From bdc90837987ed8919dd611fd01553b0c170ded5c Mon Sep 17 00:00:00 2001
From: Roy Shilkrot <roy.shil@gmail.com>
Date: Thu, 27 Oct 2022 15:20:15 -0400
Subject: Add a barebones interrogate API

---
 modules/api/api.py    | 25 ++++++++++++++++++++++++-
 modules/api/models.py | 13 ++++++++++++-
 2 files changed, 36 insertions(+), 2 deletions(-)

(limited to 'modules')

diff --git a/modules/api/api.py b/modules/api/api.py
index 6e9d6097..eabdb7b8 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -1,4 +1,4 @@
-from modules.api.models import StableDiffusionTxt2ImgProcessingAPI, StableDiffusionImg2ImgProcessingAPI
+from modules.api.models import StableDiffusionTxt2ImgProcessingAPI, StableDiffusionImg2ImgProcessingAPI, InterrogateAPI
 from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images
 from modules.sd_samplers import all_samplers
 from modules.extras import run_pnginfo
@@ -25,6 +25,11 @@ class ImageToImageResponse(BaseModel):
     parameters: Json
     info: Json
 
+class InterrogateResponse(BaseModel):
+    caption: str = Field(default=None, title="Caption", description="The generated caption for the image.")
+    parameters: Json
+    info: Json
+
 
 class Api:
     def __init__(self, app, queue_lock):
@@ -33,6 +38,7 @@ class Api:
         self.queue_lock = queue_lock
         self.app.add_api_route("/sdapi/v1/txt2img", self.text2imgapi, methods=["POST"])
         self.app.add_api_route("/sdapi/v1/img2img", self.img2imgapi, methods=["POST"])
+        self.app.add_api_route("/sdapi/v1/interrogate", self.interrogateapi, methods=["POST"])
 
     def __base64_to_image(self, base64_string):
         # if has a comma, deal with prefix
@@ -118,6 +124,23 @@ class Api:
 
         return ImageToImageResponse(images=b64images, parameters=json.dumps(vars(img2imgreq)), info=processed.js())
 
+    def interrogateapi(self, interrogatereq: InterrogateAPI):
+        image_b64 = interrogatereq.image
+        if image_b64 is None:
+            raise HTTPException(status_code=404, detail="Image not found") 
+
+        populate = interrogatereq.copy(update={ # Override __init__ params
+            }
+        )
+
+        img = self.__base64_to_image(image_b64)
+
+        # Override object param
+        with self.queue_lock:
+            processed = shared.interrogator.interrogate(img)
+        
+        return InterrogateResponse(caption=processed, parameters=json.dumps(vars(interrogatereq)), info=None)
+
     def extrasapi(self):
         raise NotImplementedError
 
diff --git a/modules/api/models.py b/modules/api/models.py
index 079e33d9..8be64749 100644
--- a/modules/api/models.py
+++ b/modules/api/models.py
@@ -63,7 +63,12 @@ class PydanticModelGenerator:
             
                 
         self._model_name = model_name
-        self._class_data = merge_class_params(class_instance)
+
+        if class_instance is not None:
+            self._class_data = merge_class_params(class_instance)
+        else:
+            self._class_data = {}            
+
         self._model_def = [
             ModelDef(
                 field=underscore(k),
@@ -105,4 +110,10 @@ StableDiffusionImg2ImgProcessingAPI = PydanticModelGenerator(
     "StableDiffusionProcessingImg2Img", 
     StableDiffusionProcessingImg2Img,
     [{"key": "sampler_index", "type": str, "default": "Euler"}, {"key": "init_images", "type": list, "default": None}, {"key": "denoising_strength", "type": float, "default": 0.75}, {"key": "mask", "type": str, "default": None}, {"key": "include_init_images", "type": bool, "default": False, "exclude" : True}]
+).generate_model()
+
+InterrogateAPI = PydanticModelGenerator(
+    "Interrogate", 
+    None,
+    [{"key": "image", "type": str, "default": None}]
 ).generate_model()
\ No newline at end of file
-- 
cgit v1.2.3


From 4b8a192f680101de247dca79e48974b53bf961fe Mon Sep 17 00:00:00 2001
From: AngelBottomless <35677394+aria1th@users.noreply.github.com>
Date: Sat, 29 Oct 2022 16:36:43 +0900
Subject: add optimizer save option to shared.opts

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

(limited to 'modules')

diff --git a/modules/shared.py b/modules/shared.py
index e4f163c1..065b893d 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -286,6 +286,7 @@ options_templates.update(options_section(('system', "System"), {
 
 options_templates.update(options_section(('training', "Training"), {
     "unload_models_when_training": OptionInfo(False, "Move VAE and CLIP to RAM when training hypernetwork. Saves VRAM."),
+    "save_optimizer_state": OptionInfo(False, "Saves Optimizer state with checkpoints. This will cause file size to increase VERY much."),
     "dataset_filename_word_regex": OptionInfo("", "Filename word regex"),
     "dataset_filename_join_string": OptionInfo(" ", "Filename join string"),
     "training_image_repeats_per_epoch": OptionInfo(1, "Number of repeats for a single input image per epoch; used only for displaying epoch number", gr.Number, {"precision": 0}),
-- 
cgit v1.2.3


From 20194fd9752a280306fb66b57b258609b0918c46 Mon Sep 17 00:00:00 2001
From: AngelBottomless <35677394+aria1th@users.noreply.github.com>
Date: Sat, 29 Oct 2022 16:56:42 +0900
Subject: We have duplicate linear now

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

(limited to 'modules')

diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py
index aad09ffc..c2d4b51c 100644
--- a/modules/hypernetworks/ui.py
+++ b/modules/hypernetworks/ui.py
@@ -9,7 +9,7 @@ from modules import devices, sd_hijack, shared
 from modules.hypernetworks import hypernetwork
 
 not_available = ["hardswish", "multiheadattention"]
-keys = ["linear"] + list(x for x in hypernetwork.HypernetworkModule.activation_dict.keys() if x not in not_available)
+keys = list(x for x in 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):
     # Remove illegal characters from name.
-- 
cgit v1.2.3


From 9d96d7d0a0aa0a966a9aefd24342345eb65952ed Mon Sep 17 00:00:00 2001
From: aria1th <35677394+aria1th@users.noreply.github.com>
Date: Sun, 30 Oct 2022 20:39:04 +0900
Subject: resolve conflicts

---
 modules/hypernetworks/hypernetwork.py | 44 ++++++++++++++++++++++++++++++-----
 1 file changed, 38 insertions(+), 6 deletions(-)

(limited to 'modules')

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index a11e01d6..8f74cdea 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -21,6 +21,7 @@ from torch.nn.init import normal_, xavier_normal_, xavier_uniform_, kaiming_norm
 from collections import defaultdict, deque
 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
@@ -139,6 +140,8 @@ class Hypernetwork:
         self.weight_init = weight_init
         self.add_layer_norm = add_layer_norm
         self.use_dropout = use_dropout
+        self.optimizer_name = None
+        self.optimizer_state_dict = None
 
         for size in enable_sizes or []:
             self.layers[size] = (
@@ -171,6 +174,10 @@ class Hypernetwork:
         state_dict['use_dropout'] = self.use_dropout
         state_dict['sd_checkpoint'] = self.sd_checkpoint
         state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name
+        if self.optimizer_name is not None:
+            state_dict['optimizer_name'] = self.optimizer_name
+        if self.optimizer_state_dict:
+            state_dict['optimizer_state_dict'] = self.optimizer_state_dict
 
         torch.save(state_dict, filename)
 
@@ -190,7 +197,14 @@ class Hypernetwork:
         self.add_layer_norm = state_dict.get('is_layer_norm', False)
         print(f"Layer norm is set to {self.add_layer_norm}")
         self.use_dropout = state_dict.get('use_dropout', False)
-        print(f"Dropout usage is set to {self.use_dropout}" )
+        print(f"Dropout usage is set to {self.use_dropout}")
+        self.optimizer_name = state_dict.get('optimizer_name', 'AdamW')
+        print(f"Optimizer name is {self.optimizer_name}")
+        self.optimizer_state_dict = state_dict.get('optimizer_state_dict', None)
+        if self.optimizer_state_dict:
+            print("Loaded existing optimizer from checkpoint")
+        else:
+            print("No saved optimizer exists in checkpoint")
 
         for size, sd in state_dict.items():
             if type(size) == int:
@@ -392,8 +406,19 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
     weights = hypernetwork.weights()
     for weight in weights:
         weight.requires_grad = True
-    # if optimizer == "AdamW": or else Adam / AdamW / SGD, etc...
-    optimizer = torch.optim.AdamW(weights, lr=scheduler.learn_rate)
+    # Here we use optimizer from saved HN, or we can specify as UI option.
+    if (optimizer_name := hypernetwork.optimizer_name) in optimizer_dict:
+        optimizer = optimizer_dict[hypernetwork.optimizer_name](params=weights, lr=scheduler.learn_rate)
+    else:
+        print(f"Optimizer type {optimizer_name} is not defined!")
+        optimizer = torch.optim.AdamW(params=weights, lr=scheduler.learn_rate)
+        optimizer_name = 'AdamW'
+    if hypernetwork.optimizer_state_dict:  # This line must be changed if Optimizer type can be different from saved optimizer.
+        try:
+            optimizer.load_state_dict(hypernetwork.optimizer_state_dict)
+        except RuntimeError as e:
+            print("Cannot resume from saved optimizer!")
+            print(e)
 
     steps_without_grad = 0
 
@@ -455,8 +480,11 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
             # Before saving, change name to match current checkpoint.
             hypernetwork_name_every = f'{hypernetwork_name}-{steps_done}'
             last_saved_file = os.path.join(hypernetwork_dir, f'{hypernetwork_name_every}.pt')
+            hypernetwork.optimizer_name = optimizer_name
+            if shared.opts.save_optimizer_state:
+                hypernetwork.optimizer_state_dict = optimizer.state_dict()
             save_hypernetwork(hypernetwork, checkpoint, hypernetwork_name, last_saved_file)
-
+            hypernetwork.optimizer_state_dict = None  # dereference it after saving, to save memory.
         textual_inversion.write_loss(log_directory, "hypernetwork_loss.csv", hypernetwork.step, len(ds), {
             "loss": f"{previous_mean_loss:.7f}",
             "learn_rate": scheduler.learn_rate
@@ -514,14 +542,18 @@ Last saved hypernetwork: {html.escape(last_saved_file)}<br/>
 Last saved image: {html.escape(last_saved_image)}<br/>
 </p>
 """
-        
     report_statistics(loss_dict)
 
     filename = os.path.join(shared.cmd_opts.hypernetwork_dir, f'{hypernetwork_name}.pt')
+    hypernetwork.optimizer_name = optimizer_name
+    if shared.opts.save_optimizer_state:
+        hypernetwork.optimizer_state_dict = optimizer.state_dict()
     save_hypernetwork(hypernetwork, checkpoint, hypernetwork_name, filename)
-
+    del optimizer
+    hypernetwork.optimizer_state_dict = None  # dereference it after saving, to save memory.
     return hypernetwork, filename
 
+
 def save_hypernetwork(hypernetwork, checkpoint, hypernetwork_name, filename):
     old_hypernetwork_name = hypernetwork.name
     old_sd_checkpoint = hypernetwork.sd_checkpoint if hasattr(hypernetwork, "sd_checkpoint") else None
-- 
cgit v1.2.3


From df6a7ebfe8cc4da23861e3e2583693bb7808d573 Mon Sep 17 00:00:00 2001
From: Roy Shilkrot <roy.shil@gmail.com>
Date: Mon, 31 Oct 2022 11:50:33 -0400
Subject: revert things to master

---
 modules/api/api.py    | 2 --
 modules/api/models.py | 6 +-----
 2 files changed, 1 insertion(+), 7 deletions(-)

(limited to 'modules')

diff --git a/modules/api/api.py b/modules/api/api.py
index c510a833..6a903e4c 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -117,8 +117,6 @@ class Api:
 
         return ImageToImageResponse(images=b64images, parameters=vars(img2imgreq), info=processed.js())
 
-    def extrasapi(self):
-        raise NotImplementedError
     def extras_single_image_api(self, req: ExtrasSingleImageRequest):
         reqDict = setUpscalers(req)
 
diff --git a/modules/api/models.py b/modules/api/models.py
index 035a7179..82ab29b8 100644
--- a/modules/api/models.py
+++ b/modules/api/models.py
@@ -64,11 +64,7 @@ class PydanticModelGenerator:
 
 
         self._model_name = model_name
-
-        if class_instance is not None:
-            self._class_data = merge_class_params(class_instance)
-        else:
-            self._class_data = {}            
+        self._class_data = merge_class_params(class_instance)
 
         self._model_def = [
             ModelDef(
-- 
cgit v1.2.3


From 3f3d14afd5abd07d3843370dc1c28be299dbdbab Mon Sep 17 00:00:00 2001
From: Roy Shilkrot <roy.shil@gmail.com>
Date: Mon, 31 Oct 2022 11:51:21 -0400
Subject: nix unused thing

