From 9fd457e21d6c809a69a1318f03d75f7b3e09b865 Mon Sep 17 00:00:00 2001
From: camenduru <54370274+camenduru@users.noreply.github.com>
Date: Thu, 15 Dec 2022 21:57:48 +0300
Subject: allow_credentials and allow_headers for api

from https://fastapi.tiangolo.com/tutorial/cors/
---
 webui.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

(limited to 'webui.py')

diff --git a/webui.py b/webui.py
index c2d0c6be..13a4d14a 100644
--- a/webui.py
+++ b/webui.py
@@ -90,11 +90,11 @@ def initialize():
 
 def setup_cors(app):
     if cmd_opts.cors_allow_origins and cmd_opts.cors_allow_origins_regex:
-        app.add_middleware(CORSMiddleware, allow_origins=cmd_opts.cors_allow_origins.split(','), allow_origin_regex=cmd_opts.cors_allow_origins_regex, allow_methods=['*'])
+        app.add_middleware(CORSMiddleware, allow_origins=cmd_opts.cors_allow_origins.split(','), allow_origin_regex=cmd_opts.cors_allow_origins_regex, allow_methods=['*'], allow_credentials=True, allow_headers=['*'])
     elif cmd_opts.cors_allow_origins:
-        app.add_middleware(CORSMiddleware, allow_origins=cmd_opts.cors_allow_origins.split(','), allow_methods=['*'])
+        app.add_middleware(CORSMiddleware, allow_origins=cmd_opts.cors_allow_origins.split(','), allow_methods=['*'], allow_credentials=True, allow_headers=['*'])
     elif cmd_opts.cors_allow_origins_regex:
-        app.add_middleware(CORSMiddleware, allow_origin_regex=cmd_opts.cors_allow_origins_regex, allow_methods=['*'])
+        app.add_middleware(CORSMiddleware, allow_origin_regex=cmd_opts.cors_allow_origins_regex, allow_methods=['*'], allow_credentials=True, allow_headers=['*'])
 
 
 def create_api(app):
-- 
cgit v1.2.3


From 2d5a5076bb2a0c05cc27d75a1bcadab7f32a46d0 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 3 Jan 2023 18:38:21 +0300
Subject: Make it so that upscalers are not repeated when restarting UI.

---
 modules/modelloader.py | 20 ++++++++++++++++++++
 webui.py               | 14 +++++++-------
 2 files changed, 27 insertions(+), 7 deletions(-)

(limited to 'webui.py')

diff --git a/modules/modelloader.py b/modules/modelloader.py
index e647f6fa..6a1a7ac8 100644
--- a/modules/modelloader.py
+++ b/modules/modelloader.py
@@ -123,6 +123,23 @@ def move_files(src_path: str, dest_path: str, ext_filter: str = None):
         pass
 
 
+builtin_upscaler_classes = []
+forbidden_upscaler_classes = set()
+
+
+def list_builtin_upscalers():
+    load_upscalers()
+
+    builtin_upscaler_classes.clear()
+    builtin_upscaler_classes.extend(Upscaler.__subclasses__())
+
+
+def forbid_loaded_nonbuiltin_upscalers():
+    for cls in Upscaler.__subclasses__():
+        if cls not in builtin_upscaler_classes:
+            forbidden_upscaler_classes.add(cls)
+
+
 def load_upscalers():
     # 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__
@@ -139,6 +156,9 @@ def load_upscalers():
     datas = []
     commandline_options = vars(shared.cmd_opts)
     for cls in Upscaler.__subclasses__():
+        if cls in forbidden_upscaler_classes:
+            continue
+
         name = cls.__name__
         cmd_name = f"{name.lower().replace('upscaler', '')}_models_path"
         scaler = cls(commandline_options.get(cmd_name, None))
diff --git a/webui.py b/webui.py
index 3aee8792..c7d55a97 100644
--- a/webui.py
+++ b/webui.py
@@ -1,4 +1,5 @@
 import os
+import sys
 import threading
 import time
 import importlib
@@ -55,8 +56,8 @@ def initialize():
     gfpgan.setup_model(cmd_opts.gfpgan_models_path)
     shared.face_restorers.append(modules.face_restoration.FaceRestoration())
 
+    modelloader.list_builtin_upscalers()
     modules.scripts.load_scripts()
-
     modelloader.load_upscalers()
 
     modules.sd_vae.refresh_vae_list()
@@ -169,23 +170,22 @@ def webui():
         modules.script_callbacks.app_started_callback(shared.demo, app)
 
         wait_on_server(shared.demo)
+        print('Restarting UI...')
 
         sd_samplers.set_samplers()
 
-        print('Reloading extensions')
         extensions.list_extensions()
 
         localization.list_localizations(cmd_opts.localizations_dir)
 
-        print('Reloading custom scripts')
+        modelloader.forbid_loaded_nonbuiltin_upscalers()
         modules.scripts.reload_scripts()
         modelloader.load_upscalers()
 
-        print('Reloading modules: modules.ui')
-        importlib.reload(modules.ui)
-        print('Refreshing Model List')
+        for module in [module for name, module in sys.modules.items() if name.startswith("modules.ui")]:
+            importlib.reload(module)
+
         modules.sd_models.list_models()
-        print('Restarting Gradio')
 
 
 if __name__ == "__main__":
-- 
cgit v1.2.3


From 02d7abf5141431b9a3a8a189bb3136c71abd5e79 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 4 Jan 2023 12:35:07 +0300
Subject: helpful error message when trying to load 2.0 without config failing
 to load model weights from settings won't break generation for currently
 loaded model anymore

---
 modules/errors.py    | 25 +++++++++++++++++++++++--
 modules/sd_models.py | 26 ++++++++++++++++++--------
 modules/shared.py    |  9 +++++++--
 webui.py             | 12 ++++++++++--
 4 files changed, 58 insertions(+), 14 deletions(-)

(limited to 'webui.py')

diff --git a/modules/errors.py b/modules/errors.py
index 372dc51a..a668c014 100644
--- a/modules/errors.py
+++ b/modules/errors.py
@@ -2,9 +2,30 @@ import sys
 import traceback
 
 
+def print_error_explanation(message):
+    lines = message.strip().split("\n")
+    max_len = max([len(x) for x in lines])
+
+    print('=' * max_len, file=sys.stderr)
+    for line in lines:
+        print(line, file=sys.stderr)
+    print('=' * max_len, file=sys.stderr)
+
+
+def display(e: Exception, task):
+    print(f"{task or 'error'}: {type(e).__name__}", file=sys.stderr)
+    print(traceback.format_exc(), file=sys.stderr)
+
+    message = str(e)
+    if "copying a param with shape torch.Size([640, 1024]) from checkpoint, the shape in current model is torch.Size([640, 768])" in message:
+        print_error_explanation("""
+The most likely cause of this is you are trying to load Stable Diffusion 2.0 model without specifying its connfig file.
+See https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#stable-diffusion-20 for how to solve this.
+        """)
+
+
 def run(code, task):
     try:
         code()
     except Exception as e:
-        print(f"{task}: {type(e).__name__}", file=sys.stderr)
-        print(traceback.format_exc(), file=sys.stderr)
+        display(task, e)
diff --git a/modules/sd_models.py b/modules/sd_models.py
index b98b05fc..6846b74a 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -278,6 +278,7 @@ def enable_midas_autodownload():
 
     midas.api.load_model = load_model_wrapper
 
+
 def load_model(checkpoint_info=None):
     from modules import lowvram, sd_hijack
     checkpoint_info = checkpoint_info or select_checkpoint()
@@ -312,6 +313,7 @@ def load_model(checkpoint_info=None):
         sd_config.model.params.unet_config.params.use_fp16 = False
 
     sd_model = instantiate_from_config(sd_config.model)
+
     load_model_weights(sd_model, checkpoint_info)
 
     if shared.cmd_opts.lowvram or shared.cmd_opts.medvram:
@@ -336,10 +338,12 @@ def load_model(checkpoint_info=None):
 def reload_model_weights(sd_model=None, info=None):
     from modules import lowvram, devices, sd_hijack
     checkpoint_info = info or select_checkpoint()
- 
+
     if not sd_model:
         sd_model = shared.sd_model
 
+    current_checkpoint_info = sd_model.sd_checkpoint_info
+
     if sd_model.sd_model_checkpoint == checkpoint_info.filename:
         return
 
@@ -356,13 +360,19 @@ def reload_model_weights(sd_model=None, info=None):
 
     sd_hijack.model_hijack.undo_hijack(sd_model)
 
-    load_model_weights(sd_model, checkpoint_info)
-
-    sd_hijack.model_hijack.hijack(sd_model)
-    script_callbacks.model_loaded_callback(sd_model)
-
-    if not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram:
-        sd_model.to(devices.device)
+    try:
+        load_model_weights(sd_model, checkpoint_info)
+    except Exception as e:
+        print("Failed to load checkpoint, restoring previous")
+        load_model_weights(sd_model, current_checkpoint_info)
+        raise
+    finally:
+        sd_hijack.model_hijack.hijack(sd_model)
+        script_callbacks.model_loaded_callback(sd_model)
+
+        if not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram:
+            sd_model.to(devices.device)
 
     print("Weights loaded.")
+
     return sd_model
diff --git a/modules/shared.py b/modules/shared.py
index 23657a93..7588c47b 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -14,7 +14,7 @@ import modules.interrogate
 import modules.memmon
 import modules.styles
 import modules.devices as devices
-from modules import localization, sd_vae, extensions, script_loading
+from modules import localization, sd_vae, extensions, script_loading, errors
 from modules.paths import models_path, script_path, sd_path
 
 
@@ -494,7 +494,12 @@ class Options:
             return False
 
         if self.data_labels[key].onchange is not None:
-            self.data_labels[key].onchange()
+            try:
+                self.data_labels[key].onchange()
+            except Exception as e:
+                errors.display(e, f"changing setting {key} to {value}")
+                setattr(self, key, oldval)
+                return False
 
         return True
 
diff --git a/webui.py b/webui.py
index c7d55a97..13375e71 100644
--- a/webui.py
+++ b/webui.py
@@ -9,7 +9,7 @@ from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.middleware.gzip import GZipMiddleware
 
-from modules import import_hook
+from modules import import_hook, errors
 from modules.call_queue import wrap_queued_call, queue_lock, wrap_gradio_gpu_call
 from modules.paths import script_path
 
@@ -61,7 +61,15 @@ def initialize():
     modelloader.load_upscalers()
 
     modules.sd_vae.refresh_vae_list()
-    modules.sd_models.load_model()
+
+    try:
+        modules.sd_models.load_model()
+    except Exception as e:
+        errors.display(e, "loading stable diffusion model")
+        print("", file=sys.stderr)
+        print("Stable diffusion model failed to load, exiting", file=sys.stderr)
+        exit(1)
+
     shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights()))
     shared.opts.onchange("sd_vae", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)
     shared.opts.onchange("sd_vae_as_default", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)
-- 
cgit v1.2.3


From 8111b5569d07c7ac3b695e28171aede728b4ae56 Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Tue, 3 Jan 2023 20:43:05 -0500
Subject: Add support for PyTorch nightly and local builds

---
 modules/devices.py | 28 +++++++++++++++++++++++-----
 webui.py           |  7 ++++++-
 2 files changed, 29 insertions(+), 6 deletions(-)

(limited to 'webui.py')

diff --git a/modules/devices.py b/modules/devices.py
index 800510b7..caeb0276 100644
--- a/modules/devices.py
+++ b/modules/devices.py
@@ -133,8 +133,26 @@ def numpy_fix(self, *args, **kwargs):
     return orig_tensor_numpy(self, *args, **kwargs)
 
 
-# PyTorch 1.13 doesn't need these fixes but unfortunately is slower and has regressions that prevent training from working
-if has_mps() and version.parse(torch.__version__) < version.parse("1.13"):
-    torch.Tensor.to = tensor_to_fix
-    torch.nn.functional.layer_norm = layer_norm_fix
-    torch.Tensor.numpy = numpy_fix
+# MPS workaround for https://github.com/pytorch/pytorch/issues/89784
+orig_cumsum = torch.cumsum
+orig_Tensor_cumsum = torch.Tensor.cumsum
+def cumsum_fix(input, cumsum_func, *args, **kwargs):
+    if input.device.type == 'mps':
+        output_dtype = kwargs.get('dtype', input.dtype)
+        if any(output_dtype == broken_dtype for broken_dtype in [torch.bool, torch.int8, torch.int16, torch.int64]):
+            return cumsum_func(input.cpu(), *args, **kwargs).to(input.device)
+    return cumsum_func(input, *args, **kwargs)
+
+
+if has_mps():
+    if version.parse(torch.__version__) < version.parse("1.13"):
+        # PyTorch 1.13 doesn't need these fixes but unfortunately is slower and has regressions that prevent training from working
+        torch.Tensor.to = tensor_to_fix
+        torch.nn.functional.layer_norm = layer_norm_fix
+        torch.Tensor.numpy = numpy_fix
+    elif version.parse(torch.__version__) > version.parse("1.13.1"):
+        if not torch.Tensor([1,2]).to(torch.device("mps")).equal(torch.Tensor([1,1]).to(torch.device("mps")).cumsum(0, dtype=torch.int16)):
+            torch.cumsum = lambda input, *args, **kwargs: ( cumsum_fix(input, orig_cumsum, *args, **kwargs) )
+            torch.Tensor.cumsum = lambda self, *args, **kwargs: ( cumsum_fix(self, orig_Tensor_cumsum, *args, **kwargs) )
+        orig_narrow = torch.narrow
+        torch.narrow = lambda *args, **kwargs: ( orig_narrow(*args, **kwargs).clone() )
diff --git a/webui.py b/webui.py
index 13375e71..ddfaea95 100644
--- a/webui.py
+++ b/webui.py
@@ -4,7 +4,7 @@ import threading
 import time
 import importlib
 import signal
-import threading
+import re
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.middleware.gzip import GZipMiddleware
@@ -13,6 +13,11 @@ from modules import import_hook, errors
 from modules.call_queue import wrap_queued_call, queue_lock, wrap_gradio_gpu_call
 from modules.paths import script_path
 
+import torch
+# Truncate version number of nightly/local build of PyTorch to not cause exceptions with CodeFormer or Safetensors
+if ".dev" in torch.__version__ or "+git" in torch.__version__:
+    torch.__version__ = re.search(r'[\d.]+', torch.__version__).group(0)
+
 from modules import shared, devices, sd_samplers, upscaler, extensions, localization, ui_tempdir
 import modules.codeformer_model as codeformer
 import modules.extras
-- 
cgit v1.2.3


From 65ed4421e609dda3112f236c13e4db14caa71364 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 6 Jan 2023 13:55:50 +0300
Subject: add callback for when the script is unloaded

---
 modules/script_callbacks.py | 18 +++++++++++++++++-
 webui.py                    |  2 ++
 2 files changed, 19 insertions(+), 1 deletion(-)

(limited to 'webui.py')

diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py
index de69fd9f..608c5300 100644
--- a/modules/script_callbacks.py
+++ b/modules/script_callbacks.py
@@ -71,6 +71,7 @@ callback_map = dict(
     callbacks_before_component=[],
     callbacks_after_component=[],
     callbacks_image_grid=[],
+    callbacks_script_unloaded=[],
 )
 
 
@@ -171,6 +172,14 @@ def image_grid_callback(params: ImageGridLoopParams):
             report_exception(c, 'image_grid')
 
 
+def script_unloaded_callback():
+    for c in reversed(callback_map['callbacks_script_unloaded']):
+        try:
+            c.callback()
+        except Exception:
+            report_exception(c, 'script_unloaded')
+
+
 def add_callback(callbacks, fun):
     stack = [x for x in inspect.stack() if x.filename != __file__]
     filename = stack[0].filename if len(stack) > 0 else 'unknown file'
@@ -202,7 +211,7 @@ def on_app_started(callback):
 
 def on_model_loaded(callback):
     """register a function to be called when the stable diffusion model is created; the model is
-    passed as an argument"""
+    passed as an argument; this function is also called when the script is reloaded. """
     add_callback(callback_map['callbacks_model_loaded'], callback)
 
 
@@ -279,3 +288,10 @@ def on_image_grid(callback):
        - params: ImageGridLoopParams - parameters to be used for grid creation. Can be modified.
     """
     add_callback(callback_map['callbacks_image_grid'], callback)
+
+
+def on_script_unloaded(callback):
+    """register a function to be called before the script is unloaded. Any hooks/hijacks/monkeying about that
+    the script did should be reverted here"""
+
+    add_callback(callback_map['callbacks_script_unloaded'], callback)
diff --git a/webui.py b/webui.py
index ff6eb6eb..733a06b5 100644
--- a/webui.py
+++ b/webui.py
@@ -187,12 +187,14 @@ def webui():
 
         sd_samplers.set_samplers()
 
+        modules.script_callbacks.script_unloaded_callback()
         extensions.list_extensions()
 
         localization.list_localizations(cmd_opts.localizations_dir)
 
         modelloader.forbid_loaded_nonbuiltin_upscalers()
         modules.scripts.reload_scripts()
+        modules.script_callbacks.model_loaded_callback(shared.sd_model)
         modelloader.load_upscalers()
 
         for module in [module for name, module in sys.modules.items() if name.startswith("modules.ui")]:
-- 
cgit v1.2.3


From 5e6566324bba20554bcc04f3dda798e560397f38 Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Fri, 6 Jan 2023 07:06:26 -0500
Subject: Always end version number with a digit

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

(limited to 'webui.py')

diff --git a/webui.py b/webui.py
index 733a06b5..8737e593 100644
--- a/webui.py
+++ b/webui.py
@@ -16,7 +16,7 @@ from modules.paths import script_path
 import torch
 # Truncate version number of nightly/local build of PyTorch to not cause exceptions with CodeFormer or Safetensors
 if ".dev" in torch.__version__ or "+git" in torch.__version__:
-    torch.__version__ = re.search(r'[\d.]+', torch.__version__).group(0)
+    torch.__version__ = re.search(r'[\d.]+[\d]', torch.__version__).group(0)
 
 from modules import shared, devices, sd_samplers, upscaler, extensions, localization, ui_tempdir
 import modules.codeformer_model as codeformer
-- 
cgit v1.2.3


From 1fbb6f9ebe48326a3b12ecf611105dbc4a46891e Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 9 Jan 2023 23:35:40 +0300
Subject: make a dropdown for prompt template selection

---
 modules/hypernetworks/hypernetwork.py          |  7 ++++--
 modules/shared.py                              |  1 +
 modules/textual_inversion/textual_inversion.py | 35 ++++++++++++++++++++------
 modules/ui.py                                  | 11 ++++++--
 webui.py                                       |  3 +++
 5 files changed, 45 insertions(+), 12 deletions(-)

(limited to 'webui.py')

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 32c67ccc..ea3f1db9 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -24,6 +24,7 @@ from statistics import stdev, mean
 
 optimizer_dict = {optim_name : cls_obj for optim_name, cls_obj in inspect.getmembers(torch.optim, inspect.isclass) if optim_name != "Optimizer"}
 
+
 class HypernetworkModule(torch.nn.Module):
     multiplier = 1.0
     activation_dict = {
@@ -403,13 +404,15 @@ def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None,
     shared.reload_hypernetworks()
 
 
-def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, 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 train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_hypernetwork_every, template_filename, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
     # images allows training previews to have infotext. Importing it at the top causes a circular import problem.
     from modules import images
 
     save_hypernetwork_every = save_hypernetwork_every or 0
     create_image_every = create_image_every or 0
-    textual_inversion.validate_train_inputs(hypernetwork_name, learn_rate, batch_size, gradient_step, data_root, template_file, steps, save_hypernetwork_every, create_image_every, log_directory, name="hypernetwork")
+    template_file = textual_inversion.textual_inversion_templates.get(template_filename, None)
+    textual_inversion.validate_train_inputs(hypernetwork_name, learn_rate, batch_size, gradient_step, data_root, template_file, template_filename, steps, save_hypernetwork_every, create_image_every, log_directory, name="hypernetwork")
+    template_file = template_file.path
 
     path = shared.hypernetworks.get(hypernetwork_name, None)
     shared.loaded_hypernetwork = Hypernetwork()
diff --git a/modules/shared.py b/modules/shared.py
index a1e10201..aa37c8ce 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -33,6 +33,7 @@ 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("--textual-inversion-templates-dir", type=str, default=os.path.join(script_path, 'textual_inversion_templates'), help="directory with textual inversion templates")
 parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_path, 'hypernetworks'), help="hypernetwork directory")
 parser.add_argument("--localizations-dir", type=str, default=os.path.join(script_path, 'localizations'), help="localizations directory")
 parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui")
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 14be2c96..5420903f 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -2,6 +2,7 @@ import os
 import sys
 import traceback
 import inspect
+from collections import namedtuple
 
 import torch
 import tqdm
@@ -15,12 +16,26 @@ from modules import shared, devices, sd_hijack, processing, sd_models, images, s
 import modules.textual_inversion.dataset
 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,
-                                                       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
 from modules.textual_inversion.logging import save_settings_to_file
 
 
+TextualInversionTemplate = namedtuple("TextualInversionTemplate", ["name", "path"])
+textual_inversion_templates = {}
+
+
+def list_textual_inversion_templates():
+    textual_inversion_templates.clear()
+
+    for root, dirs, fns in os.walk(shared.cmd_opts.textual_inversion_templates_dir):
+        for fn in fns:
+            path = os.path.join(root, fn)
+
+            textual_inversion_templates[fn] = TextualInversionTemplate(fn, path)
+
+    return textual_inversion_templates
+
+
 class Embedding:
     def __init__(self, vec, name, step=None):
         self.vec = vec
@@ -274,7 +289,7 @@ def write_loss(log_directory, filename, step, epoch_len, values):
         })
 
 
-def validate_train_inputs(model_name, learn_rate, batch_size, gradient_step, data_root, template_file, steps, save_model_every, create_image_every, log_directory, name="embedding"):
+def validate_train_inputs(model_name, learn_rate, batch_size, gradient_step, data_root, template_file, template_filename, steps, save_model_every, create_image_every, log_directory, name="embedding"):
     assert model_name, f"{name} not selected"
     assert learn_rate, "Learning rate is empty or 0"
     assert isinstance(batch_size, int), "Batch size must be integer"
@@ -284,8 +299,9 @@ def validate_train_inputs(model_name, learn_rate, batch_size, gradient_step, dat
     assert data_root, "Dataset directory is empty"
     assert os.path.isdir(data_root), "Dataset directory doesn't exist"
     assert os.listdir(data_root), "Dataset directory is empty"
-    assert template_file, "Prompt template file is empty"
-    assert os.path.isfile(template_file), "Prompt template file doesn't exist"
+    assert template_filename, "Prompt template file not selected"
+    assert template_file, f"Prompt template file {template_filename} not found"
+    assert os.path.isfile(template_file.path), f"Prompt template file {template_filename} doesn't exist"
     assert steps, "Max steps is empty or 0"
     assert isinstance(steps, int), "Max steps must be integer"
     assert steps > 0, "Max steps must be positive"
@@ -296,10 +312,13 @@ def validate_train_inputs(model_name, learn_rate, batch_size, gradient_step, dat
     if save_model_every or create_image_every:
         assert log_directory, "Log directory is empty"
 
