork import hypernetwork
 
 
 def create_hypernetwork(name):
     fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt")
     assert not os.path.exists(fn), f"file {fn} already exists"
 
-    hypernetwork = modules.hypernetwork.hypernetwork.Hypernetwork(name=name)
-    hypernetwork.save(fn)
+    hypernet = modules.hypernetwork.hypernetwork.Hypernetwork(name=name)
+    hypernet.save(fn)
 
     shared.reload_hypernetworks()
-    shared.hypernetwork = shared.hypernetworks.get(shared.opts.sd_hypernetwork, None)
 
     return gr.Dropdown.update(choices=sorted([x for x in shared.hypernetworks.keys()])), f"Created: {fn}", ""
 
 
 def train_hypernetwork(*args):
 
-    initial_hypernetwork = shared.hypernetwork
+    initial_hypernetwork = shared.loaded_hypernetwork
 
     try:
         sd_hijack.undo_optimizations()
@@ -38,6 +38,6 @@ Hypernetwork saved to {html.escape(filename)}
     except Exception:
         raise
     finally:
-        shared.hypernetwork = initial_hypernetwork
+        shared.loaded_hypernetwork = initial_hypernetwork
         sd_hijack.apply_optimizations()
 
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index 25cb67a4..27e571fc 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -8,7 +8,8 @@ from torch import einsum
 from ldm.util import default
 from einops import rearrange
 
-from modules import shared, hypernetwork
+from modules import shared
+from modules.hypernetwork import hypernetwork
 
 
 if shared.cmd_opts.xformers or shared.cmd_opts.force_enable_xformers:
diff --git a/modules/shared.py b/modules/shared.py
index 14b40d70..8753015e 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -13,7 +13,8 @@ import modules.memmon
 import modules.sd_models
 import modules.styles
 import modules.devices as devices
-from modules import sd_samplers, hypernetwork
+from modules import sd_samplers
+from modules.hypernetwork import hypernetwork
 from modules.paths import models_path, script_path, sd_path
 
 sd_model_file = os.path.join(script_path, 'model.ckpt')
@@ -29,6 +30,7 @@ parser.add_argument("--no-half-vae", action='store_true', help="do not switch th
 parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware acceleration in browser)")
 parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI")
 parser.add_argument("--embeddings-dir", type=str, default=os.path.join(script_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)")
+parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_path, 'hypernetworks'), help="hypernetwork directory")
 parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui")
 parser.add_argument("--medvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a little speed for low VRM usage")
 parser.add_argument("--lowvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a lot of speed for very low VRM usage")
@@ -82,10 +84,17 @@ parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram
 xformers_available = False
 config_filename = cmd_opts.ui_settings_file
 
-hypernetworks = hypernetwork.list_hypernetworks(os.path.join(models_path, 'hypernetworks'))
+hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir)
 loaded_hypernetwork = None
 
 
+def reload_hypernetworks():
+    global hypernetworks
+
+    hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir)
+    hypernetwork.load_hypernetwork(opts.sd_hypernetwork)
+
+
 class State:
     skipped = False
     interrupted = False
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 5965c5a0..d6977950 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -156,7 +156,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'):
     return fn
 
 
-def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, num_repeats, create_image_every, save_embedding_every, template_file):
+def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, num_repeats, create_image_every, save_embedding_every, template_file, preview_image_prompt):
     assert embedding_name, 'embedding not selected'
 
     shared.state.textinfo = "Initializing textual inversion training..."
@@ -238,12 +238,14 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
         if embedding.step > 0 and images_dir is not None and embedding.step % create_image_every == 0:
             last_saved_image = os.path.join(images_dir, f'{embedding_name}-{embedding.step}.png')
 
+            preview_text = text if preview_image_prompt == "" else preview_image_prompt
+
             p = processing.StableDiffusionProcessingTxt2Img(
                 sd_model=shared.sd_model,
-                prompt=text,
+                prompt=preview_text,
                 steps=20,
-				height=training_height,
-				width=training_width,
+                height=training_height,
+                width=training_width,
                 do_not_save_grid=True,
                 do_not_save_samples=True,
             )
@@ -254,7 +256,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
             shared.state.current_image = image
             image.save(last_saved_image)
 
-            last_saved_image += f", prompt: {text}"
+            last_saved_image += f", prompt: {preview_text}"
 
         shared.state.job_no = embedding.step
 
diff --git a/modules/ui.py b/modules/ui.py
index 10b1ee3a..df653059 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1023,7 +1023,7 @@ def create_ui(wrap_gradio_gpu_call):
                             gr.HTML(value="")
 
                         with gr.Column():
-                            create_embedding = gr.Button(value="Create", variant='primary')
+                            create_embedding = gr.Button(value="Create embedding", variant='primary')
 
                 with gr.Group():
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Create a new hypernetwork</p>")
@@ -1035,7 +1035,7 @@ def create_ui(wrap_gradio_gpu_call):
                             gr.HTML(value="")
 
                         with gr.Column():
-                            create_hypernetwork = gr.Button(value="Create", variant='primary')
+                            create_hypernetwork = gr.Button(value="Create hypernetwork", variant='primary')
 
                 with gr.Group():
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Preprocess images</p>")
@@ -1147,6 +1147,7 @@ def create_ui(wrap_gradio_gpu_call):
                 create_image_every,
                 save_embedding_every,
                 template_file,
+                preview_image_prompt,
             ],
             outputs=[
                 ti_output,
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 42e1489c..0af5993c 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -10,7 +10,8 @@ import numpy as np
 import modules.scripts as scripts
 import gradio as gr
 
-from modules import images, hypernetwork
+from modules import images
+from modules.hypernetwork import hypernetwork
 from modules.processing import process_images, Processed, get_correct_sampler
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
diff --git a/webui.py b/webui.py
index 7c200551..ba2156c8 100644
--- a/webui.py
+++ b/webui.py
@@ -29,6 +29,7 @@ from modules import devices
 from modules import modelloader
 from modules.paths import script_path
 from modules.shared import cmd_opts
+import modules.hypernetwork.hypernetwork
 
 modelloader.cleanup_models()
 modules.sd_models.setup_model()
@@ -77,22 +78,12 @@ def wrap_gradio_gpu_call(func, extra_outputs=None):
     return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs)
 
 
-def set_hypernetwork():
-    shared.hypernetwork = shared.hypernetworks.get(shared.opts.sd_hypernetwork, None)
-
-
-shared.reload_hypernetworks()
-shared.opts.onchange("sd_hypernetwork", set_hypernetwork)
-set_hypernetwork()
-
-
 modules.scripts.load_scripts(os.path.join(script_path, "scripts"))
 
 shared.sd_model = modules.sd_models.load_model()
 shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model)))
 
-loaded_hypernetwork = modules.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)
-shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)))
+shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetwork.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)))
 
 
 def webui():
@@ -117,7 +108,7 @@ def webui():
             prevent_thread_lock=True
         )
         
-        app.add_middleware(GZipMiddleware,minimum_size=1000)
+        app.add_middleware(GZipMiddleware, minimum_size=1000)
 
         while 1:
             time.sleep(0.5)
-- 
cgit v1.2.3


From 7b1db45e1fda8603d4617affd976066be5e5b821 Mon Sep 17 00:00:00 2001
From: yfszzx <yfszzx@gmail.com>
Date: Tue, 11 Oct 2022 20:17:27 +0800
Subject: images history improvement

---
 javascript/images_history.js   | 170 ++++++++++++++++++++----------
 javascript/jquery-3.6.0.min.js |   2 -
 modules/images_history.py      | 229 ++++++++++++++++++++++-------------------
 style.css                      |   3 +
 4 files changed, 238 insertions(+), 166 deletions(-)
 delete mode 100644 javascript/jquery-3.6.0.min.js

diff --git a/javascript/images_history.js b/javascript/images_history.js
index 93d2b89a..9a3e00a0 100644
--- a/javascript/images_history.js
+++ b/javascript/images_history.js
@@ -1,66 +1,124 @@
-function init_images_history(){ 
-	if (gradioApp().getElementById('txt2img_images_history_first_page') == null) {
-		setTimeout(init_images_history, 1000)
-	} else {
-		tab_list = ["txt2img", "img2img"]
-		for (i in tab_list){
-			tab = tab_list[i]
-			gradioApp().getElementById(tab + "_images_history_first_page").click()
-			$(gradioApp().getElementById(tab + '_images_history')).addClass("images_history_gallery")
-			item = $(gradioApp().getElementById(tab + '_images_history_set_index'))
-			item.addClass("images_history_set_index")
-			item.hide()
-		}		
-	}
-	
+images_history_tab_list = ["txt2img", "img2img", "extras"]
+function images_history_init(){ 
+    if (gradioApp().getElementById('txt2img_images_history_first_page') == null) {
+        setTimeout(images_history_init, 500)
+    } else {        
+        for (i in images_history_tab_list ){
+            tab = images_history_tab_list[i]
+            gradioApp().getElementById(tab + '_images_history').classList.add("images_history_gallery")
+            gradioApp().getElementById(tab + '_images_history_set_index').classList.add("images_history_set_index")      
+            
+        }
+        gradioApp().getElementById("txt2img_images_history_first_page").click()     
+    }    
+}
+setTimeout(images_history_init, 500)
+var images_history_button_actions = function(){
+    if (!this.classList.contains("transform")){        
+        gallery = this.parentElement
+        while(!gallery.classList.contains("images_history_gallery")){gallery = gallery.parentElement}        
+        buttons = gallery.querySelectorAll(".gallery-item")
+        i = 0
+        hidden_list = []
+        buttons.forEach(function(e){
+            if (e.style.display == "none"){
+                hidden_list.push(i)
+            }
+            i += 1
+        })
+        if (hidden_list.length > 0){
+            setTimeout(images_history_hide_buttons, 10, hidden_list, gallery)
+        }
+        
+    }    
+    images_history_set_image_info(this) 
+
 }
-setTimeout(init_images_history, 1000)
 onUiUpdate(function(){
-    fullImg_preview = gradioApp().querySelectorAll('#txt2img_images_history img.w-full')
-        if(fullImg_preview.length > 0){
-	    	fullImg_preview.forEach(set_history_index_from_img);
-    }
-    fullImg_preview = gradioApp().querySelectorAll('#img2img_images_history img.w-full')
-        if(fullImg_preview.length > 0){
-	    	fullImg_preview.forEach(set_history_index_from_img);
+    for (i in images_history_tab_list ){
+        tab = images_history_tab_list[i]
+        buttons = gradioApp().querySelectorAll('#' + tab + '_images_history .gallery-item')
+        buttons.forEach(function(bnt){    
+            bnt.addEventListener('click', images_history_button_actions, true)
+         });
     }
 })
+function images_history_hide_buttons(hidden_list, gallery){
+    buttons = gallery.querySelectorAll(".gallery-item")
+    num = 0
+    buttons.forEach(function(e){
+        if (e.style.display == "none"){
+            num += 1
+        }
+    })
+    if (num == hidden_list.length){
+        setTimeout(images_history_hide_buttons, 10, hidden_list, gallery)
+    } 
+    for( i in hidden_list){
+        buttons[hidden_list[i]].style.display = "none"
+    }    
+}
 
-function set_history_gallery_index(item){
-	buttons = item.find(".gallery-item")
-	// alert(item.attr("id") + " " + buttons.length)
-	index = -1
-	i = 0
-	buttons.each(function(){
-		if($(this).hasClass("!ring-2")){ index = i }
-		i += 1
-	})
-	if (index == -1){
-		setTimeout(set_history_gallery_index, 10, item)     
-	} else {
-		item = item.find(".images_history_set_index").first()
-    	item.attr("img_index", index)
-    	item.click()
-	}
+function images_history_set_image_info(button){
+    item = button.parentElement
+    while(item.tagName != "DIV"){item = item.parentElement}    
+    buttons = item.querySelectorAll(".gallery-item")
+    index = -1
+    i = 0
+    buttons.forEach(function(e){
+        if(e==button){index = i}
+        if(e.style.display != "none"){
+            i += 1
+        }        
+    })
+    gallery = button.parentElement
+    while(!gallery.classList.contains("images_history_gallery")){gallery = gallery.parentElement}    
+    set_btn = gallery.querySelector(".images_history_set_index")
+    set_btn.setAttribute("img_index", index)
+    set_btn.click()
 }
-function set_history_index_from_img(e){
-    if(e && e.parentElement.tagName == 'BUTTON'){
-    	bnt = $(e).parent()
-    	if (bnt.hasClass("transform")){
-    		bnt.off("click").on("click",function(){
-    		set_history_gallery_index($(this).parents(".images_history_gallery").first())  
-     		})
-    	} else {
-    		bnt.off("mousedown").on("mousedown", function(){
-    		set_history_gallery_index($(this).parents(".images_history_gallery").first())  
-    		})
 
-		}  		
-    }
+function images_history_get_current_img(tabname, image_path, files){
+    s =  gradioApp().getElementById(tabname + '_images_history_set_index').getAttribute("img_index")
+    return [s, image_path, files]
 }
-function images_history_get_current_img(is_image2image, image_path, files){
-	head = is_image2image?"img2img":"txt2img"
-	s =  $(gradioApp().getElementById(head + '_images_history_set_index')).attr("img_index")
-	return [s, image_path, files]
+
+function images_history_delete(tabname, img_path, img_file_name, page_index, filenames, image_index){
+    image_index = parseInt(image_index)
+    tab = gradioApp().getElementById(tabname + '_images_history')
+    set_btn = tab.querySelector(".images_history_set_index")
+    buttons = []
+    tab.querySelectorAll(".gallery-item").forEach(function(e){
+        if (e.style.display != 'none'){
+            buttons.push(e)
+        }
+    })
+
+    
+    img_num = buttons.length / 2
+    if (img_num == 1){
+            setTimeout(function(tabname){
+                gradioApp().getElementById(tabname + '_images_history_renew_page').click()
+            }, 30, tabname) 
+    } else {
+        buttons[image_index].style.display = 'none'
+        buttons[image_index + img_num].style.display = 'none'
+        if (image_index  >= img_num - 1){
+            console.log(buttons.length, img_num)
+            btn = buttons[img_num - 2]
+        } else {
+            btn = buttons[image_index + 1]           
+        }    
+        setTimeout(function(btn){btn.click()}, 30, btn)
+    }  
+    
+    return [tabname, img_path, img_file_name, page_index, filenames, image_index]
 }
 
+function images_history_turnpage(img_path, page_index, image_index, tabname){
+    buttons = gradioApp().getElementById(tabname + '_images_history').querySelectorAll(".gallery-item")
+    buttons.forEach(function(elem) {
+         elem.style.display = 'block'
+    })
+    return [img_path, page_index, image_index, tabname]
+}
diff --git a/javascript/jquery-3.6.0.min.js b/javascript/jquery-3.6.0.min.js
deleted file mode 100644
index c4c6022f..00000000
--- a/javascript/jquery-3.6.0.min.js
+++ /dev/null
@@ -1,2 +0,0 @@
-/*! jQuery v3.6.0 | (c) OpenJS Foundation and other contributors | jquery.org/license */
-!function(e,t){"use strict";"object"==typeof module&&"object"==typeof module.exports?module.exports=e.document?t(e,!0):function(e){if(!e.document)throw new Error("jQuery requires a window with a document");return t(e)}:t(e)}("undefined"!=typeof window?window:this,function(C,e){"use strict";var t=[],r=Object.getPrototypeOf,s=t.slice,g=t.flat?function(e){return t.flat.call(e)}:function(e){return t.concat.apply([],e)},u=t.push,i=t.indexOf,n={},o=n.toString,v=n.hasOwnProperty,a=v.toString,l=a.call(Object),y={},m=function(e){return"function"==typeof e&&"number"!=typeof e.nodeType&&"function"!=typeof e.item},x=function(e){return null!=e&&e===e.window},E=C.document,c={type:!0,src:!0,nonce:!0,noModule:!0};function b(e,t,n){var r,i,o=(n=n||E).createElement("script");if(o.text=e,t)for(r in c)(i=t[r]||t.getAttribute&&t.getAttribute(r))&&o.setAttribute(r,i);n.head.appendChild(o).parentNode.removeChild(o)}function w(e){return null==e?e+"":"object"==typeof e||"function"==typeof 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diff --git a/modules/images_history.py b/modules/images_history.py
index 0e0a48f3..01d11a01 100644
--- a/modules/images_history.py
+++ b/modules/images_history.py
@@ -1,117 +1,130 @@
 import os
 def get_recent_images(dir_name, page_index, step, image_index):
-	print(image_index)
-	page_index = int(page_index)
-	f_list = os.listdir(dir_name)
-	file_list = []
-	for file in f_list:
-		if file[-4:] == ".txt":
-			continue
-		file_list.append(file)	
-	file_list = sorted(file_list, key=lambda file: -os.path.getctime(os.path.join(dir_name, file)))
-	num = 48
-	max_page_index = len(file_list) // num + 1	
-	page_index = max_page_index if page_index == -1 else page_index + step
-	page_index = 1 if page_index < 1 else page_index	
-	page_index = max_page_index if page_index > max_page_index else page_index
-	idx_frm = (page_index - 1) * num
-	file_list = file_list[idx_frm:idx_frm + num]
-	print(f"Loading history page {page_index}")	
-	image_index = int(image_index)
-	if image_index < 0 or image_index > len(file_list)  - 1:
-		current_file = None 
-		hide_image = None
-	else:
-		current_file =  file_list[int(image_index)]
-		hide_image = os.path.join(dir_name, current_file)
-	return [os.path.join(dir_name, file) for file in file_list], page_index, file_list, current_file, hide_image
-def first_page_click(dir_name, page_index, image_index):
-	return get_recent_images(dir_name, 1, 0, image_index)
-def end_page_click(dir_name, page_index, image_index):
-	return get_recent_images(dir_name, -1, 0, image_index)
-def prev_page_click(dir_name, page_index, image_index):
-	return get_recent_images(dir_name, page_index, -1, image_index)
-def next_page_click(dir_name, page_index, image_index):	
-	return get_recent_images(dir_name, page_index, 1, image_index)
-def page_index_change(dir_name, page_index, image_index):	
-	return get_recent_images(dir_name, page_index, 0, image_index)
+    #print(image_index)
+    page_index = int(page_index)
+    f_list = os.listdir(dir_name)
+    file_list = []
+    for file in f_list:
+        if file[-4:] == ".txt":
+            continue
+        file_list.append(file)    
+    file_list = sorted(file_list, key=lambda file: -os.path.getctime(os.path.join(dir_name, file)))
+    num = 48
+    max_page_index = len(file_list) // num + 1    
+    page_index = max_page_index if page_index == -1 else page_index + step
+    page_index = 1 if page_index < 1 else page_index    
+    page_index = max_page_index if page_index > max_page_index else page_index
+    idx_frm = (page_index - 1) * num
+    file_list = file_list[idx_frm:idx_frm + num]
+    #print(f"Loading history page {page_index}")    
+    image_index = int(image_index)
+    if image_index < 0 or image_index > len(file_list)  - 1:
+        current_file = None 
+        hide_image = None
+    else:
+        current_file =  file_list[int(image_index)]
+        hide_image = os.path.join(dir_name, current_file)
+    return [os.path.join(dir_name, file) for file in file_list], page_index, file_list, current_file, hide_image
+def first_page_click(dir_name, page_index, image_index, tabname):
+    return get_recent_images(dir_name, 1, 0, image_index)
+def end_page_click(dir_name, page_index, image_index, tabname):
+    return get_recent_images(dir_name, -1, 0, image_index)
+def prev_page_click(dir_name, page_index, image_index, tabname):
+    return get_recent_images(dir_name, page_index, -1, image_index)
+def next_page_click(dir_name, page_index, image_index, tabname):    
+    return get_recent_images(dir_name, page_index, 1, image_index)
+def page_index_change(dir_name, page_index, image_index, tabname):    
+    return get_recent_images(dir_name, page_index, 0, image_index)
 
 def show_image_info(num, image_path, filenames):
-	file = filenames[int(num)]
-	return file, num, os.path.join(image_path, file)
-def delete_image(is_img2img, dir_name, name, page_index, filenames, image_index):
-	print("filename", name)
-	path = os.path.join(dir_name, name)		
-	if os.path.exists(path):
-		print(f"Delete file {path}")
-		os.remove(path)	
-	images, page_index, file_list, current_file, hide_image = get_recent_images(dir_name, page_index, 0, image_index)
-	return images, page_index, file_list, current_file, hide_image
+    #print("set img",num)
+    file = filenames[int(num)]
+    return file, num, os.path.join(image_path, file)
+def delete_image(tabname, dir_name, name, page_index, filenames, image_index):
+    #print("filename", name)
+    path = os.path.join(dir_name, name)           
+    if os.path.exists(path):
+        print(f"Delete file {path}")
+        os.remove(path)    
+        new_file_list = []
+        for f in filenames:
+            if f == name:
+                continue
+            new_file_list.append(f)
+    else:
+        print(f"Not exists file {path}")
+        new_file_list = filenames
+    return page_index, new_file_list
 
+def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict):
+        if tabname == "txt2img":
+            dir_name = opts.outdir_txt2img_samples
+        elif tabname == "img2img":
+            dir_name = opts.outdir_img2img_samples
+        elif tabname == "extras":
+            dir_name = opts.outdir_extras_samples
+        with gr.Row():    
+                renew_page = gr.Button('Renew', elem_id=tabname + "_images_history_renew_page") 
+                first_page = gr.Button('First', elem_id=tabname + "_images_history_first_page")
+                prev_page = gr.Button('Prev') 
+                page_index = gr.Number(value=1, label="Page Index")
+                next_page = gr.Button('Next', elem_id=tabname + "_images_history_next_page") 
+                end_page = gr.Button('End')    
+        with gr.Row(elem_id=tabname + "_images_history"):            
+            with gr.Row():     
+                with gr.Column():
+                    history_gallery = gr.Gallery(show_label=False).style(grid=6)
+                with gr.Column():     
+                    with gr.Row():          
+                        delete = gr.Button('Delete')
+                        pnginfo_send_to_txt2img = gr.Button('Send to txt2img')
+                        pnginfo_send_to_img2img = gr.Button('Send to img2img')
+                    with gr.Row():
+                        with gr.Column():
+                            img_file_info = gr.Textbox(label="Generate Info")
+                            img_file_name = gr.Textbox(label="File Name")    
+                    with gr.Row():    
+                            # hiden items
+                            img_path = gr.Textbox(dir_name, visible=False)                
+                            tabname_box = gr.Textbox(tabname, visible=False)    
+                            image_index = gr.Textbox(value=-1, visible=False)                        
+                            set_index = gr.Button('set_index',  elem_id=tabname + "_images_history_set_index", visible=False)
+                            filenames = gr.State()
+                            hide_image = gr.Image(visible=False, type="pil")
+                            info1 = gr.Textbox(visible=False)
+                            info2 = gr.Textbox(visible=False)
 
-def show_images_history(gr, opts, is_img2img, run_pnginfo, switch_dict):
-		def id_name(is_img2img, name):	
-			return ("img2img" if is_img2img else "txt2img") + "_" + name
-		if is_img2img:
-			dir_name = opts.outdir_img2img_samples
-		else:
-			dir_name = opts.outdir_txt2img_samples
-		with gr.Row():	 
-				first_page = gr.Button('First', elem_id=id_name(is_img2img,"images_history_first_page"))
-				prev_page = gr.Button('Prev') 
-				page_index = gr.Number(value=1, label="Page Index")
-				next_page = gr.Button('Next') 
-				end_page = gr.Button('End')	
-		with gr.Row(elem_id=id_name(is_img2img,"images_history")):			
-			with gr.Row():	 
-				with gr.Column():
-					history_gallery = gr.Gallery(show_label=False).style(grid=6)
-				with gr.Column():	 
-					with gr.Row():	      
-						delete = gr.Button('Delete')
-						pnginfo_send_to_txt2img = gr.Button('Send to txt2img')
-						pnginfo_send_to_img2img = gr.Button('Send to img2img')
-					with gr.Row():
-						with gr.Column():
-							img_file_info = gr.Textbox(dir_name, label="Generate Info")
-							img_file_name = gr.Textbox(label="File Name")	
-					with gr.Row():	
-							# hiden items
-							img_path = gr.Textbox(dir_name, visible=False)				
-							is_img2img_flag = gr.Checkbox(is_img2img, visible=False)	
-							image_index = gr.Textbox(value=-1, visible=False)						
-							set_index = gr.Button('set_index',  elem_id=id_name(is_img2img,"images_history_set_index"))
-							filenames = gr.State()
-							hide_image = gr.Image(visible=False, type="pil")
-							info1 = gr.Textbox(visible=False)
-							info2 = gr.Textbox(visible=False)
+                
+        # turn pages
+        gallery_inputs = [img_path, page_index, image_index, tabname_box]
+        gallery_outputs = [history_gallery, page_index, filenames, img_file_name, hide_image]
 
-				
-		# turn pages
-		gallery_inputs = [img_path, page_index, image_index]
-		gallery_outputs = [history_gallery, page_index, filenames, img_file_name, hide_image]
-		first_page.click(first_page_click, inputs=gallery_inputs, outputs=gallery_outputs)
-		next_page.click(next_page_click, inputs=gallery_inputs, outputs=gallery_outputs)
-		prev_page.click(prev_page_click, inputs=gallery_inputs, outputs=gallery_outputs)		
-		end_page.click(end_page_click, inputs=gallery_inputs, outputs=gallery_outputs)
-		page_index.submit(page_index_change, inputs=gallery_inputs, outputs=gallery_outputs)
-		#page_index.change(page_index_change, inputs=[is_img2img_flag, img_path,  page_index], outputs=[history_gallery, page_index])
+        first_page.click(first_page_click, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)
+        next_page.click(next_page_click, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)
+        prev_page.click(prev_page_click, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)        
+        end_page.click(end_page_click, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)
+        page_index.submit(page_index_change, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)
+        renew_page.click(page_index_change, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)
+        #page_index.change(page_index_change, inputs=[tabname_box, img_path,  page_index], outputs=[history_gallery, page_index])
 
-		#other funcitons
-		set_index.click(show_image_info, _js="images_history_get_current_img", inputs=[is_img2img_flag,  img_path, filenames], outputs=[img_file_name, image_index, hide_image])
-		delete.click(delete_image, inputs=[is_img2img_flag, img_path, img_file_name, page_index, filenames, image_index], outputs=gallery_outputs) 
-		hide_image.change(fn=run_pnginfo, inputs=[hide_image], outputs=[info1, img_file_info, info2])
-		switch_dict["fn"](pnginfo_send_to_txt2img, switch_dict["t2i"], img_file_info, 'switch_to_txt2img')
-		switch_dict["fn"](pnginfo_send_to_img2img, switch_dict["i2i"], img_file_info, 'switch_to_img2img_img2img')
-	
-		
+        #other funcitons
+        set_index.click(show_image_info, _js="images_history_get_current_img", inputs=[tabname_box,  img_path, filenames], outputs=[img_file_name, image_index, hide_image])
+        delete.click(delete_image,_js="images_history_delete", inputs=[tabname_box, img_path, img_file_name, page_index, filenames, image_index], outputs=[page_index, filenames]) 
+        hide_image.change(fn=run_pnginfo, inputs=[hide_image], outputs=[info1, img_file_info, info2])
+        switch_dict["fn"](pnginfo_send_to_txt2img, switch_dict["t2i"], img_file_info, 'switch_to_txt2img')
+        switch_dict["fn"](pnginfo_send_to_img2img, switch_dict["i2i"], img_file_info, 'switch_to_img2img_img2img')
+    
+        
 def create_history_tabs(gr, opts, run_pnginfo, switch_dict):
-	with gr.Blocks(analytics_enabled=False) as images_history:
-		with gr.Tabs() as tabs:			
-			with gr.Tab("txt2img history", id="images_history_txt2img"):
-				with gr.Blocks(analytics_enabled=False) as images_history_txt2img:   
-					show_images_history(gr, opts, False, run_pnginfo, switch_dict) 
-			with gr.Tab("img2img history", id="images_history_img2img"):
-				with gr.Blocks(analytics_enabled=False) as images_history_img2img:
-					show_images_history(gr, opts, True, run_pnginfo, switch_dict)
-	return images_history
+    with gr.Blocks(analytics_enabled=False) as images_history:
+        with gr.Tabs() as tabs:            
+            with gr.Tab("txt2img history"):
+                with gr.Blocks(analytics_enabled=False) as images_history_txt2img:   
+                    show_images_history(gr, opts, "txt2img", run_pnginfo, switch_dict) 
+            with gr.Tab("img2img history"):
+                with gr.Blocks(analytics_enabled=False) as images_history_img2img:
+                    show_images_history(gr, opts, "img2img", run_pnginfo, switch_dict)
+            with gr.Tab("extras history"):
+                with gr.Blocks(analytics_enabled=False) as images_history_img2img:
+                    show_images_history(gr, opts, "extras", run_pnginfo, switch_dict)
+    return images_history
diff --git a/style.css b/style.css
index c0c3f2bb..ca1cdba1 100644
--- a/style.css
+++ b/style.css
@@ -463,3 +463,6 @@ input[type="range"]{
     max-width: 32em;
     padding: 0;
 }
+.images-history-hidden{
+    display: none;
+}
\ No newline at end of file
-- 
cgit v1.2.3


From 45ada1c91025e221df04f911de6377e419f19e3f Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Tue, 11 Oct 2022 13:10:11 +0100
Subject: Correct list style, apply gen forever to both tabs, roll3 on both
 tabs

---
 javascript/contextMenus.js | 24 ++++++++++++++++--------
 1 file changed, 16 insertions(+), 8 deletions(-)

diff --git a/javascript/contextMenus.js b/javascript/contextMenus.js
index 7852793c..4e772065 100644
--- a/javascript/contextMenus.js
+++ b/javascript/contextMenus.js
@@ -16,7 +16,7 @@ contextMenuInit = function(){
       oldMenu.remove()
     }
 
-    let tabButton = gradioApp().querySelector('button')
+    let tabButton = uiCurrentTab
     let baseStyle = window.getComputedStyle(tabButton)
 
     const contextMenu = document.createElement('nav')
@@ -130,9 +130,9 @@ addContextMenuEventListener = initResponse[2]
 
 
 //Start example Context Menu Items
-generateOnRepeatId = appendContextMenuOption('#txt2img_generate','Generate forever',function(){
-  let genbutton = gradioApp().querySelector('#txt2img_generate');
-  let interruptbutton = gradioApp().querySelector('#txt2img_interrupt');
+generateOnRepeat = function(genbuttonid,interruptbuttonid){
+  let genbutton = gradioApp().querySelector(genbuttonid);
+  let interruptbutton = gradioApp().querySelector(interruptbuttonid);
   if(!interruptbutton.offsetParent){
     genbutton.click();
   }
@@ -142,8 +142,15 @@ generateOnRepeatId = appendContextMenuOption('#txt2img_generate','Generate forev
       genbutton.click();
     }
   },
-  500)}
-)
+  500)
+}
+
+generateOnRepeatId = appendContextMenuOption('#txt2img_generate','Generate forever',function(){
+  generateOnRepeat('#txt2img_generate','#txt2img_interrupt');
+})
+generateOnRepeatId = appendContextMenuOption('#img2img_generate','Generate forever',function(){
+  generateOnRepeat('#img2img_generate','#img2img_interrupt');
+})
 
 cancelGenerateForever = function(){ 
   clearInterval(window.generateOnRepeatInterval) 
@@ -151,11 +158,12 @@ cancelGenerateForever = function(){
 
 appendContextMenuOption('#txt2img_interrupt','Cancel generate forever',cancelGenerateForever)
 appendContextMenuOption('#txt2img_generate', 'Cancel generate forever',cancelGenerateForever)
-
+appendContextMenuOption('#img2img_interrupt','Cancel generate forever',cancelGenerateForever)
+appendContextMenuOption('#img2img_generate', 'Cancel generate forever',cancelGenerateForever)
 
 appendContextMenuOption('#roll','Roll three',
   function(){ 
-    let rollbutton = gradioApp().querySelector('#roll');
+    let rollbutton = get_uiCurrentTabContent().querySelector('#roll');
     setTimeout(function(){rollbutton.click()},100)
     setTimeout(function(){rollbutton.click()},200)
     setTimeout(function(){rollbutton.click()},300)
-- 
cgit v1.2.3


From 9b8faefde05464fe6ba51668fe1d361e4fe22339 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Tue, 11 Oct 2022 13:19:16 +0100
Subject: context menus closure

---
 javascript/contextMenus.js | 81 +++++++++++++++++++++++-----------------------
 1 file changed, 41 insertions(+), 40 deletions(-)

diff --git a/javascript/contextMenus.js b/javascript/contextMenus.js
index 4e772065..7636c4b3 100644
--- a/javascript/contextMenus.js
+++ b/javascript/contextMenus.js
@@ -123,52 +123,53 @@ contextMenuInit = function(){
   return [appendContextMenuOption, removeContextMenuOption, addContextMenuEventListener]
 }
 
-initResponse = contextMenuInit()
-appendContextMenuOption     = initResponse[0]
-removeContextMenuOption     = initResponse[1]
-addContextMenuEventListener = initResponse[2]
-
-
-//Start example Context Menu Items
-generateOnRepeat = function(genbuttonid,interruptbuttonid){
-  let genbutton = gradioApp().querySelector(genbuttonid);
-  let interruptbutton = gradioApp().querySelector(interruptbuttonid);
-  if(!interruptbutton.offsetParent){
-    genbutton.click();
-  }
-  clearInterval(window.generateOnRepeatInterval)
-  window.generateOnRepeatInterval = setInterval(function(){
+initResponse = contextMenuInit();
+appendContextMenuOption     = initResponse[0];
+removeContextMenuOption     = initResponse[1];
+addContextMenuEventListener = initResponse[2];
+
+(function(){
+  //Start example Context Menu Items
+  let generateOnRepeat = function(genbuttonid,interruptbuttonid){
+    let genbutton = gradioApp().querySelector(genbuttonid);
+    let interruptbutton = gradioApp().querySelector(interruptbuttonid);
     if(!interruptbutton.offsetParent){
       genbutton.click();
     }
-  },
-  500)
-}
-
-generateOnRepeatId = appendContextMenuOption('#txt2img_generate','Generate forever',function(){
-  generateOnRepeat('#txt2img_generate','#txt2img_interrupt');
-})
-generateOnRepeatId = appendContextMenuOption('#img2img_generate','Generate forever',function(){
-  generateOnRepeat('#img2img_generate','#img2img_interrupt');
-})
+    clearInterval(window.generateOnRepeatInterval)
+    window.generateOnRepeatInterval = setInterval(function(){
+      if(!interruptbutton.offsetParent){
+        genbutton.click();
+      }
+    },
+    500)
+  }
 
-cancelGenerateForever = function(){ 
-  clearInterval(window.generateOnRepeatInterval) 
-}
+  appendContextMenuOption('#txt2img_generate','Generate forever',function(){
+    generateOnRepeat('#txt2img_generate','#txt2img_interrupt');
+  })
+  appendContextMenuOption('#img2img_generate','Generate forever',function(){
+    generateOnRepeat('#img2img_generate','#img2img_interrupt');
+  })
 
-appendContextMenuOption('#txt2img_interrupt','Cancel generate forever',cancelGenerateForever)
-appendContextMenuOption('#txt2img_generate', 'Cancel generate forever',cancelGenerateForever)
-appendContextMenuOption('#img2img_interrupt','Cancel generate forever',cancelGenerateForever)
-appendContextMenuOption('#img2img_generate', 'Cancel generate forever',cancelGenerateForever)
-
-appendContextMenuOption('#roll','Roll three',
-  function(){ 
-    let rollbutton = get_uiCurrentTabContent().querySelector('#roll');
-    setTimeout(function(){rollbutton.click()},100)
-    setTimeout(function(){rollbutton.click()},200)
-    setTimeout(function(){rollbutton.click()},300)
+  let cancelGenerateForever = function(){ 
+    clearInterval(window.generateOnRepeatInterval) 
   }
-)
+
+  appendContextMenuOption('#txt2img_interrupt','Cancel generate forever',cancelGenerateForever)
+  appendContextMenuOption('#txt2img_generate', 'Cancel generate forever',cancelGenerateForever)
+  appendContextMenuOption('#img2img_interrupt','Cancel generate forever',cancelGenerateForever)
+  appendContextMenuOption('#img2img_generate', 'Cancel generate forever',cancelGenerateForever)
+
+  appendContextMenuOption('#roll','Roll three',
+    function(){ 
+      let rollbutton = get_uiCurrentTabContent().querySelector('#roll');
+      setTimeout(function(){rollbutton.click()},100)
+      setTimeout(function(){rollbutton.click()},200)
+      setTimeout(function(){rollbutton.click()},300)
+    }
+  )
+})();
 //End example Context Menu Items
 
 onUiUpdate(function(){
-- 
cgit v1.2.3


From 92d7a138857b308c97a8d009848f642aeb93d6c8 Mon Sep 17 00:00:00 2001
From: Martin Cairns <Martin.Cairns+github@gmail.com>
Date: Tue, 11 Oct 2022 00:02:44 +0100
Subject: Handle different parameters for DPM fast & adaptive

---
 modules/sd_samplers.py | 25 ++++++++++++++++++-------
 1 file changed, 18 insertions(+), 7 deletions(-)

diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index d168b938..eee52e7d 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -57,7 +57,7 @@ def set_samplers():
     global samplers, samplers_for_img2img
 
     hidden = set(opts.hide_samplers)
-    hidden_img2img = set(opts.hide_samplers + ['PLMS', 'DPM fast', 'DPM adaptive'])
+    hidden_img2img = set(opts.hide_samplers + ['PLMS'])
 
     samplers = [x for x in all_samplers if x.name not in hidden]
     samplers_for_img2img = [x for x in all_samplers if x.name not in hidden_img2img]
@@ -365,16 +365,27 @@ class KDiffusionSampler:
         else:
             sigmas = self.model_wrap.get_sigmas(steps)
 
-        noise = noise * sigmas[steps - t_enc - 1]
-        xi = x + noise
-
-        extra_params_kwargs = self.initialize(p)
-
         sigma_sched = sigmas[steps - t_enc - 1:]
+        print('check values same', sigmas[steps - t_enc - 1] , sigma_sched[0], sigmas[steps - t_enc - 1] - sigma_sched[0])
+        xi = x + noise * sigma_sched[0]
+        
+        extra_params_kwargs = self.initialize(p)
+        if 'sigma_min' in inspect.signature(self.func).parameters:
+            ## last sigma is zero which is allowed by DPM Fast & Adaptive so taking value before last
+            extra_params_kwargs['sigma_min'] = sigma_sched[-2]
+        if 'sigma_max' in inspect.signature(self.func).parameters:
+            extra_params_kwargs['sigma_max'] = sigma_sched[0]
+        if 'n' in inspect.signature(self.func).parameters:
+            extra_params_kwargs['n'] = len(sigma_sched) - 1
+        if 'sigma_sched' in inspect.signature(self.func).parameters:
+            extra_params_kwargs['sigma_sched'] = sigma_sched
+        if 'sigmas' in inspect.signature(self.func).parameters:
+            extra_params_kwargs['sigmas'] = sigma_sched
 
         self.model_wrap_cfg.init_latent = x
 
-        return self.func(self.model_wrap_cfg, xi, sigma_sched, extra_args={'cond': conditioning, 'uncond': unconditional_conditioning, 'cond_scale': p.cfg_scale}, disable=False, callback=self.callback_state, **extra_params_kwargs)
+        return self.func(self.model_wrap_cfg, xi, extra_args={'cond': conditioning, 'uncond': unconditional_conditioning, 'cond_scale': p.cfg_scale}, disable=False, callback=self.callback_state, **extra_params_kwargs)
+
 
     def sample(self, p, x, conditioning, unconditional_conditioning, steps=None):
         steps = steps or p.steps
-- 
cgit v1.2.3


From 1eae3076078f00ecc5d0fac3c77fffb85cd2eb77 Mon Sep 17 00:00:00 2001
From: Martin Cairns <Martin.Cairns+github@gmail.com>
Date: Tue, 11 Oct 2022 00:04:06 +0100
Subject: Remove debug code for checking that first sigma value is same after
 code cleanup

---
 modules/sd_samplers.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index eee52e7d..32272916 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -366,7 +366,6 @@ class KDiffusionSampler:
             sigmas = self.model_wrap.get_sigmas(steps)
 
         sigma_sched = sigmas[steps - t_enc - 1:]
-        print('check values same', sigmas[steps - t_enc - 1] , sigma_sched[0], sigmas[steps - t_enc - 1] - sigma_sched[0])
         xi = x + noise * sigma_sched[0]
         
         extra_params_kwargs = self.initialize(p)
-- 
cgit v1.2.3


From eacc03b16730bcc5be95cda2d7c966ff1b4a8263 Mon Sep 17 00:00:00 2001
From: Martin Cairns <Martin.Cairns+github@gmail.com>
Date: Tue, 11 Oct 2022 00:36:00 +0100
Subject: Fix typo in comments

---
 modules/sd_samplers.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index 32272916..20309e06 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -370,7 +370,7 @@ class KDiffusionSampler:
         
         extra_params_kwargs = self.initialize(p)
         if 'sigma_min' in inspect.signature(self.func).parameters:
-            ## last sigma is zero which is allowed by DPM Fast & Adaptive so taking value before last
+            ## last sigma is zero which isn't allowed by DPM Fast & Adaptive so taking value before last
             extra_params_kwargs['sigma_min'] = sigma_sched[-2]
         if 'sigma_max' in inspect.signature(self.func).parameters:
             extra_params_kwargs['sigma_max'] = sigma_sched[0]
-- 
cgit v1.2.3


From 87d63bbab5c973ac5cec777ef7304d28f1ab3f24 Mon Sep 17 00:00:00 2001
From: yfszzx <yfszzx@gmail.com>
Date: Tue, 11 Oct 2022 20:37:03 +0800
Subject: images history improvement

---
 javascript/images_history.js |  6 ++----
 modules/images_history.py    | 30 +++++++++++++++---------------
 2 files changed, 17 insertions(+), 19 deletions(-)

diff --git a/javascript/images_history.js b/javascript/images_history.js
index 9a3e00a0..d62eb181 100644
--- a/javascript/images_history.js
+++ b/javascript/images_history.js
@@ -93,7 +93,6 @@ function images_history_delete(tabname, img_path, img_file_name, page_index, fil
             buttons.push(e)
         }
     })
-
     
     img_num = buttons.length / 2
     if (img_num == 1){
@@ -110,15 +109,14 @@ function images_history_delete(tabname, img_path, img_file_name, page_index, fil
             btn = buttons[image_index + 1]           
         }    
         setTimeout(function(btn){btn.click()}, 30, btn)
-    }  
-    
+    }      
     return [tabname, img_path, img_file_name, page_index, filenames, image_index]
 }
 
 function images_history_turnpage(img_path, page_index, image_index, tabname){
     buttons = gradioApp().getElementById(tabname + '_images_history').querySelectorAll(".gallery-item")
     buttons.forEach(function(elem) {
-         elem.style.display = 'block'
+        elem.style.display = 'block'
     })
     return [img_path, page_index, image_index, tabname]
 }
diff --git a/modules/images_history.py b/modules/images_history.py
index 01d11a01..23f55b30 100644
--- a/modules/images_history.py
+++ b/modules/images_history.py
@@ -64,12 +64,12 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict):
         elif tabname == "extras":
             dir_name = opts.outdir_extras_samples
         with gr.Row():    
-                renew_page = gr.Button('Renew', elem_id=tabname + "_images_history_renew_page") 
-                first_page = gr.Button('First', elem_id=tabname + "_images_history_first_page")
-                prev_page = gr.Button('Prev') 
-                page_index = gr.Number(value=1, label="Page Index")
-                next_page = gr.Button('Next', elem_id=tabname + "_images_history_next_page") 
-                end_page = gr.Button('End')    
+            renew_page = gr.Button('Renew', elem_id=tabname + "_images_history_renew_page") 
+            first_page = gr.Button('First', elem_id=tabname + "_images_history_first_page")
+            prev_page = gr.Button('Prev') 
+            page_index = gr.Number(value=1, label="Page Index")
+            next_page = gr.Button('Next', elem_id=tabname + "_images_history_next_page") 
+            end_page = gr.Button('End')    
         with gr.Row(elem_id=tabname + "_images_history"):            
             with gr.Row():     
                 with gr.Column():
@@ -84,15 +84,15 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict):
                             img_file_info = gr.Textbox(label="Generate Info")
                             img_file_name = gr.Textbox(label="File Name")    
                     with gr.Row():    
-                            # hiden items
-                            img_path = gr.Textbox(dir_name, visible=False)                
-                            tabname_box = gr.Textbox(tabname, visible=False)    
-                            image_index = gr.Textbox(value=-1, visible=False)                        
-                            set_index = gr.Button('set_index',  elem_id=tabname + "_images_history_set_index", visible=False)
-                            filenames = gr.State()
-                            hide_image = gr.Image(visible=False, type="pil")
-                            info1 = gr.Textbox(visible=False)
-                            info2 = gr.Textbox(visible=False)
+                        # hiden items
+                        img_path = gr.Textbox(dir_name, visible=False)                
+                        tabname_box = gr.Textbox(tabname, visible=False)    
+                        image_index = gr.Textbox(value=-1, visible=False)                        
+                        set_index = gr.Button('set_index',  elem_id=tabname + "_images_history_set_index", visible=False)
+                        filenames = gr.State()
+                        hide_image = gr.Image(visible=False, type="pil")
+                        info1 = gr.Textbox(visible=False)
+                        info2 = gr.Textbox(visible=False)
 
                 
         # turn pages
-- 
cgit v1.2.3


From b372f5538bee4feba87080af4f3acf1e437accc6 Mon Sep 17 00:00:00 2001
From: Ben <110583491+TheLastBen@users.noreply.github.com>
Date: Mon, 10 Oct 2022 19:34:07 +0100
Subject: Save some space

---
 style.css | 12 ++++++++++++
 1 file changed, 12 insertions(+)

diff --git a/style.css b/style.css
index 00a3d07f..38410ca4 100644
--- a/style.css
+++ b/style.css
@@ -2,6 +2,18 @@
     max-width: 100%;
 }
 
+#txt2img_token_counter {
+    height: 0px;
+}
+
+#img2img_token_counter {
+    height: 0px;
+}
+
+#negative_prompt {
+    width: 97.9%;
+}
+
 .output-html p {margin: 0 0.5em;}
 
 .row > *,
-- 
cgit v1.2.3


From 87b77cad5f3017c952a7dfec0e7904a9df5b72fd Mon Sep 17 00:00:00 2001
From: Ben <110583491+TheLastBen@users.noreply.github.com>
Date: Mon, 10 Oct 2022 19:37:16 +0100
Subject: Layout fix

---
 modules/ui.py | 28 ++++++++++++++--------------
 1 file changed, 14 insertions(+), 14 deletions(-)

diff --git a/modules/ui.py b/modules/ui.py
index df653059..de4cd7f2 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -550,15 +550,15 @@ def create_ui(wrap_gradio_gpu_call):
                         button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder'
                         open_txt2img_folder = gr.Button(folder_symbol, elem_id=button_id)
 
-                    with gr.Row():
-                        do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
+                with gr.Row():
+                    do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
                     
-                    with gr.Row():
-                        download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
+                with gr.Row():
+                    download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
 
-                with gr.Group():
-                    html_info = gr.HTML()
-                    generation_info = gr.Textbox(visible=False)
+                    with gr.Group():
+                        html_info = gr.HTML()
+                        generation_info = gr.Textbox(visible=False)
 
             connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
             connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
@@ -738,15 +738,15 @@ def create_ui(wrap_gradio_gpu_call):
                         button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder'
                         open_img2img_folder = gr.Button(folder_symbol, elem_id=button_id)
 
-                    with gr.Row():
-                        do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
+                with gr.Row():
+                    do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
                     
-                    with gr.Row():
-                        download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
+                with gr.Row():
+                    download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
 
-                with gr.Group():
-                    html_info = gr.HTML()
-                    generation_info = gr.Textbox(visible=False)
+                    with gr.Group():
+                        html_info = gr.HTML()
+                        generation_info = gr.Textbox(visible=False)
 
             connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
             connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
-- 
cgit v1.2.3


From 861297cefe2bb663f4e09dd4778a4cb93ebe8ff1 Mon Sep 17 00:00:00 2001
From: Ben <110583491+TheLastBen@users.noreply.github.com>
Date: Tue, 11 Oct 2022 08:08:45 +0100
Subject: add a space holder

---
 modules/ui.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/modules/ui.py b/modules/ui.py
index de4cd7f2..fc0f3d3c 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -429,7 +429,10 @@ def create_toprow(is_img2img):
 
             with gr.Row():
                 with gr.Column(scale=8):
-                    negative_prompt = gr.Textbox(label="Negative prompt", elem_id="negative_prompt", show_label=False, placeholder="Negative prompt", lines=2)
+                    with gr.Row():
+                        negative_prompt = gr.Textbox(label="Negative prompt", elem_id="negative_prompt", show_label=False, placeholder="Negative prompt", lines=2)
+                with gr.Column(scale=1, elem_id="roll_col"):
+                    sh = gr.Button(elem_id="sh", visible=True)                           
 
                 with gr.Column(scale=1, elem_id="style_neg_col"):
                     prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())), visible=len(shared.prompt_styles.styles) > 1)
-- 
cgit v1.2.3


From 031dc8cd7fa6bc74b44114715b28e0737342de37 Mon Sep 17 00:00:00 2001
From: Ben <110583491+TheLastBen@users.noreply.github.com>
Date: Tue, 11 Oct 2022 08:08:47 +0100
Subject: space holder

---
 style.css | 12 ++++++++++--
 1 file changed, 10 insertions(+), 2 deletions(-)

diff --git a/style.css b/style.css
index 38410ca4..d1c866fc 100644
--- a/style.css
+++ b/style.css
@@ -10,8 +10,16 @@
     height: 0px;
 }
 
-#negative_prompt {
-    width: 97.9%;
+#sh{
+    min-width: 2em;
+    min-height: 2em;
+    max-width: 2em;
+    max-height: 2em;
+    flex-grow: 0;
+    padding-left: 0.25em;
+    padding-right: 0.25em;
+    margin: 0.1em 0;
+    opacity: 0%;
 }
 
 .output-html p {margin: 0 0.5em;}
-- 
cgit v1.2.3


From 54c519943a24881ea61af5a73dedbab92f9431ce Mon Sep 17 00:00:00 2001
From: Ben <110583491+TheLastBen@users.noreply.github.com>
Date: Tue, 11 Oct 2022 10:16:53 +0100
Subject: Update style.css

---
 style.css | 1 +
 1 file changed, 1 insertion(+)

diff --git a/style.css b/style.css
index d1c866fc..ecb51bb0 100644
--- a/style.css
+++ b/style.css
@@ -20,6 +20,7 @@
     padding-right: 0.25em;
     margin: 0.1em 0;
     opacity: 0%;
+    cursor: default;	
 }
 
 .output-html p {margin: 0 0.5em;}
-- 
cgit v1.2.3


From 210fd72babb8314b280a7b5ef8603c62024a22db Mon Sep 17 00:00:00 2001
From: parsec501 <105080989+parsec501@users.noreply.github.com>
Date: Tue, 11 Oct 2022 14:37:01 +0200
Subject: Added 'suggestion' flair to suggestion template

---
 .github/ISSUE_TEMPLATE/feature_request.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/ISSUE_TEMPLATE/feature_request.md b/.github/ISSUE_TEMPLATE/feature_request.md
index bbcbbe7d..eda42fa7 100644
--- a/.github/ISSUE_TEMPLATE/feature_request.md
+++ b/.github/ISSUE_TEMPLATE/feature_request.md
@@ -2,7 +2,7 @@
 name: Feature request
 about: Suggest an idea for this project
 title: ''
-labels: ''
+labels: 'suggestion'
 assignees: ''
 
 ---
-- 
cgit v1.2.3


From 4e485b79238666ace2b270045f73a12e5ccc7af9 Mon Sep 17 00:00:00 2001
From: JamnedZ <zaguzinegor@gmail.com>
Date: Tue, 11 Oct 2022 16:38:03 +0700
Subject: Added installation of pyngrok if needed

---
 launch.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/launch.py b/launch.py
index e1000f55..16627a03 100644
--- a/launch.py
+++ b/launch.py
@@ -104,6 +104,7 @@ def prepare_enviroment():
     args, skip_torch_cuda_test = extract_arg(args, '--skip-torch-cuda-test')
     xformers = '--xformers' in args
     deepdanbooru = '--deepdanbooru' in args
+    ngrok = '--ngrok' in args
 
     try:
         commit = run(f"{git} rev-parse HEAD").strip()
@@ -134,6 +135,9 @@ def prepare_enviroment():
     if not is_installed("deepdanbooru") and deepdanbooru:
         run_pip("install git+https://github.com/KichangKim/DeepDanbooru.git@edf73df4cdaeea2cf00e9ac08bd8a9026b7a7b26#egg=deepdanbooru[tensorflow] tensorflow==2.10.0 tensorflow-io==0.27.0", "deepdanbooru")
 
+    if not is_installed("pyngrok") and ngrok:
+        run_pip("install pyngrok", "ngrok")
+
     os.makedirs(dir_repos, exist_ok=True)
 
     git_clone("https://github.com/CompVis/stable-diffusion.git", repo_dir('stable-diffusion'), "Stable Diffusion", stable_diffusion_commit_hash)
-- 
cgit v1.2.3


From 59925644480b6fd84f6bb84b4df7d4fbc6a0cce8 Mon Sep 17 00:00:00 2001
From: JamnedZ <zaguzinegor@gmail.com>
Date: Tue, 11 Oct 2022 16:40:27 +0700
Subject: Cleaned ngrok integration

---
 modules/ngrok.py  | 15 +++++++++++++++
 modules/shared.py |  1 +
 modules/ui.py     |  5 +++++
 3 files changed, 21 insertions(+)
 create mode 100644 modules/ngrok.py

diff --git a/modules/ngrok.py b/modules/ngrok.py
new file mode 100644
index 00000000..17e6976f
--- /dev/null
+++ b/modules/ngrok.py
@@ -0,0 +1,15 @@
+from pyngrok import ngrok, conf, exception
+
+
+def connect(token, port):
+    if token == None:
+        token = 'None'
+    conf.get_default().auth_token = token
+    try:
+        public_url = ngrok.connect(port).public_url
+    except exception.PyngrokNgrokError:
+        print(f'Invalid ngrok authtoken, ngrok connection aborted.\n'
+              f'Your token: {token}, get the right one on https://dashboard.ngrok.com/get-started/your-authtoken')
+    else:
+        print(f'ngrok connected to localhost:{port}! URL: {public_url}\n'
+               'You can use this link after the launch is complete.')
\ No newline at end of file
diff --git a/modules/shared.py b/modules/shared.py
index 8753015e..375e3afb 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -38,6 +38,7 @@ parser.add_argument("--always-batch-cond-uncond", action='store_true', help="dis
 parser.add_argument("--unload-gfpgan", action='store_true', help="does not do anything.")
 parser.add_argument("--precision", type=str, help="evaluate at this precision", choices=["full", "autocast"], default="autocast")
 parser.add_argument("--share", action='store_true', help="use share=True for gradio and make the UI accessible through their site (doesn't work for me but you might have better luck)")
+parser.add_argument("--ngrok", type=str, help="ngrok authtoken, alternative to gradio --share", default=None)
 parser.add_argument("--codeformer-models-path", type=str, help="Path to directory with codeformer model file(s).", default=os.path.join(models_path, 'Codeformer'))
 parser.add_argument("--gfpgan-models-path", type=str, help="Path to directory with GFPGAN model file(s).", default=os.path.join(models_path, 'GFPGAN'))
 parser.add_argument("--esrgan-models-path", type=str, help="Path to directory with ESRGAN model file(s).", default=os.path.join(models_path, 'ESRGAN'))
diff --git a/modules/ui.py b/modules/ui.py
index fc0f3d3c..f57f32db 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -51,6 +51,11 @@ if not cmd_opts.share and not cmd_opts.listen:
     gradio.utils.version_check = lambda: None
     gradio.utils.get_local_ip_address = lambda: '127.0.0.1'
 
+if cmd_opts.ngrok != None:
+    import modules.ngrok as ngrok
+    print('ngrok authtoken detected, trying to connect...')
+    ngrok.connect(cmd_opts.ngrok, cmd_opts.port if cmd_opts.port != None else 7860)
+
 
 def gr_show(visible=True):
     return {"visible": visible, "__type__": "update"}
-- 
cgit v1.2.3


From a004d1a855311b0d7ff2976a4e31b0247ad9d1f6 Mon Sep 17 00:00:00 2001
From: JamnedZ <zaguzinegor@gmail.com>
Date: Tue, 11 Oct 2022 16:48:27 +0700
Subject: Added new line at the end of ngrok.py

---
 modules/ngrok.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/ngrok.py b/modules/ngrok.py
index 17e6976f..7d03a6df 100644
--- a/modules/ngrok.py
+++ b/modules/ngrok.py
@@ -12,4 +12,4 @@ def connect(token, port):
               f'Your token: {token}, get the right one on https://dashboard.ngrok.com/get-started/your-authtoken')
     else:
         print(f'ngrok connected to localhost:{port}! URL: {public_url}\n'
-               'You can use this link after the launch is complete.')
\ No newline at end of file
+               'You can use this link after the launch is complete.')
-- 
cgit v1.2.3


From 873efeed49bb5197a42da18272115b326c5d68f3 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 15:51:22 +0300
Subject: rename hypernetwork dir to hypernetworks to prevent clash with an old
 filename that people who use zip instead of git clone will have