---
 modules/api/api.py | 4 ----
 1 file changed, 4 deletions(-)

(limited to 'modules')

diff --git a/modules/api/api.py b/modules/api/api.py
index 6a903e4c..536e3f16 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -182,10 +182,6 @@ class Api:
         if image_b64 is None:
             raise HTTPException(status_code=404, detail="Image not found") 
 
-        populate = interrogatereq.copy(update={ # Override __init__ params
-            }
-        )
-
         img = self.__base64_to_image(image_b64)
 
         # Override object param
-- 
cgit v1.2.3


From 3178c35224467893cf8dcedb1028c59c6c23db58 Mon Sep 17 00:00:00 2001
From: AngelBottomless <35677394+aria1th@users.noreply.github.com>
Date: Wed, 2 Nov 2022 22:16:32 +0900
Subject: resolve conflicts

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

(limited to 'modules')

diff --git a/modules/shared.py b/modules/shared.py
index 065b893d..959937d7 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -285,7 +285,7 @@ options_templates.update(options_section(('system', "System"), {
 }))
 
 options_templates.update(options_section(('training', "Training"), {
-    "unload_models_when_training": OptionInfo(False, "Move VAE and CLIP to RAM when training hypernetwork. Saves VRAM."),
+    "unload_models_when_training": OptionInfo(False, "Move VAE and CLIP to RAM when training if possible. Saves VRAM."),
     "save_optimizer_state": OptionInfo(False, "Saves Optimizer state with checkpoints. This will cause file size to increase VERY much."),
     "dataset_filename_word_regex": OptionInfo("", "Filename word regex"),
     "dataset_filename_join_string": OptionInfo(" ", "Filename join string"),
-- 
cgit v1.2.3


From 9b5f85ac83f864310fe19c9deab6670bad695b0d Mon Sep 17 00:00:00 2001
From: AngelBottomless <35677394+aria1th@users.noreply.github.com>
Date: Wed, 2 Nov 2022 22:18:04 +0900
Subject: first revert

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

(limited to 'modules')

diff --git a/modules/shared.py b/modules/shared.py
index 959937d7..7e8c552b 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -286,7 +286,6 @@ options_templates.update(options_section(('system', "System"), {
 
 options_templates.update(options_section(('training', "Training"), {
     "unload_models_when_training": OptionInfo(False, "Move VAE and CLIP to RAM when training if possible. Saves VRAM."),
-    "save_optimizer_state": OptionInfo(False, "Saves Optimizer state with checkpoints. This will cause file size to increase VERY much."),
     "dataset_filename_word_regex": OptionInfo("", "Filename word regex"),
     "dataset_filename_join_string": OptionInfo(" ", "Filename join string"),
     "training_image_repeats_per_epoch": OptionInfo(1, "Number of repeats for a single input image per epoch; used only for displaying epoch number", gr.Number, {"precision": 0}),
-- 
cgit v1.2.3


From 7ea5956ad5fa925f92116e8a3bf78d7f6517b654 Mon Sep 17 00:00:00 2001
From: AngelBottomless <35677394+aria1th@users.noreply.github.com>
Date: Wed, 2 Nov 2022 22:18:55 +0900
Subject: now add

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

(limited to 'modules')

diff --git a/modules/shared.py b/modules/shared.py
index d8e99f85..7ecb40d8 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -309,6 +309,7 @@ options_templates.update(options_section(('system', "System"), {
 
 options_templates.update(options_section(('training', "Training"), {
     "unload_models_when_training": OptionInfo(False, "Move VAE and CLIP to RAM when training if possible. Saves VRAM."),
+    "save_optimizer_state": OptionInfo(False, "Saves Optimizer state with checkpoints. This will cause file size to increase VERY much."),
     "dataset_filename_word_regex": OptionInfo("", "Filename word regex"),
     "dataset_filename_join_string": OptionInfo(" ", "Filename join string"),
     "training_image_repeats_per_epoch": OptionInfo(1, "Number of repeats for a single input image per epoch; used only for displaying epoch number", gr.Number, {"precision": 0}),
-- 
cgit v1.2.3


From e21fcd72fcf147904a1df060226c4df12acf251e Mon Sep 17 00:00:00 2001
From: evshiron <evshiron@gmail.com>
Date: Wed, 2 Nov 2022 22:37:45 +0800
Subject: add back png info in image api

---
 modules/api/api.py | 21 +++++++++++++++++----
 1 file changed, 17 insertions(+), 4 deletions(-)

(limited to 'modules')

diff --git a/modules/api/api.py b/modules/api/api.py
index 71c9c160..ceaf08b0 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -7,8 +7,9 @@ from fastapi import APIRouter, Depends, HTTPException
 import modules.shared as shared
 from modules.api.models import *
 from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images
-from modules.sd_samplers import all_samplers, sample_to_image, samples_to_image_grid
+from modules.sd_samplers import all_samplers
 from modules.extras import run_extras, run_pnginfo
+from PIL import PngImagePlugin
 
 
 def upscaler_to_index(name: str):
@@ -31,9 +32,21 @@ def setUpscalers(req: dict):
 
 
 def encode_pil_to_base64(image):
-    buffer = io.BytesIO()
-    image.save(buffer, format="png")
-    return base64.b64encode(buffer.getvalue())
+    with io.BytesIO() as output_bytes:
+
+        # Copy any text-only metadata
+        use_metadata = False
+        metadata = PngImagePlugin.PngInfo()
+        for key, value in image.info.items():
+            if isinstance(key, str) and isinstance(value, str):
+                metadata.add_text(key, value)
+                use_metadata = True
+
+        image.save(
+            output_bytes, "PNG", pnginfo=(metadata if use_metadata else None)
+        )
+        bytes_data = output_bytes.getvalue()
+    return base64.b64encode(bytes_data)
 
 
 class Api:
-- 
cgit v1.2.3


From c07f1d0d7821f85b9ce1419992c118963d605bd7 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Wed, 2 Nov 2022 16:59:10 +0000
Subject: Convert callbacks into a private map, add utility functions for
 removing callbacks

---
 modules/script_callbacks.py | 68 +++++++++++++++++++++++++++------------------
 1 file changed, 41 insertions(+), 27 deletions(-)

(limited to 'modules')

diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py
index c28e220e..4a7fb944 100644
--- a/modules/script_callbacks.py
+++ b/modules/script_callbacks.py
@@ -46,25 +46,23 @@ class CFGDenoiserParams:
 
 
 ScriptCallback = namedtuple("ScriptCallback", ["script", "callback"])
-callbacks_app_started = []
-callbacks_model_loaded = []
-callbacks_ui_tabs = []
-callbacks_ui_settings = []
-callbacks_before_image_saved = []
-callbacks_image_saved = []
-callbacks_cfg_denoiser = []
+__callback_map = dict(
+    callbacks_app_started=[],
+    callbacks_model_loaded=[],
+    callbacks_ui_tabs=[],
+    callbacks_ui_settings=[],
+    callbacks_before_image_saved=[],
+    callbacks_image_saved=[],
+    callbacks_cfg_denoiser=[]
+)
 
 
 def clear_callbacks():
-    callbacks_model_loaded.clear()
-    callbacks_ui_tabs.clear()
-    callbacks_ui_settings.clear()
-    callbacks_before_image_saved.clear()
-    callbacks_image_saved.clear()
-    callbacks_cfg_denoiser.clear()
+    for callback_list in __callback_map.values():
+        callback_list.clear()
 
 def app_started_callback(demo: Optional[Blocks], app: FastAPI):
-    for c in callbacks_app_started:
+    for c in __callback_map['callbacks_app_started']:
         try:
             c.callback(demo, app)
         except Exception:
@@ -72,7 +70,7 @@ def app_started_callback(demo: Optional[Blocks], app: FastAPI):
 
 
 def model_loaded_callback(sd_model):
-    for c in callbacks_model_loaded:
+    for c in __callback_map['callbacks_model_loaded']:
         try:
             c.callback(sd_model)
         except Exception:
@@ -82,7 +80,7 @@ def model_loaded_callback(sd_model):
 def ui_tabs_callback():
     res = []
     
-    for c in callbacks_ui_tabs:
+    for c in __callback_map['callbacks_ui_tabs']:
         try:
             res += c.callback() or []
         except Exception:
@@ -92,7 +90,7 @@ def ui_tabs_callback():
 
 
 def ui_settings_callback():
-    for c in callbacks_ui_settings:
+    for c in __callback_map['callbacks_ui_settings']:
         try:
             c.callback()
         except Exception:
@@ -100,7 +98,7 @@ def ui_settings_callback():
 
 
 def before_image_saved_callback(params: ImageSaveParams):
-    for c in callbacks_before_image_saved:
+    for c in __callback_map['callbacks_before_image_saved']:
         try:
             c.callback(params)
         except Exception:
@@ -108,7 +106,7 @@ def before_image_saved_callback(params: ImageSaveParams):
 
 
 def image_saved_callback(params: ImageSaveParams):
-    for c in callbacks_image_saved:
+    for c in __callback_map['callbacks_image_saved']:
         try:
             c.callback(params)
         except Exception:
@@ -116,7 +114,7 @@ def image_saved_callback(params: ImageSaveParams):
 
 
 def cfg_denoiser_callback(params: CFGDenoiserParams):
-    for c in callbacks_cfg_denoiser:
+    for c in __callback_map['callbacks_cfg_denoiser']:
         try:
             c.callback(params)
         except Exception:
@@ -129,17 +127,33 @@ def add_callback(callbacks, fun):
 
     callbacks.append(ScriptCallback(filename, fun))
 
+    
+def remove_current_script_callbacks():
+    stack = [x for x in inspect.stack() if x.filename != __file__]
+    filename = stack[0].filename if len(stack) > 0 else 'unknown file'
+    if filename == 'unknown file':
+        return
+    for callback_list in __callback_map.values():
+        for callback_to_remove in [cb for cb in callback_list if cb.script == filename]:
+            callback_list.remove(callback_to_remove)
+
+
+def remove_callbacks_for_function(callback_func):
+    for callback_list in __callback_map.values():
+        for callback_to_remove in [cb for cb in callback_list if cb.callback == callback_func]:
+            callback_list.remove(callback_to_remove)
+
 
 def on_app_started(callback):
     """register a function to be called when the webui started, the gradio `Block` component and
     fastapi `FastAPI` object are passed as the arguments"""
-    add_callback(callbacks_app_started, callback)
+    add_callback(__callback_map['callbacks_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"""
-    add_callback(callbacks_model_loaded, callback)
+    add_callback(__callback_map['callbacks_model_loaded'], callback)
 
 
 def on_ui_tabs(callback):
@@ -152,13 +166,13 @@ def on_ui_tabs(callback):
     title is tab text displayed to user in the UI
     elem_id is HTML id for the tab
     """
-    add_callback(callbacks_ui_tabs, callback)
+    add_callback(__callback_map['callbacks_ui_tabs'], callback)
 
 
 def on_ui_settings(callback):
     """register a function to be called before UI settings are populated; add your settings
     by using shared.opts.add_option(shared.OptionInfo(...)) """
-    add_callback(callbacks_ui_settings, callback)
+    add_callback(__callback_map['callbacks_ui_settings'], callback)
 
 
 def on_before_image_saved(callback):
@@ -166,7 +180,7 @@ def on_before_image_saved(callback):
     The callback is called with one argument:
         - params: ImageSaveParams - parameters the image is to be saved with. You can change fields in this object.
     """
-    add_callback(callbacks_before_image_saved, callback)
+    add_callback(__callback_map['callbacks_before_image_saved'], callback)
 
 
 def on_image_saved(callback):
@@ -174,7 +188,7 @@ def on_image_saved(callback):
     The callback is called with one argument:
         - params: ImageSaveParams - parameters the image was saved with. Changing fields in this object does nothing.
     """
-    add_callback(callbacks_image_saved, callback)
+    add_callback(__callback_map['callbacks_image_saved'], callback)
 
 
 def on_cfg_denoiser(callback):
@@ -182,5 +196,5 @@ def on_cfg_denoiser(callback):
     The callback is called with one argument:
         - params: CFGDenoiserParams - parameters to be passed to the inner model and sampling state details.
     """
-    add_callback(callbacks_cfg_denoiser, callback)
+    add_callback(__callback_map['callbacks_cfg_denoiser'], callback)
 