-def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, 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, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_embedding_every, template_filename, 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):
     save_embedding_every = save_embedding_every or 0
     create_image_every = create_image_every or 0
-    validate_train_inputs(embedding_name, learn_rate, batch_size, gradient_step, data_root, template_file, steps, save_embedding_every, create_image_every, log_directory, name="embedding")
+    template_file = textual_inversion_templates.get(template_filename, None)
+    validate_train_inputs(embedding_name, learn_rate, batch_size, gradient_step, data_root, template_file, template_filename, steps, save_embedding_every, create_image_every, log_directory, name="embedding")
+    template_file = template_file.path
 
     shared.state.job = "train-embedding"
     shared.state.textinfo = "Initializing textual inversion training..."
diff --git a/modules/ui.py b/modules/ui.py
index ddfe1b1a..b6079aec 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -37,7 +37,7 @@ from modules import prompt_parser
 from modules.images import save_image
 from modules.sd_hijack import model_hijack
 from modules.sd_samplers import samplers, samplers_for_img2img
-import modules.textual_inversion.ui
+from modules.textual_inversion import textual_inversion
 import modules.hypernetworks.ui
 from modules.generation_parameters_copypaste import image_from_url_text
 
@@ -1322,6 +1322,9 @@ def create_ui():
                         outputs=[process_focal_crop_row],
                     )
 
+                def get_textual_inversion_template_names():
+                    return sorted([x for x in textual_inversion.textual_inversion_templates])
+
                 with gr.Tab(label="Train"):
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images <a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\" style=\"font-weight:bold;\">[wiki]</a></p>")
                     with FormRow():
@@ -1345,7 +1348,11 @@ def create_ui():
 
                     dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images", elem_id="train_dataset_directory")
                     log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion", elem_id="train_log_directory")
-                    template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"), elem_id="train_template_file")
+
+                    with FormRow():
+                        template_file = gr.Dropdown(label='Prompt template', value="style_filewords.txt", elem_id="train_template_file", choices=get_textual_inversion_template_names())
+                        create_refresh_button(template_file, textual_inversion.list_textual_inversion_templates, lambda: {"choices": get_textual_inversion_template_names()}, "refrsh_train_template_file")
+
                     training_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_training_width")
                     training_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_training_height")
                     varsize = gr.Checkbox(label="Do not resize images", value=False, elem_id="train_varsize")
diff --git a/webui.py b/webui.py
index 8737e593..47d372c7 100644
--- a/webui.py
+++ b/webui.py
@@ -33,6 +33,7 @@ import modules.sd_models
 import modules.sd_vae
 import modules.txt2img
 import modules.script_callbacks
+import modules.textual_inversion.textual_inversion
 
 import modules.ui
 from modules import modelloader
@@ -67,6 +68,8 @@ def initialize():
 
     modules.sd_vae.refresh_vae_list()
 
+    modules.textual_inversion.textual_inversion.list_textual_inversion_templates()
+
     try:
         modules.sd_models.load_model()
     except Exception as e:
-- 
cgit v1.2.3


From a95f1353089bdeaccd7c266b40cdd79efedfe632 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 14 Jan 2023 09:56:59 +0300
Subject: change hash to sha256

---
 .gitignore                                     |   1 +
 modules/api/api.py                             |   2 +-
 modules/api/models.py                          |   3 +-
 modules/hashes.py                              |  72 +++++++++++++++
 modules/hypernetworks/hypernetwork.py          |   4 +-
 modules/sd_models.py                           | 116 ++++++++++++++++---------
 modules/shared.py                              |   2 +-
 modules/textual_inversion/textual_inversion.py |   6 +-
 webui.py                                       |   2 +
 9 files changed, 158 insertions(+), 50 deletions(-)
 create mode 100644 modules/hashes.py

(limited to 'webui.py')

diff --git a/.gitignore b/.gitignore
index 21fa26a7..0b1d17ca 100644
--- a/.gitignore
+++ b/.gitignore
@@ -32,3 +32,4 @@ notification.mp3
 /extensions
 /test/stdout.txt
 /test/stderr.txt
+/cache.json
diff --git a/modules/api/api.py b/modules/api/api.py
index 5767ba90..9814bbc2 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -371,7 +371,7 @@ class Api:
         return upscalers
 
     def get_sd_models(self):
-        return [{"title":x.title, "model_name":x.model_name, "hash":x.hash, "filename": x.filename, "config": find_checkpoint_config(x)} for x in checkpoints_list.values()]
+        return [{"title": x.title, "model_name": x.model_name, "hash": x.shorthash, "sha256": x.sha256, "filename": x.filename, "config": find_checkpoint_config(x)} for x in checkpoints_list.values()]
 
     def get_hypernetworks(self):
         return [{"name": name, "path": shared.hypernetworks[name]} for name in shared.hypernetworks]
diff --git a/modules/api/models.py b/modules/api/models.py
index c78095ca..1eb1fcf1 100644
--- a/modules/api/models.py
+++ b/modules/api/models.py
@@ -224,7 +224,8 @@ class UpscalerItem(BaseModel):
 class SDModelItem(BaseModel):
     title: str = Field(title="Title")
     model_name: str = Field(title="Model Name")
-    hash: str = Field(title="Hash")
+    hash: Optional[str] = Field(title="Short hash")
+    sha256: Optional[str] = Field(title="sha256 hash")
     filename: str = Field(title="Filename")
     config: str = Field(title="Config file")
 
diff --git a/modules/hashes.py b/modules/hashes.py
new file mode 100644
index 00000000..ebfbd90c
--- /dev/null
+++ b/modules/hashes.py
@@ -0,0 +1,72 @@
+import hashlib
+import json
+import os.path
+
+import filelock
+
+
+cache_filename = "cache.json"
+cache_data = None
+
+
+def dump_cache():
+    with filelock.FileLock(cache_filename+".lock"):
+        with open(cache_filename, "w", encoding="utf8") as file:
+            json.dump(cache_data, file, indent=4)
+
+
+def cache(subsection):
+    global cache_data
+
+    if cache_data is None:
+        with filelock.FileLock(cache_filename+".lock"):
+            if not os.path.isfile(cache_filename):
+                cache_data = {}
+            else:
+                with open(cache_filename, "r", encoding="utf8") as file:
+                    cache_data = json.load(file)
+
+    s = cache_data.get(subsection, {})
+    cache_data[subsection] = s
+
+    return s
+
+
+def calculate_sha256(filename):
+    hash_sha256 = hashlib.sha256()
+
+    with open(filename, "rb") as f:
+        for chunk in iter(lambda: f.read(4096), b""):
+            hash_sha256.update(chunk)
+
+    return hash_sha256.hexdigest()
+
+
+def sha256(filename, title):
+    hashes = cache("hashes")
+    ondisk_mtime = os.path.getmtime(filename)
+
+    if title in hashes:
+        cached_sha256 = hashes[title].get("sha256", None)
+        cached_mtime = hashes[title].get("mtime", 0)
+
+        if ondisk_mtime <= cached_mtime and cached_sha256 is not None:
+            return cached_sha256
+
+    print(f"Calculating sha256 for {filename}: ", end='')
+    sha256_value = calculate_sha256(filename)
+    print(f"{sha256_value}")
+
+    hashes[title] = {
+        "mtime": ondisk_mtime,
+        "sha256": sha256_value,
+    }
+
+    dump_cache()
+
+    return sha256_value
+
+
+
+
+
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 83cbb4f0..9b5f2e79 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -509,7 +509,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step,
 
     if shared.opts.save_training_settings_to_txt:
         saved_params = dict(
-            model_name=checkpoint.model_name, model_hash=checkpoint.hash, num_of_dataset_images=len(ds),
+            model_name=checkpoint.model_name, model_hash=checkpoint.shorthash, num_of_dataset_images=len(ds),
             **{field: getattr(hypernetwork, field) for field in ['layer_structure', 'activation_func', 'weight_init', 'add_layer_norm', 'use_dropout', ]}
         )
         logging.save_settings_to_file(log_directory, {**saved_params, **locals()})
@@ -737,7 +737,7 @@ def save_hypernetwork(hypernetwork, checkpoint, hypernetwork_name, filename):
     old_sd_checkpoint = hypernetwork.sd_checkpoint if hasattr(hypernetwork, "sd_checkpoint") else None
     old_sd_checkpoint_name = hypernetwork.sd_checkpoint_name if hasattr(hypernetwork, "sd_checkpoint_name") else None
     try:
-        hypernetwork.sd_checkpoint = checkpoint.hash
+        hypernetwork.sd_checkpoint = checkpoint.shorthash
         hypernetwork.sd_checkpoint_name = checkpoint.model_name
         hypernetwork.name = hypernetwork_name
         hypernetwork.save(filename)
diff --git a/modules/sd_models.py b/modules/sd_models.py
index c466f273..7babb9ae 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -14,17 +14,56 @@ import ldm.modules.midas as midas
 
 from ldm.util import instantiate_from_config
 
-from modules import shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors
+from modules import shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes
 from modules.paths import models_path
 from modules.sd_hijack_inpainting import do_inpainting_hijack, should_hijack_inpainting
 
 model_dir = "Stable-diffusion"
 model_path = os.path.abspath(os.path.join(models_path, model_dir))
 
-CheckpointInfo = namedtuple("CheckpointInfo", ['filename', 'title', 'hash', 'model_name'])
 checkpoints_list = {}
+checkpoint_alisases = {}
 checkpoints_loaded = collections.OrderedDict()
 
+
+class CheckpointInfo:
+    def __init__(self, filename):
+        self.filename = filename
+        abspath = os.path.abspath(filename)
+
+        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:
+            name = os.path.basename(filename)
+
+        if name.startswith("\\") or name.startswith("/"):
+            name = name[1:]
+
+        self.title = name
+        self.model_name = os.path.splitext(name.replace("/", "_").replace("\\", "_"))[0]
+        self.hash = model_hash(filename)
+        self.ids = [self.hash, self.model_name, self.title, f'{name} [{self.hash}]']
+        self.shorthash = None
+        self.sha256 = None
+
+    def register(self):
+        checkpoints_list[self.title] = self
+        for id in self.ids:
+            checkpoint_alisases[id] = self
+
+    def calculate_shorthash(self):
+        self.sha256 = hashes.sha256(self.filename, self.title)
+        self.shorthash = self.sha256[0:10]
+
+        if self.shorthash not in self.ids:
+            self.ids += [self.shorthash, self.sha256]
+            self.register()
+
+        return self.shorthash
+
+
 try:
     # this silences the annoying "Some weights of the model checkpoint were not used when initializing..." message at start.
 
@@ -43,10 +82,14 @@ def setup_model():
     enable_midas_autodownload()
 
 
-def checkpoint_tiles(): 
-    convert = lambda name: int(name) if name.isdigit() else name.lower() 
-    alphanumeric_key = lambda key: [convert(c) for c in re.split('([0-9]+)', key)] 
-    return sorted([x.title for x in checkpoints_list.values()], key = alphanumeric_key)
+def checkpoint_tiles():
+    def convert(name):
+        return int(name) if name.isdigit() else name.lower()
+
+    def alphanumeric_key(key):
+        return [convert(c) for c in re.split('([0-9]+)', key)]
+
+    return sorted([x.title for x in checkpoints_list.values()], key=alphanumeric_key)
 
 
 def find_checkpoint_config(info):
@@ -62,48 +105,38 @@ def find_checkpoint_config(info):
 
 def list_models():
     checkpoints_list.clear()
+    checkpoint_alisases.clear()
     model_list = modelloader.load_models(model_path=model_path, command_path=shared.cmd_opts.ckpt_dir, ext_filter=[".ckpt", ".safetensors"], ext_blacklist=[".vae.safetensors"])
 
-    def modeltitle(path, shorthash):
-        abspath = os.path.abspath(path)
-
-        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:
-            name = os.path.basename(path)
-
-        if name.startswith("\\") or name.startswith("/"):
-            name = name[1:]
-
-        shortname = os.path.splitext(name.replace("/", "_").replace("\\", "_"))[0]
-
-        return f'{name} [{shorthash}]', shortname
-
     cmd_ckpt = shared.cmd_opts.ckpt
     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)
-        shared.opts.data['sd_model_checkpoint'] = title
+        checkpoint_info = CheckpointInfo(cmd_ckpt)
+        checkpoint_info.register()
+
+        shared.opts.data['sd_model_checkpoint'] = checkpoint_info.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)
+        checkpoint_info = CheckpointInfo(filename)
+        checkpoint_info.register()
+
 
-        checkpoints_list[title] = CheckpointInfo(filename, title, h, short_model_name)
+def get_closet_checkpoint_match(search_string):
+    checkpoint_info = checkpoint_alisases.get(search_string, None)
+    if checkpoint_info is not None:
+        return
 
+    found = sorted([info for info in checkpoints_list.values() if search_string in info.title], key=lambda x: len(x.title))
+    if found:
+        return found[0]
 
-def get_closet_checkpoint_match(searchString):
-    applicable = sorted([info for info in checkpoints_list.values() if searchString in info.title], key = lambda x:len(x.title))
-    if len(applicable) > 0:
-        return applicable[0]
     return None
 
 
 def model_hash(filename):
+    """old hash that only looks at a small part of the file and is prone to collisions"""
+
     try:
         with open(filename, "rb") as file:
             import hashlib
@@ -119,7 +152,7 @@ def model_hash(filename):
 def select_checkpoint():
     model_checkpoint = shared.opts.sd_model_checkpoint
         
-    checkpoint_info = checkpoints_list.get(model_checkpoint, None)
+    checkpoint_info = checkpoint_alisases.get(model_checkpoint, None)
     if checkpoint_info is not None:
         return checkpoint_info
 
@@ -189,9 +222,8 @@ def read_state_dict(checkpoint_file, print_global_state=False, map_location=None
     return sd
 
 
-def load_model_weights(model, checkpoint_info, vae_file="auto"):
-    checkpoint_file = checkpoint_info.filename
-    sd_model_hash = checkpoint_info.hash
+def load_model_weights(model, checkpoint_info: CheckpointInfo, vae_file="auto"):
+    sd_model_hash = checkpoint_info.calculate_shorthash()
 
     cache_enabled = shared.opts.sd_checkpoint_cache > 0
 
@@ -201,9 +233,9 @@ def load_model_weights(model, checkpoint_info, vae_file="auto"):
         model.load_state_dict(checkpoints_loaded[checkpoint_info])
     else:
         # load from file
-        print(f"Loading weights [{sd_model_hash}] from {checkpoint_file}")
+        print(f"Loading weights [{sd_model_hash}] from {checkpoint_info.filename}")
 
-        sd = read_state_dict(checkpoint_file)
+        sd = read_state_dict(checkpoint_info.filename)
         model.load_state_dict(sd, strict=False)
         del sd
         
@@ -235,14 +267,14 @@ def load_model_weights(model, checkpoint_info, vae_file="auto"):
             checkpoints_loaded.popitem(last=False)  # LRU
 
     model.sd_model_hash = sd_model_hash
-    model.sd_model_checkpoint = checkpoint_file
+    model.sd_model_checkpoint = checkpoint_info.filename
     model.sd_checkpoint_info = checkpoint_info
 
     model.logvar = model.logvar.to(devices.device)  # fix for training
 
     sd_vae.delete_base_vae()
     sd_vae.clear_loaded_vae()
-    vae_file = sd_vae.resolve_vae(checkpoint_file, vae_file=vae_file)
+    vae_file = sd_vae.resolve_vae(checkpoint_info.filename, vae_file=vae_file)
     sd_vae.load_vae(model, vae_file)
 
 
diff --git a/modules/shared.py b/modules/shared.py
index b90ded52..d74c069d 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -428,7 +428,7 @@ 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_model_name_to_info": OptionInfo(False, "Add model name to generation information"),
+    "add_model_name_to_info": OptionInfo(True, "Add model name to generation information"),
     "disable_weights_auto_swap": OptionInfo(False, "When reading generation parameters from text into UI (from PNG info or pasted text), do not change the selected model/checkpoint."),
     "send_seed": OptionInfo(True, "Send seed when sending prompt or image to other interface"),
     "send_size": OptionInfo(True, "Send size when sending prompt or image to another interface"),
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 6939efcc..63935878 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -407,7 +407,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_
     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, cond_model=shared.sd_model.cond_stage_model, device=devices.device, template_file=template_file, batch_size=batch_size, gradient_step=gradient_step, shuffle_tags=shuffle_tags, tag_drop_out=tag_drop_out, latent_sampling_method=latent_sampling_method, varsize=varsize)
 
     if shared.opts.save_training_settings_to_txt:
-        save_settings_to_file(log_directory, {**dict(model_name=checkpoint.model_name, model_hash=checkpoint.hash, num_of_dataset_images=len(ds), num_vectors_per_token=len(embedding.vec)), **locals()})
+        save_settings_to_file(log_directory, {**dict(model_name=checkpoint.model_name, model_hash=checkpoint.shorthash, num_of_dataset_images=len(ds), num_vectors_per_token=len(embedding.vec)), **locals()})
 
     latent_sampling_method = ds.latent_sampling_method
 
@@ -584,7 +584,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_
 
                         checkpoint = sd_models.select_checkpoint()
                         footer_left = checkpoint.model_name
-                        footer_mid = '[{}]'.format(checkpoint.hash)
+                        footer_mid = '[{}]'.format(checkpoint.shorthash)
                         footer_right = '{}v {}s'.format(vectorSize, steps_done)
 
                         captioned_image = caption_image_overlay(image, title, footer_left, footer_mid, footer_right)
@@ -626,7 +626,7 @@ def save_embedding(embedding, optimizer, checkpoint, embedding_name, filename, r
     old_sd_checkpoint_name = embedding.sd_checkpoint_name if hasattr(embedding, "sd_checkpoint_name") else None
     old_cached_checksum = embedding.cached_checksum if hasattr(embedding, "cached_checksum") else None
     try:
-        embedding.sd_checkpoint = checkpoint.hash
+        embedding.sd_checkpoint = checkpoint.shorthash
         embedding.sd_checkpoint_name = checkpoint.model_name
         if remove_cached_checksum:
             embedding.cached_checksum = None
diff --git a/webui.py b/webui.py
index 47d372c7..1fff80da 100644
--- a/webui.py
+++ b/webui.py
@@ -78,6 +78,8 @@ def initialize():
         print("Stable diffusion model failed to load, exiting", file=sys.stderr)
         exit(1)
 
+    shared.opts.data["sd_model_checkpoint"] = shared.sd_model.sd_checkpoint_info.title
+
     shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights()))
     shared.opts.onchange("sd_vae", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)
     shared.opts.onchange("sd_vae_as_default", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)
-- 
cgit v1.2.3


From 6eb72fd13f34d94d5459290dd1a0bf0e9ddeda82 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 14 Jan 2023 13:38:10 +0300
Subject: bump gradio to 3.16.1

---
 modules/ui.py             | 13 ++++++-----
 requirements.txt          |  2 +-
 requirements_versions.txt |  2 +-
 style.css                 | 57 ++++++++++++++++++++++++++++++++---------------
 webui.py                  |  3 +--
 5 files changed, 49 insertions(+), 28 deletions(-)

(limited to 'webui.py')

diff --git a/modules/ui.py b/modules/ui.py
index e86a624b..202e84e5 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -605,7 +605,7 @@ def create_ui():
                 setup_progressbar(progressbar, txt2img_preview, 'txt2img')
 
         with gr.Row().style(equal_height=False):
-            with gr.Column(variant='panel', elem_id="txt2img_settings"):
+            with gr.Column(variant='compact', elem_id="txt2img_settings"):
                 for category in ordered_ui_categories():
                     if category == "sampler":
                         steps, sampler_index = create_sampler_and_steps_selection(samplers, "txt2img")
@@ -794,7 +794,7 @@ def create_ui():
                 setup_progressbar(progressbar, img2img_preview, 'img2img')
 
         with FormRow().style(equal_height=False):
-            with gr.Column(variant='panel', elem_id="img2img_settings"):
+            with gr.Column(variant='compact', elem_id="img2img_settings"):
                 with gr.Tabs(elem_id="mode_img2img"):
                     with gr.TabItem('img2img', id='img2img', elem_id="img2img_img2img_tab") as tab_img2img:
                         init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool="editor", image_mode="RGBA").style(height=480)
@@ -1026,7 +1026,7 @@ def create_ui():
 
     with gr.Blocks(analytics_enabled=False) as extras_interface:
         with gr.Row().style(equal_height=False):
-            with gr.Column(variant='panel'):
+            with gr.Column(variant='compact'):
                 with gr.Tabs(elem_id="mode_extras"):
                     with gr.TabItem('Single Image', elem_id="extras_single_tab"):
                         extras_image = gr.Image(label="Source", source="upload", interactive=True, type="pil", elem_id="extras_image")
@@ -1127,8 +1127,8 @@ def create_ui():
 
     with gr.Blocks(analytics_enabled=False) as modelmerger_interface:
         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.Column(variant='compact'):
+                gr.HTML(value="<p style='margin-bottom: 2.5em'>A merger of the two checkpoints will be generated in your <b>checkpoint</b> directory.</p>")
 
                 with FormRow():
                     primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)")
@@ -1150,7 +1150,8 @@ def create_ui():
 
                 config_source = gr.Radio(choices=["A, B or C", "B", "C", "Don't"], value="A, B or C", label="Copy config from", type="index", elem_id="modelmerger_config_method")
 
-                modelmerger_merge = gr.Button(elem_id="modelmerger_merge", value="Merge", variant='primary')
+                with gr.Row():
+                    modelmerger_merge = gr.Button(elem_id="modelmerger_merge", value="Merge", variant='primary')
 
             with gr.Column(variant='panel'):
                 submit_result = gr.Textbox(elem_id="modelmerger_result", show_label=False)
diff --git a/requirements.txt b/requirements.txt
index e1dbf8e5..6cdea781 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -5,7 +5,7 @@ fairscale==0.4.4
 fonts
 font-roboto
 gfpgan
-gradio==3.15.0
+gradio==3.16.1
 invisible-watermark
 numpy
 omegaconf
diff --git a/requirements_versions.txt b/requirements_versions.txt
index d2899292..cc06d2b4 100644
--- a/requirements_versions.txt
+++ b/requirements_versions.txt
@@ -3,7 +3,7 @@ transformers==4.19.2
 accelerate==0.12.0
 basicsr==1.4.2
 gfpgan==1.3.8
-gradio==3.15.0
+gradio==3.16.1
 numpy==1.23.3
 Pillow==9.4.0
 realesrgan==0.3.0
diff --git a/style.css b/style.css
index ffd6307f..14b15191 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;}
@@ -221,7 +221,10 @@ fieldset span.text-gray-500, .gr-block.gr-box span.text-gray-500,  label.block s
 
 .dark fieldset span.text-gray-500, .dark .gr-block.gr-box span.text-gray-500, .dark label.block span{
     background-color: rgb(31, 41, 55);
-    box-shadow: 6px 0 6px 0px rgb(31, 41, 55), -6px 0 6px 0px rgb(31, 41, 55);
+    box-shadow: none;
+    border: 1px solid rgba(128, 128, 128, 0.1);
+    border-radius: 6px;
+    padding: 0.1em 0.5em;
 }
 
 #txt2img_column_batch, #img2img_column_batch{
@@ -371,7 +374,7 @@ input[type="range"]{
     grid-area: tile;
 }
 
-.modalClose, 
+.modalClose,
 .modalZoom,
 .modalTileImage {
   color: white;
@@ -509,29 +512,20 @@ input[type="range"]{
 }
 
 #quicksettings > div{
-    border: none;
-    background: none;
-    flex: unset;
-    gap: 1em;
-}
-
-#quicksettings > div > div{
-    max-width: 32em;
+    max-width: 24em;
     min-width: 24em;
     padding: 0;
+    border: none;
+    box-shadow: none;
+    background: none;
 }
 
-#quicksettings > div > div > div > div > label > span {
+#quicksettings > div > div > div > label > span {
     position: relative;
     margin-right: 9em;
     margin-bottom: -1em;
 }
 