---
 modules/hypernetwork/hypernetwork.py  | 283 ----------------------------------
 modules/hypernetwork/ui.py            |  43 ------
 modules/hypernetworks/hypernetwork.py | 283 ++++++++++++++++++++++++++++++++++
 modules/hypernetworks/ui.py           |  43 ++++++
 modules/sd_hijack.py                  |   2 +-
 modules/sd_hijack_optimizations.py    |   2 +-
 modules/shared.py                     |   2 +-
 modules/ui.py                         |   2 +-
 scripts/xy_grid.py                    |   2 +-
 webui.py                              |   2 +-
 10 files changed, 332 insertions(+), 332 deletions(-)
 delete mode 100644 modules/hypernetwork/hypernetwork.py
 delete mode 100644 modules/hypernetwork/ui.py
 create mode 100644 modules/hypernetworks/hypernetwork.py
 create mode 100644 modules/hypernetworks/ui.py

diff --git a/modules/hypernetwork/hypernetwork.py b/modules/hypernetwork/hypernetwork.py
deleted file mode 100644
index aa701bda..00000000
--- a/modules/hypernetwork/hypernetwork.py
+++ /dev/null
@@ -1,283 +0,0 @@
-import datetime
-import glob
-import html
-import os
-import sys
-import traceback
-import tqdm
-
-import torch
-
-from ldm.util import default
-from modules import devices, shared, processing, sd_models
-import torch
-from torch import einsum
-from einops import rearrange, repeat
-import modules.textual_inversion.dataset
-
-
-class HypernetworkModule(torch.nn.Module):
-    def __init__(self, dim, state_dict=None):
-        super().__init__()
-
-        self.linear1 = torch.nn.Linear(dim, dim * 2)
-        self.linear2 = torch.nn.Linear(dim * 2, dim)
-
-        if state_dict is not None:
-            self.load_state_dict(state_dict, strict=True)
-        else:
-
-            self.linear1.weight.data.normal_(mean=0.0, std=0.01)
-            self.linear1.bias.data.zero_()
-            self.linear2.weight.data.normal_(mean=0.0, std=0.01)
-            self.linear2.bias.data.zero_()
-
-        self.to(devices.device)
-
-    def forward(self, x):
-        return x + (self.linear2(self.linear1(x)))
-
-
-class Hypernetwork:
-    filename = None
-    name = None
-
-    def __init__(self, name=None):
-        self.filename = None
-        self.name = name
-        self.layers = {}
-        self.step = 0
-        self.sd_checkpoint = None
-        self.sd_checkpoint_name = None
-
-        for size in [320, 640, 768, 1280]:
-            self.layers[size] = (HypernetworkModule(size), HypernetworkModule(size))
-
-    def weights(self):
-        res = []
-
-        for k, layers in self.layers.items():
-            for layer in layers:
-                layer.train()
-                res += [layer.linear1.weight, layer.linear1.bias, layer.linear2.weight, layer.linear2.bias]
-
-        return res
-
-    def save(self, filename):
-        state_dict = {}
-
-        for k, v in self.layers.items():
-            state_dict[k] = (v[0].state_dict(), v[1].state_dict())
-
-        state_dict['step'] = self.step
-        state_dict['name'] = self.name
-        state_dict['sd_checkpoint'] = self.sd_checkpoint
-        state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name
-
-        torch.save(state_dict, filename)
-
-    def load(self, filename):
-        self.filename = filename
-        if self.name is None:
-            self.name = os.path.splitext(os.path.basename(filename))[0]
-
-        state_dict = torch.load(filename, map_location='cpu')
-
-        for size, sd in state_dict.items():
-            if type(size) == int:
-                self.layers[size] = (HypernetworkModule(size, sd[0]), HypernetworkModule(size, sd[1]))
-
-        self.name = state_dict.get('name', self.name)
-        self.step = state_dict.get('step', 0)
-        self.sd_checkpoint = state_dict.get('sd_checkpoint', None)
-        self.sd_checkpoint_name = state_dict.get('sd_checkpoint_name', None)
-
-
-def list_hypernetworks(path):
-    res = {}
-    for filename in glob.iglob(os.path.join(path, '**/*.pt'), recursive=True):
-        name = os.path.splitext(os.path.basename(filename))[0]
-        res[name] = filename
-    return res
-
-
-def load_hypernetwork(filename):
-    path = shared.hypernetworks.get(filename, None)
-    if path is not None:
-        print(f"Loading hypernetwork {filename}")
-        try:
-            shared.loaded_hypernetwork = Hypernetwork()
-            shared.loaded_hypernetwork.load(path)
-
-        except Exception:
-            print(f"Error loading hypernetwork {path}", file=sys.stderr)
-            print(traceback.format_exc(), file=sys.stderr)
-    else:
-        if shared.loaded_hypernetwork is not None:
-            print(f"Unloading hypernetwork")
-
-        shared.loaded_hypernetwork = None
-
-
-def apply_hypernetwork(hypernetwork, context, layer=None):
-    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
-
-    if hypernetwork_layers is None:
-        return context, context
-
-    if layer is not None:
-        layer.hyper_k = hypernetwork_layers[0]
-        layer.hyper_v = hypernetwork_layers[1]
-
-    context_k = hypernetwork_layers[0](context)
-    context_v = hypernetwork_layers[1](context)
-    return context_k, context_v
-
-
-def attention_CrossAttention_forward(self, x, context=None, mask=None):
-    h = self.heads
-
-    q = self.to_q(x)
-    context = default(context, x)
-
-    context_k, context_v = apply_hypernetwork(shared.loaded_hypernetwork, context, self)
-    k = self.to_k(context_k)
-    v = self.to_v(context_v)
-
-    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
-
-    sim = einsum('b i d, b j d -> b i j', q, k) * self.scale
-
-    if mask is not None:
-        mask = rearrange(mask, 'b ... -> b (...)')
-        max_neg_value = -torch.finfo(sim.dtype).max
-        mask = repeat(mask, 'b j -> (b h) () j', h=h)
-        sim.masked_fill_(~mask, max_neg_value)
-
-    # attention, what we cannot get enough of
-    attn = sim.softmax(dim=-1)
-
-    out = einsum('b i j, b j d -> b i d', attn, v)
-    out = rearrange(out, '(b h) n d -> b n (h d)', h=h)
-    return self.to_out(out)
-
-
-def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_image_prompt):
-    assert hypernetwork_name, 'embedding not selected'
-
-    path = shared.hypernetworks.get(hypernetwork_name, None)
-    shared.loaded_hypernetwork = Hypernetwork()
-    shared.loaded_hypernetwork.load(path)
-
-    shared.state.textinfo = "Initializing hypernetwork training..."
-    shared.state.job_count = steps
-
-    filename = os.path.join(shared.cmd_opts.hypernetwork_dir, f'{hypernetwork_name}.pt')
-
-    log_directory = os.path.join(log_directory, datetime.datetime.now().strftime("%Y-%m-%d"), hypernetwork_name)
-
-    if save_hypernetwork_every > 0:
-        hypernetwork_dir = os.path.join(log_directory, "hypernetworks")
-        os.makedirs(hypernetwork_dir, exist_ok=True)
-    else:
-        hypernetwork_dir = None
-
-    if create_image_every > 0:
-        images_dir = os.path.join(log_directory, "images")
-        os.makedirs(images_dir, exist_ok=True)
-    else:
-        images_dir = None
-
-    cond_model = shared.sd_model.cond_stage_model
-
-    shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
-    with torch.autocast("cuda"):
-        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=512, height=512, repeats=1, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file)
-
-    hypernetwork = shared.loaded_hypernetwork
-    weights = hypernetwork.weights()
-    for weight in weights:
-        weight.requires_grad = True
-
-    optimizer = torch.optim.AdamW(weights, lr=learn_rate)
-
-    losses = torch.zeros((32,))
-
-    last_saved_file = "<none>"
-    last_saved_image = "<none>"
-
-    ititial_step = hypernetwork.step or 0
-    if ititial_step > steps:
-        return hypernetwork, filename
-
-    pbar = tqdm.tqdm(enumerate(ds), total=steps - ititial_step)
-    for i, (x, text) in pbar:
-        hypernetwork.step = i + ititial_step
-
-        if hypernetwork.step > steps:
-            break
-
-        if shared.state.interrupted:
-            break
-
-        with torch.autocast("cuda"):
-            c = cond_model([text])
-
-            x = x.to(devices.device)
-            loss = shared.sd_model(x.unsqueeze(0), c)[0]
-            del x
-
-            losses[hypernetwork.step % losses.shape[0]] = loss.item()
-
-            optimizer.zero_grad()
-            loss.backward()
-            optimizer.step()
-
-        pbar.set_description(f"loss: {losses.mean():.7f}")
-
-        if hypernetwork.step > 0 and hypernetwork_dir is not None and hypernetwork.step % save_hypernetwork_every == 0:
-            last_saved_file = os.path.join(hypernetwork_dir, f'{hypernetwork_name}-{hypernetwork.step}.pt')
-            hypernetwork.save(last_saved_file)
-
-        if hypernetwork.step > 0 and images_dir is not None and hypernetwork.step % create_image_every == 0:
-            last_saved_image = os.path.join(images_dir, f'{hypernetwork_name}-{hypernetwork.step}.png')
-
-            preview_text = text if preview_image_prompt == "" else preview_image_prompt
-
-            p = processing.StableDiffusionProcessingTxt2Img(
-                sd_model=shared.sd_model,
-                prompt=preview_text,
-                steps=20,
-                do_not_save_grid=True,
-                do_not_save_samples=True,
-            )
-
-            processed = processing.process_images(p)
-            image = processed.images[0]
-
-            shared.state.current_image = image
-            image.save(last_saved_image)
-
-            last_saved_image += f", prompt: {preview_text}"
-
-        shared.state.job_no = hypernetwork.step
-
-        shared.state.textinfo = f"""
-<p>
-Loss: {losses.mean():.7f}<br/>
-Step: {hypernetwork.step}<br/>
-Last prompt: {html.escape(text)}<br/>
-Last saved embedding: {html.escape(last_saved_file)}<br/>
-Last saved image: {html.escape(last_saved_image)}<br/>
-</p>
-"""
-
-    checkpoint = sd_models.select_checkpoint()
-
-    hypernetwork.sd_checkpoint = checkpoint.hash
-    hypernetwork.sd_checkpoint_name = checkpoint.model_name
-    hypernetwork.save(filename)
-
-    return hypernetwork, filename
-
-
diff --git a/modules/hypernetwork/ui.py b/modules/hypernetwork/ui.py
deleted file mode 100644
index f6d1d0a3..00000000
--- a/modules/hypernetwork/ui.py
+++ /dev/null
@@ -1,43 +0,0 @@
-import html
-import os
-
-import gradio as gr
-
-import modules.textual_inversion.textual_inversion
-import modules.textual_inversion.preprocess
-from modules import sd_hijack, shared
-from modules.hypernetwork import hypernetwork
-
-
-def create_hypernetwork(name):
-    fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt")
-    assert not os.path.exists(fn), f"file {fn} already exists"
-
-    hypernet = modules.hypernetwork.hypernetwork.Hypernetwork(name=name)
-    hypernet.save(fn)
-
-    shared.reload_hypernetworks()
-
-    return gr.Dropdown.update(choices=sorted([x for x in shared.hypernetworks.keys()])), f"Created: {fn}", ""
-
-
-def train_hypernetwork(*args):
-
-    initial_hypernetwork = shared.loaded_hypernetwork
-
-    try:
-        sd_hijack.undo_optimizations()
-
-        hypernetwork, filename = modules.hypernetwork.hypernetwork.train_hypernetwork(*args)
-
-        res = f"""
-Training {'interrupted' if shared.state.interrupted else 'finished'} at {hypernetwork.step} steps.
-Hypernetwork saved to {html.escape(filename)}
-"""
-        return res, ""
-    except Exception:
-        raise
-    finally:
-        shared.loaded_hypernetwork = initial_hypernetwork
-        sd_hijack.apply_optimizations()
-
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
new file mode 100644
index 00000000..aa701bda
--- /dev/null
+++ b/modules/hypernetworks/hypernetwork.py
@@ -0,0 +1,283 @@
+import datetime
+import glob
+import html
+import os
+import sys
+import traceback
+import tqdm
+
+import torch
+
+from ldm.util import default
+from modules import devices, shared, processing, sd_models
+import torch
+from torch import einsum
+from einops import rearrange, repeat
+import modules.textual_inversion.dataset
+
+
+class HypernetworkModule(torch.nn.Module):
+    def __init__(self, dim, state_dict=None):
+        super().__init__()
+
+        self.linear1 = torch.nn.Linear(dim, dim * 2)
+        self.linear2 = torch.nn.Linear(dim * 2, dim)
+
+        if state_dict is not None:
+            self.load_state_dict(state_dict, strict=True)
+        else:
+
+            self.linear1.weight.data.normal_(mean=0.0, std=0.01)
+            self.linear1.bias.data.zero_()
+            self.linear2.weight.data.normal_(mean=0.0, std=0.01)
+            self.linear2.bias.data.zero_()
+
+        self.to(devices.device)
+
+    def forward(self, x):
+        return x + (self.linear2(self.linear1(x)))
+
+
+class Hypernetwork:
+    filename = None
+    name = None
+
+    def __init__(self, name=None):
+        self.filename = None
+        self.name = name
+        self.layers = {}
+        self.step = 0
+        self.sd_checkpoint = None
+        self.sd_checkpoint_name = None
+
+        for size in [320, 640, 768, 1280]:
+            self.layers[size] = (HypernetworkModule(size), HypernetworkModule(size))
+
+    def weights(self):
+        res = []
+
+        for k, layers in self.layers.items():
+            for layer in layers:
+                layer.train()
+                res += [layer.linear1.weight, layer.linear1.bias, layer.linear2.weight, layer.linear2.bias]
+
+        return res
+
+    def save(self, filename):
+        state_dict = {}
+
+        for k, v in self.layers.items():
+            state_dict[k] = (v[0].state_dict(), v[1].state_dict())
+
+        state_dict['step'] = self.step
+        state_dict['name'] = self.name
+        state_dict['sd_checkpoint'] = self.sd_checkpoint
+        state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name
+
+        torch.save(state_dict, filename)
+
+    def load(self, filename):
+        self.filename = filename
+        if self.name is None:
+            self.name = os.path.splitext(os.path.basename(filename))[0]
+
+        state_dict = torch.load(filename, map_location='cpu')
+
+        for size, sd in state_dict.items():
+            if type(size) == int:
+                self.layers[size] = (HypernetworkModule(size, sd[0]), HypernetworkModule(size, sd[1]))
+
+        self.name = state_dict.get('name', self.name)
+        self.step = state_dict.get('step', 0)
+        self.sd_checkpoint = state_dict.get('sd_checkpoint', None)
+        self.sd_checkpoint_name = state_dict.get('sd_checkpoint_name', None)
+
+
+def list_hypernetworks(path):
+    res = {}
+    for filename in glob.iglob(os.path.join(path, '**/*.pt'), recursive=True):
+        name = os.path.splitext(os.path.basename(filename))[0]
+        res[name] = filename
+    return res
+
+
+def load_hypernetwork(filename):
+    path = shared.hypernetworks.get(filename, None)
+    if path is not None:
+        print(f"Loading hypernetwork {filename}")
+        try:
+            shared.loaded_hypernetwork = Hypernetwork()
+            shared.loaded_hypernetwork.load(path)
+
+        except Exception:
+            print(f"Error loading hypernetwork {path}", file=sys.stderr)
+            print(traceback.format_exc(), file=sys.stderr)
+    else:
+        if shared.loaded_hypernetwork is not None:
+            print(f"Unloading hypernetwork")
+
+        shared.loaded_hypernetwork = None
+
+
+def apply_hypernetwork(hypernetwork, context, layer=None):
+    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
+
+    if hypernetwork_layers is None:
+        return context, context
+
+    if layer is not None:
+        layer.hyper_k = hypernetwork_layers[0]
+        layer.hyper_v = hypernetwork_layers[1]
+
+    context_k = hypernetwork_layers[0](context)
+    context_v = hypernetwork_layers[1](context)
+    return context_k, context_v
+
+
+def attention_CrossAttention_forward(self, x, context=None, mask=None):
+    h = self.heads
+
+    q = self.to_q(x)
+    context = default(context, x)
+
+    context_k, context_v = apply_hypernetwork(shared.loaded_hypernetwork, context, self)
+    k = self.to_k(context_k)
+    v = self.to_v(context_v)
+
+    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
+
+    sim = einsum('b i d, b j d -> b i j', q, k) * self.scale
+
+    if mask is not None:
+        mask = rearrange(mask, 'b ... -> b (...)')
+        max_neg_value = -torch.finfo(sim.dtype).max
+        mask = repeat(mask, 'b j -> (b h) () j', h=h)
+        sim.masked_fill_(~mask, max_neg_value)
+
+    # attention, what we cannot get enough of
+    attn = sim.softmax(dim=-1)
+
+    out = einsum('b i j, b j d -> b i d', attn, v)
+    out = rearrange(out, '(b h) n d -> b n (h d)', h=h)
+    return self.to_out(out)
+
+
+def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_image_prompt):
+    assert hypernetwork_name, 'embedding not selected'
+
+    path = shared.hypernetworks.get(hypernetwork_name, None)
+    shared.loaded_hypernetwork = Hypernetwork()
+    shared.loaded_hypernetwork.load(path)
+
+    shared.state.textinfo = "Initializing hypernetwork training..."
+    shared.state.job_count = steps
+
+    filename = os.path.join(shared.cmd_opts.hypernetwork_dir, f'{hypernetwork_name}.pt')
+
+    log_directory = os.path.join(log_directory, datetime.datetime.now().strftime("%Y-%m-%d"), hypernetwork_name)
+
+    if save_hypernetwork_every > 0:
+        hypernetwork_dir = os.path.join(log_directory, "hypernetworks")
+        os.makedirs(hypernetwork_dir, exist_ok=True)
+    else:
+        hypernetwork_dir = None
+
+    if create_image_every > 0:
+        images_dir = os.path.join(log_directory, "images")
+        os.makedirs(images_dir, exist_ok=True)
+    else:
+        images_dir = None
+
+    cond_model = shared.sd_model.cond_stage_model
+
+    shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
+    with torch.autocast("cuda"):
+        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=512, height=512, repeats=1, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file)
+
+    hypernetwork = shared.loaded_hypernetwork
+    weights = hypernetwork.weights()
+    for weight in weights:
+        weight.requires_grad = True
+
+    optimizer = torch.optim.AdamW(weights, lr=learn_rate)
+
+    losses = torch.zeros((32,))
+
+    last_saved_file = "<none>"
+    last_saved_image = "<none>"
+
+    ititial_step = hypernetwork.step or 0
+    if ititial_step > steps:
+        return hypernetwork, filename
+
+    pbar = tqdm.tqdm(enumerate(ds), total=steps - ititial_step)
+    for i, (x, text) in pbar:
+        hypernetwork.step = i + ititial_step
+
+        if hypernetwork.step > steps:
+            break
+
+        if shared.state.interrupted:
+            break
+
+        with torch.autocast("cuda"):
+            c = cond_model([text])
+
+            x = x.to(devices.device)
+            loss = shared.sd_model(x.unsqueeze(0), c)[0]
+            del x
+
+            losses[hypernetwork.step % losses.shape[0]] = loss.item()
+
+            optimizer.zero_grad()
+            loss.backward()
+            optimizer.step()
+
+        pbar.set_description(f"loss: {losses.mean():.7f}")
+
+        if hypernetwork.step > 0 and hypernetwork_dir is not None and hypernetwork.step % save_hypernetwork_every == 0:
+            last_saved_file = os.path.join(hypernetwork_dir, f'{hypernetwork_name}-{hypernetwork.step}.pt')
+            hypernetwork.save(last_saved_file)
+
+        if hypernetwork.step > 0 and images_dir is not None and hypernetwork.step % create_image_every == 0:
+            last_saved_image = os.path.join(images_dir, f'{hypernetwork_name}-{hypernetwork.step}.png')
+
+            preview_text = text if preview_image_prompt == "" else preview_image_prompt
+
+            p = processing.StableDiffusionProcessingTxt2Img(
+                sd_model=shared.sd_model,
+                prompt=preview_text,
+                steps=20,
+                do_not_save_grid=True,
+                do_not_save_samples=True,
+            )
+
+            processed = processing.process_images(p)
+            image = processed.images[0]
+
+            shared.state.current_image = image
+            image.save(last_saved_image)
+
+            last_saved_image += f", prompt: {preview_text}"
+
+        shared.state.job_no = hypernetwork.step
+
+        shared.state.textinfo = f"""
+<p>
+Loss: {losses.mean():.7f}<br/>
+Step: {hypernetwork.step}<br/>
+Last prompt: {html.escape(text)}<br/>
+Last saved embedding: {html.escape(last_saved_file)}<br/>
+Last saved image: {html.escape(last_saved_image)}<br/>
+</p>
+"""
+
+    checkpoint = sd_models.select_checkpoint()
+
+    hypernetwork.sd_checkpoint = checkpoint.hash
+    hypernetwork.sd_checkpoint_name = checkpoint.model_name
+    hypernetwork.save(filename)
+
+    return hypernetwork, filename
+
+
diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py
new file mode 100644
index 00000000..811bc31e
--- /dev/null
+++ b/modules/hypernetworks/ui.py
@@ -0,0 +1,43 @@
+import html
+import os
+
+import gradio as gr
+
+import modules.textual_inversion.textual_inversion
+import modules.textual_inversion.preprocess
+from modules import sd_hijack, shared
+from modules.hypernetworks import hypernetwork
+
+
+def create_hypernetwork(name):
+    fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt")
+    assert not os.path.exists(fn), f"file {fn} already exists"
+
+    hypernet = modules.hypernetwork.hypernetwork.Hypernetwork(name=name)
+    hypernet.save(fn)
+
+    shared.reload_hypernetworks()
+
+    return gr.Dropdown.update(choices=sorted([x for x in shared.hypernetworks.keys()])), f"Created: {fn}", ""
+
+
+def train_hypernetwork(*args):
+
+    initial_hypernetwork = shared.loaded_hypernetwork
+
+    try:
+        sd_hijack.undo_optimizations()
+
+        hypernetwork, filename = modules.hypernetwork.hypernetwork.train_hypernetwork(*args)
+
+        res = f"""
+Training {'interrupted' if shared.state.interrupted else 'finished'} at {hypernetwork.step} steps.
+Hypernetwork saved to {html.escape(filename)}
+"""
+        return res, ""
+    except Exception:
+        raise
+    finally:
+        shared.loaded_hypernetwork = initial_hypernetwork
+        sd_hijack.apply_optimizations()
+
diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index f873049a..f07ec041 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -37,7 +37,7 @@ def apply_optimizations():
 
 
 def undo_optimizations():
-    from modules.hypernetwork import hypernetwork
+    from modules.hypernetworks import hypernetwork
 
     ldm.modules.attention.CrossAttention.forward = hypernetwork.attention_CrossAttention_forward
     ldm.modules.diffusionmodules.model.nonlinearity = diffusionmodules_model_nonlinearity
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index 27e571fc..3349b9c3 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -9,7 +9,7 @@ from ldm.util import default
 from einops import rearrange
 
 from modules import shared
-from modules.hypernetwork import hypernetwork
+from modules.hypernetworks import hypernetwork
 
 
 if shared.cmd_opts.xformers or shared.cmd_opts.force_enable_xformers:
diff --git a/modules/shared.py b/modules/shared.py
index 375e3afb..1dc2ccf2 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -14,7 +14,7 @@ import modules.sd_models
 import modules.styles
 import modules.devices as devices
 from modules import sd_samplers
-from modules.hypernetwork import hypernetwork
+from modules.hypernetworks import hypernetwork
 from modules.paths import models_path, script_path, sd_path
 
 sd_model_file = os.path.join(script_path, 'model.ckpt')
diff --git a/modules/ui.py b/modules/ui.py
index f57f32db..42e5d866 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -39,7 +39,7 @@ import modules.generation_parameters_copypaste
 from modules import prompt_parser
 from modules.images import save_image
 import modules.textual_inversion.ui
-import modules.hypernetwork.ui
+import modules.hypernetworks.ui
 
 # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI
 mimetypes.init()
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 16918c99..cddb192a 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -11,7 +11,7 @@ import modules.scripts as scripts
 import gradio as gr
 
 from modules import images
-from modules.hypernetwork import hypernetwork
+from modules.hypernetworks import hypernetwork
 from modules.processing import process_images, Processed, get_correct_sampler
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
diff --git a/webui.py b/webui.py
index ba2156c8..faa38a0d 100644
--- a/webui.py
+++ b/webui.py
@@ -29,7 +29,7 @@ from modules import devices
 from modules import modelloader
 from modules.paths import script_path
 from modules.shared import cmd_opts
-import modules.hypernetwork.hypernetwork
+import modules.hypernetworks.hypernetwork
 
 modelloader.cleanup_models()
 modules.sd_models.setup_model()
-- 
cgit v1.2.3


From b0583be0884cd17dafb408fd79b52b2a0a972563 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 15:54:34 +0300
Subject: more renames

---
 modules/hypernetworks/ui.py | 4 ++--
 modules/ui.py               | 4 ++--
 webui.py                    | 2 +-
 3 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py
index 811bc31e..e7540f41 100644
--- a/modules/hypernetworks/ui.py
+++ b/modules/hypernetworks/ui.py
@@ -13,7 +13,7 @@ def create_hypernetwork(name):
     fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt")
     assert not os.path.exists(fn), f"file {fn} already exists"
 
-    hypernet = modules.hypernetwork.hypernetwork.Hypernetwork(name=name)
+    hypernet = modules.hypernetworks.hypernetwork.Hypernetwork(name=name)
     hypernet.save(fn)
 
     shared.reload_hypernetworks()
@@ -28,7 +28,7 @@ def train_hypernetwork(*args):
     try:
         sd_hijack.undo_optimizations()
 
-        hypernetwork, filename = modules.hypernetwork.hypernetwork.train_hypernetwork(*args)
+        hypernetwork, filename = modules.hypernetworks.hypernetwork.train_hypernetwork(*args)
 
         res = f"""
 Training {'interrupted' if shared.state.interrupted else 'finished'} at {hypernetwork.step} steps.
diff --git a/modules/ui.py b/modules/ui.py
index 42e5d866..ee333c3b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1111,7 +1111,7 @@ def create_ui(wrap_gradio_gpu_call):
         )
 
         create_hypernetwork.click(
-            fn=modules.hypernetwork.ui.create_hypernetwork,
+            fn=modules.hypernetworks.ui.create_hypernetwork,
             inputs=[
                 new_hypernetwork_name,
             ],
@@ -1164,7 +1164,7 @@ def create_ui(wrap_gradio_gpu_call):
         )
 
         train_hypernetwork.click(
-            fn=wrap_gradio_gpu_call(modules.hypernetwork.ui.train_hypernetwork, extra_outputs=[gr.update()]),
+            fn=wrap_gradio_gpu_call(modules.hypernetworks.ui.train_hypernetwork, extra_outputs=[gr.update()]),
             _js="start_training_textual_inversion",
             inputs=[
                 train_hypernetwork_name,
diff --git a/webui.py b/webui.py
index faa38a0d..338f58e1 100644
--- a/webui.py
+++ b/webui.py
@@ -83,7 +83,7 @@ modules.scripts.load_scripts(os.path.join(script_path, "scripts"))
 shared.sd_model = modules.sd_models.load_model()
 shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model)))
 
-shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetwork.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)))
+shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetworks.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)))
 
 
 def webui():
-- 
cgit v1.2.3


From 5766ce21abc1986c94d8bd3279b6f4d5205ba984 Mon Sep 17 00:00:00 2001
From: ClashSAN <98228077+ClashSAN@users.noreply.github.com>
Date: Tue, 11 Oct 2022 13:20:03 +0000
Subject: Update README.md

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 0e938768..a10faa01 100644
--- a/README.md
+++ b/README.md
@@ -69,7 +69,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
      - also supports weights for prompts: `a cat :1.2 AND a dog AND a penguin :2.2`
 - No token limit for prompts (original stable diffusion lets you use up to 75 tokens)
 - DeepDanbooru integration, creates danbooru style tags for anime prompts (add --deepdanbooru to commandline args)
-- [xformers](https://github.com/mv-lab/swin2sr), major speed increase for select cards: (add --xformers to commandline args)
+- [xformers](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers), major speed increase for select cards: (add --xformers to commandline args)
 
 ## Installation and Running
 Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for both [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended) and [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs.
-- 
cgit v1.2.3


From d01a2d01560b31937df1f3433d210c18f97d32fa Mon Sep 17 00:00:00 2001
From: papuSpartan <mcgpapu@gmail.com>
Date: Tue, 11 Oct 2022 08:03:31 -0500
Subject: move list refresh to webui.py and add stdout indicating it's doing so

---
 modules/ui.py | 3 ---
 webui.py      | 2 ++
 2 files changed, 2 insertions(+), 3 deletions(-)

diff --git a/modules/ui.py b/modules/ui.py
index 06ff118f..ae9317a3 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -39,7 +39,6 @@ import modules.generation_parameters_copypaste
 from modules import prompt_parser
 from modules.images import save_image
 import modules.textual_inversion.ui
-from modules.sd_models import list_models
 
 # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI
 mimetypes.init()
@@ -1291,8 +1290,6 @@ Requested path was: {f}
             shared.state.interrupt()
             settings_interface.gradio_ref.do_restart = True
 
-            # refresh models so that new models/.ckpt's show up on reload
-            list_models()
 
         restart_gradio.click(
             fn=request_restart,
diff --git a/webui.py b/webui.py
index 270584f7..94098c4c 100644
--- a/webui.py
+++ b/webui.py
@@ -124,6 +124,8 @@ def webui():
         modules.scripts.reload_scripts(os.path.join(script_path, "scripts"))
         print('Reloading modules: modules.ui')
         importlib.reload(modules.ui)
+        print('Refreshing Model List')
+        modules.sd_models.list_models()
         print('Restarting Gradio')
 
 
-- 
cgit v1.2.3


From 66b7d7584f0b44ce1316425808c27ca7df38293c Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 17:03:00 +0300
Subject: become even stricter with pickles no pickle shall pass thank you
 again, RyotaK

---
 modules/safe.py | 17 +++++++++++++++++
 1 file changed, 17 insertions(+)

diff --git a/modules/safe.py b/modules/safe.py
index 05917463..20be16a5 100644
--- a/modules/safe.py
+++ b/modules/safe.py
@@ -10,6 +10,7 @@ import torch
 import numpy
 import _codecs
 import zipfile
+import re
 
 
 # PyTorch 1.13 and later have _TypedStorage renamed to TypedStorage
@@ -54,11 +55,27 @@ class RestrictedUnpickler(pickle.Unpickler):
         raise pickle.UnpicklingError(f"global '{module}/{name}' is forbidden")
 
 
+allowed_zip_names = ["archive/data.pkl", "archive/version"]
+allowed_zip_names_re = re.compile(r"^archive/data/\d+$")
+
+
+def check_zip_filenames(filename, names):
+    for name in names:
+        if name in allowed_zip_names:
+            continue
+        if allowed_zip_names_re.match(name):
+            continue
+
+        raise Exception(f"bad file inside {filename}: {name}")
+
+
 def check_pt(filename):
     try:
 
         # new pytorch format is a zip file
         with zipfile.ZipFile(filename) as z:
+            check_zip_filenames(filename, z.namelist())
+
             with z.open('archive/data.pkl') as file:
                 unpickler = RestrictedUnpickler(file)
                 unpickler.load()
-- 
cgit v1.2.3


From e0ee5bf703996b33e6d97aa36e0973ceedc88503 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 17:08:03 +0300
Subject: add codeowners file so stop the great guys who are collaborating on
 the project from merging in PRs.

---
 CODEOWNERS | 1 +
 1 file changed, 1 insertion(+)
 create mode 100644 CODEOWNERS

diff --git a/CODEOWNERS b/CODEOWNERS
new file mode 100644
index 00000000..935fedcf
--- /dev/null
+++ b/CODEOWNERS
@@ -0,0 +1 @@
+*       @AUTOMATIC1111
-- 
cgit v1.2.3


From c0484f1b986ce7acb0e3596f6089a191279f5442 Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Mon, 10 Oct 2022 22:48:54 -0400
Subject: Add cross-attention optimization from InvokeAI

* Add cross-attention optimization from InvokeAI (~30% speed improvement on MPS)
* Add command line option for it
* Make it default when CUDA is unavailable
---
 modules/sd_hijack.py               |  5 ++-
 modules/sd_hijack_optimizations.py | 79 ++++++++++++++++++++++++++++++++++++++
 modules/shared.py                  |  5 ++-
 3 files changed, 86 insertions(+), 3 deletions(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index f07ec041..5a1b167f 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -30,8 +30,11 @@ def apply_optimizations():
     elif cmd_opts.opt_split_attention_v1:
         print("Applying v1 cross attention optimization.")
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1
+    elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention_invokeai or not torch.cuda.is_available()):
+        print("Applying cross attention optimization (InvokeAI).")
+        ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_invokeAI
     elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention or torch.cuda.is_available()):
-        print("Applying cross attention optimization.")
+        print("Applying cross attention optimization (Doggettx).")
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward
         ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.cross_attention_attnblock_forward
 
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index 3349b9c3..870226c5 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -1,6 +1,7 @@
 import math
 import sys
 import traceback
+import psutil
 
 import torch
 from torch import einsum
@@ -116,6 +117,84 @@ def split_cross_attention_forward(self, x, context=None, mask=None):
 
     return self.to_out(r2)
 
+# -- From https://github.com/invoke-ai/InvokeAI/blob/main/ldm/modules/attention.py (with hypernetworks support added) --
+
+mem_total_gb = psutil.virtual_memory().total // (1 << 30)
+
+def einsum_op_compvis(q, k, v):
+    s = einsum('b i d, b j d -> b i j', q, k)
+    s = s.softmax(dim=-1, dtype=s.dtype)
+    return einsum('b i j, b j d -> b i d', s, v)
+
+def einsum_op_slice_0(q, k, v, slice_size):
+    r = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device, dtype=q.dtype)
+    for i in range(0, q.shape[0], slice_size):
+        end = i + slice_size
+        r[i:end] = einsum_op_compvis(q[i:end], k[i:end], v[i:end])
+    return r
+
+def einsum_op_slice_1(q, k, v, slice_size):
+    r = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device, dtype=q.dtype)
+    for i in range(0, q.shape[1], slice_size):
+        end = i + slice_size
+        r[:, i:end] = einsum_op_compvis(q[:, i:end], k, v)
+    return r
+
+def einsum_op_mps_v1(q, k, v):
+    if q.shape[1] <= 4096: # (512x512) max q.shape[1]: 4096
+        return einsum_op_compvis(q, k, v)
+    else:
+        slice_size = math.floor(2**30 / (q.shape[0] * q.shape[1]))
+        return einsum_op_slice_1(q, k, v, slice_size)
+
+def einsum_op_mps_v2(q, k, v):
+    if mem_total_gb > 8 and q.shape[1] <= 4096:
+        return einsum_op_compvis(q, k, v)
+    else:
+        return einsum_op_slice_0(q, k, v, 1)
+
+def einsum_op_tensor_mem(q, k, v, max_tensor_mb):
+    size_mb = q.shape[0] * q.shape[1] * k.shape[1] * q.element_size() // (1 << 20)
+    if size_mb <= max_tensor_mb:
+        return einsum_op_compvis(q, k, v)
+    div = 1 << int((size_mb - 1) / max_tensor_mb).bit_length()
+    if div <= q.shape[0]:
+        return einsum_op_slice_0(q, k, v, q.shape[0] // div)
+    return einsum_op_slice_1(q, k, v, max(q.shape[1] // div, 1))
+
+def einsum_op(q, k, v):
+    if q.device.type == 'mps':
+        if mem_total_gb >= 32:
+            return einsum_op_mps_v1(q, k, v)
+        return einsum_op_mps_v2(q, k, v)
+
+    # Smaller slices are faster due to L2/L3/SLC caches.
+    # Tested on i7 with 8MB L3 cache.
+    return einsum_op_tensor_mem(q, k, v, 32)
+
+def split_cross_attention_forward_invokeAI(self, x, context=None, mask=None):
+    h = self.heads
+
+    q = self.to_q(x)
+    context = default(context, x)
+
+    hypernetwork = shared.loaded_hypernetwork
+    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
+
+    if hypernetwork_layers is not None:
+        k = self.to_k(hypernetwork_layers[0](context)) * self.scale
+        v = self.to_v(hypernetwork_layers[1](context))
+    else:
+        k = self.to_k(context) * self.scale
+        v = self.to_v(context)
+    del context, x
+
+    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
+    r = einsum_op(q, k, v)
+    return self.to_out(rearrange(r, '(b h) n d -> b n (h d)', h=h))
+
+# -- End of code from https://github.com/invoke-ai/InvokeAI/blob/main/ldm/modules/attention.py --
+
 def xformers_attention_forward(self, x, context=None, mask=None):
     h = self.heads
     q_in = self.to_q(x)
diff --git a/modules/shared.py b/modules/shared.py
index 1dc2ccf2..20b45f23 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -50,9 +50,10 @@ parser.add_argument("--ldsr-models-path", type=str, help="Path to directory with
 parser.add_argument("--xformers", action='store_true', help="enable xformers for cross attention layers")
 parser.add_argument("--force-enable-xformers", action='store_true', help="enable xformers for cross attention layers regardless of whether the checking code thinks you can run it; do not make bug reports if this fails to work")
 parser.add_argument("--deepdanbooru", action='store_true', help="enable deepdanbooru interrogator")
-parser.add_argument("--opt-split-attention", action='store_true', help="force-enables cross-attention layer optimization. By default, it's on for torch.cuda and off for other torch devices.")
-parser.add_argument("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization")
+parser.add_argument("--opt-split-attention", action='store_true', help="force-enables Doggettx's cross-attention layer optimization. By default, it's on for torch cuda.")
+parser.add_argument("--opt-split-attention-invokeai", action='store_true', help="force-enables InvokeAI's cross-attention layer optimization. By default, it's on when cuda is unavailable.")
 parser.add_argument("--opt-split-attention-v1", action='store_true', help="enable older version of split attention optimization that does not consume all the VRAM it can find")
+parser.add_argument("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization")
 parser.add_argument("--use-cpu", nargs='+',choices=['SD', 'GFPGAN', 'BSRGAN', 'ESRGAN', 'SCUNet', 'CodeFormer'], help="use CPU as torch device for specified modules", default=[])
 parser.add_argument("--listen", action='store_true', help="launch gradio with 0.0.0.0 as server name, allowing to respond to network requests")
 parser.add_argument("--port", type=int, help="launch gradio with given server port, you need root/admin rights for ports < 1024, defaults to 7860 if available", default=None)
-- 
cgit v1.2.3


From 98fd5cde72d5bda1620ab78416c7828fdc3dc10b Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Mon, 10 Oct 2022 23:55:48 -0400
Subject: Add check for psutil

---
 modules/sd_hijack.py               | 10 ++++++++--
 modules/sd_hijack_optimizations.py | 19 +++++++++++++++----
 2 files changed, 23 insertions(+), 6 deletions(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 5a1b167f..ac70f876 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -10,6 +10,7 @@ from torch.nn.functional import silu
 import modules.textual_inversion.textual_inversion
 from modules import prompt_parser, devices, sd_hijack_optimizations, shared
 from modules.shared import opts, device, cmd_opts
+from modules.sd_hijack_optimizations import invokeAI_mps_available
 
 import ldm.modules.attention
 import ldm.modules.diffusionmodules.model
@@ -31,8 +32,13 @@ def apply_optimizations():
         print("Applying v1 cross attention optimization.")
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1
     elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention_invokeai or not torch.cuda.is_available()):
-        print("Applying cross attention optimization (InvokeAI).")
-        ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_invokeAI
+        if not invokeAI_mps_available and shared.device.type == 'mps':
+            print("The InvokeAI cross attention optimization for MPS requires the psutil package which is not installed.")
+            print("Applying v1 cross attention optimization.")
+            ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1
+        else:
+            print("Applying cross attention optimization (InvokeAI).")
+            ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_invokeAI
     elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention or torch.cuda.is_available()):
         print("Applying cross attention optimization (Doggettx).")
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index 870226c5..2a4ac7e0 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -1,7 +1,7 @@
 import math
 import sys
 import traceback
-import psutil
+import importlib
 
 import torch
 from torch import einsum
@@ -117,9 +117,20 @@ def split_cross_attention_forward(self, x, context=None, mask=None):
 
     return self.to_out(r2)
 
-# -- From https://github.com/invoke-ai/InvokeAI/blob/main/ldm/modules/attention.py (with hypernetworks support added) --
 
-mem_total_gb = psutil.virtual_memory().total // (1 << 30)
+def check_for_psutil():
+    try:
+        spec = importlib.util.find_spec('psutil')
+        return spec is not None
+    except ModuleNotFoundError:
+        return False
+
+invokeAI_mps_available = check_for_psutil()
+
+# -- Taken from https://github.com/invoke-ai/InvokeAI --
+if invokeAI_mps_available:
+    import psutil
+    mem_total_gb = psutil.virtual_memory().total // (1 << 30)
 
 def einsum_op_compvis(q, k, v):
     s = einsum('b i d, b j d -> b i j', q, k)
@@ -193,7 +204,7 @@ def split_cross_attention_forward_invokeAI(self, x, context=None, mask=None):
     r = einsum_op(q, k, v)
     return self.to_out(rearrange(r, '(b h) n d -> b n (h d)', h=h))
 
-# -- End of code from https://github.com/invoke-ai/InvokeAI/blob/main/ldm/modules/attention.py --
+# -- End of code from https://github.com/invoke-ai/InvokeAI --
 
 def xformers_attention_forward(self, x, context=None, mask=None):
     h = self.heads
-- 
cgit v1.2.3


From 574c8e554a5371eca2cbf344764cb241c6ec4efc Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Tue, 11 Oct 2022 03:32:11 -0400
Subject: Add InvokeAI and lstein to credits, add back CUDA support

---
 README.md                          |  1 +
 modules/sd_hijack_optimizations.py | 13 +++++++++++++
 2 files changed, 14 insertions(+)

diff --git a/README.md b/README.md
index a10faa01..859a91b6 100644
--- a/README.md
+++ b/README.md
@@ -123,6 +123,7 @@ The documentation was moved from this README over to the project's [wiki](https:
 - LDSR - https://github.com/Hafiidz/latent-diffusion
 - Ideas for optimizations - https://github.com/basujindal/stable-diffusion
 - Doggettx - Cross Attention layer optimization - https://github.com/Doggettx/stable-diffusion, original idea for prompt editing.
+- InvokeAI, lstein - Cross Attention layer optimization - https://github.com/invoke-ai/InvokeAI (originally http://github.com/lstein/stable-diffusion)
 - Rinon Gal - Textual Inversion - https://github.com/rinongal/textual_inversion (we're not using his code, but we are using his ideas).
 - Idea for SD upscale - https://github.com/jquesnelle/txt2imghd
 - Noise generation for outpainting mk2 - https://github.com/parlance-zz/g-diffuser-bot
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index 2a4ac7e0..f006427f 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -173,7 +173,20 @@ def einsum_op_tensor_mem(q, k, v, max_tensor_mb):
         return einsum_op_slice_0(q, k, v, q.shape[0] // div)
     return einsum_op_slice_1(q, k, v, max(q.shape[1] // div, 1))
 
+def einsum_op_cuda(q, k, v):
+    stats = torch.cuda.memory_stats(q.device)
+    mem_active = stats['active_bytes.all.current']
+    mem_reserved = stats['reserved_bytes.all.current']
+    mem_free_cuda, _ = torch.cuda.mem_get_info(q.device)
+    mem_free_torch = mem_reserved - mem_active
+    mem_free_total = mem_free_cuda + mem_free_torch
+    # Divide factor of safety as there's copying and fragmentation
+    return self.einsum_op_tensor_mem(q, k, v, mem_free_total / 3.3 / (1 << 20))
+
 def einsum_op(q, k, v):
+    if q.device.type == 'cuda':
+        return einsum_op_cuda(q, k, v)
+
     if q.device.type == 'mps':
         if mem_total_gb >= 32:
             return einsum_op_mps_v1(q, k, v)
-- 
cgit v1.2.3


From 861db783c7acfcb93cf0b5191db3d50f9a9bc531 Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Tue, 11 Oct 2022 05:13:17 -0400
Subject: Use apply_hypernetwork function

---
 modules/sd_hijack_optimizations.py | 14 ++++----------
 1 file changed, 4 insertions(+), 10 deletions(-)

diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index f006427f..79405525 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -202,16 +202,10 @@ def split_cross_attention_forward_invokeAI(self, x, context=None, mask=None):
     q = self.to_q(x)
     context = default(context, x)
 
-    hypernetwork = shared.loaded_hypernetwork
-    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
-
-    if hypernetwork_layers is not None:
-        k = self.to_k(hypernetwork_layers[0](context)) * self.scale
-        v = self.to_v(hypernetwork_layers[1](context))
-    else:
-        k = self.to_k(context) * self.scale
-        v = self.to_v(context)
-    del context, x
+    context_k, context_v = hypernetwork.apply_hypernetwork(shared.loaded_hypernetwork, context)
+    k = self.to_k(context_k) * self.scale
+    v = self.to_v(context_v)
+    del context, context_k, context_v, x
 
     q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
     r = einsum_op(q, k, v)
-- 
cgit v1.2.3


From 5ba23cb41f28f5856a7f64cb0d95e1e94dce90af Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 17:28:17 +0300
Subject: change default for XY plot's Y to Nothing.

---
 scripts/xy_grid.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index cddb192a..ef431105 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -197,7 +197,7 @@ class Script(scripts.Script):
             x_values = gr.Textbox(label="X values", visible=False, lines=1)
 
         with gr.Row():
-            y_type = gr.Dropdown(label="Y type", choices=[x.label for x in current_axis_options], value=current_axis_options[4].label, visible=False, type="index", elem_id="y_type")
+            y_type = gr.Dropdown(label="Y type", choices=[x.label for x in current_axis_options], value=current_axis_options[0].label, visible=False, type="index", elem_id="y_type")
             y_values = gr.Textbox(label="Y values", visible=False, lines=1)
         
         draw_legend = gr.Checkbox(label='Draw legend', value=True)
-- 
cgit v1.2.3


From d682444ecc99319fbd2b142a12727501e2884ba7 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 18:04:47 +0300
Subject: add option to select hypernetwork modules when creating

---
 modules/hypernetworks/hypernetwork.py | 4 ++--
 modules/hypernetworks/ui.py           | 4 ++--
 modules/ui.py                         | 2 ++
 3 files changed, 6 insertions(+), 4 deletions(-)

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index aa701bda..b081f14e 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -42,7 +42,7 @@ class Hypernetwork:
     filename = None
     name = None
 
-    def __init__(self, name=None):
+    def __init__(self, name=None, enable_sizes=None):
         self.filename = None
         self.name = name
         self.layers = {}
@@ -50,7 +50,7 @@ class Hypernetwork:
         self.sd_checkpoint = None
         self.sd_checkpoint_name = None
 
-        for size in [320, 640, 768, 1280]:
+        for size in enable_sizes or [320, 640, 768, 1280]:
             self.layers[size] = (HypernetworkModule(size), HypernetworkModule(size))
 
     def weights(self):
diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py
index e7540f41..cdddcce1 100644
--- a/modules/hypernetworks/ui.py
+++ b/modules/hypernetworks/ui.py
@@ -9,11 +9,11 @@ from modules import sd_hijack, shared
 from modules.hypernetworks import hypernetwork
 
 
-def create_hypernetwork(name):
+def create_hypernetwork(name, enable_sizes):
     fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt")
     assert not os.path.exists(fn), f"file {fn} already exists"
 
-    hypernet = modules.hypernetworks.hypernetwork.Hypernetwork(name=name)
+    hypernet = modules.hypernetworks.hypernetwork.Hypernetwork(name=name, enable_sizes=[int(x) for x in enable_sizes])
     hypernet.save(fn)
 
     shared.reload_hypernetworks()
diff --git a/modules/ui.py b/modules/ui.py
index f2d16b12..14b87b92 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1037,6 +1037,7 @@ def create_ui(wrap_gradio_gpu_call):
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Create a new hypernetwork</p>")
 
                     new_hypernetwork_name = gr.Textbox(label="Name")
+                    new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"])
 
                     with gr.Row():
                         with gr.Column(scale=3):
@@ -1114,6 +1115,7 @@ def create_ui(wrap_gradio_gpu_call):
             fn=modules.hypernetworks.ui.create_hypernetwork,
             inputs=[
                 new_hypernetwork_name,
+                new_hypernetwork_sizes,
             ],
             outputs=[
                 train_hypernetwork_name,
-- 
cgit v1.2.3


From ff4ef13dd591ec52f196f344f47537695df95364 Mon Sep 17 00:00:00 2001
From: JC_Array <justin318@att.net>
Date: Tue, 11 Oct 2022 10:24:27 -0500
Subject: removed unneeded print

---
 modules/deepbooru.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index e31e92c0..89dcac3c 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -119,7 +119,6 @@ def get_deepbooru_tags_from_model(model, tags, pil_image, threshold, alpha_sort)
     # sort tags
     result_tags_out = []
     sort_ndx = 0
-    print(alpha_sort)
     if alpha_sort:
         sort_ndx = 1
 
-- 
cgit v1.2.3


From 6d09b8d1df3a96e1380bb1650f5961781630af96 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 18:33:57 +0300
Subject: produce error when training with medvram/lowvram enabled

---
 modules/hypernetworks/ui.py     | 2 ++
 modules/textual_inversion/ui.py | 3 +++
 2 files changed, 5 insertions(+)

diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py
index cdddcce1..3541a388 100644
--- a/modules/hypernetworks/ui.py
+++ b/modules/hypernetworks/ui.py
@@ -25,6 +25,8 @@ def train_hypernetwork(*args):
 
     initial_hypernetwork = shared.loaded_hypernetwork
 
+    assert not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram, 'Training models with lowvram or medvram is not possible'
+
     try:
         sd_hijack.undo_optimizations()
 
diff --git a/modules/textual_inversion/ui.py b/modules/textual_inversion/ui.py
index c57de1f9..70f47343 100644
--- a/modules/textual_inversion/ui.py
+++ b/modules/textual_inversion/ui.py
@@ -22,6 +22,9 @@ def preprocess(*args):
 
 
 def train_embedding(*args):
+
+    assert not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram, 'Training models with lowvram or medvram is not possible'
+
     try:
         sd_hijack.undo_optimizations()
 
-- 
cgit v1.2.3


From d4ea5f4d8631f778d11efcde397e4a5b8801d43b Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 19:03:08 +0300
Subject: add an option to unload models during hypernetwork training to save
 VRAM

---
 modules/hypernetworks/hypernetwork.py          | 25 +++++++++++++++-------
 modules/hypernetworks/ui.py                    |  4 +++-
 modules/shared.py                              |  4 ++++
 modules/textual_inversion/dataset.py           | 29 ++++++++++++++++++--------
 modules/textual_inversion/textual_inversion.py |  2 +-
 5 files changed, 46 insertions(+), 18 deletions(-)

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index b081f14e..4700e1ec 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -175,6 +175,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
     filename = os.path.join(shared.cmd_opts.hypernetwork_dir, f'{hypernetwork_name}.pt')
 
     log_directory = os.path.join(log_directory, datetime.datetime.now().strftime("%Y-%m-%d"), hypernetwork_name)
+    unload = shared.opts.unload_models_when_training
 
     if save_hypernetwork_every > 0:
         hypernetwork_dir = os.path.join(log_directory, "hypernetworks")
@@ -188,11 +189,13 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
     else:
         images_dir = None
 
-    cond_model = shared.sd_model.cond_stage_model
-
     shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
     with torch.autocast("cuda"):
-        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=512, height=512, repeats=1, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file)
+        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=512, height=512, repeats=1, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file, include_cond=True)
+
+    if unload:
+        shared.sd_model.cond_stage_model.to(devices.cpu)
+        shared.sd_model.first_stage_model.to(devices.cpu)
 
     hypernetwork = shared.loaded_hypernetwork
     weights = hypernetwork.weights()
@@ -211,7 +214,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
         return hypernetwork, filename
 
     pbar = tqdm.tqdm(enumerate(ds), total=steps - ititial_step)
-    for i, (x, text) in pbar:
+    for i, (x, text, cond) in pbar:
         hypernetwork.step = i + ititial_step
 
         if hypernetwork.step > steps:
@@ -221,11 +224,11 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
             break
 
         with torch.autocast("cuda"):
-            c = cond_model([text])
-
+            cond = cond.to(devices.device)
             x = x.to(devices.device)
-            loss = shared.sd_model(x.unsqueeze(0), c)[0]
+            loss = shared.sd_model(x.unsqueeze(0), cond)[0]
             del x
+            del cond
 
             losses[hypernetwork.step % losses.shape[0]] = loss.item()
 
@@ -244,6 +247,10 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
 
             preview_text = text if preview_image_prompt == "" else preview_image_prompt
 
+            optimizer.zero_grad()
+            shared.sd_model.cond_stage_model.to(devices.device)
+            shared.sd_model.first_stage_model.to(devices.device)
+
             p = processing.StableDiffusionProcessingTxt2Img(
                 sd_model=shared.sd_model,
                 prompt=preview_text,
@@ -255,6 +262,10 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
             processed = processing.process_images(p)
             image = processed.images[0]
 
+            if unload:
+                shared.sd_model.cond_stage_model.to(devices.cpu)
+                shared.sd_model.first_stage_model.to(devices.cpu)
+
             shared.state.current_image = image
             image.save(last_saved_image)
 
diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py
index 3541a388..c67facbb 100644
--- a/modules/hypernetworks/ui.py
+++ b/modules/hypernetworks/ui.py
@@ -5,7 +5,7 @@ import gradio as gr
 
 import modules.textual_inversion.textual_inversion
 import modules.textual_inversion.preprocess
-from modules import sd_hijack, shared
+from modules import sd_hijack, shared, devices
 from modules.hypernetworks import hypernetwork
 
 
@@ -41,5 +41,7 @@ Hypernetwork saved to {html.escape(filename)}
         raise
     finally:
         shared.loaded_hypernetwork = initial_hypernetwork
+        shared.sd_model.cond_stage_model.to(devices.device)
+        shared.sd_model.first_stage_model.to(devices.device)
         sd_hijack.apply_optimizations()
 
diff --git a/modules/shared.py b/modules/shared.py
index 20b45f23..c1092ff7 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -228,6 +228,10 @@ options_templates.update(options_section(('system', "System"), {
     "multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job."),
 }))
 
+options_templates.update(options_section(('training', "Training"), {
+    "unload_models_when_training": OptionInfo(False, "Unload VAE and CLIP form VRAM when training"),
+}))
+
 options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, show_on_main_page=True),
     "sd_hypernetwork": OptionInfo("None", "Stable Diffusion finetune hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}),
diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index 4d006366..f61f40d3 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -8,14 +8,14 @@ from torchvision import transforms
 
 import random
 import tqdm
-from modules import devices
+from modules import devices, shared
 import re
 
 re_tag = re.compile(r"[a-zA-Z][_\w\d()]+")
 
 
 class PersonalizedBase(Dataset):
-    def __init__(self, data_root, width, height, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None):
+    def __init__(self, data_root, width, height, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None, include_cond=False):
 
         self.placeholder_token = placeholder_token
 
@@ -32,6 +32,8 @@ class PersonalizedBase(Dataset):
 
         assert data_root, 'dataset directory not specified'
 
+        cond_model = shared.sd_model.cond_stage_model
+
         self.image_paths = [os.path.join(data_root, file_path) for file_path in os.listdir(data_root)]
         print("Preparing dataset...")
         for path in tqdm.tqdm(self.image_paths):
@@ -53,7 +55,13 @@ class PersonalizedBase(Dataset):
             init_latent = model.get_first_stage_encoding(model.encode_first_stage(torchdata.unsqueeze(dim=0))).squeeze()
             init_latent = init_latent.to(devices.cpu)
 
-            self.dataset.append((init_latent, filename_tokens))
+            if include_cond:
+                text = self.create_text(filename_tokens)
+                cond = cond_model([text]).to(devices.cpu)
+            else:
+                cond = None
+
+            self.dataset.append((init_latent, filename_tokens, cond))
 
         self.length = len(self.dataset) * repeats
 
@@ -64,6 +72,12 @@ class PersonalizedBase(Dataset):
     def shuffle(self):
         self.indexes = self.initial_indexes[torch.randperm(self.initial_indexes.shape[0])]
 
+    def create_text(self, filename_tokens):
+        text = random.choice(self.lines)
+        text = text.replace("[name]", self.placeholder_token)
+        text = text.replace("[filewords]", ' '.join(filename_tokens))
+        return text
+
     def __len__(self):
         return self.length
 
@@ -72,10 +86,7 @@ class PersonalizedBase(Dataset):
             self.shuffle()
 
         index = self.indexes[i % len(self.indexes)]
-        x, filename_tokens = self.dataset[index]
-
-        text = random.choice(self.lines)
-        text = text.replace("[name]", self.placeholder_token)
-        text = text.replace("[filewords]", ' '.join(filename_tokens))
+        x, filename_tokens, cond = self.dataset[index]
 
-        return x, text
+        text = self.create_text(filename_tokens)
+        return x, text, cond
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index bb05cdc6..35f4bd9e 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -201,7 +201,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
         return embedding, filename
 
     pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step)
-    for i, (x, text) in pbar:
+    for i, (x, text, _) in pbar:
         embedding.step = i + ititial_step
 
         if embedding.step > steps:
-- 
cgit v1.2.3


From 6a9ea5b41cf92cd9e980349bb5034439f4e7a58b Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 19:22:30 +0300
Subject: prevent extra modules from being saved/loaded with hypernet

---
 modules/hypernetworks/hypernetwork.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 4700e1ec..5608e799 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -50,7 +50,7 @@ class Hypernetwork:
         self.sd_checkpoint = None
         self.sd_checkpoint_name = None
 
-        for size in enable_sizes or [320, 640, 768, 1280]:
+        for size in enable_sizes or []:
             self.layers[size] = (HypernetworkModule(size), HypernetworkModule(size))
 
     def weights(self):
-- 
cgit v1.2.3


From d7474a5185df2af84a93a12bc7e140d24e0fc516 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 21:10:55 +0300
Subject: bump gradio to 3.4.1

---
 requirements.txt          |  2 +-
 requirements_versions.txt |  2 +-
 style.css                 | 11 +++++++++++
 3 files changed, 13 insertions(+), 2 deletions(-)

diff --git a/requirements.txt b/requirements.txt
index 631fe616..a0d985ce 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -4,7 +4,7 @@ fairscale==0.4.4
 fonts
 font-roboto
 gfpgan
-gradio==3.4b3
+gradio==3.4.1
 invisible-watermark
 numpy
 omegaconf
diff --git a/requirements_versions.txt b/requirements_versions.txt
index fdff2687..2bbea40b 100644
--- a/requirements_versions.txt
+++ b/requirements_versions.txt
@@ -2,7 +2,7 @@ transformers==4.19.2
 diffusers==0.3.0
 basicsr==1.4.2
 gfpgan==1.3.8
-gradio==3.4b3
+gradio==3.4.1
 numpy==1.23.3
 Pillow==9.2.0
 realesrgan==0.3.0
diff --git a/style.css b/style.css
index ecb51bb0..e6fa10b4 100644
--- a/style.css
+++ b/style.css
@@ -240,6 +240,7 @@ fieldset span.text-gray-500, .gr-block.gr-box span.text-gray-500,  label.block s
 #settings fieldset span.text-gray-500, #settings .gr-block.gr-box span.text-gray-500, #settings label.block span{
     position: relative;
     border: none;
+    margin-right: 8em;
 }
 
 .gr-panel div.flex-col div.justify-between label span{
@@ -495,3 +496,13 @@ canvas[key="mask"] {
     mix-blend-mode: multiply;
     pointer-events: none;
 }
+
+
+/* gradio 3.4.1 stuff for editable scrollbar values */
+.gr-box > div > div > input.gr-text-input{
+    position: absolute;
+    right: 0.5em;
+    top: -0.6em;
+    z-index: 200;
+    width: 8em;
+}
-- 
cgit v1.2.3


From 9e5f6b558072f6cdfa0f7010fa819662952fcaf1 Mon Sep 17 00:00:00 2001
From: nai-degen <92774204+nai-degen@users.noreply.github.com>
Date: Sun, 9 Oct 2022 19:37:35 -0500
Subject: triggers 'input' event when using arrow keys to edit attention

---
 javascript/edit-attention.js | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/javascript/edit-attention.js b/javascript/edit-attention.js
index 0280c603..79566a2e 100644
--- a/javascript/edit-attention.js
+++ b/javascript/edit-attention.js
@@ -38,4 +38,7 @@ addEventListener('keydown', (event) => {
 		target.selectionStart = selectionStart;
 		target.selectionEnd = selectionEnd;
 	}
+	// Since we've modified a Gradio Textbox component manually, we need to simulate an `input` DOM event to ensure its
+	// internal Svelte data binding remains in sync.
+	target.dispatchEvent(new Event("input", { bubbles: true }));
 });
-- 
cgit v1.2.3


From c080f52ceae73b893155eff7de577aaf1a982a2f Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Tue, 11 Oct 2022 19:37:58 +0100
Subject: move embedding logic to separate file

---
 modules/textual_inversion/image_embedding.py | 234 +++++++++++++++++++++++++++
 1 file changed, 234 insertions(+)
 create mode 100644 modules/textual_inversion/image_embedding.py

diff --git a/modules/textual_inversion/image_embedding.py b/modules/textual_inversion/image_embedding.py
new file mode 100644
index 00000000..6ad39602
--- /dev/null
+++ b/modules/textual_inversion/image_embedding.py
@@ -0,0 +1,234 @@
+import base64
+import json
+import numpy as np
+import zlib
+from PIL import Image,PngImagePlugin,ImageDraw,ImageFont
+from fonts.ttf import Roboto
+import torch
+
+class EmbeddingEncoder(json.JSONEncoder):
+    def default(self, obj):
+        if isinstance(obj, torch.Tensor):
+            return {'TORCHTENSOR':obj.cpu().detach().numpy().tolist()}
+        return json.JSONEncoder.default(self, obj)
+
+class EmbeddingDecoder(json.JSONDecoder):
+    def __init__(self, *args, **kwargs):
+        json.JSONDecoder.__init__(self, object_hook=self.object_hook, *args, **kwargs)
+    def object_hook(self, d):
+        if 'TORCHTENSOR' in d:
+            return torch.from_numpy(np.array(d['TORCHTENSOR']))
+        return d
+
+def embedding_to_b64(data):
+    d = json.dumps(data,cls=EmbeddingEncoder)
+    return base64.b64encode(d.encode())
+
+def embedding_from_b64(data):
+    d = base64.b64decode(data)
+    return json.loads(d,cls=EmbeddingDecoder)
+
+def lcg(m=2**32, a=1664525, c=1013904223, seed=0):
+    while True:
+        seed = (a * seed + c) % m
+        yield seed%255
+
+def xor_block(block):
+    g = lcg()
+    randblock = np.array([next(g) for _ in range(np.product(block.shape))]).astype(np.uint8).reshape(block.shape)
+    return np.bitwise_xor(block.astype(np.uint8),randblock & 0x0F) 
+
+def style_block(block,sequence):
+    im = Image.new('RGB',(block.shape[1],block.shape[0]))
+    draw = ImageDraw.Draw(im)
+    i=0
+    for x in range(-6,im.size[0],8):
+        for yi,y in enumerate(range(-6,im.size[1],8)):
+            offset=0
+            if yi%2==0:
+                offset=4
+            shade = sequence[i%len(sequence)]
+            i+=1
+            draw.ellipse((x+offset, y, x+6+offset, y+6), fill =(shade,shade,shade) )
+
+    fg = np.array(im).astype(np.uint8) & 0xF0
+
+    return block ^ fg
+
+def insert_image_data_embed(image,data):
+    d = 3
+    data_compressed = zlib.compress( json.dumps(data,cls=EmbeddingEncoder).encode(),level=9)
+    data_np_ = np.frombuffer(data_compressed,np.uint8).copy()
+    data_np_high = data_np_ >> 4
+    data_np_low  = data_np_ & 0x0F
+    
+    h = image.size[1]
+    next_size = data_np_low.shape[0] + (h-(data_np_low.shape[0]%h))
+    next_size = next_size + ((h*d)-(next_size%(h*d)))
+
+    data_np_low.resize(next_size)
+    data_np_low = data_np_low.reshape((h,-1,d))
+
+    data_np_high.resize(next_size)
+    data_np_high = data_np_high.reshape((h,-1,d))
+
+    edge_style = list(data['string_to_param'].values())[0].cpu().detach().numpy().tolist()[0][:1024]
+    edge_style = (np.abs(edge_style)/np.max(np.abs(edge_style))*255).astype(np.uint8)
+
+    data_np_low   = style_block(data_np_low,sequence=edge_style)
+    data_np_low   = xor_block(data_np_low)    
+    data_np_high  = style_block(data_np_high,sequence=edge_style[::-1])
+    data_np_high  = xor_block(data_np_high)
+
+    im_low  = Image.fromarray(data_np_low,mode='RGB')
+    im_high = Image.fromarray(data_np_high,mode='RGB')
+
+    background = Image.new('RGB',(image.size[0]+im_low.size[0]+im_high.size[0]+2,image.size[1]),(0,0,0))
+    background.paste(im_low,(0,0))
+    background.paste(image,(im_low.size[0]+1,0))
+    background.paste(im_high,(im_low.size[0]+1+image.size[0]+1,0))
+
+    return background
+
+def crop_black(img,tol=0):
+    mask = (img>tol).all(2)
+    mask0,mask1 = mask.any(0),mask.any(1)
+    col_start,col_end = mask0.argmax(),mask.shape[1]-mask0[::-1].argmax()
+    row_start,row_end = mask1.argmax(),mask.shape[0]-mask1[::-1].argmax()
+    return img[row_start:row_end,col_start:col_end]
+
+def extract_image_data_embed(image):
+    d=3
+    outarr = crop_black(np.array(image.convert('RGB').getdata()).reshape(image.size[1],image.size[0],d ).astype(np.uint8) ) & 0x0F
+    black_cols = np.where( np.sum(outarr, axis=(0,2))==0)
+    if black_cols[0].shape[0] < 2:
+        print('No Image data blocks found.')
+        return None
+
+    data_block_lower = outarr[:,:black_cols[0].min(),:].astype(np.uint8)
+    data_block_upper = outarr[:,black_cols[0].max()+1:,:].astype(np.uint8)
+
+    data_block_lower = xor_block(data_block_lower)
+    data_block_upper = xor_block(data_block_upper)
+    
+    data_block = (data_block_upper << 4) | (data_block_lower)
+    data_block = data_block.flatten().tobytes()
+
+    data = zlib.decompress(data_block)
+    return json.loads(data,cls=EmbeddingDecoder)
+
+def addCaptionLines(lines,image,initialx,textfont):
+    draw = ImageDraw.Draw(image)
+    hstart =initialx
+    for fill,line in lines:
+        fontsize = 32
+        font = ImageFont.truetype(textfont, fontsize)
+        _,_,w, h = draw.textbbox((0,0),line,font=font)
+        fontsize =  min( int(fontsize * ((image.size[0]-35)/w) ), 28)
+        font = ImageFont.truetype(textfont, fontsize)
+        _,_,w,h = draw.textbbox((0,0),line,font=font)
+        draw.text(((image.size[0]-w)/2,hstart), line, font=font, fill=fill)
+        hstart += h
+    return hstart
+
+def caption_image(image,prelines,postlines,background=(51, 51, 51),font=None):
+    if font is None:
+        try:
+            font = ImageFont.truetype(opts.font or Roboto, fontsize)
+            font = opts.font or Roboto
+        except Exception:
+            font = Roboto
+
+    sample_image = image
+    background = Image.new("RGBA", (sample_image.size[0],sample_image.size[1]+1024), background)
+    hoffset = addCaptionLines(prelines,background,5,font)+16
+    background.paste(sample_image,(0,hoffset))
+    hoffset = hoffset+sample_image.size[1]+8
+    hoffset = addCaptionLines(postlines,background,hoffset,font)
+    background = background.crop((0,0,sample_image.size[0],hoffset+8))
+    return background
+
+def caption_image_overlay(srcimage,title,footerLeft,footerMid,footerRight,textfont=None):
+    from math import cos
+
+    image = srcimage.copy()
+
+    if textfont is None:
+        try:
+            textfont = ImageFont.truetype(opts.font or Roboto, fontsize)
+            textfont = opts.font or Roboto
+        except Exception:
+            textfont = Roboto
+
+    factor = 1.5
+    gradient = Image.new('RGBA', (1,image.size[1]), color=(0,0,0,0))
+    for y in range(image.size[1]):
+        mag = 1-cos(y/image.size[1]*factor)
+        mag = max(mag,1-cos((image.size[1]-y)/image.size[1]*factor*1.1))
+        gradient.putpixel((0, y), (0,0,0,int(mag*255)))
+    image = Image.alpha_composite(image.convert('RGBA'), gradient.resize(image.size))
+
+    draw = ImageDraw.Draw(image)
+    fontsize = 32
+    font = ImageFont.truetype(textfont, fontsize)
+    padding = 10
+
+    _,_,w, h = draw.textbbox((0,0),title,font=font)
+    fontsize =  min( int(fontsize * (((image.size[0]*0.75)-(padding*4))/w) ), 72)
+    font = ImageFont.truetype(textfont, fontsize)
+    _,_,w,h = draw.textbbox((0,0),title,font=font)
+    draw.text((padding,padding), title, anchor='lt', font=font, fill=(255,255,255,230))
+
+    _,_,w, h = draw.textbbox((0,0),footerLeft,font=font)
+    fontsize_left =  min( int(fontsize * (((image.size[0]/3)-(padding))/w) ), 72)
+    _,_,w, h = draw.textbbox((0,0),footerMid,font=font)
+    fontsize_mid =  min( int(fontsize * (((image.size[0]/3)-(padding))/w) ), 72)
+    _,_,w, h = draw.textbbox((0,0),footerRight,font=font)
+    fontsize_right =  min( int(fontsize * (((image.size[0]/3)-(padding))/w) ), 72)
+
+    font = ImageFont.truetype(textfont, min(fontsize_left,fontsize_mid,fontsize_right))
+
+    draw.text((padding,image.size[1]-padding),               footerLeft, anchor='ls', font=font, fill=(255,255,255,230))
+    draw.text((image.size[0]/2,image.size[1]-padding),       footerMid, anchor='ms', font=font, fill=(255,255,255,230))
+    draw.text((image.size[0]-padding,image.size[1]-padding), footerRight, anchor='rs', font=font, fill=(255,255,255,230))
+
+    return image
+
+if __name__ == '__main__':
+
+    image = Image.new('RGBA',(512,512),(255,255,200,255))
+    caption_image(image,[((255,255,255),'line a'),((255,255,255),'line b')],
+                        [((255,255,255),'line c'),((255,255,255),'line d')])
+
+    image = Image.new('RGBA',(512,512),(255,255,200,255))
+    cap_image = caption_image_overlay(image, 'title', 'footerLeft', 'footerMid', 'footerRight')
+
+    test_embed = {'string_to_param':{'*':torch.from_numpy(np.random.random((2, 4096)))}}
+
+    embedded_image = insert_image_data_embed(cap_image, test_embed)
+
+    retrived_embed = extract_image_data_embed(embedded_image)
+
+    assert str(retrived_embed) == str(test_embed)
+
+    embedded_image2 = insert_image_data_embed(cap_image, retrived_embed)
+
+    assert embedded_image == embedded_image2
+
+    g = lcg()
+    shared_random = np.array([next(g) for _ in range(100)]).astype(np.uint8).tolist()
+
+    reference_random = [253, 242, 127,  44, 157,  27, 239, 133,  38,  79, 167,   4, 177, 
+                         95, 130,  79,  78,  14,  52, 215, 220, 194, 126,  28, 240, 179, 
+                        160, 153, 149,  50, 105,  14,  21, 218, 199,  18,  54, 198, 193, 
+                         38, 128,  19,  53, 195, 124,  75, 205,  12,   6, 145,   0,  28, 
+                         30, 148,   8,  45, 218, 171,  55, 249,  97, 166,  12,  35,   0, 
+                         41, 221, 122, 215, 170,  31, 113, 186,  97, 119,  31,  23, 185, 
+                         66, 140,  30,  41,  37,  63, 137, 109, 216,  55, 159, 145,  82, 
+                         204, 86,  73, 222,  44, 198, 118, 240,  97]
+
+    assert shared_random == reference_random   
+
+    hunna_kay_random_sum = sum(np.array([next(g) for _ in range(100000)]).astype(np.uint8).tolist())
+
+    assert 12731374 == hunna_kay_random_sum
\ No newline at end of file
-- 
cgit v1.2.3