-- 
cgit v1.2.3


From 0b143c1163a96b193a4e8512be9c5831c661a50d Mon Sep 17 00:00:00 2001
From: aria1th <35677394+aria1th@users.noreply.github.com>
Date: Thu, 3 Nov 2022 14:30:53 +0900
Subject: Separate .optim file from model

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

(limited to 'modules')

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 8f74cdea..63c25de8 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -161,6 +161,7 @@ class Hypernetwork:
 
     def save(self, filename):
         state_dict = {}
+        optimizer_saved_dict = {}
 
         for k, v in self.layers.items():
             state_dict[k] = (v[0].state_dict(), v[1].state_dict())
@@ -175,9 +176,10 @@ class Hypernetwork:
         state_dict['sd_checkpoint'] = self.sd_checkpoint
         state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name
         if self.optimizer_name is not None:
-            state_dict['optimizer_name'] = self.optimizer_name
+            optimizer_saved_dict['optimizer_name'] = self.optimizer_name
         if self.optimizer_state_dict:
-            state_dict['optimizer_state_dict'] = self.optimizer_state_dict
+            optimizer_saved_dict['optimizer_state_dict'] = self.optimizer_state_dict
+            torch.save(optimizer_saved_dict, filename + '.optim')
 
         torch.save(state_dict, filename)
 
@@ -198,9 +200,11 @@ class Hypernetwork:
         print(f"Layer norm is set to {self.add_layer_norm}")
         self.use_dropout = state_dict.get('use_dropout', False)
         print(f"Dropout usage is set to {self.use_dropout}")
-        self.optimizer_name = state_dict.get('optimizer_name', 'AdamW')
+
+        optimizer_saved_dict = torch.load(self.filename + '.optim', map_location = 'cpu') if os.path.exists(self.filename + '.optim') else {}
+        self.optimizer_name = optimizer_saved_dict.get('optimizer_name', 'AdamW')
         print(f"Optimizer name is {self.optimizer_name}")
-        self.optimizer_state_dict = state_dict.get('optimizer_state_dict', None)
+        self.optimizer_state_dict = optimizer_saved_dict.get('optimizer_state_dict', None)
         if self.optimizer_state_dict:
             print("Loaded existing optimizer from checkpoint")
         else:
-- 
cgit v1.2.3


From 1764ac3c8bc482bd575987850e96630d9115e51a Mon Sep 17 00:00:00 2001
From: aria1th <35677394+aria1th@users.noreply.github.com>
Date: Thu, 3 Nov 2022 14:49:26 +0900
Subject: use hash to check valid optim

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

(limited to 'modules')

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 63c25de8..4230b8cf 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -177,12 +177,13 @@ class Hypernetwork:
         state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name
         if self.optimizer_name is not None:
             optimizer_saved_dict['optimizer_name'] = self.optimizer_name
+
+        torch.save(state_dict, filename)
         if self.optimizer_state_dict:
+            optimizer_saved_dict['hash'] = sd_models.model_hash(filename)
             optimizer_saved_dict['optimizer_state_dict'] = self.optimizer_state_dict
             torch.save(optimizer_saved_dict, filename + '.optim')
 
-        torch.save(state_dict, filename)
-
     def load(self, filename):
         self.filename = filename
         if self.name is None:
@@ -204,7 +205,10 @@ class Hypernetwork:
         optimizer_saved_dict = torch.load(self.filename + '.optim', map_location = 'cpu') if os.path.exists(self.filename + '.optim') else {}
         self.optimizer_name = optimizer_saved_dict.get('optimizer_name', 'AdamW')
         print(f"Optimizer name is {self.optimizer_name}")
-        self.optimizer_state_dict = optimizer_saved_dict.get('optimizer_state_dict', None)
+        if sd_models.model_hash(filename) == optimizer_saved_dict.get('hash', None):
+            self.optimizer_state_dict = optimizer_saved_dict.get('optimizer_state_dict', None)
+        else:
+            self.optimizer_state_dict = None
         if self.optimizer_state_dict:
             print("Loaded existing optimizer from checkpoint")
         else:
@@ -229,7 +233,7 @@ def list_hypernetworks(path):
         name = os.path.splitext(os.path.basename(filename))[0]
         # Prevent a hypothetical "None.pt" from being listed.
         if name != "None":
-            res[name] = filename
+            res[name + f"({sd_models.model_hash(filename)})"] = filename
     return res
 
 
@@ -375,6 +379,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
     else:
         hypernetwork_dir = None
 
+    hypernetwork_name = hypernetwork_name.rsplit('(', 1)[0]
     if create_image_every > 0:
         images_dir = os.path.join(log_directory, "images")
         os.makedirs(images_dir, exist_ok=True)
-- 
cgit v1.2.3


From 0abb39f461baa343ae7c23abffb261e57c3168d4 Mon Sep 17 00:00:00 2001
From: aria1th <35677394+aria1th@users.noreply.github.com>
Date: Fri, 4 Nov 2022 15:47:19 +0900
Subject: resolve conflict - first revert

---
 modules/hypernetworks/hypernetwork.py | 123 ++++++++++++++--------------------
 1 file changed, 52 insertions(+), 71 deletions(-)

(limited to 'modules')

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 4230b8cf..674fcedd 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -21,7 +21,6 @@ from torch.nn.init import normal_, xavier_normal_, xavier_uniform_, kaiming_norm
 from collections import defaultdict, deque
 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
@@ -34,9 +33,12 @@ class HypernetworkModule(torch.nn.Module):
         "tanh": torch.nn.Tanh,
         "sigmoid": torch.nn.Sigmoid,
     }
-    activation_dict.update({cls_name.lower(): cls_obj for cls_name, cls_obj in inspect.getmembers(torch.nn.modules.activation) if inspect.isclass(cls_obj) and cls_obj.__module__ == 'torch.nn.modules.activation'})
+    activation_dict.update(
+        {cls_name.lower(): cls_obj for cls_name, cls_obj in inspect.getmembers(torch.nn.modules.activation) if
+         inspect.isclass(cls_obj) and cls_obj.__module__ == 'torch.nn.modules.activation'})
 
-    def __init__(self, dim, state_dict=None, layer_structure=None, activation_func=None, weight_init='Normal', add_layer_norm=False, use_dropout=False):
+    def __init__(self, dim, state_dict=None, layer_structure=None, activation_func=None, weight_init='Normal',
+                 add_layer_norm=False, use_dropout=False):
         super().__init__()
 
         assert layer_structure is not None, "layer_structure must not be None"
@@ -47,7 +49,7 @@ class HypernetworkModule(torch.nn.Module):
         for i in range(len(layer_structure) - 1):
 
             # Add a fully-connected layer
-            linears.append(torch.nn.Linear(int(dim * layer_structure[i]), int(dim * layer_structure[i+1])))
+            linears.append(torch.nn.Linear(int(dim * layer_structure[i]), int(dim * layer_structure[i + 1])))
 
             # Add an activation func
             if activation_func == "linear" or activation_func is None:
@@ -59,7 +61,7 @@ class HypernetworkModule(torch.nn.Module):
 
             # Add layer normalization
             if add_layer_norm:
-                linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i+1])))
+                linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i + 1])))
 
             # Add dropout expect last layer
             if use_dropout and i < len(layer_structure) - 3:
@@ -128,7 +130,8 @@ class Hypernetwork:
     filename = None
     name = None
 
-    def __init__(self, name=None, enable_sizes=None, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False):
+    def __init__(self, name=None, enable_sizes=None, layer_structure=None, activation_func=None, weight_init=None,
+                 add_layer_norm=False, use_dropout=False):
         self.filename = None
         self.name = name
         self.layers = {}
@@ -140,13 +143,13 @@ class Hypernetwork:
         self.weight_init = weight_init
         self.add_layer_norm = add_layer_norm
         self.use_dropout = use_dropout
-        self.optimizer_name = None
-        self.optimizer_state_dict = None
 
         for size in enable_sizes or []:
             self.layers[size] = (
-                HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout),
-                HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout),
+                HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init,
+                                   self.add_layer_norm, self.use_dropout),
+                HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init,
+                                   self.add_layer_norm, self.use_dropout),
             )
 
     def weights(self):
@@ -161,7 +164,6 @@ class Hypernetwork:
 
     def save(self, filename):
         state_dict = {}
-        optimizer_saved_dict = {}
 
         for k, v in self.layers.items():
             state_dict[k] = (v[0].state_dict(), v[1].state_dict())
@@ -175,14 +177,8 @@ class Hypernetwork:
         state_dict['use_dropout'] = self.use_dropout
         state_dict['sd_checkpoint'] = self.sd_checkpoint
         state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name
-        if self.optimizer_name is not None:
-            optimizer_saved_dict['optimizer_name'] = self.optimizer_name
 
         torch.save(state_dict, filename)
-        if self.optimizer_state_dict:
-            optimizer_saved_dict['hash'] = sd_models.model_hash(filename)
-            optimizer_saved_dict['optimizer_state_dict'] = self.optimizer_state_dict
-            torch.save(optimizer_saved_dict, filename + '.optim')
 
     def load(self, filename):
         self.filename = filename
@@ -202,23 +198,13 @@ class Hypernetwork:
         self.use_dropout = state_dict.get('use_dropout', False)
         print(f"Dropout usage is set to {self.use_dropout}")
 
-        optimizer_saved_dict = torch.load(self.filename + '.optim', map_location = 'cpu') if os.path.exists(self.filename + '.optim') else {}
-        self.optimizer_name = optimizer_saved_dict.get('optimizer_name', 'AdamW')
-        print(f"Optimizer name is {self.optimizer_name}")
-        if sd_models.model_hash(filename) == optimizer_saved_dict.get('hash', None):
-            self.optimizer_state_dict = optimizer_saved_dict.get('optimizer_state_dict', None)
-        else:
-            self.optimizer_state_dict = None
-        if self.optimizer_state_dict:
-            print("Loaded existing optimizer from checkpoint")
-        else:
-            print("No saved optimizer exists in checkpoint")
-
         for size, sd in state_dict.items():
             if type(size) == int:
                 self.layers[size] = (
-                    HypernetworkModule(size, sd[0], self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout),
-                    HypernetworkModule(size, sd[1], self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout),
+                    HypernetworkModule(size, sd[0], self.layer_structure, self.activation_func, self.weight_init,
+                                       self.add_layer_norm, self.use_dropout),
+                    HypernetworkModule(size, sd[1], self.layer_structure, self.activation_func, self.weight_init,
+                                       self.add_layer_norm, self.use_dropout),
                 )
 
         self.name = state_dict.get('name', self.name)
@@ -233,7 +219,7 @@ def list_hypernetworks(path):
         name = os.path.splitext(os.path.basename(filename))[0]
         # Prevent a hypothetical "None.pt" from being listed.
         if name != "None":
-            res[name + f"({sd_models.model_hash(filename)})"] = filename
+            res[name] = filename
     return res
 
 
@@ -330,7 +316,7 @@ def statistics(data):
         std = 0
     else:
         std = stdev(data)
-    total_information = f"loss:{mean(data):.3f}" + u"\u00B1" + f"({std/ (len(data) ** 0.5):.3f})"
+    total_information = f"loss:{mean(data):.3f}" + u"\u00B1" + f"({std / (len(data) ** 0.5):.3f})"
     recent_data = data[-32:]
     if len(recent_data) < 2:
         std = 0
@@ -340,7 +326,7 @@ def statistics(data):
     return total_information, recent_information
 
 
-def report_statistics(loss_info:dict):
+def report_statistics(loss_info: dict):
     keys = sorted(loss_info.keys(), key=lambda x: sum(loss_info[x]) / len(loss_info[x]))
     for key in keys:
         try:
@@ -352,14 +338,18 @@ def report_statistics(loss_info:dict):
             print(e)
 
 
-
-def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log_directory, training_width, training_height, steps, create_image_every, save_hypernetwork_every, template_file, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
+def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log_directory, training_width,
+                       training_height, steps, create_image_every, save_hypernetwork_every, template_file,
+                       preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps,
+                       preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
     # 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, data_root, template_file, steps, save_hypernetwork_every, create_image_every, log_directory, name="hypernetwork")
+    textual_inversion.validate_train_inputs(hypernetwork_name, learn_rate, batch_size, data_root, template_file, steps,
+                                            save_hypernetwork_every, create_image_every, log_directory,
+                                            name="hypernetwork")
 
     path = shared.hypernetworks.get(hypernetwork_name, None)
     shared.loaded_hypernetwork = Hypernetwork()
@@ -379,7 +369,6 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
     else:
         hypernetwork_dir = None
 