-#quicksettings > div > div > label > span {
-    position: relative;
-    margin-bottom: -1em;
-}
-
 canvas[key="mask"] {
     z-index: 12 !important;
     filter: invert();
@@ -666,7 +660,10 @@ footer {
     font-weight: bold;
 }
 
-#txt2img_checkboxes > div > div{
+#txt2img_checkboxes, #img2img_checkboxes{
+    margin-bottom: 0.5em;
+}
+#txt2img_checkboxes > div > div, #img2img_checkboxes > div > div{
     flex: 0;
     white-space: nowrap;
     min-width: auto;
@@ -676,6 +673,30 @@ footer {
     opacity: 0.5;
 }
 
+.gr-compact {
+    border: none;
+    padding-top: 1em;
+}
+
+.dark .gr-compact{
+    background-color: rgb(31 41 55 / var(--tw-bg-opacity));
+    margin-left: 0.8em;
+}
+
+.gr-compact > *{
+    margin-top: 0.5em !important;
+}
+
+.gr-compact .gr-block, .gr-compact .gr-form{
+    border: none;
+    box-shadow: none;
+}
+
+.gr-compact .gr-box{
+    border-radius: .5rem !important;
+    border-width: 1px !important;
+}
+
 /* The following handles localization for right-to-left (RTL) languages like Arabic.
 The rtl media type will only be activated by the logic in javascript/localization.js.
 If you change anything above, you need to make sure it is RTL compliant by just running
diff --git a/webui.py b/webui.py
index 1fff80da..84159515 100644
--- a/webui.py
+++ b/webui.py
@@ -157,7 +157,7 @@ def webui():
 
         shared.demo = modules.ui.create_ui()
 
-        app, local_url, share_url = shared.demo.queue(default_enabled=False).launch(
+        app, local_url, share_url = shared.demo.launch(
             share=cmd_opts.share,
             server_name=server_name,
             server_port=cmd_opts.port,
@@ -185,7 +185,6 @@ def webui():
             create_api(app)
 
         modules.script_callbacks.app_started_callback(shared.demo, app)
-        modules.script_callbacks.app_started_callback(shared.demo, app)
 
         wait_on_server(shared.demo)
         print('Restarting UI...')
-- 
cgit v1.2.3


From d8b90ac121cbf0c18b1dc9d56a5e1d14ca51e74e Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 15 Jan 2023 18:50:56 +0300
Subject: big rework of progressbar/preview system to allow multiple users to
 prompts at the same time and do not get previews of each other

---
 javascript/progressbar.js                      | 249 ++++++++++++++++---------
 javascript/textualInversion.js                 |  13 +-
 javascript/ui.js                               |  33 +++-
 modules/call_queue.py                          |  19 +-
 modules/hypernetworks/hypernetwork.py          |   6 +-
 modules/img2img.py                             |   2 +-
 modules/progress.py                            |  96 ++++++++++
 modules/sd_samplers.py                         |   2 +-
 modules/shared.py                              |  16 +-
 modules/textual_inversion/preprocess.py        |   2 +-
 modules/textual_inversion/textual_inversion.py |   6 +-
 modules/txt2img.py                             |   2 +-
 modules/ui.py                                  |  41 ++--
 modules/ui_progress.py                         | 101 ----------
 style.css                                      |  74 +++++---
 webui.py                                       |   3 +
 16 files changed, 390 insertions(+), 275 deletions(-)
 create mode 100644 modules/progress.py
 delete mode 100644 modules/ui_progress.py

(limited to 'webui.py')

diff --git a/javascript/progressbar.js b/javascript/progressbar.js
index d6323ed9..b7524ef7 100644
--- a/javascript/progressbar.js
+++ b/javascript/progressbar.js
@@ -1,82 +1,25 @@
 // code related to showing and updating progressbar shown as the image is being made
-global_progressbars = {}
-galleries = {}
-galleryObservers = {}
-
-// this tracks launches of window.setTimeout for progressbar to prevent starting a new timeout when the previous is still running
-timeoutIds = {}
 
-function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_skip, id_interrupt, id_preview, id_gallery){
-    // gradio 3.8's enlightened approach allows them to create two nested div elements inside each other with same id
-    // every time you use gr.HTML(elem_id='xxx'), so we handle this here
-    var progressbar = gradioApp().querySelector("#"+id_progressbar+" #"+id_progressbar)
-    var progressbarParent
-    if(progressbar){
-        progressbarParent = gradioApp().querySelector("#"+id_progressbar)
-    } else{
-        progressbar = gradioApp().getElementById(id_progressbar)
-        progressbarParent = null
-    }
 
-    var skip = id_skip ? gradioApp().getElementById(id_skip) : null
-    var interrupt = gradioApp().getElementById(id_interrupt)
-
-    if(opts.show_progress_in_title && progressbar && progressbar.offsetParent){
-        if(progressbar.innerText){
-            let newtitle = '[' + progressbar.innerText.trim() + '] Stable Diffusion';
-            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
-
-        var mutationObserver = new MutationObserver(function(m){
-            if(timeoutIds[id_part]) return;
-
-            preview = gradioApp().getElementById(id_preview)
-            gallery = gradioApp().getElementById(id_gallery)
+galleries = {}
+storedGallerySelections = {}
+galleryObservers = {}
 
-            if(preview != null && gallery != null){
-                preview.style.width = gallery.clientWidth + "px"
-                preview.style.height = gallery.clientHeight + "px"
-                if(progressbarParent) progressbar.style.width = progressbarParent.clientWidth + "px"
+function rememberGallerySelection(id_gallery){
+    storedGallerySelections[id_gallery] = getGallerySelectedIndex(id_gallery)
+}
 
-				//only watch gallery if there is a generation process going on
-                check_gallery(id_gallery);
+function getGallerySelectedIndex(id_gallery){
+    let galleryButtons = gradioApp().querySelectorAll('#'+id_gallery+' .gallery-item')
+    let galleryBtnSelected = gradioApp().querySelector('#'+id_gallery+' .gallery-item.\\!ring-2')
 
-                var progressDiv = gradioApp().querySelectorAll('#' + id_progressbar_span).length > 0;
-                if(progressDiv){
-                    timeoutIds[id_part] = window.setTimeout(function() {
-                        timeoutIds[id_part] = null
-                        requestMoreProgress(id_part, id_progressbar_span, id_skip, id_interrupt)
-                    }, 500)
-                } else{
-                    if (skip) {
-                        skip.style.display = "none"
-                    }
-                    interrupt.style.display = "none"
+     let currentlySelectedIndex = -1
+     galleryButtons.forEach(function(v, i){ if(v==galleryBtnSelected) { currentlySelectedIndex = i } })
 
-                    //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;
-                    }
-                }
-            }
-
-        });
-        mutationObserver.observe( progressbar, { childList:true, subtree:true })
-	}
+     return currentlySelectedIndex
 }
 
+// this is a workaround for https://github.com/gradio-app/gradio/issues/2984
 function check_gallery(id_gallery){
     let gallery = gradioApp().getElementById(id_gallery)
     // if gallery has no change, no need to setting up observer again.
@@ -85,10 +28,16 @@ function check_gallery(id_gallery){
         if(galleryObservers[id_gallery]){
             galleryObservers[id_gallery].disconnect();
         }
-        let prevSelectedIndex = selected_gallery_index();
+
+        storedGallerySelections[id_gallery] = -1
+
         galleryObservers[id_gallery] = new MutationObserver(function (){
             let galleryButtons = gradioApp().querySelectorAll('#'+id_gallery+' .gallery-item')
             let galleryBtnSelected = gradioApp().querySelector('#'+id_gallery+' .gallery-item.\\!ring-2')
+            let currentlySelectedIndex = getGallerySelectedIndex(id_gallery)
+            prevSelectedIndex = storedGallerySelections[id_gallery]
+            storedGallerySelections[id_gallery] = -1
+
             if (prevSelectedIndex !== -1 && galleryButtons.length>prevSelectedIndex && !galleryBtnSelected) {
                 // automatically re-open previously selected index (if exists)
                 activeElement = gradioApp().activeElement;
@@ -120,30 +69,150 @@ function check_gallery(id_gallery){
 }
 
 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')
-    check_progressbar('ti', 'ti_progressbar', 'ti_progress_span', '', 'ti_interrupt', 'ti_preview', 'ti_gallery')
+    check_gallery('txt2img_gallery')
+    check_gallery('img2img_gallery')
 })
 
-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"
+function request(url, data, handler, errorHandler){
+    var xhr = new XMLHttpRequest();
+    var url = url;
+    xhr.open("POST", url, true);
+    xhr.setRequestHeader("Content-Type", "application/json");
+    xhr.onreadystatechange = function () {
+        if (xhr.readyState === 4) {
+            if (xhr.status === 200) {
+                var js = JSON.parse(xhr.responseText);
+                handler(js)
+            } else{
+                errorHandler()
+            }
         }
-        interrupt.style.display = "block"
+    };
+    var js = JSON.stringify(data);
+    xhr.send(js);
+}
+
+function pad2(x){
+    return x<10 ? '0'+x : x
+}
+
+function formatTime(secs){
+    if(secs > 3600){
+        return pad2(Math.floor(secs/60/60)) + ":" + pad2(Math.floor(secs/60)%60) + ":" + pad2(Math.floor(secs)%60)
+    } else if(secs > 60){
+        return pad2(Math.floor(secs/60)) + ":" + pad2(Math.floor(secs)%60)
+    } else{
+        return Math.floor(secs) + "s"
     }
 }
 
-function requestProgress(id_part){
-    btn = gradioApp().getElementById(id_part+"_check_progress_initial");
-    if(btn==null) return;
+function randomId(){
+    return "task(" + Math.random().toString(36).slice(2, 7) + Math.random().toString(36).slice(2, 7) + Math.random().toString(36).slice(2, 7)+")"
+}
+
+// starts sending progress requests to "/internal/progress" uri, creating progressbar above progressbarContainer element and
+// preview inside gallery element. Cleans up all created stuff when the task is over and calls atEnd.
+// calls onProgress every time there is a progress update
+function requestProgress(id_task, progressbarContainer, gallery, atEnd, onProgress){
+    var dateStart = new Date()
+    var wasEverActive = false
+    var parentProgressbar = progressbarContainer.parentNode
+    var parentGallery = gallery.parentNode
+
+    var divProgress = document.createElement('div')
+    divProgress.className='progressDiv'
+    var divInner = document.createElement('div')
+    divInner.className='progress'
+
+    divProgress.appendChild(divInner)
+    parentProgressbar.insertBefore(divProgress, progressbarContainer)
+
+    var livePreview = document.createElement('div')
+    livePreview.className='livePreview'
+    parentGallery.insertBefore(livePreview, gallery)
+
+    var removeProgressBar = function(){
+        parentProgressbar.removeChild(divProgress)
+        parentGallery.removeChild(livePreview)
+        atEnd()
+    }
+
+    var fun = function(id_task, id_live_preview){
+        request("/internal/progress", {"id_task": id_task, "id_live_preview": id_live_preview}, function(res){
+            console.log(res)
+
+            if(res.completed){
+                removeProgressBar()
+                return
+            }
+
+            var rect = progressbarContainer.getBoundingClientRect()
+
+            if(rect.width){
+                divProgress.style.width = rect.width + "px";
+            }
+
+            progressText = ""
+
+            divInner.style.width = ((res.progress || 0) * 100.0) + '%'
+
+            if(res.progress > 0){
+                progressText = ((res.progress || 0) * 100.0).toFixed(0) + '%'
+            }
+
+            if(res.eta){
+                progressText += " ETA: " + formatTime(res.eta)
+            } else if(res.textinfo){
+                progressText += " " + res.textinfo
+            }
+
+            divInner.textContent = progressText
+
+            var elapsedFromStart = (new Date() - dateStart) / 1000
+
+            if(res.active) wasEverActive = true;
+
+            if(! res.active && wasEverActive){
+                removeProgressBar()
+                return
+            }
+
+            if(elapsedFromStart > 5 && !res.queued && !res.active){
+                removeProgressBar()
+                return
+            }
+
+
+            if(res.live_preview){
+                var img = new Image();
+                img.onload = function() {
+                    var rect = gallery.getBoundingClientRect()
+                    if(rect.width){
+                        livePreview.style.width = rect.width + "px"
+                        livePreview.style.height = rect.height + "px"
+                    }
+
+                    livePreview.innerHTML = ''
+                    livePreview.appendChild(img)
+                    if(livePreview.childElementCount > 2){
+                        livePreview.removeChild(livePreview.firstElementChild)
+                    }
+                }
+                img.src = res.live_preview;
+            }
+
+
+            if(onProgress){
+                onProgress(res)
+            }
+
+            setTimeout(() => {
+                fun(id_task, res.id_live_preview);
+            }, 500)
+        }, function(){
+            removeProgressBar()
+        })
+    }
 
-    btn.click();
+    fun(id_task, 0)
 }
diff --git a/javascript/textualInversion.js b/javascript/textualInversion.js
index 8061be08..0354b860 100644
--- a/javascript/textualInversion.js
+++ b/javascript/textualInversion.js
@@ -1,8 +1,17 @@
 
 
+
 function start_training_textual_inversion(){
-    requestProgress('ti')
     gradioApp().querySelector('#ti_error').innerHTML=''
 
-    return args_to_array(arguments)
+    var id = randomId()
+    requestProgress(id, gradioApp().getElementById('ti_output'), gradioApp().getElementById('ti_gallery'), function(){}, function(progress){
+        gradioApp().getElementById('ti_progress').innerHTML = progress.textinfo
+    })
+
+    var res = args_to_array(arguments)
+
+    res[0] = id
+
+    return res
 }
diff --git a/javascript/ui.js b/javascript/ui.js
index f8279124..ecf97cb3 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -126,18 +126,41 @@ function create_submit_args(args){
     return res
 }
 
+function showSubmitButtons(tabname, show){
+    gradioApp().getElementById(tabname+'_interrupt').style.display = show ? "none" : "block"
+    gradioApp().getElementById(tabname+'_skip').style.display = show ? "none" : "block"
+}
+
 function submit(){
-    requestProgress('txt2img')
+    rememberGallerySelection('txt2img_gallery')
+    showSubmitButtons('txt2img', false)
+
+    var id = randomId()
+    requestProgress(id, gradioApp().getElementById('txt2img_gallery_container'), gradioApp().getElementById('txt2img_gallery'), function(){
+        showSubmitButtons('txt2img', true)
+
+    })
 
-    return create_submit_args(arguments)
+    var res = create_submit_args(arguments)
+
+    res[0] = id
+
+    return res
 }
 
 function submit_img2img(){
-    requestProgress('img2img')
+    rememberGallerySelection('img2img_gallery')
+    showSubmitButtons('img2img', false)
+
+    var id = randomId()
+    requestProgress(id, gradioApp().getElementById('img2img_gallery_container'), gradioApp().getElementById('img2img_gallery'), function(){
+        showSubmitButtons('img2img', true)
+    })
 
-    res = create_submit_args(arguments)
+    var res = create_submit_args(arguments)
 
-    res[0] = get_tab_index('mode_img2img')
+    res[0] = id
+    res[1] = get_tab_index('mode_img2img')
 
     return res
 }
diff --git a/modules/call_queue.py b/modules/call_queue.py
index 4cd49533..92097c15 100644
--- a/modules/call_queue.py
+++ b/modules/call_queue.py
@@ -4,7 +4,7 @@ import threading
 import traceback
 import time
 
-from modules import shared
+from modules import shared, progress
 
 queue_lock = threading.Lock()
 
@@ -22,12 +22,23 @@ def wrap_queued_call(func):
 def wrap_gradio_gpu_call(func, extra_outputs=None):
     def f(*args, **kwargs):
 
-        shared.state.begin()
+        # if the first argument is a string that says "task(...)", it is treated as a job id
+        if len(args) > 0 and type(args[0]) == str and args[0][0:5] == "task(" and args[0][-1] == ")":
+            id_task = args[0]
+            progress.add_task_to_queue(id_task)
+        else:
+            id_task = None
 
         with queue_lock:
-            res = func(*args, **kwargs)
+            shared.state.begin()
+            progress.start_task(id_task)
+
+            try:
+                res = func(*args, **kwargs)
+            finally:
+                progress.finish_task(id_task)
 
-        shared.state.end()
+            shared.state.end()
 
         return res
 
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 3aebefa8..ae6af516 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -453,7 +453,7 @@ def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None,
     shared.reload_hypernetworks()
 
 
-def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_hypernetwork_every, template_filename, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
+def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_hypernetwork_every, template_filename, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
     # images allows training previews to have infotext. Importing it at the top causes a circular import problem.
     from modules import images
 
@@ -629,7 +629,6 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step,
 
                 description = f"Training hypernetwork [Epoch {epoch_num}: {epoch_step+1}/{steps_per_epoch}]loss: {loss_step:.7f}"
                 pbar.set_description(description)
-                shared.state.textinfo = description
                 if hypernetwork_dir is not None and steps_done % save_hypernetwork_every == 0:
                     # Before saving, change name to match current checkpoint.
                     hypernetwork_name_every = f'{hypernetwork_name}-{steps_done}'
@@ -701,7 +700,8 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step,
                         torch.cuda.set_rng_state_all(cuda_rng_state)
                     hypernetwork.train()
                     if image is not None:
-                        shared.state.current_image = image
+                        shared.state.assign_current_image(image)
+
                         last_saved_image, last_text_info = images.save_image(image, images_dir, "", p.seed, p.prompt, shared.opts.samples_format, processed.infotexts[0], p=p, forced_filename=forced_filename, save_to_dirs=False)
                         last_saved_image += f", prompt: {preview_text}"
 
diff --git a/modules/img2img.py b/modules/img2img.py
index f62783c6..f4a03c57 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -59,7 +59,7 @@ def process_batch(p, input_dir, output_dir, args):
                 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, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, 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):
+def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, 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):
     is_batch = mode == 5
 
     if mode == 0:  # img2img
diff --git a/modules/progress.py b/modules/progress.py
new file mode 100644
index 00000000..3327b883
--- /dev/null
+++ b/modules/progress.py
@@ -0,0 +1,96 @@
+import base64
+import io
+import time
+
+import gradio as gr
+from pydantic import BaseModel, Field
+
+from modules.shared import opts
+
+import modules.shared as shared
+
+
+current_task = None
+pending_tasks = {}
+finished_tasks = []
+
+
+def start_task(id_task):
+    global current_task
+
+    current_task = id_task
+    pending_tasks.pop(id_task, None)
+
+
+def finish_task(id_task):
+    global current_task
+
+    if current_task == id_task:
+        current_task = None
+
+    finished_tasks.append(id_task)
+    if len(finished_tasks) > 16:
+        finished_tasks.pop(0)
+
+
+def add_task_to_queue(id_job):
+    pending_tasks[id_job] = time.time()
+
+
+class ProgressRequest(BaseModel):
+    id_task: str = Field(default=None, title="Task ID", description="id of the task to get progress for")
+    id_live_preview: int = Field(default=-1, title="Live preview image ID", description="id of last received last preview image")
+
+
+class ProgressResponse(BaseModel):
+    active: bool = Field(title="Whether the task is being worked on right now")
+    queued: bool = Field(title="Whether the task is in queue")
+    completed: bool = Field(title="Whether the task has already finished")
+    progress: float = Field(default=None, title="Progress", description="The progress with a range of 0 to 1")
+    eta: float = Field(default=None, title="ETA in secs")
+    live_preview: str = Field(default=None, title="Live preview image", description="Current live preview; a data: uri")
+    id_live_preview: int = Field(default=None, title="Live preview image ID", description="Send this together with next request to prevent receiving same image")
+    textinfo: str = Field(default=None, title="Info text", description="Info text used by WebUI.")
+
+
+def setup_progress_api(app):
+    return app.add_api_route("/internal/progress", progressapi, methods=["POST"], response_model=ProgressResponse)
+
+
+def progressapi(req: ProgressRequest):
+    active = req.id_task == current_task
+    queued = req.id_task in pending_tasks
+    completed = req.id_task in finished_tasks
+
+    if not active:
+        return ProgressResponse(active=active, queued=queued, completed=completed, id_live_preview=-1, textinfo="In queue..." if queued else "Waiting...")
+
+    progress = 0
+
+    if shared.state.job_count > 0:
+        progress += shared.state.job_no / shared.state.job_count
+    if shared.state.sampling_steps > 0:
+        progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps
+
+    progress = min(progress, 1)
+
+    elapsed_since_start = time.time() - shared.state.time_start
+    predicted_duration = elapsed_since_start / progress if progress > 0 else None
+    eta = predicted_duration - elapsed_since_start if predicted_duration is not None else None
+
+    id_live_preview = req.id_live_preview
+    shared.state.set_current_image()
+    if opts.live_previews_enable and shared.state.id_live_preview != req.id_live_preview:
+        image = shared.state.current_image
+        if image is not None:
+            buffered = io.BytesIO()
+            image.save(buffered, format="png")
+            live_preview = 'data:image/png;base64,' + base64.b64encode(buffered.getvalue()).decode("ascii")
+            id_live_preview = shared.state.id_live_preview
+        else:
+            live_preview = None
+    else:
+        live_preview = None
+
+    return ProgressResponse(active=active, queued=queued, completed=completed, progress=progress, eta=eta, live_preview=live_preview, id_live_preview=id_live_preview, textinfo=shared.state.textinfo)
+
diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index 7616fded..76e0e0d5 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -140,7 +140,7 @@ def store_latent(decoded):
 
     if opts.live_previews_enable and opts.show_progress_every_n_steps > 0 and shared.state.sampling_step % opts.show_progress_every_n_steps == 0:
         if not shared.parallel_processing_allowed:
-            shared.state.current_image = sample_to_image(decoded)
+            shared.state.assign_current_image(sample_to_image(decoded))
 
 
 class InterruptedException(BaseException):
diff --git a/modules/shared.py b/modules/shared.py
index 51df056c..de99aca9 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -152,6 +152,7 @@ def reload_hypernetworks():
     hypernetwork.load_hypernetwork(opts.sd_hypernetwork)
 
 
+
 class State:
     skipped = False
     interrupted = False
@@ -165,6 +166,7 @@ class State:
     current_latent = None
     current_image = None
     current_image_sampling_step = 0
+    id_live_preview = 0
     textinfo = None
     time_start = None
     need_restart = False
@@ -207,6 +209,7 @@ class State:
         self.current_latent = None
         self.current_image = None
         self.current_image_sampling_step = 0
+        self.id_live_preview = 0
         self.skipped = False
         self.interrupted = False
         self.textinfo = None
@@ -220,8 +223,8 @@ class State:
 
         devices.torch_gc()
 
-    """sets self.current_image from self.current_latent if enough sampling steps have been made after the last call to this"""
     def set_current_image(self):
+        """sets self.current_image from self.current_latent if enough sampling steps have been made after the last call to this"""
         if not parallel_processing_allowed:
             return
 
@@ -234,12 +237,16 @@ class State:
 
         import modules.sd_samplers
         if opts.show_progress_grid:
-            self.current_image = modules.sd_samplers.samples_to_image_grid(self.current_latent)
+            self.assign_current_image(modules.sd_samplers.samples_to_image_grid(self.current_latent))
         else:
-            self.current_image = modules.sd_samplers.sample_to_image(self.current_latent)
+            self.assign_current_image(modules.sd_samplers.sample_to_image(self.current_latent))
 
         self.current_image_sampling_step = self.sampling_step
 
+    def assign_current_image(self, image):
+        self.current_image = image
+        self.id_live_preview += 1
+
 
 state = State()
 state.server_start = time.time()
@@ -424,8 +431,6 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"),
 }))
 
 options_templates.update(options_section(('ui', "User interface"), {
-    "show_progressbar": OptionInfo(True, "Show progressbar"),
-    "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"),
     "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"),
@@ -446,6 +451,7 @@ options_templates.update(options_section(('ui', "User interface"), {
 
 options_templates.update(options_section(('ui', "Live previews"), {
     "live_previews_enable": OptionInfo(True, "Show live previews of the created image"),
+    "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"),
     "show_progress_every_n_steps": OptionInfo(10, "Show new live preview image every N sampling steps. Set to -1 to show after completion of batch.", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}),
     "show_progress_type": OptionInfo("Approx NN", "Image creation progress preview mode", gr.Radio, {"choices": ["Full", "Approx NN", "Approx cheap"]}),
     "live_preview_content": OptionInfo("Prompt", "Live preview subject", gr.Radio, {"choices": ["Combined", "Prompt", "Negative prompt"]}),
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index 3c1042ad..64abff4d 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -12,7 +12,7 @@ from modules.shared import opts, cmd_opts
 from modules.textual_inversion import autocrop
 