From e5fbf5c755b7c306696546405385d5d2314e555b Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Tue, 11 Oct 2022 19:46:33 +0100
Subject: remove embedding related image functions from images

---
 modules/images.py | 77 -------------------------------------------------------
 1 file changed, 77 deletions(-)

diff --git a/modules/images.py b/modules/images.py
index e62eec8e..c0a90676 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -463,80 +463,3 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i
         txt_fullfn = None
 
     return fullfn, txt_fullfn
-
-def addCaptionLines(lines,image,initialx,textfont):
-    draw = ImageDraw.Draw(image)
-    hstart =initialx
-    for fill,line in lines:
-        fontSize = 32
-        font = ImageFont.truetype(textfont, fontSize)
-        _,_,w, h = draw.textbbox((0,0),line,font=font)
-        fontSize =  min( int(fontSize * ((image.size[0]-35)/w) ), 28)
-        font = ImageFont.truetype(textfont, fontSize)
-        _,_,w,h = draw.textbbox((0,0),line,font=font)
-        draw.text(((image.size[0]-w)/2,hstart), line, font=font, fill=fill)
-        hstart += h
-    return hstart
-
-def captionImge(image,prelines,postlines,background=(51, 51, 51),font=None):
-    if font is None:
-        try:
-            font = ImageFont.truetype(opts.font or Roboto, fontsize)
-            font = opts.font or Roboto
-        except Exception:
-            font = Roboto
-
-    sampleImage = image
-    background = Image.new("RGBA", (sampleImage.size[0],sampleImage.size[1]+1024), background)
-    hoffset = addCaptionLines(prelines,background,5,font)+16
-    background.paste(sampleImage,(0,hoffset))
-    hoffset = hoffset+sampleImage.size[1]+8
-    hoffset = addCaptionLines(postlines,background,hoffset,font)
-    background = background.crop((0,0,sampleImage.size[0],hoffset+8))
-    return background
-
-def captionImageOverlay(srcimage,title,footerLeft,footerMid,footerRight,textfont=None):
-    from math import cos
-
-    image = srcimage.copy()
-
-    if textfont is None:
-        try:
-            textfont = ImageFont.truetype(opts.font or Roboto, fontsize)
-            textfont = opts.font or Roboto
-        except Exception:
-            textfont = Roboto
-
-    factor = 1.5
-    gradient = Image.new('RGBA', (1,image.size[1]), color=(0,0,0,0))
-    for y in range(image.size[1]):
-        mag = 1-cos(y/image.size[1]*factor)
-        mag = max(mag,1-cos((image.size[1]-y)/image.size[1]*factor*1.1))
-        gradient.putpixel((0, y), (0,0,0,int(mag*255)))
-    image = Image.alpha_composite(image.convert('RGBA'), gradient.resize(image.size))
-
-    draw = ImageDraw.Draw(image)
-    fontSize = 32
-    font = ImageFont.truetype(textfont, fontSize)
-    padding = 10
-
-    _,_,w, h = draw.textbbox((0,0),title,font=font)
-    fontSize =  min( int(fontSize * (((image.size[0]*0.75)-(padding*4))/w) ), 72)
-    font = ImageFont.truetype(textfont, fontSize)
-    _,_,w,h = draw.textbbox((0,0),title,font=font)
-    draw.text((padding,padding), title, anchor='lt', font=font, fill=(255,255,255,230))
-
-    _,_,w, h = draw.textbbox((0,0),footerLeft,font=font)
-    fontSizeleft =  min( int(fontSize * (((image.size[0]/3)-(padding))/w) ), 72)
-    _,_,w, h = draw.textbbox((0,0),footerMid,font=font)
-    fontSizemid =  min( int(fontSize * (((image.size[0]/3)-(padding))/w) ), 72)
-    _,_,w, h = draw.textbbox((0,0),footerRight,font=font)
-    fontSizeright =  min( int(fontSize * (((image.size[0]/3)-(padding))/w) ), 72)
-
-    font = ImageFont.truetype(textfont, min(fontSizeleft,fontSizemid,fontSizeright))
-
-    draw.text((padding,image.size[1]-padding),               footerLeft, anchor='ls', font=font, fill=(255,255,255,230))
-    draw.text((image.size[0]/2,image.size[1]-padding),       footerMid, anchor='ms', font=font, fill=(255,255,255,230))
-    draw.text((image.size[0]-padding,image.size[1]-padding), footerRight, anchor='rs', font=font, fill=(255,255,255,230))
-
-    return image
-- 
cgit v1.2.3


From 61788c0538415fa9ca1dd1b306519c116b18bd2c Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Tue, 11 Oct 2022 19:50:50 +0100
Subject: shift embedding logic out of textual_inversion

---
 modules/textual_inversion/textual_inversion.py | 125 ++-----------------------
 1 file changed, 6 insertions(+), 119 deletions(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 8c66aeb5..22b4ae7f 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -7,124 +7,11 @@ import tqdm
 import html
 import datetime
 
-from PIL import Image,PngImagePlugin,ImageDraw
-from ..images import captionImageOverlay
-import numpy as np
-import base64
-import json
-import zlib
+from PIL import Image,PngImagePlugin
 
 from modules import shared, devices, sd_hijack, processing, sd_models
 import modules.textual_inversion.dataset
 
-class EmbeddingEncoder(json.JSONEncoder):
-    def default(self, obj):
-        if isinstance(obj, torch.Tensor):
-            return {'TORCHTENSOR':obj.cpu().detach().numpy().tolist()}
-        return json.JSONEncoder.default(self, obj)
-
-class EmbeddingDecoder(json.JSONDecoder):
-    def __init__(self, *args, **kwargs):
-        json.JSONDecoder.__init__(self, object_hook=self.object_hook, *args, **kwargs)
-    def object_hook(self, d):
-        if 'TORCHTENSOR' in d:
-            return torch.from_numpy(np.array(d['TORCHTENSOR']))
-        return d
-
-def embeddingToB64(data):
-    d = json.dumps(data,cls=EmbeddingEncoder)
-    return base64.b64encode(d.encode())
-
-def embeddingFromB64(data):
-    d = base64.b64decode(data)
-    return json.loads(d,cls=EmbeddingDecoder)
-
-def lcg(m=2**32, a=1664525, c=1013904223, seed=0):
-    while True:
-        seed = (a * seed + c) % m
-        yield seed
-
-def xorBlock(block):
-    g = lcg()
-    randblock = np.array([next(g) for _ in range(np.product(block.shape))]).astype(np.uint8).reshape(block.shape)
-    return np.bitwise_xor(block.astype(np.uint8),randblock & 0x0F) 
-
-def styleBlock(block,sequence):
-    im = Image.new('RGB',(block.shape[1],block.shape[0]))
-    draw = ImageDraw.Draw(im)
-    i=0
-    for x in range(-6,im.size[0],8):
-        for yi,y in enumerate(range(-6,im.size[1],8)):
-            offset=0
-            if yi%2==0:
-                offset=4
-            shade = sequence[i%len(sequence)]
-            i+=1
-            draw.ellipse((x+offset, y, x+6+offset, y+6), fill =(shade,shade,shade) )
-
-    fg = np.array(im).astype(np.uint8) & 0xF0
-    return block ^ fg
-
-def insertImageDataEmbed(image,data):
-    d = 3
-    data_compressed = zlib.compress( json.dumps(data,cls=EmbeddingEncoder).encode(),level=9)
-    dnp = np.frombuffer(data_compressed,np.uint8).copy()
-    dnphigh = dnp >> 4
-    dnplow  = dnp & 0x0F
-    
-    h = image.size[1]
-    next_size = dnplow.shape[0] + (h-(dnplow.shape[0]%h))
-    next_size = next_size + ((h*d)-(next_size%(h*d)))
-
-    dnplow.resize(next_size)
-    dnplow = dnplow.reshape((h,-1,d))
-
-    dnphigh.resize(next_size)
-    dnphigh = dnphigh.reshape((h,-1,d))
-
-    edgeStyleWeights = list(data['string_to_param'].values())[0].cpu().detach().numpy().tolist()[0][:1024]
-    edgeStyleWeights = (np.abs(edgeStyleWeights)/np.max(np.abs(edgeStyleWeights))*255).astype(np.uint8)
-
-    dnplow   = styleBlock(dnplow,sequence=edgeStyleWeights)
-    dnplow   = xorBlock(dnplow)    
-    dnphigh  = styleBlock(dnphigh,sequence=edgeStyleWeights[::-1])
-    dnphigh  = xorBlock(dnphigh)
-
-    imlow  = Image.fromarray(dnplow,mode='RGB')
-    imhigh = Image.fromarray(dnphigh,mode='RGB')
-
-    background = Image.new('RGB',(image.size[0]+imlow.size[0]+imhigh.size[0]+2,image.size[1]),(0,0,0))
-    background.paste(imlow,(0,0))
-    background.paste(image,(imlow.size[0]+1,0))
-    background.paste(imhigh,(imlow.size[0]+1+image.size[0]+1,0))
-
-    return background
-
-def crop_black(img,tol=0):
-    mask = (img>tol).all(2)
-    mask0,mask1 = mask.any(0),mask.any(1)
-    col_start,col_end = mask0.argmax(),mask.shape[1]-mask0[::-1].argmax()
-    row_start,row_end = mask1.argmax(),mask.shape[0]-mask1[::-1].argmax()
-    return img[row_start:row_end,col_start:col_end]
-
-def extractImageDataEmbed(image):
-    d=3
-    outarr = crop_black(np.array(image.convert('RGB').getdata()).reshape(image.size[1],image.size[0],d ).astype(np.uint8) ) & 0x0F
-    blackCols = np.where( np.sum(outarr, axis=(0,2))==0)
-    if blackCols[0].shape[0] < 2:
-        print('No Image data blocks found.')
-        return None
-
-    dataBlocklower = outarr[:,:blackCols[0].min(),:].astype(np.uint8)
-    dataBlockupper = outarr[:,blackCols[0].max()+1:,:].astype(np.uint8)
-
-    dataBlocklower = xorBlock(dataBlocklower)
-    dataBlockupper = xorBlock(dataBlockupper)
-    
-    dataBlock = (dataBlockupper << 4) | (dataBlocklower)
-    dataBlock = dataBlock.flatten().tobytes()   
-    data = zlib.decompress(dataBlock)
-    return json.loads(data,cls=EmbeddingDecoder)
 
 class Embedding:
     def __init__(self, vec, name, step=None):
@@ -199,10 +86,10 @@ class EmbeddingDatabase:
             if filename.upper().endswith('.PNG'):
                 embed_image = Image.open(path)
                 if 'sd-ti-embedding' in embed_image.text:
-                    data = embeddingFromB64(embed_image.text['sd-ti-embedding'])
+                    data = embedding_from_b64(embed_image.text['sd-ti-embedding'])
                     name = data.get('name',name)
                 else:
-                    data = extractImageDataEmbed(embed_image)
+                    data = extract_image_data_embed(embed_image)
                     name = data.get('name',name)
             else:
                 data = torch.load(path, map_location="cpu")
@@ -393,7 +280,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
 
                 info = PngImagePlugin.PngInfo()
                 data = torch.load(last_saved_file)
-                info.add_text("sd-ti-embedding", embeddingToB64(data))
+                info.add_text("sd-ti-embedding", embedding_to_b64(data))
 
                 title = "<{}>".format(data.get('name','???'))
                 checkpoint = sd_models.select_checkpoint()
@@ -401,8 +288,8 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
                 footer_mid = '[{}]'.format(checkpoint.hash)
                 footer_right = '{}'.format(embedding.step)
 
-                captioned_image = captionImageOverlay(image,title,footer_left,footer_mid,footer_right)
-                captioned_image = insertImageDataEmbed(captioned_image,data)
+                captioned_image = caption_image_overlay(image,title,footer_left,footer_mid,footer_right)
+                captioned_image = insert_image_data_embed(captioned_image,data)
 
                 captioned_image.save(last_saved_image_chunks, "PNG", pnginfo=info)
             
-- 
cgit v1.2.3


From db71290d2659d3b58ff9b57a82e4721a9eab9229 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Tue, 11 Oct 2022 19:55:54 +0100
Subject: remove old caption method

---
 modules/textual_inversion/image_embedding.py | 39 ++--------------------------
 1 file changed, 2 insertions(+), 37 deletions(-)

diff --git a/modules/textual_inversion/image_embedding.py b/modules/textual_inversion/image_embedding.py
index 6ad39602..c67028a5 100644
--- a/modules/textual_inversion/image_embedding.py
+++ b/modules/textual_inversion/image_embedding.py
@@ -117,37 +117,6 @@ def extract_image_data_embed(image):
     data = zlib.decompress(data_block)
     return json.loads(data,cls=EmbeddingDecoder)
 
-def addCaptionLines(lines,image,initialx,textfont):
-    draw = ImageDraw.Draw(image)
-    hstart =initialx
-    for fill,line in lines:
-        fontsize = 32
-        font = ImageFont.truetype(textfont, fontsize)
-        _,_,w, h = draw.textbbox((0,0),line,font=font)
-        fontsize =  min( int(fontsize * ((image.size[0]-35)/w) ), 28)
-        font = ImageFont.truetype(textfont, fontsize)
-        _,_,w,h = draw.textbbox((0,0),line,font=font)
-        draw.text(((image.size[0]-w)/2,hstart), line, font=font, fill=fill)
-        hstart += h
-    return hstart
-
-def caption_image(image,prelines,postlines,background=(51, 51, 51),font=None):
-    if font is None:
-        try:
-            font = ImageFont.truetype(opts.font or Roboto, fontsize)
-            font = opts.font or Roboto
-        except Exception:
-            font = Roboto
-
-    sample_image = image
-    background = Image.new("RGBA", (sample_image.size[0],sample_image.size[1]+1024), background)
-    hoffset = addCaptionLines(prelines,background,5,font)+16
-    background.paste(sample_image,(0,hoffset))
-    hoffset = hoffset+sample_image.size[1]+8
-    hoffset = addCaptionLines(postlines,background,hoffset,font)
-    background = background.crop((0,0,sample_image.size[0],hoffset+8))
-    return background
-
 def caption_image_overlay(srcimage,title,footerLeft,footerMid,footerRight,textfont=None):
     from math import cos
 
@@ -195,11 +164,7 @@ def caption_image_overlay(srcimage,title,footerLeft,footerMid,footerRight,textfo
     return image
 
 if __name__ == '__main__':
-
-    image = Image.new('RGBA',(512,512),(255,255,200,255))
-    caption_image(image,[((255,255,255),'line a'),((255,255,255),'line b')],
-                        [((255,255,255),'line c'),((255,255,255),'line d')])
-
+    
     image = Image.new('RGBA',(512,512),(255,255,200,255))
     cap_image = caption_image_overlay(image, 'title', 'footerLeft', 'footerMid', 'footerRight')
 
@@ -231,4 +196,4 @@ if __name__ == '__main__':
 
     hunna_kay_random_sum = sum(np.array([next(g) for _ in range(100000)]).astype(np.uint8).tolist())
 
-    assert 12731374 == hunna_kay_random_sum
\ No newline at end of file
+    assert 12731374 == hunna_kay_random_sum
-- 
cgit v1.2.3


From d6fcc6b87bc00fcdecea276fe5b7c7945f7a8b14 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 22:03:05 +0300
Subject: apply lr schedule to hypernets

---
 modules/hypernetworks/hypernetwork.py          | 19 ++++++++---
 modules/textual_inversion/learn_schedule.py    | 34 ++++++++++++++++++++
 modules/textual_inversion/textual_inversion.py | 44 +++-----------------------
 modules/ui.py                                  |  2 +-
 4 files changed, 54 insertions(+), 45 deletions(-)
 create mode 100644 modules/textual_inversion/learn_schedule.py

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 5608e799..470659df 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -14,6 +14,7 @@ import torch
 from torch import einsum
 from einops import rearrange, repeat
 import modules.textual_inversion.dataset
+from modules.textual_inversion.learn_schedule import LearnSchedule
 
 
 class HypernetworkModule(torch.nn.Module):
@@ -202,8 +203,6 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
     for weight in weights:
         weight.requires_grad = True
 
-    optimizer = torch.optim.AdamW(weights, lr=learn_rate)
-
     losses = torch.zeros((32,))
 
     last_saved_file = "<none>"
@@ -213,12 +212,24 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
     if ititial_step > steps:
         return hypernetwork, filename
 
+    schedules = iter(LearnSchedule(learn_rate, steps, ititial_step))
+    (learn_rate, end_step) = next(schedules)
+    print(f'Training at rate of {learn_rate} until step {end_step}')
+
+    optimizer = torch.optim.AdamW(weights, lr=learn_rate)
+
     pbar = tqdm.tqdm(enumerate(ds), total=steps - ititial_step)
     for i, (x, text, cond) in pbar:
         hypernetwork.step = i + ititial_step
 
-        if hypernetwork.step > steps:
-            break
+        if hypernetwork.step > end_step:
+            try:
+                (learn_rate, end_step) = next(schedules)
+            except Exception:
+                break
+            tqdm.tqdm.write(f'Training at rate of {learn_rate} until step {end_step}')
+            for pg in optimizer.param_groups:
+                pg['lr'] = learn_rate
 
         if shared.state.interrupted:
             break
diff --git a/modules/textual_inversion/learn_schedule.py b/modules/textual_inversion/learn_schedule.py
new file mode 100644
index 00000000..db720271
--- /dev/null
+++ b/modules/textual_inversion/learn_schedule.py
@@ -0,0 +1,34 @@
+
+class LearnSchedule:
+    def __init__(self, learn_rate, max_steps, cur_step=0):
+        pairs = learn_rate.split(',')
+        self.rates = []
+        self.it = 0
+        self.maxit = 0
+        for i, pair in enumerate(pairs):
+            tmp = pair.split(':')
+            if len(tmp) == 2:
+                step = int(tmp[1])
+                if step > cur_step:
+                    self.rates.append((float(tmp[0]), min(step, max_steps)))
+                    self.maxit += 1
+                    if step > max_steps:
+                        return
+                elif step == -1:
+                    self.rates.append((float(tmp[0]), max_steps))
+                    self.maxit += 1
+                    return
+            else:
+                self.rates.append((float(tmp[0]), max_steps))
+                self.maxit += 1
+                return
+
+    def __iter__(self):
+        return self
+
+    def __next__(self):
+        if self.it < self.maxit:
+            self.it += 1
+            return self.rates[self.it - 1]
+        else:
+            raise StopIteration
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 47a27faf..7717837d 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -10,6 +10,7 @@ import datetime
 
 from modules import shared, devices, sd_hijack, processing, sd_models
 import modules.textual_inversion.dataset
+from modules.textual_inversion.learn_schedule import LearnSchedule
 
 
 class Embedding:
@@ -198,11 +199,8 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
     if ititial_step > steps:
         return embedding, filename
 
-    tr_img_len = len([os.path.join(data_root, file_path) for file_path in os.listdir(data_root)])
-    epoch_len = (tr_img_len * num_repeats) + tr_img_len
-
-    scheduleIter = iter(LearnSchedule(learn_rate, steps, ititial_step))
-    (learn_rate, end_step) = next(scheduleIter)
+    schedules = iter(LearnSchedule(learn_rate, steps, ititial_step))
+    (learn_rate, end_step) = next(schedules)
     print(f'Training at rate of {learn_rate} until step {end_step}')
 
     optimizer = torch.optim.AdamW([embedding.vec], lr=learn_rate)
@@ -213,7 +211,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
 
         if embedding.step > end_step:
             try:
-                (learn_rate, end_step) = next(scheduleIter)
+                (learn_rate, end_step) = next(schedules)
             except:
                 break
             tqdm.tqdm.write(f'Training at rate of {learn_rate} until step {end_step}')
@@ -288,37 +286,3 @@ Last saved image: {html.escape(last_saved_image)}<br/>
     embedding.save(filename)
 
     return embedding, filename
-
-class LearnSchedule:
-    def __init__(self, learn_rate, max_steps, cur_step=0):
-        pairs = learn_rate.split(',')
-        self.rates = []
-        self.it = 0
-        self.maxit = 0
-        for i, pair in enumerate(pairs):
-            tmp = pair.split(':')
-            if len(tmp) == 2:
-                step = int(tmp[1])
-                if step > cur_step:
-                    self.rates.append((float(tmp[0]), min(step, max_steps)))
-                    self.maxit += 1
-                    if step > max_steps:
-                        return
-                elif step == -1:
-                    self.rates.append((float(tmp[0]), max_steps))
-                    self.maxit += 1
-                    return
-            else:
-                self.rates.append((float(tmp[0]), max_steps))
-                self.maxit += 1
-                return
-
-    def __iter__(self):
-        return self
-
-    def __next__(self):
-        if self.it < self.maxit:
-            self.it += 1
-            return self.rates[self.it - 1]
-        else:
-            raise StopIteration
diff --git a/modules/ui.py b/modules/ui.py
index 2b688e32..1204eef7 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1070,7 +1070,7 @@ def create_ui(wrap_gradio_gpu_call):
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding; must specify a directory with a set of 1:1 ratio images</p>")
                     train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
                     train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', choices=[x for x in shared.hypernetworks.keys()])
-                    learn_rate = gr.Textbox(label='Learning rate', placeholder="Learning rate", value = "5.0e-03")
+                    learn_rate = gr.Textbox(label='Learning rate', placeholder="Learning rate", value="0.005")
                     dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images")
                     log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")
                     template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"))
-- 
cgit v1.2.3


From aa75d5cfe8c84768b0f5d16f977ddba298677379 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Tue, 11 Oct 2022 20:06:13 +0100
Subject: correct conflict resolution typo

---
 modules/textual_inversion/textual_inversion.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 22b4ae7f..789383ce 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -169,7 +169,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'):
 
 
 
-def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, num_repeats, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_image_prompt)
+def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, num_repeats, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_image_prompt):
     assert embedding_name, 'embedding not selected'
 
     shared.state.textinfo = "Initializing textual inversion training..."
-- 
cgit v1.2.3


From 91d7ee0d097a7ea203d261b570cd2b834837d9e2 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Tue, 11 Oct 2022 20:09:10 +0100
Subject: update imports

---
 modules/textual_inversion/textual_inversion.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 789383ce..ff0a62b3 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -12,6 +12,9 @@ from PIL import Image,PngImagePlugin
 from modules import shared, devices, sd_hijack, processing, sd_models
 import modules.textual_inversion.dataset
 
+from modules.textual_inversion.image_embedding import( embedding_to_b64,embedding_from_b64,
+                                                       insert_image_data_embed,extract_image_data_embed,
+                                                       caption_image_overlay )
 
 class Embedding:
     def __init__(self, vec, name, step=None):
-- 
cgit v1.2.3


From 5f3317376bb7952bc5145f05f16c1bbd466efc85 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Tue, 11 Oct 2022 20:09:49 +0100
Subject: spacing

---
 modules/textual_inversion/textual_inversion.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index ff0a62b3..485ef46c 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -12,7 +12,7 @@ from PIL import Image,PngImagePlugin
 from modules import shared, devices, sd_hijack, processing, sd_models
 import modules.textual_inversion.dataset
 
-from modules.textual_inversion.image_embedding import( embedding_to_b64,embedding_from_b64,
+from modules.textual_inversion.image_embedding import (embedding_to_b64,embedding_from_b64,
                                                        insert_image_data_embed,extract_image_data_embed,
                                                        caption_image_overlay )
 
-- 
cgit v1.2.3


From 7e6a6e00ad6f3b7ef43c8120db9ecac6e8d6bea5 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Tue, 11 Oct 2022 20:20:46 +0100
Subject: Add files via upload

---
 modules/textual_inversion/test_embedding.png | Bin 0 -> 489220 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)
 create mode 100644 modules/textual_inversion/test_embedding.png

diff --git a/modules/textual_inversion/test_embedding.png b/modules/textual_inversion/test_embedding.png
new file mode 100644
index 00000000..07e2d9af
Binary files /dev/null and b/modules/textual_inversion/test_embedding.png differ
-- 
cgit v1.2.3


From 66ec505975aaa305a217fc27281ce368cbaef281 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Tue, 11 Oct 2022 20:21:30 +0100
Subject: add file based test

---
 modules/textual_inversion/image_embedding.py | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/modules/textual_inversion/image_embedding.py b/modules/textual_inversion/image_embedding.py
index c67028a5..1224fb42 100644
--- a/modules/textual_inversion/image_embedding.py
+++ b/modules/textual_inversion/image_embedding.py
@@ -164,6 +164,14 @@ def caption_image_overlay(srcimage,title,footerLeft,footerMid,footerRight,textfo
     return image
 
 if __name__ == '__main__':
+
+    testEmbed = Image.open('test_embedding.png')
+    
+    data = extract_image_data_embed(testEmbed)
+    assert data is not None
+
+    data = embedding_from_b64(testEmbed.text['sd-ti-embedding'])
+    assert data is not None
     
     image = Image.new('RGBA',(512,512),(255,255,200,255))
     cap_image = caption_image_overlay(image, 'title', 'footerLeft', 'footerMid', 'footerRight')
-- 
cgit v1.2.3


From 6be32b31d181e42c639dad3451229aa7b9cfd1cf Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 23:07:09 +0300
Subject: reports that training with medvram is possible.

---
 modules/hypernetworks/ui.py     | 2 +-
 modules/textual_inversion/ui.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py
index c67facbb..dfa599af 100644
--- a/modules/hypernetworks/ui.py
+++ b/modules/hypernetworks/ui.py
@@ -25,7 +25,7 @@ def train_hypernetwork(*args):
 
     initial_hypernetwork = shared.loaded_hypernetwork
 
-    assert not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram, 'Training models with lowvram or medvram is not possible'
+    assert not shared.cmd_opts.lowvram, 'Training models with lowvram is not possible'
 
     try:
         sd_hijack.undo_optimizations()
diff --git a/modules/textual_inversion/ui.py b/modules/textual_inversion/ui.py
index 70f47343..36881e7a 100644
--- a/modules/textual_inversion/ui.py
+++ b/modules/textual_inversion/ui.py
@@ -23,7 +23,7 @@ def preprocess(*args):
 
 def train_embedding(*args):
 
-    assert not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram, 'Training models with lowvram or medvram is not possible'
+    assert not shared.cmd_opts.lowvram, 'Training models with lowvram not possible'
 
     try:
         sd_hijack.undo_optimizations()
-- 
cgit v1.2.3


From f53f703aebc801c4204182d52bb1e0bef9808e1f Mon Sep 17 00:00:00 2001
From: JC_Array <justin318@att.net>
Date: Tue, 11 Oct 2022 18:12:12 -0500
Subject: resolved conflicts, moved settings under interrogate section,
 settings only show if deepbooru flag is enabled

---
 modules/deepbooru.py                    |  2 +-
 modules/shared.py                       | 19 +++++++++----------
 modules/textual_inversion/preprocess.py |  2 +-
 modules/ui.py                           |  2 +-
 4 files changed, 12 insertions(+), 13 deletions(-)

diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index 89dcac3c..29529949 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -8,7 +8,7 @@ def get_deepbooru_tags(pil_image):
     This method is for running only one image at a time for simple use.  Used to the img2img interrogate.
     """
     from modules import shared  # prevents circular reference
-    create_deepbooru_process(shared.opts.deepbooru_threshold, shared.opts.deepbooru_sort_alpha)
+    create_deepbooru_process(shared.opts.interrogate_deepbooru_score_threshold, shared.opts.deepbooru_sort_alpha)
     shared.deepbooru_process_return["value"] = -1
     shared.deepbooru_process_queue.put(pil_image)
     while shared.deepbooru_process_return["value"] == -1:
diff --git a/modules/shared.py b/modules/shared.py
index 817203f8..5456c477 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -248,15 +248,20 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}),
 }))
 
-options_templates.update(options_section(('interrogate', "Interrogate Options"), {
+interrogate_option_dictionary = {
     "interrogate_keep_models_in_memory": OptionInfo(False, "Interrogate: keep models in VRAM"),
     "interrogate_use_builtin_artists": OptionInfo(True, "Interrogate: use artists from artists.csv"),
     "interrogate_clip_num_beams": OptionInfo(1, "Interrogate: num_beams for BLIP", gr.Slider, {"minimum": 1, "maximum": 16, "step": 1}),
     "interrogate_clip_min_length": OptionInfo(24, "Interrogate: minimum description length (excluding artists, etc..)", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}),
     "interrogate_clip_max_length": OptionInfo(48, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}),
-    "interrogate_clip_dict_limit": OptionInfo(1500, "Interrogate: maximum number of lines in text file (0 = No limit)"),
-    "interrogate_deepbooru_score_threshold": OptionInfo(0.5, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
-}))
+    "interrogate_clip_dict_limit": OptionInfo(1500, "Interrogate: maximum number of lines in text file (0 = No limit)")
+}
+
+if cmd_opts.deepdanbooru:
+    interrogate_option_dictionary["interrogate_deepbooru_score_threshold"] = OptionInfo(0.5, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01})
+    interrogate_option_dictionary["deepbooru_sort_alpha"] = OptionInfo(True, "Interrogate: deepbooru sort alphabetically", gr.Checkbox)
+
+options_templates.update(options_section(('interrogate', "Interrogate Options"), interrogate_option_dictionary))
 
 options_templates.update(options_section(('ui', "User interface"), {
     "show_progressbar": OptionInfo(True, "Show progressbar"),
@@ -282,12 +287,6 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters"
     'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}),
 }))
 
-if cmd_opts.deepdanbooru:
-    options_templates.update(options_section(('deepbooru-params', "DeepBooru parameters"), {
-        "deepbooru_sort_alpha": OptionInfo(True, "Sort Alphabetical", gr.Checkbox),
-        'deepbooru_threshold': OptionInfo(0.5, "Threshold", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
-    }))
-
 
 class Options:
     data = None
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index a96388d6..113cecf1 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -29,7 +29,7 @@ def preprocess(process_src, process_dst, process_width, process_height, process_
         shared.interrogator.load()
 
     if process_caption_deepbooru:
-        deepbooru.create_deepbooru_process(opts.deepbooru_threshold, opts.deepbooru_sort_alpha)
+        deepbooru.create_deepbooru_process(opts.interrogate_deepbooru_score_threshold, opts.deepbooru_sort_alpha)
 
     def save_pic_with_caption(image, index):
         if process_caption:
diff --git a/modules/ui.py b/modules/ui.py
index 2891fc8c..fa45edca 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -317,7 +317,7 @@ def interrogate(image):
 
 
 def interrogate_deepbooru(image):
-    prompt = get_deepbooru_tags(image, opts.interrogate_deepbooru_score_threshold)
+    prompt = get_deepbooru_tags(image)
     return gr_show(True) if prompt is None else prompt
 
 
-- 
cgit v1.2.3


From 6d408c06c634cc96480f055941754dcc43f781d9 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Wed, 12 Oct 2022 00:19:28 +0100
Subject: Prevent nans from failed float parsing from overwriting weights

---
 javascript/edit-attention.js | 1 +
 1 file changed, 1 insertion(+)

diff --git a/javascript/edit-attention.js b/javascript/edit-attention.js
index 79566a2e..3f1d2fbb 100644
--- a/javascript/edit-attention.js
+++ b/javascript/edit-attention.js
@@ -25,6 +25,7 @@ addEventListener('keydown', (event) => {
 	} else {
 		end = target.value.slice(selectionEnd + 1).indexOf(")") + 1;
 		weight = parseFloat(target.value.slice(selectionEnd + 1, selectionEnd + 1 + end));
+		if (isNaN(weight)) return;
 		if (event.key == minus) weight -= 0.1;
 		if (event.key == plus) weight += 0.1;
 
-- 
cgit v1.2.3


From 65b973ac4e547a325f30a05f852b161421af2041 Mon Sep 17 00:00:00 2001
From: supersteve3d <39339941+supersteve3d@users.noreply.github.com>
Date: Wed, 12 Oct 2022 08:21:52 +0800
Subject: Update shared.py

Correct typo to "Unload VAE and CLIP from VRAM when training" in settings tab.
---
 modules/shared.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/shared.py b/modules/shared.py
index c1092ff7..46bc740c 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -229,7 +229,7 @@ options_templates.update(options_section(('system', "System"), {
 }))
 
 options_templates.update(options_section(('training', "Training"), {
-    "unload_models_when_training": OptionInfo(False, "Unload VAE and CLIP form VRAM when training"),
+    "unload_models_when_training": OptionInfo(False, "Unload VAE and CLIP from VRAM when training"),
 }))
 
 options_templates.update(options_section(('sd', "Stable Diffusion"), {
-- 
cgit v1.2.3


From d717eb079cd6b7fa7a4f97c0a10d400bdec753fb Mon Sep 17 00:00:00 2001
From: Greg Fuller <gfuller23@gmail.com>
Date: Tue, 11 Oct 2022 18:02:41 -0700
Subject: Interrogate: add option to include ranks in output

Since the UI also allows users to specify ranks, it can be useful to show people what ranks are being returned by interrogate

This can also give much better results when feeding the interrogate results back into either img2img or txt2img, especially when trying to generate a specific character or scene for which you have a similar concept image

Testing Steps:

Launch Webui with command line arg: --deepdanbooru
Navigate to img2img tab, use interrogate DeepBooru, verify tags appears as before. Use "Interrogate CLIP", verify prompt appears as before
Navigate to Settings tab, enable new option, click "apply settings"
Navigate to img2img, Interrogate DeepBooru again, verify that weights appear and are properly formatted. Note that "Interrogate CLIP" prompt is still unchanged
In my testing, this change has no effect to "Interrogate CLIP", as it seems to generate a sentence-structured caption, and not a set of tags.

(reproduce changes from https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/2149/commits/6ed4faac46c45ca7353f228aca9b436bbaba7bc7)
---
 modules/deepbooru.py   | 14 +++++++++-----
 modules/interrogate.py |  7 +++++--
 modules/shared.py      |  1 +
 modules/ui.py          |  5 ++---
 4 files changed, 17 insertions(+), 10 deletions(-)

diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index 7e3c0618..32d741e2 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -3,7 +3,7 @@ from concurrent.futures import ProcessPoolExecutor
 from multiprocessing import get_context
 
 
-def _load_tf_and_return_tags(pil_image, threshold):
+def _load_tf_and_return_tags(pil_image, threshold, include_ranks):
     import deepdanbooru as dd
     import tensorflow as tf
     import numpy as np
@@ -52,12 +52,16 @@ def _load_tf_and_return_tags(pil_image, threshold):
         if result_dict[tag] >= threshold:
             if tag.startswith("rating:"):
                 continue
-            result_tags_out.append(tag)
+            tag_formatted = tag.replace('_', ' ').replace(':', ' ')
+            if include_ranks:
+                result_tags_out.append(f'({tag_formatted}:{result_dict[tag]})')
+            else:
+                result_tags_out.append(tag_formatted)
             result_tags_print.append(f'{result_dict[tag]} {tag}')
 
     print('\n'.join(sorted(result_tags_print, reverse=True)))
 
-    return ', '.join(result_tags_out).replace('_', ' ').replace(':', ' ')
+    return ', '.join(result_tags_out)
 
 
 def subprocess_init_no_cuda():
@@ -65,9 +69,9 @@ def subprocess_init_no_cuda():
     os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
 
 
-def get_deepbooru_tags(pil_image, threshold=0.5):
+def get_deepbooru_tags(pil_image, threshold=0.5, include_ranks=False):
     context = get_context('spawn')
     with ProcessPoolExecutor(initializer=subprocess_init_no_cuda, mp_context=context) as executor:
-        f = executor.submit(_load_tf_and_return_tags, pil_image, threshold, )
+        f = executor.submit(_load_tf_and_return_tags, pil_image, threshold, include_ranks)
         ret = f.result()  # will rethrow any exceptions
     return ret
\ No newline at end of file
diff --git a/modules/interrogate.py b/modules/interrogate.py
index 635e266e..af858cc0 100644
--- a/modules/interrogate.py
+++ b/modules/interrogate.py
@@ -123,7 +123,7 @@ class InterrogateModels:
 
         return caption[0]
 
-    def interrogate(self, pil_image):
+    def interrogate(self, pil_image, include_ranks=False):
         res = None
 
         try:
@@ -156,7 +156,10 @@ class InterrogateModels:
                 for name, topn, items in self.categories:
                     matches = self.rank(image_features, items, top_count=topn)
                     for match, score in matches:
-                        res += ", " + match
+                        if include_ranks:
+                            res += ", " + match
+                        else:
+                            res += f", ({match}:{score})"
 
         except Exception:
             print(f"Error interrogating", file=sys.stderr)
diff --git a/modules/shared.py b/modules/shared.py
index c1092ff7..3e0bfd72 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -251,6 +251,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
 options_templates.update(options_section(('interrogate', "Interrogate Options"), {
     "interrogate_keep_models_in_memory": OptionInfo(False, "Interrogate: keep models in VRAM"),
     "interrogate_use_builtin_artists": OptionInfo(True, "Interrogate: use artists from artists.csv"),
+    "interrogate_return_ranks": OptionInfo(False, "Interrogate: include ranks of model tags matches in results (Has no effect on caption-based interrogators)."),
     "interrogate_clip_num_beams": OptionInfo(1, "Interrogate: num_beams for BLIP", gr.Slider, {"minimum": 1, "maximum": 16, "step": 1}),
     "interrogate_clip_min_length": OptionInfo(24, "Interrogate: minimum description length (excluding artists, etc..)", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}),
     "interrogate_clip_max_length": OptionInfo(48, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}),
diff --git a/modules/ui.py b/modules/ui.py
index 1204eef7..f4dbe247 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -311,13 +311,12 @@ def apply_styles(prompt, prompt_neg, style1_name, style2_name):
 
 
 def interrogate(image):
-    prompt = shared.interrogator.interrogate(image)
-
+    prompt = shared.interrogator.interrogate(image, include_ranks=opts.interrogate_return_ranks)
     return gr_show(True) if prompt is None else prompt
 
 
 def interrogate_deepbooru(image):
-    prompt = get_deepbooru_tags(image, opts.interrogate_deepbooru_score_threshold)
+    prompt = get_deepbooru_tags(image, opts.interrogate_deepbooru_score_threshold, opts.interrogate_return_ranks)
     return gr_show(True) if prompt is None else prompt
 
 
-- 
cgit v1.2.3


From 6ac2ec2b78bc5fabd09cb866dd9a71061d669269 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 12 Oct 2022 07:01:20 +0300
Subject: create dir for hypernetworks

---
 modules/shared.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/modules/shared.py b/modules/shared.py
index c1092ff7..e65e77f8 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -86,6 +86,7 @@ parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram
 xformers_available = False
 config_filename = cmd_opts.ui_settings_file
 
+os.makedirs(cmd_opts.hypernetwork_dir, exist_ok=True)
 hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir)
 loaded_hypernetwork = None
 
-- 
cgit v1.2.3


From fec2221eeaafb50afd26ba3e109bf6f928011e69 Mon Sep 17 00:00:00 2001
From: Greg Fuller <gfuller23@gmail.com>
Date: Tue, 11 Oct 2022 19:29:38 -0700
Subject: Truncate error text to fix service lockup / stall

What:
* Update wrap_gradio_call to add a limit to the maximum amount of text output

Why:
* wrap_gradio_call currently prints out a list of the arguments provided to the failing function.
   * if that function is save_image, this causes the entire image to be printed to stderr
    * If the image is large, this can cause the service to lock up while attempting to print all the text
 * It is easy to generate large images using the x/y plot script
 * it is easy to encounter image save exceptions, including if the output directory does not exist / cannot be written to, or if the file is too big
  * The huge amount of log spam is confusing and not particularly helpful
---
 modules/ui.py | 9 ++++++++-
 1 file changed, 8 insertions(+), 1 deletion(-)

diff --git a/modules/ui.py b/modules/ui.py
index 1204eef7..33a49d3b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -181,8 +181,15 @@ def wrap_gradio_call(func, extra_outputs=None):
         try:
             res = list(func(*args, **kwargs))
         except Exception as e:
+            # When printing out our debug argument list, do not print out more than a MB of text
+            max_debug_str_len = 131072 # (1024*1024)/8
+
             print("Error completing request", file=sys.stderr)
-            print("Arguments:", args, kwargs, file=sys.stderr)
+            argStr = f"Arguments: {str(args)} {str(kwargs)}"
+            print(argStr[:max_debug_str_len], file=sys.stderr)
+            if len(argStr) > max_debug_str_len:
+                print(f"(Argument list truncated at {max_debug_str_len}/{len(argStr)} characters)", file=sys.stderr)
+
             print(traceback.format_exc(), file=sys.stderr)
 
             shared.state.job = ""
-- 
cgit v1.2.3


From 336bd8703c7b4d71f2f096f303599925a30b8167 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 12 Oct 2022 09:00:07 +0300
Subject: just add the deepdanbooru settings unconditionally

---
 modules/shared.py | 13 ++++---------
 1 file changed, 4 insertions(+), 9 deletions(-)

diff --git a/modules/shared.py b/modules/shared.py
index f150e024..42e99741 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -249,20 +249,15 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}),
 }))
 
-interrogate_option_dictionary = {
+options_templates.update(options_section(('interrogate', "Interrogate Options"), {
     "interrogate_keep_models_in_memory": OptionInfo(False, "Interrogate: keep models in VRAM"),
     "interrogate_use_builtin_artists": OptionInfo(True, "Interrogate: use artists from artists.csv"),
     "interrogate_clip_num_beams": OptionInfo(1, "Interrogate: num_beams for BLIP", gr.Slider, {"minimum": 1, "maximum": 16, "step": 1}),
     "interrogate_clip_min_length": OptionInfo(24, "Interrogate: minimum description length (excluding artists, etc..)", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}),
     "interrogate_clip_max_length": OptionInfo(48, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}),
-    "interrogate_clip_dict_limit": OptionInfo(1500, "Interrogate: maximum number of lines in text file (0 = No limit)")
-}
-
-if cmd_opts.deepdanbooru:
-    interrogate_option_dictionary["interrogate_deepbooru_score_threshold"] = OptionInfo(0.5, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01})
-    interrogate_option_dictionary["deepbooru_sort_alpha"] = OptionInfo(True, "Interrogate: deepbooru sort alphabetically", gr.Checkbox)
-
-options_templates.update(options_section(('interrogate', "Interrogate Options"), interrogate_option_dictionary))
+    "interrogate_deepbooru_score_threshold": OptionInfo(0.5, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
+    "deepbooru_sort_alpha": OptionInfo(True, "Interrogate: deepbooru sort alphabetically"),
+}))
 
 options_templates.update(options_section(('ui', "User interface"), {
     "show_progressbar": OptionInfo(True, "Show progressbar"),
-- 
cgit v1.2.3


From fd07b103aeb70a80e3641068e483475e32c9750c Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 12 Oct 2022 09:00:39 +0300
Subject: prevent SD model from loading when running in deepdanbooru process

---
 webui.py | 26 ++++++++++++++------------
 1 file changed, 14 insertions(+), 12 deletions(-)

diff --git a/webui.py b/webui.py
index ca278e94..32bcdb06 100644
--- a/webui.py
+++ b/webui.py
@@ -31,12 +31,7 @@ from modules.paths import script_path
 from modules.shared import cmd_opts
 import modules.hypernetworks.hypernetwork
 
-modelloader.cleanup_models()
-modules.sd_models.setup_model()
-codeformer.setup_model(cmd_opts.codeformer_models_path)
-gfpgan.setup_model(cmd_opts.gfpgan_models_path)
-shared.face_restorers.append(modules.face_restoration.FaceRestoration())
-modelloader.load_upscalers()
+
 queue_lock = threading.Lock()
 
 
@@ -78,12 +73,19 @@ def wrap_gradio_gpu_call(func, extra_outputs=None):
     return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs)
 
 
-modules.scripts.load_scripts(os.path.join(script_path, "scripts"))
+def initialize():
+    modelloader.cleanup_models()
+    modules.sd_models.setup_model()
+    codeformer.setup_model(cmd_opts.codeformer_models_path)
+    gfpgan.setup_model(cmd_opts.gfpgan_models_path)
+    shared.face_restorers.append(modules.face_restoration.FaceRestoration())
+    modelloader.load_upscalers()
 
-shared.sd_model = modules.sd_models.load_model()
-shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model)))
+    modules.scripts.load_scripts(os.path.join(script_path, "scripts"))
 
-shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetworks.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)))
+    shared.sd_model = modules.sd_models.load_model()
+    shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model)))
+    shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetworks.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)))
 
 
 def webui():
@@ -98,7 +100,7 @@ def webui():
 
         demo = modules.ui.create_ui(wrap_gradio_gpu_call=wrap_gradio_gpu_call)
         
-        app,local_url,share_url = demo.launch(
+        app, local_url, share_url = demo.launch(
             share=cmd_opts.share,
             server_name="0.0.0.0" if cmd_opts.listen else None,
             server_port=cmd_opts.port,
@@ -129,6 +131,6 @@ def webui():
         print('Restarting Gradio')
 
 
-
 if __name__ == "__main__":
+    initialize()
     webui()
-- 
cgit v1.2.3


From 7edd58d90dd08f68fab5ff84d26dedd0eb85cae3 Mon Sep 17 00:00:00 2001
From: James Noeckel <jamesn8@cs.washington.edu>
Date: Tue, 11 Oct 2022 17:48:24 -0700
Subject: update environment-wsl2.yaml

---
 environment-wsl2.yaml | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/environment-wsl2.yaml b/environment-wsl2.yaml
index c9ce11df..f8872750 100644
--- a/environment-wsl2.yaml
+++ b/environment-wsl2.yaml
@@ -3,9 +3,9 @@ channels:
   - pytorch
   - defaults
 dependencies:
-  - python=3.8.5
-  - pip=20.3
+  - python=3.10
+  - pip=22.2.2
   - cudatoolkit=11.3
-  - pytorch=1.11.0
-  - torchvision=0.12.0
-  - numpy=1.19.2
+  - pytorch=1.12.1
+  - torchvision=0.13.1
+  - numpy=1.23.1
\ No newline at end of file
-- 
cgit v1.2.3


From 8aead63f1ac9fec0e5198bd626ec2c5bcbeff4d8 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 12 Oct 2022 09:32:14 +0300
Subject: emergency fix

---
 webui.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/webui.py b/webui.py
index 32bcdb06..33ba7905 100644
--- a/webui.py
+++ b/webui.py
@@ -89,6 +89,8 @@ def initialize():
 
 
 def webui():
+    initialize()
+    
     # make the program just exit at ctrl+c without waiting for anything
     def sigint_handler(sig, frame):
         print(f'Interrupted with signal {sig} in {frame}')
@@ -132,5 +134,4 @@ def webui():
 
 
 if __name__ == "__main__":
-    initialize()
     webui()
-- 
cgit v1.2.3


From 57e03cdd244eee4e33ccab7554b3594563a3d0cd Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Wed, 12 Oct 2022 00:54:24 -0400
Subject: Ensure the directory exists before saving to it

The directory for the images saved with the Save button may still not exist, so it needs to be created prior to opening the log.csv file.
---
 modules/ui.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/modules/ui.py b/modules/ui.py
index 00bf09ae..cd67b84b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -131,6 +131,8 @@ def save_files(js_data, images, do_make_zip, index):
         images = [images[index]]
         start_index = index
 
+    os.makedirs(opts.outdir_save, exist_ok=True)
+
     with open(os.path.join(opts.outdir_save, "log.csv"), "a", encoding="utf8", newline='') as file:
         at_start = file.tell() == 0
         writer = csv.writer(file)
-- 
cgit v1.2.3


From f421f2af2df41a86af1aea1e82b4c32a2d143385 Mon Sep 17 00:00:00 2001
From: aoirusann <yimodo.siki@gmail.com>
Date: Wed, 12 Oct 2022 13:02:28 +0800
Subject: [img2imgalt] Fix seed & Allow batch.

---
 scripts/img2imgalt.py | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/scripts/img2imgalt.py b/scripts/img2imgalt.py
index f9894cb0..313a55d2 100644
--- a/scripts/img2imgalt.py
+++ b/scripts/img2imgalt.py
@@ -129,8 +129,6 @@ class Script(scripts.Script):
         return [original_prompt, original_negative_prompt, cfg, st, randomness, sigma_adjustment]
 
     def run(self, p, original_prompt, original_negative_prompt, cfg, st, randomness, sigma_adjustment):
-        p.batch_size = 1
-        p.batch_count = 1
 
 
         def sample_extra(conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength):
@@ -154,7 +152,7 @@ class Script(scripts.Script):
                     rec_noise = find_noise_for_image(p, cond, uncond, cfg, st)
                 self.cache = Cached(rec_noise, cfg, st, lat, original_prompt, original_negative_prompt, sigma_adjustment)
 
-            rand_noise = processing.create_random_tensors(p.init_latent.shape[1:], [p.seed + x + 1 for x in range(p.init_latent.shape[0])])
+            rand_noise = processing.create_random_tensors(p.init_latent.shape[1:], seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength, seed_resize_from_h=p.seed_resize_from_h, seed_resize_from_w=p.seed_resize_from_w, p=p)
             
             combined_noise = ((1 - randomness) * rec_noise + randomness * rand_noise) / ((randomness**2 + (1-randomness)**2) ** 0.5)
             
-- 
cgit v1.2.3


From ca5efc316b9431746ff886d259275310f63f95fb Mon Sep 17 00:00:00 2001
From: LunixWasTaken <Lunixwastaken@protonmail.com>
Date: Tue, 11 Oct 2022 22:04:56 +0200
Subject: Typo fix in watermark hint.

---
 javascript/hints.js | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/javascript/hints.js b/javascript/hints.js
index 045f2d3c..b81c181b 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -80,7 +80,7 @@ titles = {
     "Scale latent": "Uscale the image in latent space. Alternative is to produce the full image from latent representation, upscale that, and then move it back to latent space.",
 
     "Eta noise seed delta": "If this values is non-zero, it will be added to seed and used to initialize RNG for noises when using samplers with Eta. You can use this to produce even more variation of images, or you can use this to match images of other software if you know what you are doing.",
-    "Do not add watermark to images": "If this option is enabled, watermark will not be added to created images. Warning: if you do not add watermark, you may be bevaing in an unethical manner.",
+    "Do not add watermark to images": "If this option is enabled, watermark will not be added to created images. Warning: if you do not add watermark, you may be behaving in an unethical manner.",
 }
 
 
-- 
cgit v1.2.3


From 2d006ce16cd95d587533656c3ac4991495e96f23 Mon Sep 17 00:00:00 2001
From: Milly <milly.ca@gmail.com>
Date: Mon, 10 Oct 2022 00:56:36 +0900
Subject: xy_grid: Find hypernetwork by closest name

---
 modules/hypernetworks/hypernetwork.py | 11 +++++++++++
 scripts/xy_grid.py                    |  6 +++++-
 2 files changed, 16 insertions(+), 1 deletion(-)

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 470659df..8f2192e2 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -120,6 +120,17 @@ def load_hypernetwork(filename):
         shared.loaded_hypernetwork = None
 
 
+def find_closest_hypernetwork_name(search: str):
+    if not search:
+        return None
+    search = search.lower()
+    applicable = [name for name in shared.hypernetworks if search in name.lower()]
+    if not applicable:
+        return None
+    applicable = sorted(applicable, key=lambda name: len(name))
+    return applicable[0]
+
+
 def apply_hypernetwork(hypernetwork, context, layer=None):
     hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
 
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index ef431105..6f4217ec 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -84,7 +84,11 @@ def apply_checkpoint(p, x, xs):
 
 
 def apply_hypernetwork(p, x, xs):
-    hypernetwork.load_hypernetwork(x)
+    if x.lower() in ["", "none"]:
+        name = None
+    else:
+        name = hypernetwork.find_closest_hypernetwork_name(x)
+    hypernetwork.load_hypernetwork(name)
 
 
 def apply_clip_skip(p, x, xs):
-- 
cgit v1.2.3


From 7dba1c07cb337114507d9c256f9b843162c187d6 Mon Sep 17 00:00:00 2001
From: Milly <milly.ca@gmail.com>
Date: Mon, 10 Oct 2022 01:37:09 +0900
Subject: xy_grid: Confirm that hypernetwork options are valid before starting

---
 scripts/xy_grid.py | 12 ++++++++++++
 1 file changed, 12 insertions(+)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 6f4217ec..b2239d0a 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -88,9 +88,19 @@ def apply_hypernetwork(p, x, xs):
         name = None
     else:
         name = hypernetwork.find_closest_hypernetwork_name(x)
+        if not name:
+            raise RuntimeError(f"Unknown hypernetwork: {x}")
     hypernetwork.load_hypernetwork(name)
 
 
+def confirm_hypernetworks(xs):
+    for x in xs:
+        if x.lower() in ["", "none"]:
+            continue
+        if not hypernetwork.find_closest_hypernetwork_name(x):
+            raise RuntimeError(f"Unknown hypernetwork: {x}")
+
+
 def apply_clip_skip(p, x, xs):
     opts.data["CLIP_stop_at_last_layers"] = x
 
@@ -284,6 +294,8 @@ class Script(scripts.Script):
                 for ckpt_val in valslist:
                     if modules.sd_models.get_closet_checkpoint_match(ckpt_val) is None:
                         raise RuntimeError(f"Checkpoint for {ckpt_val} not found")
+            elif opt.label == "Hypernetwork":
+                confirm_hypernetworks(valslist)
 
             return valslist
 
-- 
cgit v1.2.3


From 2fffd4bddce12b2c98a5bae5a2cc6d64450d65a0 Mon Sep 17 00:00:00 2001
From: Milly <milly.ca@gmail.com>
Date: Mon, 10 Oct 2022 02:20:35 +0900
Subject: xy_grid: Refactor confirm functions

---
 scripts/xy_grid.py | 73 +++++++++++++++++++++++++++++-------------------------
 1 file changed, 39 insertions(+), 34 deletions(-)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index b2239d0a..3bb080bf 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -77,12 +77,26 @@ def apply_sampler(p, x, xs):
     p.sampler_index = sampler_index
 
 
+def confirm_samplers(p, xs):
+    samplers_dict = build_samplers_dict(p)
+    for x in xs:
+        if x.lower() not in samplers_dict.keys():
+            raise RuntimeError(f"Unknown sampler: {x}")
+
+
 def apply_checkpoint(p, x, xs):
     info = modules.sd_models.get_closet_checkpoint_match(x)
-    assert info is not None, f'Checkpoint for {x} not found'
+    if info is None:
+        raise RuntimeError(f"Unknown checkpoint: {x}")
     modules.sd_models.reload_model_weights(shared.sd_model, info)
 
 
+def confirm_checkpoints(p, xs):
+    for x in xs:
+        if modules.sd_models.get_closet_checkpoint_match(x) is None:
+            raise RuntimeError(f"Unknown checkpoint: {x}")
+
+
 def apply_hypernetwork(p, x, xs):
     if x.lower() in ["", "none"]:
         name = None
@@ -93,7 +107,7 @@ def apply_hypernetwork(p, x, xs):
     hypernetwork.load_hypernetwork(name)
 
 
-def confirm_hypernetworks(xs):
+def confirm_hypernetworks(p, xs):
     for x in xs:
         if x.lower() in ["", "none"]:
             continue
@@ -135,29 +149,29 @@ def str_permutations(x):
     return x
 
 
-AxisOption = namedtuple("AxisOption", ["label", "type", "apply", "format_value"])
-AxisOptionImg2Img = namedtuple("AxisOptionImg2Img", ["label", "type", "apply", "format_value"])
+AxisOption = namedtuple("AxisOption", ["label", "type", "apply", "format_value", "confirm"])
+AxisOptionImg2Img = namedtuple("AxisOptionImg2Img", ["label", "type", "apply", "format_value", "confirm"])
 
 
 axis_options = [
-    AxisOption("Nothing", str, do_nothing, format_nothing),
-    AxisOption("Seed", int, apply_field("seed"), format_value_add_label),
-    AxisOption("Var. seed", int, apply_field("subseed"), format_value_add_label),
-    AxisOption("Var. strength", float, apply_field("subseed_strength"), format_value_add_label),
-    AxisOption("Steps", int, apply_field("steps"), format_value_add_label),
-    AxisOption("CFG Scale", float, apply_field("cfg_scale"), format_value_add_label),
-    AxisOption("Prompt S/R", str, apply_prompt, format_value),
-    AxisOption("Prompt order", str_permutations, apply_order, format_value_join_list),
-    AxisOption("Sampler", str, apply_sampler, format_value),
-    AxisOption("Checkpoint name", str, apply_checkpoint, format_value),
-    AxisOption("Hypernetwork", str, apply_hypernetwork, format_value),
-    AxisOption("Sigma Churn", float, apply_field("s_churn"), format_value_add_label),
-    AxisOption("Sigma min", float, apply_field("s_tmin"), format_value_add_label),
-    AxisOption("Sigma max", float, apply_field("s_tmax"), format_value_add_label),
-    AxisOption("Sigma noise", float, apply_field("s_noise"), format_value_add_label),
-    AxisOption("Eta", float, apply_field("eta"), format_value_add_label),
-    AxisOption("Clip skip", int, apply_clip_skip, format_value_add_label),
-    AxisOptionImg2Img("Denoising", float, apply_field("denoising_strength"), format_value_add_label),  # as it is now all AxisOptionImg2Img items must go after AxisOption ones
+    AxisOption("Nothing", str, do_nothing, format_nothing, None),
+    AxisOption("Seed", int, apply_field("seed"), format_value_add_label, None),
+    AxisOption("Var. seed", int, apply_field("subseed"), format_value_add_label, None),
+    AxisOption("Var. strength", float, apply_field("subseed_strength"), format_value_add_label, None),
+    AxisOption("Steps", int, apply_field("steps"), format_value_add_label, None),
+    AxisOption("CFG Scale", float, apply_field("cfg_scale"), format_value_add_label, None),
+    AxisOption("Prompt S/R", str, apply_prompt, format_value, None),
+    AxisOption("Prompt order", str_permutations, apply_order, format_value_join_list, None),
+    AxisOption("Sampler", str, apply_sampler, format_value, confirm_samplers),
+    AxisOption("Checkpoint name", str, apply_checkpoint, format_value, confirm_checkpoints),
+    AxisOption("Hypernetwork", str, apply_hypernetwork, format_value, confirm_hypernetworks),
+    AxisOption("Sigma Churn", float, apply_field("s_churn"), format_value_add_label, None),
+    AxisOption("Sigma min", float, apply_field("s_tmin"), format_value_add_label, None),
+    AxisOption("Sigma max", float, apply_field("s_tmax"), format_value_add_label, None),
+    AxisOption("Sigma noise", float, apply_field("s_noise"), format_value_add_label, None),
+    AxisOption("Eta", float, apply_field("eta"), format_value_add_label, None),
+    AxisOption("Clip skip", int, apply_clip_skip, format_value_add_label, None),
+    AxisOptionImg2Img("Denoising", float, apply_field("denoising_strength"), format_value_add_label, None),  # as it is now all AxisOptionImg2Img items must go after AxisOption ones
 ]
 
 
@@ -283,19 +297,10 @@ class Script(scripts.Script):
                 valslist = list(permutations(valslist))
 
             valslist = [opt.type(x) for x in valslist]
-            
+
             # Confirm options are valid before starting
-            if opt.label == "Sampler":
-                samplers_dict = build_samplers_dict(p)
-                for sampler_val in valslist:
-                    if sampler_val.lower() not in samplers_dict.keys():
-                        raise RuntimeError(f"Unknown sampler: {sampler_val}")
-            elif opt.label == "Checkpoint name":
-                for ckpt_val in valslist:
-                    if modules.sd_models.get_closet_checkpoint_match(ckpt_val) is None:
-                        raise RuntimeError(f"Checkpoint for {ckpt_val} not found")
-            elif opt.label == "Hypernetwork":
-                confirm_hypernetworks(valslist)
+            if opt.confirm:
+                opt.confirm(p, valslist)
 
             return valslist
 
-- 
cgit v1.2.3


From ee015a1af66a94a75c914659fa0d321e702a0a87 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 12 Oct 2022 11:05:57 +0300
Subject: change textual inversion tab to train remake train interface to use
 tabs