-    hypernetwork_name = hypernetwork_name.rsplit('(', 1)[0]
     if create_image_every > 0:
         images_dir = os.path.join(log_directory, "images")
         os.makedirs(images_dir, exist_ok=True)
@@ -395,39 +384,34 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
         return hypernetwork, filename
 
     scheduler = LearnRateScheduler(learn_rate, steps, ititial_step)
-    
+
     # dataset loading may take a while, so input validations and early returns should be done before this
     shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
     with torch.autocast("cuda"):
-        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, height=training_height, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file, include_cond=True, batch_size=batch_size)
+        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=hypernetwork_name,
+                                                                model=shared.sd_model, device=devices.device,
+                                                                template_file=template_file, include_cond=True,
+                                                                batch_size=batch_size)
 
     if unload:
         shared.sd_model.cond_stage_model.to(devices.cpu)
         shared.sd_model.first_stage_model.to(devices.cpu)
 
     size = len(ds.indexes)
-    loss_dict = defaultdict(lambda : deque(maxlen = 1024))
+    loss_dict = defaultdict(lambda: deque(maxlen=1024))
     losses = torch.zeros((size,))
     previous_mean_losses = [0]
     previous_mean_loss = 0
     print("Mean loss of {} elements".format(size))
-    
+
     weights = hypernetwork.weights()
     for weight in weights:
         weight.requires_grad = True
-    # Here we use optimizer from saved HN, or we can specify as UI option.
-    if (optimizer_name := hypernetwork.optimizer_name) in optimizer_dict:
-        optimizer = optimizer_dict[hypernetwork.optimizer_name](params=weights, lr=scheduler.learn_rate)
-    else:
-        print(f"Optimizer type {optimizer_name} is not defined!")
-        optimizer = torch.optim.AdamW(params=weights, lr=scheduler.learn_rate)
-        optimizer_name = 'AdamW'
-    if hypernetwork.optimizer_state_dict:  # This line must be changed if Optimizer type can be different from saved optimizer.
-        try:
-            optimizer.load_state_dict(hypernetwork.optimizer_state_dict)
-        except RuntimeError as e:
-            print("Cannot resume from saved optimizer!")
-            print(e)
+    # if optimizer == "AdamW": or else Adam / AdamW / SGD, etc...
+    optimizer = torch.optim.AdamW(weights, lr=scheduler.learn_rate)
 
     steps_without_grad = 0
 
@@ -441,7 +425,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
         if len(loss_dict) > 0:
             previous_mean_losses = [i[-1] for i in loss_dict.values()]
             previous_mean_loss = mean(previous_mean_losses)
-            
+
         scheduler.apply(optimizer, hypernetwork.step)
         if scheduler.finished:
             break
@@ -460,7 +444,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
             losses[hypernetwork.step % losses.shape[0]] = loss.item()
             for entry in entries:
                 loss_dict[entry.filename].append(loss.item())
-                
+
             optimizer.zero_grad()
             weights[0].grad = None
             loss.backward()
@@ -475,9 +459,9 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
 
         steps_done = hypernetwork.step + 1
 
-        if torch.isnan(losses[hypernetwork.step % losses.shape[0]]): 
+        if torch.isnan(losses[hypernetwork.step % losses.shape[0]]):
             raise RuntimeError("Loss diverged.")
-        
+
         if len(previous_mean_losses) > 1:
             std = stdev(previous_mean_losses)
         else:
@@ -489,11 +473,8 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
             # Before saving, change name to match current checkpoint.
             hypernetwork_name_every = f'{hypernetwork_name}-{steps_done}'
             last_saved_file = os.path.join(hypernetwork_dir, f'{hypernetwork_name_every}.pt')
-            hypernetwork.optimizer_name = optimizer_name
-            if shared.opts.save_optimizer_state:
-                hypernetwork.optimizer_state_dict = optimizer.state_dict()
             save_hypernetwork(hypernetwork, checkpoint, hypernetwork_name, last_saved_file)
-            hypernetwork.optimizer_state_dict = None  # dereference it after saving, to save memory.
+
         textual_inversion.write_loss(log_directory, "hypernetwork_loss.csv", hypernetwork.step, len(ds), {
             "loss": f"{previous_mean_loss:.7f}",
             "learn_rate": scheduler.learn_rate
@@ -529,7 +510,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
             preview_text = p.prompt
 
             processed = processing.process_images(p)
-            image = processed.images[0] if len(processed.images)>0 else None
+            image = processed.images[0] if len(processed.images) > 0 else None
 
             if unload:
                 shared.sd_model.cond_stage_model.to(devices.cpu)
@@ -537,7 +518,10 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
 
             if image is not None:
                 shared.state.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, 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}"
 
         shared.state.job_no = hypernetwork.step
@@ -551,15 +535,12 @@ Last saved hypernetwork: {html.escape(last_saved_file)}<br/>
 Last saved image: {html.escape(last_saved_image)}<br/>
 </p>
 """
+
     report_statistics(loss_dict)
 
     filename = os.path.join(shared.cmd_opts.hypernetwork_dir, f'{hypernetwork_name}.pt')
-    hypernetwork.optimizer_name = optimizer_name
-    if shared.opts.save_optimizer_state:
-        hypernetwork.optimizer_state_dict = optimizer.state_dict()
     save_hypernetwork(hypernetwork, checkpoint, hypernetwork_name, filename)
-    del optimizer
-    hypernetwork.optimizer_state_dict = None  # dereference it after saving, to save memory.
+
     return hypernetwork, filename
 
 
@@ -576,4 +557,4 @@ def save_hypernetwork(hypernetwork, checkpoint, hypernetwork_name, filename):
         hypernetwork.sd_checkpoint = old_sd_checkpoint
         hypernetwork.sd_checkpoint_name = old_sd_checkpoint_name
         hypernetwork.name = old_hypernetwork_name
-        raise
+        raise
\ No newline at end of file
-- 
cgit v1.2.3


From 0d07cbfa15d34294a4fa22d74359cdd6fe2f799c Mon Sep 17 00:00:00 2001
From: AngelBottomless <35677394+aria1th@users.noreply.github.com>
Date: Fri, 4 Nov 2022 15:50:54 +0900
Subject: I blame code autocomplete

---
 modules/hypernetworks/hypernetwork.py | 76 +++++++++++++----------------------
 1 file changed, 27 insertions(+), 49 deletions(-)

(limited to 'modules')

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 674fcedd..a11e01d6 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -33,12 +33,9 @@ class HypernetworkModule(torch.nn.Module):
         "tanh": torch.nn.Tanh,
         "sigmoid": torch.nn.Sigmoid,
     }
-    activation_dict.update(
-        {cls_name.lower(): cls_obj for cls_name, cls_obj in inspect.getmembers(torch.nn.modules.activation) if
-         inspect.isclass(cls_obj) and cls_obj.__module__ == 'torch.nn.modules.activation'})
+    activation_dict.update({cls_name.lower(): cls_obj for cls_name, cls_obj in inspect.getmembers(torch.nn.modules.activation) if inspect.isclass(cls_obj) and cls_obj.__module__ == 'torch.nn.modules.activation'})
 
-    def __init__(self, dim, state_dict=None, layer_structure=None, activation_func=None, weight_init='Normal',
-                 add_layer_norm=False, use_dropout=False):
+    def __init__(self, dim, state_dict=None, layer_structure=None, activation_func=None, weight_init='Normal', add_layer_norm=False, use_dropout=False):
         super().__init__()
 
         assert layer_structure is not None, "layer_structure must not be None"
@@ -49,7 +46,7 @@ class HypernetworkModule(torch.nn.Module):
         for i in range(len(layer_structure) - 1):
 
             # Add a fully-connected layer
-            linears.append(torch.nn.Linear(int(dim * layer_structure[i]), int(dim * layer_structure[i + 1])))
+            linears.append(torch.nn.Linear(int(dim * layer_structure[i]), int(dim * layer_structure[i+1])))
 
             # Add an activation func
             if activation_func == "linear" or activation_func is None:
@@ -61,7 +58,7 @@ class HypernetworkModule(torch.nn.Module):
 
             # Add layer normalization
             if add_layer_norm:
-                linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i + 1])))
+                linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i+1])))
 
             # Add dropout expect last layer
             if use_dropout and i < len(layer_structure) - 3:
@@ -130,8 +127,7 @@ class Hypernetwork:
     filename = None
     name = None
 
-    def __init__(self, name=None, enable_sizes=None, layer_structure=None, activation_func=None, weight_init=None,
-                 add_layer_norm=False, use_dropout=False):
+    def __init__(self, name=None, enable_sizes=None, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False):
         self.filename = None
         self.name = name
         self.layers = {}
@@ -146,10 +142,8 @@ class Hypernetwork:
 
         for size in enable_sizes or []:
             self.layers[size] = (
-                HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init,
-                                   self.add_layer_norm, self.use_dropout),
-                HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init,
-                                   self.add_layer_norm, self.use_dropout),
+                HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout),
+                HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout),
             )
 
     def weights(self):
@@ -196,15 +190,13 @@ class Hypernetwork:
         self.add_layer_norm = state_dict.get('is_layer_norm', False)
         print(f"Layer norm is set to {self.add_layer_norm}")
         self.use_dropout = state_dict.get('use_dropout', False)
-        print(f"Dropout usage is set to {self.use_dropout}")
+        print(f"Dropout usage is set to {self.use_dropout}" )
 
         for size, sd in state_dict.items():
             if type(size) == int:
                 self.layers[size] = (
-                    HypernetworkModule(size, sd[0], self.layer_structure, self.activation_func, self.weight_init,
-                                       self.add_layer_norm, self.use_dropout),
-                    HypernetworkModule(size, sd[1], self.layer_structure, self.activation_func, self.weight_init,
-                                       self.add_layer_norm, self.use_dropout),
+                    HypernetworkModule(size, sd[0], self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout),
+                    HypernetworkModule(size, sd[1], self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout),
                 )
 
         self.name = state_dict.get('name', self.name)
@@ -316,7 +308,7 @@ def statistics(data):
         std = 0
     else:
         std = stdev(data)
-    total_information = f"loss:{mean(data):.3f}" + u"\u00B1" + f"({std / (len(data) ** 0.5):.3f})"
+    total_information = f"loss:{mean(data):.3f}" + u"\u00B1" + f"({std/ (len(data) ** 0.5):.3f})"
     recent_data = data[-32:]
     if len(recent_data) < 2:
         std = 0
@@ -326,7 +318,7 @@ def statistics(data):
     return total_information, recent_information
 
 
-def report_statistics(loss_info: dict):
+def report_statistics(loss_info:dict):
     keys = sorted(loss_info.keys(), key=lambda x: sum(loss_info[x]) / len(loss_info[x]))
     for key in keys:
         try:
@@ -338,18 +330,14 @@ def report_statistics(loss_info: dict):
             print(e)
 
 
-def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log_directory, training_width,
-                       training_height, steps, create_image_every, save_hypernetwork_every, template_file,
-                       preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps,
-                       preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
+
+def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log_directory, training_width, training_height, steps, create_image_every, save_hypernetwork_every, template_file, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
     # 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, data_root, template_file, steps,
-                                            save_hypernetwork_every, create_image_every, log_directory,
-                                            name="hypernetwork")
+    textual_inversion.validate_train_inputs(hypernetwork_name, learn_rate, batch_size, data_root, template_file, steps, save_hypernetwork_every, create_image_every, log_directory, name="hypernetwork")
 
     path = shared.hypernetworks.get(hypernetwork_name, None)
     shared.loaded_hypernetwork = Hypernetwork()
@@ -384,29 +372,23 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
         return hypernetwork, filename
 
     scheduler = LearnRateScheduler(learn_rate, steps, ititial_step)
-
+    
     # dataset loading may take a while, so input validations and early returns should be done before this
     shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
     with torch.autocast("cuda"):
-        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width,
-                                                                height=training_height,
-                                                                repeats=shared.opts.training_image_repeats_per_epoch,
-                                                                placeholder_token=hypernetwork_name,
-                                                                model=shared.sd_model, device=devices.device,
-                                                                template_file=template_file, include_cond=True,
-                                                                batch_size=batch_size)
+        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=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file, include_cond=True, batch_size=batch_size)
 
     if unload:
         shared.sd_model.cond_stage_model.to(devices.cpu)
         shared.sd_model.first_stage_model.to(devices.cpu)
 
     size = len(ds.indexes)
-    loss_dict = defaultdict(lambda: deque(maxlen=1024))
+    loss_dict = defaultdict(lambda : deque(maxlen = 1024))
     losses = torch.zeros((size,))
     previous_mean_losses = [0]
     previous_mean_loss = 0
     print("Mean loss of {} elements".format(size))
-
+    
     weights = hypernetwork.weights()
     for weight in weights:
         weight.requires_grad = True
@@ -425,7 +407,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
         if len(loss_dict) > 0:
             previous_mean_losses = [i[-1] for i in loss_dict.values()]
             previous_mean_loss = mean(previous_mean_losses)
-
+            
         scheduler.apply(optimizer, hypernetwork.step)
         if scheduler.finished:
             break
@@ -444,7 +426,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
             losses[hypernetwork.step % losses.shape[0]] = loss.item()
             for entry in entries:
                 loss_dict[entry.filename].append(loss.item())
-
+                
             optimizer.zero_grad()
             weights[0].grad = None
             loss.backward()
@@ -459,9 +441,9 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
 