 
-def preprocess(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False):
+def preprocess(id_task, process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False):
     try:
         if process_caption:
             shared.interrogator.load()
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 63935878..7e4a6d24 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -345,7 +345,7 @@ def validate_train_inputs(model_name, learn_rate, batch_size, gradient_step, dat
         assert log_directory, "Log directory is empty"
 
 
-def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_embedding_every, template_filename, 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(id_task, embedding_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_embedding_every, template_filename, 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):
     save_embedding_every = save_embedding_every or 0
     create_image_every = create_image_every or 0
     template_file = textual_inversion_templates.get(template_filename, None)
@@ -510,7 +510,6 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_
 
                 description = f"Training textual inversion [Epoch {epoch_num}: {epoch_step+1}/{steps_per_epoch}] loss: {loss_step:.7f}"
                 pbar.set_description(description)
-                shared.state.textinfo = description
                 if embedding_dir is not None and steps_done % save_embedding_every == 0:
                     # Before saving, change name to match current checkpoint.
                     embedding_name_every = f'{embedding_name}-{steps_done}'
@@ -560,7 +559,8 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_
                         shared.sd_model.first_stage_model.to(devices.cpu)
 
                     if image is not None:
-                        shared.state.current_image = image
+                        shared.state.assign_current_image(image)
+
                         last_saved_image, last_text_info = images.save_image(image, images_dir, "", p.seed, p.prompt, shared.opts.samples_format, processed.infotexts[0], p=p, forced_filename=forced_filename, save_to_dirs=False)
                         last_saved_image += f", prompt: {preview_text}"
 
diff --git a/modules/txt2img.py b/modules/txt2img.py
index 38b5f591..ca5d4550 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -8,7 +8,7 @@ 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, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, *args):
+def txt2img(id_task: str, 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, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, *args):
     p = StableDiffusionProcessingTxt2Img(
         sd_model=shared.sd_model,
         outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples,
diff --git a/modules/ui.py b/modules/ui.py
index 2425c66f..ff33236b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -356,7 +356,7 @@ def create_toprow(is_img2img):
                 button_deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru")
 
         with gr.Column(scale=1):
-            with gr.Row():
+            with gr.Row(elem_id=f"{id_part}_generate_box"):
                 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')
@@ -384,9 +384,7 @@ def create_toprow(is_img2img):
 
 
 def setup_progressbar(*args, **kwargs):
-    import modules.ui_progress
-
-    modules.ui_progress.setup_progressbar(*args, **kwargs)
+    pass
 
 
 def apply_setting(key, value):
@@ -479,8 +477,8 @@ Requested path was: {f}
             else:
                 sp.Popen(["xdg-open", path])
 
-    with gr.Column(variant='panel'):
-            with gr.Group():
+    with gr.Column(variant='panel', elem_id=f"{tabname}_results"):
+            with gr.Group(elem_id=f"{tabname}_gallery_container"):
                 result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery").style(grid=4)
 
             generation_info = None
@@ -595,15 +593,6 @@ def create_ui():
         dummy_component = gr.Label(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):
-                pass
-
-            with gr.Column(scale=1):
-                progressbar = gr.HTML(elem_id="txt2img_progressbar")
-                txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False)
-                setup_progressbar(progressbar, txt2img_preview, 'txt2img')
-
         with gr.Row().style(equal_height=False):
             with gr.Column(variant='panel', elem_id="txt2img_settings"):
                 for category in ordered_ui_categories():
@@ -682,6 +671,7 @@ def create_ui():
                 fn=wrap_gradio_gpu_call(modules.txt2img.txt2img, extra_outputs=[None, '', '']),
                 _js="submit",
                 inputs=[
+                    dummy_component,
                     txt2img_prompt,
                     txt2img_negative_prompt,
                     txt2img_prompt_style,
@@ -782,16 +772,7 @@ def create_ui():
     with gr.Blocks(analytics_enabled=False) as img2img_interface:
         img2img_prompt, 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)
-
-            with gr.Column(scale=1):
-                pass
-
-            with gr.Column(scale=1):
-                progressbar = gr.HTML(elem_id="img2img_progressbar")
-                img2img_preview = gr.Image(elem_id='img2img_preview', visible=False)
-                setup_progressbar(progressbar, img2img_preview, 'img2img')
+        img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False)
 
         with FormRow().style(equal_height=False):
             with gr.Column(variant='panel', elem_id="img2img_settings"):
@@ -958,6 +939,7 @@ def create_ui():
                 fn=wrap_gradio_gpu_call(modules.img2img.img2img, extra_outputs=[None, '', '']),
                 _js="submit_img2img",
                 inputs=[
+                    dummy_component,
                     dummy_component,
                     img2img_prompt,
                     img2img_negative_prompt,
@@ -1335,15 +1317,11 @@ def create_ui():
 
                 script_callbacks.ui_train_tabs_callback(params)
 
-            with gr.Column():
-                progressbar = gr.HTML(elem_id="ti_progressbar")
+            with gr.Column(elem_id='ti_gallery_container'):
                 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,
@@ -1384,6 +1362,7 @@ def create_ui():
             fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]),
             _js="start_training_textual_inversion",
             inputs=[
+                dummy_component,
                 process_src,
                 process_dst,
                 process_width,
@@ -1411,6 +1390,7 @@ def create_ui():
             fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.train_embedding, extra_outputs=[gr.update()]),
             _js="start_training_textual_inversion",
             inputs=[
+                dummy_component,
                 train_embedding_name,
                 embedding_learn_rate,
                 batch_size,
@@ -1443,6 +1423,7 @@ def create_ui():
             fn=wrap_gradio_gpu_call(modules.hypernetworks.ui.train_hypernetwork, extra_outputs=[gr.update()]),
             _js="start_training_textual_inversion",
             inputs=[
+                dummy_component,
                 train_hypernetwork_name,
                 hypernetwork_learn_rate,
                 batch_size,
diff --git a/modules/ui_progress.py b/modules/ui_progress.py
deleted file mode 100644
index 7cd312e4..00000000
--- a/modules/ui_progress.py
+++ /dev/null
@@ -1,101 +0,0 @@
-import time
-
-import gradio as gr
-
-from modules.shared import opts
-
-import modules.shared as shared
-
-
-def calc_time_left(progress, threshold, label, force_display, show_eta):
-    if progress == 0:
-        return ""
-    else:
-        time_since_start = time.time() - shared.state.time_start
-        eta = (time_since_start/progress)
-        eta_relative = eta-time_since_start
-        if (eta_relative > threshold and show_eta) or force_display:
-            if eta_relative > 3600:
-                return label + time.strftime('%H:%M:%S', time.gmtime(eta_relative))
-            elif eta_relative > 60:
-                return label + time.strftime('%M:%S',  time.gmtime(eta_relative))
-            else:
-                return label + time.strftime('%Ss',  time.gmtime(eta_relative))
-        else:
-            return ""
-
-
-def check_progress_call(id_part):
-    if shared.state.job_count == 0:
-        return "", gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
-
-    progress = 0
-
-    if shared.state.job_count > 0:
-        progress += shared.state.job_no / shared.state.job_count
-    if shared.state.sampling_steps > 0:
-        progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps
-
-    # Show progress percentage and time left at the same moment, and base it also on steps done
-    show_eta = progress >= 0.01 or shared.state.sampling_step >= 10
-
-    time_left = calc_time_left(progress, 1, " ETA: ", shared.state.time_left_force_display, show_eta)
-    if time_left != "":
-        shared.state.time_left_force_display = True
-
-    progress = min(progress, 1)
-
-    progressbar = ""
-    if opts.show_progressbar:
-        progressbar = f"""<div class='progressDiv'><div class='progress' style="overflow:visible;width:{progress * 100}%;white-space:nowrap;">{"&nbsp;" * 2 + str(int(progress*100))+"%" + time_left if show_eta else ""}</div></div>"""
-
-    image = gr.update(visible=False)
-    preview_visibility = gr.update(visible=False)
-
-    if opts.live_previews_enable:
-        shared.state.set_current_image()
-        image = shared.state.current_image
-
-        if image is None:
-            image = gr.update(value=None)
-        else:
-            preview_visibility = gr.update(visible=True)
-
-    if shared.state.textinfo is not None:
-        textinfo_result = gr.HTML.update(value=shared.state.textinfo, visible=True)
-    else:
-        textinfo_result = gr.update(visible=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
-    shared.state.time_start = time.time()
-    shared.state.time_left_force_display = False
-
-    return check_progress_call(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, textinfo],
-    )
-
-    check_progress_initial = gr.Button('Check progress (first)', elem_id=f"{id_part}_check_progress_initial", visible=False)
-    check_progress_initial.click(
-        fn=lambda: check_progress_call_initial(id_part),
-        show_progress=False,
-        inputs=[],
-        outputs=[progressbar, preview, preview, textinfo],
-    )
diff --git a/style.css b/style.css
index 2d484e06..786b71d1 100644
--- a/style.css
+++ b/style.css
@@ -305,26 +305,42 @@ input[type="range"]{
 }
 
 .progressDiv{
-  width: 100%;
-  height: 20px;
-  background: #b4c0cc;
-  border-radius: 8px;
+    position: absolute;
+    height: 20px;
+    top: -20px;
+    background: #b4c0cc;
+    border-radius: 8px !important;
 }
 
 .dark .progressDiv{
-  background: #424c5b;
+    background: #424c5b;
 }
 
 .progressDiv .progress{
-  width: 0%;
-  height: 20px;
-  background: #0060df;
-  color: white;
-  font-weight: bold;
-  line-height: 20px;
-  padding: 0 8px 0 0;
-  text-align: right;
-  border-radius: 8px;
+    width: 0%;
+    height: 20px;
+    background: #0060df;
+    color: white;
+    font-weight: bold;
+    line-height: 20px;
+    padding: 0 8px 0 0;
+    text-align: right;
+    border-radius: 8px;
+    overflow: visible;
+    white-space: nowrap;
+}
+
+.livePreview{
+    position: absolute;
+    z-index: 300;
+    background-color: white;
+    margin: -4px;
+}
+
+.livePreview img{
+    object-fit: contain;
+    width: 100%;
+    height: 100%;
 }
 
 #lightboxModal{
@@ -450,23 +466,25 @@ input[type="range"]{
     display:none
 }
 
-#txt2img_interrupt, #img2img_interrupt{
-  position: absolute;
-  width: 50%;
-  height: 72px;
-  background: #b4c0cc;
-  border-radius: 0px;
-  display: none;
+#txt2img_generate_box, #img2img_generate_box{
+    position: relative;
+}
+
+#txt2img_interrupt, #img2img_interrupt, #txt2img_skip, #img2img_skip{
+    position: absolute;
+    width: 50%;
+    height: 100%;
+    background: #b4c0cc;
+    display: none;
 }
 
+#txt2img_interrupt, #img2img_interrupt{
+    right: 0;
+    border-radius: 0 0.5rem 0.5rem 0;
+}
 #txt2img_skip, #img2img_skip{
-  position: absolute;
-  width: 50%;
-  right: 0px;
-  height: 72px;
-  background: #b4c0cc;
-  border-radius: 0px;
-  display: none;
+    left: 0;
+    border-radius: 0.5rem 0 0 0.5rem;
 }
 
 .red {
diff --git a/webui.py b/webui.py
index 1fff80da..4624fe18 100644
--- a/webui.py
+++ b/webui.py
@@ -34,6 +34,7 @@ import modules.sd_vae
 import modules.txt2img
 import modules.script_callbacks
 import modules.textual_inversion.textual_inversion
+import modules.progress
 
 import modules.ui
 from modules import modelloader
@@ -181,6 +182,8 @@ def webui():
 
         app.add_middleware(GZipMiddleware, minimum_size=1000)
 
+        modules.progress.setup_progress_api(app)
+
         if launch_api:
             create_api(app)
 
-- 
cgit v1.2.3


From 40ff6db5325fc34ad4fa35e80cb1e7768d9f7e75 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 21 Jan 2023 08:36:07 +0300
Subject: extra networks UI rework of hypernets: rather than via settings,
 hypernets are added directly to prompt as <hypernet:name:weight>

---
 html/card-no-preview.png                       | Bin 0 -> 84440 bytes
 html/extra-networks-card.html                  |  11 ++
 html/extra-networks-no-cards.html              |   8 ++
 javascript/extraNetworks.js                    |  60 ++++++++
 javascript/hints.js                            |   2 +
 javascript/ui.js                               |   9 +-
 modules/api/api.py                             |   7 +-
 modules/extra_networks.py                      | 147 +++++++++++++++++++
 modules/extra_networks_hypernet.py             |  21 +++
 modules/generation_parameters_copypaste.py     |  12 +-
 modules/hypernetworks/hypernetwork.py          | 107 +++++++++-----
 modules/hypernetworks/ui.py                    |   5 +-
 modules/processing.py                          |  24 ++--
 modules/sd_hijack_optimizations.py             |  10 +-
 modules/shared.py                              |  21 ++-
 modules/textual_inversion/textual_inversion.py |   2 +
 modules/ui.py                                  |  50 ++++---
 modules/ui_components.py                       |  10 ++
 modules/ui_extra_networks.py                   | 149 +++++++++++++++++++
 modules/ui_extra_networks_hypernets.py         |  34 +++++
 modules/ui_extra_networks_textual_inversion.py |  32 +++++
 script.js                                      |  13 +-
 scripts/xy_grid.py                             |  29 ----
 style.css                                      | 190 +++++++++++++------------
 webui.py                                       |  26 +++-
 25 files changed, 765 insertions(+), 214 deletions(-)
 create mode 100644 html/card-no-preview.png
 create mode 100644 html/extra-networks-card.html
 create mode 100644 html/extra-networks-no-cards.html
 create mode 100644 javascript/extraNetworks.js
 create mode 100644 modules/extra_networks.py
 create mode 100644 modules/extra_networks_hypernet.py
 create mode 100644 modules/ui_extra_networks.py
 create mode 100644 modules/ui_extra_networks_hypernets.py
 create mode 100644 modules/ui_extra_networks_textual_inversion.py

(limited to 'webui.py')

diff --git a/html/card-no-preview.png b/html/card-no-preview.png
new file mode 100644
index 00000000..e2beb269
Binary files /dev/null and b/html/card-no-preview.png differ
diff --git a/html/extra-networks-card.html b/html/extra-networks-card.html
new file mode 100644
index 00000000..7314b063
--- /dev/null
+++ b/html/extra-networks-card.html
@@ -0,0 +1,11 @@
+<div class='card' {preview_html} onclick='return cardClicked({prompt}, {allow_negative_prompt})'>
+	<div class='actions'>
+		<div class='additional'>
+			<ul>
+				<a href="#" title="replace preview image with currently selected in gallery" onclick='return saveCardPreview(event, {tabname}, {local_preview})'>replace preview</a>
+			</ul>
+		</div>
+		<span class='name'>{name}</span>
+	</div>
+</div>
+
diff --git a/html/extra-networks-no-cards.html b/html/extra-networks-no-cards.html
new file mode 100644
index 00000000..389358d6
--- /dev/null
+++ b/html/extra-networks-no-cards.html
@@ -0,0 +1,8 @@
+<div class='nocards'>
+<h1>Nothing here. Add some content to the following directories:</h1>
+
+<ul>
+{dirs}
+</ul>
+</div>
+
diff --git a/javascript/extraNetworks.js b/javascript/extraNetworks.js
new file mode 100644
index 00000000..71e522d1
--- /dev/null
+++ b/javascript/extraNetworks.js
@@ -0,0 +1,60 @@
+
+function setupExtraNetworksForTab(tabname){
+    gradioApp().querySelector('#'+tabname+'_extra_tabs').classList.add('extra-networks')
+
+    gradioApp().querySelector('#'+tabname+'_extra_tabs > div').appendChild(gradioApp().getElementById(tabname+'_extra_refresh'))
+    gradioApp().querySelector('#'+tabname+'_extra_tabs > div').appendChild(gradioApp().getElementById(tabname+'_extra_close'))
+}
+
+var activePromptTextarea = null;
+var activePositivePromptTextarea = null;
+
+function setupExtraNetworks(){
+    setupExtraNetworksForTab('txt2img')
+    setupExtraNetworksForTab('img2img')
+
+    function registerPrompt(id, isNegative){
+        var textarea = gradioApp().querySelector("#" + id + " > label > textarea");
+
+        if (activePromptTextarea == null){
+            activePromptTextarea = textarea
+        }
+        if (activePositivePromptTextarea == null && ! isNegative){
+            activePositivePromptTextarea = textarea
+        }
+
+		textarea.addEventListener("focus", function(){
+            activePromptTextarea = textarea;
+            if(! isNegative)  activePositivePromptTextarea = textarea;
+		});
+    }
+
+    registerPrompt('txt2img_prompt')
+    registerPrompt('txt2img_neg_prompt', true)
+    registerPrompt('img2img_prompt')
+    registerPrompt('img2img_neg_prompt', true)
+}
+
+onUiLoaded(setupExtraNetworks)
+
+function cardClicked(textToAdd, allowNegativePrompt){
+    textarea = allowNegativePrompt ? activePromptTextarea : activePositivePromptTextarea
+
+    textarea.value = textarea.value + " " + textToAdd
+    updateInput(textarea)
+
+    return false
+}
+
+function saveCardPreview(event, tabname, filename){
+    textarea = gradioApp().querySelector("#" + tabname + '_preview_filename  > label > textarea')
+    button = gradioApp().getElementById(tabname + '_save_preview')
+
+    textarea.value = filename
+    updateInput(textarea)
+
+    button.click()
+
+    event.stopPropagation()
+    event.preventDefault()
+}
diff --git a/javascript/hints.js b/javascript/hints.js
index e746e20d..f4079f96 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -21,6 +21,8 @@ titles = {
     "\U0001F5D1": "Clear prompt",
     "\u{1f4cb}": "Apply selected styles to current prompt",
     "\u{1f4d2}": "Paste available values into the field",
+    "\u{1f3b4}": "Show extra networks",
+
 
     "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/javascript/ui.js b/javascript/ui.js
index 3ba90ca8..a7e75439 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -196,8 +196,6 @@ function confirm_clear_prompt(prompt, negative_prompt) {
     return [prompt, negative_prompt]
 }
 
-
-
 opts = {}
 onUiUpdate(function(){
 	if(Object.keys(opts).length != 0) return;
@@ -239,11 +237,14 @@ onUiUpdate(function(){
             return
         }
 
+
         prompt.parentElement.insertBefore(counter, prompt)
         counter.classList.add("token-counter")
         prompt.parentElement.style.position = "relative"
 
-		textarea.addEventListener("input", () => update_token_counter(id_button));
+		textarea.addEventListener("input", function(){
+		    update_token_counter(id_button);
+		});
     }
 
     registerTextarea('txt2img_prompt', 'txt2img_token_counter', 'txt2img_token_button')
@@ -261,10 +262,8 @@ onUiUpdate(function(){
             })
         }
     }
-
 })
 
-
 onOptionsChanged(function(){
     elem = gradioApp().getElementById('sd_checkpoint_hash')
     sd_checkpoint_hash = opts.sd_checkpoint_hash || ""
diff --git a/modules/api/api.py b/modules/api/api.py
index 9814bbc2..2c371e6e 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -480,7 +480,7 @@ class Api:
     def train_hypernetwork(self, args: dict):
         try:
             shared.state.begin()
-            initial_hypernetwork = shared.loaded_hypernetwork
+            shared.loaded_hypernetworks = []
             apply_optimizations = shared.opts.training_xattention_optimizations
             error = None
             filename = ''
@@ -491,16 +491,15 @@ class Api:
             except Exception as e:
                 error = e
             finally:
-                shared.loaded_hypernetwork = initial_hypernetwork
                 shared.sd_model.cond_stage_model.to(devices.device)
                 shared.sd_model.first_stage_model.to(devices.device)
                 if not apply_optimizations:
                     sd_hijack.apply_optimizations()
                 shared.state.end()
-            return TrainResponse(info = "train embedding complete: filename: {filename} error: {error}".format(filename = filename, error = error))
+            return TrainResponse(info="train embedding complete: filename: {filename} error: {error}".format(filename=filename, error=error))
         except AssertionError as msg:
             shared.state.end()
-            return TrainResponse(info = "train embedding error: {error}".format(error = error))
+            return TrainResponse(info="train embedding error: {error}".format(error=error))
 
     def get_memory(self):
         try:
diff --git a/modules/extra_networks.py b/modules/extra_networks.py
new file mode 100644
index 00000000..1978673d
--- /dev/null
+++ b/modules/extra_networks.py
@@ -0,0 +1,147 @@
+import re
+from collections import defaultdict
+
+from modules import errors
+
+extra_network_registry = {}
+
+
+def initialize():
+    extra_network_registry.clear()
+
+
+def register_extra_network(extra_network):
+    extra_network_registry[extra_network.name] = extra_network
+
+
+class ExtraNetworkParams:
+    def __init__(self, items=None):
+        self.items = items or []
+
+
+class ExtraNetwork:
+    def __init__(self, name):
+        self.name = name
+
+    def activate(self, p, params_list):
+        """
+        Called by processing on every run. Whatever the extra network is meant to do should be activated here.
+        Passes arguments related to this extra network in params_list.
+        User passes arguments by specifying this in his prompt:
+
+        <name:arg1:arg2:arg3>
+
+        Where name matches the name of this ExtraNetwork object, and arg1:arg2:arg3 are any natural number of text arguments
+        separated by colon.
+
+        Even if the user does not mention this ExtraNetwork in his prompt, the call will stil be made, with empty params_list -
+        in this case, all effects of this extra networks should be disabled.
+
+        Can be called multiple times before deactivate() - each new call should override the previous call completely.
+
+        For example, if this ExtraNetwork's name is 'hypernet' and user's prompt is:
+
+        > "1girl, <hypernet:agm:1.1> <extrasupernet:master:12:13:14> <hypernet:ray>"
+
+        params_list will be:
+
+        [
+            ExtraNetworkParams(items=["agm", "1.1"]),
+            ExtraNetworkParams(items=["ray"])
+        ]
+
+        """
+        raise NotImplementedError
+
+    def deactivate(self, p):
+        """
+        Called at the end of processing for housekeeping. No need to do anything here.
+        """
+
+        raise NotImplementedError
+
+
+def activate(p, extra_network_data):
+    """call activate for extra networks in extra_network_data in specified order, then call
+    activate for all remaining registered networks with an empty argument list"""
+
+    for extra_network_name, extra_network_args in extra_network_data.items():
+        extra_network = extra_network_registry.get(extra_network_name, None)
+        if extra_network is None:
+            print(f"Skipping unknown extra network: {extra_network_name}")
+            continue
+
+        try:
+            extra_network.activate(p, extra_network_args)
+        except Exception as e:
+            errors.display(e, f"activating extra network {extra_network_name} with arguments {extra_network_args}")
+
+    for extra_network_name, extra_network in extra_network_registry.items():
+        args = extra_network_data.get(extra_network_name, None)
+        if args is not None:
+            continue
+
+        try:
+            extra_network.activate(p, [])
+        except Exception as e:
+            errors.display(e, f"activating extra network {extra_network_name}")
+
+
+def deactivate(p, extra_network_data):
+    """call deactivate for extra networks in extra_network_data in specified order, then call
+    deactivate for all remaining registered networks"""
+
+    for extra_network_name, extra_network_args in extra_network_data.items():
+        extra_network = extra_network_registry.get(extra_network_name, None)
+        if extra_network is None:
+            continue
+
+        try:
+            extra_network.deactivate(p)
+        except Exception as e:
+            errors.display(e, f"deactivating extra network {extra_network_name}")
+
+    for extra_network_name, extra_network in extra_network_registry.items():
+        args = extra_network_data.get(extra_network_name, None)
+        if args is not None:
+            continue
+
+        try:
+            extra_network.deactivate(p)
+        except Exception as e:
+            errors.display(e, f"deactivating unmentioned extra network {extra_network_name}")
+
+
+re_extra_net = re.compile(r"<(\w+):([^>]+)>")
+
+
+def parse_prompt(prompt):
+    res = defaultdict(list)
+
+    def found(m):
+        name = m.group(1)
+        args = m.group(2)
+
+        res[name].append(ExtraNetworkParams(items=args.split(":")))
+
+        return ""
+
+    prompt = re.sub(re_extra_net, found, prompt)
+
+    return prompt, res
+
+
+def parse_prompts(prompts):
+    res = []
+    extra_data = None
+
+    for prompt in prompts:
+        updated_prompt, parsed_extra_data = parse_prompt(prompt)
+
+        if extra_data is None:
+            extra_data = parsed_extra_data
+
+        res.append(updated_prompt)
+
+    return res, extra_data
+
diff --git a/modules/extra_networks_hypernet.py b/modules/extra_networks_hypernet.py
new file mode 100644
index 00000000..6a0c4ba8
--- /dev/null
+++ b/modules/extra_networks_hypernet.py
@@ -0,0 +1,21 @@
+from modules import extra_networks
+from modules.hypernetworks import hypernetwork
+
+
+class ExtraNetworkHypernet(extra_networks.ExtraNetwork):
+    def __init__(self):
+        super().__init__('hypernet')
+
+    def activate(self, p, params_list):
+        names = []
+        multipliers = []
+        for params in params_list:
+            assert len(params.items) > 0
+
+            names.append(params.items[0])
+            multipliers.append(float(params.items[1]) if len(params.items) > 1 else 1.0)
+
+        hypernetwork.load_hypernetworks(names, multipliers)
+
+    def deactivate(p, self):
+        pass
diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py
index a381ff59..46e12dc6 100644
--- a/modules/generation_parameters_copypaste.py
+++ b/modules/generation_parameters_copypaste.py
@@ -79,8 +79,6 @@ def integrate_settings_paste_fields(component_dict):
     from modules import ui
 
     settings_map = {
-        'sd_hypernetwork': 'Hypernet',
-        'sd_hypernetwork_strength': 'Hypernet strength',
         'CLIP_stop_at_last_layers': 'Clip skip',
         'inpainting_mask_weight': 'Conditional mask weight',
         'sd_model_checkpoint': 'Model hash',
@@ -275,13 +273,9 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
     if "Clip skip" not in res:
         res["Clip skip"] = "1"
 