---
 modules/hypernetworks/hypernetwork.py |  2 +-
 modules/ui.py                         | 22 +++++++++-------------
 2 files changed, 10 insertions(+), 14 deletions(-)

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 8f2192e2..8314450a 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -175,7 +175,7 @@ def attention_CrossAttention_forward(self, x, context=None, mask=None):
 
 
 def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_image_prompt):
-    assert hypernetwork_name, 'embedding not selected'
+    assert hypernetwork_name, 'hypernetwork not selected'
 
     path = shared.hypernetworks.get(hypernetwork_name, None)
     shared.loaded_hypernetwork = Hypernetwork()
diff --git a/modules/ui.py b/modules/ui.py
index 4bfdd275..86a2da6c 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1035,14 +1035,14 @@ def create_ui(wrap_gradio_gpu_call):
 
     sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings()
 
-    with gr.Blocks() as textual_inversion_interface:
+    with gr.Blocks() as train_interface:
         with gr.Row().style(equal_height=False):
-            with gr.Column():
-                with gr.Group():
-                    gr.HTML(value="<p style='margin-bottom: 0.7em'>See <b><a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\">wiki</a></b> for detailed explanation.</p>")
+            gr.HTML(value="<p style='margin-bottom: 0.7em'>See <b><a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\">wiki</a></b> for detailed explanation.</p>")
 
-                    gr.HTML(value="<p style='margin-bottom: 0.7em'>Create a new embedding</p>")
+        with gr.Row().style(equal_height=False):
+            with gr.Tabs(elem_id="train_tabs"):
 
+                with gr.Tab(label="Create embedding"):
                     new_embedding_name = gr.Textbox(label="Name")
                     initialization_text = gr.Textbox(label="Initialization text", value="*")
                     nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1)
@@ -1054,9 +1054,7 @@ def create_ui(wrap_gradio_gpu_call):
                         with gr.Column():
                             create_embedding = gr.Button(value="Create embedding", variant='primary')
 
-                with gr.Group():
-                    gr.HTML(value="<p style='margin-bottom: 0.7em'>Create a new hypernetwork</p>")
-
+                with gr.Tab(label="Create hypernetwork"):
                     new_hypernetwork_name = gr.Textbox(label="Name")
                     new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"])
 
@@ -1067,9 +1065,7 @@ def create_ui(wrap_gradio_gpu_call):
                         with gr.Column():
                             create_hypernetwork = gr.Button(value="Create hypernetwork", variant='primary')
 
-                with gr.Group():
-                    gr.HTML(value="<p style='margin-bottom: 0.7em'>Preprocess images</p>")
-
+                with gr.Tab(label="Preprocess images"):
                     process_src = gr.Textbox(label='Source directory')
                     process_dst = gr.Textbox(label='Destination directory')
                     process_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
@@ -1091,7 +1087,7 @@ def create_ui(wrap_gradio_gpu_call):
                         with gr.Column():
                             run_preprocess = gr.Button(value="Preprocess", variant='primary')
 
-                with gr.Group():
+                with gr.Tab(label="Train"):
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding; must specify a directory with a set of 1:1 ratio images</p>")
                     train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
                     train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', choices=[x for x in shared.hypernetworks.keys()])
@@ -1388,7 +1384,7 @@ Requested path was: {f}
         (extras_interface, "Extras", "extras"),
         (pnginfo_interface, "PNG Info", "pnginfo"),
         (modelmerger_interface, "Checkpoint Merger", "modelmerger"),
-        (textual_inversion_interface, "Textual inversion", "ti"),
+        (train_interface, "Train", "ti"),
         (settings_interface, "Settings", "settings"),
     ]
 
-- 
cgit v1.2.3


From 80f3cf2bb2ce3f00d801cae2c3a8c20a8d4167d8 Mon Sep 17 00:00:00 2001
From: hentailord85ez <112723046+hentailord85ez@users.noreply.github.com>
Date: Tue, 11 Oct 2022 19:48:53 +0100
Subject: Account when lines are mismatched

---
 modules/sd_hijack.py | 12 +++++++++++-
 1 file changed, 11 insertions(+), 1 deletion(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index ac70f876..2753d4fa 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -321,7 +321,17 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
                         fixes.append(fix[1])
                 self.hijack.fixes.append(fixes)
             
-            z1 = self.process_tokens([x[:75] for x in remade_batch_tokens], [x[:75] for x in batch_multipliers])
+            tokens = []
+            multipliers = []
+            for i in range(len(remade_batch_tokens)):
+                if len(remade_batch_tokens[i]) > 0:
+                    tokens.append(remade_batch_tokens[i][:75])
+                    multipliers.append(batch_multipliers[i][:75])
+                else:
+                    tokens.append([self.wrapped.tokenizer.eos_token_id] * 75)
+                    multipliers.append([1.0] * 75)
+
+            z1 = self.process_tokens(tokens, multipliers)
             z = z1 if z is None else torch.cat((z, z1), axis=-2)
             
             remade_batch_tokens = rem_tokens
-- 
cgit v1.2.3


From 8561d5762b98bf7cfb764128ebf11633d8bb4405 Mon Sep 17 00:00:00 2001
From: Kalle <kalekkiorg@gmail.com>
Date: Wed, 12 Oct 2022 12:43:11 +0300
Subject: Remove duplicate artist from file

---
 artists.csv | 1 -
 1 file changed, 1 deletion(-)

diff --git a/artists.csv b/artists.csv
index 14ba2022..99cdbdc6 100644
--- a/artists.csv
+++ b/artists.csv
@@ -1045,7 +1045,6 @@ Bakemono Zukushi,0.67051035,anime
 Lucy Madox Brown,0.67032814,fineart
 Paul Wonner,0.6700563,scribbles
 Guido Borelli Da Caluso,0.66966087,digipa-high-impact
-Guido Borelli da Caluso,0.66966087,digipa-high-impact
 Emil Alzamora,0.5844039,nudity
 Heinrich Brocksieper,0.64469147,fineart
 Dan Smith,0.669563,digipa-high-impact
-- 
cgit v1.2.3


From 429442f4a6aab7301efb89d27bef524fe827e81a Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 12 Oct 2022 13:38:03 +0300
Subject: fix iterator bug for #2295

---
 modules/sd_hijack.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 2753d4fa..c81722a0 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -323,10 +323,10 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
             
             tokens = []
             multipliers = []
-            for i in range(len(remade_batch_tokens)):
-                if len(remade_batch_tokens[i]) > 0:
-                    tokens.append(remade_batch_tokens[i][:75])
-                    multipliers.append(batch_multipliers[i][:75])
+            for j in range(len(remade_batch_tokens)):
+                if len(remade_batch_tokens[j]) > 0:
+                    tokens.append(remade_batch_tokens[j][:75])
+                    multipliers.append(batch_multipliers[j][:75])
                 else:
                     tokens.append([self.wrapped.tokenizer.eos_token_id] * 75)
                     multipliers.append([1.0] * 75)
-- 
cgit v1.2.3


From 50be33e953be93c40814262c6dbce36e66004528 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Wed, 12 Oct 2022 13:13:25 +0100
Subject: formatting

---
 modules/textual_inversion/image_embedding.py | 170 ++++++++++++++-------------
 1 file changed, 91 insertions(+), 79 deletions(-)

diff --git a/modules/textual_inversion/image_embedding.py b/modules/textual_inversion/image_embedding.py
index 1224fb42..898ce3b3 100644
--- a/modules/textual_inversion/image_embedding.py
+++ b/modules/textual_inversion/image_embedding.py
@@ -2,122 +2,134 @@ import base64
 import json
 import numpy as np
 import zlib
-from PIL import Image,PngImagePlugin,ImageDraw,ImageFont
+from PIL import Image, PngImagePlugin, ImageDraw, ImageFont
 from fonts.ttf import Roboto
 import torch
 
+
 class EmbeddingEncoder(json.JSONEncoder):
     def default(self, obj):
         if isinstance(obj, torch.Tensor):
-            return {'TORCHTENSOR':obj.cpu().detach().numpy().tolist()}
+            return {'TORCHTENSOR': obj.cpu().detach().numpy().tolist()}
         return json.JSONEncoder.default(self, obj)
 
+
 class EmbeddingDecoder(json.JSONDecoder):
     def __init__(self, *args, **kwargs):
         json.JSONDecoder.__init__(self, object_hook=self.object_hook, *args, **kwargs)
+
     def object_hook(self, d):
         if 'TORCHTENSOR' in d:
             return torch.from_numpy(np.array(d['TORCHTENSOR']))
         return d
 
+
 def embedding_to_b64(data):
-    d = json.dumps(data,cls=EmbeddingEncoder)
+    d = json.dumps(data, cls=EmbeddingEncoder)
     return base64.b64encode(d.encode())
 
+
 def embedding_from_b64(data):
     d = base64.b64decode(data)
-    return json.loads(d,cls=EmbeddingDecoder)
+    return json.loads(d, cls=EmbeddingDecoder)
+
 
 def lcg(m=2**32, a=1664525, c=1013904223, seed=0):
     while True:
         seed = (a * seed + c) % m
-        yield seed%255
+        yield seed % 255
+
 
 def xor_block(block):
     g = lcg()
     randblock = np.array([next(g) for _ in range(np.product(block.shape))]).astype(np.uint8).reshape(block.shape)
-    return np.bitwise_xor(block.astype(np.uint8),randblock & 0x0F) 
+    return np.bitwise_xor(block.astype(np.uint8), randblock & 0x0F)
 
-def style_block(block,sequence):
-    im = Image.new('RGB',(block.shape[1],block.shape[0]))
+
+def style_block(block, sequence):
+    im = Image.new('RGB', (block.shape[1], block.shape[0]))
     draw = ImageDraw.Draw(im)
-    i=0
-    for x in range(-6,im.size[0],8):
-        for yi,y in enumerate(range(-6,im.size[1],8)):
-            offset=0
-            if yi%2==0:
-                offset=4
-            shade = sequence[i%len(sequence)]
-            i+=1
-            draw.ellipse((x+offset, y, x+6+offset, y+6), fill =(shade,shade,shade) )
+    i = 0
+    for x in range(-6, im.size[0], 8):
+        for yi, y in enumerate(range(-6, im.size[1], 8)):
+            offset = 0
+            if yi % 2 == 0:
+                offset = 4
+            shade = sequence[i % len(sequence)]
+            i += 1
+            draw.ellipse((x+offset, y, x+6+offset, y+6), fill=(shade, shade, shade))
 
     fg = np.array(im).astype(np.uint8) & 0xF0
 
     return block ^ fg
 
-def insert_image_data_embed(image,data):
+
+def insert_image_data_embed(image, data):
     d = 3
-    data_compressed = zlib.compress( json.dumps(data,cls=EmbeddingEncoder).encode(),level=9)
-    data_np_ = np.frombuffer(data_compressed,np.uint8).copy()
+    data_compressed = zlib.compress(json.dumps(data, cls=EmbeddingEncoder).encode(), level=9)
+    data_np_ = np.frombuffer(data_compressed, np.uint8).copy()
     data_np_high = data_np_ >> 4
-    data_np_low  = data_np_ & 0x0F
-    
+    data_np_low = data_np_ & 0x0F
+
     h = image.size[1]
-    next_size = data_np_low.shape[0] + (h-(data_np_low.shape[0]%h))
-    next_size = next_size + ((h*d)-(next_size%(h*d)))
+    next_size = data_np_low.shape[0] + (h-(data_np_low.shape[0] % h))
+    next_size = next_size + ((h*d)-(next_size % (h*d)))
 
     data_np_low.resize(next_size)
-    data_np_low = data_np_low.reshape((h,-1,d))
+    data_np_low = data_np_low.reshape((h, -1, d))
 
     data_np_high.resize(next_size)
-    data_np_high = data_np_high.reshape((h,-1,d))
+    data_np_high = data_np_high.reshape((h, -1, d))
 
     edge_style = list(data['string_to_param'].values())[0].cpu().detach().numpy().tolist()[0][:1024]
     edge_style = (np.abs(edge_style)/np.max(np.abs(edge_style))*255).astype(np.uint8)
 
-    data_np_low   = style_block(data_np_low,sequence=edge_style)
-    data_np_low   = xor_block(data_np_low)    
-    data_np_high  = style_block(data_np_high,sequence=edge_style[::-1])
-    data_np_high  = xor_block(data_np_high)
+    data_np_low = style_block(data_np_low, sequence=edge_style)
+    data_np_low = xor_block(data_np_low)
+    data_np_high = style_block(data_np_high, sequence=edge_style[::-1])
+    data_np_high = xor_block(data_np_high)
 
-    im_low  = Image.fromarray(data_np_low,mode='RGB')
-    im_high = Image.fromarray(data_np_high,mode='RGB')
+    im_low = Image.fromarray(data_np_low, mode='RGB')
+    im_high = Image.fromarray(data_np_high, mode='RGB')
 
-    background = Image.new('RGB',(image.size[0]+im_low.size[0]+im_high.size[0]+2,image.size[1]),(0,0,0))
-    background.paste(im_low,(0,0))
-    background.paste(image,(im_low.size[0]+1,0))
-    background.paste(im_high,(im_low.size[0]+1+image.size[0]+1,0))
+    background = Image.new('RGB', (image.size[0]+im_low.size[0]+im_high.size[0]+2, image.size[1]), (0, 0, 0))
+    background.paste(im_low, (0, 0))
+    background.paste(image, (im_low.size[0]+1, 0))
+    background.paste(im_high, (im_low.size[0]+1+image.size[0]+1, 0))
 
     return background
 
-def crop_black(img,tol=0):
-    mask = (img>tol).all(2)
-    mask0,mask1 = mask.any(0),mask.any(1)
-    col_start,col_end = mask0.argmax(),mask.shape[1]-mask0[::-1].argmax()
-    row_start,row_end = mask1.argmax(),mask.shape[0]-mask1[::-1].argmax()
-    return img[row_start:row_end,col_start:col_end]
+
+def crop_black(img, tol=0):
+    mask = (img > tol).all(2)
+    mask0, mask1 = mask.any(0), mask.any(1)
+    col_start, col_end = mask0.argmax(), mask.shape[1]-mask0[::-1].argmax()
+    row_start, row_end = mask1.argmax(), mask.shape[0]-mask1[::-1].argmax()
+    return img[row_start:row_end, col_start:col_end]
+
 
 def extract_image_data_embed(image):
-    d=3
-    outarr = crop_black(np.array(image.convert('RGB').getdata()).reshape(image.size[1],image.size[0],d ).astype(np.uint8) ) & 0x0F
-    black_cols = np.where( np.sum(outarr, axis=(0,2))==0)
+    d = 3
+    outarr = crop_black(np.array(image.convert('RGB').getdata()).reshape(image.size[1], image.size[0], d).astype(np.uint8)) & 0x0F
+    black_cols = np.where(np.sum(outarr, axis=(0, 2)) == 0)
     if black_cols[0].shape[0] < 2:
         print('No Image data blocks found.')
         return None
 
-    data_block_lower = outarr[:,:black_cols[0].min(),:].astype(np.uint8)
-    data_block_upper = outarr[:,black_cols[0].max()+1:,:].astype(np.uint8)
+    data_block_lower = outarr[:, :black_cols[0].min(), :].astype(np.uint8)
+    data_block_upper = outarr[:, black_cols[0].max()+1:, :].astype(np.uint8)
 
     data_block_lower = xor_block(data_block_lower)
     data_block_upper = xor_block(data_block_upper)
-    
+
     data_block = (data_block_upper << 4) | (data_block_lower)
     data_block = data_block.flatten().tobytes()
 
     data = zlib.decompress(data_block)
-    return json.loads(data,cls=EmbeddingDecoder)
+    return json.loads(data, cls=EmbeddingDecoder)
+
 
-def caption_image_overlay(srcimage,title,footerLeft,footerMid,footerRight,textfont=None):
+def caption_image_overlay(srcimage, title, footerLeft, footerMid, footerRight, textfont=None):
     from math import cos
 
     image = srcimage.copy()
@@ -130,11 +142,11 @@ def caption_image_overlay(srcimage,title,footerLeft,footerMid,footerRight,textfo
             textfont = Roboto
 
     factor = 1.5
-    gradient = Image.new('RGBA', (1,image.size[1]), color=(0,0,0,0))
+    gradient = Image.new('RGBA', (1, image.size[1]), color=(0, 0, 0, 0))
     for y in range(image.size[1]):
         mag = 1-cos(y/image.size[1]*factor)
-        mag = max(mag,1-cos((image.size[1]-y)/image.size[1]*factor*1.1))
-        gradient.putpixel((0, y), (0,0,0,int(mag*255)))
+        mag = max(mag, 1-cos((image.size[1]-y)/image.size[1]*factor*1.1))
+        gradient.putpixel((0, y), (0, 0, 0, int(mag*255)))
     image = Image.alpha_composite(image.convert('RGBA'), gradient.resize(image.size))
 
     draw = ImageDraw.Draw(image)
@@ -142,41 +154,41 @@ def caption_image_overlay(srcimage,title,footerLeft,footerMid,footerRight,textfo
     font = ImageFont.truetype(textfont, fontsize)
     padding = 10
 
-    _,_,w, h = draw.textbbox((0,0),title,font=font)
-    fontsize =  min( int(fontsize * (((image.size[0]*0.75)-(padding*4))/w) ), 72)
+    _, _, w, h = draw.textbbox((0, 0), title, font=font)
+    fontsize = min(int(fontsize * (((image.size[0]*0.75)-(padding*4))/w)), 72)
     font = ImageFont.truetype(textfont, fontsize)
-    _,_,w,h = draw.textbbox((0,0),title,font=font)
-    draw.text((padding,padding), title, anchor='lt', font=font, fill=(255,255,255,230))
+    _, _, w, h = draw.textbbox((0, 0), title, font=font)
+    draw.text((padding, padding), title, anchor='lt', font=font, fill=(255, 255, 255, 230))
 
-    _,_,w, h = draw.textbbox((0,0),footerLeft,font=font)
-    fontsize_left =  min( int(fontsize * (((image.size[0]/3)-(padding))/w) ), 72)
-    _,_,w, h = draw.textbbox((0,0),footerMid,font=font)
-    fontsize_mid =  min( int(fontsize * (((image.size[0]/3)-(padding))/w) ), 72)
-    _,_,w, h = draw.textbbox((0,0),footerRight,font=font)
-    fontsize_right =  min( int(fontsize * (((image.size[0]/3)-(padding))/w) ), 72)
+    _, _, w, h = draw.textbbox((0, 0), footerLeft, font=font)
+    fontsize_left = min(int(fontsize * (((image.size[0]/3)-(padding))/w)), 72)
+    _, _, w, h = draw.textbbox((0, 0), footerMid, font=font)
+    fontsize_mid = min(int(fontsize * (((image.size[0]/3)-(padding))/w)), 72)
+    _, _, w, h = draw.textbbox((0, 0), footerRight, font=font)
+    fontsize_right = min(int(fontsize * (((image.size[0]/3)-(padding))/w)), 72)
 
-    font = ImageFont.truetype(textfont, min(fontsize_left,fontsize_mid,fontsize_right))
+    font = ImageFont.truetype(textfont, min(fontsize_left, fontsize_mid, fontsize_right))
 
-    draw.text((padding,image.size[1]-padding),               footerLeft, anchor='ls', font=font, fill=(255,255,255,230))
-    draw.text((image.size[0]/2,image.size[1]-padding),       footerMid, anchor='ms', font=font, fill=(255,255,255,230))
-    draw.text((image.size[0]-padding,image.size[1]-padding), footerRight, anchor='rs', font=font, fill=(255,255,255,230))
+    draw.text((padding, image.size[1]-padding),               footerLeft, anchor='ls', font=font, fill=(255, 255, 255, 230))
+    draw.text((image.size[0]/2, image.size[1]-padding),       footerMid, anchor='ms', font=font, fill=(255, 255, 255, 230))
+    draw.text((image.size[0]-padding, image.size[1]-padding), footerRight, anchor='rs', font=font, fill=(255, 255, 255, 230))
 
     return image
 
+
 if __name__ == '__main__':
 
     testEmbed = Image.open('test_embedding.png')
-    
     data = extract_image_data_embed(testEmbed)
     assert data is not None
 
     data = embedding_from_b64(testEmbed.text['sd-ti-embedding'])
     assert data is not None
-    
-    image = Image.new('RGBA',(512,512),(255,255,200,255))
+
+    image = Image.new('RGBA', (512, 512), (255, 255, 200, 255))
     cap_image = caption_image_overlay(image, 'title', 'footerLeft', 'footerMid', 'footerRight')
 
-    test_embed = {'string_to_param':{'*':torch.from_numpy(np.random.random((2, 4096)))}}
+    test_embed = {'string_to_param': {'*': torch.from_numpy(np.random.random((2, 4096)))}}
 
     embedded_image = insert_image_data_embed(cap_image, test_embed)
 
@@ -191,16 +203,16 @@ if __name__ == '__main__':
     g = lcg()
     shared_random = np.array([next(g) for _ in range(100)]).astype(np.uint8).tolist()
 
-    reference_random = [253, 242, 127,  44, 157,  27, 239, 133,  38,  79, 167,   4, 177, 
-                         95, 130,  79,  78,  14,  52, 215, 220, 194, 126,  28, 240, 179, 
-                        160, 153, 149,  50, 105,  14,  21, 218, 199,  18,  54, 198, 193, 
-                         38, 128,  19,  53, 195, 124,  75, 205,  12,   6, 145,   0,  28, 
-                         30, 148,   8,  45, 218, 171,  55, 249,  97, 166,  12,  35,   0, 
-                         41, 221, 122, 215, 170,  31, 113, 186,  97, 119,  31,  23, 185, 
-                         66, 140,  30,  41,  37,  63, 137, 109, 216,  55, 159, 145,  82, 
+    reference_random = [253, 242, 127,  44, 157,  27, 239, 133,  38,  79, 167,   4, 177,
+                         95, 130,  79,  78,  14,  52, 215, 220, 194, 126,  28, 240, 179,
+                        160, 153, 149,  50, 105,  14,  21, 218, 199,  18,  54, 198, 193,
+                         38, 128,  19,  53, 195, 124,  75, 205,  12,   6, 145,   0,  28,
+                         30, 148,   8,  45, 218, 171,  55, 249,  97, 166,  12,  35,   0,
+                         41, 221, 122, 215, 170,  31, 113, 186,  97, 119,  31,  23, 185,
+                         66, 140,  30,  41,  37,  63, 137, 109, 216,  55, 159, 145,  82,
                          204, 86,  73, 222,  44, 198, 118, 240,  97]
 
-    assert shared_random == reference_random   
+    assert shared_random == reference_random
 
     hunna_kay_random_sum = sum(np.array([next(g) for _ in range(100000)]).astype(np.uint8).tolist())
 
-- 
cgit v1.2.3


From 10a2de644f8ea4cfade88e85d768da3480f4c9f0 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Wed, 12 Oct 2022 13:15:35 +0100
Subject: formatting

---
 modules/textual_inversion/textual_inversion.py | 22 +++++++++++-----------
 1 file changed, 11 insertions(+), 11 deletions(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 485ef46c..b072d745 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -7,14 +7,14 @@ import tqdm
 import html
 import datetime
 
-from PIL import Image,PngImagePlugin
+from PIL import Image, PngImagePlugin
 
 from modules import shared, devices, sd_hijack, processing, sd_models
 import modules.textual_inversion.dataset
 
-from modules.textual_inversion.image_embedding import (embedding_to_b64,embedding_from_b64,
-                                                       insert_image_data_embed,extract_image_data_embed,
-                                                       caption_image_overlay )
+from modules.textual_inversion.image_embedding import (embedding_to_b64, embedding_from_b64,
+                                                       insert_image_data_embed, extract_image_data_embed,
+                                                       caption_image_overlay)
 
 class Embedding:
     def __init__(self, vec, name, step=None):
@@ -90,10 +90,10 @@ class EmbeddingDatabase:
                 embed_image = Image.open(path)
                 if 'sd-ti-embedding' in embed_image.text:
                     data = embedding_from_b64(embed_image.text['sd-ti-embedding'])
-                    name = data.get('name',name)
+                    name = data.get('name', name)
                 else:
                     data = extract_image_data_embed(embed_image)
-                    name = data.get('name',name)
+                    name = data.get('name', name)
             else:
                 data = torch.load(path, map_location="cpu")
 
@@ -278,24 +278,24 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
             shared.state.current_image = image
 
             if save_image_with_stored_embedding and os.path.exists(last_saved_file):
-                
+
                 last_saved_image_chunks = os.path.join(images_embeds_dir, f'{embedding_name}-{embedding.step}.png')
 
                 info = PngImagePlugin.PngInfo()
                 data = torch.load(last_saved_file)
                 info.add_text("sd-ti-embedding", embedding_to_b64(data))
 
-                title = "<{}>".format(data.get('name','???'))
+                title = "<{}>".format(data.get('name', '???'))
                 checkpoint = sd_models.select_checkpoint()
                 footer_left = checkpoint.model_name
                 footer_mid = '[{}]'.format(checkpoint.hash)
                 footer_right = '{}'.format(embedding.step)
 
-                captioned_image = caption_image_overlay(image,title,footer_left,footer_mid,footer_right)
-                captioned_image = insert_image_data_embed(captioned_image,data)
+                captioned_image = caption_image_overlay(image, title, footer_left, footer_mid, footer_right)
+                captioned_image = insert_image_data_embed(captioned_image, data)
 
                 captioned_image.save(last_saved_image_chunks, "PNG", pnginfo=info)
-            
+
             image.save(last_saved_image)
 
             last_saved_image += f", prompt: {preview_text}"
-- 
cgit v1.2.3


From e05573e1adc1cde1e3bd7eb651a1ab27c446b3d5 Mon Sep 17 00:00:00 2001
From: yfszzx <yfszzx@gmail.com>
Date: Wed, 12 Oct 2022 20:47:55 +0800
Subject: images history improvement

---
 .gitignore                   |   1 +
 javascript/images_history.js | 222 ++++++++++++++++++++++++++++---------------
 modules/images_history.py    |  67 ++++++++-----
 3 files changed, 190 insertions(+), 100 deletions(-)

diff --git a/.gitignore b/.gitignore
index 7afc9395..434e23ce 100644
--- a/.gitignore
+++ b/.gitignore
@@ -26,3 +26,4 @@ __pycache__
 notification.mp3
 /SwinIR
 /textual_inversion
+/images_history_testui.py
diff --git a/javascript/images_history.js b/javascript/images_history.js
index d62eb181..c9a63166 100644
--- a/javascript/images_history.js
+++ b/javascript/images_history.js
@@ -1,122 +1,192 @@
-images_history_tab_list = ["txt2img", "img2img", "extras"]
-function images_history_init(){ 
-    if (gradioApp().getElementById('txt2img_images_history_first_page') == null) {
-        setTimeout(images_history_init, 500)
-    } else {        
-        for (i in images_history_tab_list ){
-            tab = images_history_tab_list[i]
-            gradioApp().getElementById(tab + '_images_history').classList.add("images_history_gallery")
-            gradioApp().getElementById(tab + '_images_history_set_index').classList.add("images_history_set_index")      
-            
-        }
-        gradioApp().getElementById("txt2img_images_history_first_page").click()     
-    }    
-}
-setTimeout(images_history_init, 500)
-var images_history_button_actions = function(){
+var images_history_click_image = function(){
     if (!this.classList.contains("transform")){        
-        gallery = this.parentElement
-        while(!gallery.classList.contains("images_history_gallery")){gallery = gallery.parentElement}        
-        buttons = gallery.querySelectorAll(".gallery-item")
-        i = 0
-        hidden_list = []
+        var gallery = images_history_get_parent_by_class(this, "images_history_cantainor");
+        var buttons = gallery.querySelectorAll(".gallery-item");
+        var i = 0;
+        var hidden_list = [];
         buttons.forEach(function(e){
             if (e.style.display == "none"){
-                hidden_list.push(i)
+                hidden_list.push(i);
             }
-            i += 1
+            i += 1;
         })
         if (hidden_list.length > 0){
-            setTimeout(images_history_hide_buttons, 10, hidden_list, gallery)
-        }
-        
+            setTimeout(images_history_hide_buttons, 10, hidden_list, gallery);
+        }        
     }    
-    images_history_set_image_info(this) 
+    images_history_set_image_info(this); 
+}
 
+var images_history_click_tab = function(){
+	var tabs_box = gradioApp().getElementById("images_history_tab");
+	if (!tabs_box.classList.contains(this.getAttribute("tabname"))) {
+		gradioApp().getElementById(this.getAttribute("tabname") + "_images_history_renew_page").click();
+		tabs_box.classList.add(this.getAttribute("tabname"))
+	}	            
 }
-onUiUpdate(function(){
-    for (i in images_history_tab_list ){
-        tab = images_history_tab_list[i]
-        buttons = gradioApp().querySelectorAll('#' + tab + '_images_history .gallery-item')
-        buttons.forEach(function(bnt){    
-            bnt.addEventListener('click', images_history_button_actions, true)
-         });
+
+var images_history_close_full_view = function(){
+	var box = images_history_get_parent_by_class(this, "images_history_cantainor");
+	box.querySelector(".images_history_del_button").setAttribute("disabled", "disabled");
+}
+
+function images_history_get_parent_by_class(item, class_name){
+	var parent = item.parentElement;
+    while(!parent.classList.contains(class_name)){
+        parent = parent.parentElement;
     }
-})
+    return parent;  
+}
+
+function images_history_get_parent_by_tagname(item, tagname){
+	var parent = item.parentElement;
+	tagname = tagname.toUpperCase()
+    while(parent.tagName != tagname){
+    	console.log(parent.tagName, tagname)
+        parent = parent.parentElement;
+    }  
+    return parent;
+}
 function images_history_hide_buttons(hidden_list, gallery){
-    buttons = gallery.querySelectorAll(".gallery-item")
-    num = 0
+    var buttons = gallery.querySelectorAll(".gallery-item");
+    var num = 0;
     buttons.forEach(function(e){
         if (e.style.display == "none"){
-            num += 1
+            num += 1;
         }
     })
     if (num == hidden_list.length){
-        setTimeout(images_history_hide_buttons, 10, hidden_list, gallery)
+        setTimeout(images_history_hide_buttons, 10, hidden_list, gallery);
     } 
     for( i in hidden_list){
-        buttons[hidden_list[i]].style.display = "none"
+        buttons[hidden_list[i]].style.display = "none";
     }    
 }
 
 function images_history_set_image_info(button){
-    item = button.parentElement
-    while(item.tagName != "DIV"){item = item.parentElement}    
-    buttons = item.querySelectorAll(".gallery-item")
-    index = -1
-    i = 0
+    var buttons = images_history_get_parent_by_tagname(button, "DIV").querySelectorAll(".gallery-item");
+    var index = -1;
+    var i = 0;
     buttons.forEach(function(e){
-        if(e==button){index = i}
+        if(e == button){
+            index = i;
+        }
         if(e.style.display != "none"){
-            i += 1
+            i += 1;
         }        
     })
-    gallery = button.parentElement
-    while(!gallery.classList.contains("images_history_gallery")){gallery = gallery.parentElement}    
-    set_btn = gallery.querySelector(".images_history_set_index")
-    set_btn.setAttribute("img_index", index)
-    set_btn.click()
+    var gallery = images_history_get_parent_by_class(button, "images_history_cantainor");
+    var set_btn = gallery.querySelector(".images_history_set_index");
+    set_btn.setAttribute("img_index", index);    
+    set_btn.click();
+    gradioApp().querySelectorAll(".images_history_del_button").forEach(function(btn){
+    	btn.setAttribute('disabled','disabled');
+    })
+    
 }
 
 function images_history_get_current_img(tabname, image_path, files){
-    s =  gradioApp().getElementById(tabname + '_images_history_set_index').getAttribute("img_index")
-    return [s, image_path, files]
+    return [
+        gradioApp().getElementById(tabname + '_images_history_set_index').getAttribute("img_index"), 
+        image_path, 
+        files
+    ];
 }
 
 function images_history_delete(tabname, img_path, img_file_name, page_index, filenames, image_index){
-    image_index = parseInt(image_index)
-    tab = gradioApp().getElementById(tabname + '_images_history')
-    set_btn = tab.querySelector(".images_history_set_index")
-    buttons = []
+    image_index = parseInt(image_index);
+    var tab = gradioApp().getElementById(tabname + '_images_history');
+    var set_btn = tab.querySelector(".images_history_set_index");
+    var buttons = [];
     tab.querySelectorAll(".gallery-item").forEach(function(e){
         if (e.style.display != 'none'){
-            buttons.push(e)
+            buttons.push(e);
         }
-    })
+    });
     
-    img_num = buttons.length / 2
-    if (img_num == 1){
-            setTimeout(function(tabname){
-                gradioApp().getElementById(tabname + '_images_history_renew_page').click()
-            }, 30, tabname) 
+    var img_num = buttons.length / 2;
+    if (img_num === 1){
+        setTimeout(function(tabname){
+            gradioApp().getElementById(tabname + '_images_history_renew_page').click();
+        }, 30, tabname); 
     } else {
-        buttons[image_index].style.display = 'none'
-        buttons[image_index + img_num].style.display = 'none'
-        if (image_index  >= img_num - 1){
-            console.log(buttons.length, img_num)
-            btn = buttons[img_num - 2]
+        buttons[image_index].style.display = 'none';
+        buttons[image_index + img_num].style.display = 'none';
+        var bnt;
+        if (image_index >= img_num - 1){
+            btn = buttons[img_num - 2];
         } else {
-            btn = buttons[image_index + 1]           
+            btn = buttons[image_index + 1] ;          
         }    
-        setTimeout(function(btn){btn.click()}, 30, btn)
+        setTimeout(function(btn){btn.click()}, 30, btn);
     }      
-    return [tabname, img_path, img_file_name, page_index, filenames, image_index]
+    return [tabname, img_path, img_file_name, page_index, filenames, image_index];
 }
 
 function images_history_turnpage(img_path, page_index, image_index, tabname){
-    buttons = gradioApp().getElementById(tabname + '_images_history').querySelectorAll(".gallery-item")
+    var buttons = gradioApp().getElementById(tabname + '_images_history').querySelectorAll(".gallery-item");
     buttons.forEach(function(elem) {
-        elem.style.display = 'block'
+        elem.style.display = 'block';
     })
-    return [img_path, page_index, image_index, tabname]
+    return [img_path, page_index, image_index, tabname];
 }
+
+function images_history_enable_del_buttons(){
+	gradioApp().querySelectorAll(".images_history_del_button").forEach(function(btn){
+    	btn.removeAttribute('disabled');
+    })
+}
+
+function images_history_init(){ 
+    if (gradioApp().getElementById('txt2img_images_history_renew_page') == null) {
+        setTimeout(images_history_init, 500);
+    } else {        
+        for (var i in images_history_tab_list ){
+            tab = images_history_tab_list[i];
+            gradioApp().getElementById(tab + '_images_history').classList.add("images_history_cantainor");
+            gradioApp().getElementById(tab + '_images_history_set_index').classList.add("images_history_set_index");
+            gradioApp().getElementById(tab + '_images_history_del_button').classList.add("images_history_del_button");
+            gradioApp().getElementById(tab + '_images_history_gallery').classList.add("images_history_gallery"); 
+           
+           	      
+        }
+        var tabs_box = gradioApp().getElementById("tab_images_history").querySelector("div").querySelector("div").querySelector("div");
+        tabs_box.setAttribute("id", "images_history_tab");
+        tabs_box.classList.add(images_history_tab_list[0]);
+        gradioApp().getElementById("txt2img_images_history_renew_page").click();
+    }
+}
+
+var images_history_tab_list = ["txt2img", "img2img", "extras"];
+var images_history_start_flag = false;
+
+onUiUpdate(function(){
+	var tab = gradioApp().getElementById("images_history_tab");
+	if (tab) {
+		if (!images_history_start_flag){
+			images_history_init();
+			images_history_start_flag = true;
+		}
+	    var tab_btns = gradioApp().getElementById("images_history_tab").querySelectorAll("button");
+	    for (var i in images_history_tab_list ){
+	        var buttons = gradioApp().querySelectorAll('#' + images_history_tab_list[i] + '_images_history .gallery-item');
+	        buttons.forEach(function(bnt){    
+	            bnt.addEventListener('click', images_history_click_image, true);
+	         });
+	        var tabname = images_history_tab_list[i]
+	        tab_btns[i].setAttribute("tabname", tabname);
+	        tab_btns[i].addEventListener('click', images_history_click_tab, true);
+        // var cls_btn = gradioApp().getElementById(tabname + '_images_history_gallery').querySelector("svg");
+        // if (cls_btn){
+        // 	cls_btn.addEventListener('click', images_history_close_full_view, false);
+        // }
+        // console.log(cls_btn, cls_btn.parentElement.parentElement)
+        // if (cls_btn) {
+        // 	cls_btn = images_history_get_parent_by_tagname(cls_btn, "BUTTON");
+        // 	cls_btn.addEventListener('click', images_history_close_full_view, true);
+        // }
+    }
+
+    }
+});    
+
diff --git a/modules/images_history.py b/modules/images_history.py
index 23f55b30..77f692fe 100644
--- a/modules/images_history.py
+++ b/modules/images_history.py
@@ -1,15 +1,29 @@
 import os
-def get_recent_images(dir_name, page_index, step, image_index):
-    #print(image_index)
+import shutil
+def get_recent_images(dir_name, page_index, step, image_index, tabname):
+    print(f"renew page {page_index}")
     page_index = int(page_index)
     f_list = os.listdir(dir_name)
     file_list = []
     for file in f_list:
         if file[-4:] == ".txt":
             continue
-        file_list.append(file)    
+        #subdirectories        
+        if file[-10:].rfind(".") < 0:
+            sub_dir = os.path.join(dir_name, file)
+            if os.path.isfile(sub_dir):
+                continue
+            sub_file_list = os.listdir(sub_dir)
+            for sub_file in sub_file_list:
+                if sub_file[-4:] == ".txt":
+                    continue
+                if os.path.isfile(os.path.join(sub_dir, sub_file) ): 
+                    file_list.append(os.path.join(file, sub_file)) 
+            continue
+        file_list.append(file)        
+
     file_list = sorted(file_list, key=lambda file: -os.path.getctime(os.path.join(dir_name, file)))
-    num = 48
+    num = 48 if tabname != "extras" else 12
     max_page_index = len(file_list) // num + 1    
     page_index = max_page_index if page_index == -1 else page_index + step
     page_index = 1 if page_index < 1 else page_index    
@@ -26,26 +40,28 @@ def get_recent_images(dir_name, page_index, step, image_index):
         hide_image = os.path.join(dir_name, current_file)
     return [os.path.join(dir_name, file) for file in file_list], page_index, file_list, current_file, hide_image
 def first_page_click(dir_name, page_index, image_index, tabname):
-    return get_recent_images(dir_name, 1, 0, image_index)
+    return get_recent_images(dir_name, 1, 0, image_index, tabname)
 def end_page_click(dir_name, page_index, image_index, tabname):
-    return get_recent_images(dir_name, -1, 0, image_index)
+    return get_recent_images(dir_name, -1, 0, image_index, tabname)
 def prev_page_click(dir_name, page_index, image_index, tabname):
-    return get_recent_images(dir_name, page_index, -1, image_index)
+    return get_recent_images(dir_name, page_index, -1, image_index, tabname)
 def next_page_click(dir_name, page_index, image_index, tabname):    
-    return get_recent_images(dir_name, page_index, 1, image_index)
+    return get_recent_images(dir_name, page_index, 1, image_index, tabname)
 def page_index_change(dir_name, page_index, image_index, tabname):    
-    return get_recent_images(dir_name, page_index, 0, image_index)
+    return get_recent_images(dir_name, page_index, 0, image_index, tabname)
 
 def show_image_info(num, image_path, filenames):
-    #print("set img",num)
+    print(f"select image {num}")
     file = filenames[int(num)]
     return file, num, os.path.join(image_path, file)
 def delete_image(tabname, dir_name, name, page_index, filenames, image_index):
-    #print("filename", name)
     path = os.path.join(dir_name, name)           
-    if os.path.exists(path):
+    if os.path.exists(path):        
         print(f"Delete file {path}")
-        os.remove(path)    
+        os.remove(path)
+        txt_file = os.path.splitext(path)[0]  + ".txt"
+        if os.path.exists(txt_file):
+        	os.remove(txt_file)
         new_file_list = []
         for f in filenames:
             if f == name:
@@ -64,25 +80,26 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict):
         elif tabname == "extras":
             dir_name = opts.outdir_extras_samples
         with gr.Row():    
-            renew_page = gr.Button('Renew', elem_id=tabname + "_images_history_renew_page") 
-            first_page = gr.Button('First', elem_id=tabname + "_images_history_first_page")
-            prev_page = gr.Button('Prev') 
+            renew_page = gr.Button('Renew Page', elem_id=tabname + "_images_history_renew_page") 
+            first_page = gr.Button('First Page')
+            prev_page = gr.Button('Prev Page') 
             page_index = gr.Number(value=1, label="Page Index")
-            next_page = gr.Button('Next', elem_id=tabname + "_images_history_next_page") 
-            end_page = gr.Button('End')    
+            next_page = gr.Button('Next Page') 
+            end_page = gr.Button('End Page')    
         with gr.Row(elem_id=tabname + "_images_history"):            
             with gr.Row():     
-                with gr.Column():
-                    history_gallery = gr.Gallery(show_label=False).style(grid=6)
+                with gr.Column(scale=2):                	
+                    history_gallery = gr.Gallery(show_label=False, elem_id=tabname + "_images_history_gallery").style(grid=6)
+                    delete = gr.Button('Delete',  elem_id=tabname + "_images_history_del_button")
                 with gr.Column():     
                     with gr.Row():          
-                        delete = gr.Button('Delete')
+                        #pnginfo = gr.Button('PNG info')
                         pnginfo_send_to_txt2img = gr.Button('Send to txt2img')
                         pnginfo_send_to_img2img = gr.Button('Send to img2img')
                     with gr.Row():
                         with gr.Column():
-                            img_file_info = gr.Textbox(label="Generate Info")
-                            img_file_name = gr.Textbox(label="File Name")    
+                            img_file_info = gr.Textbox(label="Generate Info", interactive=False)
+                            img_file_name = gr.Textbox(label="File Name", interactive=False)    
                     with gr.Row():    
                         # hiden items
                         img_path = gr.Textbox(dir_name, visible=False)                
@@ -90,7 +107,7 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict):
                         image_index = gr.Textbox(value=-1, visible=False)                        
                         set_index = gr.Button('set_index',  elem_id=tabname + "_images_history_set_index", visible=False)
                         filenames = gr.State()
-                        hide_image = gr.Image(visible=False, type="pil")
+                        hide_image = gr.Image(type="pil", visible=False)
                         info1 = gr.Textbox(visible=False)
                         info2 = gr.Textbox(visible=False)
 
@@ -111,6 +128,8 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict):
         set_index.click(show_image_info, _js="images_history_get_current_img", inputs=[tabname_box,  img_path, filenames], outputs=[img_file_name, image_index, hide_image])
         delete.click(delete_image,_js="images_history_delete", inputs=[tabname_box, img_path, img_file_name, page_index, filenames, image_index], outputs=[page_index, filenames]) 
         hide_image.change(fn=run_pnginfo, inputs=[hide_image], outputs=[info1, img_file_info, info2])
+        hide_image.change(fn=None, _js="images_history_enable_del_buttons", inputs=None, outputs=None)
+        #pnginfo.click(fn=run_pnginfo, inputs=[hide_image], outputs=[info1, img_file_info, info2])
         switch_dict["fn"](pnginfo_send_to_txt2img, switch_dict["t2i"], img_file_info, 'switch_to_txt2img')
         switch_dict["fn"](pnginfo_send_to_img2img, switch_dict["i2i"], img_file_info, 'switch_to_img2img_img2img')
     
-- 
cgit v1.2.3


From a1a94b8b5f342f467aecc53b21b80ed0227ee76a Mon Sep 17 00:00:00 2001
From: yfszzx <yfszzx@gmail.com>
Date: Thu, 13 Oct 2022 00:19:34 +0800
Subject: images history improvement

---
 javascript/images_history.js | 125 ++++++++++++++++++++++---------------------
 modules/images_history.py    |   7 +--
 modules/ui.py                |  40 +++++++-------
 3 files changed, 88 insertions(+), 84 deletions(-)

diff --git a/javascript/images_history.js b/javascript/images_history.js
index c9a63166..620f242c 100644
--- a/javascript/images_history.js
+++ b/javascript/images_history.js
@@ -18,20 +18,26 @@ var images_history_click_image = function(){
 }
 
 var images_history_click_tab = function(){
-	var tabs_box = gradioApp().getElementById("images_history_tab");
-	if (!tabs_box.classList.contains(this.getAttribute("tabname"))) {
-		gradioApp().getElementById(this.getAttribute("tabname") + "_images_history_renew_page").click();
-		tabs_box.classList.add(this.getAttribute("tabname"))
-	}	            
+    var tabs_box = gradioApp().getElementById("images_history_tab");
+    if (!tabs_box.classList.contains(this.getAttribute("tabname"))) {
+        gradioApp().getElementById(this.getAttribute("tabname") + "_images_history_renew_page").click();
+        tabs_box.classList.add(this.getAttribute("tabname"))
+    }                
 }
 
 var images_history_close_full_view = function(){
-	var box = images_history_get_parent_by_class(this, "images_history_cantainor");
-	box.querySelector(".images_history_del_button").setAttribute("disabled", "disabled");
+    var box = images_history_get_parent_by_class(this, "images_history_cantainor");
+    box.querySelector(".images_history_del_button").setAttribute("disabled", "disabled");
+}
+
+function images_history_disabled_del(){
+    gradioApp().querySelectorAll(".images_history_del_button").forEach(function(btn){
+        btn.setAttribute('disabled','disabled');
+    }); 
 }
 
 function images_history_get_parent_by_class(item, class_name){
-	var parent = item.parentElement;
+    var parent = item.parentElement;
     while(!parent.classList.contains(class_name)){
         parent = parent.parentElement;
     }
@@ -39,14 +45,15 @@ function images_history_get_parent_by_class(item, class_name){
 }
 
 function images_history_get_parent_by_tagname(item, tagname){
-	var parent = item.parentElement;
-	tagname = tagname.toUpperCase()
+    var parent = item.parentElement;
+    tagname = tagname.toUpperCase()
     while(parent.tagName != tagname){
-    	console.log(parent.tagName, tagname)
+        console.log(parent.tagName, tagname)
         parent = parent.parentElement;
     }  
     return parent;
 }
+
 function images_history_hide_buttons(hidden_list, gallery){
     var buttons = gallery.querySelectorAll(".gallery-item");
     var num = 0;
@@ -54,7 +61,7 @@ function images_history_hide_buttons(hidden_list, gallery){
         if (e.style.display == "none"){
             num += 1;
         }
-    })
+    });
     if (num == hidden_list.length){
         setTimeout(images_history_hide_buttons, 10, hidden_list, gallery);
     } 
@@ -74,14 +81,15 @@ function images_history_set_image_info(button){
         if(e.style.display != "none"){
             i += 1;
         }        
-    })
+    });
     var gallery = images_history_get_parent_by_class(button, "images_history_cantainor");
     var set_btn = gallery.querySelector(".images_history_set_index");
-    set_btn.setAttribute("img_index", index);    
+    var curr_idx = set_btn.getAttribute("img_index", index);  
+    if (curr_idx != index) {
+        set_btn.setAttribute("img_index", index);        
+        images_history_disabled_del();
+    }
     set_btn.click();
-    gradioApp().querySelectorAll(".images_history_del_button").forEach(function(btn){
-    	btn.setAttribute('disabled','disabled');
-    })
     
 }
 
@@ -102,24 +110,24 @@ function images_history_delete(tabname, img_path, img_file_name, page_index, fil
         if (e.style.display != 'none'){
             buttons.push(e);
         }
-    });
-    
+    });    
     var img_num = buttons.length / 2;
     if (img_num === 1){
         setTimeout(function(tabname){
             gradioApp().getElementById(tabname + '_images_history_renew_page').click();
         }, 30, tabname); 
-    } else {
+    } else {        
         buttons[image_index].style.display = 'none';
         buttons[image_index + img_num].style.display = 'none';
         var bnt;
         if (image_index >= img_num - 1){
             btn = buttons[img_num - 2];
-        } else {
+        } else {            
             btn = buttons[image_index + 1] ;          
-        }    
+        } 
         setTimeout(function(btn){btn.click()}, 30, btn);
-    }      
+    }
+    images_history_disabled_del();  
     return [tabname, img_path, img_file_name, page_index, filenames, image_index];
 }
 
@@ -132,61 +140,58 @@ function images_history_turnpage(img_path, page_index, image_index, tabname){
 }
 
 function images_history_enable_del_buttons(){
-	gradioApp().querySelectorAll(".images_history_del_button").forEach(function(btn){
-    	btn.removeAttribute('disabled');
+    gradioApp().querySelectorAll(".images_history_del_button").forEach(function(btn){
+        btn.removeAttribute('disabled');
     })
 }
 
 function images_history_init(){ 
-    if (gradioApp().getElementById('txt2img_images_history_renew_page') == null) {
-        setTimeout(images_history_init, 500);
-    } else {        
+    var load_txt2img_button = gradioApp().getElementById('txt2img_images_history_renew_page')
+    if (load_txt2img_button){        
         for (var i in images_history_tab_list ){
             tab = images_history_tab_list[i];
             gradioApp().getElementById(tab + '_images_history').classList.add("images_history_cantainor");
             gradioApp().getElementById(tab + '_images_history_set_index').classList.add("images_history_set_index");
             gradioApp().getElementById(tab + '_images_history_del_button').classList.add("images_history_del_button");
-            gradioApp().getElementById(tab + '_images_history_gallery').classList.add("images_history_gallery"); 
-           
-           	      
+            gradioApp().getElementById(tab + '_images_history_gallery').classList.add("images_history_gallery");            
+                     
         }
         var tabs_box = gradioApp().getElementById("tab_images_history").querySelector("div").querySelector("div").querySelector("div");
-        tabs_box.setAttribute("id", "images_history_tab");
-        tabs_box.classList.add(images_history_tab_list[0]);
-        gradioApp().getElementById("txt2img_images_history_renew_page").click();
-    }
+        tabs_box.setAttribute("id", "images_history_tab");        
+        var tab_btns = tabs_box.querySelectorAll("button");        
+        for (var i in images_history_tab_list){               
+            var tabname = images_history_tab_list[i]
+            tab_btns[i].setAttribute("tabname", tabname);
+            tab_btns[i].addEventListener('click', images_history_click_tab);
+        }    
+        tabs_box.classList.add(images_history_tab_list[0]);   
+           load_txt2img_button.click();
+    } else {
+        setTimeout(images_history_init, 500);
+    } 
 }
 
 var images_history_tab_list = ["txt2img", "img2img", "extras"];
-var images_history_start_flag = false;
-
-onUiUpdate(function(){
-	var tab = gradioApp().getElementById("images_history_tab");
-	if (tab) {
-		if (!images_history_start_flag){
-			images_history_init();
-			images_history_start_flag = true;
-		}
-	    var tab_btns = gradioApp().getElementById("images_history_tab").querySelectorAll("button");
-	    for (var i in images_history_tab_list ){
-	        var buttons = gradioApp().querySelectorAll('#' + images_history_tab_list[i] + '_images_history .gallery-item');
-	        buttons.forEach(function(bnt){    
-	            bnt.addEventListener('click', images_history_click_image, true);
-	         });
-	        var tabname = images_history_tab_list[i]
-	        tab_btns[i].setAttribute("tabname", tabname);
-	        tab_btns[i].addEventListener('click', images_history_click_tab, true);
+setTimeout(images_history_init, 500)
+document.addEventListener("DOMContentLoaded", function() {
+    var mutationObserver = new MutationObserver(function(m){
+        for (var i in images_history_tab_list ){
+            var buttons = gradioApp().querySelectorAll('#' + images_history_tab_list[i] + '_images_history .gallery-item');
+            buttons.forEach(function(bnt){    
+                bnt.addEventListener('click', images_history_click_image, true);
+            });
         // var cls_btn = gradioApp().getElementById(tabname + '_images_history_gallery').querySelector("svg");
         // if (cls_btn){
-        // 	cls_btn.addEventListener('click', images_history_close_full_view, false);
+        //     cls_btn.addEventListener('click', images_history_close_full_view, false);
         // }
         // console.log(cls_btn, cls_btn.parentElement.parentElement)
         // if (cls_btn) {
-        // 	cls_btn = images_history_get_parent_by_tagname(cls_btn, "BUTTON");
-        // 	cls_btn.addEventListener('click', images_history_close_full_view, true);
-        // }
-    }
+        //     cls_btn = images_history_get_parent_by_tagname(cls_btn, "BUTTON");
+        //     cls_btn.addEventListener('click', images_history_close_full_view, true);
+        }     
+    });
+    mutationObserver.observe( gradioApp(), { childList:true, subtree:true });
+
+});
 
-    }
-});    
 
diff --git a/modules/images_history.py b/modules/images_history.py
index 2bc4b7ee..1bca0ad9 100644
--- a/modules/images_history.py
+++ b/modules/images_history.py
@@ -61,7 +61,7 @@ def delete_image(tabname, dir_name, name, page_index, filenames, image_index):
         os.remove(path)
         txt_file = os.path.splitext(path)[0]  + ".txt"
         if os.path.exists(txt_file):
-        	os.remove(txt_file)
+            os.remove(txt_file)
         new_file_list = []
         for f in filenames:
             if f == name:
@@ -88,7 +88,7 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict):
             end_page = gr.Button('End Page')    
         with gr.Row(elem_id=tabname + "_images_history"):            
             with gr.Row():     
-                with gr.Column(scale=2):                	
+                with gr.Column(scale=2):                    
                     history_gallery = gr.Gallery(show_label=False, elem_id=tabname + "_images_history_gallery").style(grid=6)
                     delete = gr.Button('Delete',  elem_id=tabname + "_images_history_del_button")
                 with gr.Column():     
@@ -126,9 +126,10 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict):
 
         #other funcitons
         set_index.click(show_image_info, _js="images_history_get_current_img", inputs=[tabname_box,  img_path, filenames], outputs=[img_file_name, image_index, hide_image])
+        img_file_name.change(fn=None, _js="images_history_enable_del_buttons", inputs=None, outputs=None)
         delete.click(delete_image,_js="images_history_delete", inputs=[tabname_box, img_path, img_file_name, page_index, filenames, image_index], outputs=[page_index, filenames]) 
         hide_image.change(fn=run_pnginfo, inputs=[hide_image], outputs=[info1, img_file_info, info2])
-        hide_image.change(fn=None, _js="images_history_enable_del_buttons", inputs=None, outputs=None)
+       
         #pnginfo.click(fn=run_pnginfo, inputs=[hide_image], outputs=[info1, img_file_info, info2])
         switch_dict["fn"](pnginfo_send_to_txt2img, switch_dict["t2i"], img_file_info, 'switch_to_txt2img')
         switch_dict["fn"](pnginfo_send_to_img2img, switch_dict["i2i"], img_file_info, 'switch_to_img2img_img2img')
diff --git a/modules/ui.py b/modules/ui.py
index 94297ba6..8cd12b51 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -39,7 +39,7 @@ import modules.generation_parameters_copypaste
 from modules import prompt_parser
 from modules.images import save_image
 import modules.textual_inversion.ui
-import modules.hypernetwork.ui
+import modules.hypernetworks.ui
 import modules.images_history as img_his
 
 # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI
@@ -554,6 +554,7 @@ def create_ui(wrap_gradio_gpu_call):
                     custom_inputs = modules.scripts.scripts_txt2img.setup_ui(is_img2img=False)
 
             with gr.Column(variant='panel'):
+
                 with gr.Group():
                     txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False)
                     txt2img_gallery = gr.Gallery(label='Output', show_label=False, elem_id='txt2img_gallery').style(grid=4)
@@ -573,9 +574,9 @@ def create_ui(wrap_gradio_gpu_call):
                     with gr.Row():
                         download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
 
-                with gr.Group():
-                    html_info = gr.HTML()
-                    generation_info = gr.Textbox(visible=False)
+                    with gr.Group():
+                        html_info = gr.HTML()
+                        generation_info = gr.Textbox(visible=False)
 
             connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
             connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
@@ -669,7 +670,6 @@ def create_ui(wrap_gradio_gpu_call):
             ]
             modules.generation_parameters_copypaste.connect_paste(paste, txt2img_paste_fields, txt2img_prompt)
             token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter])
-        
 
     with gr.Blocks(analytics_enabled=False) as img2img_interface:
         img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=True)
@@ -762,10 +762,10 @@ def create_ui(wrap_gradio_gpu_call):
                     with gr.Row():
                         download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
 
-                with gr.Group():
-                    html_info = gr.HTML()
-                    generation_info = gr.Textbox(visible=False)
-                
+                    with gr.Group():
+                        html_info = gr.HTML()
+                        generation_info = gr.Textbox(visible=False)
+
             connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
             connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
 
@@ -1016,6 +1016,13 @@ def create_ui(wrap_gradio_gpu_call):
             inputs=[image],
             outputs=[html, generation_info, html2],
         )
+    #images history
+    images_history_switch_dict = {
+        "fn":modules.generation_parameters_copypaste.connect_paste,
+        "t2i":txt2img_paste_fields,
+        "i2i":img2img_paste_fields
+    }
+    images_history = img_his.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) 
 
     with gr.Blocks() as modelmerger_interface:
         with gr.Row().style(equal_height=False):
@@ -1285,16 +1292,7 @@ Requested path was: {f}
 
         opts.save(shared.config_filename)
 
-        return f'{changed} settings changed.', opts.dumpjson()    
-
-    #images history
-    images_history_switch_dict = {
-        "fn":modules.generation_parameters_copypaste.connect_paste,
-        "t2i":txt2img_paste_fields,
-        "i2i":img2img_paste_fields
-    }
-    images_history = img_his.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict)    
-    
+        return f'{changed} settings changed.', opts.dumpjson()
 
     def run_settings_single(value, key):
         if not opts.same_type(value, opts.data_labels[key].default):
@@ -1393,11 +1391,10 @@ Requested path was: {f}
         (img2img_interface, "img2img", "img2img"),
         (extras_interface, "Extras", "extras"),
         (pnginfo_interface, "PNG Info", "pnginfo"),
-        (modelmerger_interface, "Checkpoint Merger", "modelmerger"),
         (images_history, "History", "images_history"),
+        (modelmerger_interface, "Checkpoint Merger", "modelmerger"),
         (train_interface, "Train", "ti"),
         (settings_interface, "Settings", "settings"),
-
     ]
 
     with open(os.path.join(script_path, "style.css"), "r", encoding="utf8") as file:
@@ -1616,3 +1613,4 @@ if 'gradio_routes_templates_response' not in globals():
 
     gradio_routes_templates_response = gradio.routes.templates.TemplateResponse
     gradio.routes.templates.TemplateResponse = template_response
+
-- 
cgit v1.2.3


From a2aa2a68bc7868320b502a78765be597e507ce45 Mon Sep 17 00:00:00 2001
From: yfszzx <yfszzx@gmail.com>
Date: Thu, 13 Oct 2022 00:21:16 +0800
Subject: images history improvement

---
 modules/images_history.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/modules/images_history.py b/modules/images_history.py
index 1bca0ad9..6408973c 100644
--- a/modules/images_history.py
+++ b/modules/images_history.py
@@ -1,7 +1,7 @@
 import os
 import shutil
 def get_recent_images(dir_name, page_index, step, image_index, tabname):
-    print(f"renew page {page_index}")
+    #print(f"renew page {page_index}")
     page_index = int(page_index)
     f_list = os.listdir(dir_name)
     file_list = []
@@ -51,7 +51,7 @@ def page_index_change(dir_name, page_index, image_index, tabname):
     return get_recent_images(dir_name, page_index, 0, image_index, tabname)
 
 def show_image_info(num, image_path, filenames):
-    print(f"select image {num}")
+    #print(f"select image {num}")
     file = filenames[int(num)]
     return file, num, os.path.join(image_path, file)
 def delete_image(tabname, dir_name, name, page_index, filenames, image_index):
-- 
cgit v1.2.3


From 717ba4c71c86cb2d49d731caeed82ce8bec0c057 Mon Sep 17 00:00:00 2001
From: yfszzx <yfszzx@gmail.com>
Date: Thu, 13 Oct 2022 00:27:45 +0800
Subject: images history improvement

---
 javascript/images_history.js | 2 +-
 style.css                    | 4 ++--
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/javascript/images_history.js b/javascript/images_history.js
index 620f242c..c5c2886e 100644
--- a/javascript/images_history.js
+++ b/javascript/images_history.js
@@ -172,7 +172,7 @@ function images_history_init(){
 }
 
 var images_history_tab_list = ["txt2img", "img2img", "extras"];
-setTimeout(images_history_init, 500)
+setTimeout(images_history_init, 500);
 document.addEventListener("DOMContentLoaded", function() {
     var mutationObserver = new MutationObserver(function(m){
         for (var i in images_history_tab_list ){
diff --git a/style.css b/style.css
index 7704e7bd..c75dce4c 100644
--- a/style.css
+++ b/style.css
@@ -20,7 +20,7 @@
     padding-right: 0.25em;
     margin: 0.1em 0;
     opacity: 0%;
-    cursor: default;	
+    cursor: default;    
 }
 
 .output-html p {margin: 0 0.5em;}
@@ -442,7 +442,7 @@ input[type="range"]{
 }
 
 .red {
-	color: red;
+    color: red;
 }
 
 .gallery-item {
-- 
cgit v1.2.3


From c3c8eef9fd5a0c8b26319e32ca4a19b56204e6df Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 12 Oct 2022 20:49:47 +0300
Subject: train: change filename processing to be more simple and configurable
 train: make it possible to make text files with prompts train: rework
 scheduler so that there's less repeating code in textual inversion and
 hypernets train: move epochs setting to options

---
 javascript/hints.js                            |  3 ++
 modules/hypernetworks/hypernetwork.py          | 40 +++++++++-------------
 modules/shared.py                              |  3 ++
 modules/textual_inversion/dataset.py           | 47 +++++++++++++++++++-------
 modules/textual_inversion/learn_schedule.py    | 37 +++++++++++++++++++-
 modules/textual_inversion/textual_inversion.py | 35 +++++++------------
 modules/ui.py                                  |  2 --
 7 files changed, 105 insertions(+), 62 deletions(-)

diff --git a/javascript/hints.js b/javascript/hints.js
index b81c181b..d51ee14c 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -81,6 +81,9 @@ titles = {
 
     "Eta noise seed delta": "If this values is non-zero, it will be added to seed and used to initialize RNG for noises when using samplers with Eta. You can use this to produce even more variation of images, or you can use this to match images of other software if you know what you are doing.",
     "Do not add watermark to images": "If this option is enabled, watermark will not be added to created images. Warning: if you do not add watermark, you may be behaving in an unethical manner.",
+
+    "Filename word regex": "This regular expression will be used extract words from filename, and they will be joined using the option below into label text used for training. Leave empty to keep filename text as it is.",
+    "Filename join string": "This string will be used to hoin split words into a single line if the option above is enabled.",
 }
 
 
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 8314450a..b6c06d49 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -14,7 +14,7 @@ import torch
 from torch import einsum
 from einops import rearrange, repeat
 import modules.textual_inversion.dataset
-from modules.textual_inversion.learn_schedule import LearnSchedule
+from modules.textual_inversion.learn_schedule import LearnRateScheduler
 
 
 class HypernetworkModule(torch.nn.Module):
@@ -223,31 +223,23 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
     if ititial_step > steps:
         return hypernetwork, filename
 