         steps_done = hypernetwork.step + 1
 
-        if torch.isnan(losses[hypernetwork.step % losses.shape[0]]):
+        if torch.isnan(losses[hypernetwork.step % losses.shape[0]]): 
             raise RuntimeError("Loss diverged.")
-
+        
         if len(previous_mean_losses) > 1:
             std = stdev(previous_mean_losses)
         else:
@@ -510,7 +492,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
             preview_text = p.prompt
 
             processed = processing.process_images(p)
-            image = processed.images[0] if len(processed.images) > 0 else None
+            image = processed.images[0] if len(processed.images)>0 else None
 
             if unload:
                 shared.sd_model.cond_stage_model.to(devices.cpu)
@@ -518,10 +500,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
 
             if image is not None:
                 shared.state.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, 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}"
 
         shared.state.job_no = hypernetwork.step
@@ -535,7 +514,7 @@ Last saved hypernetwork: {html.escape(last_saved_file)}<br/>
 Last saved image: {html.escape(last_saved_image)}<br/>
 </p>
 """
-
+        
     report_statistics(loss_dict)
 
     filename = os.path.join(shared.cmd_opts.hypernetwork_dir, f'{hypernetwork_name}.pt')
@@ -543,7 +522,6 @@ Last saved image: {html.escape(last_saved_image)}<br/>
 
     return hypernetwork, filename
 
-
 def save_hypernetwork(hypernetwork, checkpoint, hypernetwork_name, filename):
     old_hypernetwork_name = hypernetwork.name
     old_sd_checkpoint = hypernetwork.sd_checkpoint if hasattr(hypernetwork, "sd_checkpoint") else None
@@ -557,4 +535,4 @@ def save_hypernetwork(hypernetwork, checkpoint, hypernetwork_name, filename):
         hypernetwork.sd_checkpoint = old_sd_checkpoint
         hypernetwork.sd_checkpoint_name = old_sd_checkpoint_name
         hypernetwork.name = old_hypernetwork_name
-        raise
\ No newline at end of file
+        raise
-- 
cgit v1.2.3


From 283249d2390f0f3a1c8a55d5d9aa551e3e9b2f9c Mon Sep 17 00:00:00 2001
From: aria1th <35677394+aria1th@users.noreply.github.com>
Date: Fri, 4 Nov 2022 15:57:17 +0900
Subject: apply

---
 modules/hypernetworks/hypernetwork.py | 54 +++++++++++++++++++++++++++++++----
 1 file changed, 49 insertions(+), 5 deletions(-)

(limited to 'modules')

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 6e1a10cf..de8688a9 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -22,6 +22,8 @@ from collections import defaultdict, deque
 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 = {
@@ -142,6 +144,8 @@ class Hypernetwork:
         self.use_dropout = use_dropout
         self.activate_output = activate_output
         self.last_layer_dropout = kwargs['last_layer_dropout'] if 'last_layer_dropout' in kwargs else True
+        self.optimizer_name = None
+        self.optimizer_state_dict = None
 
         for size in enable_sizes or []:
             self.layers[size] = (
@@ -163,6 +167,7 @@ class Hypernetwork:
 
     def save(self, filename):
         state_dict = {}
+        optimizer_saved_dict = {}
 
         for k, v in self.layers.items():
             state_dict[k] = (v[0].state_dict(), v[1].state_dict())
@@ -178,8 +183,15 @@ class Hypernetwork:
         state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name
         state_dict['activate_output'] = self.activate_output
         state_dict['last_layer_dropout'] = self.last_layer_dropout
-        
+
+        if self.optimizer_name is not None:
+            optimizer_saved_dict['optimizer_name'] = self.optimizer_name
+
         torch.save(state_dict, filename)
+        if self.optimizer_state_dict:
+            optimizer_saved_dict['hash'] = sd_models.model_hash(filename)
+            optimizer_saved_dict['optimizer_state_dict'] = self.optimizer_state_dict
+            torch.save(optimizer_saved_dict, filename + '.optim')
 
     def load(self, filename):
         self.filename = filename
@@ -202,6 +214,18 @@ class Hypernetwork:
         print(f"Activate last layer is set to {self.activate_output}")
         self.last_layer_dropout = state_dict.get('last_layer_dropout', False)
 
+        optimizer_saved_dict = torch.load(self.filename + '.optim', map_location = 'cpu') if os.path.exists(self.filename + '.optim') else {}
+        self.optimizer_name = optimizer_saved_dict.get('optimizer_name', 'AdamW')
+        print(f"Optimizer name is {self.optimizer_name}")
+        if sd_models.model_hash(filename) == optimizer_saved_dict.get('hash', None):
+            self.optimizer_state_dict = optimizer_saved_dict.get('optimizer_state_dict', None)
+        else:
+            self.optimizer_state_dict = None
+        if self.optimizer_state_dict:
+            print("Loaded existing optimizer from checkpoint")
+        else:
+            print("No saved optimizer exists in checkpoint")
+
         for size, sd in state_dict.items():
             if type(size) == int:
                 self.layers[size] = (
@@ -223,7 +247,7 @@ def list_hypernetworks(path):
         name = os.path.splitext(os.path.basename(filename))[0]
         # Prevent a hypothetical "None.pt" from being listed.
         if name != "None":
-            res[name] = filename
+            res[name + f"({sd_models.model_hash(filename)})"] = filename
     return res
 
 
@@ -369,6 +393,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
     else:
         hypernetwork_dir = None
 
+    hypernetwork_name = hypernetwork_name.rsplit('(', 1)[0]
     if create_image_every > 0:
         images_dir = os.path.join(log_directory, "images")
         os.makedirs(images_dir, exist_ok=True)
@@ -404,8 +429,19 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
     weights = hypernetwork.weights()
     for weight in weights:
         weight.requires_grad = True
-    # if optimizer == "AdamW": or else Adam / AdamW / SGD, etc...
-    optimizer = torch.optim.AdamW(weights, lr=scheduler.learn_rate)
+    # Here we use optimizer from saved HN, or we can specify as UI option.
+    if (optimizer_name := hypernetwork.optimizer_name) in optimizer_dict:
+        optimizer = optimizer_dict[hypernetwork.optimizer_name](params=weights, lr=scheduler.learn_rate)
+    else:
+        print(f"Optimizer type {optimizer_name} is not defined!")
+        optimizer = torch.optim.AdamW(params=weights, lr=scheduler.learn_rate)
+        optimizer_name = 'AdamW'
+    if hypernetwork.optimizer_state_dict:  # This line must be changed if Optimizer type can be different from saved optimizer.
+        try:
+            optimizer.load_state_dict(hypernetwork.optimizer_state_dict)
+        except RuntimeError as e:
+            print("Cannot resume from saved optimizer!")
+            print(e)
 
     steps_without_grad = 0
 
@@ -467,7 +503,11 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
             # Before saving, change name to match current checkpoint.
             hypernetwork_name_every = f'{hypernetwork_name}-{steps_done}'
             last_saved_file = os.path.join(hypernetwork_dir, f'{hypernetwork_name_every}.pt')
+            hypernetwork.optimizer_name = optimizer_name
+            if shared.opts.save_optimizer_state:
+                hypernetwork.optimizer_state_dict = optimizer.state_dict()
             save_hypernetwork(hypernetwork, checkpoint, hypernetwork_name, last_saved_file)
+            hypernetwork.optimizer_state_dict = None  # dereference it after saving, to save memory.
 
         textual_inversion.write_loss(log_directory, "hypernetwork_loss.csv", hypernetwork.step, len(ds), {
             "loss": f"{previous_mean_loss:.7f}",
@@ -530,8 +570,12 @@ Last saved image: {html.escape(last_saved_image)}<br/>
     report_statistics(loss_dict)
 
     filename = os.path.join(shared.cmd_opts.hypernetwork_dir, f'{hypernetwork_name}.pt')
+    hypernetwork.optimizer_name = optimizer_name
+    if shared.opts.save_optimizer_state:
+        hypernetwork.optimizer_state_dict = optimizer.state_dict()
     save_hypernetwork(hypernetwork, checkpoint, hypernetwork_name, filename)
-
+    del optimizer
+    hypernetwork.optimizer_state_dict = None  # dereference it after saving, to save memory.
     return hypernetwork, filename
 
 def save_hypernetwork(hypernetwork, checkpoint, hypernetwork_name, filename):
-- 
cgit v1.2.3


From f5d394214d6ee74a682d0a1016bcbebc4b43c13a Mon Sep 17 00:00:00 2001
From: aria1th <35677394+aria1th@users.noreply.github.com>
Date: Fri, 4 Nov 2022 16:04:03 +0900
Subject: split before declaring file name

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

(limited to 'modules')

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index de8688a9..9b6a3e62 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -382,6 +382,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
     shared.state.textinfo = "Initializing hypernetwork training..."
     shared.state.job_count = steps
 
+    hypernetwork_name = hypernetwork_name.rsplit('(', 1)[0]
     filename = os.path.join(shared.cmd_opts.hypernetwork_dir, f'{hypernetwork_name}.pt')
 
     log_directory = os.path.join(log_directory, datetime.datetime.now().strftime("%Y-%m-%d"), hypernetwork_name)
@@ -393,7 +394,6 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
     else:
         hypernetwork_dir = None
 
-    hypernetwork_name = hypernetwork_name.rsplit('(', 1)[0]
     if create_image_every > 0:
         images_dir = os.path.join(log_directory, "images")
         os.makedirs(images_dir, exist_ok=True)
-- 
cgit v1.2.3


From 1ca0bcd3a7003dd2c1324de7d97fd2a6fc5ddc53 Mon Sep 17 00:00:00 2001
From: aria1th <35677394+aria1th@users.noreply.github.com>
Date: Fri, 4 Nov 2022 16:09:19 +0900
Subject: only save if option is enabled

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

(limited to 'modules')

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 9b6a3e62..b1f308e2 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -188,7 +188,7 @@ class Hypernetwork:
             optimizer_saved_dict['optimizer_name'] = self.optimizer_name
 
         torch.save(state_dict, filename)
-        if self.optimizer_state_dict:
+        if shared.opts.save_optimizer_state and self.optimizer_state_dict:
             optimizer_saved_dict['hash'] = sd_models.model_hash(filename)
             optimizer_saved_dict['optimizer_state_dict'] = self.optimizer_state_dict
             torch.save(optimizer_saved_dict, filename + '.optim')
-- 
cgit v1.2.3


From 7278897982bfb640ee95f144c97ed25fb3f77ea3 Mon Sep 17 00:00:00 2001
From: AngelBottomless <35677394+aria1th@users.noreply.github.com>
Date: Fri, 4 Nov 2022 17:12:28 +0900
Subject: Update shared.py

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

(limited to 'modules')

diff --git a/modules/shared.py b/modules/shared.py
index 4d6e1c8b..6e7a02e0 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -309,7 +309,7 @@ options_templates.update(options_section(('system', "System"), {
 
 options_templates.update(options_section(('training', "Training"), {
     "unload_models_when_training": OptionInfo(False, "Move VAE and CLIP to RAM when training if possible. Saves VRAM."),
-    "save_optimizer_state": OptionInfo(False, "Saves Optimizer state with checkpoints. This will cause file size to increase VERY much."),
+    "save_optimizer_state": OptionInfo(False, "Saves Optimizer state as separate *.optim file. Training can be resumed with HN itself and matching optim file."),
     "dataset_filename_word_regex": OptionInfo("", "Filename word regex"),
     "dataset_filename_join_string": OptionInfo(" ", "Filename join string"),
     "training_image_repeats_per_epoch": OptionInfo(1, "Number of repeats for a single input image per epoch; used only for displaying epoch number", gr.Number, {"precision": 0}),
-- 
cgit v1.2.3


From fd62727893f9face287b0a9620251afaa38a627d Mon Sep 17 00:00:00 2001
From: Isaac Poulton <flagredomega@gmail.com>
Date: Fri, 4 Nov 2022 18:34:35 +0700
Subject: Sort hypernetworks

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

(limited to 'modules')

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 6e1a10cf..f1f04a70 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -224,7 +224,7 @@ def list_hypernetworks(path):
         # Prevent a hypothetical "None.pt" from being listed.
         if name != "None":
             res[name] = filename
-    return res
+    return dict(sorted(res.items()))
 
 
 def load_hypernetwork(filename):
-- 
cgit v1.2.3


From c3cd0d7a86f35a5bfc58fdc3ecfaf203c0aee06f Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Fri, 4 Nov 2022 12:19:16 +0000
Subject: Should be one underscore for module privates not two