-    if "Hypernet strength" not in res:
-        res["Hypernet strength"] = "1"
-
-    if "Hypernet" in res:
-        hypernet_name = res["Hypernet"]
-        hypernet_hash = res.get("Hypernet hash", None)
-        res["Hypernet"] = find_hypernetwork_key(hypernet_name, hypernet_hash)
+    hypernet = res.get("Hypernet", None)
+    if hypernet is not None:
+        res["Prompt"] += f"""<hypernet:{hypernet}:{res.get("Hypernet strength", "1.0")}>"""
 
     if "Hires resize-1" not in res:
         res["Hires resize-1"] = 0
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 74e78582..80a47c79 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -25,7 +25,6 @@ from statistics import stdev, mean
 optimizer_dict = {optim_name : cls_obj for optim_name, cls_obj in inspect.getmembers(torch.optim, inspect.isclass) if optim_name != "Optimizer"}
 
 class HypernetworkModule(torch.nn.Module):
-    multiplier = 1.0
     activation_dict = {
         "linear": torch.nn.Identity,
         "relu": torch.nn.ReLU,
@@ -41,6 +40,8 @@ class HypernetworkModule(torch.nn.Module):
                  add_layer_norm=False, activate_output=False, dropout_structure=None):
         super().__init__()
 
+        self.multiplier = 1.0
+
         assert layer_structure is not None, "layer_structure must not be None"
         assert layer_structure[0] == 1, "Multiplier Sequence should start with size 1!"
         assert layer_structure[-1] == 1, "Multiplier Sequence should end with size 1!"
@@ -115,7 +116,7 @@ class HypernetworkModule(torch.nn.Module):
             state_dict[to] = x
 
     def forward(self, x):
-        return x + self.linear(x) * (HypernetworkModule.multiplier if not self.training else 1)
+        return x + self.linear(x) * (self.multiplier if not self.training else 1)
 
     def trainables(self):
         layer_structure = []
@@ -125,9 +126,6 @@ class HypernetworkModule(torch.nn.Module):
         return layer_structure
 
 
-def apply_strength(value=None):
-    HypernetworkModule.multiplier = value if value is not None else shared.opts.sd_hypernetwork_strength
-
 #param layer_structure : sequence used for length, use_dropout : controlling boolean, last_layer_dropout : for compatibility check.
 def parse_dropout_structure(layer_structure, use_dropout, last_layer_dropout):
     if layer_structure is None:
@@ -192,6 +190,20 @@ class Hypernetwork:
                 for param in layer.parameters():
                     param.requires_grad = mode
 
+    def to(self, device):
+        for k, layers in self.layers.items():
+            for layer in layers:
+                layer.to(device)
+
+        return self
+
+    def set_multiplier(self, multiplier):
+        for k, layers in self.layers.items():
+            for layer in layers:
+                layer.multiplier = multiplier
+
+        return self
+
     def eval(self):
         for k, layers in self.layers.items():
             for layer in layers:
@@ -269,11 +281,13 @@ class Hypernetwork:
             self.optimizer_state_dict = None
         if self.optimizer_state_dict:
             self.optimizer_name = optimizer_saved_dict.get('optimizer_name', 'AdamW')
-            print("Loaded existing optimizer from checkpoint")
-            print(f"Optimizer name is {self.optimizer_name}")
+            if shared.opts.print_hypernet_extra:
+                print("Loaded existing optimizer from checkpoint")
+                print(f"Optimizer name is {self.optimizer_name}")
         else:
             self.optimizer_name = "AdamW"
-            print("No saved optimizer exists in checkpoint")
+            if shared.opts.print_hypernet_extra:
+                print("No saved optimizer exists in checkpoint")
 
         for size, sd in state_dict.items():
             if type(size) == int:
@@ -306,23 +320,43 @@ def list_hypernetworks(path):
     return res
 
 
-def load_hypernetwork(filename):
-    path = shared.hypernetworks.get(filename, None)
-    # Prevent any file named "None.pt" from being loaded.
-    if path is not None and filename != "None":
-        print(f"Loading hypernetwork {filename}")
-        try:
-            shared.loaded_hypernetwork = Hypernetwork()
-            shared.loaded_hypernetwork.load(path)
+def load_hypernetwork(name):
+    path = shared.hypernetworks.get(name, None)
 
-        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("Unloading hypernetwork")
+    if path is None:
+        return None
+
+    hypernetwork = Hypernetwork()
+
+    try:
+        hypernetwork.load(path)
+    except Exception:
+        print(f"Error loading hypernetwork {path}", file=sys.stderr)
+        print(traceback.format_exc(), file=sys.stderr)
+        return None
+
+    return hypernetwork
+
+
+def load_hypernetworks(names, multipliers=None):
+    already_loaded = {}
+
+    for hypernetwork in shared.loaded_hypernetworks:
+        if hypernetwork.name in names:
+            already_loaded[hypernetwork.name] = hypernetwork
 
-        shared.loaded_hypernetwork = None
+    shared.loaded_hypernetworks.clear()
+
+    for i, name in enumerate(names):
+        hypernetwork = already_loaded.get(name, None)
+        if hypernetwork is None:
+            hypernetwork = load_hypernetwork(name)
+
+        if hypernetwork is None:
+            continue
+
+        hypernetwork.set_multiplier(multipliers[i] if multipliers else 1.0)
+        shared.loaded_hypernetworks.append(hypernetwork)
 
 
 def find_closest_hypernetwork_name(search: str):
@@ -336,18 +370,27 @@ def find_closest_hypernetwork_name(search: str):
     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)
+def apply_single_hypernetwork(hypernetwork, context_k, context_v, layer=None):
+    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context_k.shape[2], None)
 
     if hypernetwork_layers is None:
-        return context, context
+        return context_k, context_v
 
     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)
+    context_k = hypernetwork_layers[0](context_k)
+    context_v = hypernetwork_layers[1](context_v)
+    return context_k, context_v
+
+
+def apply_hypernetworks(hypernetworks, context, layer=None):
+    context_k = context
+    context_v = context
+    for hypernetwork in hypernetworks:
+        context_k, context_v = apply_single_hypernetwork(hypernetwork, context_k, context_v, layer)
+
     return context_k, context_v
 
 
@@ -357,7 +400,7 @@ def attention_CrossAttention_forward(self, x, context=None, mask=None):
     q = self.to_q(x)
     context = default(context, x)
 
-    context_k, context_v = apply_hypernetwork(shared.loaded_hypernetwork, context, self)
+    context_k, context_v = apply_hypernetworks(shared.loaded_hypernetworks, context, self)
     k = self.to_k(context_k)
     v = self.to_v(context_v)
 
@@ -464,8 +507,9 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
     template_file = template_file.path
 
     path = shared.hypernetworks.get(hypernetwork_name, None)
-    shared.loaded_hypernetwork = Hypernetwork()
-    shared.loaded_hypernetwork.load(path)
+    hypernetwork = Hypernetwork()
+    hypernetwork.load(path)
+    shared.loaded_hypernetworks = [hypernetwork]
 
     shared.state.job = "train-hypernetwork"
     shared.state.textinfo = "Initializing hypernetwork training..."
@@ -489,7 +533,6 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
     else:
         images_dir = None
 
-    hypernetwork = shared.loaded_hypernetwork
     checkpoint = sd_models.select_checkpoint()
 
     initial_step = hypernetwork.step or 0
diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py
index 81e3f519..76599f5a 100644
--- a/modules/hypernetworks/ui.py
+++ b/modules/hypernetworks/ui.py
@@ -9,6 +9,7 @@ from modules import devices, sd_hijack, shared
 not_available = ["hardswish", "multiheadattention"]
 keys = list(x for x in modules.hypernetworks.hypernetwork.HypernetworkModule.activation_dict.keys() if x not in not_available)
 
+
 def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False, dropout_structure=None):
     filename = modules.hypernetworks.hypernetwork.create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure, activation_func, weight_init, add_layer_norm, use_dropout, dropout_structure)
 
@@ -16,8 +17,7 @@ def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None,
 
 
 def train_hypernetwork(*args):
-
-    initial_hypernetwork = shared.loaded_hypernetwork
+    shared.loaded_hypernetworks = []
 
     assert not shared.cmd_opts.lowvram, 'Training models with lowvram is not possible'
 
@@ -34,7 +34,6 @@ Hypernetwork saved to {html.escape(filename)}
     except Exception:
         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/processing.py b/modules/processing.py
index a3e9f709..b5deeacf 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -13,7 +13,7 @@ from skimage import exposure
 from typing import Any, Dict, List, Optional
 
 import modules.sd_hijack
-from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, script_callbacks
+from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, script_callbacks, extra_networks
 from modules.sd_hijack import model_hijack
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
@@ -438,9 +438,6 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
         "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_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),
-        "Hypernet hash": (None if shared.loaded_hypernetwork is None else shared.loaded_hypernetwork.shorthash()),
-        "Hypernet strength": (None if shared.loaded_hypernetwork is None or shared.opts.sd_hypernetwork_strength >= 1 else shared.opts.sd_hypernetwork_strength),
         "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]),
@@ -468,14 +465,12 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
     try:
         for k, v in p.override_settings.items():
             setattr(opts, k, v)
-            if k == 'sd_hypernetwork':
-                shared.reload_hypernetworks()  # make onchange call for changing hypernet
 
             if k == 'sd_model_checkpoint':
-                sd_models.reload_model_weights()  # make onchange call for changing SD model
+                sd_models.reload_model_weights()
 
             if k == 'sd_vae':
-                sd_vae.reload_vae_weights()  # make onchange call for changing VAE
+                sd_vae.reload_vae_weights()
 
         res = process_images_inner(p)
 
@@ -484,9 +479,11 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
         if p.override_settings_restore_afterwards:
             for k, v in stored_opts.items():
                 setattr(opts, k, v)
-                if k == 'sd_hypernetwork': shared.reload_hypernetworks()
-                if k == 'sd_model_checkpoint': sd_models.reload_model_weights()
-                if k == 'sd_vae': sd_vae.reload_vae_weights()
+                if k == 'sd_model_checkpoint':
+                    sd_models.reload_model_weights()
+
+                if k == 'sd_vae':
+                    sd_vae.reload_vae_weights()
 
     return res
 
@@ -564,10 +561,14 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
         cache[0] = (required_prompts, steps)
         return cache[1]
 
+    p.all_prompts, extra_network_data = extra_networks.parse_prompts(p.all_prompts)
+
     with torch.no_grad(), p.sd_model.ema_scope():
         with devices.autocast():
             p.init(p.all_prompts, p.all_seeds, p.all_subseeds)
 
+            extra_networks.activate(p, extra_network_data)
+
         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))
@@ -681,6 +682,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
             if opts.grid_save:
                 images.save_image(grid, p.outpath_grids, "grid", p.all_seeds[0], p.all_prompts[0], opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename, p=p, grid=True)
 
+    extra_networks.deactivate(p, extra_network_data)
     devices.torch_gc()
 
     res = Processed(p, output_images, p.all_seeds[0], infotext(), comments="".join(["\n\n" + x for x in comments]), subseed=p.all_subseeds[0], index_of_first_image=index_of_first_image, infotexts=infotexts)
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index cdc63ed7..4fa54329 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -44,7 +44,7 @@ def split_cross_attention_forward_v1(self, x, context=None, mask=None):
     q_in = self.to_q(x)
     context = default(context, x)
 
-    context_k, context_v = hypernetwork.apply_hypernetwork(shared.loaded_hypernetwork, context)
+    context_k, context_v = hypernetwork.apply_hypernetworks(shared.loaded_hypernetworks, context)
     k_in = self.to_k(context_k)
     v_in = self.to_v(context_v)
     del context, context_k, context_v, x
@@ -78,7 +78,7 @@ def split_cross_attention_forward(self, x, context=None, mask=None):
     q_in = self.to_q(x)
     context = default(context, x)
 
-    context_k, context_v = hypernetwork.apply_hypernetwork(shared.loaded_hypernetwork, context)
+    context_k, context_v = hypernetwork.apply_hypernetworks(shared.loaded_hypernetworks, context)
     k_in = self.to_k(context_k)
     v_in = self.to_v(context_v)
 
@@ -203,7 +203,7 @@ def split_cross_attention_forward_invokeAI(self, x, context=None, mask=None):
     q = self.to_q(x)
     context = default(context, x)
 
-    context_k, context_v = hypernetwork.apply_hypernetwork(shared.loaded_hypernetwork, context)
+    context_k, context_v = hypernetwork.apply_hypernetworks(shared.loaded_hypernetworks, context)
     k = self.to_k(context_k) * self.scale
     v = self.to_v(context_v)
     del context, context_k, context_v, x
@@ -225,7 +225,7 @@ def sub_quad_attention_forward(self, x, context=None, mask=None):
     q = self.to_q(x)
     context = default(context, x)
 
-    context_k, context_v = hypernetwork.apply_hypernetwork(shared.loaded_hypernetwork, context)
+    context_k, context_v = hypernetwork.apply_hypernetworks(shared.loaded_hypernetworks, context)
     k = self.to_k(context_k)
     v = self.to_v(context_v)
     del context, context_k, context_v, x
@@ -284,7 +284,7 @@ def xformers_attention_forward(self, x, context=None, mask=None):
     q_in = self.to_q(x)
     context = default(context, x)
 
-    context_k, context_v = hypernetwork.apply_hypernetwork(shared.loaded_hypernetwork, context)
+    context_k, context_v = hypernetwork.apply_hypernetworks(shared.loaded_hypernetworks, context)
     k_in = self.to_k(context_k)
     v_in = self.to_v(context_v)
 
diff --git a/modules/shared.py b/modules/shared.py
index 2f366454..c0e11f18 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -23,6 +23,7 @@ demo = None
 sd_default_config = os.path.join(script_path, "configs/v1-inference.yaml")
 sd_model_file = os.path.join(script_path, 'model.ckpt')
 default_sd_model_file = sd_model_file
+
 parser = argparse.ArgumentParser()
 parser.add_argument("--config", type=str, default=sd_default_config, 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",)
@@ -145,7 +146,7 @@ config_filename = cmd_opts.ui_settings_file
 
 os.makedirs(cmd_opts.hypernetwork_dir, exist_ok=True)
 hypernetworks = {}
-loaded_hypernetwork = None
+loaded_hypernetworks = []
 
 
 def reload_hypernetworks():
@@ -153,8 +154,6 @@ def reload_hypernetworks():
     global hypernetworks
 
     hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir)
-    hypernetwork.load_hypernetwork(opts.sd_hypernetwork)
-
 
 
 class State:
@@ -399,8 +398,6 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "sd_vae_checkpoint_cache": OptionInfo(0, "VAE Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
     "sd_vae": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": ["Automatic", "None"] + list(sd_vae.vae_dict)}, refresh=sd_vae.refresh_vae_list),
     "sd_vae_as_default": OptionInfo(True, "Ignore selected VAE for stable diffusion checkpoints that have their own .vae.pt next to them"),
-    "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}),
     "inpainting_mask_weight": OptionInfo(1.0, "Inpainting conditioning mask strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
     "initial_noise_multiplier": OptionInfo(1.0, "Noise multiplier for img2img", gr.Slider, {"minimum": 0.5, "maximum": 1.5, "step": 0.01 }),
     "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."),
@@ -661,3 +658,17 @@ mem_mon.start()
 def listfiles(dirname):
     filenames = [os.path.join(dirname, x) for x in sorted(os.listdir(dirname)) if not x.startswith(".")]
     return [file for file in filenames if os.path.isfile(file)]
+
+
+def html_path(filename):
+    return os.path.join(script_path, "html", filename)
+
+
+def html(filename):
+    path = html_path(filename)
+
+    if os.path.exists(path):
+        with open(path, encoding="utf8") as file:
+            return file.read()
+
+    return ""
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 5a7be422..4e90f690 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -50,6 +50,7 @@ class Embedding:
         self.sd_checkpoint = None
         self.sd_checkpoint_name = None
         self.optimizer_state_dict = None
+        self.filename = None
 
     def save(self, filename):
         embedding_data = {
@@ -182,6 +183,7 @@ class EmbeddingDatabase:
         embedding.sd_checkpoint_name = data.get('sd_checkpoint_name', None)
         embedding.vectors = vec.shape[0]
         embedding.shape = vec.shape[-1]
+        embedding.filename = path
 
         if self.expected_shape == -1 or self.expected_shape == embedding.shape:
             self.register_embedding(embedding, shared.sd_model)
diff --git a/modules/ui.py b/modules/ui.py
index 06c11848..d23b2b8e 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -20,7 +20,7 @@ import numpy as np
 from PIL import Image, PngImagePlugin
 from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
 
-from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae
+from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks
 from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
 from modules.paths import script_path
 
@@ -90,6 +90,7 @@ refresh_symbol = '\U0001f504'  # 🔄
 save_style_symbol = '\U0001f4be'  # 💾
 apply_style_symbol = '\U0001f4cb'  # 📋
 clear_prompt_symbol = '\U0001F5D1'  # 🗑️
+extra_networks_symbol = '\U0001F3B4'  # 🎴
 
 
 def plaintext_to_html(text):
@@ -324,6 +325,8 @@ def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info:
 
 def update_token_counter(text, steps):
     try:
+        text, _ = extra_networks.parse_prompt(text)
+
         _, prompt_flat_list, _ = prompt_parser.get_multicond_prompt_list([text])
         prompt_schedules = prompt_parser.get_learned_conditioning_prompt_schedules(prompt_flat_list, steps)
 
@@ -354,10 +357,10 @@ def create_toprow(is_img2img):
                         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"):
-            paste = gr.Button(value=paste_symbol, elem_id="paste")
-            save_style = gr.Button(value=save_style_symbol, elem_id="style_create")
-            prompt_style_apply = gr.Button(value=apply_style_symbol, elem_id="style_apply")
-            clear_prompt_button = gr.Button(value=clear_prompt_symbol, elem_id=f"{id_part}_clear_prompt")
+            paste = ToolButton(value=paste_symbol, elem_id="paste")
+            clear_prompt_button = ToolButton(value=clear_prompt_symbol, elem_id=f"{id_part}_clear_prompt")
+            extra_networks_button = ToolButton(value=extra_networks_symbol, elem_id=f"{id_part}_extra_networks")
+
             token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_token_counter")
             token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button")
             negative_token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_negative_token_counter")
@@ -395,11 +398,14 @@ def create_toprow(is_img2img):
                     outputs=[],
                 )
 
-            with gr.Row():
+            with gr.Row(elem_id=f"{id_part}_styles_row"):
                 prompt_styles = gr.Dropdown(label="Styles", elem_id=f"{id_part}_styles", choices=[k for k, v in shared.prompt_styles.styles.items()], value=[], multiselect=True)
                 create_refresh_button(prompt_styles, shared.prompt_styles.reload, lambda: {"choices": [k for k, v in shared.prompt_styles.styles.items()]}, f"refresh_{id_part}_styles")
 
-    return prompt, prompt_styles, negative_prompt, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button, negative_token_counter, negative_token_button
+                prompt_style_apply = ToolButton(value=apply_style_symbol, elem_id="style_apply")
+                save_style = ToolButton(value=save_style_symbol, elem_id="style_create")
+
+    return prompt, prompt_styles, negative_prompt, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, extra_networks_button, token_counter, token_button, negative_token_counter, negative_token_button
 
 
 def setup_progressbar(*args, **kwargs):
@@ -616,11 +622,15 @@ def create_ui():
     modules.scripts.scripts_txt2img.initialize_scripts(is_img2img=False)
 
     with gr.Blocks(analytics_enabled=False) as txt2img_interface:
-        txt2img_prompt, txt2img_prompt_styles, txt2img_negative_prompt, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button, negative_token_counter, negative_token_button = create_toprow(is_img2img=False)
+        txt2img_prompt, txt2img_prompt_styles, txt2img_negative_prompt, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, extra_networks_button, token_counter, token_button, negative_token_counter, negative_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="binary", visible=False)
 
+        with FormRow(variant='compact', elem_id="txt2img_extra_networks", visible=False) as extra_networks:
+            from modules import ui_extra_networks
+            extra_networks_ui = ui_extra_networks.create_ui(extra_networks, extra_networks_button, 'txt2img')
+
         with gr.Row().style(equal_height=False):
             with gr.Column(variant='compact', elem_id="txt2img_settings"):
                 for category in ordered_ui_categories():
@@ -794,14 +804,20 @@ def create_ui():
             token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[txt2img_prompt, steps], outputs=[token_counter])
             negative_token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[txt2img_negative_prompt, steps], outputs=[negative_token_counter])
 