-    schedules = iter(LearnSchedule(learn_rate, steps, ititial_step))
-    (learn_rate, end_step) = next(schedules)
-    print(f'Training at rate of {learn_rate} until step {end_step}')
-
-    optimizer = torch.optim.AdamW(weights, lr=learn_rate)
+    scheduler = LearnRateScheduler(learn_rate, steps, ititial_step)
+    optimizer = torch.optim.AdamW(weights, lr=scheduler.learn_rate)
 
     pbar = tqdm.tqdm(enumerate(ds), total=steps - ititial_step)
-    for i, (x, text, cond) in pbar:
+    for i, entry in pbar:
         hypernetwork.step = i + ititial_step
 
-        if hypernetwork.step > end_step:
-            try:
-                (learn_rate, end_step) = next(schedules)
-            except Exception:
-                break
-            tqdm.tqdm.write(f'Training at rate of {learn_rate} until step {end_step}')
-            for pg in optimizer.param_groups:
-                pg['lr'] = learn_rate
+        scheduler.apply(optimizer, hypernetwork.step)
+        if scheduler.finished:
+            break
 
         if shared.state.interrupted:
             break
 
         with torch.autocast("cuda"):
-            cond = cond.to(devices.device)
-            x = x.to(devices.device)
+            cond = entry.cond.to(devices.device)
+            x = entry.latent.to(devices.device)
             loss = shared.sd_model(x.unsqueeze(0), cond)[0]
             del x
             del cond
@@ -267,7 +259,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
         if hypernetwork.step > 0 and images_dir is not None and hypernetwork.step % create_image_every == 0:
             last_saved_image = os.path.join(images_dir, f'{hypernetwork_name}-{hypernetwork.step}.png')
 
-            preview_text = text if preview_image_prompt == "" else preview_image_prompt
+            preview_text = entry.cond_text if preview_image_prompt == "" else preview_image_prompt
 
             optimizer.zero_grad()
             shared.sd_model.cond_stage_model.to(devices.device)
@@ -282,16 +274,16 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
             )
 
             processed = processing.process_images(p)
-            image = processed.images[0]
+            image = processed.images[0] if len(processed.images)>0 else None
 
             if unload:
                 shared.sd_model.cond_stage_model.to(devices.cpu)
                 shared.sd_model.first_stage_model.to(devices.cpu)
 
-            shared.state.current_image = image
-            image.save(last_saved_image)
-
-            last_saved_image += f", prompt: {preview_text}"
+            if image is not None:
+                shared.state.current_image = image
+                image.save(last_saved_image)
+                last_saved_image += f", prompt: {preview_text}"
 
         shared.state.job_no = hypernetwork.step
 
@@ -299,7 +291,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
 <p>
 Loss: {losses.mean():.7f}<br/>
 Step: {hypernetwork.step}<br/>
-Last prompt: {html.escape(text)}<br/>
+Last prompt: {html.escape(entry.cond_text)}<br/>
 Last saved embedding: {html.escape(last_saved_file)}<br/>
 Last saved image: {html.escape(last_saved_image)}<br/>
 </p>
diff --git a/modules/shared.py b/modules/shared.py
index 42e99741..e64e69fc 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -231,6 +231,9 @@ options_templates.update(options_section(('system', "System"), {
 
 options_templates.update(options_section(('training', "Training"), {
     "unload_models_when_training": OptionInfo(False, "Unload VAE and CLIP from VRAM when training"),
+    "dataset_filename_word_regex": OptionInfo("", "Filename word regex"),
+    "dataset_filename_join_string": OptionInfo(" ", "Filename join string"),
+    "training_image_repeats_per_epoch": OptionInfo(100, "Number of repeats for a single input image per epoch; used only for displaying epoch number", gr.Number, {"precision": 0}),
 }))
 
 options_templates.update(options_section(('sd', "Stable Diffusion"), {
diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index f61f40d3..67e90afe 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -11,11 +11,21 @@ import tqdm
 from modules import devices, shared
 import re
 
-re_tag = re.compile(r"[a-zA-Z][_\w\d()]+")
+re_numbers_at_start = re.compile(r"^[-\d]+\s*")
+
+
+class DatasetEntry:
+    def __init__(self, filename=None, latent=None, filename_text=None):
+        self.filename = filename
+        self.latent = latent
+        self.filename_text = filename_text
+        self.cond = None
+        self.cond_text = None
 
 
 class PersonalizedBase(Dataset):
     def __init__(self, data_root, width, height, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None, include_cond=False):
+        re_word = re.compile(shared.opts.dataset_filename_word_regex) if len(shared.opts.dataset_filename_word_regex)>0 else None
 
         self.placeholder_token = placeholder_token
 
@@ -42,9 +52,18 @@ class PersonalizedBase(Dataset):
             except Exception:
                 continue
 
+            text_filename = os.path.splitext(path)[0] + ".txt"
             filename = os.path.basename(path)
-            filename_tokens = os.path.splitext(filename)[0]
-            filename_tokens = re_tag.findall(filename_tokens)
+
+            if os.path.exists(text_filename):
+                with open(text_filename, "r", encoding="utf8") as file:
+                    filename_text = file.read()
+            else:
+                filename_text = os.path.splitext(filename)[0]
+                filename_text = re.sub(re_numbers_at_start, '', filename_text)
+                if re_word:
+                    tokens = re_word.findall(filename_text)
+                    filename_text = (shared.opts.dataset_filename_join_string or "").join(tokens)
 
             npimage = np.array(image).astype(np.uint8)
             npimage = (npimage / 127.5 - 1.0).astype(np.float32)
@@ -55,13 +74,13 @@ class PersonalizedBase(Dataset):
             init_latent = model.get_first_stage_encoding(model.encode_first_stage(torchdata.unsqueeze(dim=0))).squeeze()
             init_latent = init_latent.to(devices.cpu)
 
+            entry = DatasetEntry(filename=path, filename_text=filename_text, latent=init_latent)
+
             if include_cond:
-                text = self.create_text(filename_tokens)
-                cond = cond_model([text]).to(devices.cpu)
-            else:
-                cond = None
+                entry.cond_text = self.create_text(filename_text)
+                entry.cond = cond_model([entry.cond_text]).to(devices.cpu)
 
-            self.dataset.append((init_latent, filename_tokens, cond))
+            self.dataset.append(entry)
 
         self.length = len(self.dataset) * repeats
 
@@ -72,10 +91,10 @@ class PersonalizedBase(Dataset):
     def shuffle(self):
         self.indexes = self.initial_indexes[torch.randperm(self.initial_indexes.shape[0])]
 
-    def create_text(self, filename_tokens):
+    def create_text(self, filename_text):
         text = random.choice(self.lines)
         text = text.replace("[name]", self.placeholder_token)
-        text = text.replace("[filewords]", ' '.join(filename_tokens))
+        text = text.replace("[filewords]", filename_text)
         return text
 
     def __len__(self):
@@ -86,7 +105,9 @@ class PersonalizedBase(Dataset):
             self.shuffle()
 
         index = self.indexes[i % len(self.indexes)]
-        x, filename_tokens, cond = self.dataset[index]
+        entry = self.dataset[index]
+
+        if entry.cond is None:
+            entry.cond_text = self.create_text(entry.filename_text)
 
-        text = self.create_text(filename_tokens)
-        return x, text, cond
+        return entry
diff --git a/modules/textual_inversion/learn_schedule.py b/modules/textual_inversion/learn_schedule.py
index db720271..2062726a 100644
--- a/modules/textual_inversion/learn_schedule.py
+++ b/modules/textual_inversion/learn_schedule.py
@@ -1,6 +1,12 @@
+import tqdm
 
-class LearnSchedule:
+
+class LearnScheduleIterator:
     def __init__(self, learn_rate, max_steps, cur_step=0):
+        """
+        specify learn_rate as "0.001:100, 0.00001:1000, 1e-5:10000" to have lr of 0.001 until step 100, 0.00001 until 1000, 1e-5:10000 until 10000
+        """
+
         pairs = learn_rate.split(',')
         self.rates = []
         self.it = 0
@@ -32,3 +38,32 @@ class LearnSchedule:
             return self.rates[self.it - 1]
         else:
             raise StopIteration
+
+
+class LearnRateScheduler:
+    def __init__(self, learn_rate, max_steps, cur_step=0, verbose=True):
+        self.schedules = LearnScheduleIterator(learn_rate, max_steps, cur_step)
+        (self.learn_rate,  self.end_step) = next(self.schedules)
+        self.verbose = verbose
+
+        if self.verbose:
+            print(f'Training at rate of {self.learn_rate} until step {self.end_step}')
+
+        self.finished = False
+
+    def apply(self, optimizer, step_number):
+        if step_number <= self.end_step:
+            return
+
+        try:
+            (self.learn_rate, self.end_step) = next(self.schedules)
+        except Exception:
+            self.finished = True
+            return
+
+        if self.verbose:
+            tqdm.tqdm.write(f'Training at rate of {self.learn_rate} until step {self.end_step}')
+
+        for pg in optimizer.param_groups:
+            pg['lr'] = self.learn_rate
+
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index c5153e4a..fa0e33a2 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -11,7 +11,7 @@ from PIL import Image, PngImagePlugin
 
 from modules import shared, devices, sd_hijack, processing, sd_models
 import modules.textual_inversion.dataset
-from modules.textual_inversion.learn_schedule import LearnSchedule
+from modules.textual_inversion.learn_schedule import LearnRateScheduler
 
 from modules.textual_inversion.image_embedding import (embedding_to_b64, embedding_from_b64,
                                                        insert_image_data_embed, extract_image_data_embed,
@@ -172,8 +172,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'):
     return fn
 
 
-
-def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, num_repeats, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_image_prompt):
+def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_image_prompt):
     assert embedding_name, 'embedding not selected'
 
     shared.state.textinfo = "Initializing textual inversion training..."
@@ -205,7 +204,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
 
     shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
     with torch.autocast("cuda"):
-        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, height=training_height, repeats=num_repeats, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file)
+        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, height=training_height, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file)
 
     hijack = sd_hijack.model_hijack
 
@@ -221,32 +220,24 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
     if ititial_step > steps:
         return embedding, filename
 
-    schedules = iter(LearnSchedule(learn_rate, steps, ititial_step))
-    (learn_rate, end_step) = next(schedules)
-    print(f'Training at rate of {learn_rate} until step {end_step}')
-
-    optimizer = torch.optim.AdamW([embedding.vec], lr=learn_rate)
+    scheduler = LearnRateScheduler(learn_rate, steps, ititial_step)
+    optimizer = torch.optim.AdamW([embedding.vec], lr=scheduler.learn_rate)
 
     pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step)
-    for i, (x, text, _) in pbar:
+    for i, entry in pbar:
         embedding.step = i + ititial_step
 
-        if embedding.step > end_step:
-            try:
-                (learn_rate, end_step) = next(schedules)
-            except:
-                break
-            tqdm.tqdm.write(f'Training at rate of {learn_rate} until step {end_step}')
-            for pg in optimizer.param_groups:
-                pg['lr'] = learn_rate
+        scheduler.apply(optimizer, embedding.step)
+        if scheduler.finished:
+            break
 
         if shared.state.interrupted:
             break
 
         with torch.autocast("cuda"):
-            c = cond_model([text])
+            c = cond_model([entry.cond_text])
 
-            x = x.to(devices.device)
+            x = entry.latent.to(devices.device)
             loss = shared.sd_model(x.unsqueeze(0), c)[0]
             del x
 
@@ -268,7 +259,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
         if embedding.step > 0 and images_dir is not None and embedding.step % create_image_every == 0:
             last_saved_image = os.path.join(images_dir, f'{embedding_name}-{embedding.step}.png')
 
-            preview_text = text if preview_image_prompt == "" else preview_image_prompt
+            preview_text = entry.cond_text if preview_image_prompt == "" else preview_image_prompt
 
             p = processing.StableDiffusionProcessingTxt2Img(
                 sd_model=shared.sd_model,
@@ -314,7 +305,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
 <p>
 Loss: {losses.mean():.7f}<br/>
 Step: {embedding.step}<br/>
-Last prompt: {html.escape(text)}<br/>
+Last prompt: {html.escape(entry.cond_text)}<br/>
 Last saved embedding: {html.escape(last_saved_file)}<br/>
 Last saved image: {html.escape(last_saved_image)}<br/>
 </p>
diff --git a/modules/ui.py b/modules/ui.py
index 2b332267..c42535c8 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1098,7 +1098,6 @@ def create_ui(wrap_gradio_gpu_call):
                     training_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
                     training_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
                     steps = gr.Number(label='Max steps', value=100000, precision=0)
-                    num_repeats = gr.Number(label='Number of repeats for a single input image per epoch', value=100, precision=0)
                     create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0)
                     save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0)
                     save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True)
@@ -1176,7 +1175,6 @@ def create_ui(wrap_gradio_gpu_call):
                 training_width,
                 training_height,
                 steps,
-                num_repeats,
                 create_image_every,
                 save_embedding_every,
                 template_file,
-- 
cgit v1.2.3


From 698d303b04e293635bfb49c525409f3bcf671dce Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 12 Oct 2022 21:55:43 +0300
Subject: deepbooru: added option to use spaces or underscores deepbooru: added
 option to quote (\) in tags deepbooru/BLIP: write caption to file instead of
 image filename deepbooru/BLIP: now possible to use both for captions
 deepbooru: process is stopped even if an exception occurs

---
 modules/deepbooru.py                    | 65 ++++++++++++++++++-----
 modules/shared.py                       |  2 +
 modules/textual_inversion/preprocess.py | 92 ++++++++++++++-------------------
 modules/ui.py                           |  7 +--
 4 files changed, 95 insertions(+), 71 deletions(-)

diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index 29529949..419e6a9c 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -2,33 +2,44 @@ import os.path
 from concurrent.futures import ProcessPoolExecutor
 import multiprocessing
 import time
+import re
+
+re_special = re.compile(r'([\\()])')
 
 def get_deepbooru_tags(pil_image):
     """
     This method is for running only one image at a time for simple use.  Used to the img2img interrogate.
     """
     from modules import shared  # prevents circular reference
-    create_deepbooru_process(shared.opts.interrogate_deepbooru_score_threshold, shared.opts.deepbooru_sort_alpha)
-    shared.deepbooru_process_return["value"] = -1
-    shared.deepbooru_process_queue.put(pil_image)
-    while shared.deepbooru_process_return["value"] == -1:
-        time.sleep(0.2)
-    tags = shared.deepbooru_process_return["value"]
-    release_process()
-    return tags
 
+    try:
+        create_deepbooru_process(shared.opts.interrogate_deepbooru_score_threshold, create_deepbooru_opts())
+        return get_tags_from_process(pil_image)
+    finally:
+        release_process()
+
+
+def create_deepbooru_opts():
+    from modules import shared
 
-def deepbooru_process(queue, deepbooru_process_return, threshold, alpha_sort):
+    return {
+        "use_spaces": shared.opts.deepbooru_use_spaces,
+        "use_escape": shared.opts.deepbooru_escape,
+        "alpha_sort": shared.opts.deepbooru_sort_alpha,
+    }
+
+
+def deepbooru_process(queue, deepbooru_process_return, threshold, deepbooru_opts):
     model, tags = get_deepbooru_tags_model()
     while True: # while process is running, keep monitoring queue for new image
         pil_image = queue.get()
         if pil_image == "QUIT":
             break
         else:
-            deepbooru_process_return["value"] = get_deepbooru_tags_from_model(model, tags, pil_image, threshold, alpha_sort)
+            deepbooru_process_return["value"] = get_deepbooru_tags_from_model(model, tags, pil_image, threshold, deepbooru_opts)
 
 
-def create_deepbooru_process(threshold, alpha_sort):
+def create_deepbooru_process(threshold, deepbooru_opts):
     """
     Creates deepbooru process.  A queue is created to send images into the process.  This enables multiple images
     to be processed in a row without reloading the model or creating a new process.  To return the data, a shared
@@ -41,10 +52,23 @@ def create_deepbooru_process(threshold, alpha_sort):
     shared.deepbooru_process_queue = shared.deepbooru_process_manager.Queue()
     shared.deepbooru_process_return = shared.deepbooru_process_manager.dict()
     shared.deepbooru_process_return["value"] = -1
-    shared.deepbooru_process = multiprocessing.Process(target=deepbooru_process, args=(shared.deepbooru_process_queue, shared.deepbooru_process_return, threshold, alpha_sort))
+    shared.deepbooru_process = multiprocessing.Process(target=deepbooru_process, args=(shared.deepbooru_process_queue, shared.deepbooru_process_return, threshold, deepbooru_opts))
     shared.deepbooru_process.start()
 
 
+def get_tags_from_process(image):
+    from modules import shared
+
+    shared.deepbooru_process_return["value"] = -1
+    shared.deepbooru_process_queue.put(image)
+    while shared.deepbooru_process_return["value"] == -1:
+        time.sleep(0.2)
+    caption = shared.deepbooru_process_return["value"]
+    shared.deepbooru_process_return["value"] = -1
+
+    return caption
+
+
 def release_process():
     """
     Stops the deepbooru process to return used memory
@@ -81,10 +105,15 @@ def get_deepbooru_tags_model():
     return model, tags
 
 
-def get_deepbooru_tags_from_model(model, tags, pil_image, threshold, alpha_sort):
+def get_deepbooru_tags_from_model(model, tags, pil_image, threshold, deepbooru_opts):
     import deepdanbooru as dd
     import tensorflow as tf
     import numpy as np
+
+    alpha_sort = deepbooru_opts['alpha_sort']
+    use_spaces = deepbooru_opts['use_spaces']
+    use_escape = deepbooru_opts['use_escape']
+
     width = model.input_shape[2]
     height = model.input_shape[1]
     image = np.array(pil_image)
@@ -129,4 +158,12 @@ def get_deepbooru_tags_from_model(model, tags, pil_image, threshold, alpha_sort)
 
     print('\n'.join(sorted(result_tags_print, reverse=True)))
 
-    return ', '.join(result_tags_out).replace('_', ' ').replace(':', ' ')
+    tags_text = ', '.join(result_tags_out)
+
+    if use_spaces:
+        tags_text = tags_text.replace('_', ' ')
+
+    if use_escape:
+        tags_text = re.sub(re_special, r'\\\1', tags_text)
+
+    return tags_text.replace(':', ' ')
diff --git a/modules/shared.py b/modules/shared.py
index e64e69fc..78b73aae 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -260,6 +260,8 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"),
     "interrogate_clip_max_length": OptionInfo(48, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}),
     "interrogate_deepbooru_score_threshold": OptionInfo(0.5, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
     "deepbooru_sort_alpha": OptionInfo(True, "Interrogate: deepbooru sort alphabetically"),
+    "deepbooru_use_spaces": OptionInfo(False, "use spaces for tags in deepbooru"),
+    "deepbooru_escape": OptionInfo(True, "escape (\\) brackets in deepbooru (so they are used as literal brackets and not for emphasis)"),
 }))
 
 options_templates.update(options_section(('ui', "User interface"), {
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index 113cecf1..3047bede 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -10,7 +10,28 @@ from modules.shared import opts, cmd_opts
 if cmd_opts.deepdanbooru:
     import modules.deepbooru as deepbooru
 
+
 def preprocess(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption, process_caption_deepbooru=False):
+    try:
+        if process_caption:
+            shared.interrogator.load()
+
+        if process_caption_deepbooru:
+            deepbooru.create_deepbooru_process(opts.interrogate_deepbooru_score_threshold, deepbooru.create_deepbooru_opts())
+
+        preprocess_work(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption, process_caption_deepbooru)
+
+    finally:
+
+        if process_caption:
+            shared.interrogator.send_blip_to_ram()
+
+        if process_caption_deepbooru:
+            deepbooru.release_process()
+
+
+
+def preprocess_work(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption, process_caption_deepbooru=False):
     width = process_width
     height = process_height
     src = os.path.abspath(process_src)
@@ -25,30 +46,28 @@ def preprocess(process_src, process_dst, process_width, process_height, process_
     shared.state.textinfo = "Preprocessing..."
     shared.state.job_count = len(files)
 
-    if process_caption:
-        shared.interrogator.load()
-
-    if process_caption_deepbooru:
-        deepbooru.create_deepbooru_process(opts.interrogate_deepbooru_score_threshold, opts.deepbooru_sort_alpha)
-
     def save_pic_with_caption(image, index):
+        caption = ""
+
         if process_caption:
-            caption = "-" + shared.interrogator.generate_caption(image)
-            caption = sanitize_caption(os.path.join(dst, f"{index:05}-{subindex[0]}"), caption, ".png")
-        elif process_caption_deepbooru:
-            shared.deepbooru_process_return["value"] = -1
-            shared.deepbooru_process_queue.put(image)
-            while shared.deepbooru_process_return["value"] == -1:
-                time.sleep(0.2)
-            caption = "-" + shared.deepbooru_process_return["value"]
-            caption = sanitize_caption(os.path.join(dst, f"{index:05}-{subindex[0]}"), caption, ".png")
-            shared.deepbooru_process_return["value"] = -1
-        else:
-            caption = filename
-            caption = os.path.splitext(caption)[0]
-            caption = os.path.basename(caption)
+            caption += shared.interrogator.generate_caption(image)
+
+        if process_caption_deepbooru:
+            if len(caption) > 0:
+                caption += ", "
+            caption += deepbooru.get_tags_from_process(image)
+
+        filename_part = filename
+        filename_part = os.path.splitext(filename_part)[0]
+        filename_part = os.path.basename(filename_part)
+
+        basename = f"{index:05}-{subindex[0]}-{filename_part}"
+        image.save(os.path.join(dst, f"{basename}.png"))
+
+        if len(caption) > 0:
+            with open(os.path.join(dst, f"{basename}.txt"), "w", encoding="utf8") as file:
+                file.write(caption)
 
-        image.save(os.path.join(dst, f"{index:05}-{subindex[0]}{caption}.png"))
         subindex[0] += 1
 
     def save_pic(image, index):
@@ -93,34 +112,3 @@ def preprocess(process_src, process_dst, process_width, process_height, process_
             save_pic(img, index)
 
         shared.state.nextjob()
-
-    if process_caption:
-        shared.interrogator.send_blip_to_ram()
-
-    if process_caption_deepbooru:
-        deepbooru.release_process()
-
-
-def sanitize_caption(base_path, original_caption, suffix):
-    operating_system = platform.system().lower()
-    if (operating_system == "windows"):
-        invalid_path_characters = "\\/:*?\"<>|"
-        max_path_length = 259
-    else:
-        invalid_path_characters = "/" #linux/macos
-        max_path_length = 1023
-    caption = original_caption
-    for invalid_character in invalid_path_characters:
-        caption = caption.replace(invalid_character, "")
-    fixed_path_length = len(base_path) + len(suffix) 
-    if fixed_path_length + len(caption) <= max_path_length:
-        return caption
-    caption_tokens = caption.split()
-    new_caption = ""
-    for token in caption_tokens:
-        last_caption = new_caption
-        new_caption = new_caption + token + " "
-        if (len(new_caption) + fixed_path_length - 1  > max_path_length):
-            break
-    print(f"\nPath will be too long. Truncated caption: {original_caption}\nto: {last_caption}", file=sys.stderr)
-    return last_caption.strip()
diff --git a/modules/ui.py b/modules/ui.py
index c42535c8..e07ee0e1 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1074,11 +1074,8 @@ def create_ui(wrap_gradio_gpu_call):
                     with gr.Row():
                         process_flip = gr.Checkbox(label='Create flipped copies')
                         process_split = gr.Checkbox(label='Split oversized images into two')
-                        process_caption = gr.Checkbox(label='Use BLIP caption as filename')
-                        if cmd_opts.deepdanbooru:
-                            process_caption_deepbooru = gr.Checkbox(label='Use deepbooru caption as filename')
-                        else:
-                            process_caption_deepbooru = gr.Checkbox(label='Use deepbooru caption as filename', visible=False)
+                        process_caption = gr.Checkbox(label='Use BLIP for caption')
+                        process_caption_deepbooru = gr.Checkbox(label='Use deepbooru for caption', visible=True if cmd_opts.deepdanbooru else False)
 
                     with gr.Row():
                         with gr.Column(scale=3):
-- 
cgit v1.2.3


From efefa4862c6c75115d3da9f768348630cc32bdea Mon Sep 17 00:00:00 2001
From: Greg Fuller <gfuller23@gmail.com>
Date: Wed, 12 Oct 2022 13:03:00 -0700
Subject: [1/?] [wip] Reintroduce opts.interrogate_return_ranks

looks functionally correct, needs testing

Needs particular testing care around whether the colon usage (:) will break anything in whatever new use cases were introduced by https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/2143
---
 modules/deepbooru.py | 25 ++++++++++++++-----------
 1 file changed, 14 insertions(+), 11 deletions(-)

diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index 419e6a9c..2cbf2cab 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -26,6 +26,7 @@ def create_deepbooru_opts():
         "use_spaces": shared.opts.deepbooru_use_spaces,
         "use_escape": shared.opts.deepbooru_escape,
         "alpha_sort": shared.opts.deepbooru_sort_alpha,
+        "include_ranks": shared.opts.interrogate_return_ranks,
     }
 
 
@@ -113,6 +114,7 @@ def get_deepbooru_tags_from_model(model, tags, pil_image, threshold, deepbooru_o
     alpha_sort = deepbooru_opts['alpha_sort']
     use_spaces = deepbooru_opts['use_spaces']
     use_escape = deepbooru_opts['use_escape']
+    include_ranks = deepbooru_opts['include_ranks']
 
     width = model.input_shape[2]
     height = model.input_shape[1]
@@ -151,19 +153,20 @@ def get_deepbooru_tags_from_model(model, tags, pil_image, threshold, deepbooru_o
     if alpha_sort:
         sort_ndx = 1
 
-    # sort by reverse by likelihood and normal for alpha
+    # sort by reverse by likelihood and normal for alpha, and format tag text as requested
     unsorted_tags_in_theshold.sort(key=lambda y: y[sort_ndx], reverse=(not alpha_sort))
     for weight, tag in unsorted_tags_in_theshold:
-        result_tags_out.append(tag)
+        # note: tag_outformat will still have a colon if include_ranks is True
+        tag_outformat = tag.replace(':', ' ')
+        if use_spaces:
+            tag_outformat = tag_outformat.replace('_', ' ')
+        if use_escape:
+            tag_outformat = re.sub(re_special, r'\\\1', tag_outformat)
+        if include_ranks:
+            use_escape += f":{weight:.3f}"
 
-    print('\n'.join(sorted(result_tags_print, reverse=True)))
-
-    tags_text = ', '.join(result_tags_out)
+        result_tags_out.append(tag_outformat)
 
-    if use_spaces:
-        tags_text = tags_text.replace('_', ' ')
-
-    if use_escape:
-        tags_text = re.sub(re_special, r'\\\1', tags_text)
+    print('\n'.join(sorted(result_tags_print, reverse=True)))
 
-    return tags_text.replace(':', ' ')
+    return ', '.join(result_tags_out)
-- 
cgit v1.2.3


From f776254b12361b5bae16f6629bcdcb47b450c48d Mon Sep 17 00:00:00 2001
From: Greg Fuller <gfuller23@gmail.com>
Date: Wed, 12 Oct 2022 13:08:06 -0700
Subject: [2/?] [wip] ignore OPT_INCLUDE_RANKS for training filenames

---
 modules/deepbooru.py                    | 3 ++-
 modules/textual_inversion/preprocess.py | 4 +++-
 2 files changed, 5 insertions(+), 2 deletions(-)

diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index 2cbf2cab..fcc05819 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -19,6 +19,7 @@ def get_deepbooru_tags(pil_image):
         release_process()
 
 
+OPT_INCLUDE_RANKS = "include_ranks"
 def create_deepbooru_opts():
     from modules import shared
 
@@ -26,7 +27,7 @@ def create_deepbooru_opts():
         "use_spaces": shared.opts.deepbooru_use_spaces,
         "use_escape": shared.opts.deepbooru_escape,
         "alpha_sort": shared.opts.deepbooru_sort_alpha,
-        "include_ranks": shared.opts.interrogate_return_ranks,
+        OPT_INCLUDE_RANKS: shared.opts.interrogate_return_ranks,
     }
 
 
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index 3047bede..886cf0c3 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -17,7 +17,9 @@ def preprocess(process_src, process_dst, process_width, process_height, process_
             shared.interrogator.load()
 
         if process_caption_deepbooru:
-            deepbooru.create_deepbooru_process(opts.interrogate_deepbooru_score_threshold, deepbooru.create_deepbooru_opts())
+            db_opts = deepbooru.create_deepbooru_opts()
+            db_opts[deepbooru.OPT_INCLUDE_RANKS] = False
+            deepbooru.create_deepbooru_process(opts.interrogate_deepbooru_score_threshold, db_opts)
 
         preprocess_work(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption, process_caption_deepbooru)
 
-- 
cgit v1.2.3


From 514456101b142b47acf87f6de95bad1a23d73be7 Mon Sep 17 00:00:00 2001
From: Greg Fuller <gfuller23@gmail.com>
Date: Wed, 12 Oct 2022 13:14:13 -0700
Subject: [3/?] [wip] fix incorrect variable reference

still needs testing
---
 modules/deepbooru.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index fcc05819..c2004696 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -164,7 +164,7 @@ def get_deepbooru_tags_from_model(model, tags, pil_image, threshold, deepbooru_o
         if use_escape:
             tag_outformat = re.sub(re_special, r'\\\1', tag_outformat)
         if include_ranks:
-            use_escape += f":{weight:.3f}"
+            tag_outformat += f":{weight:.3f}"
 
         result_tags_out.append(tag_outformat)
 
-- 
cgit v1.2.3


From 1cfc2a18981ee56bdb69a2de7b463a11ad05e329 Mon Sep 17 00:00:00 2001
From: Melan <alexleander91@gmail.com>
Date: Wed, 12 Oct 2022 23:36:29 +0200
Subject: Save a csv containing the loss while training

---
 modules/hypernetworks/hypernetwork.py          | 17 ++++++++++++++++-
 modules/textual_inversion/textual_inversion.py | 17 ++++++++++++++++-
 modules/ui.py                                  |  3 +++
 3 files changed, 35 insertions(+), 2 deletions(-)

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index b6c06d49..6522078f 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -5,6 +5,7 @@ import os
 import sys
 import traceback
 import tqdm
+import csv
 
 import torch
 
@@ -174,7 +175,7 @@ def attention_CrossAttention_forward(self, x, context=None, mask=None):
     return self.to_out(out)
 
 
-def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_image_prompt):
+def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, write_csv_every, template_file, preview_image_prompt):
     assert hypernetwork_name, 'hypernetwork not selected'
 
     path = shared.hypernetworks.get(hypernetwork_name, None)
@@ -256,6 +257,20 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
             last_saved_file = os.path.join(hypernetwork_dir, f'{hypernetwork_name}-{hypernetwork.step}.pt')
             hypernetwork.save(last_saved_file)
 
+        print(f"{write_csv_every} > {hypernetwork.step % write_csv_every == 0}, {write_csv_every}")
+        if write_csv_every > 0 and hypernetwork_dir is not None and hypernetwork.step % write_csv_every == 0:
+            write_csv_header = False if os.path.exists(os.path.join(hypernetwork_dir, "hypernetwork_loss.csv")) else True
+            
+            with open(os.path.join(hypernetwork_dir, "hypernetwork_loss.csv"), "a+") as fout:
+
+                csv_writer = csv.DictWriter(fout, fieldnames=["step", "loss"])
+                
+                if write_csv_header:
+                    csv_writer.writeheader()
+
+                csv_writer.writerow({"step": hypernetwork.step, 
+                    "loss": f"{losses.mean():.7f}"})
+
         if hypernetwork.step > 0 and images_dir is not None and hypernetwork.step % create_image_every == 0:
             last_saved_image = os.path.join(images_dir, f'{hypernetwork_name}-{hypernetwork.step}.png')
 
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index fa0e33a2..25038a89 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -6,6 +6,7 @@ import torch
 import tqdm
 import html
 import datetime
+import csv
 
 from PIL import Image, PngImagePlugin
 
@@ -172,7 +173,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'):
     return fn
 
 
-def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_image_prompt):
+def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, write_csv_every, template_file, save_image_with_stored_embedding, preview_image_prompt):
     assert embedding_name, 'embedding not selected'
 
     shared.state.textinfo = "Initializing textual inversion training..."
@@ -256,6 +257,20 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
             last_saved_file = os.path.join(embedding_dir, f'{embedding_name}-{embedding.step}.pt')
             embedding.save(last_saved_file)
 
+        if write_csv_every > 0 and log_directory is not None and embedding.step % write_csv_every == 0:
+            write_csv_header = False if os.path.exists(os.path.join(log_directory, "textual_inversion_loss.csv")) else True
+
+            with open(os.path.join(log_directory, "textual_inversion_loss.csv"), "a+") as fout:
+
+                csv_writer = csv.DictWriter(fout, fieldnames=["epoch", "epoch_step", "loss"])
+                
+                if write_csv_header:
+                    csv_writer.writeheader()
+
+                csv_writer.writerow({"epoch": epoch_num + 1, 
+                    "epoch_step": epoch_step - 1, 
+                    "loss": f"{losses.mean():.7f}"})
+
         if embedding.step > 0 and images_dir is not None and embedding.step % create_image_every == 0:
             last_saved_image = os.path.join(images_dir, f'{embedding_name}-{embedding.step}.png')
 
diff --git a/modules/ui.py b/modules/ui.py
index e07ee0e1..1195c2f1 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1096,6 +1096,7 @@ def create_ui(wrap_gradio_gpu_call):
                     training_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
                     steps = gr.Number(label='Max steps', value=100000, precision=0)
                     create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0)
+                    write_csv_every = gr.Number(label='Save an csv containing the loss to log directory every N steps, 0 to disable', value=500, precision=0)
                     save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0)
                     save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True)
                     preview_image_prompt = gr.Textbox(label='Preview prompt', value="")
@@ -1174,6 +1175,7 @@ def create_ui(wrap_gradio_gpu_call):
                 steps,
                 create_image_every,
                 save_embedding_every,
+                write_csv_every,
                 template_file,
                 save_image_with_stored_embedding,
                 preview_image_prompt,
@@ -1195,6 +1197,7 @@ def create_ui(wrap_gradio_gpu_call):
                 steps,
                 create_image_every,
                 save_embedding_every,
+                write_csv_every,
                 template_file,
                 preview_image_prompt,
             ],
-- 
cgit v1.2.3


From 54e0051bdd7dea7348825c09600ec61ea0771cb8 Mon Sep 17 00:00:00 2001
From: d8ahazard <d8ahazard@gmail.com>
Date: Wed, 12 Oct 2022 18:17:26 -0500
Subject: Add drag/drop param loading.

Drop an image or generational text onto the prompt bar, it loads the info for parsing.
---
 javascript/dragdrop.js    |  3 +++
 javascript/imageParams.js | 22 ++++++++++++++++++++++
 modules/images.py         | 20 ++++++++++++++++++++
 modules/ui.py             | 30 +++++++++++++++++++++++++++++-
 4 files changed, 74 insertions(+), 1 deletion(-)
 create mode 100644 javascript/imageParams.js

diff --git a/javascript/dragdrop.js b/javascript/dragdrop.js
index 5aac57f7..cf900f50 100644
--- a/javascript/dragdrop.js
+++ b/javascript/dragdrop.js
@@ -53,6 +53,9 @@ window.document.addEventListener('dragover', e => {
 
 window.document.addEventListener('drop', e => {
     const target = e.composedPath()[0];
+    if (target.placeholder === "Prompt") {
+        return;
+    }
     const imgWrap = target.closest('[data-testid="image"]');
     if ( !imgWrap ) {
         return;
diff --git a/javascript/imageParams.js b/javascript/imageParams.js
new file mode 100644
index 00000000..f9d0c0aa
--- /dev/null
+++ b/javascript/imageParams.js
@@ -0,0 +1,22 @@
+window.onload = (function(){
+    window.addEventListener('drop', e => {
+        const target = e.composedPath()[0];
+        const idx = selected_gallery_index();
+        let prompt_target = "txt2img_prompt_image";
+        if (idx === 1) {
+            prompt_target = "img2img_prompt_image";
+        }
+        if (target.placeholder === "Prompt") {
+            e.stopPropagation();
+            e.preventDefault();
+            const imgParent = gradioApp().getElementById(prompt_target);
+            const files = e.dataTransfer.files;
+            const fileInput = imgParent.querySelector('input[type="file"]');
+            if ( fileInput ) {
+                fileInput.files = files;
+                fileInput.dispatchEvent(new Event('change'));
+            }
+        }
+    });
+
+});
\ No newline at end of file
diff --git a/modules/images.py b/modules/images.py
index c0a90676..f1155b7f 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -463,3 +463,23 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i
         txt_fullfn = None
 
     return fullfn, txt_fullfn
+
+
+def image_data(image_path):
+    file, ext = os.path.splitext(image_path.name)
+    data = {}
+    if "png" in ext:
+        image = Image.open(image_path.name, "r")
+        print(f"Image data requested for {image_path.name} {image.format} of {type(image)}")
+        try:
+            data = image.text["parameters"]
+        except Exception as e:
+            print(f"Exception: {e}")
+            pass
+        print(f"Image data: {data}")
+    if "txt" in ext:
+        myfile = open(image_path.name, 'r')
+        data = myfile.read()
+        myfile.close()
+
+    return data, None
diff --git a/modules/ui.py b/modules/ui.py
index 2b332267..dd793c39 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -431,7 +431,6 @@ def create_toprow(is_img2img):
                 with gr.Column(scale=80):
                     with gr.Row():
                         prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, placeholder="Prompt", lines=2)
-
                 with gr.Column(scale=1, elem_id="roll_col"):
                     roll = gr.Button(value=art_symbol, elem_id="roll", visible=len(shared.artist_db.artists) > 0)
                     paste = gr.Button(value=paste_symbol, elem_id="paste")
@@ -513,6 +512,7 @@ def create_ui(wrap_gradio_gpu_call):
     with gr.Blocks(analytics_enabled=False) as txt2img_interface:
         txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=False)
         dummy_component = gr.Label(visible=False)
+        txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="file", visible=False)
 
         with gr.Row(elem_id='txt2img_progress_row'):
             with gr.Column(scale=1):
@@ -614,6 +614,18 @@ def create_ui(wrap_gradio_gpu_call):
             txt2img_prompt.submit(**txt2img_args)
             submit.click(**txt2img_args)
 
+            txt_prompt_img.change(
+                fn=modules.images.image_data,
+                # _js = "get_extras_tab_index",
+                inputs=[
+                    txt_prompt_img
+                ],
+                outputs=[
+                    txt2img_prompt,
+                    txt_prompt_img
+                ]
+            )
+
             enable_hr.change(
                 fn=lambda x: gr_show(x),
                 inputs=[enable_hr],
@@ -674,6 +686,9 @@ def create_ui(wrap_gradio_gpu_call):
         img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=True)
 
         with gr.Row(elem_id='img2img_progress_row'):
+            img2img_prompt_img = gr.File(label="", elem_id="txt_prompt_image", file_count="single", type="file",
+                                         visible=False)
+
             with gr.Column(scale=1):
                 pass
 
@@ -768,6 +783,18 @@ def create_ui(wrap_gradio_gpu_call):
             connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
             connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
 
+            img2img_prompt_img.change(
+                fn=modules.images.image_data,
+                # _js = "get_extras_tab_index",
+                inputs=[
+                    txt_prompt_img
+                ],
+                outputs=[
+                    img2img_prompt,
+                    img2img_prompt_img
+                ]
+            )
+
             mask_mode.change(
                 lambda mode, img: {
                     init_img_with_mask: gr_show(mode == 0),
@@ -956,6 +983,7 @@ def create_ui(wrap_gradio_gpu_call):
                 button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else ''
                 open_extras_folder = gr.Button('Open output directory', elem_id=button_id)
 
+
         submit.click(
             fn=wrap_gradio_gpu_call(modules.extras.run_extras),
             _js="get_extras_tab_index",
-- 
cgit v1.2.3


From 716a9e034f1aff434083363b218bd6043a774fc2 Mon Sep 17 00:00:00 2001
From: yfszzx <yfszzx@gmail.com>
Date: Thu, 13 Oct 2022 12:19:50 +0800
Subject: images history delete a number of images  consecutively next

---
 javascript/images_history.js | 24 +++++++++++++++---------
 modules/images_history.py    | 44 ++++++++++++++++++++++++--------------------
 2 files changed, 39 insertions(+), 29 deletions(-)

diff --git a/javascript/images_history.js b/javascript/images_history.js
index c5c2886e..8fa4a15e 100644
--- a/javascript/images_history.js
+++ b/javascript/images_history.js
@@ -101,7 +101,7 @@ function images_history_get_current_img(tabname, image_path, files){
     ];
 }
 
-function images_history_delete(tabname, img_path, img_file_name, page_index, filenames, image_index){
+function images_history_delete(del_num, tabname, img_path, img_file_name, page_index, filenames, image_index){
     image_index = parseInt(image_index);
     var tab = gradioApp().getElementById(tabname + '_images_history');
     var set_btn = tab.querySelector(".images_history_set_index");
@@ -112,23 +112,29 @@ function images_history_delete(tabname, img_path, img_file_name, page_index, fil
         }
     });    
     var img_num = buttons.length / 2;
-    if (img_num === 1){
+    if (img_num <= del_num){
         setTimeout(function(tabname){
             gradioApp().getElementById(tabname + '_images_history_renew_page').click();
         }, 30, tabname); 
-    } else {        
-        buttons[image_index].style.display = 'none';
-        buttons[image_index + img_num].style.display = 'none';
+    } else {
+        var next_img  
+        for (var i = 0; i < del_num; i++){
+            if (image_index + i < image_index + img_num){
+                buttons[image_index + i].style.display = 'none';
+                buttons[image_index + img_num + 1].style.display = 'none';
+                next_img = image_index + i + 1
+            }
+        }
         var bnt;
-        if (image_index >= img_num - 1){
-            btn = buttons[img_num - 2];
+        if (next_img  >= img_num){
+            btn = buttons[image_index - del_num];
         } else {            
-            btn = buttons[image_index + 1] ;          
+            btn = buttons[next_img];          
         } 
         setTimeout(function(btn){btn.click()}, 30, btn);
     }
     images_history_disabled_del();  
-    return [tabname, img_path, img_file_name, page_index, filenames, image_index];
+    return [del_num, tabname, img_path, img_file_name, page_index, filenames, image_index];
 }
 
 function images_history_turnpage(img_path, page_index, image_index, tabname){
diff --git a/modules/images_history.py b/modules/images_history.py
index 6408973c..f812ea4e 100644
--- a/modules/images_history.py
+++ b/modules/images_history.py
@@ -54,23 +54,26 @@ def show_image_info(num, image_path, filenames):
     #print(f"select image {num}")
     file = filenames[int(num)]
     return file, num, os.path.join(image_path, file)
-def delete_image(tabname, dir_name, name, page_index, filenames, image_index):
-    path = os.path.join(dir_name, name)           
-    if os.path.exists(path):        
-        print(f"Delete file {path}")
-        os.remove(path)
-        txt_file = os.path.splitext(path)[0]  + ".txt"
-        if os.path.exists(txt_file):
-            os.remove(txt_file)
-        new_file_list = []
-        for f in filenames:
-            if f == name:
-                continue
-            new_file_list.append(f)
-    else:
-        print(f"Not exists file {path}")
-        new_file_list = filenames
-    return page_index, new_file_list
+def delete_image(delete_num, tabname, dir_name, name, page_index, filenames, image_index):
+    delete_num = int(delete_num)
+    index = list(filenames).index(name)
+    i = 0
+    new_file_list = []
+    for name in filenames:
+        if i  >= index and i < index + delete_num:            
+            path = os.path.join(dir_name, name)
+            if os.path.exists(path):        
+                print(f"Delete file {path}")
+                os.remove(path)
+                txt_file = os.path.splitext(path)[0]  + ".txt"
+                if os.path.exists(txt_file):
+                    os.remove(txt_file)       
+            else:
+                print(f"Not exists file {path}")
+        else:
+            new_file_list.append(name)
+        i += 1
+    return page_index, new_file_list, 1
 
 def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict):
         if tabname == "txt2img":
@@ -90,10 +93,11 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict):
             with gr.Row():     
                 with gr.Column(scale=2):                    
                     history_gallery = gr.Gallery(show_label=False, elem_id=tabname + "_images_history_gallery").style(grid=6)
-                    delete = gr.Button('Delete',  elem_id=tabname + "_images_history_del_button")
+                    with gr.Row():
+                        delete = gr.Button('Delete',  elem_id=tabname + "_images_history_del_button")
+                        delete_num = gr.Number(value=1, interactive=True, label="number of images to delete consecutively next")                                           
                 with gr.Column():     
                     with gr.Row():          
-                        #pnginfo = gr.Button('PNG info')
                         pnginfo_send_to_txt2img = gr.Button('Send to txt2img')
                         pnginfo_send_to_img2img = gr.Button('Send to img2img')
                     with gr.Row():
@@ -127,7 +131,7 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict):
         #other funcitons
         set_index.click(show_image_info, _js="images_history_get_current_img", inputs=[tabname_box,  img_path, filenames], outputs=[img_file_name, image_index, hide_image])
         img_file_name.change(fn=None, _js="images_history_enable_del_buttons", inputs=None, outputs=None)
-        delete.click(delete_image,_js="images_history_delete", inputs=[tabname_box, img_path, img_file_name, page_index, filenames, image_index], outputs=[page_index, filenames]) 
+        delete.click(delete_image,_js="images_history_delete", inputs=[delete_num, tabname_box, img_path, img_file_name, page_index, filenames, image_index], outputs=[page_index, filenames, delete_num]) 
         hide_image.change(fn=run_pnginfo, inputs=[hide_image], outputs=[info1, img_file_info, info2])
        
         #pnginfo.click(fn=run_pnginfo, inputs=[hide_image], outputs=[info1, img_file_info, info2])
-- 
cgit v1.2.3


From 78592d404acba7db3baf8d78bdc19266906e684a Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 13 Oct 2022 07:40:03 +0300
Subject: remove interrogate option I accidentally deleted

---
 modules/shared.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/modules/shared.py b/modules/shared.py
index 78b73aae..9bda45c1 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -258,6 +258,7 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"),
     "interrogate_clip_num_beams": OptionInfo(1, "Interrogate: num_beams for BLIP", gr.Slider, {"minimum": 1, "maximum": 16, "step": 1}),
     "interrogate_clip_min_length": OptionInfo(24, "Interrogate: minimum description length (excluding artists, etc..)", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}),
     "interrogate_clip_max_length": OptionInfo(48, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}),
+    "interrogate_clip_dict_limit": OptionInfo(1500, "CLIP: maximum number of lines in text file (0 = No limit)"),
     "interrogate_deepbooru_score_threshold": OptionInfo(0.5, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
     "deepbooru_sort_alpha": OptionInfo(True, "Interrogate: deepbooru sort alphabetically"),
     "deepbooru_use_spaces": OptionInfo(False, "use spaces for tags in deepbooru"),
-- 
cgit v1.2.3


From 490494320ec8b5e1049c4ff35c3416258b75807b Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Thu, 13 Oct 2022 04:10:38 +0100
Subject: add missing id property

---
 javascript/contextMenus.js | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/javascript/contextMenus.js b/javascript/contextMenus.js
index 7636c4b3..fe67c42e 100644
--- a/javascript/contextMenus.js
+++ b/javascript/contextMenus.js
@@ -94,7 +94,7 @@ contextMenuInit = function(){
     }
     gradioApp().addEventListener("click", function(e) {
       let source = e.composedPath()[0]
-      if(source.id && source.indexOf('check_progress')>-1){
+      if(source.id && source.id.indexOf('check_progress')>-1){
         return
       }
       
-- 
cgit v1.2.3


From 04c0e643f2eec68d93a76db171b4d70595808702 Mon Sep 17 00:00:00 2001
From: Greg Fuller <gfuller23@gmail.com>
Date: Wed, 12 Oct 2022 22:13:53 -0700
Subject: Merge branch 'master' of
 https://github.com/HunterVacui/stable-diffusion-webui

---
 modules/deepbooru.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index c2004696..f34f3788 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -164,7 +164,7 @@ def get_deepbooru_tags_from_model(model, tags, pil_image, threshold, deepbooru_o
         if use_escape:
             tag_outformat = re.sub(re_special, r'\\\1', tag_outformat)
         if include_ranks:
-            tag_outformat += f":{weight:.3f}"
+            tag_outformat = f"({tag_outformat}:{weight:.3f})"
 
         result_tags_out.append(tag_outformat)
 
-- 
cgit v1.2.3


From e72adc999b3531370eafb9d316924ac497feb445 Mon Sep 17 00:00:00 2001
From: Trung Ngo <codem01@gmail.com>
Date: Sat, 8 Oct 2022 22:57:19 -0500
Subject: Restore last generation params

---
 .gitignore                                 | 1 +
 javascript/hints.js                        | 2 +-
 modules/generation_parameters_copypaste.py | 8 ++++++++
 modules/processing.py                      | 4 ++++
 4 files changed, 14 insertions(+), 1 deletion(-)

diff --git a/.gitignore b/.gitignore
index 7afc9395..69785b3e 100644
--- a/.gitignore
+++ b/.gitignore
@@ -17,6 +17,7 @@ __pycache__
 /webui.settings.bat
 /embeddings
 /styles.csv
+/params.txt
 /styles.csv.bak
 /webui-user.bat
 /webui-user.sh
diff --git a/javascript/hints.js b/javascript/hints.js
index d51ee14c..32f10fde 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -14,7 +14,7 @@ titles = {
     "\u{1f3b2}\ufe0f": "Set seed to -1, which will cause a new random number to be used every time",
     "\u267b\ufe0f": "Reuse seed from last generation, mostly useful if it was randomed",
     "\u{1f3a8}": "Add a random artist to the prompt.",
-    "\u2199\ufe0f": "Read generation parameters from prompt into user interface.",
+    "\u2199\ufe0f": "Read generation parameters from prompt or last generation if prompt is empty into user interface.",
     "\u{1f4c2}": "Open images output directory",
 
     "Inpaint a part of image": "Draw a mask over an image, and the script will regenerate the masked area with content according to prompt",
diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py
index ac1ba7f4..3e75aecc 100644
--- a/modules/generation_parameters_copypaste.py
+++ b/modules/generation_parameters_copypaste.py
@@ -1,5 +1,7 @@
+import os
 import re
 import gradio as gr
+from modules.shared import script_path
 
 re_param_code = r"\s*([\w ]+):\s*([^,]+)(?:,|$)"
 re_param = re.compile(re_param_code)
@@ -61,6 +63,12 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
 
 def connect_paste(button, paste_fields, input_comp, js=None):
     def paste_func(prompt):
+        if not prompt:
+            filename = os.path.join(script_path, "params.txt")
+            if os.path.exists(filename):
+                with open(filename, "r", encoding="utf8") as file:
+                    prompt = file.read()
+
         params = parse_generation_parameters(prompt)
         res = []
 
diff --git a/modules/processing.py b/modules/processing.py
index 698b3069..d5172f00 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -324,6 +324,10 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
     else:
         assert p.prompt is not None
 
+    with open(os.path.join(shared.script_path, "params.txt"), "w", encoding="utf8") as file:
+        processed = Processed(p, [], p.seed, "")
+        file.write(processed.infotext(p, 0))
+
     devices.torch_gc()
 
     seed = get_fixed_seed(p.seed)
-- 
cgit v1.2.3


From fde7fefa2ea23747f1107e3e46bf60c08a1134f1 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 13 Oct 2022 12:26:34 +0300
Subject: update #2336 to prevent reading params.txt when --hide-ui-dir-config
 option is enabled (for servers, since this will let some users access others'
 params)

---
 modules/generation_parameters_copypaste.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py
index 3e75aecc..c27826b6 100644
--- a/modules/generation_parameters_copypaste.py
+++ b/modules/generation_parameters_copypaste.py
@@ -2,6 +2,7 @@ import os
 import re
 import gradio as gr
 from modules.shared import script_path
+from modules import shared
 
 re_param_code = r"\s*([\w ]+):\s*([^,]+)(?:,|$)"
 re_param = re.compile(re_param_code)
@@ -63,7 +64,7 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
 
 def connect_paste(button, paste_fields, input_comp, js=None):
     def paste_func(prompt):
-        if not prompt:
+        if not prompt and not shared.cmd_opts.hide_ui_dir_config:
             filename = os.path.join(script_path, "params.txt")
             if os.path.exists(filename):
                 with open(filename, "r", encoding="utf8") as file:
-- 
cgit v1.2.3


From 94c01aa35656130b56f401830ad443ce3d97c364 Mon Sep 17 00:00:00 2001
From: Greg Fuller <gfuller23@gmail.com>
Date: Tue, 11 Oct 2022 17:05:20 -0700
Subject: draw_xy_grid provides the option to also return lone images

---
 scripts/xy_grid.py | 17 ++++++++++++-----
 1 file changed, 12 insertions(+), 5 deletions(-)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 3bb080bf..14edacc1 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -175,8 +175,9 @@ axis_options = [
 ]
 
 
-def draw_xy_grid(p, xs, ys, x_labels, y_labels, cell, draw_legend):
+def draw_xy_grid(p, xs, ys, x_labels, y_labels, cell, draw_legend, include_lone_images):
     res = []
+    successful_images = []
 
     ver_texts = [[images.GridAnnotation(y)] for y in y_labels]
     hor_texts = [[images.GridAnnotation(x)] for x in x_labels]
@@ -194,7 +195,9 @@ def draw_xy_grid(p, xs, ys, x_labels, y_labels, cell, draw_legend):
                 first_processed = processed
 
             try:
-              res.append(processed.images[0])
+              processed_image = processed.images[0]
+              res.append(processed_image)
+              successful_images.append(processed_image)
             except:
               res.append(Image.new(res[0].mode, res[0].size))
 
@@ -203,6 +206,8 @@ def draw_xy_grid(p, xs, ys, x_labels, y_labels, cell, draw_legend):
         grid = images.draw_grid_annotations(grid, res[0].width, res[0].height, hor_texts, ver_texts)
 
     first_processed.images = [grid]
+    if include_lone_images:
+        first_processed.images += successful_images
 
     return first_processed
 
@@ -229,11 +234,12 @@ class Script(scripts.Script):
             y_values = gr.Textbox(label="Y values", visible=False, lines=1)
         
         draw_legend = gr.Checkbox(label='Draw legend', value=True)
+        include_lone_images = gr.Checkbox(label='Include Separate Images', value=True)
         no_fixed_seeds = gr.Checkbox(label='Keep -1 for seeds', value=False)
 
-        return [x_type, x_values, y_type, y_values, draw_legend, no_fixed_seeds]
+        return [x_type, x_values, y_type, y_values, draw_legend, include_lone_images, no_fixed_seeds]
 
-    def run(self, p, x_type, x_values, y_type, y_values, draw_legend, no_fixed_seeds):
+    def run(self, p, x_type, x_values, y_type, y_values, draw_legend, include_lone_images, no_fixed_seeds):
         if not no_fixed_seeds:
             modules.processing.fix_seed(p)
 
@@ -344,7 +350,8 @@ class Script(scripts.Script):
             x_labels=[x_opt.format_value(p, x_opt, x) for x in xs],
             y_labels=[y_opt.format_value(p, y_opt, y) for y in ys],
             cell=cell,
-            draw_legend=draw_legend
+            draw_legend=draw_legend,
+            include_lone_images=include_lone_images
         )
 
         if opts.grid_save:
-- 
cgit v1.2.3


From aeacbac218c47f61f1d0d3f3b429c9038b8faf0f Mon Sep 17 00:00:00 2001
From: Greg Fuller <gfuller23@gmail.com>
Date: Tue, 11 Oct 2022 19:46:33 -0700
Subject: Fix save error

---
 modules/ui.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/modules/ui.py b/modules/ui.py
index e07ee0e1..4fa405a9 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -148,7 +148,10 @@ def save_files(js_data, images, do_make_zip, index):
             is_grid = image_index < p.index_of_first_image
             i = 0 if is_grid else (image_index - p.index_of_first_image)
 
-            fullfn, txt_fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
+            seed = p.all_seeds[i] if len(p.all_seeds) > 1 else p.seed
+            prompt = p.all_prompts[i] if len(p.all_prompts) > 1 else p.prompt
+            info = p.infotexts[image_index] if len(p.infotexts) > 1 else p.infotexts[0]
+            fullfn, txt_fullfn = save_image(image, path, "", seed=seed, prompt=prompt, extension=extension, info=info, grid=is_grid, p=p, save_to_dirs=save_to_dirs)
 
             filename = os.path.relpath(fullfn, path)
             filenames.append(filename)
-- 
cgit v1.2.3


From 8711c2fe0135d5c160a57db41cb79ed1942ce7fa Mon Sep 17 00:00:00 2001
From: Greg Fuller <gfuller23@gmail.com>
Date: Wed, 12 Oct 2022 16:12:12 -0700
Subject: Fix metadata contents

---
 modules/ui.py      |  5 +----
 scripts/xy_grid.py | 52 ++++++++++++++++++++++++++++++++++------------------
 2 files changed, 35 insertions(+), 22 deletions(-)

diff --git a/modules/ui.py b/modules/ui.py
index 4fa405a9..e07ee0e1 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -148,10 +148,7 @@ def save_files(js_data, images, do_make_zip, index):
             is_grid = image_index < p.index_of_first_image
             i = 0 if is_grid else (image_index - p.index_of_first_image)
 
-            seed = p.all_seeds[i] if len(p.all_seeds) > 1 else p.seed
-            prompt = p.all_prompts[i] if len(p.all_prompts) > 1 else p.prompt
-            info = p.infotexts[image_index] if len(p.infotexts) > 1 else p.infotexts[0]
-            fullfn, txt_fullfn = save_image(image, path, "", seed=seed, prompt=prompt, extension=extension, info=info, grid=is_grid, p=p, save_to_dirs=save_to_dirs)
+            fullfn, txt_fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
 
             filename = os.path.relpath(fullfn, path)
             filenames.append(filename)
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 14edacc1..02931ae6 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -176,13 +176,16 @@ axis_options = [
 
 
 def draw_xy_grid(p, xs, ys, x_labels, y_labels, cell, draw_legend, include_lone_images):
-    res = []
-    successful_images = []
-
     ver_texts = [[images.GridAnnotation(y)] for y in y_labels]
     hor_texts = [[images.GridAnnotation(x)] for x in x_labels]
 
-    first_processed = None
+    # Temporary list of all the images that are generated to be populated into the grid.
+    # Will be filled with empty images for any individual step that fails to process properly
+    image_cache = []
+
+    processed_result = None
+    cell_mode = "P"
+    cell_size = (1,1)
 
     state.job_count = len(xs) * len(ys) * p.n_iter
 
@@ -190,26 +193,39 @@ def draw_xy_grid(p, xs, ys, x_labels, y_labels, cell, draw_legend, include_lone_
         for ix, x in enumerate(xs):
             state.job = f"{ix + iy * len(xs) + 1} out of {len(xs) * len(ys)}"
 
-            processed = cell(x, y)
-            if first_processed is None:
-                first_processed = processed
-
+            processed:Processed = cell(x, y)
             try:
-              processed_image = processed.images[0]
-              res.append(processed_image)
-              successful_images.append(processed_image)
+                # this dereference will throw an exception if the image was not processed
+                # (this happens in cases such as if the user stops the process from the UI)
+                processed_image = processed.images[0]
+                
+                if processed_result is None:
+                    # Use our first valid processed result as a template container to hold our full results
+                    processed_result = copy(processed)
+                    cell_mode = processed_image.mode
+                    cell_size = processed_image.size
+                    processed_result.images = [Image.new(cell_mode, cell_size)]
+
+                image_cache.append(processed_image)
+                if include_lone_images:
+                    processed_result.images.append(processed_image)
+                    processed_result.all_prompts.append(processed.prompt)
+                    processed_result.all_seeds.append(processed.seed)
+                    processed_result.infotexts.append(processed.infotexts[0])
             except:
-              res.append(Image.new(res[0].mode, res[0].size))
+                image_cache.append(Image.new(cell_mode, cell_size))
+
+    if not processed_result:
+        print("Unexpected error: draw_xy_grid failed to return even a single processed image")
+        return Processed()
 
-    grid = images.image_grid(res, rows=len(ys))
+    grid = images.image_grid(image_cache, rows=len(ys))
     if draw_legend:
-        grid = images.draw_grid_annotations(grid, res[0].width, res[0].height, hor_texts, ver_texts)
+        grid = images.draw_grid_annotations(grid, cell_size[0], cell_size[1], hor_texts, ver_texts)
 
-    first_processed.images = [grid]
-    if include_lone_images:
-        first_processed.images += successful_images
+    processed_result.images[0] = grid
 
-    return first_processed
+    return processed_result
 
 
 re_range = re.compile(r"\s*([+-]?\s*\d+)\s*-\s*([+-]?\s*\d+)(?:\s*\(([+-]\d+)\s*\))?\s*")
-- 
cgit v1.2.3


From a3f02e4690844715a510b7bc857a0971dd05c4d8 Mon Sep 17 00:00:00 2001
From: Greg Fuller <gfuller23@gmail.com>
Date: Wed, 12 Oct 2022 16:48:53 -0700
Subject: fix prompt in log.csv

---
 modules/ui.py | 8 ++++++--
 1 file changed, 6 insertions(+), 2 deletions(-)

diff --git a/modules/ui.py b/modules/ui.py
index e07ee0e1..edb4dab1 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -139,6 +139,8 @@ def save_files(js_data, images, do_make_zip, index):
         if at_start:
             writer.writerow(["prompt", "seed", "width", "height", "sampler", "cfgs", "steps", "filename", "negative_prompt"])
 
+        log_prompt=data["prompt"]
+        log_seed=data["seed"]
         for image_index, filedata in enumerate(images, start_index):
             if filedata.startswith("data:image/png;base64,"):
                 filedata = filedata[len("data:image/png;base64,"):]
@@ -148,7 +150,9 @@ def save_files(js_data, images, do_make_zip, index):
             is_grid = image_index < p.index_of_first_image
             i = 0 if is_grid else (image_index - p.index_of_first_image)
 
-            fullfn, txt_fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
+            log_seed=p.all_seeds[i]
+            log_prompt=p.all_prompts[i]
+            fullfn, txt_fullfn = save_image(image, path, "", seed=log_seed, prompt=log_prompt, extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
 
             filename = os.path.relpath(fullfn, path)
             filenames.append(filename)
@@ -157,7 +161,7 @@ def save_files(js_data, images, do_make_zip, index):
                 filenames.append(os.path.basename(txt_fullfn))
                 fullfns.append(txt_fullfn)
 
-        writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]])
+        writer.writerow([log_prompt, log_seed, data["width"], data["height"], data["sampler"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]])
 
     # Make Zip
     if do_make_zip:
-- 
cgit v1.2.3


From fed7f0e281a42ea962bbe422e018468bafa6f1e6 Mon Sep 17 00:00:00 2001
From: Greg Fuller <gfuller23@gmail.com>
Date: Wed, 12 Oct 2022 23:09:30 -0700
Subject: Revert "fix prompt in log.csv"