---
 modules/script_callbacks.py | 37 ++++++++++++++++++-------------------
 1 file changed, 18 insertions(+), 19 deletions(-)

(limited to 'modules')

diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py
index 4a7fb944..83da7ca4 100644
--- a/modules/script_callbacks.py
+++ b/modules/script_callbacks.py
@@ -46,7 +46,7 @@ class CFGDenoiserParams:
 
 
 ScriptCallback = namedtuple("ScriptCallback", ["script", "callback"])
-__callback_map = dict(
+_callback_map = dict(
     callbacks_app_started=[],
     callbacks_model_loaded=[],
     callbacks_ui_tabs=[],
@@ -58,11 +58,11 @@ __callback_map = dict(
 
 
 def clear_callbacks():
-    for callback_list in __callback_map.values():
+    for callback_list in _callback_map.values():
         callback_list.clear()
 
 def app_started_callback(demo: Optional[Blocks], app: FastAPI):
-    for c in __callback_map['callbacks_app_started']:
+    for c in _callback_map['callbacks_app_started']:
         try:
             c.callback(demo, app)
         except Exception:
@@ -70,7 +70,7 @@ def app_started_callback(demo: Optional[Blocks], app: FastAPI):
 
 
 def model_loaded_callback(sd_model):
-    for c in __callback_map['callbacks_model_loaded']:
+    for c in _callback_map['callbacks_model_loaded']:
         try:
             c.callback(sd_model)
         except Exception:
@@ -80,7 +80,7 @@ def model_loaded_callback(sd_model):
 def ui_tabs_callback():
     res = []
     
-    for c in __callback_map['callbacks_ui_tabs']:
+    for c in _callback_map['callbacks_ui_tabs']:
         try:
             res += c.callback() or []
         except Exception:
@@ -90,7 +90,7 @@ def ui_tabs_callback():
 
 
 def ui_settings_callback():
-    for c in __callback_map['callbacks_ui_settings']:
+    for c in _callback_map['callbacks_ui_settings']:
         try:
             c.callback()
         except Exception:
@@ -98,7 +98,7 @@ def ui_settings_callback():
 
 
 def before_image_saved_callback(params: ImageSaveParams):
-    for c in __callback_map['callbacks_before_image_saved']:
+    for c in _callback_map['callbacks_before_image_saved']:
         try:
             c.callback(params)
         except Exception:
@@ -106,7 +106,7 @@ def before_image_saved_callback(params: ImageSaveParams):
 
 
 def image_saved_callback(params: ImageSaveParams):
-    for c in __callback_map['callbacks_image_saved']:
+    for c in _callback_map['callbacks_image_saved']:
         try:
             c.callback(params)
         except Exception:
@@ -114,7 +114,7 @@ def image_saved_callback(params: ImageSaveParams):
 
 
 def cfg_denoiser_callback(params: CFGDenoiserParams):
-    for c in __callback_map['callbacks_cfg_denoiser']:
+    for c in _callback_map['callbacks_cfg_denoiser']:
         try:
             c.callback(params)
         except Exception:
@@ -133,13 +133,13 @@ def remove_current_script_callbacks():
     filename = stack[0].filename if len(stack) > 0 else 'unknown file'
     if filename == 'unknown file':
         return
-    for callback_list in __callback_map.values():
+    for callback_list in _callback_map.values():
         for callback_to_remove in [cb for cb in callback_list if cb.script == filename]:
             callback_list.remove(callback_to_remove)
 
 
 def remove_callbacks_for_function(callback_func):
-    for callback_list in __callback_map.values():
+    for callback_list in _callback_map.values():
         for callback_to_remove in [cb for cb in callback_list if cb.callback == callback_func]:
             callback_list.remove(callback_to_remove)
 
@@ -147,13 +147,13 @@ def remove_callbacks_for_function(callback_func):
 def on_app_started(callback):
     """register a function to be called when the webui started, the gradio `Block` component and
     fastapi `FastAPI` object are passed as the arguments"""
-    add_callback(__callback_map['callbacks_app_started'], callback)
+    add_callback(_callback_map['callbacks_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"""
-    add_callback(__callback_map['callbacks_model_loaded'], callback)
+    add_callback(_callback_map['callbacks_model_loaded'], callback)
 
 
 def on_ui_tabs(callback):
@@ -166,13 +166,13 @@ def on_ui_tabs(callback):
     title is tab text displayed to user in the UI
     elem_id is HTML id for the tab
     """
-    add_callback(__callback_map['callbacks_ui_tabs'], callback)
+    add_callback(_callback_map['callbacks_ui_tabs'], callback)
 
 
 def on_ui_settings(callback):
     """register a function to be called before UI settings are populated; add your settings
     by using shared.opts.add_option(shared.OptionInfo(...)) """
-    add_callback(__callback_map['callbacks_ui_settings'], callback)
+    add_callback(_callback_map['callbacks_ui_settings'], callback)
 
 
 def on_before_image_saved(callback):
@@ -180,7 +180,7 @@ def on_before_image_saved(callback):
     The callback is called with one argument:
         - params: ImageSaveParams - parameters the image is to be saved with. You can change fields in this object.
     """
-    add_callback(__callback_map['callbacks_before_image_saved'], callback)
+    add_callback(_callback_map['callbacks_before_image_saved'], callback)
 
 
 def on_image_saved(callback):
@@ -188,7 +188,7 @@ def on_image_saved(callback):
     The callback is called with one argument:
         - params: ImageSaveParams - parameters the image was saved with. Changing fields in this object does nothing.
     """
-    add_callback(__callback_map['callbacks_image_saved'], callback)
+    add_callback(_callback_map['callbacks_image_saved'], callback)
 
 
 def on_cfg_denoiser(callback):
@@ -196,5 +196,4 @@ def on_cfg_denoiser(callback):
     The callback is called with one argument:
         - params: CFGDenoiserParams - parameters to be passed to the inner model and sampling state details.
     """
-    add_callback(__callback_map['callbacks_cfg_denoiser'], callback)
-
+    add_callback(_callback_map['callbacks_cfg_denoiser'], callback)
-- 
cgit v1.2.3


From f316280ad3634a2343b086a6de0bfcd473e18599 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 4 Nov 2022 16:48:40 +0300
Subject: fix the error that prevents from setting some options

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

(limited to 'modules')

diff --git a/modules/shared.py b/modules/shared.py
index a9e28b9c..962115f6 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -406,7 +406,8 @@ class Options:
             if key in self.data or key in self.data_labels:
                 assert not cmd_opts.freeze_settings, "changing settings is disabled"
 
-                comp_args = opts.data_labels[key].component_args
+                info = opts.data_labels.get(key, None)
+                comp_args = info.component_args if info else None
                 if isinstance(comp_args, dict) and comp_args.get('visible', True) is False:
                     raise RuntimeError(f"not possible to set {key} because it is restricted")
 
-- 
cgit v1.2.3


From 116bcf730ade8d3ac5d76d04c5887b6bba000970 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 4 Nov 2022 16:48:46 +0300
Subject: disable setting options via API until it is fixed by the author

---
 modules/api/api.py | 4 ++++
 1 file changed, 4 insertions(+)

(limited to 'modules')

diff --git a/modules/api/api.py b/modules/api/api.py
index a49f3755..8a7ab2f5 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -218,6 +218,10 @@ class Api:
         return options
         
     def set_config(self, req: OptionsModel):
+        # currently req has all options fields even if you send a dict like { "send_seed": false }, which means it will
+        # overwrite all options with default values.
+        raise RuntimeError('Setting options via API is not supported')
+
         reqDict = vars(req)
         for o in reqDict:
             setattr(shared.opts, o, reqDict[o])
-- 
cgit v1.2.3


From 08feb4c364e8b2aed929fd7d22dfa21a93d78b2c Mon Sep 17 00:00:00 2001
From: Isaac Poulton <flagredomega@gmail.com>
Date: Fri, 4 Nov 2022 20:53:11 +0700
Subject: Sort straight out of the glob

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

(limited to 'modules')

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index f1f04a70..a441ab10 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -219,12 +219,12 @@ class Hypernetwork:
 
 def list_hypernetworks(path):
     res = {}
-    for filename in glob.iglob(os.path.join(path, '**/*.pt'), recursive=True):
+    for filename in sorted(glob.iglob(os.path.join(path, '**/*.pt'), recursive=True)):
         name = os.path.splitext(os.path.basename(filename))[0]
         # Prevent a hypothetical "None.pt" from being listed.
         if name != "None":
             res[name] = filename
-    return dict(sorted(res.items()))
+    return res
 
 
 def load_hypernetwork(filename):
-- 
cgit v1.2.3


From 5844ef8a9a165e0f456a4658bda830282cf5a55e Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Fri, 4 Nov 2022 16:02:25 +0000
Subject: remove private underscore indicator

---
 modules/script_callbacks.py | 36 ++++++++++++++++++------------------
 1 file changed, 18 insertions(+), 18 deletions(-)

(limited to 'modules')

diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py
index 83da7ca4..74dfb880 100644
--- a/modules/script_callbacks.py
+++ b/modules/script_callbacks.py
@@ -46,7 +46,7 @@ class CFGDenoiserParams:
 
 
 ScriptCallback = namedtuple("ScriptCallback", ["script", "callback"])
-_callback_map = dict(
+callback_map = dict(
     callbacks_app_started=[],
     callbacks_model_loaded=[],
     callbacks_ui_tabs=[],
@@ -58,11 +58,11 @@ _callback_map = dict(
 
 
 def clear_callbacks():
-    for callback_list in _callback_map.values():
+    for callback_list in callback_map.values():
         callback_list.clear()
 
 def app_started_callback(demo: Optional[Blocks], app: FastAPI):
-    for c in _callback_map['callbacks_app_started']:
+    for c in callback_map['callbacks_app_started']:
         try:
             c.callback(demo, app)
         except Exception:
@@ -70,7 +70,7 @@ def app_started_callback(demo: Optional[Blocks], app: FastAPI):
 
 
 def model_loaded_callback(sd_model):
-    for c in _callback_map['callbacks_model_loaded']:
+    for c in callback_map['callbacks_model_loaded']:
         try:
             c.callback(sd_model)
         except Exception:
@@ -80,7 +80,7 @@ def model_loaded_callback(sd_model):
 def ui_tabs_callback():
     res = []
     
-    for c in _callback_map['callbacks_ui_tabs']:
+    for c in callback_map['callbacks_ui_tabs']:
         try:
             res += c.callback() or []
         except Exception:
@@ -90,7 +90,7 @@ def ui_tabs_callback():
 
 
 def ui_settings_callback():
-    for c in _callback_map['callbacks_ui_settings']:
+    for c in callback_map['callbacks_ui_settings']:
         try:
             c.callback()
         except Exception:
@@ -98,7 +98,7 @@ def ui_settings_callback():
 
 
 def before_image_saved_callback(params: ImageSaveParams):
-    for c in _callback_map['callbacks_before_image_saved']:
+    for c in callback_map['callbacks_before_image_saved']:
         try:
             c.callback(params)
         except Exception:
@@ -106,7 +106,7 @@ def before_image_saved_callback(params: ImageSaveParams):
 
 
 def image_saved_callback(params: ImageSaveParams):
-    for c in _callback_map['callbacks_image_saved']:
+    for c in callback_map['callbacks_image_saved']:
         try:
             c.callback(params)
         except Exception:
@@ -114,7 +114,7 @@ def image_saved_callback(params: ImageSaveParams):
 
 
 def cfg_denoiser_callback(params: CFGDenoiserParams):
-    for c in _callback_map['callbacks_cfg_denoiser']:
+    for c in callback_map['callbacks_cfg_denoiser']:
         try:
             c.callback(params)
         except Exception:
@@ -133,13 +133,13 @@ def remove_current_script_callbacks():
     filename = stack[0].filename if len(stack) > 0 else 'unknown file'
     if filename == 'unknown file':
         return
-    for callback_list in _callback_map.values():
+    for callback_list in callback_map.values():
         for callback_to_remove in [cb for cb in callback_list if cb.script == filename]:
             callback_list.remove(callback_to_remove)
 
 
 def remove_callbacks_for_function(callback_func):
-    for callback_list in _callback_map.values():
+    for callback_list in callback_map.values():
         for callback_to_remove in [cb for cb in callback_list if cb.callback == callback_func]:
             callback_list.remove(callback_to_remove)
 