+            ui_extra_networks.setup_ui(extra_networks_ui, txt2img_gallery)
+
     modules.scripts.scripts_current = modules.scripts.scripts_img2img
     modules.scripts.scripts_img2img.initialize_scripts(is_img2img=True)
 
     with gr.Blocks(analytics_enabled=False) as img2img_interface:
-        img2img_prompt, img2img_prompt_styles, img2img_negative_prompt, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste, token_counter, token_button, negative_token_counter, negative_token_button = create_toprow(is_img2img=True)
+        img2img_prompt, img2img_prompt_styles, img2img_negative_prompt, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste, extra_networks_button, token_counter, token_button, negative_token_counter, negative_token_button = create_toprow(is_img2img=True)
 
         img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="binary", visible=False)
 
+        with FormRow(variant='compact', elem_id="img2img_extra_networks", visible=False) as extra_networks:
+            from modules import ui_extra_networks
+            extra_networks_ui_img2img = ui_extra_networks.create_ui(extra_networks, extra_networks_button, 'img2img')
+
         with FormRow().style(equal_height=False):
             with gr.Column(variant='compact', elem_id="img2img_settings"):
                 copy_image_buttons = []
@@ -1064,6 +1080,8 @@ def create_ui():
             token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter])
             negative_token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[txt2img_negative_prompt, steps], outputs=[negative_token_counter])
 
+            ui_extra_networks.setup_ui(extra_networks_ui_img2img, img2img_gallery)
+
             img2img_paste_fields = [
                 (img2img_prompt, "Prompt"),
                 (img2img_negative_prompt, "Negative prompt"),
@@ -1666,10 +1684,8 @@ def create_ui():
                 download_localization = gr.Button(value='Download localization template', elem_id="download_localization")
                 reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary', elem_id="settings_reload_script_bodies")
 
-            if os.path.exists("html/licenses.html"):
-                with open("html/licenses.html", encoding="utf8") as file:
-                    with gr.TabItem("Licenses"):
-                        gr.HTML(file.read(), elem_id="licenses")
+            with gr.TabItem("Licenses"):
+                gr.HTML(shared.html("licenses.html"), elem_id="licenses")
 
             gr.Button(value="Show all pages", elem_id="settings_show_all_pages")
 
@@ -1756,11 +1772,9 @@ def create_ui():
         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)
 
-        if os.path.exists("html/footer.html"):
-            with open("html/footer.html", encoding="utf8") as file:
-                footer = file.read()
-                footer = footer.format(versions=versions_html())
-                gr.HTML(footer, elem_id="footer")
+        footer = shared.html("footer.html")
+        footer = footer.format(versions=versions_html())
+        gr.HTML(footer, elem_id="footer")
 
         text_settings = gr.Textbox(elem_id="settings_json", value=lambda: opts.dumpjson(), visible=False)
         settings_submit.click(
diff --git a/modules/ui_components.py b/modules/ui_components.py
index 97acff06..46324425 100644
--- a/modules/ui_components.py
+++ b/modules/ui_components.py
@@ -11,6 +11,16 @@ class ToolButton(gr.Button, gr.components.FormComponent):
         return "button"
 
 
+class ToolButtonTop(gr.Button, gr.components.FormComponent):
+    """Small button with single emoji as text, with extra margin at top, fits inside gradio forms"""
+
+    def __init__(self, **kwargs):
+        super().__init__(variant="tool-top", **kwargs)
+
+    def get_block_name(self):
+        return "button"
+
+
 class FormRow(gr.Row, gr.components.FormComponent):
     """Same as gr.Row but fits inside gradio forms"""
 
diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py
new file mode 100644
index 00000000..253e90f7
--- /dev/null
+++ b/modules/ui_extra_networks.py
@@ -0,0 +1,149 @@
+import os.path
+
+from modules import shared
+import gradio as gr
+import json
+
+from modules.generation_parameters_copypaste import image_from_url_text
+
+extra_pages = []
+
+
+def register_page(page):
+    """registers extra networks page for the UI; recommend doing it in on_app_started() callback for extensions"""
+
+    extra_pages.append(page)
+
+
+class ExtraNetworksPage:
+    def __init__(self, title):
+        self.title = title
+        self.card_page = shared.html("extra-networks-card.html")
+        self.allow_negative_prompt = False
+
+    def refresh(self):
+        pass
+
+    def create_html(self, tabname):
+        items_html = ''
+
+        for item in self.list_items():
+            items_html += self.create_html_for_item(item, tabname)
+
+        if items_html == '':
+            dirs = "".join([f"<li>{x}</li>" for x in self.allowed_directories_for_previews()])
+            items_html = shared.html("extra-networks-no-cards.html").format(dirs=dirs)
+
+        res = "<div class='extra-network-cards'>" + items_html + "</div>"
+
+        return res
+
+    def list_items(self):
+        raise NotImplementedError()
+
+    def allowed_directories_for_previews(self):
+        return []
+
+    def create_html_for_item(self, item, tabname):
+        preview = item.get("preview", None)
+
+        args = {
+            "preview_html": "style='background-image: url(" + json.dumps(preview) + ")'" if preview else '',
+            "prompt": json.dumps(item["prompt"]),
+            "tabname": json.dumps(tabname),
+            "local_preview": json.dumps(item["local_preview"]),
+            "name": item["name"],
+            "allow_negative_prompt": "true" if self.allow_negative_prompt else "false",
+        }
+
+        return self.card_page.format(**args)
+
+
+def intialize():
+    extra_pages.clear()
+
+
+class ExtraNetworksUi:
+    def __init__(self):
+        self.pages = None
+        self.stored_extra_pages = None
+
+        self.button_save_preview = None
+        self.preview_target_filename = None
+
+        self.tabname = None
+
+
+def create_ui(container, button, tabname):
+    ui = ExtraNetworksUi()
+    ui.pages = []
+    ui.stored_extra_pages = extra_pages.copy()
+    ui.tabname = tabname
+
+    with gr.Tabs(elem_id=tabname+"_extra_tabs") as tabs:
+        button_refresh = gr.Button('Refresh', elem_id=tabname+"_extra_refresh")
+        button_close = gr.Button('Close', elem_id=tabname+"_extra_close")
+
+        for page in ui.stored_extra_pages:
+            with gr.Tab(page.title):
+                page_elem = gr.HTML(page.create_html(ui.tabname))
+                ui.pages.append(page_elem)
+
+    ui.button_save_preview = gr.Button('Save preview', elem_id=tabname+"_save_preview", visible=False)
+    ui.preview_target_filename = gr.Textbox('Preview save filename', elem_id=tabname+"_preview_filename", visible=False)
+
+    button.click(fn=lambda: gr.update(visible=True), inputs=[], outputs=[container])
+    button_close.click(fn=lambda: gr.update(visible=False), inputs=[], outputs=[container])
+
+    def refresh():
+        res = []
+
+        for pg in ui.stored_extra_pages:
+            pg.refresh()
+            res.append(pg.create_html(ui.tabname))
+
+        return res
+
+    button_refresh.click(fn=refresh, inputs=[], outputs=ui.pages)
+
+    return ui
+
+
+def path_is_parent(parent_path, child_path):
+    parent_path = os.path.abspath(parent_path)
+    child_path = os.path.abspath(child_path)
+
+    return os.path.commonpath([parent_path]) == os.path.commonpath([parent_path, child_path])
+
+
+def setup_ui(ui, gallery):
+    def save_preview(index, images, filename):
+        if len(images) == 0:
+            print("There is no image in gallery to save as a preview.")
+            return [page.create_html(ui.tabname) for page in ui.stored_extra_pages]
+
+        index = int(index)
+        index = 0 if index < 0 else index
+        index = len(images) - 1 if index >= len(images) else index
+
+        img_info = images[index if index >= 0 else 0]
+        image = image_from_url_text(img_info)
+
+        is_allowed = False
+        for extra_page in ui.stored_extra_pages:
+            if any([path_is_parent(x, filename) for x in extra_page.allowed_directories_for_previews()]):
+                is_allowed = True
+                break
+
+        assert is_allowed, f'writing to {filename} is not allowed'
+
+        image.save(filename)
+
+        return [page.create_html(ui.tabname) for page in ui.stored_extra_pages]
+
+    ui.button_save_preview.click(
+        fn=save_preview,
+        _js="function(x, y, z){console.log(x, y, z); return [selected_gallery_index(), y, z]}",
+        inputs=[ui.preview_target_filename, gallery, ui.preview_target_filename],
+        outputs=[*ui.pages]
+    )
diff --git a/modules/ui_extra_networks_hypernets.py b/modules/ui_extra_networks_hypernets.py
new file mode 100644
index 00000000..312dbaf0
--- /dev/null
+++ b/modules/ui_extra_networks_hypernets.py
@@ -0,0 +1,34 @@
+import os
+
+from modules import shared, ui_extra_networks
+
+
+class ExtraNetworksPageHypernetworks(ui_extra_networks.ExtraNetworksPage):
+    def __init__(self):
+        super().__init__('Hypernetworks')
+
+    def refresh(self):
+        shared.reload_hypernetworks()
+
+    def list_items(self):
+        for name, path in shared.hypernetworks.items():
+            path, ext = os.path.splitext(path)
+            previews = [path + ".png", path + ".preview.png"]
+
+            preview = None
+            for file in previews:
+                if os.path.isfile(file):
+                    preview = "./file=" + file.replace('\\', '/') + "?mtime=" + str(os.path.getmtime(file))
+                    break
+
+            yield {
+                "name": name,
+                "filename": path,
+                "preview": preview,
+                "prompt": f"<hypernet:{name}:1.0>",
+                "local_preview": path + ".png",
+            }
+
+    def allowed_directories_for_previews(self):
+        return [shared.cmd_opts.hypernetwork_dir]
+
diff --git a/modules/ui_extra_networks_textual_inversion.py b/modules/ui_extra_networks_textual_inversion.py
new file mode 100644
index 00000000..e4a6e3bf
--- /dev/null
+++ b/modules/ui_extra_networks_textual_inversion.py
@@ -0,0 +1,32 @@
+import os
+
+from modules import ui_extra_networks, sd_hijack
+
+
+class ExtraNetworksPageTextualInversion(ui_extra_networks.ExtraNetworksPage):
+    def __init__(self):
+        super().__init__('Textual Inversion')
+        self.allow_negative_prompt = True
+
+    def refresh(self):
+        sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings(force_reload=True)
+
+    def list_items(self):
+        for embedding in sd_hijack.model_hijack.embedding_db.word_embeddings.values():
+            path, ext = os.path.splitext(embedding.filename)
+            preview_file = path + ".preview.png"
+
+            preview = None
+            if os.path.isfile(preview_file):
+                preview = "./file=" + preview_file.replace('\\', '/') + "?mtime=" + str(os.path.getmtime(preview_file))
+
+            yield {
+                "name": embedding.name,
+                "filename": embedding.filename,
+                "preview": preview,
+                "prompt": embedding.name,
+                "local_preview": path + ".preview.png",
+            }
+
+    def allowed_directories_for_previews(self):
+        return list(sd_hijack.model_hijack.embedding_db.embedding_dirs)
diff --git a/script.js b/script.js
index 3345e32b..97e0bfcf 100644
--- a/script.js
+++ b/script.js
@@ -13,6 +13,7 @@ function get_uiCurrentTabContent() {
 }
 
 uiUpdateCallbacks = []
+uiLoadedCallbacks = []
 uiTabChangeCallbacks = []
 optionsChangedCallbacks = []
 let uiCurrentTab = null
@@ -20,6 +21,9 @@ let uiCurrentTab = null
 function onUiUpdate(callback){
     uiUpdateCallbacks.push(callback)
 }
+function onUiLoaded(callback){
+    uiLoadedCallbacks.push(callback)
+}
 function onUiTabChange(callback){
     uiTabChangeCallbacks.push(callback)
 }
@@ -38,8 +42,15 @@ function executeCallbacks(queue, m) {
     queue.forEach(function(x){runCallback(x, m)})
 }
 
+var executedOnLoaded = false;
+
 document.addEventListener("DOMContentLoaded", function() {
     var mutationObserver = new MutationObserver(function(m){
+        if(!executedOnLoaded && gradioApp().querySelector('#txt2img_prompt')){
+            executedOnLoaded = true;
+            executeCallbacks(uiLoadedCallbacks);
+        }
+
         executeCallbacks(uiUpdateCallbacks, m);
         const newTab = get_uiCurrentTab();
         if ( newTab && ( newTab !== uiCurrentTab ) ) {
@@ -53,7 +64,7 @@ document.addEventListener("DOMContentLoaded", function() {
 /**
  * Add a ctrl+enter as a shortcut to start a generation
  */
- document.addEventListener('keydown', function(e) {
+document.addEventListener('keydown', function(e) {
     var handled = false;
     if (e.key !== undefined) {
         if((e.key == "Enter" && (e.metaKey || e.ctrlKey || e.altKey))) handled = true;
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 6629f5d5..b1badec9 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -11,7 +11,6 @@ import modules.scripts as scripts
 import gradio as gr
 
 from modules import images, paths, sd_samplers, processing, sd_models, sd_vae
-from modules.hypernetworks import hypernetwork
 from modules.processing import process_images, Processed, StableDiffusionProcessingTxt2Img
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
@@ -94,28 +93,6 @@ def confirm_checkpoints(p, xs):
             raise RuntimeError(f"Unknown checkpoint: {x}")
 
 
-def apply_hypernetwork(p, x, xs):
-    if x.lower() in ["", "none"]:
-        name = None
-    else:
-        name = hypernetwork.find_closest_hypernetwork_name(x)
-        if not name:
-            raise RuntimeError(f"Unknown hypernetwork: {x}")
-    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"]:
-            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
 
@@ -208,8 +185,6 @@ axis_options = [
     AxisOption("Prompt order", str_permutations, apply_order, format_value=format_value_join_list),
     AxisOption("Sampler", str, apply_sampler, format_value=format_value, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.samplers]),
     AxisOption("Checkpoint name", str, apply_checkpoint, format_value=format_value, confirm=confirm_checkpoints, cost=1.0, choices=lambda: list(sd_models.checkpoints_list)),
-    AxisOption("Hypernetwork", str, apply_hypernetwork, format_value=format_value, confirm=confirm_hypernetworks, cost=0.2, choices=lambda: list(shared.hypernetworks)),
-    AxisOption("Hypernet str.", float, apply_hypernetwork_strength),
     AxisOption("Sigma Churn", float, apply_field("s_churn")),
     AxisOption("Sigma min", float, apply_field("s_tmin")),
     AxisOption("Sigma max", float, apply_field("s_tmax")),
@@ -291,7 +266,6 @@ def draw_xy_grid(p, xs, ys, x_labels, y_labels, cell, draw_legend, include_lone_
 class SharedSettingsStackHelper(object):
     def __enter__(self):
         self.CLIP_stop_at_last_layers = opts.CLIP_stop_at_last_layers
-        self.hypernetwork = opts.sd_hypernetwork
         self.vae = opts.sd_vae
   
     def __exit__(self, exc_type, exc_value, tb):
@@ -299,9 +273,6 @@ class SharedSettingsStackHelper(object):
         modules.sd_models.reload_model_weights()
         modules.sd_vae.reload_vae_weights()
 
-        hypernetwork.load_hypernetwork(self.hypernetwork)
-        hypernetwork.apply_strength()
-
         opts.data["CLIP_stop_at_last_layers"] = self.CLIP_stop_at_last_layers
 
 
diff --git a/style.css b/style.css
index 3a515ebd..5e8bc2ca 100644
--- a/style.css
+++ b/style.css
@@ -132,13 +132,6 @@
 }
 
 #roll_col > button {
-    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;
 }
 
@@ -146,9 +139,10 @@
     min-width: 0 !important;
     max-width: 8em !important;
     margin-right: 1em;
+    gap: 0;
 }
 #interrogate, #deepbooru{
-    margin: 0em 0.25em 0.9em 0.25em;
+    margin: 0em 0.25em 0.5em 0.25em;
     min-width: 8em;
     max-width: 8em;
 }
@@ -157,8 +151,17 @@
     min-width: 8em !important;
 }
 
+#txt2img_styles_row, #img2img_styles_row{
+    gap: 0.25em;
+    margin-top: 0.5em;
+}
+
+#txt2img_styles_row > button, #img2img_styles_row > button{
+    margin: 0;
+}
+
 #txt2img_styles, #img2img_styles{
-    margin-top: 1em;
+    padding: 0;
 }
 
 #txt2img_styles ul, #img2img_styles ul{
@@ -635,17 +638,21 @@ canvas[key="mask"] {
     background-color: rgb(31 41 55 / var(--tw-bg-opacity));
 }
 
-.gr-button-tool{
+.gr-button-tool, .gr-button-tool-top{
     max-width: 2.5em;
     min-width: 2.5em !important;
     height: 2.4em;
-    margin: 1.6em 0.7em 0.55em 0;
 }
 
-#tab_modelmerger .gr-button-tool{
+.gr-button-tool{
     margin: 0.6em 0em 0.55em 0;
 }
 
+.gr-button-tool-top, #settings .gr-button-tool{
+    margin: 1.6em 0.7em 0.55em 0;
+}
+
+
 #modelmerger_results_container{
     margin-top: 1em;
     overflow: visible;
@@ -763,81 +770,88 @@ footer {
     line-height: 2.4em;
 }
 
-/* The following handles localization for right-to-left (RTL) languages like Arabic.
-The rtl media type will only be activated by the logic in javascript/localization.js.
-If you change anything above, you need to make sure it is RTL compliant by just running
-your changes through converters like https://cssjanus.github.io/ or https://rtlcss.com/.
-Then, you will need to add the RTL counterpart only if needed in the rtl section below.*/
-@media rtl {
-    /* this part was added manually */
-    :host {
-        direction: rtl;
-    }
-    select, .file-preview, .gr-text-input, .output-html:has(.performance), #ti_progress {
-        direction: ltr;
-    }
-    #script_list > label > select,
-    #x_type > label > select,
-    #y_type > label > select {
-        direction: rtl;
-    }
-    .gr-radio, .gr-checkbox{
-        margin-left: 0.25em;
-    }
+#txt2img_extra_networks, #img2img_extra_networks{
+    margin-top: -1em;
+}
 
-    /* automatically generated with few manual modifications */
-    .performance .time {
-        margin-right: unset;
-        margin-left: 0;
-    }
-    .justify-center.overflow-x-scroll {
-        justify-content: right;
-    }
-    .justify-center.overflow-x-scroll button:first-of-type {
-        margin-left: unset;
-        margin-right: auto;
-    }
-    .justify-center.overflow-x-scroll button:last-of-type {
-        margin-right: unset;
-        margin-left: auto;
-    }
-    #settings fieldset span.text-gray-500, #settings .gr-block.gr-box span.text-gray-500, #settings label.block span{
-        margin-right: unset;
-        margin-left: 8em;
-    }
-    #txt2img_progressbar, #img2img_progressbar, #ti_progressbar{
-        right: unset;
-        left: 0;
-    }
-    .progressDiv .progress{
-        padding: 0 0 0 8px;
-        text-align: left;
-    }
-    #lightboxModal{
-        left: unset;
-        right: 0;
-    }
-    .modalPrev, .modalNext{
-        border-radius: 3px 0 0 3px;
-    }
-    .modalNext {
-        right: unset;
-        left: 0;
-        border-radius: 0 3px 3px 0;
-    }
-    #imageARPreview{
-        left:unset;
-        right:0px;
-    }
-    #txt2img_skip, #img2img_skip{
-        right: unset;
-        left: 0px;
-    }
-    #context-menu{
-        box-shadow:-1px 1px 2px #CE6400;
-    }
-    .gr-box > div > div > input.gr-text-input{
-        right: unset;
-        left: 0.5em;
-    }
+.extra-networks > div > [id *= '_extra_']{
+    margin: 0.3em;
 }
+
+.extra-network-cards .nocards{
+    margin: 1.25em 0.5em 0.5em 0.5em;
+}
+
+.extra-network-cards .nocards h1{
+    font-size: 1.5em;
+    margin-bottom: 1em;
+}
+
+.extra-network-cards .nocards li{
+    margin-left: 0.5em;
+}
+
+.extra-network-cards .card{
+    display: inline-block;
+    margin: 0.5em;
+    width: 16em;
+    height: 24em;
+    box-shadow: 0 0 5px rgba(128, 128, 128, 0.5);
+    border-radius: 0.2em;
+    position: relative;
+
+    background-size: auto 100%;
+    background-position: center;
+    overflow: hidden;
+    cursor: pointer;
+
+    background-image: url('./file=html/card-no-preview.png')
+}
+
+.extra-network-cards .card:hover{
+    box-shadow: 0 0 2px 0.3em rgba(0, 128, 255, 0.35);
+}
+
+.extra-network-cards .card .actions .additional{
+    display: none;
+}
+
+.extra-network-cards .card .actions{
+    position: absolute;
+    bottom: 0;
+    left: 0;
+    right: 0;
+    padding: 0.5em;
+    color: white;
+    background: rgba(0,0,0,0.5);
+    box-shadow: 0 0 0.25em 0.25em rgba(0,0,0,0.5);
+    text-shadow: 0 0 0.2em black;
+}
+
+.extra-network-cards .card .actions:hover{
+    box-shadow: 0 0 0.75em 0.75em rgba(0,0,0,0.5) !important;
+}
+
+.extra-network-cards .card .actions .name{
+    font-size: 1.7em;
+    font-weight: bold;
+    line-break: anywhere;
+}
+
+.extra-network-cards .card .actions:hover .additional{
+    display: block;
+}
+
+.extra-network-cards .card ul{
+    margin: 0.25em 0 0.75em 0.25em;
+    cursor: unset;
+}
+
+.extra-network-cards .card ul a{
+    cursor: pointer;
+}
+
+.extra-network-cards .card ul a:hover{
+    color: red;
+}
+
diff --git a/webui.py b/webui.py
index 865a7300..e8dd822a 100644
--- a/webui.py
+++ b/webui.py
@@ -9,16 +9,18 @@ from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.middleware.gzip import GZipMiddleware
 
-from modules import import_hook, errors
+from modules import import_hook, errors, extra_networks
+from modules import extra_networks_hypernet, ui_extra_networks_hypernets, ui_extra_networks_textual_inversion
 from modules.call_queue import wrap_queued_call, queue_lock, wrap_gradio_gpu_call
 from modules.paths import script_path
 
 import torch
+
 # Truncate version number of nightly/local build of PyTorch to not cause exceptions with CodeFormer or Safetensors
 if ".dev" in torch.__version__ or "+git" in torch.__version__:
     torch.__version__ = re.search(r'[\d.]+[\d]', torch.__version__).group(0)
 
-from modules import shared, devices, sd_samplers, upscaler, extensions, localization, ui_tempdir
+from modules import shared, devices, sd_samplers, upscaler, extensions, localization, ui_tempdir, ui_extra_networks
 import modules.codeformer_model as codeformer
 import modules.extras
 import modules.face_restoration
@@ -84,10 +86,17 @@ def initialize():
     shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights()))
     shared.opts.onchange("sd_vae", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)
     shared.opts.onchange("sd_vae_as_default", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)
-    shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: shared.reload_hypernetworks()))
-    shared.opts.onchange("sd_hypernetwork_strength", modules.hypernetworks.hypernetwork.apply_strength)
     shared.opts.onchange("temp_dir", ui_tempdir.on_tmpdir_changed)
 