This reverts commit e4b5d1696429ab78dae9779420ce6ec4cd9c5f67.
---
 modules/ui.py | 8 ++------
 1 file changed, 2 insertions(+), 6 deletions(-)

diff --git a/modules/ui.py b/modules/ui.py
index edb4dab1..e07ee0e1 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -139,8 +139,6 @@ def save_files(js_data, images, do_make_zip, index):
         if at_start:
             writer.writerow(["prompt", "seed", "width", "height", "sampler", "cfgs", "steps", "filename", "negative_prompt"])
 
-        log_prompt=data["prompt"]
-        log_seed=data["seed"]
         for image_index, filedata in enumerate(images, start_index):
             if filedata.startswith("data:image/png;base64,"):
                 filedata = filedata[len("data:image/png;base64,"):]
@@ -150,9 +148,7 @@ def save_files(js_data, images, do_make_zip, index):
             is_grid = image_index < p.index_of_first_image
             i = 0 if is_grid else (image_index - p.index_of_first_image)
 
-            log_seed=p.all_seeds[i]
-            log_prompt=p.all_prompts[i]
-            fullfn, txt_fullfn = save_image(image, path, "", seed=log_seed, prompt=log_prompt, extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
+            fullfn, txt_fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
 
             filename = os.path.relpath(fullfn, path)
             filenames.append(filename)
@@ -161,7 +157,7 @@ def save_files(js_data, images, do_make_zip, index):
                 filenames.append(os.path.basename(txt_fullfn))
                 fullfns.append(txt_fullfn)
 
-        writer.writerow([log_prompt, log_seed, data["width"], data["height"], data["sampler"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]])
+        writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]])
 
     # Make Zip
     if do_make_zip:
-- 
cgit v1.2.3


From 8636b50aea83f9c743f005722d9f3f8ee9303e00 Mon Sep 17 00:00:00 2001
From: Melan <alexleander91@gmail.com>
Date: Thu, 13 Oct 2022 12:37:58 +0200
Subject: Add learn_rate to csv and removed a left-over debug statement

---
 modules/hypernetworks/hypernetwork.py          | 6 +++---
 modules/textual_inversion/textual_inversion.py | 5 +++--
 2 files changed, 6 insertions(+), 5 deletions(-)

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 6522078f..2751a8c8 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -257,19 +257,19 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
             last_saved_file = os.path.join(hypernetwork_dir, f'{hypernetwork_name}-{hypernetwork.step}.pt')
             hypernetwork.save(last_saved_file)
 
-        print(f"{write_csv_every} > {hypernetwork.step % write_csv_every == 0}, {write_csv_every}")
         if write_csv_every > 0 and hypernetwork_dir is not None and hypernetwork.step % write_csv_every == 0:
             write_csv_header = False if os.path.exists(os.path.join(hypernetwork_dir, "hypernetwork_loss.csv")) else True
             
             with open(os.path.join(hypernetwork_dir, "hypernetwork_loss.csv"), "a+") as fout:
 
-                csv_writer = csv.DictWriter(fout, fieldnames=["step", "loss"])
+                csv_writer = csv.DictWriter(fout, fieldnames=["step", "loss", "learn_rate"])
                 
                 if write_csv_header:
                     csv_writer.writeheader()
 
                 csv_writer.writerow({"step": hypernetwork.step, 
-                    "loss": f"{losses.mean():.7f}"})
+                    "loss": f"{losses.mean():.7f}",
+                    "learn_rate": scheduler.learn_rate})
 
         if hypernetwork.step > 0 and images_dir is not None and hypernetwork.step % create_image_every == 0:
             last_saved_image = os.path.join(images_dir, f'{hypernetwork_name}-{hypernetwork.step}.png')
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 25038a89..b83df079 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -262,14 +262,15 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
 
             with open(os.path.join(log_directory, "textual_inversion_loss.csv"), "a+") as fout:
 
-                csv_writer = csv.DictWriter(fout, fieldnames=["epoch", "epoch_step", "loss"])
+                csv_writer = csv.DictWriter(fout, fieldnames=["epoch", "epoch_step", "loss", "learn_rate"])
                 
                 if write_csv_header:
                     csv_writer.writeheader()
 
                 csv_writer.writerow({"epoch": epoch_num + 1, 
                     "epoch_step": epoch_step - 1, 
-                    "loss": f"{losses.mean():.7f}"})
+                    "loss": f"{losses.mean():.7f}",
+                    "learn_rate": scheduler.learn_rate})
 
         if embedding.step > 0 and images_dir is not None and embedding.step % create_image_every == 0:
             last_saved_image = os.path.join(images_dir, f'{embedding_name}-{embedding.step}.png')
-- 
cgit v1.2.3


From bb7baf6b9cb6b4b9fa09b6f07ef997db32fe6e58 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 13 Oct 2022 16:07:18 +0300
Subject: add option to change what's shown in quicksettings bar

---
 javascript/hints.js |  2 ++
 modules/shared.py   |  4 ++--
 modules/ui.py       | 16 +++++++++-------
 style.css           |  1 +
 4 files changed, 14 insertions(+), 9 deletions(-)

diff --git a/javascript/hints.js b/javascript/hints.js
index 32f10fde..06bbd9e2 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -84,6 +84,8 @@ titles = {
 
     "Filename word regex": "This regular expression will be used extract words from filename, and they will be joined using the option below into label text used for training. Leave empty to keep filename text as it is.",
     "Filename join string": "This string will be used to hoin split words into a single line if the option above is enabled.",
+
+    "Quicksettings list": "List of setting names, separated by commas, for settings that should go to the quick access bar at the top, rather than the usual stetting tab. See modules/shared.py for setting names. Requires restart to apply."
 }
 
 
diff --git a/modules/shared.py b/modules/shared.py
index 5f6101a4..4d3ed625 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -152,7 +152,6 @@ class OptionInfo:
         self.component_args = component_args
         self.onchange = onchange
         self.section = None
-        self.show_on_main_page = show_on_main_page
 
 
 def options_section(section_identifier, options_dict):
@@ -237,7 +236,7 @@ options_templates.update(options_section(('training', "Training"), {
 }))
 
 options_templates.update(options_section(('sd', "Stable Diffusion"), {
-    "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, show_on_main_page=True),
+    "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}),
     "sd_hypernetwork": OptionInfo("None", "Stable Diffusion finetune hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}),
     "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."),
     "save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"),
@@ -250,6 +249,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "filter_nsfw": OptionInfo(False, "Filter NSFW content"),
     'CLIP_stop_at_last_layers': OptionInfo(1, "Stop At last layers of CLIP model", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}),
     "random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}),
+    'quicksettings': OptionInfo("sd_model_checkpoint", "Quicksettings list"),
 }))
 
 options_templates.update(options_section(('interrogate', "Interrogate Options"), {
diff --git a/modules/ui.py b/modules/ui.py
index e07ee0e1..a0529860 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1305,6 +1305,9 @@ Requested path was: {f}
         settings_cols = 3
         items_per_col = int(len(opts.data_labels) * 0.9 / settings_cols)
 
+        quicksettings_names = [x.strip() for x in opts.quicksettings.split(",")]
+        quicksettings_names = set(x for x in quicksettings_names if x != 'quicksettings')
+
         quicksettings_list = []
 
         cols_displayed = 0
@@ -1329,7 +1332,7 @@ Requested path was: {f}
 
                     gr.HTML(elem_id="settings_header_text_{}".format(item.section[0]), value='<h1 class="gr-button-lg">{}</h1>'.format(item.section[1]))
 
-                if item.show_on_main_page:
+                if k in quicksettings_names:
                     quicksettings_list.append((i, k, item))
                     components.append(dummy_component)
                 else:
@@ -1338,7 +1341,11 @@ Requested path was: {f}
                     components.append(component)
                     items_displayed += 1
 
-        request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications")
+        with gr.Row():
+            request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications")
+            reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary')
+            restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary')
+
         request_notifications.click(
             fn=lambda: None,
             inputs=[],
@@ -1346,10 +1353,6 @@ Requested path was: {f}
             _js='function(){}'
         )
 
-        with gr.Row():
-            reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary')
-            restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary')
-
         def reload_scripts():
             modules.scripts.reload_script_body_only()
 
@@ -1364,7 +1367,6 @@ Requested path was: {f}
             shared.state.interrupt()
             settings_interface.gradio_ref.do_restart = True
 
-
         restart_gradio.click(
             fn=request_restart,
             inputs=[],
diff --git a/style.css b/style.css
index e6fa10b4..55c41971 100644
--- a/style.css
+++ b/style.css
@@ -488,6 +488,7 @@ input[type="range"]{
 #quicksettings > div > div{
     max-width: 32em;
     padding: 0;
+    margin-right: 0.75em;
 }
 
 canvas[key="mask"] {
-- 
cgit v1.2.3


From cf1e8fcb303a21ab626fc1e8b3bc95bb780e8758 Mon Sep 17 00:00:00 2001
From: Kalle <kalekkiorg@gmail.com>
Date: Thu, 13 Oct 2022 00:12:20 +0300
Subject: Correct img gen count in notification

Display correct count of images generated in browser notification regardless of "Show grid in results for web" setting.
---
 javascript/notification.js | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/javascript/notification.js b/javascript/notification.js
index bdf614ad..f96de313 100644
--- a/javascript/notification.js
+++ b/javascript/notification.js
@@ -36,7 +36,7 @@ onUiUpdate(function(){
     const notification = new Notification(
         'Stable Diffusion',
         {
-            body: `Generated ${imgs.size > 1 ? imgs.size - 1 : 1} image${imgs.size > 1 ? 's' : ''}`,
+            body: `Generated ${imgs.size > 1 ? imgs.size - opts.return_grid : 1} image${imgs.size > 1 ? 's' : ''}`,
             icon: headImg,
             image: headImg,
         }
-- 
cgit v1.2.3


From a4170875b00e5362cd252277c9830024dcea0c51 Mon Sep 17 00:00:00 2001
From: aoirusann <yimodo.siki@gmail.com>
Date: Wed, 12 Oct 2022 20:09:42 +0800
Subject: [img2imgalt] Add `override` in UI for convenience. Some params in
 img2imgalt are fixed, such as `Sampling method` and  `Denosing Strength`. And
 some params should be matched with those in decode, such as `steps`.

---
 scripts/img2imgalt.py | 35 ++++++++++++++++++++++++++++++++---
 1 file changed, 32 insertions(+), 3 deletions(-)

diff --git a/scripts/img2imgalt.py b/scripts/img2imgalt.py
index 313a55d2..1e52f69b 100644
--- a/scripts/img2imgalt.py
+++ b/scripts/img2imgalt.py
@@ -120,15 +120,44 @@ class Script(scripts.Script):
         return is_img2img
 
     def ui(self, is_img2img):
+        info = gr.Markdown('''
+        * `Sampling method` is overriden as Euler, as this script is built on it.
+        * `CFG Scale` should be 2 or lower.
+        ''')
+
+        override_prompt = gr.Checkbox(label="Override `prompt` to the same value as `original prompt`?(and `negative prompt`)", value=True)
         original_prompt = gr.Textbox(label="Original prompt", lines=1)
         original_negative_prompt = gr.Textbox(label="Original negative prompt", lines=1)
-        cfg = gr.Slider(label="Decode CFG scale", minimum=0.0, maximum=15.0, step=0.1, value=1.0)
+
+        override_steps = gr.Checkbox(label="Override `Sampling Steps` to the same value as `Decode steps`?", value=True)
         st = gr.Slider(label="Decode steps", minimum=1, maximum=150, step=1, value=50)
+
+        override_strength = gr.Checkbox(label="Override `Denoising strength` to 1?", value=True)
+
+        cfg = gr.Slider(label="Decode CFG scale", minimum=0.0, maximum=15.0, step=0.1, value=1.0)
         randomness = gr.Slider(label="Randomness", minimum=0.0, maximum=1.0, step=0.01, value=0.0)
         sigma_adjustment = gr.Checkbox(label="Sigma adjustment for finding noise for image", value=False)
-        return [original_prompt, original_negative_prompt, cfg, st, randomness, sigma_adjustment]
 
-    def run(self, p, original_prompt, original_negative_prompt, cfg, st, randomness, sigma_adjustment):
+        return [
+            info, 
+            override_prompt, original_prompt, original_negative_prompt, 
+            override_steps, st,
+            override_strength,
+            cfg, randomness, sigma_adjustment,
+        ]
+
+    def run(self, p, _, override_prompt, original_prompt, original_negative_prompt, override_steps, st, override_strength, cfg, randomness, sigma_adjustment):
+        # MUST Override
+        p.sampler_index = [sampler.name for sampler in sd_samplers.samplers].index("Euler")
+
+        # OPTIONAL Override
+        if override_prompt:
+            p.prompt = original_prompt
+            p.negative_prompt = original_negative_prompt
+        if override_steps:
+            p.steps = st
+        if override_strength:
+            p.denoising_strength = 1.0
 
 
         def sample_extra(conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength):
-- 
cgit v1.2.3


From e548fc4aca19e58fa97da5404a2116915eb85531 Mon Sep 17 00:00:00 2001
From: aoirusann <yimodo.siki@gmail.com>
Date: Thu, 13 Oct 2022 07:39:33 +0800
Subject: [img2imgalt] Make sampler's override be optional

---
 scripts/img2imgalt.py | 13 +++++++------
 1 file changed, 7 insertions(+), 6 deletions(-)

diff --git a/scripts/img2imgalt.py b/scripts/img2imgalt.py
index 1e52f69b..d438175c 100644
--- a/scripts/img2imgalt.py
+++ b/scripts/img2imgalt.py
@@ -121,10 +121,11 @@ class Script(scripts.Script):
 
     def ui(self, is_img2img):
         info = gr.Markdown('''
-        * `Sampling method` is overriden as Euler, as this script is built on it.
         * `CFG Scale` should be 2 or lower.
         ''')
 
+        override_sampler = gr.Checkbox(label="Override `Sampling method` to Euler?(this method is built for it)", value=True)
+
         override_prompt = gr.Checkbox(label="Override `prompt` to the same value as `original prompt`?(and `negative prompt`)", value=True)
         original_prompt = gr.Textbox(label="Original prompt", lines=1)
         original_negative_prompt = gr.Textbox(label="Original negative prompt", lines=1)
@@ -140,17 +141,17 @@ class Script(scripts.Script):
 
         return [
             info, 
+            override_sampler,
             override_prompt, original_prompt, original_negative_prompt, 
             override_steps, st,
             override_strength,
             cfg, randomness, sigma_adjustment,
         ]
 
-    def run(self, p, _, override_prompt, original_prompt, original_negative_prompt, override_steps, st, override_strength, cfg, randomness, sigma_adjustment):
-        # MUST Override
-        p.sampler_index = [sampler.name for sampler in sd_samplers.samplers].index("Euler")
-
-        # OPTIONAL Override
+    def run(self, p, _, override_sampler, override_prompt, original_prompt, original_negative_prompt, override_steps, st, override_strength, cfg, randomness, sigma_adjustment):
+        # Override
+        if override_sampler:
+            p.sampler_index = [sampler.name for sampler in sd_samplers.samplers].index("Euler")
         if override_prompt:
             p.prompt = original_prompt
             p.negative_prompt = original_negative_prompt
-- 
cgit v1.2.3


From dccc181b55100b09182c1679c8dd75011aad7335 Mon Sep 17 00:00:00 2001
From: Taithrah <Taithrah@users.noreply.github.com>
Date: Thu, 13 Oct 2022 10:43:57 -0400
Subject: Update hints.js

typo
---
 javascript/hints.js | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/javascript/hints.js b/javascript/hints.js
index 06bbd9e2..f65e7b88 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -85,7 +85,7 @@ titles = {
     "Filename word regex": "This regular expression will be used extract words from filename, and they will be joined using the option below into label text used for training. Leave empty to keep filename text as it is.",
     "Filename join string": "This string will be used to hoin split words into a single line if the option above is enabled.",
 
-    "Quicksettings list": "List of setting names, separated by commas, for settings that should go to the quick access bar at the top, rather than the usual stetting tab. See modules/shared.py for setting names. Requires restart to apply."
+    "Quicksettings list": "List of setting names, separated by commas, for settings that should go to the quick access bar at the top, rather than the usual setting tab. See modules/shared.py for setting names. Requires restarting to apply."
 }
 
 
-- 
cgit v1.2.3


From a10b0e11fc22cc67b6a3664f2ddd17425d8433a8 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 13 Oct 2022 19:22:41 +0300
Subject: options to refresh list of models and hypernetworks

---
 modules/shared.py |  9 +++++----
 modules/ui.py     | 33 +++++++++++++++++++++++++++++----
 style.css         | 21 ++++++++++++++++++++-
 3 files changed, 54 insertions(+), 9 deletions(-)

diff --git a/modules/shared.py b/modules/shared.py
index 4d3ed625..d8e3a286 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -13,7 +13,7 @@ import modules.memmon
 import modules.sd_models
 import modules.styles
 import modules.devices as devices
-from modules import sd_samplers
+from modules import sd_samplers, sd_models
 from modules.hypernetworks import hypernetwork
 from modules.paths import models_path, script_path, sd_path
 
@@ -145,13 +145,14 @@ def realesrgan_models_names():
 
 
 class OptionInfo:
-    def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, show_on_main_page=False):
+    def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, show_on_main_page=False, refresh=None):
         self.default = default
         self.label = label
         self.component = component
         self.component_args = component_args
         self.onchange = onchange
         self.section = None
+        self.refresh = refresh
 
 
 def options_section(section_identifier, options_dict):
@@ -236,8 +237,8 @@ options_templates.update(options_section(('training', "Training"), {
 }))
 
 options_templates.update(options_section(('sd', "Stable Diffusion"), {
-    "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}),
-    "sd_hypernetwork": OptionInfo("None", "Stable Diffusion finetune hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}),
+    "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, refresh=sd_models.list_models),
+    "sd_hypernetwork": OptionInfo("None", "Stable Diffusion finetune hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks),
     "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."),
     "save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"),
     "img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies (normally you'd do less with less denoising)."),
diff --git a/modules/ui.py b/modules/ui.py
index a0529860..0a58f6be 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -78,6 +78,8 @@ reuse_symbol = '\u267b\ufe0f'  # ♻️
 art_symbol = '\U0001f3a8'  # 🎨
 paste_symbol = '\u2199\ufe0f'  # ↙
 folder_symbol = '\U0001f4c2'  # 📂
+refresh_symbol = '\U0001f504'  # 🔄
+
 
 def plaintext_to_html(text):
     text = "<p>" + "<br>\n".join([f"{html.escape(x)}" for x in text.split('\n')]) + "</p>"
@@ -1210,8 +1212,7 @@ def create_ui(wrap_gradio_gpu_call):
             outputs=[],
         )
 
-
-    def create_setting_component(key):
+    def create_setting_component(key, is_quicksettings=False):
         def fun():
             return opts.data[key] if key in opts.data else opts.data_labels[key].default
 
@@ -1231,7 +1232,31 @@ def create_ui(wrap_gradio_gpu_call):
         else:
             raise Exception(f'bad options item type: {str(t)} for key {key}')
 
-        return comp(label=info.label, value=fun, **(args or {}))
+        if info.refresh is not None:
+            if is_quicksettings:
+                res = comp(label=info.label, value=fun, **(args or {}))
+                refresh_button = gr.Button(value=refresh_symbol, elem_id="refresh_"+key)
+            else:
+                with gr.Row(variant="compact"):
+                    res = comp(label=info.label, value=fun, **(args or {}))
+                    refresh_button = gr.Button(value=refresh_symbol, elem_id="refresh_" + key)
+
+            def refresh():
+                info.refresh()
+                refreshed_args = info.component_args() if callable(info.component_args) else info.component_args
+                res.choices = refreshed_args["choices"]
+                return gr.update(**(refreshed_args or {}))
+
+            refresh_button.click(
+                fn=refresh,
+                inputs=[],
+                outputs=[res],
+            )
+        else:
+            res = comp(label=info.label, value=fun, **(args or {}))
+
+
+        return res
 
     components = []
     component_dict = {}
@@ -1401,7 +1426,7 @@ Requested path was: {f}
     with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion") as demo:
         with gr.Row(elem_id="quicksettings"):
             for i, k, item in quicksettings_list:
-                component = create_setting_component(k)
+                component = create_setting_component(k, is_quicksettings=True)
                 component_dict[k] = component
 
         settings_interface.gradio_ref = demo
diff --git a/style.css b/style.css
index 55c41971..ad2a52cc 100644
--- a/style.css
+++ b/style.css
@@ -228,6 +228,8 @@ fieldset span.text-gray-500, .gr-block.gr-box span.text-gray-500,  label.block s
     border-top: 1px solid #eee;
     border-left: 1px solid #eee;
     border-right: 1px solid #eee;
+
+    z-index: 300;
 }
 
 .dark fieldset span.text-gray-500, .dark .gr-block.gr-box span.text-gray-500, .dark label.block span{
@@ -480,17 +482,30 @@ input[type="range"]{
     background: #a55000;
 }
 
+#quicksettings {
+    gap: 0.4em;
+}
+
 #quicksettings > div{
     border: none;
     background: none;
+    flex: unset;
+    gap: 0.5em;
 }
 
 #quicksettings > div > div{
     max-width: 32em;
+    min-width: 24em;
     padding: 0;
-    margin-right: 0.75em;
 }
 
+#refresh_sd_model_checkpoint, #refresh_sd_hypernetwork{
+    max-width: 2.5em;
+    min-width: 2.5em;
+    height: 2.4em;
+}
+
+
 canvas[key="mask"] {
     z-index: 12 !important;
     filter: invert();
@@ -507,3 +522,7 @@ canvas[key="mask"] {
     z-index: 200;
     width: 8em;
 }
+
+.row.gr-compact{
+    overflow: visible;
+}
-- 
cgit v1.2.3


From 354ef0da3b1f0fa5c113d04b6c79e3908c848d23 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 13 Oct 2022 20:12:37 +0300
Subject: add hypernetwork multipliers

---
 modules/hypernetworks/hypernetwork.py | 8 +++++++-
 modules/shared.py                     | 5 ++++-
 modules/ui.py                         | 5 ++++-
 scripts/xy_grid.py                    | 9 ++++++++-
 style.css                             | 3 +++
 webui.py                              | 2 +-
 6 files changed, 27 insertions(+), 5 deletions(-)

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index b6c06d49..f1248bb7 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -18,6 +18,8 @@ from modules.textual_inversion.learn_schedule import LearnRateScheduler
 
 
 class HypernetworkModule(torch.nn.Module):
+    multiplier = 1.0
+
     def __init__(self, dim, state_dict=None):
         super().__init__()
 
@@ -36,7 +38,11 @@ class HypernetworkModule(torch.nn.Module):
         self.to(devices.device)
 
     def forward(self, x):
-        return x + (self.linear2(self.linear1(x)))
+        return x + (self.linear2(self.linear1(x))) * self.multiplier
+
+
+def apply_strength(value=None):
+    HypernetworkModule.multiplier = value if value is not None else shared.opts.sd_hypernetwork_strength
 
 
 class Hypernetwork:
diff --git a/modules/shared.py b/modules/shared.py
index d8e3a286..5901e605 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -238,7 +238,8 @@ options_templates.update(options_section(('training', "Training"), {
 
 options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, refresh=sd_models.list_models),
-    "sd_hypernetwork": OptionInfo("None", "Stable Diffusion finetune hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks),
+    "sd_hypernetwork": OptionInfo("None", "Hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks),
+    "sd_hypernetwork_strength": OptionInfo(1.0, "Hypernetwork strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.001}),
     "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."),
     "save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"),
     "img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies (normally you'd do less with less denoising)."),
@@ -348,6 +349,8 @@ class Options:
         item = self.data_labels.get(key)
         item.onchange = func
 
+        func()
+
     def dumpjson(self):
         d = {k: self.data.get(k, self.data_labels.get(k).default) for k in self.data_labels.keys()}
         return json.dumps(d)
diff --git a/modules/ui.py b/modules/ui.py
index 0a58f6be..673014f2 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1244,7 +1244,10 @@ def create_ui(wrap_gradio_gpu_call):
             def refresh():
                 info.refresh()
                 refreshed_args = info.component_args() if callable(info.component_args) else info.component_args
-                res.choices = refreshed_args["choices"]
+
+                for k, v in refreshed_args.items():
+                    setattr(res, k, v)
+
                 return gr.update(**(refreshed_args or {}))
 
             refresh_button.click(
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 02931ae6..efb63af5 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -107,6 +107,10 @@ def apply_hypernetwork(p, x, xs):
     hypernetwork.load_hypernetwork(name)
 
 
+def apply_hypernetwork_strength(p, x, xs):
+    hypernetwork.apply_strength(x)
+
+
 def confirm_hypernetworks(p, xs):
     for x in xs:
         if x.lower() in ["", "none"]:
@@ -165,6 +169,7 @@ axis_options = [
     AxisOption("Sampler", str, apply_sampler, format_value, confirm_samplers),
     AxisOption("Checkpoint name", str, apply_checkpoint, format_value, confirm_checkpoints),
     AxisOption("Hypernetwork", str, apply_hypernetwork, format_value, confirm_hypernetworks),
+    AxisOption("Hypernet str.", float, apply_hypernetwork_strength, format_value_add_label, None),
     AxisOption("Sigma Churn", float, apply_field("s_churn"), format_value_add_label, None),
     AxisOption("Sigma min", float, apply_field("s_tmin"), format_value_add_label, None),
     AxisOption("Sigma max", float, apply_field("s_tmax"), format_value_add_label, None),
@@ -250,7 +255,7 @@ class Script(scripts.Script):
             y_values = gr.Textbox(label="Y values", visible=False, lines=1)
         
         draw_legend = gr.Checkbox(label='Draw legend', value=True)
-        include_lone_images = gr.Checkbox(label='Include Separate Images', value=True)
+        include_lone_images = gr.Checkbox(label='Include Separate Images', value=False)
         no_fixed_seeds = gr.Checkbox(label='Keep -1 for seeds', value=False)
 
         return [x_type, x_values, y_type, y_values, draw_legend, include_lone_images, no_fixed_seeds]
@@ -377,6 +382,8 @@ class Script(scripts.Script):
         modules.sd_models.reload_model_weights(shared.sd_model)
 
         hypernetwork.load_hypernetwork(opts.sd_hypernetwork)
+        hypernetwork.apply_strength()
+
 
         opts.data["CLIP_stop_at_last_layers"] = CLIP_stop_at_last_layers
 
diff --git a/style.css b/style.css
index ad2a52cc..aa3d379c 100644
--- a/style.css
+++ b/style.css
@@ -522,6 +522,9 @@ canvas[key="mask"] {
     z-index: 200;
     width: 8em;
 }
+#quicksettings .gr-box > div > div > input.gr-text-input {
+  top: -1.12em;
+}
 
 .row.gr-compact{
     overflow: visible;
diff --git a/webui.py b/webui.py
index 33ba7905..fe0ce321 100644
--- a/webui.py
+++ b/webui.py
@@ -72,7 +72,6 @@ def wrap_gradio_gpu_call(func, extra_outputs=None):
 
     return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs)
 
-
 def initialize():
     modelloader.cleanup_models()
     modules.sd_models.setup_model()
@@ -86,6 +85,7 @@ def initialize():
     shared.sd_model = modules.sd_models.load_model()
     shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model)))
     shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetworks.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)))
+    shared.opts.onchange("sd_hypernetwork_strength", modules.hypernetworks.hypernetwork.apply_strength)
 
 
 def webui():
-- 
cgit v1.2.3


From 08b3f7aef15f74f4d2254b1274dd66fcc7940348 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 13 Oct 2022 20:42:27 +0300
Subject: emergency fix for broken send to buttons

---
 javascript/ui.js | 8 ++++----
 modules/ui.py    | 2 +-
 2 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/javascript/ui.js b/javascript/ui.js
index 4100944e..0f8fe68e 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -33,27 +33,27 @@ function args_to_array(args){
 }
 
 function switch_to_txt2img(){
-    gradioApp().querySelectorAll('button')[0].click();
+    gradioApp().querySelector('#tabs').querySelectorAll('button')[0].click();
 
     return args_to_array(arguments);
 }
 
 function switch_to_img2img_img2img(){
-    gradioApp().querySelectorAll('button')[1].click();
+    gradioApp().querySelector('#tabs').querySelectorAll('button')[1].click();
     gradioApp().getElementById('mode_img2img').querySelectorAll('button')[0].click();
 
     return args_to_array(arguments);
 }
 
 function switch_to_img2img_inpaint(){
-    gradioApp().querySelectorAll('button')[1].click();
+    gradioApp().querySelector('#tabs').querySelectorAll('button')[1].click();
     gradioApp().getElementById('mode_img2img').querySelectorAll('button')[1].click();
 
     return args_to_array(arguments);
 }
 
 function switch_to_extras(){
-    gradioApp().querySelectorAll('button')[2].click();
+    gradioApp().querySelector('#tabs').querySelectorAll('button')[2].click();
 
     return args_to_array(arguments);
 }
diff --git a/modules/ui.py b/modules/ui.py
index 673014f2..7446439d 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1434,7 +1434,7 @@ Requested path was: {f}
 
         settings_interface.gradio_ref = demo
 
-        with gr.Tabs() as tabs:
+        with gr.Tabs(elem_id="tabs") as tabs:
             for interface, label, ifid in interfaces:
                 with gr.TabItem(label, id=ifid, elem_id='tab_' + ifid):
                     interface.render()
-- 
cgit v1.2.3


From a1489f94283c07824a7a58353c03dc89541bbe49 Mon Sep 17 00:00:00 2001
From: yfszzx <yfszzx@gmail.com>
Date: Fri, 14 Oct 2022 07:13:38 +0800
Subject: images history fix all known bug

---
 .gitignore                   |  1 +
 javascript/images_history.js | 23 ++++++++------------
 modules/images_history.py    | 51 +++++++++++++++++++++++---------------------
 repositorieslatent-diffusion |  1 -
 style.css                    |  6 +++---
 5 files changed, 40 insertions(+), 42 deletions(-)
 delete mode 160000 repositorieslatent-diffusion

diff --git a/.gitignore b/.gitignore
index 434e23ce..b9e23112 100644
--- a/.gitignore
+++ b/.gitignore
@@ -27,3 +27,4 @@ notification.mp3
 /SwinIR
 /textual_inversion
 /images_history_testui.py
+/repositorieslatent-diffusion
diff --git a/javascript/images_history.js b/javascript/images_history.js
index 8fa4a15e..3a20056b 100644
--- a/javascript/images_history.js
+++ b/javascript/images_history.js
@@ -25,11 +25,6 @@ var images_history_click_tab = function(){
     }                
 }
 
-var images_history_close_full_view = function(){
-    var box = images_history_get_parent_by_class(this, "images_history_cantainor");
-    box.querySelector(".images_history_del_button").setAttribute("disabled", "disabled");
-}
-
 function images_history_disabled_del(){
     gradioApp().querySelectorAll(".images_history_del_button").forEach(function(btn){
         btn.setAttribute('disabled','disabled');
@@ -182,18 +177,18 @@ setTimeout(images_history_init, 500);
 document.addEventListener("DOMContentLoaded", function() {
     var mutationObserver = new MutationObserver(function(m){
         for (var i in images_history_tab_list ){
-            var buttons = gradioApp().querySelectorAll('#' + images_history_tab_list[i] + '_images_history .gallery-item');
+            let tabname = images_history_tab_list[i]
+            var buttons = gradioApp().querySelectorAll('#' + tabname + '_images_history .gallery-item');
             buttons.forEach(function(bnt){    
                 bnt.addEventListener('click', images_history_click_image, true);
             });
-        // var cls_btn = gradioApp().getElementById(tabname + '_images_history_gallery').querySelector("svg");
-        // if (cls_btn){
-        //     cls_btn.addEventListener('click', images_history_close_full_view, false);
-        // }
-        // console.log(cls_btn, cls_btn.parentElement.parentElement)
-        // if (cls_btn) {
-        //     cls_btn = images_history_get_parent_by_tagname(cls_btn, "BUTTON");
-        //     cls_btn.addEventListener('click', images_history_close_full_view, true);
+            var cls_btn = gradioApp().getElementById(tabname + '_images_history_gallery').querySelector("svg");
+            if (cls_btn){
+                cls_btn.addEventListener('click', function(){
+                    gradioApp().getElementById(tabname + '_images_history_renew_page').click();
+                }, false);
+            }
+
         }     
     });
     mutationObserver.observe( gradioApp(), { childList:true, subtree:true });
diff --git a/modules/images_history.py b/modules/images_history.py
index f812ea4e..cdfcffed 100644
--- a/modules/images_history.py
+++ b/modules/images_history.py
@@ -38,7 +38,7 @@ def get_recent_images(dir_name, page_index, step, image_index, tabname):
     else:
         current_file =  file_list[int(image_index)]
         hide_image = os.path.join(dir_name, current_file)
-    return [os.path.join(dir_name, file) for file in file_list], page_index, file_list, current_file, hide_image
+    return [os.path.join(dir_name, file) for file in file_list], page_index, file_list, current_file, hide_image, ""
 def first_page_click(dir_name, page_index, image_index, tabname):
     return get_recent_images(dir_name, 1, 0, image_index, tabname)
 def end_page_click(dir_name, page_index, image_index, tabname):
@@ -55,25 +55,28 @@ def show_image_info(num, image_path, filenames):
     file = filenames[int(num)]
     return file, num, os.path.join(image_path, file)
 def delete_image(delete_num, tabname, dir_name, name, page_index, filenames, image_index):
-    delete_num = int(delete_num)
-    index = list(filenames).index(name)
-    i = 0
-    new_file_list = []
-    for name in filenames:
-        if i  >= index and i < index + delete_num:            
-            path = os.path.join(dir_name, name)
-            if os.path.exists(path):        
-                print(f"Delete file {path}")
-                os.remove(path)
-                txt_file = os.path.splitext(path)[0]  + ".txt"
-                if os.path.exists(txt_file):
-                    os.remove(txt_file)       
+    if name == "":
+        return filenames, delete_num
+    else:
+        delete_num = int(delete_num)
+        index = list(filenames).index(name)
+        i = 0
+        new_file_list = []
+        for name in filenames:
+            if i  >= index and i < index + delete_num:            
+                path = os.path.join(dir_name, name)
+                if os.path.exists(path):        
+                    print(f"Delete file {path}")
+                    os.remove(path)
+                    txt_file = os.path.splitext(path)[0]  + ".txt"
+                    if os.path.exists(txt_file):
+                        os.remove(txt_file)       
+                else:
+                    print(f"Not exists file {path}")
             else:
-                print(f"Not exists file {path}")
-        else:
-            new_file_list.append(name)
-        i += 1
-    return page_index, new_file_list, 1
+                new_file_list.append(name)
+            i += 1
+    return new_file_list, 1
 
 def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict):
         if tabname == "txt2img":
@@ -93,9 +96,9 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict):
             with gr.Row():     
                 with gr.Column(scale=2):                    
                     history_gallery = gr.Gallery(show_label=False, elem_id=tabname + "_images_history_gallery").style(grid=6)
-                    with gr.Row():
-                        delete = gr.Button('Delete',  elem_id=tabname + "_images_history_del_button")
-                        delete_num = gr.Number(value=1, interactive=True, label="number of images to delete consecutively next")                                           
+                    with gr.Row():                        
+                        delete_num = gr.Number(value=1, interactive=True, label="number of images to delete consecutively next")   
+                        delete = gr.Button('Delete',  elem_id=tabname + "_images_history_del_button")                                        
                 with gr.Column():     
                     with gr.Row():          
                         pnginfo_send_to_txt2img = gr.Button('Send to txt2img')
@@ -118,7 +121,7 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict):
                 
         # turn pages
         gallery_inputs = [img_path, page_index, image_index, tabname_box]
-        gallery_outputs = [history_gallery, page_index, filenames, img_file_name, hide_image]
+        gallery_outputs = [history_gallery, page_index, filenames, img_file_name, hide_image, img_file_name]
 
         first_page.click(first_page_click, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)
         next_page.click(next_page_click, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)
@@ -131,7 +134,7 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict):
         #other funcitons
         set_index.click(show_image_info, _js="images_history_get_current_img", inputs=[tabname_box,  img_path, filenames], outputs=[img_file_name, image_index, hide_image])
         img_file_name.change(fn=None, _js="images_history_enable_del_buttons", inputs=None, outputs=None)
-        delete.click(delete_image,_js="images_history_delete", inputs=[delete_num, tabname_box, img_path, img_file_name, page_index, filenames, image_index], outputs=[page_index, filenames, delete_num]) 
+        delete.click(delete_image,_js="images_history_delete", inputs=[delete_num, tabname_box, img_path, img_file_name, page_index, filenames, image_index], outputs=[filenames, delete_num]) 
         hide_image.change(fn=run_pnginfo, inputs=[hide_image], outputs=[info1, img_file_info, info2])
        
         #pnginfo.click(fn=run_pnginfo, inputs=[hide_image], outputs=[info1, img_file_info, info2])
diff --git a/repositorieslatent-diffusion b/repositorieslatent-diffusion
deleted file mode 160000
index abf33e70..00000000
--- a/repositorieslatent-diffusion
+++ /dev/null
@@ -1 +0,0 @@
-Subproject commit abf33e7002d59d9085081bce93ec798dcabd49af
diff --git a/style.css b/style.css
index c75dce4c..e6fa10b4 100644
--- a/style.css
+++ b/style.css
@@ -20,7 +20,7 @@
     padding-right: 0.25em;
     margin: 0.1em 0;
     opacity: 0%;
-    cursor: default;    
+    cursor: default;	
 }
 
 .output-html p {margin: 0 0.5em;}
@@ -442,7 +442,7 @@ input[type="range"]{
 }
 
 .red {
-    color: red;
+	color: red;
 }
 
 .gallery-item {
@@ -505,4 +505,4 @@ canvas[key="mask"] {
     top: -0.6em;
     z-index: 200;
     width: 8em;
-}
\ No newline at end of file
+}
-- 
cgit v1.2.3


From 4a37c7eedeab579efec03e8dae3f3f9fd4a37b02 Mon Sep 17 00:00:00 2001
From: yfszzx <yfszzx@gmail.com>
Date: Fri, 14 Oct 2022 11:48:28 +0800
Subject: fix  deep nesting directories problem

---
 modules/images_history.py | 76 ++++++++++++++++++++++++++---------------------
 1 file changed, 42 insertions(+), 34 deletions(-)

diff --git a/modules/images_history.py b/modules/images_history.py
index cdfcffed..723f5301 100644
--- a/modules/images_history.py
+++ b/modules/images_history.py
@@ -1,44 +1,47 @@
 import os
 import shutil
-def get_recent_images(dir_name, page_index, step, image_index, tabname):
-    #print(f"renew page {page_index}")
-    page_index = int(page_index)
-    f_list = os.listdir(dir_name)
-    file_list = []
+def traverse_all_files(output_dir, image_list, curr_dir=None):
+    curr_path = output_dir if curr_dir is None else os.path.join(output_dir, curr_dir)
+    try:
+        f_list = os.listdir(curr_path)
+    except:
+        if curr_dir[-10:].rfind(".") > 0 and curr_dir[-4:] != ".txt":
+            image_list.append(curr_dir)
+        return image_list
     for file in f_list:
+        file = file if curr_dir is None else os.path.join(curr_dir, file)
+        file_path = os.path.join(curr_path, file)
         if file[-4:] == ".txt":
-            continue
-        #subdirectories        
-        if file[-10:].rfind(".") < 0:
-            sub_dir = os.path.join(dir_name, file)
-            if os.path.isfile(sub_dir):
-                continue
-            sub_file_list = os.listdir(sub_dir)
-            for sub_file in sub_file_list:
-                if sub_file[-4:] == ".txt":
-                    continue
-                if os.path.isfile(os.path.join(sub_dir, sub_file) ): 
-                    file_list.append(os.path.join(file, sub_file)) 
-            continue
-        file_list.append(file)        
+            pass
+        elif os.path.isfile(file_path) and file[-10:].rfind(".") > 0:
+            image_list.append(file)
+        else:
+            image_list = traverse_all_files(output_dir, image_list, file)            
+    return image_list
 
-    file_list = sorted(file_list, key=lambda file: -os.path.getctime(os.path.join(dir_name, file)))
+        
+def get_recent_images(dir_name, page_index, step, image_index, tabname):
+    page_index = int(page_index)
+    f_list = os.listdir(dir_name)
+    image_list = []
+    image_list = traverse_all_files(dir_name, image_list)
+    image_list = sorted(image_list, key=lambda file: -os.path.getctime(os.path.join(dir_name, file)))
     num = 48 if tabname != "extras" else 12
-    max_page_index = len(file_list) // num + 1    
+    max_page_index = len(image_list) // num + 1    
     page_index = max_page_index if page_index == -1 else page_index + step
     page_index = 1 if page_index < 1 else page_index    
     page_index = max_page_index if page_index > max_page_index else page_index
     idx_frm = (page_index - 1) * num
-    file_list = file_list[idx_frm:idx_frm + num]
-    #print(f"Loading history page {page_index}")    
+    image_list = image_list[idx_frm:idx_frm + num]
     image_index = int(image_index)
-    if image_index < 0 or image_index > len(file_list)  - 1:
+    if image_index < 0 or image_index > len(image_list)  - 1:
         current_file = None 
-        hide_image = None
+        hidden = None
     else:
-        current_file =  file_list[int(image_index)]
-        hide_image = os.path.join(dir_name, current_file)
-    return [os.path.join(dir_name, file) for file in file_list], page_index, file_list, current_file, hide_image, ""
+        current_file =  image_list[int(image_index)]
+        hidden = os.path.join(dir_name, current_file)
+    return [os.path.join(dir_name, file) for file in image_list], page_index, image_list, current_file, hidden, ""
+
 def first_page_click(dir_name, page_index, image_index, tabname):
     return get_recent_images(dir_name, 1, 0, image_index, tabname)
 def end_page_click(dir_name, page_index, image_index, tabname):
@@ -85,6 +88,10 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict):
             dir_name = opts.outdir_img2img_samples
         elif tabname == "extras":
             dir_name = opts.outdir_extras_samples
+        d = dir_name.split("/")
+        dir_name = d[0]
+        for p in d[1:]:
+            dir_name = os.path.join(dir_name, p)
         with gr.Row():    
             renew_page = gr.Button('Renew Page', elem_id=tabname + "_images_history_renew_page") 
             first_page = gr.Button('First Page')
@@ -109,19 +116,20 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict):
                             img_file_name = gr.Textbox(label="File Name", interactive=False)    
                     with gr.Row():    
                         # hiden items
-                        img_path = gr.Textbox(dir_name, visible=False)                
+
+                        img_path = gr.Textbox(dir_name.rstrip("/") , visible=False)                
                         tabname_box = gr.Textbox(tabname, visible=False)    
                         image_index = gr.Textbox(value=-1, visible=False)                        
                         set_index = gr.Button('set_index',  elem_id=tabname + "_images_history_set_index", visible=False)
                         filenames = gr.State()
-                        hide_image = gr.Image(type="pil", visible=False)
+                        hidden = gr.Image(type="pil", visible=False)
                         info1 = gr.Textbox(visible=False)
                         info2 = gr.Textbox(visible=False)
 
                 
         # turn pages
         gallery_inputs = [img_path, page_index, image_index, tabname_box]
-        gallery_outputs = [history_gallery, page_index, filenames, img_file_name, hide_image, img_file_name]
+        gallery_outputs = [history_gallery, page_index, filenames, img_file_name, hidden, img_file_name]
 
         first_page.click(first_page_click, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)
         next_page.click(next_page_click, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)
@@ -132,12 +140,12 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict):
         #page_index.change(page_index_change, inputs=[tabname_box, img_path,  page_index], outputs=[history_gallery, page_index])
 
         #other funcitons
-        set_index.click(show_image_info, _js="images_history_get_current_img", inputs=[tabname_box,  img_path, filenames], outputs=[img_file_name, image_index, hide_image])
+        set_index.click(show_image_info, _js="images_history_get_current_img", inputs=[tabname_box,  img_path, filenames], outputs=[img_file_name, image_index, hidden])
         img_file_name.change(fn=None, _js="images_history_enable_del_buttons", inputs=None, outputs=None)
         delete.click(delete_image,_js="images_history_delete", inputs=[delete_num, tabname_box, img_path, img_file_name, page_index, filenames, image_index], outputs=[filenames, delete_num]) 
-        hide_image.change(fn=run_pnginfo, inputs=[hide_image], outputs=[info1, img_file_info, info2])
+        hidden.change(fn=run_pnginfo, inputs=[hidden], outputs=[info1, img_file_info, info2])
        
-        #pnginfo.click(fn=run_pnginfo, inputs=[hide_image], outputs=[info1, img_file_info, info2])
+        #pnginfo.click(fn=run_pnginfo, inputs=[hidden], outputs=[info1, img_file_info, info2])
         switch_dict["fn"](pnginfo_send_to_txt2img, switch_dict["t2i"], img_file_info, 'switch_to_txt2img')
         switch_dict["fn"](pnginfo_send_to_img2img, switch_dict["i2i"], img_file_info, 'switch_to_img2img_img2img')
     
-- 
cgit v1.2.3


From 494afccbc1d7b0aca4ffeb3d8354b09c414d95f4 Mon Sep 17 00:00:00 2001
From: crackfoo <info@zpool.ca>
Date: Thu, 13 Oct 2022 20:26:54 -0700
Subject: Update hints.js

typo
---
 javascript/hints.js | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/javascript/hints.js b/javascript/hints.js
index f65e7b88..94438c5c 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -83,7 +83,7 @@ titles = {
     "Do not add watermark to images": "If this option is enabled, watermark will not be added to created images. Warning: if you do not add watermark, you may be behaving in an unethical manner.",
 
     "Filename word regex": "This regular expression will be used extract words from filename, and they will be joined using the option below into label text used for training. Leave empty to keep filename text as it is.",
-    "Filename join string": "This string will be used to hoin split words into a single line if the option above is enabled.",
+    "Filename join string": "This string will be used to join split words into a single line if the option above is enabled.",
 
     "Quicksettings list": "List of setting names, separated by commas, for settings that should go to the quick access bar at the top, rather than the usual setting tab. See modules/shared.py for setting names. Requires restarting to apply."
 }
-- 
cgit v1.2.3


From fdecb636855748e03efc40c846a0043800aadfcc Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 14 Oct 2022 09:05:06 +0300
Subject: add an ability to merge three checkpoints

---
 javascript/hints.js |  5 ++++-
 modules/extras.py   | 29 +++++++++++++++++++++--------
 modules/ui.py       | 11 +++++++----
 3 files changed, 32 insertions(+), 13 deletions(-)

diff --git a/javascript/hints.js b/javascript/hints.js
index 94438c5c..af010a59 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -85,7 +85,10 @@ titles = {
     "Filename word regex": "This regular expression will be used extract words from filename, and they will be joined using the option below into label text used for training. Leave empty to keep filename text as it is.",
     "Filename join string": "This string will be used to join split words into a single line if the option above is enabled.",
 
-    "Quicksettings list": "List of setting names, separated by commas, for settings that should go to the quick access bar at the top, rather than the usual setting tab. See modules/shared.py for setting names. Requires restarting to apply."
+    "Quicksettings list": "List of setting names, separated by commas, for settings that should go to the quick access bar at the top, rather than the usual setting tab. See modules/shared.py for setting names. Requires restarting to apply.",
+
+    "Weighted Sum": "Result = A * (1 - M) + B * M",
+    "Add difference": "Result = A + (B - C) * (1 - M)",
 }
 
 
diff --git a/modules/extras.py b/modules/extras.py
index b24d7de3..532d869f 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -159,48 +159,61 @@ def run_pnginfo(image):
     return '', geninfo, info
 
 
-def run_modelmerger(primary_model_name, secondary_model_name, interp_method, interp_amount, save_as_half, custom_name):
+def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_name, interp_method, interp_amount, save_as_half, custom_name):
     # Linear interpolation (https://en.wikipedia.org/wiki/Linear_interpolation)
-    def weighted_sum(theta0, theta1, alpha):
+    def weighted_sum(theta0, theta1, theta2, alpha):
         return ((1 - alpha) * theta0) + (alpha * theta1)
 
     # Smoothstep (https://en.wikipedia.org/wiki/Smoothstep)
-    def sigmoid(theta0, theta1, alpha):
+    def sigmoid(theta0, theta1, theta2, alpha):
         alpha = alpha * alpha * (3 - (2 * alpha))
         return theta0 + ((theta1 - theta0) * alpha)
 
     # Inverse Smoothstep (https://en.wikipedia.org/wiki/Smoothstep)
-    def inv_sigmoid(theta0, theta1, alpha):
+    def inv_sigmoid(theta0, theta1, theta2, alpha):
         import math
         alpha = 0.5 - math.sin(math.asin(1.0 - 2.0 * alpha) / 3.0)
         return theta0 + ((theta1 - theta0) * alpha)
 
+    def add_difference(theta0, theta1, theta2, alpha):
+        return theta0 + (theta1 - theta2) * (1.0 - alpha)
+
     primary_model_info = sd_models.checkpoints_list[primary_model_name]
     secondary_model_info = sd_models.checkpoints_list[secondary_model_name]
+    teritary_model_info = sd_models.checkpoints_list.get(teritary_model_name, None)
 
     print(f"Loading {primary_model_info.filename}...")
     primary_model = torch.load(primary_model_info.filename, map_location='cpu')
+    theta_0 = sd_models.get_state_dict_from_checkpoint(primary_model)
 
     print(f"Loading {secondary_model_info.filename}...")
     secondary_model = torch.load(secondary_model_info.filename, map_location='cpu')
-
-    theta_0 = sd_models.get_state_dict_from_checkpoint(primary_model)
     theta_1 = sd_models.get_state_dict_from_checkpoint(secondary_model)
 
+    if teritary_model_info is not None:
+        print(f"Loading {teritary_model_info.filename}...")
+        teritary_model = torch.load(teritary_model_info.filename, map_location='cpu')
+        theta_2 = sd_models.get_state_dict_from_checkpoint(teritary_model)
+    else:
+        theta_2 = None
+
     theta_funcs = {
         "Weighted Sum": weighted_sum,
         "Sigmoid": sigmoid,
         "Inverse Sigmoid": inv_sigmoid,
+        "Add difference": add_difference,
     }
     theta_func = theta_funcs[interp_method]
 
     print(f"Merging...")
+
     for key in tqdm.tqdm(theta_0.keys()):
         if 'model' in key and key in theta_1:
-            theta_0[key] = theta_func(theta_0[key], theta_1[key], (float(1.0) - interp_amount))  # Need to reverse the interp_amount to match the desired mix ration in the merged checkpoint
+            theta_0[key] = theta_func(theta_0[key], theta_1[key], theta_2[key] if theta_2 else None, (float(1.0) - interp_amount))  # Need to reverse the interp_amount to match the desired mix ration in the merged checkpoint
             if save_as_half:
                 theta_0[key] = theta_0[key].half()
 
+    # I believe this part should be discarded, but I'll leave it for now until I am sure
     for key in theta_1.keys():
         if 'model' in key and key not in theta_0:
             theta_0[key] = theta_1[key]
@@ -219,4 +232,4 @@ def run_modelmerger(primary_model_name, secondary_model_name, interp_method, int
     sd_models.list_models()
 
     print(f"Checkpoint saved.")
-    return ["Checkpoint saved to " + output_modelname] + [gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(3)]
+    return ["Checkpoint saved to " + output_modelname] + [gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)]
diff --git a/modules/ui.py b/modules/ui.py
index 7446439d..220fb80b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1024,11 +1024,12 @@ def create_ui(wrap_gradio_gpu_call):
                 gr.HTML(value="<p>A merger of the two checkpoints will be generated in your <b>checkpoint</b> directory.</p>")
 
                 with gr.Row():
-                    primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary Model Name")
-                    secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary Model Name")
+                    primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)")
+                    secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary model (B)")
+                    tertiary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_tertiary_model_name", label="Tertiary model (C)")
                 custom_name = gr.Textbox(label="Custom Name (Optional)")
-                interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Interpolation Amount', value=0.3)
-                interp_method = gr.Radio(choices=["Weighted Sum", "Sigmoid", "Inverse Sigmoid"], value="Weighted Sum", label="Interpolation Method")
+                interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Interpolation amount (1 - M)', value=0.3)
+                interp_method = gr.Radio(choices=["Weighted Sum", "Sigmoid", "Inverse Sigmoid", "Add difference"], value="Weighted Sum", label="Interpolation Method")
                 save_as_half = gr.Checkbox(value=False, label="Save as float16")
                 modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary')
 
@@ -1473,6 +1474,7 @@ Requested path was: {f}
             inputs=[
                 primary_model_name,
                 secondary_model_name,
+                tertiary_model_name,
                 interp_method,
                 interp_amount,
                 save_as_half,
@@ -1482,6 +1484,7 @@ Requested path was: {f}
                 submit_result,
                 primary_model_name,
                 secondary_model_name,
+                tertiary_model_name,
                 component_dict['sd_model_checkpoint'],
             ]
         )
-- 
cgit v1.2.3


From fdef8253a43ca5135923092ca9b85e878d980869 Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Fri, 14 Oct 2022 04:42:53 -0400
Subject: Add 'interrogate' and 'all' choices to --use-cpu

* Add 'interrogate' and 'all' choices to --use-cpu
* Change type for --use-cpu argument to str.lower, so that choices are case insensitive
---
 modules/devices.py     |  2 +-
 modules/interrogate.py | 14 +++++++-------
 modules/shared.py      |  6 +++---
 3 files changed, 11 insertions(+), 11 deletions(-)

diff --git a/modules/devices.py b/modules/devices.py
index 03ef58f1..eb422583 100644
--- a/modules/devices.py
+++ b/modules/devices.py
@@ -34,7 +34,7 @@ def enable_tf32():
 
 errors.run(enable_tf32, "Enabling TF32")
 
-device = device_gfpgan = device_bsrgan = device_esrgan = device_scunet = device_codeformer = get_optimal_device()
+device = device_interrogate = device_gfpgan = device_bsrgan = device_esrgan = device_scunet = device_codeformer = get_optimal_device()
 dtype = torch.float16
 dtype_vae = torch.float16
 
diff --git a/modules/interrogate.py b/modules/interrogate.py
index af858cc0..9263d65a 100644
--- a/modules/interrogate.py
+++ b/modules/interrogate.py
@@ -55,7 +55,7 @@ class InterrogateModels:
 
         model, preprocess = clip.load(clip_model_name)
         model.eval()
-        model = model.to(shared.device)
+        model = model.to(devices.device_interrogate)
 
         return model, preprocess
 
@@ -65,14 +65,14 @@ class InterrogateModels:
             if not shared.cmd_opts.no_half:
                 self.blip_model = self.blip_model.half()
 
-        self.blip_model = self.blip_model.to(shared.device)
+        self.blip_model = self.blip_model.to(devices.device_interrogate)
 
         if self.clip_model is None:
             self.clip_model, self.clip_preprocess = self.load_clip_model()
             if not shared.cmd_opts.no_half:
                 self.clip_model = self.clip_model.half()
 
-        self.clip_model = self.clip_model.to(shared.device)
+        self.clip_model = self.clip_model.to(devices.device_interrogate)
 
         self.dtype = next(self.clip_model.parameters()).dtype
 
@@ -99,11 +99,11 @@ class InterrogateModels:
             text_array = text_array[0:int(shared.opts.interrogate_clip_dict_limit)]
 
         top_count = min(top_count, len(text_array))
-        text_tokens = clip.tokenize([text for text in text_array], truncate=True).to(shared.device)
+        text_tokens = clip.tokenize([text for text in text_array], truncate=True).to(devices.device_interrogate)
         text_features = self.clip_model.encode_text(text_tokens).type(self.dtype)
         text_features /= text_features.norm(dim=-1, keepdim=True)
 
-        similarity = torch.zeros((1, len(text_array))).to(shared.device)
+        similarity = torch.zeros((1, len(text_array))).to(devices.device_interrogate)
         for i in range(image_features.shape[0]):
             similarity += (100.0 * image_features[i].unsqueeze(0) @ text_features.T).softmax(dim=-1)
         similarity /= image_features.shape[0]
@@ -116,7 +116,7 @@ class InterrogateModels:
             transforms.Resize((blip_image_eval_size, blip_image_eval_size), interpolation=InterpolationMode.BICUBIC),
             transforms.ToTensor(),
             transforms.Normalize((0.48145466, 0.4578275, 0.40821073), (0.26862954, 0.26130258, 0.27577711))
-        ])(pil_image).unsqueeze(0).type(self.dtype).to(shared.device)
+        ])(pil_image).unsqueeze(0).type(self.dtype).to(devices.device_interrogate)
 
         with torch.no_grad():
             caption = self.blip_model.generate(gpu_image, sample=False, num_beams=shared.opts.interrogate_clip_num_beams, min_length=shared.opts.interrogate_clip_min_length, max_length=shared.opts.interrogate_clip_max_length)
@@ -140,7 +140,7 @@ class InterrogateModels:
 
             res = caption
 
-            clip_image = self.clip_preprocess(pil_image).unsqueeze(0).type(self.dtype).to(shared.device)
+            clip_image = self.clip_preprocess(pil_image).unsqueeze(0).type(self.dtype).to(devices.device_interrogate)
 
             precision_scope = torch.autocast if shared.cmd_opts.precision == "autocast" else contextlib.nullcontext
             with torch.no_grad(), precision_scope("cuda"):
diff --git a/modules/shared.py b/modules/shared.py
index 5901e605..b6a5c1a8 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -54,7 +54,7 @@ parser.add_argument("--opt-split-attention", action='store_true', help="force-en
 parser.add_argument("--opt-split-attention-invokeai", action='store_true', help="force-enables InvokeAI's cross-attention layer optimization. By default, it's on when cuda is unavailable.")
 parser.add_argument("--opt-split-attention-v1", action='store_true', help="enable older version of split attention optimization that does not consume all the VRAM it can find")
 parser.add_argument("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization")
-parser.add_argument("--use-cpu", nargs='+',choices=['SD', 'GFPGAN', 'BSRGAN', 'ESRGAN', 'SCUNet', 'CodeFormer'], help="use CPU as torch device for specified modules", default=[])
+parser.add_argument("--use-cpu", nargs='+',choices=['all', 'sd', 'interrogate', 'gfpgan', 'bsrgan', 'esrgan', 'scunet', 'codeformer'], help="use CPU as torch device for specified modules", default=[], type=str.lower)
 parser.add_argument("--listen", action='store_true', help="launch gradio with 0.0.0.0 as server name, allowing to respond to network requests")
 parser.add_argument("--port", type=int, help="launch gradio with given server port, you need root/admin rights for ports < 1024, defaults to 7860 if available", default=None)
 parser.add_argument("--show-negative-prompt", action='store_true', help="does not do anything", default=False)
@@ -76,8 +76,8 @@ parser.add_argument("--disable-safe-unpickle", action='store_true', help="disabl
 
 cmd_opts = parser.parse_args()
 
-devices.device, devices.device_gfpgan, devices.device_bsrgan, devices.device_esrgan, devices.device_scunet, devices.device_codeformer = \
-(devices.cpu if x in cmd_opts.use_cpu else devices.get_optimal_device() for x in ['SD', 'GFPGAN', 'BSRGAN', 'ESRGAN', 'SCUNet', 'CodeFormer'])
+devices.device, devices.device_interrogate, devices.device_gfpgan, devices.device_bsrgan, devices.device_esrgan, devices.device_scunet, devices.device_codeformer = \
+(devices.cpu if any(y in cmd_opts.use_cpu for y in [x, 'all']) else devices.get_optimal_device() for x in ['sd', 'interrogate', 'gfpgan', 'bsrgan', 'esrgan', 'scunet', 'codeformer'])
 
 device = devices.device
 
-- 
cgit v1.2.3


From 9e5ca5077f43bb3ec1a0ec41b47964cb38d544a6 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 14 Oct 2022 16:37:32 +0300
Subject: extra message for unpicking fails

---
 modules/safe.py | 9 ++++++++-
 1 file changed, 8 insertions(+), 1 deletion(-)

diff --git a/modules/safe.py b/modules/safe.py
index 20be16a5..399165a1 100644
--- a/modules/safe.py
+++ b/modules/safe.py
@@ -96,11 +96,18 @@ def load(filename, *args, **kwargs):
         if not shared.cmd_opts.disable_safe_unpickle:
             check_pt(filename)
 
+    except pickle.UnpicklingError:
+        print(f"Error verifying pickled file from {filename}:", file=sys.stderr)
+        print(traceback.format_exc(), file=sys.stderr)
+        print(f"-----> !!!! The file is most likely corrupted !!!! <-----", file=sys.stderr)
+        print(f"You can skip this check with --disable-safe-unpickle commandline argument, but that is not going to help you.\n\n", file=sys.stderr)
+        return None
+
     except Exception:
         print(f"Error verifying pickled file from {filename}:", file=sys.stderr)
         print(traceback.format_exc(), file=sys.stderr)
         print(f"\nThe file may be malicious, so the program is not going to read it.", file=sys.stderr)
-        print(f"You can skip this check with --disable-safe-unpickle commandline argument.", file=sys.stderr)
+        print(f"You can skip this check with --disable-safe-unpickle commandline argument.\n\n", file=sys.stderr)
         return None
 
     return unsafe_torch_load(filename, *args, **kwargs)
-- 
cgit v1.2.3


From b2261b53ae4ad01b3713bc73ff62ab7b6f479e26 Mon Sep 17 00:00:00 2001
From: Buckzor <bucklogos@yahoo.co.uk>
Date: Thu, 13 Oct 2022 17:07:06 +0100
Subject: Added first_pass_width and height as adjustable inputs to "High Res
 Fix"

---
 modules/processing.py | 6 ++++--
 modules/txt2img.py    | 5 ++++-
 modules/ui.py         | 6 ++++++
 3 files changed, 14 insertions(+), 3 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index d5172f00..abbfdf98 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -506,11 +506,13 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
     firstphase_width_truncated = 0
     firstphase_height_truncated = 0
 
-    def __init__(self, enable_hr=False, scale_latent=True, denoising_strength=0.75, **kwargs):
+    def __init__(self, enable_hr=False, scale_latent=True, denoising_strength=0.75, first_pass_width=512, first_pass_height=512, **kwargs):
         super().__init__(**kwargs)
         self.enable_hr = enable_hr
         self.scale_latent = scale_latent
         self.denoising_strength = denoising_strength
+        self.first_pass_width = first_pass_width
+        self.first_pass_height = first_pass_height
 
     def init(self, all_prompts, all_seeds, all_subseeds):
         if self.enable_hr:
@@ -519,7 +521,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
             else:
                 state.job_count = state.job_count * 2
 
-            desired_pixel_count = 512 * 512
+            desired_pixel_count = self.first_pass_width * self.first_pass_height
             actual_pixel_count = self.width * self.height
             scale = math.sqrt(desired_pixel_count / actual_pixel_count)
 
diff --git a/modules/txt2img.py b/modules/txt2img.py
index e985242b..85cbece4 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -6,7 +6,7 @@ import modules.processing as processing
 from modules.ui import plaintext_to_html
 