@@ -147,13 +147,13 @@ def remove_callbacks_for_function(callback_func):
 def on_app_started(callback):
     """register a function to be called when the webui started, the gradio `Block` component and
     fastapi `FastAPI` object are passed as the arguments"""
-    add_callback(_callback_map['callbacks_app_started'], callback)
+    add_callback(callback_map['callbacks_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"""
-    add_callback(_callback_map['callbacks_model_loaded'], callback)
+    add_callback(callback_map['callbacks_model_loaded'], callback)
 
 
 def on_ui_tabs(callback):
@@ -166,13 +166,13 @@ def on_ui_tabs(callback):
     title is tab text displayed to user in the UI
     elem_id is HTML id for the tab
     """
-    add_callback(_callback_map['callbacks_ui_tabs'], callback)
+    add_callback(callback_map['callbacks_ui_tabs'], callback)
 
 
 def on_ui_settings(callback):
     """register a function to be called before UI settings are populated; add your settings
     by using shared.opts.add_option(shared.OptionInfo(...)) """
-    add_callback(_callback_map['callbacks_ui_settings'], callback)
+    add_callback(callback_map['callbacks_ui_settings'], callback)
 
 
 def on_before_image_saved(callback):
@@ -180,7 +180,7 @@ def on_before_image_saved(callback):
     The callback is called with one argument:
         - params: ImageSaveParams - parameters the image is to be saved with. You can change fields in this object.
     """
-    add_callback(_callback_map['callbacks_before_image_saved'], callback)
+    add_callback(callback_map['callbacks_before_image_saved'], callback)
 
 
 def on_image_saved(callback):
@@ -188,7 +188,7 @@ def on_image_saved(callback):
     The callback is called with one argument:
         - params: ImageSaveParams - parameters the image was saved with. Changing fields in this object does nothing.
     """
-    add_callback(_callback_map['callbacks_image_saved'], callback)
+    add_callback(callback_map['callbacks_image_saved'], callback)
 
 
 def on_cfg_denoiser(callback):
@@ -196,4 +196,4 @@ def on_cfg_denoiser(callback):
     The callback is called with one argument:
         - params: CFGDenoiserParams - parameters to be passed to the inner model and sampling state details.
     """
-    add_callback(_callback_map['callbacks_cfg_denoiser'], callback)
+    add_callback(callback_map['callbacks_cfg_denoiser'], callback)
-- 
cgit v1.2.3


From 0d7e01d9950e013784c4b77c05aa7583ea69edc8 Mon Sep 17 00:00:00 2001
From: innovaciones <sonygarcia99@gmail.com>
Date: Fri, 4 Nov 2022 12:14:32 -0600
Subject: Open extensions links in new tab

Fixed for "Available" tab
---
 modules/ui_extensions.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

(limited to 'modules')

diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py
index a81de9a7..8e0d41d5 100644
--- a/modules/ui_extensions.py
+++ b/modules/ui_extensions.py
@@ -188,7 +188,7 @@ def refresh_available_extensions_from_data():
 
         code += f"""
             <tr>
-                <td><a href="{html.escape(url)}">{html.escape(name)}</a></td>
+                <td><a href="{html.escape(url)}" target="_blank">{html.escape(name)}</a></td>
                 <td>{html.escape(description)}</td>
                 <td>{install_code}</td>
             </tr>
-- 
cgit v1.2.3


From b8435e632f7ba0da12a2c8e9c788dda519279d24 Mon Sep 17 00:00:00 2001
From: evshiron <evshiron@gmail.com>
Date: Sat, 5 Nov 2022 02:36:47 +0800
Subject: add --cors-allow-origins cmd opt

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

(limited to 'modules')

diff --git a/modules/shared.py b/modules/shared.py
index a9e28b9c..e83cbcdf 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -86,6 +86,7 @@ parser.add_argument("--nowebui", action='store_true', help="use api=True to laun
 parser.add_argument("--ui-debug-mode", action='store_true', help="Don't load model to quickly launch UI")
 parser.add_argument("--device-id", type=str, help="Select the default CUDA device to use (export CUDA_VISIBLE_DEVICES=0,1,etc might be needed before)", default=None)
 parser.add_argument("--administrator", action='store_true', help="Administrator rights", default=False)
+parser.add_argument("--cors-allow-origins", type=str, help="Allowed CORS origins", default=None)
 
 cmd_opts = parser.parse_args()
 restricted_opts = {
@@ -147,9 +148,9 @@ class State:
         self.interrupted = True
 
     def nextjob(self):
-        if opts.show_progress_every_n_steps == -1: 
+        if opts.show_progress_every_n_steps == -1:
             self.do_set_current_image()
-            
+
         self.job_no += 1
         self.sampling_step = 0
         self.current_image_sampling_step = 0
@@ -198,7 +199,7 @@ class State:
             return
         if self.current_latent is None:
             return
-            
+
         if opts.show_progress_grid:
             self.current_image = sd_samplers.samples_to_image_grid(self.current_latent)
         else:
-- 
cgit v1.2.3


From 467d8b967b5d1b1984ab113bec3fff217736e7ac Mon Sep 17 00:00:00 2001
From: AngelBottomless <35677394+aria1th@users.noreply.github.com>
Date: Sat, 5 Nov 2022 04:24:42 +0900
Subject: Fix errors from commit f2b697 with --hide-ui-dir-config

https://github.com/AUTOMATIC1111/stable-diffusion-webui/commit/f2b69709eaff88fc3a2bd49585556ec0883bf5ea
---
 modules/ui.py | 14 ++++++++------
 1 file changed, 8 insertions(+), 6 deletions(-)

(limited to 'modules')

diff --git a/modules/ui.py b/modules/ui.py
index 4c2829af..76ca9b07 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1446,17 +1446,19 @@ def create_ui(wrap_gradio_gpu_call):
                 continue
 
             oldval = opts.data.get(key, None)
-
-            setattr(opts, key, value)
-
+            try:
+                setattr(opts, key, value)
+            except RuntimeError:
+                continue
             if oldval != value:
                 if opts.data_labels[key].onchange is not None:
                     opts.data_labels[key].onchange()
 
                 changed += 1
-
-        opts.save(shared.config_filename)
-
+        try:
+            opts.save(shared.config_filename)
+        except RuntimeError:
+            return opts.dumpjson(), f'{changed} settings changed without save.'
         return opts.dumpjson(), f'{changed} settings changed.'
 
     def run_settings_single(value, key):
-- 
cgit v1.2.3


From 30b1bcc64e67ad50c5d3af3a6fe1bd1e9553f34e Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 4 Nov 2022 22:56:18 +0300
Subject: fix upscale loop erroneously applied multiple times

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

(limited to 'modules')

diff --git a/modules/upscaler.py b/modules/upscaler.py
index 83fde7ca..c4e6e6bd 100644
--- a/modules/upscaler.py
+++ b/modules/upscaler.py
@@ -57,10 +57,18 @@ class Upscaler:
         self.scale = scale
         dest_w = img.width * scale
         dest_h = img.height * scale
+
         for i in range(3):
-            if img.width > dest_w and img.height > dest_h:
-                break
+            shape = (img.width, img.height)
+
             img = self.do_upscale(img, selected_model)
+
+            if shape == (img.width, img.height):
+                break
+
+            if img.width >= dest_w and img.height >= dest_h:
+                break
+
         if img.width != dest_w or img.height != dest_h:
             img = img.resize((int(dest_w), int(dest_h)), resample=LANCZOS)
 
-- 
cgit v1.2.3


From 6008c0773ea575353f9b87da8a58454e20cc7857 Mon Sep 17 00:00:00 2001
From: hentailord85ez <112723046+hentailord85ez@users.noreply.github.com>
Date: Fri, 4 Nov 2022 23:03:05 +0000
Subject: Add support for new DPM-Solver++ samplers

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

(limited to 'modules')

diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index c7c414ef..7ece6556 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -29,6 +29,10 @@ samplers_k_diffusion = [
     ('LMS Karras', 'sample_lms', ['k_lms_ka'], {'scheduler': 'karras'}),
     ('DPM2 Karras', 'sample_dpm_2', ['k_dpm_2_ka'], {'scheduler': 'karras'}),
     ('DPM2 a Karras', 'sample_dpm_2_ancestral', ['k_dpm_2_a_ka'], {'scheduler': 'karras'}),
+    ('DPM-Solver++(2S) a', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a'], {}),
+    ('DPM-Solver++(2M)', 'sample_dpmpp_2m', ['k_dpmpp_2m'], {}),
+    ('DPM-Solver++(2S) Karras', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a_ka'], {'scheduler': 'karras'}),
+    ('DPM-Solver++(2M) Karras', 'sample_dpmpp_2m', ['k_dpmpp_2m_ka'], {'scheduler': 'karras'}),
 ]
 
 samplers_data_k_diffusion = [
-- 
cgit v1.2.3


From f92dc505a013af9e385c7edbdf97539be62503d6 Mon Sep 17 00:00:00 2001
From: hentailord85ez <112723046+hentailord85ez@users.noreply.github.com>
Date: Fri, 4 Nov 2022 23:12:48 +0000
Subject: Fix name

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

(limited to 'modules')

diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index 7ece6556..b28a2e4c 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -31,7 +31,7 @@ samplers_k_diffusion = [
     ('DPM2 a Karras', 'sample_dpm_2_ancestral', ['k_dpm_2_a_ka'], {'scheduler': 'karras'}),
     ('DPM-Solver++(2S) a', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a'], {}),
     ('DPM-Solver++(2M)', 'sample_dpmpp_2m', ['k_dpmpp_2m'], {}),
-    ('DPM-Solver++(2S) Karras', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a_ka'], {'scheduler': 'karras'}),
+    ('DPM-Solver++(2S) a Karras', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a_ka'], {'scheduler': 'karras'}),
     ('DPM-Solver++(2M) Karras', 'sample_dpmpp_2m', ['k_dpmpp_2m_ka'], {'scheduler': 'karras'}),
 ]
 
-- 
cgit v1.2.3


From 1b6c2fc749e12f12bbee4705e65f217d23fa9072 Mon Sep 17 00:00:00 2001
From: hentailord85ez <112723046+hentailord85ez@users.noreply.github.com>
Date: Fri, 4 Nov 2022 23:28:13 +0000
Subject: Reorder samplers

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

(limited to 'modules')

diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index b28a2e4c..1e88f7ee 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -24,13 +24,13 @@ samplers_k_diffusion = [
     ('Heun', 'sample_heun', ['k_heun'], {}),
     ('DPM2', 'sample_dpm_2', ['k_dpm_2'], {}),
     ('DPM2 a', 'sample_dpm_2_ancestral', ['k_dpm_2_a'], {}),
+    ('DPM-Solver++(2S) a', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a'], {}),
+    ('DPM-Solver++(2M)', 'sample_dpmpp_2m', ['k_dpmpp_2m'], {}),
     ('DPM fast', 'sample_dpm_fast', ['k_dpm_fast'], {}),
     ('DPM adaptive', 'sample_dpm_adaptive', ['k_dpm_ad'], {}),
     ('LMS Karras', 'sample_lms', ['k_lms_ka'], {'scheduler': 'karras'}),
     ('DPM2 Karras', 'sample_dpm_2', ['k_dpm_2_ka'], {'scheduler': 'karras'}),
     ('DPM2 a Karras', 'sample_dpm_2_ancestral', ['k_dpm_2_a_ka'], {'scheduler': 'karras'}),
-    ('DPM-Solver++(2S) a', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a'], {}),
-    ('DPM-Solver++(2M)', 'sample_dpmpp_2m', ['k_dpmpp_2m'], {}),
     ('DPM-Solver++(2S) a Karras', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a_ka'], {'scheduler': 'karras'}),
     ('DPM-Solver++(2M) Karras', 'sample_dpmpp_2m', ['k_dpmpp_2m_ka'], {'scheduler': 'karras'}),
 ]
-- 
cgit v1.2.3


From ebce0c57c78a3f22178e3a38938d19ec0dfb703d Mon Sep 17 00:00:00 2001
From: Billy Cao <aliencaocao@gmail.com>
Date: Sat, 5 Nov 2022 11:38:24 +0800
Subject: Use typing.Optional instead of | to add support for Python 3.9 and
 below.