+    shared.reload_hypernetworks()
+
+    ui_extra_networks.intialize()
+    ui_extra_networks.register_page(ui_extra_networks_textual_inversion.ExtraNetworksPageTextualInversion())
+    ui_extra_networks.register_page(ui_extra_networks_hypernets.ExtraNetworksPageHypernetworks())
+
+    extra_networks.initialize()
+    extra_networks.register_extra_network(extra_networks_hypernet.ExtraNetworkHypernet())
+
     if cmd_opts.tls_keyfile is not None and cmd_opts.tls_keyfile is not None:
 
         try:
@@ -209,6 +218,15 @@ def webui():
 
         modules.sd_models.list_models()
 
+        shared.reload_hypernetworks()
+
+        ui_extra_networks.intialize()
+        ui_extra_networks.register_page(ui_extra_networks_textual_inversion.ExtraNetworksPageTextualInversion())
+        ui_extra_networks.register_page(ui_extra_networks_hypernets.ExtraNetworksPageHypernetworks())
+
+        extra_networks.initialize()
+        extra_networks.register_extra_network(extra_networks_hypernet.ExtraNetworkHypernet())
+
 
 if __name__ == "__main__":
     if cmd_opts.nowebui:
-- 
cgit v1.2.3


From 855b9e3d1c5a1bd8c2d815d38a38bc7c410be5a8 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 21 Jan 2023 16:15:53 +0300
Subject: Lora support! update readme to reflect some recent changes

---
 README.md                                         |  14 +-
 extensions-builtin/Lora/extra_networks_lora.py    |  20 +++
 extensions-builtin/Lora/lora.py                   | 198 ++++++++++++++++++++++
 extensions-builtin/Lora/scripts/lora_script.py    |  30 ++++
 extensions-builtin/Lora/ui_extra_networks_lora.py |  35 ++++
 modules/extra_networks_hypernet.py                |   2 +-
 modules/script_callbacks.py                       |  15 ++
 modules/ui_extra_networks.py                      |   2 +-
 webui.py                                          |   2 +
 9 files changed, 314 insertions(+), 4 deletions(-)
 create mode 100644 extensions-builtin/Lora/extra_networks_lora.py
 create mode 100644 extensions-builtin/Lora/lora.py
 create mode 100644 extensions-builtin/Lora/scripts/lora_script.py
 create mode 100644 extensions-builtin/Lora/ui_extra_networks_lora.py

(limited to 'webui.py')

diff --git a/README.md b/README.md
index 1ac794e8..9c0cd1ef 100644
--- a/README.md
+++ b/README.md
@@ -51,6 +51,7 @@ A browser interface based on Gradio library for Stable Diffusion.
 - Possible to change defaults/mix/max/step values for UI elements via text config
 - Tiling support, a checkbox to create images that can be tiled like textures
 - Progress bar and live image generation preview
+    - Can use a separate neural network to produce previews with almost none VRAM or compute requirement
 - Negative prompt, an extra text field that allows you to list what you don't want to see in generated image
 - Styles, a way to save part of prompt and easily apply them via dropdown later
 - Variations, a way to generate same image but with tiny differences
@@ -75,13 +76,22 @@ A browser interface based on Gradio library for Stable Diffusion.
      - hypernetworks and embeddings options
      - Preprocessing images: cropping, mirroring, autotagging using BLIP or deepdanbooru (for anime)
 - Clip skip
-- Use Hypernetworks
-- Use VAEs
+- Hypernetworks
+- Loras (same as Hypernetworks but more pretty)
+- A sparate UI where you can choose, with preview, which embeddings, hypernetworks or Loras to add to your prompt. 
+- Can select to load a different VAE from settings screen
 - Estimated completion time in progress bar
 - API
 - Support for dedicated [inpainting model](https://github.com/runwayml/stable-diffusion#inpainting-with-stable-diffusion) by RunwayML.
 - via extension: [Aesthetic Gradients](https://github.com/AUTOMATIC1111/stable-diffusion-webui-aesthetic-gradients), a way to generate images with a specific aesthetic by using clip images embeds (implementation of [https://github.com/vicgalle/stable-diffusion-aesthetic-gradients](https://github.com/vicgalle/stable-diffusion-aesthetic-gradients))
 - [Stable Diffusion 2.0](https://github.com/Stability-AI/stablediffusion) support - see [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#stable-diffusion-20) for instructions
+- [Alt-Diffusion](https://arxiv.org/abs/2211.06679) support - see [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#alt-diffusion) for instructions
+- Now without any bad letters!
+- Load checkpoints in safetensors format
+- Eased resolution restriction: generated image's domension must be a multiple of 8 rather than 64
+- Now with a license!
+- Reorder elements in the UI from settings screen
+- 
 
 ## 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/extensions-builtin/Lora/extra_networks_lora.py b/extensions-builtin/Lora/extra_networks_lora.py
new file mode 100644
index 00000000..8f2e753e
--- /dev/null
+++ b/extensions-builtin/Lora/extra_networks_lora.py
@@ -0,0 +1,20 @@
+from modules import extra_networks
+import lora
+
+class ExtraNetworkLora(extra_networks.ExtraNetwork):
+    def __init__(self):
+        super().__init__('lora')
+
+    def activate(self, p, params_list):
+        names = []
+        multipliers = []
+        for params in params_list:
+            assert len(params.items) > 0
+
+            names.append(params.items[0])
+            multipliers.append(float(params.items[1]) if len(params.items) > 1 else 1.0)
+
+        lora.load_loras(names, multipliers)
+
+    def deactivate(self, p):
+        pass
diff --git a/extensions-builtin/Lora/lora.py b/extensions-builtin/Lora/lora.py
new file mode 100644
index 00000000..7a3ad9a9
--- /dev/null
+++ b/extensions-builtin/Lora/lora.py
@@ -0,0 +1,198 @@
+import glob
+import os
+import re
+import torch
+
+from modules import shared, devices, sd_models
+
+re_digits = re.compile(r"\d+")
+re_unet_down_blocks = re.compile(r"lora_unet_down_blocks_(\d+)_attentions_(\d+)_(.+)")
+re_unet_mid_blocks = re.compile(r"lora_unet_mid_block_attentions_(\d+)_(.+)")
+re_unet_up_blocks = re.compile(r"lora_unet_up_blocks_(\d+)_attentions_(\d+)_(.+)")
+re_text_block = re.compile(r"lora_te_text_model_encoder_layers_(\d+)_(.+)")
+
+
+def convert_diffusers_name_to_compvis(key):
+    def match(match_list, regex):
+        r = re.match(regex, key)
+        if not r:
+            return False
+
+        match_list.clear()
+        match_list.extend([int(x) if re.match(re_digits, x) else x for x in r.groups()])
+        return True
+
+    m = []
+
+    if match(m, re_unet_down_blocks):
+        return f"diffusion_model_input_blocks_{1 + m[0] * 3 + m[1]}_1_{m[2]}"
+
+    if match(m, re_unet_mid_blocks):
+        return f"diffusion_model_middle_block_1_{m[1]}"
+
+    if match(m, re_unet_up_blocks):
+        return f"diffusion_model_output_blocks_{m[0] * 3 + m[1]}_1_{m[2]}"
+
+    if match(m, re_text_block):
+        return f"transformer_text_model_encoder_layers_{m[0]}_{m[1]}"
+
+    return key
+
+
+class LoraOnDisk:
+    def __init__(self, name, filename):
+        self.name = name
+        self.filename = filename
+
+
+class LoraModule:
+    def __init__(self, name):
+        self.name = name
+        self.multiplier = 1.0
+        self.modules = {}
+        self.mtime = None
+
+
+class LoraUpDownModule:
+    def __init__(self):
+        self.up = None
+        self.down = None
+
+
+def assign_lora_names_to_compvis_modules(sd_model):
+    lora_layer_mapping = {}
+
+    for name, module in shared.sd_model.cond_stage_model.wrapped.named_modules():
+        lora_name = name.replace(".", "_")
+        lora_layer_mapping[lora_name] = module
+        module.lora_layer_name = lora_name
+
+    for name, module in shared.sd_model.model.named_modules():
+        lora_name = name.replace(".", "_")
+        lora_layer_mapping[lora_name] = module
+        module.lora_layer_name = lora_name
+
+    sd_model.lora_layer_mapping = lora_layer_mapping
+
+
+def load_lora(name, filename):
+    lora = LoraModule(name)
+    lora.mtime = os.path.getmtime(filename)
+
+    sd = sd_models.read_state_dict(filename)
+
+    keys_failed_to_match = []
+
+    for key_diffusers, weight in sd.items():
+        fullkey = convert_diffusers_name_to_compvis(key_diffusers)
+        key, lora_key = fullkey.split(".", 1)
+
+        sd_module = shared.sd_model.lora_layer_mapping.get(key, None)
+        if sd_module is None:
+            keys_failed_to_match.append(key_diffusers)
+            continue
+
+        if type(sd_module) == torch.nn.Linear:
+            module = torch.nn.Linear(weight.shape[1], weight.shape[0], bias=False)
+        elif type(sd_module) == torch.nn.Conv2d:
+            module = torch.nn.Conv2d(weight.shape[1], weight.shape[0], (1, 1), bias=False)
+        else:
+            assert False, f'Lora layer {key_diffusers} matched a layer with unsupported type: {type(sd_module).__name__}'
+
+        with torch.no_grad():
+            module.weight.copy_(weight)
+
+        module.to(device=devices.device, dtype=devices.dtype)
+
+        lora_module = lora.modules.get(key, None)
+        if lora_module is None:
+            lora_module = LoraUpDownModule()
+            lora.modules[key] = lora_module
+
+        if lora_key == "lora_up.weight":
+            lora_module.up = module
+        elif lora_key == "lora_down.weight":
+            lora_module.down = module
+        else:
+            assert False, f'Bad Lora layer name: {key_diffusers} - must end in lora_up.weight or lora_down.weight'
+
+    if len(keys_failed_to_match) > 0:
+        print(f"Failed to match keys when loading Lora {filename}: {keys_failed_to_match}")
+
+    return lora
+
+
+def load_loras(names, multipliers=None):
+    already_loaded = {}
+
+    for lora in loaded_loras:
+        if lora.name in names:
+            already_loaded[lora.name] = lora
+
+    loaded_loras.clear()
+
+    loras_on_disk = [available_loras.get(name, None) for name in names]
+    if any([x is None for x in loras_on_disk]):
+        list_available_loras()
+
+        loras_on_disk = [available_loras.get(name, None) for name in names]
+
+    for i, name in enumerate(names):
+        lora = already_loaded.get(name, None)
+
+        lora_on_disk = loras_on_disk[i]
+        if lora_on_disk is not None:
+            if lora is None or os.path.getmtime(lora_on_disk.filename) > lora.mtime:
+                lora = load_lora(name, lora_on_disk.filename)
+
+        if lora is None:
+            print(f"Couldn't find Lora with name {name}")
+            continue
+
+        lora.multiplier = multipliers[i] if multipliers else 1.0
+        loaded_loras.append(lora)
+
+
+def lora_forward(module, input, res):
+    if len(loaded_loras) == 0:
+        return res
+
+    lora_layer_name = getattr(module, 'lora_layer_name', None)
+    for lora in loaded_loras:
+        module = lora.modules.get(lora_layer_name, None)
+        if module is not None:
+            res = res + module.up(module.down(input)) * lora.multiplier
+
+    return res
+
+
+def lora_Linear_forward(self, input):
+    return lora_forward(self, input, torch.nn.Linear_forward_before_lora(self, input))
+
+
+def lora_Conv2d_forward(self, input):
+    return lora_forward(self, input, torch.nn.Conv2d_forward_before_lora(self, input))
+
+
+def list_available_loras():
+    available_loras.clear()
+
+    os.makedirs(lora_dir, exist_ok=True)
+
+    candidates = glob.glob(os.path.join(lora_dir, '**/*.pt'), recursive=True) + glob.glob(os.path.join(lora_dir, '**/*.safetensors'), recursive=True)
+
+    for filename in sorted(candidates):
+        if os.path.isdir(filename):
+            continue
+
+        name = os.path.splitext(os.path.basename(filename))[0]
+
+        available_loras[name] = LoraOnDisk(name, filename)
+
+
+lora_dir = os.path.join(shared.models_path, "Lora")
+available_loras = {}
+loaded_loras = []
+
+list_available_loras()
+
diff --git a/extensions-builtin/Lora/scripts/lora_script.py b/extensions-builtin/Lora/scripts/lora_script.py
new file mode 100644
index 00000000..60b9eb64
--- /dev/null
+++ b/extensions-builtin/Lora/scripts/lora_script.py
@@ -0,0 +1,30 @@
+import torch
+
+import lora
+import extra_networks_lora
+import ui_extra_networks_lora
+from modules import script_callbacks, ui_extra_networks, extra_networks
+
+
+def unload():
+    torch.nn.Linear.forward = torch.nn.Linear_forward_before_lora
+    torch.nn.Conv2d.forward = torch.nn.Conv2d_forward_before_lora
+
+
+def before_ui():
+    ui_extra_networks.register_page(ui_extra_networks_lora.ExtraNetworksPageLora())
+    extra_networks.register_extra_network(extra_networks_lora.ExtraNetworkLora())
+
+
+if not hasattr(torch.nn, 'Linear_forward_before_lora'):
+    torch.nn.Linear_forward_before_lora = torch.nn.Linear.forward
+
+if not hasattr(torch.nn, 'Conv2d_forward_before_lora'):
+    torch.nn.Conv2d_forward_before_lora = torch.nn.Conv2d.forward
+
+torch.nn.Linear.forward = lora.lora_Linear_forward
+torch.nn.Conv2d.forward = lora.lora_Conv2d_forward
+
+script_callbacks.on_model_loaded(lora.assign_lora_names_to_compvis_modules)
+script_callbacks.on_script_unloaded(unload)
+script_callbacks.on_before_ui(before_ui)
diff --git a/extensions-builtin/Lora/ui_extra_networks_lora.py b/extensions-builtin/Lora/ui_extra_networks_lora.py
new file mode 100644
index 00000000..65397890
--- /dev/null
+++ b/extensions-builtin/Lora/ui_extra_networks_lora.py
@@ -0,0 +1,35 @@
+import os
+import lora
+
+from modules import shared, ui_extra_networks
+
+
+class ExtraNetworksPageLora(ui_extra_networks.ExtraNetworksPage):
+    def __init__(self):
+        super().__init__('Lora')
+
+    def refresh(self):
+        lora.list_available_loras()
+
+    def list_items(self):
+        for name, lora_on_disk in lora.available_loras.items():
+            path, ext = os.path.splitext(lora_on_disk.filename)
+            previews = [path + ".png", path + ".preview.png"]
+
+            preview = None
+            for file in previews:
+                if os.path.isfile(file):
+                    preview = "./file=" + file.replace('\\', '/') + "?mtime=" + str(os.path.getmtime(file))
+                    break
+
+            yield {
+                "name": name,
+                "filename": path,
+                "preview": preview,
+                "prompt": f"<lora:{name}:1.0>",
+                "local_preview": path + ".png",
+            }
+
+    def allowed_directories_for_previews(self):
+        return [lora.lora_dir]
+
diff --git a/modules/extra_networks_hypernet.py b/modules/extra_networks_hypernet.py
index 6a0c4ba8..ff279a1f 100644
--- a/modules/extra_networks_hypernet.py
+++ b/modules/extra_networks_hypernet.py
@@ -17,5 +17,5 @@ class ExtraNetworkHypernet(extra_networks.ExtraNetwork):
 
         hypernetwork.load_hypernetworks(names, multipliers)
 
-    def deactivate(p, self):
+    def deactivate(self, p):
         pass
diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py
index a9e19236..4bb45ec7 100644
--- a/modules/script_callbacks.py
+++ b/modules/script_callbacks.py
@@ -73,6 +73,7 @@ callback_map = dict(
     callbacks_image_grid=[],
     callbacks_infotext_pasted=[],
     callbacks_script_unloaded=[],
+    callbacks_before_ui=[],
 )
 
 
@@ -189,6 +190,14 @@ def script_unloaded_callback():
             report_exception(c, 'script_unloaded')
 
 
+def before_ui_callback():
+    for c in reversed(callback_map['callbacks_before_ui']):
+        try:
+            c.callback()
+        except Exception:
+            report_exception(c, 'before_ui')
+
+
 def add_callback(callbacks, fun):
     stack = [x for x in inspect.stack() if x.filename != __file__]
     filename = stack[0].filename if len(stack) > 0 else 'unknown file'
@@ -313,3 +322,9 @@ def on_script_unloaded(callback):
     the script did should be reverted here"""
 
     add_callback(callback_map['callbacks_script_unloaded'], callback)
+
+
+def on_before_ui(callback):
+    """register a function to be called before the UI is created."""
+
+    add_callback(callback_map['callbacks_before_ui'], callback)
diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py
index 253e90f7..796e879c 100644
--- a/modules/ui_extra_networks.py
+++ b/modules/ui_extra_networks.py
@@ -10,7 +10,7 @@ extra_pages = []
 
 
 def register_page(page):
-    """registers extra networks page for the UI; recommend doing it in on_app_started() callback for extensions"""
+    """registers extra networks page for the UI; recommend doing it in on_before_ui() callback for extensions"""
 
     extra_pages.append(page)
 
diff --git a/webui.py b/webui.py
index e8dd822a..88d04840 100644
--- a/webui.py
+++ b/webui.py
@@ -165,6 +165,8 @@ def webui():
         if shared.opts.clean_temp_dir_at_start:
             ui_tempdir.cleanup_tmpdr()
 
+        modules.script_callbacks.before_ui_callback()
+
         shared.demo = modules.ui.create_ui()
 
         app, local_url, share_url = shared.demo.launch(
-- 
cgit v1.2.3


From 63b824376c49013880ff44c260ea426e2899511e Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 21 Jan 2023 18:47:54 +0300
Subject: add --gradio-queue option to enable gradio queue

---
 modules/shared.py | 2 ++
 webui.py          | 3 +++
 2 files changed, 5 insertions(+)

(limited to 'webui.py')

diff --git a/modules/shared.py b/modules/shared.py
index 72fb1934..52bbb807 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -100,6 +100,8 @@ parser.add_argument("--cors-allow-origins-regex", type=str, help="Allowed CORS o
 parser.add_argument("--tls-keyfile", type=str, help="Partially enables TLS, requires --tls-certfile to fully function", default=None)
 parser.add_argument("--tls-certfile", type=str, help="Partially enables TLS, requires --tls-keyfile to fully function", default=None)
 parser.add_argument("--server-name", type=str, help="Sets hostname of server", default=None)
+parser.add_argument("--gradio-queue", action='store_true', help="Uses gradio queue; experimental option; breaks restart UI button")
+
 
 script_loading.preload_extensions(extensions.extensions_dir, parser)
 script_loading.preload_extensions(extensions.extensions_builtin_dir, parser)
diff --git a/webui.py b/webui.py
index 88d04840..d235da74 100644
--- a/webui.py
+++ b/webui.py
@@ -169,6 +169,9 @@ def webui():
 
         shared.demo = modules.ui.create_ui()
 
+        if cmd_opts.gradio_queue:
+            shared.demo.queue(64)
+
         app, local_url, share_url = shared.demo.launch(
             share=cmd_opts.share,
             server_name=server_name,
-- 
cgit v1.2.3


From 68303c96e5ab31576a8238a24bf5b6191cf16ed1 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 22 Jan 2023 15:38:39 +0300
Subject: split oversize extras.py to postprocessing.py

---
 modules/extras.py         | 217 +-------------------------------------
 modules/postprocessing.py | 257 +---------------------------------------------
 modules/ui.py             |  10 +-
 modules/ui_components.py  |   7 ++
 webui.py                  |   1 -
 5 files changed, 18 insertions(+), 474 deletions(-)

(limited to 'webui.py')

diff --git a/modules/extras.py b/modules/extras.py
index 385430dc..f04ddfc2 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -1,231 +1,16 @@
-from __future__ import annotations
-import math
 import os
 import re
-import sys
-import traceback
 import shutil
 
-import numpy as np
-from PIL import Image
 
 import torch
 import tqdm
 
-from typing import Callable, List, OrderedDict, Tuple
-from functools import partial
-from dataclasses import dataclass
-
-from modules import processing, shared, images, devices, sd_models, sd_samplers, sd_vae
-from modules.shared import opts
-import modules.gfpgan_model
+from modules import shared, images, sd_models, sd_vae
 from modules.ui import plaintext_to_html
-import modules.codeformer_model
 import gradio as gr
 import safetensors.torch
 