 
-def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, scale_latent: bool, denoising_strength: float, *args):
+def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, scale_latent: bool, denoising_strength: float, first_pass_width: int, first_pass_height: int, *args):
     p = StableDiffusionProcessingTxt2Img(
         sd_model=shared.sd_model,
         outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples,
@@ -32,6 +32,9 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2:
         enable_hr=enable_hr,
         scale_latent=scale_latent if enable_hr else None,
         denoising_strength=denoising_strength if enable_hr else None,
+		first_pass_width=first_pass_width if enable_hr else None,
+		first_pass_height=first_pass_height if enable_hr else None,
+
     )
 
     if cmd_opts.enable_console_prompts:
diff --git a/modules/ui.py b/modules/ui.py
index 220fb80b..544419b2 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -540,6 +540,8 @@ def create_ui(wrap_gradio_gpu_call):
                     enable_hr = gr.Checkbox(label='Highres. fix', value=False)
 
                 with gr.Row(visible=False) as hr_options:
+                    first_pass_width = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass width", value=512)
+                    first_pass_height = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass height", value=512)
                     scale_latent = gr.Checkbox(label='Scale latent', value=False)
                     denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7)
 
@@ -604,6 +606,8 @@ def create_ui(wrap_gradio_gpu_call):
                     enable_hr,
                     scale_latent,
                     denoising_strength,
+                    first_pass_width,
+                    first_pass_height,
                 ] + custom_inputs,
                 outputs=[
                     txt2img_gallery,
@@ -668,6 +672,8 @@ def create_ui(wrap_gradio_gpu_call):
                 (denoising_strength, "Denoising strength"),
                 (enable_hr, lambda d: "Denoising strength" in d),
                 (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)),
+                (first_pass_width, "First pass width"),
+                (first_pass_height, "First pass height"),
             ]
             modules.generation_parameters_copypaste.connect_paste(paste, txt2img_paste_fields, txt2img_prompt)
             token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter])
-- 
cgit v1.2.3


From 40d1c6e423b4dc52b3bdae43d9e2442960760ced Mon Sep 17 00:00:00 2001
From: Buckzor <bucklogos@yahoo.co.uk>
Date: Thu, 13 Oct 2022 20:04:22 +0100
Subject: Option between stretch and crop for Highres. fix

---
 modules/processing.py | 34 ++++++++++++++++++++++------------
 modules/txt2img.py    |  7 ++++---
 modules/ui.py         | 25 ++++++++++++++++---------
 3 files changed, 42 insertions(+), 24 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index abbfdf98..0246f5dd 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -506,13 +506,14 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
     firstphase_width_truncated = 0
     firstphase_height_truncated = 0
 
-    def __init__(self, enable_hr=False, scale_latent=True, denoising_strength=0.75, first_pass_width=512, first_pass_height=512, **kwargs):
+    def __init__(self, enable_hr=False, scale_latent=True, denoising_strength=0.75, firstphase_width=512, firstphase_height=512, crop_scale=False, **kwargs):
         super().__init__(**kwargs)
         self.enable_hr = enable_hr
         self.scale_latent = scale_latent
         self.denoising_strength = denoising_strength
-        self.first_pass_width = first_pass_width
-        self.first_pass_height = first_pass_height
+        self.firstphase_width = firstphase_width
+        self.firstphase_height = firstphase_height
+        self.crop_scale = crop_scale
 
     def init(self, all_prompts, all_seeds, all_subseeds):
         if self.enable_hr:
@@ -521,14 +522,14 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
             else:
                 state.job_count = state.job_count * 2
 
-            desired_pixel_count = self.first_pass_width * self.first_pass_height
-            actual_pixel_count = self.width * self.height
-            scale = math.sqrt(desired_pixel_count / actual_pixel_count)
+            #desired_pixel_count = self.firstphase_width * self.firstphase_height
+            #actual_pixel_count = self.width * self.height
+            #scale = math.sqrt(desired_pixel_count / actual_pixel_count)
 
-            self.firstphase_width = math.ceil(scale * self.width / 64) * 64
-            self.firstphase_height = math.ceil(scale * self.height / 64) * 64
-            self.firstphase_width_truncated = int(scale * self.width)
-            self.firstphase_height_truncated = int(scale * self.height)
+            #self.firstphase_width = math.ceil(scale * self.width / 64) * 64
+            #self.firstphase_height = math.ceil(scale * self.height / 64) * 64
+            #self.firstphase_width_truncated = int(scale * self.width)
+            #self.firstphase_height_truncated = int(scale * self.height)
 
     def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength):
         self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers, self.sampler_index, self.sd_model)
@@ -541,8 +542,17 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
         x = create_random_tensors([opt_C, self.firstphase_height // opt_f, self.firstphase_width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self)
         samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning)
 
-        truncate_x = (self.firstphase_width - self.firstphase_width_truncated) // opt_f
-        truncate_y = (self.firstphase_height - self.firstphase_height_truncated) // opt_f
+        truncate_x = 0
+        truncate_y = 0
+
+        if self.crop_scale:
+            if self.width/self.firstphase_width > self.height/self.firstphase_height:
+                #Crop to landscape
+                truncate_y = (self.width -  self.firstphase_width)//2 // opt_f
+
+            elif self.width/self.firstphase_width < self.height/self.firstphase_height:
+                #Crop to portrait
+                truncate_x = (self.height - self.firstphase_height)//2 // opt_f
 
         samples = samples[:, :, truncate_y//2:samples.shape[2]-truncate_y//2, truncate_x//2:samples.shape[3]-truncate_x//2]
 
diff --git a/modules/txt2img.py b/modules/txt2img.py
index 85cbece4..447ec3d3 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -6,7 +6,7 @@ import modules.processing as processing
 from modules.ui import plaintext_to_html
 
 
-def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, scale_latent: bool, denoising_strength: float, first_pass_width: int, first_pass_height: int, *args):
+def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, scale_latent: bool, denoising_strength: float, firstphase_width: int, firstphase_height: int, crop_scale: bool, *args):
     p = StableDiffusionProcessingTxt2Img(
         sd_model=shared.sd_model,
         outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples,
@@ -32,8 +32,9 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2:
         enable_hr=enable_hr,
         scale_latent=scale_latent if enable_hr else None,
         denoising_strength=denoising_strength if enable_hr else None,
-		first_pass_width=first_pass_width if enable_hr else None,
-		first_pass_height=first_pass_height if enable_hr else None,
+		firstphase_width=firstphase_width if enable_hr else None,
+		firstphase_height=firstphase_height if enable_hr else None,
+        crop_scale=crop_scale if enable_hr else None,
 
     )
 
diff --git a/modules/ui.py b/modules/ui.py
index 544419b2..f2d81f68 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -540,12 +540,18 @@ def create_ui(wrap_gradio_gpu_call):
                     enable_hr = gr.Checkbox(label='Highres. fix', value=False)
 
                 with gr.Row(visible=False) as hr_options:
-                    first_pass_width = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass width", value=512)
-                    first_pass_height = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass height", value=512)
-                    scale_latent = gr.Checkbox(label='Scale latent', value=False)
-                    denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7)
+                    with gr.Column(scale=1.0):
+                        firstphase_width = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass width", value=512)
+                        firstphase_height = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass height", value=512)
+                        
+                    with gr.Column(scale=1.0):
+                        with gr.Row():
+                            crop_scale = gr.Checkbox(label='Crop when scaling', value=False)
+                            scale_latent = gr.Checkbox(label='Scale latent', value=False)
+                        with gr.Row():
+                            denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7)
 
-                with gr.Row():
+                with gr.Row(equal_height=True):
                     batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1)
                     batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1)
 
@@ -606,8 +612,9 @@ def create_ui(wrap_gradio_gpu_call):
                     enable_hr,
                     scale_latent,
                     denoising_strength,
-                    first_pass_width,
-                    first_pass_height,
+                    firstphase_width,
+                    firstphase_height,
+                    crop_scale,
                 ] + custom_inputs,
                 outputs=[
                     txt2img_gallery,
@@ -672,8 +679,8 @@ def create_ui(wrap_gradio_gpu_call):
                 (denoising_strength, "Denoising strength"),
                 (enable_hr, lambda d: "Denoising strength" in d),
                 (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)),
-                (first_pass_width, "First pass width"),
-                (first_pass_height, "First pass height"),
+                (firstphase_width, "First pass width"),
+                (firstphase_height, "First pass height"),
             ]
             modules.generation_parameters_copypaste.connect_paste(paste, txt2img_paste_fields, txt2img_prompt)
             token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter])
-- 
cgit v1.2.3


From b382de2d77c653c565840ce92d27aa668a1934d7 Mon Sep 17 00:00:00 2001
From: Buckzor <bucklogos@yahoo.co.uk>
Date: Thu, 13 Oct 2022 22:23:22 +0100
Subject: Fixed Scale ratio problem

---
 modules/processing.py | 25 +++++++++++--------------
 1 file changed, 11 insertions(+), 14 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index 0246f5dd..d9b0e0e7 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -522,15 +522,6 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
             else:
                 state.job_count = state.job_count * 2
 
-            #desired_pixel_count = self.firstphase_width * self.firstphase_height
-            #actual_pixel_count = self.width * self.height
-            #scale = math.sqrt(desired_pixel_count / actual_pixel_count)
-
-            #self.firstphase_width = math.ceil(scale * self.width / 64) * 64
-            #self.firstphase_height = math.ceil(scale * self.height / 64) * 64
-            #self.firstphase_width_truncated = int(scale * self.width)
-            #self.firstphase_height_truncated = int(scale * self.height)
-
     def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength):
         self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers, self.sampler_index, self.sd_model)
 
@@ -544,17 +535,23 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
 
         truncate_x = 0
         truncate_y = 0
+        width_ratio = self.width/self.firstphase_width
+        height_ratio = self.height/self.firstphase_height
 
         if self.crop_scale:
-            if self.width/self.firstphase_width > self.height/self.firstphase_height:
+            if width_ratio > height_ratio:
                 #Crop to landscape
-                truncate_y = (self.width -  self.firstphase_width)//2 // opt_f
+                truncate_y = int((self.width - self.firstphase_width) / width_ratio / height_ratio / opt_f)
 
-            elif self.width/self.firstphase_width < self.height/self.firstphase_height:
+            elif width_ratio < height_ratio:
                 #Crop to portrait
-                truncate_x = (self.height - self.firstphase_height)//2 // opt_f
+                truncate_x = int((self.height - self.firstphase_height) / width_ratio / height_ratio / opt_f)
+                
+            samples = samples[:, :, truncate_y//2:samples.shape[2]-truncate_y//2, truncate_x//2:samples.shape[3]-truncate_x//2]
+
+        
 
-        samples = samples[:, :, truncate_y//2:samples.shape[2]-truncate_y//2, truncate_x//2:samples.shape[3]-truncate_x//2]
+        
 
         if self.scale_latent:
             samples = torch.nn.functional.interpolate(samples, size=(self.height // opt_f, self.width // opt_f), mode="bilinear")
-- 
cgit v1.2.3


From e644b5a80beb54b6df4caa63fb19d889dd4ceff6 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 14 Oct 2022 17:03:03 +0300
Subject: remove scale latent and no-crop options from hires fix support
 copy-pasting new parameters for hires fix

---
 modules/processing.py | 64 ++++++++++++++++++++++-----------------------------
 modules/txt2img.py    |  9 +++-----
 modules/ui.py         | 19 ++++-----------
 3 files changed, 35 insertions(+), 57 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index d9b0e0e7..100a259f 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -506,14 +506,12 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
     firstphase_width_truncated = 0
     firstphase_height_truncated = 0
 
-    def __init__(self, enable_hr=False, scale_latent=True, denoising_strength=0.75, firstphase_width=512, firstphase_height=512, crop_scale=False, **kwargs):
+    def __init__(self, enable_hr=False, denoising_strength=0.75, firstphase_width=512, firstphase_height=512, **kwargs):
         super().__init__(**kwargs)
         self.enable_hr = enable_hr
-        self.scale_latent = scale_latent
         self.denoising_strength = denoising_strength
         self.firstphase_width = firstphase_width
         self.firstphase_height = firstphase_height
-        self.crop_scale = crop_scale
 
     def init(self, all_prompts, all_seeds, all_subseeds):
         if self.enable_hr:
@@ -530,6 +528,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
             samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning)
             return samples
 
+        self.extra_generation_params["First pass size"] = f"{self.firstphase_width}x{self.firstphase_height}"
+
         x = create_random_tensors([opt_C, self.firstphase_height // opt_f, self.firstphase_width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self)
         samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning)
 
@@ -538,46 +538,36 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
         width_ratio = self.width/self.firstphase_width
         height_ratio = self.height/self.firstphase_height
 
-        if self.crop_scale:
-            if width_ratio > height_ratio:
-                #Crop to landscape
-                truncate_y = int((self.width - self.firstphase_width) / width_ratio / height_ratio / opt_f)
+        if width_ratio > height_ratio:
+            truncate_y = int((self.width - self.firstphase_width) / width_ratio / height_ratio / opt_f)
 
-            elif width_ratio < height_ratio:
-                #Crop to portrait
-                truncate_x = int((self.height - self.firstphase_height) / width_ratio / height_ratio / opt_f)
+        elif width_ratio < height_ratio:
+            truncate_x = int((self.height - self.firstphase_height) / width_ratio / height_ratio / opt_f)
                 
-            samples = samples[:, :, truncate_y//2:samples.shape[2]-truncate_y//2, truncate_x//2:samples.shape[3]-truncate_x//2]
-
-        
+        samples = samples[:, :, truncate_y//2:samples.shape[2]-truncate_y//2, truncate_x//2:samples.shape[3]-truncate_x//2]
 
-        
+        decoded_samples = decode_first_stage(self.sd_model, samples)
 
-        if self.scale_latent:
-            samples = torch.nn.functional.interpolate(samples, size=(self.height // opt_f, self.width // opt_f), mode="bilinear")
+        if opts.upscaler_for_img2img is None or opts.upscaler_for_img2img == "None":
+            decoded_samples = torch.nn.functional.interpolate(decoded_samples, size=(self.height, self.width), mode="bilinear")
         else:
-            decoded_samples = decode_first_stage(self.sd_model, samples)
+            lowres_samples = torch.clamp((decoded_samples + 1.0) / 2.0, min=0.0, max=1.0)
 
-            if opts.upscaler_for_img2img is None or opts.upscaler_for_img2img == "None":
-                decoded_samples = torch.nn.functional.interpolate(decoded_samples, size=(self.height, self.width), mode="bilinear")
-            else:
-                lowres_samples = torch.clamp((decoded_samples + 1.0) / 2.0, min=0.0, max=1.0)
-
-                batch_images = []
-                for i, x_sample in enumerate(lowres_samples):
-                    x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2)
-                    x_sample = x_sample.astype(np.uint8)
-                    image = Image.fromarray(x_sample)
-                    image = images.resize_image(0, image, self.width, self.height)
-                    image = np.array(image).astype(np.float32) / 255.0
-                    image = np.moveaxis(image, 2, 0)
-                    batch_images.append(image)
-
-                decoded_samples = torch.from_numpy(np.array(batch_images))
-                decoded_samples = decoded_samples.to(shared.device)
-                decoded_samples = 2. * decoded_samples - 1.
-
-            samples = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(decoded_samples))
+            batch_images = []
+            for i, x_sample in enumerate(lowres_samples):
+                x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2)
+                x_sample = x_sample.astype(np.uint8)
+                image = Image.fromarray(x_sample)
+                image = images.resize_image(0, image, self.width, self.height)
+                image = np.array(image).astype(np.float32) / 255.0
+                image = np.moveaxis(image, 2, 0)
+                batch_images.append(image)
+
+            decoded_samples = torch.from_numpy(np.array(batch_images))
+            decoded_samples = decoded_samples.to(shared.device)
+            decoded_samples = 2. * decoded_samples - 1.
+
+        samples = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(decoded_samples))
 
         shared.state.nextjob()
 
diff --git a/modules/txt2img.py b/modules/txt2img.py
index 447ec3d3..2381347f 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -6,7 +6,7 @@ import modules.processing as processing
 from modules.ui import plaintext_to_html
 
 
-def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, scale_latent: bool, denoising_strength: float, firstphase_width: int, firstphase_height: int, crop_scale: bool, *args):
+def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, firstphase_width: int, firstphase_height: int, *args):
     p = StableDiffusionProcessingTxt2Img(
         sd_model=shared.sd_model,
         outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples,
@@ -30,12 +30,9 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2:
         restore_faces=restore_faces,
         tiling=tiling,
         enable_hr=enable_hr,
-        scale_latent=scale_latent if enable_hr else None,
         denoising_strength=denoising_strength if enable_hr else None,
-		firstphase_width=firstphase_width if enable_hr else None,
-		firstphase_height=firstphase_height if enable_hr else None,
-        crop_scale=crop_scale if enable_hr else None,
-
+        firstphase_width=firstphase_width if enable_hr else None,
+        firstphase_height=firstphase_height if enable_hr else None,
     )
 
     if cmd_opts.enable_console_prompts:
diff --git a/modules/ui.py b/modules/ui.py
index f2d81f68..d66ddc14 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -540,16 +540,9 @@ def create_ui(wrap_gradio_gpu_call):
                     enable_hr = gr.Checkbox(label='Highres. fix', value=False)
 
                 with gr.Row(visible=False) as hr_options:
-                    with gr.Column(scale=1.0):
-                        firstphase_width = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass width", value=512)
-                        firstphase_height = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass height", value=512)
-                        
-                    with gr.Column(scale=1.0):
-                        with gr.Row():
-                            crop_scale = gr.Checkbox(label='Crop when scaling', value=False)
-                            scale_latent = gr.Checkbox(label='Scale latent', value=False)
-                        with gr.Row():
-                            denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7)
+                    firstphase_width = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass width", value=512)
+                    firstphase_height = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass height", value=512)
+                    denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7)
 
                 with gr.Row(equal_height=True):
                     batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1)
@@ -610,11 +603,9 @@ def create_ui(wrap_gradio_gpu_call):
                     height,
                     width,
                     enable_hr,
-                    scale_latent,
                     denoising_strength,
                     firstphase_width,
                     firstphase_height,
-                    crop_scale,
                 ] + custom_inputs,
                 outputs=[
                     txt2img_gallery,
@@ -679,8 +670,8 @@ def create_ui(wrap_gradio_gpu_call):
                 (denoising_strength, "Denoising strength"),
                 (enable_hr, lambda d: "Denoising strength" in d),
                 (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)),
-                (firstphase_width, "First pass width"),
-                (firstphase_height, "First pass height"),
+                (firstphase_width, "First pass size-1"),
+                (firstphase_height, "First pass size-2"),
             ]
             modules.generation_parameters_copypaste.connect_paste(paste, txt2img_paste_fields, txt2img_prompt)
             token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter])
-- 
cgit v1.2.3


From 33ae6be55eaedabd49c8c888ec0b37c612618fdf Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 14 Oct 2022 17:53:34 +0300
Subject: fix paste not working in firefox fix paste always going into txt2img
 field

---
 javascript/dragdrop.js    |  2 +-
 javascript/imageParams.js | 29 +++++++++++++----------------
 2 files changed, 14 insertions(+), 17 deletions(-)

diff --git a/javascript/dragdrop.js b/javascript/dragdrop.js
index cf900f50..fe0185a5 100644
--- a/javascript/dragdrop.js
+++ b/javascript/dragdrop.js
@@ -43,7 +43,7 @@ function dropReplaceImage( imgWrap, files ) {
 window.document.addEventListener('dragover', e => {
     const target = e.composedPath()[0];
     const imgWrap = target.closest('[data-testid="image"]');
-    if ( !imgWrap ) {
+    if ( !imgWrap && target.placeholder != "Prompt") {
         return;
     }
     e.stopPropagation();
diff --git a/javascript/imageParams.js b/javascript/imageParams.js
index f9d0c0aa..4a7b0900 100644
--- a/javascript/imageParams.js
+++ b/javascript/imageParams.js
@@ -2,21 +2,18 @@ window.onload = (function(){
     window.addEventListener('drop', e => {
         const target = e.composedPath()[0];
         const idx = selected_gallery_index();
-        let prompt_target = "txt2img_prompt_image";
-        if (idx === 1) {
-            prompt_target = "img2img_prompt_image";
-        }
-        if (target.placeholder === "Prompt") {
-            e.stopPropagation();
-            e.preventDefault();
-            const imgParent = gradioApp().getElementById(prompt_target);
-            const files = e.dataTransfer.files;
-            const fileInput = imgParent.querySelector('input[type="file"]');
-            if ( fileInput ) {
-                fileInput.files = files;
-                fileInput.dispatchEvent(new Event('change'));
-            }
+        if (target.placeholder != "Prompt") return;
+
+        let prompt_target = get_tab_index('tabs') == 1 ? "img2img_prompt_image" : "txt2img_prompt_image";
+
+        e.stopPropagation();
+        e.preventDefault();
+        const imgParent = gradioApp().getElementById(prompt_target);
+        const files = e.dataTransfer.files;
+        const fileInput = imgParent.querySelector('input[type="file"]');
+        if ( fileInput ) {
+            fileInput.files = files;
+            fileInput.dispatchEvent(new Event('change'));
         }
     });
-
-});
\ No newline at end of file
+});
-- 
cgit v1.2.3


From 0aec19d7837d8564355fdb286541db7165852e41 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 14 Oct 2022 18:15:03 +0300
Subject: make pasting into img2img prompt work make image params request not
 use temp files

---
 modules/images.py | 36 ++++++++++++++++++------------------
 modules/ui.py     |  9 +++------
 2 files changed, 21 insertions(+), 24 deletions(-)

diff --git a/modules/images.py b/modules/images.py
index f1155b7f..68cdbc93 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -1,4 +1,5 @@
 import datetime
+import io
 import math
 import os
 from collections import namedtuple
@@ -465,21 +466,20 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i
     return fullfn, txt_fullfn
 
 
-def image_data(image_path):
-    file, ext = os.path.splitext(image_path.name)
-    data = {}
-    if "png" in ext:
-        image = Image.open(image_path.name, "r")
-        print(f"Image data requested for {image_path.name} {image.format} of {type(image)}")
-        try:
-            data = image.text["parameters"]
-        except Exception as e:
-            print(f"Exception: {e}")
-            pass
-        print(f"Image data: {data}")
-    if "txt" in ext:
-        myfile = open(image_path.name, 'r')
-        data = myfile.read()
-        myfile.close()
-
-    return data, None
+def image_data(data):
+    try:
+        image = Image.open(io.BytesIO(data))
+        textinfo = image.text["parameters"]
+        return textinfo, None
+    except Exception:
+        pass
+
+    try:
+        text = data.decode('utf8')
+        assert len(text) < 10000
+        return text, None
+
+    except Exception:
+        pass
+
+    return '', None
diff --git a/modules/ui.py b/modules/ui.py
index 0a3ee887..6266db49 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -514,7 +514,7 @@ def create_ui(wrap_gradio_gpu_call):
     with gr.Blocks(analytics_enabled=False) as txt2img_interface:
         txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=False)
         dummy_component = gr.Label(visible=False)
-        txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="file", visible=False)
+        txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False)
 
         with gr.Row(elem_id='txt2img_progress_row'):
             with gr.Column(scale=1):
@@ -620,7 +620,6 @@ def create_ui(wrap_gradio_gpu_call):
 
             txt_prompt_img.change(
                 fn=modules.images.image_data,
-                # _js = "get_extras_tab_index",
                 inputs=[
                     txt_prompt_img
                 ],
@@ -692,8 +691,7 @@ def create_ui(wrap_gradio_gpu_call):
         img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=True)
 
         with gr.Row(elem_id='img2img_progress_row'):
-            img2img_prompt_img = gr.File(label="", elem_id="txt_prompt_image", file_count="single", type="file",
-                                         visible=False)
+            img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False)
 
             with gr.Column(scale=1):
                 pass
@@ -791,9 +789,8 @@ def create_ui(wrap_gradio_gpu_call):
 
             img2img_prompt_img.change(
                 fn=modules.images.image_data,
-                # _js = "get_extras_tab_index",
                 inputs=[
-                    txt_prompt_img
+                    img2img_prompt_img
                 ],
                 outputs=[
                     img2img_prompt,
-- 
cgit v1.2.3


From 67f447ddcc8a17d11939c3801dca635dc22944c7 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 14 Oct 2022 19:30:28 +0300
Subject: possibility to load checkpoint, clip skip, and hypernet from infotext

---
 modules/ui.py | 52 +++++++++++++++++++++++++++++++++++++++++++++-------
 1 file changed, 45 insertions(+), 7 deletions(-)

diff --git a/modules/ui.py b/modules/ui.py
index 6266db49..a37a4e17 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -22,7 +22,7 @@ import gradio as gr
 import gradio.utils
 import gradio.routes
 
-from modules import sd_hijack
+from modules import sd_hijack, sd_models
 from modules.paths import script_path
 from modules.shared import opts, cmd_opts
 if cmd_opts.deepdanbooru:
@@ -507,12 +507,38 @@ def setup_progressbar(progressbar, preview, id_part, textinfo=None):
     )
 
 
+def apply_setting(key, value):
+    if value is None:
+        return gr.update()
+
+    if key == "sd_model_checkpoint":
+        ckpt_info = sd_models.get_closet_checkpoint_match(value)
+
+        if ckpt_info is not None:
+            value = ckpt_info.title
+        else:
+            return gr.update()
+
+    comp_args = opts.data_labels[key].component_args
+    if comp_args and isinstance(comp_args, dict) and comp_args.get('visible') is False:
+        return
+
+    valtype = type(opts.data_labels[key].default)
+    oldval = opts.data[key]
+    opts.data[key] = valtype(value) if valtype != type(None) else value
+    if oldval != value and opts.data_labels[key].onchange is not None:
+        opts.data_labels[key].onchange()
+
+    opts.save(shared.config_filename)
+    return value
+
+
 def create_ui(wrap_gradio_gpu_call):
     import modules.img2img
     import modules.txt2img
 
     with gr.Blocks(analytics_enabled=False) as txt2img_interface:
-        txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=False)
+        txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False)
         dummy_component = gr.Label(visible=False)
         txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False)
 
@@ -684,11 +710,10 @@ def create_ui(wrap_gradio_gpu_call):
                 (firstphase_width, "First pass size-1"),
                 (firstphase_height, "First pass size-2"),
             ]
-            modules.generation_parameters_copypaste.connect_paste(paste, txt2img_paste_fields, txt2img_prompt)
             token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter])
 
     with gr.Blocks(analytics_enabled=False) as img2img_interface:
-        img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, paste, token_counter, token_button = create_toprow(is_img2img=True)
+        img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste, token_counter, token_button = create_toprow(is_img2img=True)
 
         with gr.Row(elem_id='img2img_progress_row'):
             img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False)
@@ -938,7 +963,6 @@ def create_ui(wrap_gradio_gpu_call):
                 (seed_resize_from_h, "Seed resize from-2"),
                 (denoising_strength, "Denoising strength"),
             ]
-            modules.generation_parameters_copypaste.connect_paste(paste, img2img_paste_fields, img2img_prompt)
             token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter])
 
     with gr.Blocks(analytics_enabled=False) as extras_interface:
@@ -1580,8 +1604,22 @@ Requested path was: {f}
             outputs=[extras_image],
         )
 
-        modules.generation_parameters_copypaste.connect_paste(pnginfo_send_to_txt2img, txt2img_paste_fields, generation_info, 'switch_to_txt2img')
-        modules.generation_parameters_copypaste.connect_paste(pnginfo_send_to_img2img, img2img_paste_fields, generation_info, 'switch_to_img2img_img2img')
+        settings_map = {
+            'sd_hypernetwork': 'Hypernet',
+            'CLIP_stop_at_last_layers': 'Clip skip',
+            'sd_model_checkpoint': 'Model hash',
+        }
+
+        settings_paste_fields = [
+            (component_dict[k], lambda d, k=k, v=v: apply_setting(k, d.get(v, None)))
+            for k, v in settings_map.items()
+        ]
+
+        modules.generation_parameters_copypaste.connect_paste(txt2img_paste, txt2img_paste_fields + settings_paste_fields, txt2img_prompt)
+        modules.generation_parameters_copypaste.connect_paste(img2img_paste, img2img_paste_fields + settings_paste_fields, img2img_prompt)
+
+        modules.generation_parameters_copypaste.connect_paste(pnginfo_send_to_txt2img, txt2img_paste_fields + settings_paste_fields, generation_info, 'switch_to_txt2img')
+        modules.generation_parameters_copypaste.connect_paste(pnginfo_send_to_img2img, img2img_paste_fields + settings_paste_fields, generation_info, 'switch_to_img2img_img2img')
 
     ui_config_file = cmd_opts.ui_config_file
     ui_settings = {}
-- 
cgit v1.2.3


From 6c6427946087d761d548d97164594d914fdd9b78 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 14 Oct 2022 19:33:49 +0300
Subject: remove user's liners from .gitigbore - those go into
 .git/info/exclude

---
 .gitignore | 2 --
 1 file changed, 2 deletions(-)

diff --git a/.gitignore b/.gitignore
index a6f27495..69785b3e 100644
--- a/.gitignore
+++ b/.gitignore
@@ -27,5 +27,3 @@ __pycache__
 notification.mp3
 /SwinIR
 /textual_inversion
-/images_history_testui.py
-/repositorieslatent-diffusion
-- 
cgit v1.2.3


From 2fb9891af3bb4c36a6de6b44937e927bda43c10d Mon Sep 17 00:00:00 2001
From: Gugubo <29143981+Gugubo@users.noreply.github.com>
Date: Fri, 14 Oct 2022 14:19:39 +0200
Subject: Change grid row count autodetect to prevent empty spots

Instead of just rounding (sometimes resulting in grids with "empty" spots), find a divisor.
For example: 8 images will now result in a 4x2 grid instead of a 3x3 with one empty spot.
---
 modules/images.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/modules/images.py b/modules/images.py
index 68cdbc93..90eca37a 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -25,8 +25,9 @@ def image_grid(imgs, batch_size=1, rows=None):
         elif opts.n_rows == 0:
             rows = batch_size
         else:
-            rows = math.sqrt(len(imgs))
-            rows = round(rows)
+            rows = math.floor(math.sqrt(len(imgs)))
+            while len(imgs) % rows != 0:
+                rows -= 1
 
     cols = math.ceil(len(imgs) / rows)
 
-- 
cgit v1.2.3


From 43f926aad1b77a4bb642c1d173adfae1f56cf42d Mon Sep 17 00:00:00 2001
From: Gugubo <29143981+Gugubo@users.noreply.github.com>
Date: Fri, 14 Oct 2022 17:06:51 +0200
Subject: Add option to prevent empty spots in grid (1/2)

---
 modules/shared.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/modules/shared.py b/modules/shared.py
index b6a5c1a8..159f504f 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -175,6 +175,7 @@ options_templates.update(options_section(('saving-images', "Saving images/grids"
     "grid_format": OptionInfo('png', 'File format for grids'),
     "grid_extended_filename": OptionInfo(False, "Add extended info (seed, prompt) to filename when saving grid"),
     "grid_only_if_multiple": OptionInfo(True, "Do not save grids consisting of one picture"),
+    "grid_prevent_empty_spots": OptionInfo(False, "Prevent empty spots in grid (when set to autodetect)"),
     "n_rows": OptionInfo(-1, "Grid row count; use -1 for autodetect and 0 for it to be same as batch size", gr.Slider, {"minimum": -1, "maximum": 16, "step": 1}),
 
     "enable_pnginfo": OptionInfo(True, "Save text information about generation parameters as chunks to png files"),
-- 
cgit v1.2.3


From 5f87dd1ee0960963e3f756c4ebe47652ff57f715 Mon Sep 17 00:00:00 2001
From: Gugubo <29143981+Gugubo@users.noreply.github.com>
Date: Fri, 14 Oct 2022 17:07:24 +0200
Subject: Add option to prevent empty spots in grid (2/2)

---
 modules/images.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/modules/images.py b/modules/images.py
index 90eca37a..b9589563 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -24,10 +24,13 @@ def image_grid(imgs, batch_size=1, rows=None):
             rows = opts.n_rows
         elif opts.n_rows == 0:
             rows = batch_size
-        else:
+        elif opts.grid_prevent_empty_spots:
             rows = math.floor(math.sqrt(len(imgs)))
             while len(imgs) % rows != 0:
                 rows -= 1
+        else:
+            rows = math.sqrt(len(imgs))
+            rows = round(rows)
 
     cols = math.ceil(len(imgs) / rows)
 
-- 
cgit v1.2.3


From a8eeb2b7ad0c43ad60ac2ba8bd299b9cb265fdd3 Mon Sep 17 00:00:00 2001
From: Ljzd-PRO <63289359+Ljzd-PRO@users.noreply.github.com>
Date: Thu, 13 Oct 2022 02:03:08 +0800
Subject: add `--lowram` parameter

load models to VRM instead of RAM (for machines which have bigger VRM than RAM such as free Google Colab server)
---
 modules/shared.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/modules/shared.py b/modules/shared.py
index 159f504f..cd4a4714 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -34,6 +34,7 @@ parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_
 parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui")
 parser.add_argument("--medvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a little speed for low VRM usage")
 parser.add_argument("--lowvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a lot of speed for very low VRM usage")
+parser.add_argument("--lowram", action='store_true', help="load models to VRM instead of RAM (for machines which have bigger VRM than RAM such as free Google Colab server)")
 parser.add_argument("--always-batch-cond-uncond", action='store_true', help="disables cond/uncond batching that is enabled to save memory with --medvram or --lowvram")
 parser.add_argument("--unload-gfpgan", action='store_true', help="does not do anything.")
 parser.add_argument("--precision", type=str, help="evaluate at this precision", choices=["full", "autocast"], default="autocast")
-- 
cgit v1.2.3


From 4a216ded433ded315106e2989c5ff7dec1c49304 Mon Sep 17 00:00:00 2001
From: Ljzd-PRO <63289359+Ljzd-PRO@users.noreply.github.com>
Date: Thu, 13 Oct 2022 02:07:49 +0800
Subject: load models to VRAM when using `--lowram` param

load models to VRM instead of RAM (for machines which have bigger VRM than RAM such as free Google Colab server)
---
 modules/sd_models.py | 15 +++++++++++++--
 1 file changed, 13 insertions(+), 2 deletions(-)

diff --git a/modules/sd_models.py b/modules/sd_models.py
index 0a55b4c3..78a198b9 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -134,7 +134,12 @@ def load_model_weights(model, checkpoint_info):
 
     print(f"Loading weights [{sd_model_hash}] from {checkpoint_file}")
 
-    pl_sd = torch.load(checkpoint_file, map_location="cpu")
+    if shared.cmd_opts.lowram:
+        print("Load to VRAM if GPU is available (low RAM)")
+        pl_sd = torch.load(checkpoint_file)
+    else:
+        pl_sd = torch.load(checkpoint_file, map_location="cpu")
+
     if "global_step" in pl_sd:
         print(f"Global Step: {pl_sd['global_step']}")
 
@@ -158,7 +163,13 @@ def load_model_weights(model, checkpoint_info):
 
     if os.path.exists(vae_file):
         print(f"Loading VAE weights from: {vae_file}")
-        vae_ckpt = torch.load(vae_file, map_location="cpu")
+
+        if shared.cmd_opts.lowram:
+            print("Load to VRAM if GPU is available (low RAM)")
+            vae_ckpt = torch.load(vae_file)
+        else:
+            vae_ckpt = torch.load(vae_file, map_location="cpu")
+
         vae_dict = {k: v for k, v in vae_ckpt["state_dict"].items() if k[0:4] != "loss"}
 
         model.first_stage_model.load_state_dict(vae_dict)
-- 
cgit v1.2.3


From bb295f54785ac36dc6aa6f7103a3431464440fc3 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 14 Oct 2022 20:03:41 +0300
Subject: rework the code for lowram a bit

---
 modules/sd_models.py | 12 ++----------
 modules/shared.py    |  3 ++-
 2 files changed, 4 insertions(+), 11 deletions(-)

diff --git a/modules/sd_models.py b/modules/sd_models.py
index 78a198b9..3a01c93d 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -134,11 +134,7 @@ def load_model_weights(model, checkpoint_info):
 
     print(f"Loading weights [{sd_model_hash}] from {checkpoint_file}")
 
-    if shared.cmd_opts.lowram:
-        print("Load to VRAM if GPU is available (low RAM)")
-        pl_sd = torch.load(checkpoint_file)
-    else:
-        pl_sd = torch.load(checkpoint_file, map_location="cpu")
+    pl_sd = torch.load(checkpoint_file, map_location=shared.weight_load_location)
 
     if "global_step" in pl_sd:
         print(f"Global Step: {pl_sd['global_step']}")
@@ -164,11 +160,7 @@ def load_model_weights(model, checkpoint_info):
     if os.path.exists(vae_file):
         print(f"Loading VAE weights from: {vae_file}")
 
-        if shared.cmd_opts.lowram:
-            print("Load to VRAM if GPU is available (low RAM)")
-            vae_ckpt = torch.load(vae_file)
-        else:
-            vae_ckpt = torch.load(vae_file, map_location="cpu")
+        vae_ckpt = torch.load(vae_file, map_location=shared.weight_load_location)
 
         vae_dict = {k: v for k, v in vae_ckpt["state_dict"].items() if k[0:4] != "loss"}
 
diff --git a/modules/shared.py b/modules/shared.py
index cd4a4714..695d29b6 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -34,7 +34,7 @@ parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_
 parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui")
 parser.add_argument("--medvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a little speed for low VRM usage")
 parser.add_argument("--lowvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a lot of speed for very low VRM usage")
-parser.add_argument("--lowram", action='store_true', help="load models to VRM instead of RAM (for machines which have bigger VRM than RAM such as free Google Colab server)")
+parser.add_argument("--lowram", action='store_true', help="load stable diffusion checkpoint weights to VRAM instead of RAM")
 parser.add_argument("--always-batch-cond-uncond", action='store_true', help="disables cond/uncond batching that is enabled to save memory with --medvram or --lowvram")
 parser.add_argument("--unload-gfpgan", action='store_true', help="does not do anything.")
 parser.add_argument("--precision", type=str, help="evaluate at this precision", choices=["full", "autocast"], default="autocast")
@@ -81,6 +81,7 @@ devices.device, devices.device_interrogate, devices.device_gfpgan, devices.devic
 (devices.cpu if any(y in cmd_opts.use_cpu for y in [x, 'all']) else devices.get_optimal_device() for x in ['sd', 'interrogate', 'gfpgan', 'bsrgan', 'esrgan', 'scunet', 'codeformer'])
 
 device = devices.device
+weight_load_location = None if cmd_opts.lowram else "cpu"
 
 batch_cond_uncond = cmd_opts.always_batch_cond_uncond or not (cmd_opts.lowvram or cmd_opts.medvram)
 parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram
-- 
cgit v1.2.3


From c344ba3b325459abbf9b0df2c1b18f7bf99805b2 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 14 Oct 2022 20:31:49 +0300
Subject: add option to read generation params for learning previews from
 txt2img

---
 modules/hypernetworks/hypernetwork.py          | 21 ++++++++++++++++-----
 modules/textual_inversion/textual_inversion.py | 25 ++++++++++++++++++-------
 modules/ui.py                                  | 20 +++++++++++++++++---
 3 files changed, 51 insertions(+), 15 deletions(-)

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index f1248bb7..e5cb1817 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -180,7 +180,7 @@ def attention_CrossAttention_forward(self, x, context=None, mask=None):
     return self.to_out(out)
 
 
-def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_image_prompt):
+def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
     assert hypernetwork_name, 'hypernetwork not selected'
 
     path = shared.hypernetworks.get(hypernetwork_name, None)
@@ -265,20 +265,31 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
         if hypernetwork.step > 0 and images_dir is not None and hypernetwork.step % create_image_every == 0:
             last_saved_image = os.path.join(images_dir, f'{hypernetwork_name}-{hypernetwork.step}.png')
 
-            preview_text = entry.cond_text if preview_image_prompt == "" else preview_image_prompt
-
             optimizer.zero_grad()
             shared.sd_model.cond_stage_model.to(devices.device)
             shared.sd_model.first_stage_model.to(devices.device)
 
             p = processing.StableDiffusionProcessingTxt2Img(
                 sd_model=shared.sd_model,
-                prompt=preview_text,
-                steps=20,
                 do_not_save_grid=True,
                 do_not_save_samples=True,
             )
 
+            if preview_from_txt2img:
+                p.prompt = preview_prompt
+                p.negative_prompt = preview_negative_prompt
+                p.steps = preview_steps
+                p.sampler_index = preview_sampler_index
+                p.cfg_scale = preview_cfg_scale
+                p.seed = preview_seed
+                p.width = preview_width
+                p.height = preview_height
+            else:
+                p.prompt = entry.cond_text
+                p.steps = 20
+
+            preview_text = p.prompt
+
             processed = processing.process_images(p)
             image = processed.images[0] if len(processed.images)>0 else None
 
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index fa0e33a2..3d835358 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -172,7 +172,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'):
     return fn
 
 
-def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_image_prompt):
+def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
     assert embedding_name, 'embedding not selected'
 
     shared.state.textinfo = "Initializing textual inversion training..."
@@ -259,18 +259,29 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
         if embedding.step > 0 and images_dir is not None and embedding.step % create_image_every == 0:
             last_saved_image = os.path.join(images_dir, f'{embedding_name}-{embedding.step}.png')
 
-            preview_text = entry.cond_text if preview_image_prompt == "" else preview_image_prompt
-
             p = processing.StableDiffusionProcessingTxt2Img(
                 sd_model=shared.sd_model,
-                prompt=preview_text,
-                steps=20,
-                height=training_height,
-                width=training_width,
                 do_not_save_grid=True,
                 do_not_save_samples=True,
             )
 
+            if preview_from_txt2img:
+                p.prompt = preview_prompt
+                p.negative_prompt = preview_negative_prompt
+                p.steps = preview_steps
+                p.sampler_index = preview_sampler_index
+                p.cfg_scale = preview_cfg_scale
+                p.seed = preview_seed
+                p.width = preview_width
+                p.height = preview_height
+            else:
+                p.prompt = entry.cond_text
+                p.steps = 20
+                p.width = training_width
+                p.height = training_height
+
+            preview_text = p.prompt
+
             processed = processing.process_images(p)
             image = processed.images[0]
 
diff --git a/modules/ui.py b/modules/ui.py
index 828bfeea..4a04c2cc 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -711,6 +711,18 @@ def create_ui(wrap_gradio_gpu_call):
                 (firstphase_width, "First pass size-1"),
                 (firstphase_height, "First pass size-2"),
             ]
+
+            txt2img_preview_params = [
+                txt2img_prompt,
+                txt2img_negative_prompt,
+                steps,
+                sampler_index,
+                cfg_scale,
+                seed,
+                width,
+                height,
+            ]
+
             token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter])
 
     with gr.Blocks(analytics_enabled=False) as img2img_interface:
@@ -1162,7 +1174,7 @@ def create_ui(wrap_gradio_gpu_call):
                     create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0)
                     save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0)
                     save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True)
-                    preview_image_prompt = gr.Textbox(label='Preview prompt', value="")
+                    preview_from_txt2img = gr.Checkbox(label='Read parameters (prompt, etc...) from txt2img tab when making previews', value=False)
 
                     with gr.Row():
                         interrupt_training = gr.Button(value="Interrupt")
@@ -1240,7 +1252,8 @@ def create_ui(wrap_gradio_gpu_call):
                 save_embedding_every,
                 template_file,
                 save_image_with_stored_embedding,
-                preview_image_prompt,
+                preview_from_txt2img,
+                *txt2img_preview_params,
             ],
             outputs=[
                 ti_output,
@@ -1260,7 +1273,8 @@ def create_ui(wrap_gradio_gpu_call):
                 create_image_every,
                 save_embedding_every,
                 template_file,
-                preview_image_prompt,
+                preview_from_txt2img,
+                *txt2img_preview_params,
             ],
             outputs=[
                 ti_output,
-- 
cgit v1.2.3


From 6cdf55627cb4eb156fb7d8c010d396f93011c04e Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 14 Oct 2022 21:12:52 +0300
Subject: restore borders for prompts

---
 style.css | 8 --------
 1 file changed, 8 deletions(-)

diff --git a/style.css b/style.css
index aa3d379c..2306c002 100644
--- a/style.css
+++ b/style.css
@@ -167,14 +167,6 @@ button{
     align-self: stretch !important;
 }
 
-#prompt, #negative_prompt{
-    border: none !important;
-}
-#prompt textarea, #negative_prompt textarea{
-    border: none !important;
-}
-
-
 #img2maskimg .h-60{
     height: 30rem;
 }
-- 
cgit v1.2.3


From 2f0e089c7c8e1ad7d2ad658971c6fdec9622e3ab Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 14 Oct 2022 21:20:28 +0300
Subject: should fix the issue with missing layers in chechpoint merger

---
 modules/extras.py | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/modules/extras.py b/modules/extras.py
index 532d869f..2e7b3751 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -209,7 +209,12 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
 
     for key in tqdm.tqdm(theta_0.keys()):
         if 'model' in key and key in theta_1:
-            theta_0[key] = theta_func(theta_0[key], theta_1[key], theta_2[key] if theta_2 else None, (float(1.0) - interp_amount))  # Need to reverse the interp_amount to match the desired mix ration in the merged checkpoint
+            t2 = (theta_2 or {}).get(key)
+            if t2 is None:
+                t2 = torch.zeros_like(theta_0[key])
+
+            theta_0[key] = theta_func(theta_0[key], theta_1[key], t2, (float(1.0) - interp_amount))  # Need to reverse the interp_amount to match the desired mix ration in the merged checkpoint
+
             if save_as_half:
                 theta_0[key] = theta_0[key].half()
 
-- 
cgit v1.2.3


From 9b75ab144f5fa3669166374dacd5ffc340984078 Mon Sep 17 00:00:00 2001
From: ChucklesTheBeard <ChucklesTheBeard@users.noreply.github.com>
Date: Thu, 13 Oct 2022 16:45:02 -0400
Subject: fix typo

---
 launch.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/launch.py b/launch.py
index 16627a03..a7c5807b 100644
--- a/launch.py
+++ b/launch.py
@@ -76,7 +76,7 @@ def git_clone(url, dir, name, commithash=None):
             return
 
         run(f'"{git}" -C {dir} fetch', f"Fetching updates for {name}...", f"Couldn't fetch {name}")
-        run(f'"{git}" -C {dir} checkout {commithash}', f"Checking out commint for {name} with hash: {commithash}...", f"Couldn't checkout commit {commithash} for {name}")
+        run(f'"{git}" -C {dir} checkout {commithash}', f"Checking out commit for {name} with hash: {commithash}...", f"Couldn't checkout commit {commithash} for {name}")
         return
 
     run(f'"{git}" clone "{url}" "{dir}"', f"Cloning {name} into {dir}...", f"Couldn't clone {name}")
-- 
cgit v1.2.3


From 02382f7ce462a360e8aea9ee3178da48b564f70a Mon Sep 17 00:00:00 2001
From: RnDMonkey <ryandrutledge@gmail.com>
Date: Wed, 12 Oct 2022 16:35:36 -0700
Subject: regression in xy_grid Var. seed fixing

---
 scripts/xy_grid.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index efb63af5..5700b007 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -338,7 +338,7 @@ class Script(scripts.Script):
         ys = process_axis(y_opt, y_values)
 
         def fix_axis_seeds(axis_opt, axis_list):
-            if axis_opt.label == 'Seed':
+            if axis_opt.label in ['Seed','Var. seed']:
                 return [int(random.randrange(4294967294)) if val is None or val == '' or val == -1 else val for val in axis_list]
             else:
                 return axis_list
-- 
cgit v1.2.3


From c250cb289c97fe303cef69064bf45899406f6a40 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 14 Oct 2022 22:01:49 +0300
Subject: change checkpoint merger to work in a more obvious way remove sigmoid
 and inverse sigmoid because they just did the same thing as weighed sum only
 with changed multiplier

---
 javascript/hints.js |  4 ++--
 modules/extras.py   | 24 +++++-------------------
 modules/ui.py       |  4 ++--
 3 files changed, 9 insertions(+), 23 deletions(-)

diff --git a/javascript/hints.js b/javascript/hints.js
index af010a59..8fec907d 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -87,8 +87,8 @@ titles = {
 
     "Quicksettings list": "List of setting names, separated by commas, for settings that should go to the quick access bar at the top, rather than the usual setting tab. See modules/shared.py for setting names. Requires restarting to apply.",
 
-    "Weighted Sum": "Result = A * (1 - M) + B * M",
-    "Add difference": "Result = A + (B - C) * (1 - M)",
+    "Weighted sum": "Result = A * (1 - M) + B * M",
+    "Add difference": "Result = A + (B - C) * M",
 }
 
 
diff --git a/modules/extras.py b/modules/extras.py
index 2e7b3751..f2f5a7b0 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -159,24 +159,12 @@ def run_pnginfo(image):
     return '', geninfo, info
 
 
-def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_name, interp_method, interp_amount, save_as_half, custom_name):
-    # Linear interpolation (https://en.wikipedia.org/wiki/Linear_interpolation)
+def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_name, interp_method, multiplier, save_as_half, custom_name):
     def weighted_sum(theta0, theta1, theta2, alpha):
         return ((1 - alpha) * theta0) + (alpha * theta1)
 
-    # Smoothstep (https://en.wikipedia.org/wiki/Smoothstep)
-    def sigmoid(theta0, theta1, theta2, alpha):
-        alpha = alpha * alpha * (3 - (2 * alpha))
-        return theta0 + ((theta1 - theta0) * alpha)
-
-    # Inverse Smoothstep (https://en.wikipedia.org/wiki/Smoothstep)
-    def inv_sigmoid(theta0, theta1, theta2, alpha):
-        import math
-        alpha = 0.5 - math.sin(math.asin(1.0 - 2.0 * alpha) / 3.0)
-        return theta0 + ((theta1 - theta0) * alpha)
-
     def add_difference(theta0, theta1, theta2, alpha):
-        return theta0 + (theta1 - theta2) * (1.0 - alpha)
+        return theta0 + (theta1 - theta2) * alpha
 
     primary_model_info = sd_models.checkpoints_list[primary_model_name]
     secondary_model_info = sd_models.checkpoints_list[secondary_model_name]
@@ -198,9 +186,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
         theta_2 = None
 
     theta_funcs = {
-        "Weighted Sum": weighted_sum,
-        "Sigmoid": sigmoid,
-        "Inverse Sigmoid": inv_sigmoid,
+        "Weighted sum": weighted_sum,
         "Add difference": add_difference,
     }
     theta_func = theta_funcs[interp_method]
@@ -213,7 +199,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
             if t2 is None:
                 t2 = torch.zeros_like(theta_0[key])
 
-            theta_0[key] = theta_func(theta_0[key], theta_1[key], t2, (float(1.0) - interp_amount))  # Need to reverse the interp_amount to match the desired mix ration in the merged checkpoint
+            theta_0[key] = theta_func(theta_0[key], theta_1[key], t2, multiplier)
 
             if save_as_half:
                 theta_0[key] = theta_0[key].half()
@@ -227,7 +213,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
 
     ckpt_dir = shared.cmd_opts.ckpt_dir or sd_models.model_path
 
-    filename = primary_model_info.model_name + '_' + str(round(interp_amount, 2)) + '-' + secondary_model_info.model_name + '_' + str(round((float(1.0) - interp_amount), 2)) + '-' + interp_method.replace(" ", "_") + '-merged.ckpt'
+    filename = primary_model_info.model_name + '_' + str(round(1-multiplier, 2)) + '-' + secondary_model_info.model_name + '_' + str(round(multiplier, 2)) + '-' + interp_method.replace(" ", "_") + '-merged.ckpt'
     filename = filename if custom_name == '' else (custom_name + '.ckpt')
     output_modelname = os.path.join(ckpt_dir, filename)
 
diff --git a/modules/ui.py b/modules/ui.py
index 4a04c2cc..a08ffc9b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1101,8 +1101,8 @@ def create_ui(wrap_gradio_gpu_call):
                     secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary model (B)")
                     tertiary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_tertiary_model_name", label="Tertiary model (C)")
                 custom_name = gr.Textbox(label="Custom Name (Optional)")
-                interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Interpolation amount (1 - M)', value=0.3)
-                interp_method = gr.Radio(choices=["Weighted Sum", "Sigmoid", "Inverse Sigmoid", "Add difference"], value="Weighted Sum", label="Interpolation Method")
+                interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3)
+                interp_method = gr.Radio(choices=["Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method")
                 save_as_half = gr.Checkbox(value=False, label="Save as float16")
                 modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary')
 
-- 
cgit v1.2.3


From 4cc37e4cdf2ce5f5b753786b55ae1d4abd530c01 Mon Sep 17 00:00:00 2001
From: Naeaeaeaeae <niels.reisch@gmx.de>
Date: Thu, 13 Oct 2022 18:49:58 +0200
Subject: [xy_grid.py] add option denoising_strength

---
 scripts/xy_grid.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 5700b007..fda2b71d 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -176,6 +176,7 @@ axis_options = [
     AxisOption("Sigma noise", float, apply_field("s_noise"), format_value_add_label, None),
     AxisOption("Eta", float, apply_field("eta"), format_value_add_label, None),
     AxisOption("Clip skip", int, apply_clip_skip, format_value_add_label, None),
+    AxisOption("Denoising", float, apply_field("denoising_strength"), format_value_add_label, None),
     AxisOptionImg2Img("Denoising", float, apply_field("denoising_strength"), format_value_add_label, None),  # as it is now all AxisOptionImg2Img items must go after AxisOption ones
 ]
 
-- 
cgit v1.2.3


From 989a552de3d1fcd1f178fe873713b884e192dd61 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 14 Oct 2022 22:04:08 +0300
Subject: remove the other Denoising

---
 scripts/xy_grid.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index fda2b71d..8c7da6bb 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -177,7 +177,6 @@ axis_options = [
     AxisOption("Eta", float, apply_field("eta"), format_value_add_label, None),
     AxisOption("Clip skip", int, apply_clip_skip, format_value_add_label, None),
     AxisOption("Denoising", float, apply_field("denoising_strength"), format_value_add_label, None),
-    AxisOptionImg2Img("Denoising", float, apply_field("denoising_strength"), format_value_add_label, None),  # as it is now all AxisOptionImg2Img items must go after AxisOption ones
 ]
 
 
-- 
cgit v1.2.3


From 03d62538aebeff51713619fe808c953bdb70193d Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 14 Oct 2022 22:43:55 +0300
Subject: remove duplicate code for log loss, add step, make it read from
 options rather than gradio input

---
 modules/hypernetworks/hypernetwork.py          | 20 ++++--------
 modules/shared.py                              |  3 +-
 modules/textual_inversion/textual_inversion.py | 44 ++++++++++++++++++--------
 modules/ui.py                                  |  3 --
 4 files changed, 38 insertions(+), 32 deletions(-)

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index edb8cba1..59c7ac6e 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -15,6 +15,7 @@ import torch
 from torch import einsum
 from einops import rearrange, repeat
 import modules.textual_inversion.dataset
+from modules.textual_inversion import textual_inversion
 from modules.textual_inversion.learn_schedule import LearnRateScheduler
 
 
@@ -210,7 +211,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
 
     shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
     with torch.autocast("cuda"):
-        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=512, height=512, repeats=1, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file, include_cond=True)
+        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=512, height=512, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file, include_cond=True)
 
     if unload:
         shared.sd_model.cond_stage_model.to(devices.cpu)
@@ -263,19 +264,10 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
             last_saved_file = os.path.join(hypernetwork_dir, f'{hypernetwork_name}-{hypernetwork.step}.pt')
             hypernetwork.save(last_saved_file)
 
-        if write_csv_every > 0 and hypernetwork_dir is not None and hypernetwork.step % write_csv_every == 0:
-            write_csv_header = False if os.path.exists(os.path.join(hypernetwork_dir, "hypernetwork_loss.csv")) else True
-            
-            with open(os.path.join(hypernetwork_dir, "hypernetwork_loss.csv"), "a+") as fout:
-
-                csv_writer = csv.DictWriter(fout, fieldnames=["step", "loss", "learn_rate"])
-                
-                if write_csv_header:
-                    csv_writer.writeheader()
-
-                csv_writer.writerow({"step": hypernetwork.step, 
-                    "loss": f"{losses.mean():.7f}",
-                    "learn_rate": scheduler.learn_rate})
+        textual_inversion.write_loss(log_directory, "hypernetwork_loss.csv", hypernetwork.step, len(ds), {
+            "loss": f"{losses.mean():.7f}",
+            "learn_rate": scheduler.learn_rate
+        })
 
         if hypernetwork.step > 0 and images_dir is not None and hypernetwork.step % create_image_every == 0:
             last_saved_image = os.path.join(images_dir, f'{hypernetwork_name}-{hypernetwork.step}.png')
diff --git a/modules/shared.py b/modules/shared.py
index 695d29b6..d41a7ab3 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -236,7 +236,8 @@ options_templates.update(options_section(('training', "Training"), {
     "unload_models_when_training": OptionInfo(False, "Unload VAE and CLIP from VRAM when training"),
     "dataset_filename_word_regex": OptionInfo("", "Filename word regex"),
     "dataset_filename_join_string": OptionInfo(" ", "Filename join string"),
-    "training_image_repeats_per_epoch": OptionInfo(100, "Number of repeats for a single input image per epoch; used only for displaying epoch number", gr.Number, {"precision": 0}),
+    "training_image_repeats_per_epoch": OptionInfo(1, "Number of repeats for a single input image per epoch; used only for displaying epoch number", gr.Number, {"precision": 0}),
+    "training_write_csv_every": OptionInfo(500, "Save an csv containing the loss to log directory every N steps, 0 to disable"),
 }))
 
 options_templates.update(options_section(('sd', "Stable Diffusion"), {
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 1f5ace6f..da0d77a0 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -173,6 +173,32 @@ def create_embedding(name, num_vectors_per_token, init_text='*'):
     return fn
 
 
+def write_loss(log_directory, filename, step, epoch_len, values):
+    if shared.opts.training_write_csv_every == 0:
+        return
+
+    if step % shared.opts.training_write_csv_every != 0:
+        return
+
+    write_csv_header = False if os.path.exists(os.path.join(log_directory, filename)) else True
+
+    with open(os.path.join(log_directory, filename), "a+", newline='') as fout:
+        csv_writer = csv.DictWriter(fout, fieldnames=["step", "epoch", "epoch_step", *(values.keys())])
+
+        if write_csv_header:
+            csv_writer.writeheader()
+
+        epoch = step // epoch_len
+        epoch_step = step - epoch * epoch_len
+
+        csv_writer.writerow({
+            "step": step + 1,
+            "epoch": epoch + 1,
+            "epoch_step": epoch_step + 1,
+            **values,
+        })
+
+
 def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
     assert embedding_name, 'embedding not selected'
 
@@ -257,20 +283,10 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
             last_saved_file = os.path.join(embedding_dir, f'{embedding_name}-{embedding.step}.pt')
             embedding.save(last_saved_file)
 
-        if write_csv_every > 0 and log_directory is not None and embedding.step % write_csv_every == 0:
-            write_csv_header = False if os.path.exists(os.path.join(log_directory, "textual_inversion_loss.csv")) else True
-
-            with open(os.path.join(log_directory, "textual_inversion_loss.csv"), "a+") as fout:
-
-                csv_writer = csv.DictWriter(fout, fieldnames=["epoch", "epoch_step", "loss", "learn_rate"])
-                
-                if write_csv_header:
-                    csv_writer.writeheader()
-
-                csv_writer.writerow({"epoch": epoch_num + 1, 
-                    "epoch_step": epoch_step - 1, 
-                    "loss": f"{losses.mean():.7f}",
-                    "learn_rate": scheduler.learn_rate})
+        write_loss(log_directory, "textual_inversion_loss.csv", embedding.step, len(ds), {
+            "loss": f"{losses.mean():.7f}",
+            "learn_rate": scheduler.learn_rate
+        })
 
         if embedding.step > 0 and images_dir is not None and embedding.step % create_image_every == 0:
             last_saved_image = os.path.join(images_dir, f'{embedding_name}-{embedding.step}.png')
diff --git a/modules/ui.py b/modules/ui.py
index be4a43a7..a08ffc9b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1172,7 +1172,6 @@ def create_ui(wrap_gradio_gpu_call):
                     training_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
                     steps = gr.Number(label='Max steps', value=100000, precision=0)
                     create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0)
-                    write_csv_every = gr.Number(label='Save an csv containing the loss to log directory every N steps, 0 to disable', value=500, precision=0)
                     save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0)
                     save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True)
                     preview_from_txt2img = gr.Checkbox(label='Read parameters (prompt, etc...) from txt2img tab when making previews', value=False)
@@ -1251,7 +1250,6 @@ def create_ui(wrap_gradio_gpu_call):
                 steps,
                 create_image_every,
                 save_embedding_every,
-                write_csv_every,
                 template_file,
                 save_image_with_stored_embedding,
                 preview_from_txt2img,
@@ -1274,7 +1272,6 @@ def create_ui(wrap_gradio_gpu_call):
                 steps,
                 create_image_every,
                 save_embedding_every,
-                write_csv_every,
                 template_file,
                 preview_from_txt2img,
                 *txt2img_preview_params,
-- 
cgit v1.2.3


From e21f01f64504bc651da6e85216474bbd35ee010d Mon Sep 17 00:00:00 2001
From: Rae Fu <rraefu@gmail.com>
Date: Thu, 13 Oct 2022 23:00:38 -0600
Subject: add checkpoint cache option to UI for faster model switching

switching time reduced from ~1500ms to ~280ms
---
 modules/sd_models.py | 54 +++++++++++++++++++++++++++++++---------------------
 modules/shared.py    |  1 +
 2 files changed, 33 insertions(+), 22 deletions(-)

diff --git a/modules/sd_models.py b/modules/sd_models.py
index 0a55b4c3..f3660d8d 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -1,4 +1,4 @@
-import glob
+import collections
 import os.path
 import sys
 from collections import namedtuple
@@ -15,6 +15,7 @@ model_path = os.path.abspath(os.path.join(models_path, model_dir))
 
 CheckpointInfo = namedtuple("CheckpointInfo", ['filename', 'title', 'hash', 'model_name', 'config'])
 checkpoints_list = {}
+checkpoints_loaded = collections.OrderedDict()
 
 try:
     # this silences the annoying "Some weights of the model checkpoint were not used when initializing..." message at start.
@@ -132,38 +133,46 @@ def load_model_weights(model, checkpoint_info):
     checkpoint_file = checkpoint_info.filename
     sd_model_hash = checkpoint_info.hash
 
-    print(f"Loading weights [{sd_model_hash}] from {checkpoint_file}")
+    if checkpoint_info not in checkpoints_loaded:
+        print(f"Loading weights [{sd_model_hash}] from {checkpoint_file}")
 
-    pl_sd = torch.load(checkpoint_file, map_location="cpu")
-    if "global_step" in pl_sd:
-        print(f"Global Step: {pl_sd['global_step']}")
+        pl_sd = torch.load(checkpoint_file, map_location="cpu")
+        if "global_step" in pl_sd:
+            print(f"Global Step: {pl_sd['global_step']}")
 
-    sd = get_state_dict_from_checkpoint(pl_sd)
+        sd = get_state_dict_from_checkpoint(pl_sd)
+        model.load_state_dict(sd, strict=False)
 
-    model.load_state_dict(sd, strict=False)
+        if shared.cmd_opts.opt_channelslast:
+            model.to(memory_format=torch.channels_last)
 
-    if shared.cmd_opts.opt_channelslast:
-        model.to(memory_format=torch.channels_last)
+        if not shared.cmd_opts.no_half:
+            model.half()
 
-    if not shared.cmd_opts.no_half:
-        model.half()
+        devices.dtype = torch.float32 if shared.cmd_opts.no_half else torch.float16
+        devices.dtype_vae = torch.float32 if shared.cmd_opts.no_half or shared.cmd_opts.no_half_vae else torch.float16
 
-    devices.dtype = torch.float32 if shared.cmd_opts.no_half else torch.float16
-    devices.dtype_vae = torch.float32 if shared.cmd_opts.no_half or shared.cmd_opts.no_half_vae else torch.float16
+        vae_file = os.path.splitext(checkpoint_file)[0] + ".vae.pt"
 
-    vae_file = os.path.splitext(checkpoint_file)[0] + ".vae.pt"
+        if not os.path.exists(vae_file) and shared.cmd_opts.vae_path is not None:
+            vae_file = shared.cmd_opts.vae_path
 
-    if not os.path.exists(vae_file) and shared.cmd_opts.vae_path is not None:
-        vae_file = shared.cmd_opts.vae_path
+        if os.path.exists(vae_file):
+            print(f"Loading VAE weights from: {vae_file}")
+            vae_ckpt = torch.load(vae_file, map_location="cpu")
+            vae_dict = {k: v for k, v in vae_ckpt["state_dict"].items() if k[0:4] != "loss"}
 
-    if os.path.exists(vae_file):
-        print(f"Loading VAE weights from: {vae_file}")
-        vae_ckpt = torch.load(vae_file, map_location="cpu")
-        vae_dict = {k: v for k, v in vae_ckpt["state_dict"].items() if k[0:4] != "loss"}
+            model.first_stage_model.load_state_dict(vae_dict)
 
-        model.first_stage_model.load_state_dict(vae_dict)
+        model.first_stage_model.to(devices.dtype_vae)
 
-    model.first_stage_model.to(devices.dtype_vae)
+        checkpoints_loaded[checkpoint_info] = model.state_dict().copy()
+        while len(checkpoints_loaded) > shared.opts.sd_checkpoint_cache:
+            checkpoints_loaded.popitem(last=False)  # LRU
+    else:
+        print(f"Loading weights [{sd_model_hash}] from cache")
+        checkpoints_loaded.move_to_end(checkpoint_info)
+        model.load_state_dict(checkpoints_loaded[checkpoint_info])
 
     model.sd_model_hash = sd_model_hash
     model.sd_model_checkpoint = checkpoint_file
@@ -202,6 +211,7 @@ def reload_model_weights(sd_model, info=None):
         return
 
     if sd_model.sd_checkpoint_info.config != checkpoint_info.config:
+        checkpoints_loaded.clear()
         shared.sd_model = load_model()
         return shared.sd_model
 
diff --git a/modules/shared.py b/modules/shared.py
index 5901e605..b2090da1 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -238,6 +238,7 @@ options_templates.update(options_section(('training', "Training"), {
 
 options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, refresh=sd_models.list_models),
+    "sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
     "sd_hypernetwork": OptionInfo("None", "Hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks),
     "sd_hypernetwork_strength": OptionInfo(1.0, "Hypernetwork strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.001}),
     "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."),
-- 
cgit v1.2.3


From cd58e44051f658f2efb544203a92837f43786372 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 14 Oct 2022 23:17:28 +0300
Subject: disabling history - i knew it was slow as fuck but i didn't realize
 it would also show galleries on launch

---
 modules/ui.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/modules/ui.py b/modules/ui.py
index a08ffc9b..6d193955 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1089,7 +1089,8 @@ def create_ui(wrap_gradio_gpu_call):
         "t2i":txt2img_paste_fields,
         "i2i":img2img_paste_fields
     }
-    images_history = img_his.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict) 
+
+    #images_history = img_his.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict)
 
     with gr.Blocks() as modelmerger_interface:
         with gr.Row().style(equal_height=False):
@@ -1486,7 +1487,7 @@ Requested path was: {f}
         (img2img_interface, "img2img", "img2img"),
         (extras_interface, "Extras", "extras"),
         (pnginfo_interface, "PNG Info", "pnginfo"),
-        (images_history, "History", "images_history"),
+        #(images_history, "History", "images_history"),
         (modelmerger_interface, "Checkpoint Merger", "modelmerger"),
         (train_interface, "Train", "ti"),
         (settings_interface, "Settings", "settings"),
-- 
cgit v1.2.3


From 368f4cc4c73509c1968cd9defe068d8bf4ff7c4f Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 14 Oct 2022 23:19:05 +0300
Subject: set firstpass w/h to 0 by default and rever to old behavior when any
 are 0

---
 modules/processing.py | 49 ++++++++++++++++++++++++++++++-------------------
 modules/ui.py         |  4 ++--
 2 files changed, 32 insertions(+), 21 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index 100a259f..a75b9f84 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -501,17 +501,15 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
 
 class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
     sampler = None
-    firstphase_width = 0
-    firstphase_height = 0
-    firstphase_width_truncated = 0
-    firstphase_height_truncated = 0
 
-    def __init__(self, enable_hr=False, denoising_strength=0.75, firstphase_width=512, firstphase_height=512, **kwargs):
+    def __init__(self, enable_hr=False, denoising_strength=0.75, firstphase_width=0, firstphase_height=0, **kwargs):
         super().__init__(**kwargs)
         self.enable_hr = enable_hr
         self.denoising_strength = denoising_strength
         self.firstphase_width = firstphase_width
         self.firstphase_height = firstphase_height
+        self.truncate_x = 0
+        self.truncate_y = 0
 
     def init(self, all_prompts, all_seeds, all_subseeds):
         if self.enable_hr:
@@ -520,6 +518,32 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
             else:
                 state.job_count = state.job_count * 2
 
+            if self.firstphase_width == 0 or self.firstphase_height == 0:
+                desired_pixel_count = 512 * 512
+                actual_pixel_count = self.width * self.height
+                scale = math.sqrt(desired_pixel_count / actual_pixel_count)
+                self.firstphase_width = math.ceil(scale * self.width / 64) * 64
+                self.firstphase_height = math.ceil(scale * self.height / 64) * 64
+                firstphase_width_truncated = int(scale * self.width)
+                firstphase_height_truncated = int(scale * self.height)
+
+            else:
+                self.extra_generation_params["First pass size"] = f"{self.firstphase_width}x{self.firstphase_height}"
+
+                width_ratio = self.width / self.firstphase_width
+                height_ratio = self.height / self.firstphase_height
+
+                if width_ratio > height_ratio:
+                    firstphase_width_truncated = self.firstphase_width
+                    firstphase_height_truncated = self.firstphase_width * self.height / self.width
+                else:
+                    firstphase_width_truncated = self.firstphase_height * self.width / self.height
+                    firstphase_height_truncated = self.firstphase_height
+
+            self.truncate_x = int(self.firstphase_width - firstphase_width_truncated) // opt_f
+            self.truncate_y = int(self.firstphase_height - firstphase_height_truncated) // opt_f
+
+
     def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength):
         self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers, self.sampler_index, self.sd_model)
 
@@ -528,23 +552,10 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
             samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning)
             return samples
 
-        self.extra_generation_params["First pass size"] = f"{self.firstphase_width}x{self.firstphase_height}"
-
         x = create_random_tensors([opt_C, self.firstphase_height // opt_f, self.firstphase_width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self)
         samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning)
 
-        truncate_x = 0
-        truncate_y = 0
-        width_ratio = self.width/self.firstphase_width
-        height_ratio = self.height/self.firstphase_height
-
-        if width_ratio > height_ratio:
-            truncate_y = int((self.width - self.firstphase_width) / width_ratio / height_ratio / opt_f)
-
-        elif width_ratio < height_ratio:
-            truncate_x = int((self.height - self.firstphase_height) / width_ratio / height_ratio / opt_f)
-                
-        samples = samples[:, :, truncate_y//2:samples.shape[2]-truncate_y//2, truncate_x//2:samples.shape[3]-truncate_x//2]
+        samples = samples[:, :, self.truncate_y//2:samples.shape[2]-self.truncate_y//2, self.truncate_x//2:samples.shape[3]-self.truncate_x//2]
 
         decoded_samples = decode_first_stage(self.sd_model, samples)
 
diff --git a/modules/ui.py b/modules/ui.py
index 6d193955..a1d18be9 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -567,8 +567,8 @@ def create_ui(wrap_gradio_gpu_call):
                     enable_hr = gr.Checkbox(label='Highres. fix', value=False)
 
                 with gr.Row(visible=False) as hr_options:
-                    firstphase_width = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass width", value=512)
-                    firstphase_height = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass height", value=512)
+                    firstphase_width = gr.Slider(minimum=0, maximum=1024, step=64, label="First pass width", value=0)
+                    firstphase_height = gr.Slider(minimum=0, maximum=1024, step=64, label="First pass height", value=0)
                     denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7)
 
                 with gr.Row(equal_height=True):
-- 
cgit v1.2.3


From 4d19f3b7d461fe0f63e7ccff936909b0ce0c6126 Mon Sep 17 00:00:00 2001
From: Melan <alexleander91@gmail.com>
Date: Fri, 14 Oct 2022 22:45:26 +0200
Subject: Raise an assertion error if no training images have been found.

---
 modules/textual_inversion/dataset.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index 67e90afe..12e2f43b 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -81,7 +81,8 @@ class PersonalizedBase(Dataset):
                 entry.cond = cond_model([entry.cond_text]).to(devices.cpu)
 
             self.dataset.append(entry)
-
+        
+        assert len(self.dataset) > 1, "No images have been found in the dataset."
         self.length = len(self.dataset) * repeats
 
         self.initial_indexes = np.arange(self.length) % len(self.dataset)
-- 
cgit v1.2.3


From 4dc426509918e90bf4557ecfd1f84031362360c0 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 15 Oct 2022 00:21:48 +0300
Subject: rename firstpass w/h to discard old user settings

---
 modules/ui.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/modules/ui.py b/modules/ui.py
index a1d18be9..c5d295ea 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -567,8 +567,8 @@ def create_ui(wrap_gradio_gpu_call):
                     enable_hr = gr.Checkbox(label='Highres. fix', value=False)
 
                 with gr.Row(visible=False) as hr_options:
-                    firstphase_width = gr.Slider(minimum=0, maximum=1024, step=64, label="First pass width", value=0)
-                    firstphase_height = gr.Slider(minimum=0, maximum=1024, step=64, label="First pass height", value=0)
+                    firstphase_width = gr.Slider(minimum=0, maximum=1024, step=64, label="Firstpass width", value=0)
+                    firstphase_height = gr.Slider(minimum=0, maximum=1024, step=64, label="Firstpass height", value=0)
                     denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7)
 
                 with gr.Row(equal_height=True):
-- 
cgit v1.2.3


From 4bbe5d62e042e78cfe1dc83492c2398a39a2455c Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 15 Oct 2022 00:25:09 +0300
Subject: reformat lines in images_history.py

---
 modules/images_history.py | 182 +++++++++++++++++++++++++---------------------
 1 file changed, 98 insertions(+), 84 deletions(-)

diff --git a/modules/images_history.py b/modules/images_history.py
index 723f5301..f5ef44fe 100644
--- a/modules/images_history.py
+++ b/modules/images_history.py
@@ -1,5 +1,7 @@
 import os
 import shutil
+
+
 def traverse_all_files(output_dir, image_list, curr_dir=None):
     curr_path = output_dir if curr_dir is None else os.path.join(output_dir, curr_dir)
     try:
@@ -16,10 +18,10 @@ def traverse_all_files(output_dir, image_list, curr_dir=None):
         elif os.path.isfile(file_path) and file[-10:].rfind(".") > 0:
             image_list.append(file)
         else:
-            image_list = traverse_all_files(output_dir, image_list, file)            
+            image_list = traverse_all_files(output_dir, image_list, file)
     return image_list
 
-        
+
 def get_recent_images(dir_name, page_index, step, image_index, tabname):
     page_index = int(page_index)
     f_list = os.listdir(dir_name)
@@ -27,36 +29,48 @@ def get_recent_images(dir_name, page_index, step, image_index, tabname):
     image_list = traverse_all_files(dir_name, image_list)
     image_list = sorted(image_list, key=lambda file: -os.path.getctime(os.path.join(dir_name, file)))
     num = 48 if tabname != "extras" else 12
-    max_page_index = len(image_list) // num + 1    
+    max_page_index = len(image_list) // num + 1
     page_index = max_page_index if page_index == -1 else page_index + step
-    page_index = 1 if page_index < 1 else page_index    
+    page_index = 1 if page_index < 1 else page_index
     page_index = max_page_index if page_index > max_page_index else page_index
     idx_frm = (page_index - 1) * num
     image_list = image_list[idx_frm:idx_frm + num]
     image_index = int(image_index)
-    if image_index < 0 or image_index > len(image_list)  - 1:
-        current_file = None 
+    if image_index < 0 or image_index > len(image_list) - 1:
+        current_file = None
         hidden = None
     else:
-        current_file =  image_list[int(image_index)]
+        current_file = image_list[int(image_index)]
         hidden = os.path.join(dir_name, current_file)
     return [os.path.join(dir_name, file) for file in image_list], page_index, image_list, current_file, hidden, ""
 
+
 def first_page_click(dir_name, page_index, image_index, tabname):
     return get_recent_images(dir_name, 1, 0, image_index, tabname)
+
+
 def end_page_click(dir_name, page_index, image_index, tabname):
     return get_recent_images(dir_name, -1, 0, image_index, tabname)
+
+
 def prev_page_click(dir_name, page_index, image_index, tabname):
     return get_recent_images(dir_name, page_index, -1, image_index, tabname)
-def next_page_click(dir_name, page_index, image_index, tabname):    
+
+
+def next_page_click(dir_name, page_index, image_index, tabname):
     return get_recent_images(dir_name, page_index, 1, image_index, tabname)
-def page_index_change(dir_name, page_index, image_index, tabname):    
+
+
+def page_index_change(dir_name, page_index, image_index, tabname):
     return get_recent_images(dir_name, page_index, 0, image_index, tabname)
 
+
 def show_image_info(num, image_path, filenames):
-    #print(f"select image {num}")
+    # print(f"select image {num}")
     file = filenames[int(num)]
     return file, num, os.path.join(image_path, file)
+
+
 def delete_image(delete_num, tabname, dir_name, name, page_index, filenames, image_index):
     if name == "":
         return filenames, delete_num
@@ -66,14 +80,14 @@ def delete_image(delete_num, tabname, dir_name, name, page_index, filenames, ima
         i = 0
         new_file_list = []
         for name in filenames:
-            if i  >= index and i < index + delete_num:            
+            if i >= index and i < index + delete_num:
                 path = os.path.join(dir_name, name)
-                if os.path.exists(path):        
+                if os.path.exists(path):
                     print(f"Delete file {path}")
                     os.remove(path)
-                    txt_file = os.path.splitext(path)[0]  + ".txt"
+                    txt_file = os.path.splitext(path)[0] + ".txt"
                     if os.path.exists(txt_file):
-                        os.remove(txt_file)       
+                        os.remove(txt_file)
                 else:
                     print(f"Not exists file {path}")
             else:
@@ -81,81 +95,81 @@ def delete_image(delete_num, tabname, dir_name, name, page_index, filenames, ima
             i += 1
     return new_file_list, 1
 
+
 def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict):
-        if tabname == "txt2img":
-            dir_name = opts.outdir_txt2img_samples
-        elif tabname == "img2img":
-            dir_name = opts.outdir_img2img_samples
-        elif tabname == "extras":
-            dir_name = opts.outdir_extras_samples
-        d = dir_name.split("/")
-        dir_name = d[0]
-        for p in d[1:]:
-            dir_name = os.path.join(dir_name, p)
-        with gr.Row():    
-            renew_page = gr.Button('Renew Page', elem_id=tabname + "_images_history_renew_page") 
-            first_page = gr.Button('First Page')
-            prev_page = gr.Button('Prev Page') 
-            page_index = gr.Number(value=1, label="Page Index")
-            next_page = gr.Button('Next Page') 
-            end_page = gr.Button('End Page')    
-        with gr.Row(elem_id=tabname + "_images_history"):            
-            with gr.Row():     
-                with gr.Column(scale=2):                    
-                    history_gallery = gr.Gallery(show_label=False, elem_id=tabname + "_images_history_gallery").style(grid=6)
-                    with gr.Row():                        
-                        delete_num = gr.Number(value=1, interactive=True, label="number of images to delete consecutively next")   
-                        delete = gr.Button('Delete',  elem_id=tabname + "_images_history_del_button")                                        
-                with gr.Column():     
-                    with gr.Row():          
-                        pnginfo_send_to_txt2img = gr.Button('Send to txt2img')
-                        pnginfo_send_to_img2img = gr.Button('Send to img2img')
-                    with gr.Row():
-                        with gr.Column():
-                            img_file_info = gr.Textbox(label="Generate Info", interactive=False)
-                            img_file_name = gr.Textbox(label="File Name", interactive=False)    
-                    with gr.Row():    
-                        # hiden items
-
-                        img_path = gr.Textbox(dir_name.rstrip("/") , visible=False)                
-                        tabname_box = gr.Textbox(tabname, visible=False)    
-                        image_index = gr.Textbox(value=-1, visible=False)                        
-                        set_index = gr.Button('set_index',  elem_id=tabname + "_images_history_set_index", visible=False)
-                        filenames = gr.State()
-                        hidden = gr.Image(type="pil", visible=False)
-                        info1 = gr.Textbox(visible=False)
-                        info2 = gr.Textbox(visible=False)
-
-                
-        # turn pages
-        gallery_inputs = [img_path, page_index, image_index, tabname_box]
-        gallery_outputs = [history_gallery, page_index, filenames, img_file_name, hidden, img_file_name]
-
-        first_page.click(first_page_click, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)
-        next_page.click(next_page_click, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)
-        prev_page.click(prev_page_click, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)        
-        end_page.click(end_page_click, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)
-        page_index.submit(page_index_change, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)
-        renew_page.click(page_index_change, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)
-        #page_index.change(page_index_change, inputs=[tabname_box, img_path,  page_index], outputs=[history_gallery, page_index])
-
-        #other funcitons
-        set_index.click(show_image_info, _js="images_history_get_current_img", inputs=[tabname_box,  img_path, filenames], outputs=[img_file_name, image_index, hidden])
-        img_file_name.change(fn=None, _js="images_history_enable_del_buttons", inputs=None, outputs=None)
-        delete.click(delete_image,_js="images_history_delete", inputs=[delete_num, tabname_box, img_path, img_file_name, page_index, filenames, image_index], outputs=[filenames, delete_num]) 
-        hidden.change(fn=run_pnginfo, inputs=[hidden], outputs=[info1, img_file_info, info2])
-       
-        #pnginfo.click(fn=run_pnginfo, inputs=[hidden], outputs=[info1, img_file_info, info2])
-        switch_dict["fn"](pnginfo_send_to_txt2img, switch_dict["t2i"], img_file_info, 'switch_to_txt2img')
-        switch_dict["fn"](pnginfo_send_to_img2img, switch_dict["i2i"], img_file_info, 'switch_to_img2img_img2img')
-    
-        
+    if tabname == "txt2img":
+        dir_name = opts.outdir_txt2img_samples
+    elif tabname == "img2img":
+        dir_name = opts.outdir_img2img_samples
+    elif tabname == "extras":
+        dir_name = opts.outdir_extras_samples
+    d = dir_name.split("/")
+    dir_name = d[0]
+    for p in d[1:]:
+        dir_name = os.path.join(dir_name, p)
+    with gr.Row():
+        renew_page = gr.Button('Renew Page', elem_id=tabname + "_images_history_renew_page")
+        first_page = gr.Button('First Page')
+        prev_page = gr.Button('Prev Page')
+        page_index = gr.Number(value=1, label="Page Index")
+        next_page = gr.Button('Next Page')
+        end_page = gr.Button('End Page')
+    with gr.Row(elem_id=tabname + "_images_history"):
+        with gr.Row():
+            with gr.Column(scale=2):
+                history_gallery = gr.Gallery(show_label=False, elem_id=tabname + "_images_history_gallery").style(grid=6)
+                with gr.Row():
+                    delete_num = gr.Number(value=1, interactive=True, label="number of images to delete consecutively next")
+                    delete = gr.Button('Delete', elem_id=tabname + "_images_history_del_button")
+            with gr.Column():
+                with gr.Row():
+                    pnginfo_send_to_txt2img = gr.Button('Send to txt2img')
+                    pnginfo_send_to_img2img = gr.Button('Send to img2img')
+                with gr.Row():
+                    with gr.Column():
+                        img_file_info = gr.Textbox(label="Generate Info", interactive=False)
+                        img_file_name = gr.Textbox(label="File Name", interactive=False)
+                with gr.Row():
+                    # hiden items
+
+                    img_path = gr.Textbox(dir_name.rstrip("/"), visible=False)
+                    tabname_box = gr.Textbox(tabname, visible=False)
+                    image_index = gr.Textbox(value=-1, visible=False)
+                    set_index = gr.Button('set_index', elem_id=tabname + "_images_history_set_index", visible=False)
+                    filenames = gr.State()
+                    hidden = gr.Image(type="pil", visible=False)
+                    info1 = gr.Textbox(visible=False)
+                    info2 = gr.Textbox(visible=False)
+
+    # turn pages
+    gallery_inputs = [img_path, page_index, image_index, tabname_box]
+    gallery_outputs = [history_gallery, page_index, filenames, img_file_name, hidden, img_file_name]
+
+    first_page.click(first_page_click, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)
+    next_page.click(next_page_click, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)
+    prev_page.click(prev_page_click, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)
+    end_page.click(end_page_click, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)
+    page_index.submit(page_index_change, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)
+    renew_page.click(page_index_change, _js="images_history_turnpage", inputs=gallery_inputs, outputs=gallery_outputs)
+    # page_index.change(page_index_change, inputs=[tabname_box, img_path,  page_index], outputs=[history_gallery, page_index])
+
+    # other funcitons
+    set_index.click(show_image_info, _js="images_history_get_current_img", inputs=[tabname_box, img_path, filenames], outputs=[img_file_name, image_index, hidden])
+    img_file_name.change(fn=None, _js="images_history_enable_del_buttons", inputs=None, outputs=None)
+    delete.click(delete_image, _js="images_history_delete", inputs=[delete_num, tabname_box, img_path, img_file_name, page_index, filenames, image_index], outputs=[filenames, delete_num])
+    hidden.change(fn=run_pnginfo, inputs=[hidden], outputs=[info1, img_file_info, info2])
+
+    # pnginfo.click(fn=run_pnginfo, inputs=[hidden], outputs=[info1, img_file_info, info2])
+    switch_dict["fn"](pnginfo_send_to_txt2img, switch_dict["t2i"], img_file_info, 'switch_to_txt2img')
+    switch_dict["fn"](pnginfo_send_to_img2img, switch_dict["i2i"], img_file_info, 'switch_to_img2img_img2img')
+
+
 def create_history_tabs(gr, opts, run_pnginfo, switch_dict):
     with gr.Blocks(analytics_enabled=False) as images_history:
         with gr.Tabs() as tabs:
             with gr.Tab("txt2img history"):
-                with gr.Blocks(analytics_enabled=False) as images_history_txt2img:   
-                    show_images_history(gr, opts, "txt2img", run_pnginfo, switch_dict) 
+                with gr.Blocks(analytics_enabled=False) as images_history_txt2img:
+                    show_images_history(gr, opts, "txt2img", run_pnginfo, switch_dict)
             with gr.Tab("img2img history"):
                 with gr.Blocks(analytics_enabled=False) as images_history_img2img:
                     show_images_history(gr, opts, "img2img", run_pnginfo, switch_dict)
-- 
cgit v1.2.3


From a8f7722e4e7460122b44589c3718eee0c597009d Mon Sep 17 00:00:00 2001
From: space-nuko <24979496+space-nuko@users.noreply.github.com>
Date: Fri, 14 Oct 2022 14:26:38 -0700
Subject: Fix XY-plot steps if highres fix is enabled

---
 scripts/xy_grid.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 8c7da6bb..88ad3bf7 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -12,7 +12,7 @@ import gradio as gr
 
 from modules import images
 from modules.hypernetworks import hypernetwork
-from modules.processing import process_images, Processed, get_correct_sampler
+from modules.processing import process_images, Processed, get_correct_sampler, StableDiffusionProcessingTxt2Img
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
 import modules.sd_samplers
@@ -354,6 +354,9 @@ class Script(scripts.Script):
         else:
             total_steps = p.steps * len(xs) * len(ys)
 
+        if isinstance(p, StableDiffusionProcessingTxt2Img) and p.enable_hr:
+            total_steps *= 2
+
         print(f"X/Y plot will create {len(xs) * len(ys) * p.n_iter} images on a {len(xs)}x{len(ys)} grid. (Total steps to process: {total_steps * p.n_iter})")
         shared.total_tqdm.updateTotal(total_steps * p.n_iter)
 
-- 
cgit v1.2.3


From acedbe67d2b8a3af99ca3b9a2f809e7a2db285d1 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 15 Oct 2022 00:43:15 +0300
Subject: bring history tab back, make it behave; it's still slow but won't
 fuck anything up until you use it

---
 javascript/images_history.js | 16 ++++++++++++----
 modules/ui.py                |  4 ++--
 2 files changed, 14 insertions(+), 6 deletions(-)

diff --git a/javascript/images_history.js b/javascript/images_history.js
index 3a20056b..f7d052c3 100644
--- a/javascript/images_history.js
+++ b/javascript/images_history.js
@@ -163,10 +163,15 @@ function images_history_init(){
         for (var i in images_history_tab_list){               
             var tabname = images_history_tab_list[i]
             tab_btns[i].setAttribute("tabname", tabname);
-            tab_btns[i].addEventListener('click', images_history_click_tab);
+
+            // this refreshes history upon tab switch
+            // until the history is known to work well, which is not the case now, we do not do this at startup
+            //tab_btns[i].addEventListener('click', images_history_click_tab);
         }    
-        tabs_box.classList.add(images_history_tab_list[0]);   
-           load_txt2img_button.click();
+        tabs_box.classList.add(images_history_tab_list[0]);
+
+        // same as above, at page load
+        //load_txt2img_button.click();
     } else {
         setTimeout(images_history_init, 500);
     } 
@@ -182,12 +187,15 @@ document.addEventListener("DOMContentLoaded", function() {
             buttons.forEach(function(bnt){    
                 bnt.addEventListener('click', images_history_click_image, true);
             });
+
+            // same as load_txt2img_button.click() above
+            /*
             var cls_btn = gradioApp().getElementById(tabname + '_images_history_gallery').querySelector("svg");
             if (cls_btn){
                 cls_btn.addEventListener('click', function(){
                     gradioApp().getElementById(tabname + '_images_history_renew_page').click();
                 }, false);
-            }
+            }*/
 
         }     
     });
diff --git a/modules/ui.py b/modules/ui.py
index c5d295ea..1bc919c7 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1090,7 +1090,7 @@ def create_ui(wrap_gradio_gpu_call):
         "i2i":img2img_paste_fields
     }
 
-    #images_history = img_his.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict)
+    images_history = img_his.create_history_tabs(gr, opts, wrap_gradio_call(modules.extras.run_pnginfo), images_history_switch_dict)
 
     with gr.Blocks() as modelmerger_interface:
         with gr.Row().style(equal_height=False):
@@ -1487,7 +1487,7 @@ Requested path was: {f}
         (img2img_interface, "img2img", "img2img"),
         (extras_interface, "Extras", "extras"),
         (pnginfo_interface, "PNG Info", "pnginfo"),
-        #(images_history, "History", "images_history"),
+        (images_history, "History", "images_history"),
         (modelmerger_interface, "Checkpoint Merger", "modelmerger"),
         (train_interface, "Train", "ti"),
         (settings_interface, "Settings", "settings"),
-- 
cgit v1.2.3


From c7a86f7fe9c0b8967a87e8d709f507d2f44400d8 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 15 Oct 2022 09:24:59 +0300
Subject: add option to use batch size for training

---
 modules/hypernetworks/hypernetwork.py          | 33 +++++++++++++++++++-------
 modules/textual_inversion/dataset.py           | 31 ++++++++++++++----------
 modules/textual_inversion/textual_inversion.py | 17 +++++++------
 modules/ui.py                                  |  3 +++
 4 files changed, 54 insertions(+), 30 deletions(-)

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 59c7ac6e..a2b3bc0a 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -182,7 +182,21 @@ def attention_CrossAttention_forward(self, x, context=None, mask=None):
     return self.to_out(out)
 
 
-def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
+def stack_conds(conds):
+    if len(conds) == 1:
+        return torch.stack(conds)
+
+    # same as in reconstruct_multicond_batch
+    token_count = max([x.shape[0] for x in conds])
+    for i in range(len(conds)):
+        if conds[i].shape[0] != token_count:
+            last_vector = conds[i][-1:]
+            last_vector_repeated = last_vector.repeat([token_count - conds[i].shape[0], 1])
+            conds[i] = torch.vstack([conds[i], last_vector_repeated])
+
+    return torch.stack(conds)
+
+def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
     assert hypernetwork_name, 'hypernetwork not selected'
 
     path = shared.hypernetworks.get(hypernetwork_name, None)
@@ -211,7 +225,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
 
     shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
     with torch.autocast("cuda"):
-        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=512, height=512, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file, include_cond=True)
+        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=512, height=512, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file, include_cond=True, batch_size=batch_size)
 
     if unload:
         shared.sd_model.cond_stage_model.to(devices.cpu)
@@ -235,7 +249,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
     optimizer = torch.optim.AdamW(weights, lr=scheduler.learn_rate)
 
     pbar = tqdm.tqdm(enumerate(ds), total=steps - ititial_step)
-    for i, entry in pbar:
+    for i, entries in pbar:
         hypernetwork.step = i + ititial_step
 
         scheduler.apply(optimizer, hypernetwork.step)
@@ -246,11 +260,12 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
             break
 
         with torch.autocast("cuda"):
-            cond = entry.cond.to(devices.device)
-            x = entry.latent.to(devices.device)
-            loss = shared.sd_model(x.unsqueeze(0), cond)[0]
+            c = stack_conds([entry.cond for entry in entries]).to(devices.device)
+#            c = torch.vstack([entry.cond for entry in entries]).to(devices.device)
+            x = torch.stack([entry.latent for entry in entries]).to(devices.device)
+            loss = shared.sd_model(x, c)[0]
             del x
-            del cond
+            del c
 
             losses[hypernetwork.step % losses.shape[0]] = loss.item()
 
@@ -292,7 +307,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
                 p.width = preview_width
                 p.height = preview_height
             else:
-                p.prompt = entry.cond_text
+                p.prompt = entries[0].cond_text
                 p.steps = 20
 
             preview_text = p.prompt
@@ -315,7 +330,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
 <p>
 Loss: {losses.mean():.7f}<br/>
 Step: {hypernetwork.step}<br/>
-Last prompt: {html.escape(entry.cond_text)}<br/>
+Last prompt: {html.escape(entries[0].cond_text)}<br/>
 Last saved embedding: {html.escape(last_saved_file)}<br/>
 Last saved image: {html.escape(last_saved_image)}<br/>
 </p>
diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index 67e90afe..bd99c0cb 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -24,11 +24,12 @@ class DatasetEntry:
 
 
 class PersonalizedBase(Dataset):
-    def __init__(self, data_root, width, height, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None, include_cond=False):
-        re_word = re.compile(shared.opts.dataset_filename_word_regex) if len(shared.opts.dataset_filename_word_regex)>0 else None
+    def __init__(self, data_root, width, height, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None, include_cond=False, batch_size=1):
+        re_word = re.compile(shared.opts.dataset_filename_word_regex) if len(shared.opts.dataset_filename_word_regex) > 0 else None
 
         self.placeholder_token = placeholder_token
 
+        self.batch_size = batch_size
         self.width = width
         self.height = height
         self.flip = transforms.RandomHorizontalFlip(p=flip_p)
@@ -78,13 +79,13 @@ class PersonalizedBase(Dataset):
 
             if include_cond:
                 entry.cond_text = self.create_text(filename_text)
-                entry.cond = cond_model([entry.cond_text]).to(devices.cpu)
+                entry.cond = cond_model([entry.cond_text]).to(devices.cpu).squeeze(0)
 
             self.dataset.append(entry)
 
-        self.length = len(self.dataset) * repeats
+        self.length = len(self.dataset) * repeats // batch_size
 
-        self.initial_indexes = np.arange(self.length) % len(self.dataset)
+        self.initial_indexes = np.arange(len(self.dataset))
         self.indexes = None
         self.shuffle()
 
@@ -101,13 +102,19 @@ class PersonalizedBase(Dataset):
         return self.length
 
     def __getitem__(self, i):
-        if i % len(self.dataset) == 0:
-            self.shuffle()
+        res = []
 
-        index = self.indexes[i % len(self.indexes)]
-        entry = self.dataset[index]
+        for j in range(self.batch_size):
+            position = i * self.batch_size + j
+            if position % len(self.indexes) == 0:
+                self.shuffle()
 
-        if entry.cond is None:
-            entry.cond_text = self.create_text(entry.filename_text)
+            index = self.indexes[position % len(self.indexes)]
+            entry = self.dataset[index]
 
-        return entry
+            if entry.cond is None:
+                entry.cond_text = self.create_text(entry.filename_text)
+
+            res.append(entry)
+
+        return res
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index da0d77a0..e754747e 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -199,7 +199,7 @@ def write_loss(log_directory, filename, step, epoch_len, values):
         })
 
 
-def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
+def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
     assert embedding_name, 'embedding not selected'
 
     shared.state.textinfo = "Initializing textual inversion training..."
@@ -231,7 +231,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
 
     shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
     with torch.autocast("cuda"):
-        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, height=training_height, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file)
+        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, height=training_height, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file, batch_size=batch_size)
 
     hijack = sd_hijack.model_hijack
 
@@ -251,7 +251,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
     optimizer = torch.optim.AdamW([embedding.vec], lr=scheduler.learn_rate)
 
     pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step)
-    for i, entry in pbar:
+    for i, entries in pbar:
         embedding.step = i + ititial_step
 
         scheduler.apply(optimizer, embedding.step)
@@ -262,10 +262,9 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
             break
 
         with torch.autocast("cuda"):
-            c = cond_model([entry.cond_text])
-
-            x = entry.latent.to(devices.device)
-            loss = shared.sd_model(x.unsqueeze(0), c)[0]
+            c = cond_model([entry.cond_text for entry in entries])
+            x = torch.stack([entry.latent for entry in entries]).to(devices.device)
+            loss = shared.sd_model(x, c)[0]
             del x
 
             losses[embedding.step % losses.shape[0]] = loss.item()
@@ -307,7 +306,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
                 p.width = preview_width
                 p.height = preview_height
             else:
-                p.prompt = entry.cond_text
+                p.prompt = entries[0].cond_text
                 p.steps = 20
                 p.width = training_width
                 p.height = training_height
@@ -348,7 +347,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
 <p>
 Loss: {losses.mean():.7f}<br/>
 Step: {embedding.step}<br/>
-Last prompt: {html.escape(entry.cond_text)}<br/>
+Last prompt: {html.escape(entries[0].cond_text)}<br/>
 Last saved embedding: {html.escape(last_saved_file)}<br/>
 Last saved image: {html.escape(last_saved_image)}<br/>
 </p>
diff --git a/modules/ui.py b/modules/ui.py
index 1bc919c7..45550ea8 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1166,6 +1166,7 @@ def create_ui(wrap_gradio_gpu_call):
                     train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
                     train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', choices=[x for x in shared.hypernetworks.keys()])
                     learn_rate = gr.Textbox(label='Learning rate', placeholder="Learning rate", value="0.005")
+                    batch_size = gr.Number(label='Batch size', value=1, precision=0)
                     dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images")
                     log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")
                     template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"))
@@ -1244,6 +1245,7 @@ def create_ui(wrap_gradio_gpu_call):
             inputs=[
                 train_embedding_name,
                 learn_rate,
+                batch_size,
                 dataset_directory,
                 log_directory,
                 training_width,
@@ -1268,6 +1270,7 @@ def create_ui(wrap_gradio_gpu_call):
             inputs=[
                 train_hypernetwork_name,
                 learn_rate,
+                batch_size,
                 dataset_directory,
                 log_directory,
                 steps,
-- 
cgit v1.2.3


From 3bd40bb77ff274f2a09efa07b759eebf6dc40b58 Mon Sep 17 00:00:00 2001
From: ruocaled <ruocaled@gmail.com>
Date: Fri, 14 Oct 2022 11:05:14 -0700
Subject: auto re-open selected image after re-generation

attach an observer of gallery when generation in progress, if there was a image selected in gallery and gallery has only 1 image, auto re-select/open that image.

This matches behavior of prior to Gradio 3.4.1 version bump, is a quality of life feature many people enjoyed.
---
 javascript/progressbar.js | 32 ++++++++++++++++++++++++++++++++
 1 file changed, 32 insertions(+)

diff --git a/javascript/progressbar.js b/javascript/progressbar.js
index 4395a215..4994b476 100644
--- a/javascript/progressbar.js
+++ b/javascript/progressbar.js
@@ -1,5 +1,7 @@
 // code related to showing and updating progressbar shown as the image is being made
 global_progressbars = {}
+galleries = {}
+galleryObservers = {}
 
 function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_skip, id_interrupt, id_preview, id_gallery){
     var progressbar = gradioApp().getElementById(id_progressbar)
@@ -31,6 +33,9 @@ function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_skip
                 preview.style.width = gallery.clientWidth + "px"
                 preview.style.height = gallery.clientHeight + "px"
 
+				//only watch gallery if there is a generation process going on
+                check_gallery(id_gallery);    
+
                 var progressDiv = gradioApp().querySelectorAll('#' + id_progressbar_span).length > 0;
                 if(!progressDiv){
                     if (skip) {
@@ -38,6 +43,12 @@ function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_skip
                     }
                     interrupt.style.display = "none"
                 }
+
+				//disconnect observer once generation finished, so user can close selected image if they want
+				if (galleryObservers[id_gallery]) {
+					galleryObservers[id_gallery].disconnect();
+					galleries[id_gallery] = null;
+				}    
             }
 
             window.setTimeout(function() { requestMoreProgress(id_part, id_progressbar_span, id_skip, id_interrupt) }, 500)
@@ -46,6 +57,27 @@ function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_skip
 	}
 }
 
+function check_gallery(id_gallery){
+    let gallery = gradioApp().getElementById(id_gallery)
+    // if gallery has no change, no need to setting up observer again.
+    if (gallery && galleries[id_gallery] !== gallery){
+        galleries[id_gallery] = gallery;
+        if(galleryObservers[id_gallery]){
+            galleryObservers[id_gallery].disconnect();
+        }
+        galleryObservers[id_gallery] = new MutationObserver(function (){
+            let galleryButtons = gradioApp().querySelectorAll('#'+id_gallery+' .gallery-item')
+            let galleryBtnSelected = gradioApp().querySelector('#'+id_gallery+' .gallery-item.\\!ring-2')
+            if (galleryButtons.length === 1 && !galleryBtnSelected) {
+                //automatically open when there is only 1 gallery btn, and was previously selected
+                galleryButtons[0].click();
+                console.log('clicked');
+            }
+        })
+        galleryObservers[id_gallery].observe( gallery, { childList:true, subtree:false })
+    }
+}
+
 onUiUpdate(function(){
     check_progressbar('txt2img', 'txt2img_progressbar', 'txt2img_progress_span', 'txt2img_skip', 'txt2img_interrupt', 'txt2img_preview', 'txt2img_gallery')
     check_progressbar('img2img', 'img2img_progressbar', 'img2img_progress_span', 'img2img_skip', 'img2img_interrupt', 'img2img_preview', 'img2img_gallery')
-- 
cgit v1.2.3


From 6b5c54c187796900bf677c8c14b62a166eb53b24 Mon Sep 17 00:00:00 2001
From: ruocaled <ruocaled@gmail.com>
Date: Fri, 14 Oct 2022 11:06:38 -0700
Subject: remove console.log

---
 javascript/progressbar.js | 1 -
 1 file changed, 1 deletion(-)

diff --git a/javascript/progressbar.js b/javascript/progressbar.js
index 4994b476..b4925e99 100644
--- a/javascript/progressbar.js
+++ b/javascript/progressbar.js
@@ -71,7 +71,6 @@ function check_gallery(id_gallery){
             if (galleryButtons.length === 1 && !galleryBtnSelected) {
                 //automatically open when there is only 1 gallery btn, and was previously selected
                 galleryButtons[0].click();
-                console.log('clicked');
             }
         })
         galleryObservers[id_gallery].observe( gallery, { childList:true, subtree:false })
-- 
cgit v1.2.3


From c84eef8195b2bae4f4b4d1785159ae9efd937abe Mon Sep 17 00:00:00 2001
From: ruocaled <ruocaled@gmail.com>
Date: Fri, 14 Oct 2022 11:10:26 -0700
Subject: fix observer disconnect logic

---
 javascript/progressbar.js | 12 +++++++-----
 1 file changed, 7 insertions(+), 5 deletions(-)

diff --git a/javascript/progressbar.js b/javascript/progressbar.js
index b4925e99..196fe507 100644
--- a/javascript/progressbar.js
+++ b/javascript/progressbar.js
@@ -42,13 +42,15 @@ function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_skip
                         skip.style.display = "none"
                     }
                     interrupt.style.display = "none"
+			
+                    //disconnect observer once generation finished, so user can close selected image if they want
+                    if (galleryObservers[id_gallery]) {
+                        galleryObservers[id_gallery].disconnect();
+                        galleries[id_gallery] = null;
+                    }    
                 }
 
-				//disconnect observer once generation finished, so user can close selected image if they want
-				if (galleryObservers[id_gallery]) {
-					galleryObservers[id_gallery].disconnect();
-					galleries[id_gallery] = null;
-				}    
+
             }
 
             window.setTimeout(function() { requestMoreProgress(id_part, id_progressbar_span, id_skip, id_interrupt) }, 500)
-- 
cgit v1.2.3


From b26efff8c496309329cd1982aee55e81bf81a655 Mon Sep 17 00:00:00 2001
From: ruocaled <ruocaled@gmail.com>
Date: Fri, 14 Oct 2022 17:14:59 -0700
Subject: allow re-open for multiple images gallery

---
 javascript/progressbar.js | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/javascript/progressbar.js b/javascript/progressbar.js
index 196fe507..574fd549 100644
--- a/javascript/progressbar.js
+++ b/javascript/progressbar.js
@@ -67,12 +67,13 @@ function check_gallery(id_gallery){
         if(galleryObservers[id_gallery]){
             galleryObservers[id_gallery].disconnect();
         }
+        let prevSelectedIndex = selected_gallery_index();
         galleryObservers[id_gallery] = new MutationObserver(function (){
             let galleryButtons = gradioApp().querySelectorAll('#'+id_gallery+' .gallery-item')
             let galleryBtnSelected = gradioApp().querySelector('#'+id_gallery+' .gallery-item.\\!ring-2')
-            if (galleryButtons.length === 1 && !galleryBtnSelected) {
-                //automatically open when there is only 1 gallery btn, and was previously selected
-                galleryButtons[0].click();
+            if (prevSelectedIndex !== -1 && galleryButtons.length>prevSelectedIndex && !galleryBtnSelected) {
+                //automatically re-open previously selected index (if exists)
+                galleryButtons[prevSelectedIndex].click();
             }
         })
         galleryObservers[id_gallery].observe( gallery, { childList:true, subtree:false })
-- 
cgit v1.2.3


From c7cd2fda5a6c9c97d5c238e0f2e1146d346e0e93 Mon Sep 17 00:00:00 2001
From: ruocaled <ruocaled@gmail.com>
Date: Fri, 14 Oct 2022 19:05:41 -0700
Subject: re-attach full screen zoom listeners

---
 javascript/progressbar.js | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/javascript/progressbar.js b/javascript/progressbar.js
index 574fd549..35f20b15 100644
--- a/javascript/progressbar.js
+++ b/javascript/progressbar.js
@@ -74,6 +74,9 @@ function check_gallery(id_gallery){
             if (prevSelectedIndex !== -1 && galleryButtons.length>prevSelectedIndex && !galleryBtnSelected) {
                 //automatically re-open previously selected index (if exists)
                 galleryButtons[prevSelectedIndex].click();
+		setTimeout(function (){
+                    showGalleryImage()
+                },100)
             }
         })
         galleryObservers[id_gallery].observe( gallery, { childList:true, subtree:false })
-- 
cgit v1.2.3


From 661a61985c7bee34a67390a05761e25830a6b918 Mon Sep 17 00:00:00 2001
From: ruocaled <ruocaled@gmail.com>
Date: Fri, 14 Oct 2022 19:25:30 -0700
Subject: remove extra 100ms timeout

---
 javascript/progressbar.js | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/javascript/progressbar.js b/javascript/progressbar.js
index 35f20b15..076f0a97 100644
--- a/javascript/progressbar.js
+++ b/javascript/progressbar.js
@@ -74,9 +74,7 @@ function check_gallery(id_gallery){
             if (prevSelectedIndex !== -1 && galleryButtons.length>prevSelectedIndex && !galleryBtnSelected) {
                 //automatically re-open previously selected index (if exists)
                 galleryButtons[prevSelectedIndex].click();
-		setTimeout(function (){
-                    showGalleryImage()
-                },100)
+		showGalleryImage();
             }
         })
         galleryObservers[id_gallery].observe( gallery, { childList:true, subtree:false })
-- 
cgit v1.2.3


From db27b987a97fc8b7894a9dd34bd7641536f9c424 Mon Sep 17 00:00:00 2001
From: aoirusann <yimodo.siki@gmail.com>
Date: Sat, 15 Oct 2022 11:48:13 +0800
Subject: Add hint for `ctrl/alt enter` And duplicate implementations are
 removed

---
 javascript/ui.js | 10 ----------
 modules/ui.py    | 10 ++++++++--
 script.js        |  4 ++--
 3 files changed, 10 insertions(+), 14 deletions(-)

diff --git a/javascript/ui.js b/javascript/ui.js
index 0f8fe68e..56f4216f 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -187,12 +187,10 @@ onUiUpdate(function(){
 	if (!txt2img_textarea) {
 		txt2img_textarea = gradioApp().querySelector("#txt2img_prompt > label > textarea");
 		txt2img_textarea?.addEventListener("input", () => update_token_counter("txt2img_token_button"));
-        txt2img_textarea?.addEventListener("keyup", (event) => submit_prompt(event, "txt2img_generate"));
 	}
 	if (!img2img_textarea) {
 		img2img_textarea = gradioApp().querySelector("#img2img_prompt > label > textarea");
 		img2img_textarea?.addEventListener("input", () => update_token_counter("img2img_token_button"));
-        img2img_textarea?.addEventListener("keyup", (event) => submit_prompt(event, "img2img_generate"));
 	}
 })
 
@@ -220,14 +218,6 @@ function update_token_counter(button_id) {
 	token_timeout = setTimeout(() => gradioApp().getElementById(button_id)?.click(), wait_time);
 }
 
-function submit_prompt(event, generate_button_id) {
-    if (event.altKey && event.keyCode === 13) {
-        event.preventDefault();
-        gradioApp().getElementById(generate_button_id).click();
-        return;
-    }
-}
-
 function restart_reload(){
     document.body.innerHTML='<h1 style="font-family:monospace;margin-top:20%;color:lightgray;text-align:center;">Reloading...</h1>';
     setTimeout(function(){location.reload()},2000)
diff --git a/modules/ui.py b/modules/ui.py
index 45550ea8..baf4c397 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -433,7 +433,10 @@ def create_toprow(is_img2img):
             with gr.Row():
                 with gr.Column(scale=80):
                     with gr.Row():
-                        prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, placeholder="Prompt", lines=2)
+                        prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=2, 
+                            placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)"
+                        )
+
                 with gr.Column(scale=1, elem_id="roll_col"):
                     roll = gr.Button(value=art_symbol, elem_id="roll", visible=len(shared.artist_db.artists) > 0)
                     paste = gr.Button(value=paste_symbol, elem_id="paste")
@@ -446,7 +449,10 @@ def create_toprow(is_img2img):
             with gr.Row():
                 with gr.Column(scale=8):
                     with gr.Row():
-                        negative_prompt = gr.Textbox(label="Negative prompt", elem_id="negative_prompt", show_label=False, placeholder="Negative prompt", lines=2)
+                        negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2, 
+                            placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)"
+                        )
+
                 with gr.Column(scale=1, elem_id="roll_col"):
                     sh = gr.Button(elem_id="sh", visible=True)                           
 
diff --git a/script.js b/script.js
index 9543cbe6..88f2c839 100644
--- a/script.js
+++ b/script.js
@@ -50,9 +50,9 @@ document.addEventListener("DOMContentLoaded", function() {
  document.addEventListener('keydown', function(e) {
     var handled = false;
     if (e.key !== undefined) {
-        if((e.key == "Enter" && (e.metaKey || e.ctrlKey))) handled = true;
+        if((e.key == "Enter" && (e.metaKey || e.ctrlKey || e.altKey))) handled = true;
     } else if (e.keyCode !== undefined) {
-        if((e.keyCode == 13 && (e.metaKey || e.ctrlKey))) handled = true;
+        if((e.keyCode == 13 && (e.metaKey || e.ctrlKey || e.altKey))) handled = true;
     }
     if (handled) {
         button = get_uiCurrentTabContent().querySelector('button[id$=_generate]');
-- 
cgit v1.2.3


From cd28465bf87d911965790513c37e6881e4231523 Mon Sep 17 00:00:00 2001
From: ddPn08 <pyn.g.1125@gmail.com>
Date: Sat, 15 Oct 2022 10:56:02 +0900
Subject: do not force relative paths in image history

---
 modules/images_history.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/images_history.py b/modules/images_history.py
index f5ef44fe..09c749fe 100644
--- a/modules/images_history.py
+++ b/modules/images_history.py
@@ -104,7 +104,7 @@ def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict):
     elif tabname == "extras":
         dir_name = opts.outdir_extras_samples
     d = dir_name.split("/")
-    dir_name = d[0]
+    dir_name = "/" if dir_name.startswith("/") else d[0]
     for p in d[1:]:
         dir_name = os.path.join(dir_name, p)
     with gr.Row():
-- 
cgit v1.2.3


From 0da6c1809996f0f696d4047faf4b9c9939e26daa Mon Sep 17 00:00:00 2001
From: ddPn08 <pyn.g.1125@gmail.com>
Date: Sat, 15 Oct 2022 11:22:05 +0900
Subject: use "outdir_samples" if specified

---
 modules/images_history.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/modules/images_history.py b/modules/images_history.py
index 09c749fe..9260df8a 100644
--- a/modules/images_history.py
+++ b/modules/images_history.py
@@ -97,7 +97,9 @@ def delete_image(delete_num, tabname, dir_name, name, page_index, filenames, ima
 
 
 def show_images_history(gr, opts, tabname, run_pnginfo, switch_dict):
-    if tabname == "txt2img":
+    if opts.outdir_samples != "":
+        dir_name = opts.outdir_samples
+    elif tabname == "txt2img":
         dir_name = opts.outdir_txt2img_samples
     elif tabname == "img2img":
         dir_name = opts.outdir_img2img_samples
-- 
cgit v1.2.3


From 77bf3525f894e89e8f3d812319e822e44419f5ea Mon Sep 17 00:00:00 2001
From: Cassy-Lee <104408348+Cassy-Lee@users.noreply.github.com>
Date: Fri, 14 Oct 2022 17:31:39 +0800
Subject: Update launch.py

Allow change set --index-url for pip.
---
 launch.py | 13 +++++++------
 1 file changed, 7 insertions(+), 6 deletions(-)

diff --git a/launch.py b/launch.py
index a7c5807b..b753efc1 100644
--- a/launch.py
+++ b/launch.py
@@ -89,6 +89,7 @@ def prepare_enviroment():
     torch_command = os.environ.get('TORCH_COMMAND', "pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 --extra-index-url https://download.pytorch.org/whl/cu113")
     requirements_file = os.environ.get('REQS_FILE', "requirements_versions.txt")
     commandline_args = os.environ.get('COMMANDLINE_ARGS', "")
+    index_url = os.environ.get('INDEX_URL',"")
 
     gfpgan_package = os.environ.get('GFPGAN_PACKAGE', "git+https://github.com/TencentARC/GFPGAN.git@8d2447a2d918f8eba5a4a01463fd48e45126a379")
     clip_package = os.environ.get('CLIP_PACKAGE', "git+https://github.com/openai/CLIP.git@d50d76daa670286dd6cacf3bcd80b5e4823fc8e1")
@@ -121,22 +122,22 @@ def prepare_enviroment():
         run_python("import torch; assert torch.cuda.is_available(), 'Torch is not able to use GPU; add --skip-torch-cuda-test to COMMANDLINE_ARGS variable to disable this check'")
 
     if not is_installed("gfpgan"):
-        run_pip(f"install {gfpgan_package}", "gfpgan")
+        run_pip(f"install {gfpgan_package}{f' --index-url {index_url}' if index_url!='' else ''}", "gfpgan")
 
     if not is_installed("clip"):
-        run_pip(f"install {clip_package}", "clip")
+        run_pip(f"install {clip_package}{f' --index-url {index_url}' if index_url!='' else ''}", "clip")
 
     if not is_installed("xformers") and xformers and platform.python_version().startswith("3.10"):
         if platform.system() == "Windows":
             run_pip("install https://github.com/C43H66N12O12S2/stable-diffusion-webui/releases/download/c/xformers-0.0.14.dev0-cp310-cp310-win_amd64.whl", "xformers")
         elif platform.system() == "Linux":
-            run_pip("install xformers", "xformers")
+            run_pip("install xformers{f' --index-url {index_url}' if index_url!='' else ''}", "xformers")
 
     if not is_installed("deepdanbooru") and deepdanbooru:
         run_pip("install git+https://github.com/KichangKim/DeepDanbooru.git@edf73df4cdaeea2cf00e9ac08bd8a9026b7a7b26#egg=deepdanbooru[tensorflow] tensorflow==2.10.0 tensorflow-io==0.27.0", "deepdanbooru")
 
     if not is_installed("pyngrok") and ngrok:
-        run_pip("install pyngrok", "ngrok")
+        run_pip("install pyngrok{f' --index-url {index_url}' if index_url!='' else ''}", "ngrok")
 
     os.makedirs(dir_repos, exist_ok=True)
 
@@ -147,9 +148,9 @@ def prepare_enviroment():
     git_clone("https://github.com/salesforce/BLIP.git", repo_dir('BLIP'), "BLIP", blip_commit_hash)
 
     if not is_installed("lpips"):
-        run_pip(f"install -r {os.path.join(repo_dir('CodeFormer'), 'requirements.txt')}", "requirements for CodeFormer")
+        run_pip(f"install -r {os.path.join(repo_dir('CodeFormer'), 'requirements.txt')}{f' --index-url {index_url}' if index_url!='' else ''}", "requirements for CodeFormer")
 
-    run_pip(f"install -r {requirements_file}", "requirements for Web UI")
+    run_pip(f"install -r {requirements_file}{f' --index-url {index_url}' if index_url!='' else ''}", "requirements for Web UI")
 
     sys.argv += args
 
-- 
cgit v1.2.3


From 7855993bef0a16c235649027527b0f3ad7cca757 Mon Sep 17 00:00:00 2001
From: Cassy-Lee <104408348+Cassy-Lee@users.noreply.github.com>
Date: Sat, 15 Oct 2022 10:02:18 +0800
Subject: Move index_url args into run_pip.

---
 launch.py | 16 ++++++++--------
 1 file changed, 8 insertions(+), 8 deletions(-)

diff --git a/launch.py b/launch.py
index b753efc1..42072f33 100644
--- a/launch.py
+++ b/launch.py
@@ -9,6 +9,7 @@ import platform
 dir_repos = "repositories"
 python = sys.executable
 git = os.environ.get('GIT', "git")
+index_url = os.environ.get('INDEX_URL',"")
 
 
 def extract_arg(args, name):
@@ -57,7 +58,7 @@ def run_python(code, desc=None, errdesc=None):
 
 
 def run_pip(args, desc=None):
-    return run(f'"{python}" -m pip {args} --prefer-binary', desc=f"Installing {desc}", errdesc=f"Couldn't install {desc}")
+    return run(f'"{python}" -m pip {args} --prefer-binary{f' --index-url {index_url}' if index_url!='' else ''}', desc=f"Installing {desc}", errdesc=f"Couldn't install {desc}")
 
 
 def check_run_python(code):
@@ -89,7 +90,6 @@ def prepare_enviroment():
     torch_command = os.environ.get('TORCH_COMMAND', "pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 --extra-index-url https://download.pytorch.org/whl/cu113")
     requirements_file = os.environ.get('REQS_FILE', "requirements_versions.txt")
     commandline_args = os.environ.get('COMMANDLINE_ARGS', "")
-    index_url = os.environ.get('INDEX_URL',"")
 
     gfpgan_package = os.environ.get('GFPGAN_PACKAGE', "git+https://github.com/TencentARC/GFPGAN.git@8d2447a2d918f8eba5a4a01463fd48e45126a379")
     clip_package = os.environ.get('CLIP_PACKAGE', "git+https://github.com/openai/CLIP.git@d50d76daa670286dd6cacf3bcd80b5e4823fc8e1")
@@ -122,22 +122,22 @@ def prepare_enviroment():
         run_python("import torch; assert torch.cuda.is_available(), 'Torch is not able to use GPU; add --skip-torch-cuda-test to COMMANDLINE_ARGS variable to disable this check'")
 
     if not is_installed("gfpgan"):
-        run_pip(f"install {gfpgan_package}{f' --index-url {index_url}' if index_url!='' else ''}", "gfpgan")
+        run_pip(f"install {gfpgan_package}", "gfpgan")
 
     if not is_installed("clip"):
-        run_pip(f"install {clip_package}{f' --index-url {index_url}' if index_url!='' else ''}", "clip")
+        run_pip(f"install {clip_package}", "clip")
 
     if not is_installed("xformers") and xformers and platform.python_version().startswith("3.10"):
         if platform.system() == "Windows":
             run_pip("install https://github.com/C43H66N12O12S2/stable-diffusion-webui/releases/download/c/xformers-0.0.14.dev0-cp310-cp310-win_amd64.whl", "xformers")
         elif platform.system() == "Linux":
-            run_pip("install xformers{f' --index-url {index_url}' if index_url!='' else ''}", "xformers")
+            run_pip("install xformers", "xformers")
 
     if not is_installed("deepdanbooru") and deepdanbooru:
         run_pip("install git+https://github.com/KichangKim/DeepDanbooru.git@edf73df4cdaeea2cf00e9ac08bd8a9026b7a7b26#egg=deepdanbooru[tensorflow] tensorflow==2.10.0 tensorflow-io==0.27.0", "deepdanbooru")
 
     if not is_installed("pyngrok") and ngrok:
-        run_pip("install pyngrok{f' --index-url {index_url}' if index_url!='' else ''}", "ngrok")
+        run_pip("install pyngrok", "ngrok")
 
     os.makedirs(dir_repos, exist_ok=True)
 
@@ -148,9 +148,9 @@ def prepare_enviroment():
     git_clone("https://github.com/salesforce/BLIP.git", repo_dir('BLIP'), "BLIP", blip_commit_hash)
 
     if not is_installed("lpips"):
-        run_pip(f"install -r {os.path.join(repo_dir('CodeFormer'), 'requirements.txt')}{f' --index-url {index_url}' if index_url!='' else ''}", "requirements for CodeFormer")
+        run_pip(f"install -r {os.path.join(repo_dir('CodeFormer'), 'requirements.txt')}", "requirements for CodeFormer")
 
-    run_pip(f"install -r {requirements_file}{f' --index-url {index_url}' if index_url!='' else ''}", "requirements for Web UI")
+    run_pip(f"install -r {requirements_file}", "requirements for Web UI")
 
     sys.argv += args
 
-- 
cgit v1.2.3


From a13af34b902bebc5df9509228380206a01f1245b Mon Sep 17 00:00:00 2001
From: githublsx <xiaolinshen@outlook.com>
Date: Thu, 13 Oct 2022 20:05:07 -0700
Subject: Set to -1 when seed input is none

---
 modules/processing.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/processing.py b/modules/processing.py
index a75b9f84..7e2a416d 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -140,7 +140,7 @@ class Processed:
         self.sampler_noise_scheduler_override = p.sampler_noise_scheduler_override
         self.prompt = self.prompt if type(self.prompt) != list else self.prompt[0]
         self.negative_prompt = self.negative_prompt if type(self.negative_prompt) != list else self.negative_prompt[0]
-        self.seed = int(self.seed if type(self.seed) != list else self.seed[0])
+        self.seed = int(self.seed if type(self.seed) != list else self.seed[0]) if self.seed is not None else -1
         self.subseed = int(self.subseed if type(self.subseed) != list else self.subseed[0]) if self.subseed is not None else -1
 
         self.all_prompts = all_prompts or [self.prompt]
-- 
cgit v1.2.3


From c24df4b486a48c60f48276f7760a9acb4a13e22d Mon Sep 17 00:00:00 2001
From: CookieHCl <nhc7502@snu.ac.kr>
Date: Sat, 15 Oct 2022 03:26:36 +0900
Subject: Disable compiling deepbooru model

This is only necessary when you have to train,
and compiling model produces warning.
---
 modules/deepbooru.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index f34f3788..4ad334a1 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -102,7 +102,7 @@ def get_deepbooru_tags_model():
 
     tags = dd.project.load_tags_from_project(model_path)
     model = dd.project.load_model_from_project(
-        model_path, compile_model=True
+        model_path, compile_model=False
     )
     return model, tags
 
-- 
cgit v1.2.3


From f756bc540a849039d88c19378419838fe87f15b0 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 15 Oct 2022 10:28:20 +0300
Subject: fix #2588 breaking launch.py (. . .)

---
 launch.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/launch.py b/launch.py
index 42072f33..537670a3 100644
--- a/launch.py
+++ b/launch.py
@@ -9,7 +9,7 @@ import platform
 dir_repos = "repositories"
 python = sys.executable
 git = os.environ.get('GIT', "git")
-index_url = os.environ.get('INDEX_URL',"")
+index_url = os.environ.get('INDEX_URL', "")
 
 
 def extract_arg(args, name):
@@ -58,7 +58,8 @@ def run_python(code, desc=None, errdesc=None):
 
 
 def run_pip(args, desc=None):
-    return run(f'"{python}" -m pip {args} --prefer-binary{f' --index-url {index_url}' if index_url!='' else ''}', desc=f"Installing {desc}", errdesc=f"Couldn't install {desc}")
+    index_url_line = f' --index-url {index_url}' if index_url != '' else ''
+    return run(f'"{python}" -m pip {args} --prefer-binary{index_url_line}', desc=f"Installing {desc}", errdesc=f"Couldn't install {desc}")
 
 
 def check_run_python(code):
-- 
cgit v1.2.3


From 6a4e84671016d38c10a55fedcdf09321dba737ae Mon Sep 17 00:00:00 2001
From: Daniel M <danielm-github@dnml.de>
Date: Fri, 14 Oct 2022 20:50:21 +0200
Subject: Fix prerequisites check in webui.sh

- Check the actually used `$python_cmd` and `$GIT` executables instead
  of the hardcoded ones
- Fix typo in comment
---
 webui.sh | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/webui.sh b/webui.sh
index 05ca497d..980c0aaf 100755
--- a/webui.sh
+++ b/webui.sh
@@ -82,8 +82,8 @@ then
     clone_dir="${PWD##*/}"
 fi
 
-# Check prequisites
-for preq in git python3
+# Check prerequisites
+for preq in "${GIT}" "${python_cmd}"
 do
     if ! hash "${preq}" &>/dev/null
     then
-- 
cgit v1.2.3