-class LruCache(OrderedDict):
-    @dataclass(frozen=True)
-    class Key:
-        image_hash: int
-        info_hash: int
-        args_hash: int
-
-    @dataclass
-    class Value:
-        image: Image.Image
-        info: str
-
-    def __init__(self, max_size: int = 5, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-        self._max_size = max_size
-
-    def get(self, key: LruCache.Key) -> LruCache.Value:
-        ret = super().get(key)
-        if ret is not None:
-            self.move_to_end(key)  # Move to end of eviction list
-        return ret
-
-    def put(self, key: LruCache.Key, value: LruCache.Value) -> None:
-        self[key] = value
-        while len(self) > self._max_size:
-            self.popitem(last=False)
-
-
-cached_images: LruCache = LruCache(max_size=5)
-
-
-def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_dir, show_extras_results, 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, upscale_first: bool, save_output: bool = True):
-    devices.torch_gc()
-
-    shared.state.begin()
-    shared.state.job = 'extras'
-
-    imageArr = []
-    # Also keep track of original file names
-    imageNameArr = []
-    outputs = []
-
-    if extras_mode == 1:
-        #convert file to pillow image
-        for img in image_folder:
-            image = Image.open(img)
-            imageArr.append(image)
-            imageNameArr.append(os.path.splitext(img.orig_name)[0])
-    elif extras_mode == 2:
-        assert not shared.cmd_opts.hide_ui_dir_config, '--hide-ui-dir-config option must be disabled'
-
-        if input_dir == '':
-            return outputs, "Please select an input directory.", ''
-        image_list = shared.listfiles(input_dir)
-        for img in image_list:
-            try:
-                image = Image.open(img)
-            except Exception:
-                continue
-            imageArr.append(image)
-            imageNameArr.append(img)
-    else:
-        imageArr.append(image)
-        imageNameArr.append(None)
-
-    if extras_mode == 2 and output_dir != '':
-        outpath = output_dir
-    else:
-        outpath = opts.outdir_samples or opts.outdir_extras_samples
-
-    # Extra operation definitions
-
-    def run_gfpgan(image: Image.Image, info: str) -> Tuple[Image.Image, str]:
-        shared.state.job = 'extras-gfpgan'
-        restored_img = modules.gfpgan_model.gfpgan_fix_faces(np.array(image, dtype=np.uint8))
-        res = Image.fromarray(restored_img)
-
-        if gfpgan_visibility < 1.0:
-            res = Image.blend(image, res, gfpgan_visibility)
-
-        info += f"GFPGAN visibility:{round(gfpgan_visibility, 2)}\n"
-        return (res, info)
-
-    def run_codeformer(image: Image.Image, info: str) -> Tuple[Image.Image, str]:
-        shared.state.job = 'extras-codeformer'
-        restored_img = modules.codeformer_model.codeformer.restore(np.array(image, dtype=np.uint8), w=codeformer_weight)
-        res = Image.fromarray(restored_img)
-
-        if codeformer_visibility < 1.0:
-            res = Image.blend(image, res, codeformer_visibility)
-
-        info += f"CodeFormer w: {round(codeformer_weight, 2)}, CodeFormer visibility:{round(codeformer_visibility, 2)}\n"
-        return (res, info)
-
-    def upscale(image, scaler_index, resize, mode, resize_w, resize_h, crop):
-        shared.state.job = 'extras-upscale'
-        upscaler = shared.sd_upscalers[scaler_index]
-        res = upscaler.scaler.upscale(image, resize, upscaler.data_path)
-        if mode == 1 and crop:
-            cropped = Image.new("RGB", (resize_w, resize_h))
-            cropped.paste(res, box=(resize_w // 2 - res.width // 2, resize_h // 2 - res.height // 2))
-            res = cropped
-        return res
-
-    def run_prepare_crop(image: Image.Image, info: str) -> Tuple[Image.Image, str]:
-        # Actual crop happens in run_upscalers_blend, this just sets upscaling_resize and adds info text
-        nonlocal upscaling_resize
-        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"
-        return (image, info)
-
-    @dataclass
-    class UpscaleParams:
-        upscaler_idx: int
-        blend_alpha: float
-
-    def run_upscalers_blend(params: List[UpscaleParams], image: Image.Image, info: str) -> Tuple[Image.Image, str]:
-        blended_result: Image.Image = None
-        image_hash: str = hash(np.array(image.getdata()).tobytes())
-        for upscaler in params:
-            upscale_args = (upscaler.upscaler_idx, upscaling_resize, resize_mode,
-                            upscaling_resize_w, upscaling_resize_h, upscaling_crop)
-            cache_key = LruCache.Key(image_hash=image_hash,
-                                     info_hash=hash(info),
-                                     args_hash=hash(upscale_args))
-            cached_entry = cached_images.get(cache_key)
-            if cached_entry is None:
-                res = upscale(image, *upscale_args)
-                info += f"Upscale: {round(upscaling_resize, 3)}, visibility: {upscaler.blend_alpha}, model:{shared.sd_upscalers[upscaler.upscaler_idx].name}\n"
-                cached_images.put(cache_key, LruCache.Value(image=res, info=info))
-            else:
-                res, info = cached_entry.image, cached_entry.info
-
-            if blended_result is None:
-                blended_result = res
-            else:
-                blended_result = Image.blend(blended_result, res, upscaler.blend_alpha)
-        return (blended_result, info)
-
-    # Build a list of operations to run
-    facefix_ops: List[Callable] = []
-    facefix_ops += [run_gfpgan] if gfpgan_visibility > 0 else []
-    facefix_ops += [run_codeformer] if codeformer_visibility > 0 else []
-
-    upscale_ops: List[Callable] = []
-    upscale_ops += [run_prepare_crop] if resize_mode == 1 else []
-
-    if upscaling_resize != 0:
-        step_params: List[UpscaleParams] = []
-        step_params.append(UpscaleParams(upscaler_idx=extras_upscaler_1, blend_alpha=1.0))
-        if extras_upscaler_2 != 0 and extras_upscaler_2_visibility > 0:
-            step_params.append(UpscaleParams(upscaler_idx=extras_upscaler_2, blend_alpha=extras_upscaler_2_visibility))
-
-        upscale_ops.append(partial(run_upscalers_blend, step_params))
-
-    extras_ops: List[Callable] = (upscale_ops + facefix_ops) if upscale_first else (facefix_ops + upscale_ops)
-
-    for image, image_name in zip(imageArr, imageNameArr):
-        if image is None:
-            return outputs, "Please select an input image.", ''
-
-        shared.state.textinfo = f'Processing image {image_name}'
-        
-        existing_pnginfo = image.info or {}
-
-        image = image.convert("RGB")
-        info = ""
-        # Run each operation on each image
-        for op in extras_ops:
-            image, info = op(image, info)
-
-        if opts.use_original_name_batch and image_name is not None:
-            basename = os.path.splitext(os.path.basename(image_name))[0]
-        else:
-            basename = ''
-
-        if opts.enable_pnginfo: # append info before save
-            image.info = existing_pnginfo
-            image.info["extras"] = info
-
-        if save_output:
-            # Add upscaler name as a suffix.
-            suffix = f"-{shared.sd_upscalers[extras_upscaler_1].name}" if shared.opts.use_upscaler_name_as_suffix else ""
-            # Add second upscaler if applicable.
-            if suffix and extras_upscaler_2 and extras_upscaler_2_visibility:
-                suffix += f"-{shared.sd_upscalers[extras_upscaler_2].name}"
-
-            images.save_image(image, path=outpath, basename=basename, seed=None, prompt=None, extension=opts.samples_format, info=info, short_filename=True,
-                            no_prompt=True, grid=False, pnginfo_section_name="extras", existing_info=existing_pnginfo, forced_filename=None, suffix=suffix)
-
-        if extras_mode != 2 or show_extras_results :
-            outputs.append(image)
-
-    devices.torch_gc()
-
-    return outputs, plaintext_to_html(info), ''
-
-def clear_cache():
-    cached_images.clear()
-
 
 def run_pnginfo(image):
     if image is None:
diff --git a/modules/postprocessing.py b/modules/postprocessing.py
index 385430dc..cb85720b 100644
--- a/modules/postprocessing.py
+++ b/modules/postprocessing.py
@@ -1,28 +1,18 @@
 from __future__ import annotations
-import math
 import os
-import re
-import sys
-import traceback
-import shutil
 
 import numpy as np
 from PIL import Image
 
-import torch
-import tqdm
-
 from typing import Callable, List, OrderedDict, Tuple
 from functools import partial
 from dataclasses import dataclass
 
-from modules import processing, shared, images, devices, sd_models, sd_samplers, sd_vae
+from modules import shared, images, devices, ui_components
 from modules.shared import opts
 import modules.gfpgan_model
-from modules.ui import plaintext_to_html
 import modules.codeformer_model
-import gradio as gr
-import safetensors.torch
+
 
 class LruCache(OrderedDict):
     @dataclass(frozen=True)
@@ -55,7 +45,7 @@ class LruCache(OrderedDict):
 cached_images: LruCache = LruCache(max_size=5)
 
 
-def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_dir, show_extras_results, 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, upscale_first: bool, save_output: bool = True):
+def run_postprocessing(extras_mode, resize_mode, image, image_folder, input_dir, output_dir, show_extras_results, 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, upscale_first: bool, save_output: bool = True):
     devices.torch_gc()
 
     shared.state.begin()
@@ -221,246 +211,9 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_
 
     devices.torch_gc()
 
-    return outputs, plaintext_to_html(info), ''
+    return outputs, ui_components.plaintext_to_html(info), ''
+
 
 def clear_cache():
     cached_images.clear()
 
-
-def run_pnginfo(image):
-    if image is None:
-        return '', '', ''
-
-    geninfo, items = images.read_info_from_image(image)
-    items = {**{'parameters': geninfo}, **items}
-
-    info = ''
-    for key, text in items.items():
-        info += f"""
-<div>
-<p><b>{plaintext_to_html(str(key))}</b></p>
-<p>{plaintext_to_html(str(text))}</p>
-</div>
-""".strip()+"\n"
-
-    if len(info) == 0:
-        message = "Nothing found in the image."
-        info = f"<div><p>{message}<p></div>"
-
-    return '', geninfo, info
-
-
-def create_config(ckpt_result, config_source, a, b, c):
-    def config(x):
-        res = sd_models.find_checkpoint_config(x) if x else None
-        return res if res != shared.sd_default_config else None
-
-    if config_source == 0:
-        cfg = config(a) or config(b) or config(c)
-    elif config_source == 1:
-        cfg = config(b)
-    elif config_source == 2:
-        cfg = config(c)
-    else:
-        cfg = None
-
-    if cfg is None:
-        return
-
-    filename, _ = os.path.splitext(ckpt_result)
-    checkpoint_filename = filename + ".yaml"
-
-    print("Copying config:")
-    print("   from:", cfg)
-    print("     to:", checkpoint_filename)
-    shutil.copyfile(cfg, checkpoint_filename)
-
-
-checkpoint_dict_skip_on_merge = ["cond_stage_model.transformer.text_model.embeddings.position_ids"]
-
-
-def to_half(tensor, enable):
-    if enable and tensor.dtype == torch.float:
-        return tensor.half()
-
-    return tensor
-
-
-def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format, config_source, bake_in_vae, discard_weights):
-    shared.state.begin()
-    shared.state.job = 'model-merge'
-
-    def fail(message):
-        shared.state.textinfo = message
-        shared.state.end()
-        return [*[gr.update() for _ in range(4)], message]
-
-    def weighted_sum(theta0, theta1, alpha):
-        return ((1 - alpha) * theta0) + (alpha * theta1)
-
-    def get_difference(theta1, theta2):
-        return theta1 - theta2
-
-    def add_difference(theta0, theta1_2_diff, alpha):
-        return theta0 + (alpha * theta1_2_diff)
-
-    def filename_weighted_sum():
-        a = primary_model_info.model_name
-        b = secondary_model_info.model_name
-        Ma = round(1 - multiplier, 2)
-        Mb = round(multiplier, 2)
-
-        return f"{Ma}({a}) + {Mb}({b})"
-
-    def filename_add_difference():
-        a = primary_model_info.model_name
-        b = secondary_model_info.model_name
-        c = tertiary_model_info.model_name
-        M = round(multiplier, 2)
-
-        return f"{a} + {M}({b} - {c})"
-
-    def filename_nothing():
-        return primary_model_info.model_name
-
-    theta_funcs = {
-        "Weighted sum": (filename_weighted_sum, None, weighted_sum),
-        "Add difference": (filename_add_difference, get_difference, add_difference),
-        "No interpolation": (filename_nothing, None, None),
-    }
-    filename_generator, theta_func1, theta_func2 = theta_funcs[interp_method]
-    shared.state.job_count = (1 if theta_func1 else 0) + (1 if theta_func2 else 0)
-
-    if not primary_model_name:
-        return fail("Failed: Merging requires a primary model.")
-
-    primary_model_info = sd_models.checkpoints_list[primary_model_name]
-
-    if theta_func2 and not secondary_model_name:
-        return fail("Failed: Merging requires a secondary model.")
-
-    secondary_model_info = sd_models.checkpoints_list[secondary_model_name] if theta_func2 else None
-
-    if theta_func1 and not tertiary_model_name:
-        return fail(f"Failed: Interpolation method ({interp_method}) requires a tertiary model.")
-
-    tertiary_model_info = sd_models.checkpoints_list[tertiary_model_name] if theta_func1 else None
-
-    result_is_inpainting_model = False
-
-    if theta_func2:
-        shared.state.textinfo = f"Loading B"
-        print(f"Loading {secondary_model_info.filename}...")
-        theta_1 = sd_models.read_state_dict(secondary_model_info.filename, map_location='cpu')
-    else:
-        theta_1 = None
-
-    if theta_func1:
-        shared.state.textinfo = f"Loading C"
-        print(f"Loading {tertiary_model_info.filename}...")
-        theta_2 = sd_models.read_state_dict(tertiary_model_info.filename, map_location='cpu')
-
-        shared.state.textinfo = 'Merging B and C'
-        shared.state.sampling_steps = len(theta_1.keys())
-        for key in tqdm.tqdm(theta_1.keys()):
-            if key in checkpoint_dict_skip_on_merge:
-                continue
-
-            if 'model' in key:
-                if key in theta_2:
-                    t2 = theta_2.get(key, torch.zeros_like(theta_1[key]))
-                    theta_1[key] = theta_func1(theta_1[key], t2)
-                else:
-                    theta_1[key] = torch.zeros_like(theta_1[key])
-
-            shared.state.sampling_step += 1
-        del theta_2
-
-        shared.state.nextjob()
-
-    shared.state.textinfo = f"Loading {primary_model_info.filename}..."
-    print(f"Loading {primary_model_info.filename}...")
-    theta_0 = sd_models.read_state_dict(primary_model_info.filename, map_location='cpu')
-
-    print("Merging...")
-    shared.state.textinfo = 'Merging A and B'
-    shared.state.sampling_steps = len(theta_0.keys())
-    for key in tqdm.tqdm(theta_0.keys()):
-        if theta_1 and 'model' in key and key in theta_1:
-
-            if key in checkpoint_dict_skip_on_merge:
-                continue
-
-            a = theta_0[key]
-            b = theta_1[key]
-
-            # this enables merging an inpainting model (A) with another one (B);
-            # where normal model would have 4 channels, for latenst space, inpainting model would
-            # have another 4 channels for unmasked picture's latent space, plus one channel for mask, for a total of 9
-            if a.shape != b.shape and a.shape[0:1] + a.shape[2:] == b.shape[0:1] + b.shape[2:]:
-                if a.shape[1] == 4 and b.shape[1] == 9:
-                    raise RuntimeError("When merging inpainting model with a normal one, A must be the inpainting model.")
-
-                assert a.shape[1] == 9 and b.shape[1] == 4, f"Bad dimensions for merged layer {key}: A={a.shape}, B={b.shape}"
-
-                theta_0[key][:, 0:4, :, :] = theta_func2(a[:, 0:4, :, :], b, multiplier)
-                result_is_inpainting_model = True
-            else:
-                theta_0[key] = theta_func2(a, b, multiplier)
-
-            theta_0[key] = to_half(theta_0[key], save_as_half)
-
-        shared.state.sampling_step += 1
-
-    del theta_1
-
-    bake_in_vae_filename = sd_vae.vae_dict.get(bake_in_vae, None)
-    if bake_in_vae_filename is not None:
-        print(f"Baking in VAE from {bake_in_vae_filename}")
-        shared.state.textinfo = 'Baking in VAE'
-        vae_dict = sd_vae.load_vae_dict(bake_in_vae_filename, map_location='cpu')
-
-        for key in vae_dict.keys():
-            theta_0_key = 'first_stage_model.' + key
-            if theta_0_key in theta_0:
-                theta_0[theta_0_key] = to_half(vae_dict[key], save_as_half)
-
-        del vae_dict
-
-    if save_as_half and not theta_func2:
-        for key in theta_0.keys():
-            theta_0[key] = to_half(theta_0[key], save_as_half)
-
-    if discard_weights:
-        regex = re.compile(discard_weights)
-        for key in list(theta_0):
-            if re.search(regex, key):
-                theta_0.pop(key, None)
-
-    ckpt_dir = shared.cmd_opts.ckpt_dir or sd_models.model_path
-
-    filename = filename_generator() if custom_name == '' else custom_name
-    filename += ".inpainting" if result_is_inpainting_model else ""
-    filename += "." + checkpoint_format
-
-    output_modelname = os.path.join(ckpt_dir, filename)
-
-    shared.state.nextjob()
-    shared.state.textinfo = "Saving"
-    print(f"Saving to {output_modelname}...")
-
-    _, extension = os.path.splitext(output_modelname)
-    if extension.lower() == ".safetensors":
-        safetensors.torch.save_file(theta_0, output_modelname, metadata={"format": "pt"})
-    else:
-        torch.save(theta_0, output_modelname)
-
-    sd_models.list_models()
-
-    create_config(output_modelname, config_source, primary_model_info, secondary_model_info, tertiary_model_info)
-
-    print(f"Checkpoint saved to {output_modelname}.")
-    shared.state.textinfo = "Checkpoint saved"
-    shared.state.end()
-
-    return [*[gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)], "Checkpoint saved to " + output_modelname]
diff --git a/modules/ui.py b/modules/ui.py
index eb4b7e6b..4116e167 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -20,7 +20,7 @@ import numpy as np
 from PIL import Image, PngImagePlugin
 from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
 
-from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks
+from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, postprocessing, ui_components
 from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
 from modules.paths import script_path
 
@@ -95,8 +95,8 @@ extra_networks_symbol = '\U0001F3B4'  # 🎴
 
 
 def plaintext_to_html(text):
-    text = "<p>" + "<br>\n".join([f"{html.escape(x)}" for x in text.split('\n')]) + "</p>"
-    return text
+    return ui_components.plaintext_to_html(text)
+
 
 def send_gradio_gallery_to_image(x):
     if len(x) == 0:
@@ -1152,7 +1152,7 @@ def create_ui():
             result_images, html_info_x, html_info, html_log = create_output_panel("extras", opts.outdir_extras_samples)
 
         submit.click(
-            fn=wrap_gradio_gpu_call(modules.extras.run_extras, extra_outputs=[None, '']),
+            fn=wrap_gradio_gpu_call(postprocessing.run_postprocessing, extra_outputs=[None, '']),
             _js="get_extras_tab_index",
             inputs=[
                 dummy_component,
@@ -1183,7 +1183,7 @@ def create_ui():
         parameters_copypaste.add_paste_fields("extras", extras_image, None)
 
         extras_image.change(
-            fn=modules.extras.clear_cache,
+            fn=postprocessing.clear_cache,
             inputs=[], outputs=[]
         )
 
diff --git a/modules/ui_components.py b/modules/ui_components.py
index 46324425..989cc87b 100644
--- a/modules/ui_components.py
+++ b/modules/ui_components.py
@@ -1,3 +1,5 @@
+import html
+
 import gradio as gr
 
 
@@ -47,3 +49,8 @@ class FormColorPicker(gr.ColorPicker, gr.components.FormComponent):
 
     def get_block_name(self):
         return "colorpicker"
+
+
+def plaintext_to_html(text):
+    text = "<p>" + "<br>\n".join([f"{html.escape(x)}" for x in text.split('\n')]) + "</p>"
+    return text
diff --git a/webui.py b/webui.py
index d235da74..7cf5885e 100644
--- a/webui.py
+++ b/webui.py
@@ -22,7 +22,6 @@ if ".dev" in torch.__version__ or "+git" in torch.__version__:
 
 from modules import shared, devices, sd_samplers, upscaler, extensions, localization, ui_tempdir, ui_extra_networks
 import modules.codeformer_model as codeformer
-import modules.extras
 import modules.face_restoration
 import modules.gfpgan_model as gfpgan
 import modules.img2img
-- 
cgit v1.2.3


From 7ff1ef77dd22f7b38612f91b389237a5dbef2474 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 23 Jan 2023 17:17:31 +0300
Subject: add a message about new torch/xformers version and a way to upgrade
 by specifying a commandline flag

---
 launch.py |  3 ++-
 webui.py  | 26 ++++++++++++++++++++++++++
 2 files changed, 28 insertions(+), 1 deletion(-)

(limited to 'webui.py')

diff --git a/launch.py b/launch.py
index 51c322c0..e7a0b50c 100644
--- a/launch.py
+++ b/launch.py
@@ -208,6 +208,7 @@ def prepare_environment():
     sys.argv, _ = extract_arg(sys.argv, '-f')
     sys.argv, skip_torch_cuda_test = extract_arg(sys.argv, '--skip-torch-cuda-test')
     sys.argv, reinstall_xformers = extract_arg(sys.argv, '--reinstall-xformers')
+    sys.argv, reinstall_torch = extract_arg(sys.argv, '--reinstall-torch')
     sys.argv, update_check = extract_arg(sys.argv, '--update-check')
     sys.argv, run_tests, test_dir = extract_opt(sys.argv, '--tests')
     sys.argv, skip_install = extract_arg(sys.argv, '--skip-install')
@@ -219,7 +220,7 @@ def prepare_environment():
     print(f"Python {sys.version}")
     print(f"Commit hash: {commit}")
     
-    if not is_installed("torch") or not is_installed("torchvision"):
+    if reinstall_torch or 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 skip_torch_cuda_test:
diff --git a/webui.py b/webui.py
index 7cf5885e..bc2baeab 100644
--- a/webui.py
+++ b/webui.py
@@ -8,6 +8,7 @@ import re
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.middleware.gzip import GZipMiddleware
+from packaging import version
 
 from modules import import_hook, errors, extra_networks
 from modules import extra_networks_hypernet, ui_extra_networks_hypernets, ui_extra_networks_textual_inversion
@@ -49,7 +50,32 @@ else:
     server_name = "0.0.0.0" if cmd_opts.listen else None
 
 
+def check_versions():
+    expected_torch_version = "1.13.1"
+
+    if version.parse(torch.__version__) < version.parse(expected_torch_version):
+        errors.print_error_explanation(f"""
+You are running torch {torch.__version__}.
+The program is tested to work with torch {expected_torch_version}.
+To reinstall the desired version, run with commandline flag --reinstall-torch.
+Beware that this will cause a lot of large files to be downloaded.
+        """.strip())
+
+    expected_xformers_version = "0.0.16rc425"
+    if shared.xformers_available:
+        import xformers
+
+        if version.parse(xformers.__version__) < version.parse(expected_xformers_version):
+            errors.print_error_explanation(f"""
+You are running xformers {xformers.__version__}.
+The program is tested to work with xformers {expected_xformers_version}.
+To reinstall the desired version, run with commandline flag --reinstall-xformers.
+            """.strip())
+
+
 def initialize():
+    check_versions()
+
     extensions.list_extensions()
     localization.list_localizations(cmd_opts.localizations_dir)
 
-- 
cgit v1.2.3


From 865af20d8a4a823df3c950f5c9c9092a541bc57a Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 23 Jan 2023 21:28:59 +0300
Subject: suppress A matching Triton is not available message you can all now
 stop worrying about it

---
 webui.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

(limited to 'webui.py')

diff --git a/webui.py b/webui.py
index bc2baeab..e1565a8d 100644
--- a/webui.py
+++ b/webui.py
@@ -1,6 +1,5 @@
 import os
 import sys
-import threading
 import time
 import importlib
 import signal
@@ -10,6 +9,9 @@ from fastapi.middleware.cors import CORSMiddleware
 from fastapi.middleware.gzip import GZipMiddleware
 from packaging import version
 
+import logging
+logging.getLogger("xformers").addFilter(lambda record: 'A matching Triton is not available' not in record.getMessage())
+
 from modules import import_hook, errors, extra_networks
 from modules import extra_networks_hypernet, ui_extra_networks_hypernets, ui_extra_networks_textual_inversion
 from modules.call_queue import wrap_queued_call, queue_lock, wrap_gradio_gpu_call
-- 
cgit v1.2.3


From 6b3981c0685cd1df750df4eb51823f1cfd70c6d5 Mon Sep 17 00:00:00 2001
From: Max Audron <audron@cocaine.farm>
Date: Wed, 25 Jan 2023 18:00:09 +0100
Subject: clean up unused script_path imports

---
 modules/codeformer_model.py                | 2 +-
 modules/generation_parameters_copypaste.py | 2 +-
 webui.py                                   | 1 -
 3 files changed, 2 insertions(+), 3 deletions(-)

(limited to 'webui.py')

diff --git a/modules/codeformer_model.py b/modules/codeformer_model.py
index ab40d842..01fb7bd8 100644
--- a/modules/codeformer_model.py
+++ b/modules/codeformer_model.py
@@ -8,7 +8,7 @@ import torch
 import modules.face_restoration
 import modules.shared
 from modules import shared, devices, modelloader
-from modules.paths import script_path, models_path
+from modules.paths import models_path
 
 # codeformer people made a choice to include modified basicsr library to their project which makes
 # it utterly impossible to use it alongside with other libraries that also use basicsr, like GFPGAN.
diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py
index 35f72808..773c5c0e 100644
--- a/modules/generation_parameters_copypaste.py
+++ b/modules/generation_parameters_copypaste.py
@@ -6,7 +6,7 @@ import re
 from pathlib import Path
 
 import gradio as gr
-from modules.paths import data_path, script_path
+from modules.paths import data_path
 from modules import shared, ui_tempdir, script_callbacks
 import tempfile
 from PIL import Image
diff --git a/webui.py b/webui.py
index e1565a8d..41f32f5c 100644
--- a/webui.py
+++ b/webui.py
@@ -15,7 +15,6 @@ logging.getLogger("xformers").addFilter(lambda record: 'A matching Triton is not
 from modules import import_hook, errors, extra_networks
 from modules import extra_networks_hypernet, ui_extra_networks_hypernets, ui_extra_networks_textual_inversion
 from modules.call_queue import wrap_queued_call, queue_lock, wrap_gradio_gpu_call
-from modules.paths import script_path
 
 import torch
 
-- 
cgit v1.2.3