---
 modules/api/models.py | 26 +++++++++++++-------------
 1 file changed, 13 insertions(+), 13 deletions(-)

(limited to 'modules')

diff --git a/modules/api/models.py b/modules/api/models.py
index 2ae75f43..a44c5ddd 100644
--- a/modules/api/models.py
+++ b/modules/api/models.py
@@ -1,6 +1,6 @@
 import inspect
 from pydantic import BaseModel, Field, create_model
-from typing import Any, Optional, Union
+from typing import Any, Optional
 from typing_extensions import Literal
 from inflection import underscore
 from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img
@@ -185,22 +185,22 @@ _options = vars(parser)['_option_string_actions']
 for key in _options:
     if(_options[key].dest != 'help'):
         flag = _options[key]
-        _type = str 
-        if(_options[key].default != None): _type = type(_options[key].default) 
+        _type = str
+        if _options[key].default is not None: _type = type(_options[key].default)
         flags.update({flag.dest: (_type,Field(default=flag.default, description=flag.help))})
 
 FlagsModel = create_model("Flags", **flags)
 
 class SamplerItem(BaseModel):
     name: str = Field(title="Name")
-    aliases: list[str]  = Field(title="Aliases")
+    aliases: list[str] = Field(title="Aliases")
     options: dict[str, str] = Field(title="Options")
 
 class UpscalerItem(BaseModel):
     name: str = Field(title="Name")
-    model_name: str | None = Field(title="Model Name")
-    model_path: str | None = Field(title="Path")
-    model_url: str | None = Field(title="URL")
+    model_name: Optional[str] = Field(title="Model Name")
+    model_path: Optional[str] = Field(title="Path")
+    model_url: Optional[str] = Field(title="URL")
 
 class SDModelItem(BaseModel):
     title: str = Field(title="Title")
@@ -211,21 +211,21 @@ class SDModelItem(BaseModel):
 
 class HypernetworkItem(BaseModel):
     name: str = Field(title="Name")
-    path: str | None = Field(title="Path")
+    path: Optional[str] = Field(title="Path")
 
 class FaceRestorerItem(BaseModel):
     name: str = Field(title="Name")
-    cmd_dir: str | None = Field(title="Path")
+    cmd_dir: Optional[str] = Field(title="Path")
 
 class RealesrganItem(BaseModel):
     name: str = Field(title="Name")
-    path: str | None = Field(title="Path")
-    scale: int | None = Field(title="Scale")
+    path: Optional[str] = Field(title="Path")
+    scale: Optional[int] = Field(title="Scale")
 
 class PromptStyleItem(BaseModel):
     name: str = Field(title="Name")
-    prompt: str | None = Field(title="Prompt")
-    negative_prompt: str | None = Field(title="Negative Prompt")
+    prompt: Optional[str] = Field(title="Prompt")
+    negative_prompt: Optional[str] = Field(title="Negative Prompt")
 
 class ArtistItem(BaseModel):
     name: str = Field(title="Name")
-- 
cgit v1.2.3


From e9a5562b9b27a1a4f9c282637b111cefd9727a41 Mon Sep 17 00:00:00 2001
From: papuSpartan <mcgpapu@gmail.com>
Date: Sat, 5 Nov 2022 04:06:51 -0500
Subject: add support for tls (gradio tls options)

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

(limited to 'modules')

diff --git a/modules/shared.py b/modules/shared.py
index 962115f6..7a20c3af 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -86,6 +86,9 @@ parser.add_argument("--nowebui", action='store_true', help="use api=True to laun
 parser.add_argument("--ui-debug-mode", action='store_true', help="Don't load model to quickly launch UI")
 parser.add_argument("--device-id", type=str, help="Select the default CUDA device to use (export CUDA_VISIBLE_DEVICES=0,1,etc might be needed before)", default=None)
 parser.add_argument("--administrator", action='store_true', help="Administrator rights", default=False)
+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)
 
 cmd_opts = parser.parse_args()
 restricted_opts = {
-- 
cgit v1.2.3


From 03b08c4a6b0609f24ec789d40100529b92ef0612 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 5 Nov 2022 15:04:48 +0300
Subject: do not die when an extension's repo has no remote

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

(limited to 'modules')

diff --git a/modules/extensions.py b/modules/extensions.py
index 897af96e..8e0977fd 100644
--- a/modules/extensions.py
+++ b/modules/extensions.py
@@ -34,8 +34,11 @@ class Extension:
         if repo is None or repo.bare:
             self.remote = None
         else:
-            self.remote = next(repo.remote().urls, None)
-            self.status = 'unknown'
+            try:
+                self.remote = next(repo.remote().urls, None)
+                self.status = 'unknown'
+            except Exception:
+                self.remote = None
 
     def list_files(self, subdir, extension):
         from modules import scripts
-- 
cgit v1.2.3


From a170e3d22231e145f42bb878a76ae5f76fdca230 Mon Sep 17 00:00:00 2001
From: Evgeniy <github@printerror.xyz>
Date: Sat, 5 Nov 2022 17:06:56 +0300
Subject: Python 3.8 typing compatibility

Solves problems with

```Traceback (most recent call last):
  File "webui.py", line 201, in <module>
    webui()
  File "webui.py", line 178, in webui
    create_api(app)
  File "webui.py", line 117, in create_api
    from modules.api.api import Api
  File "H:\AIart\stable-diffusion\stable-diffusion-webui\modules\api\api.py", line 9, in <module>
    from modules.api.models import *
  File "H:\AIart\stable-diffusion\stable-diffusion-webui\modules\api\models.py", line 194, in <module>
    class SamplerItem(BaseModel):
  File "H:\AIart\stable-diffusion\stable-diffusion-webui\modules\api\models.py", line 196, in SamplerItem
    aliases: list[str] = Field(title="Aliases")
TypeError: 'type' object is not subscriptable```

and

```Traceback (most recent call last):
  File "webui.py", line 201, in <module>
    webui()
  File "webui.py", line 178, in webui
    create_api(app)
  File "webui.py", line 117, in create_api
    from modules.api.api import Api
  File "H:\AIart\stable-diffusion\stable-diffusion-webui\modules\api\api.py", line 9, in <module>
    from modules.api.models import *
  File "H:\AIart\stable-diffusion\stable-diffusion-webui\modules\api\models.py", line 194, in <module>
    class SamplerItem(BaseModel):
  File "H:\AIart\stable-diffusion\stable-diffusion-webui\modules\api\models.py", line 197, in SamplerItem
    options: dict[str, str] = Field(title="Options")
TypeError: 'type' object is not subscriptable```
---
 modules/api/models.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

(limited to 'modules')

diff --git a/modules/api/models.py b/modules/api/models.py
index a44c5ddd..f89da1ff 100644
--- a/modules/api/models.py
+++ b/modules/api/models.py
@@ -5,7 +5,7 @@ from typing_extensions import Literal
 from inflection import underscore
 from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img
 from modules.shared import sd_upscalers, opts, parser
-from typing import List
+from typing import Dict, List
 
 API_NOT_ALLOWED = [
     "self",
@@ -193,8 +193,8 @@ FlagsModel = create_model("Flags", **flags)
 
 class SamplerItem(BaseModel):
     name: str = Field(title="Name")
-    aliases: list[str] = Field(title="Aliases")
-    options: dict[str, str] = Field(title="Options")
+    aliases: List[str] = Field(title="Aliases")
+    options: Dict[str, str] = Field(title="Options")
 
 class UpscalerItem(BaseModel):
     name: str = Field(title="Name")
@@ -230,4 +230,4 @@ class PromptStyleItem(BaseModel):
 class ArtistItem(BaseModel):
     name: str = Field(title="Name")
     score: float = Field(title="Score")
-    category: str = Field(title="Category")
\ No newline at end of file
+    category: str = Field(title="Category")
-- 
cgit v1.2.3


From 62e3d71aa778928d63cab81d9d8cde33e55bebb3 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 5 Nov 2022 17:09:42 +0300
Subject: rework the code to not use the walrus operator because colab's 3.7
 does not support it

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

(limited to 'modules')

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 5ceed6ee..7f182712 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -429,13 +429,16 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
     weights = hypernetwork.weights()
     for weight in weights:
         weight.requires_grad = True
+
     # Here we use optimizer from saved HN, or we can specify as UI option.
-    if (optimizer_name := hypernetwork.optimizer_name) in optimizer_dict:
+    if hypernetwork.optimizer_name in optimizer_dict:
         optimizer = optimizer_dict[hypernetwork.optimizer_name](params=weights, lr=scheduler.learn_rate)
+        optimizer_name = hypernetwork.optimizer_name
     else:
-        print(f"Optimizer type {optimizer_name} is not defined!")
+        print(f"Optimizer type {hypernetwork.optimizer_name} is not defined!")
         optimizer = torch.optim.AdamW(params=weights, lr=scheduler.learn_rate)
         optimizer_name = 'AdamW'
+
     if hypernetwork.optimizer_state_dict:  # This line must be changed if Optimizer type can be different from saved optimizer.
         try:
             optimizer.load_state_dict(hypernetwork.optimizer_state_dict)
-- 
cgit v1.2.3


From 159475e072f2ed3db8235aab9c3fa18640b93b80 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 5 Nov 2022 18:32:22 +0300
Subject: tweak names a bit for new samplers

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

(limited to 'modules')

diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index 1e88f7ee..783992d2 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -24,15 +24,15 @@ samplers_k_diffusion = [
     ('Heun', 'sample_heun', ['k_heun'], {}),
     ('DPM2', 'sample_dpm_2', ['k_dpm_2'], {}),
     ('DPM2 a', 'sample_dpm_2_ancestral', ['k_dpm_2_a'], {}),
-    ('DPM-Solver++(2S) a', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a'], {}),
-    ('DPM-Solver++(2M)', 'sample_dpmpp_2m', ['k_dpmpp_2m'], {}),
+    ('DPM++ 2S a', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a'], {}),
+    ('DPM++ 2M', 'sample_dpmpp_2m', ['k_dpmpp_2m'], {}),
     ('DPM fast', 'sample_dpm_fast', ['k_dpm_fast'], {}),
     ('DPM adaptive', 'sample_dpm_adaptive', ['k_dpm_ad'], {}),
     ('LMS Karras', 'sample_lms', ['k_lms_ka'], {'scheduler': 'karras'}),
     ('DPM2 Karras', 'sample_dpm_2', ['k_dpm_2_ka'], {'scheduler': 'karras'}),
     ('DPM2 a Karras', 'sample_dpm_2_ancestral', ['k_dpm_2_a_ka'], {'scheduler': 'karras'}),
-    ('DPM-Solver++(2S) a Karras', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a_ka'], {'scheduler': 'karras'}),
-    ('DPM-Solver++(2M) Karras', 'sample_dpmpp_2m', ['k_dpmpp_2m_ka'], {'scheduler': 'karras'}),
+    ('DPM++ 2S a Karras', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a_ka'], {'scheduler': 'karras'}),
+    ('DPM++ 2M Karras', 'sample_dpmpp_2m', ['k_dpmpp_2m_ka'], {'scheduler': 'karras'}),
 ]
 
 samplers_data_k_diffusion = [
-- 
cgit v1.2.3


From 6603f63b7b8af39ab815091460c5c2a12d3f253e Mon Sep 17 00:00:00 2001
From: Han Lin <hotdogee@gmail.com>
Date: Sun, 6 Nov 2022 11:08:20 +0800
Subject: Fixes LDSR upscaler producing black bars

---
 modules/ldsr_model_arch.py | 14 +++++++++++---
 1 file changed, 11 insertions(+), 3 deletions(-)

(limited to 'modules')

diff --git a/modules/ldsr_model_arch.py b/modules/ldsr_model_arch.py
index 14db5076..90e0a2f0 100644
--- a/modules/ldsr_model_arch.py
+++ b/modules/ldsr_model_arch.py
@@ -101,8 +101,8 @@ class LDSR:
         down_sample_rate = target_scale / 4
         wd = width_og * down_sample_rate
         hd = height_og * down_sample_rate
-        width_downsampled_pre = int(wd)
-        height_downsampled_pre = int(hd)
+        width_downsampled_pre = int(np.ceil(wd))
+        height_downsampled_pre = int(np.ceil(hd))
 
         if down_sample_rate != 1:
             print(
@@ -110,7 +110,12 @@ class LDSR:
             im_og = im_og.resize((width_downsampled_pre, height_downsampled_pre), Image.LANCZOS)
         else:
             print(f"Down sample rate is 1 from {target_scale} / 4 (Not downsampling)")
-        logs = self.run(model["model"], im_og, diffusion_steps, eta)
+        
+        # pad width and height to multiples of 64, pads with the edge values of image to avoid artifacts
+        pad_w, pad_h = np.max(((2, 2), np.ceil(np.array(im_og.size) / 64).astype(int)), axis=0) * 64 - im_og.size
+        im_padded = Image.fromarray(np.pad(np.array(im_og), ((0, pad_h), (0, pad_w), (0, 0)), mode='edge'))
+        
+        logs = self.run(model["model"], im_padded, diffusion_steps, eta)
 
         sample = logs["sample"]
         sample = sample.detach().cpu()
@@ -120,6 +125,9 @@ class LDSR:
         sample = np.transpose(sample, (0, 2, 3, 1))
         a = Image.fromarray(sample[0])
 
+        # remove padding
+        a = a.crop((0, 0) + tuple(np.array(im_og.size) * 4))
+
         del model
         gc.collect()
         torch.cuda.empty_cache()
-- 
cgit v1.2.3


From a2a1a2f7270a865175f64475229838a8d64509ea Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 6 Nov 2022 09:02:25 +0300
Subject: add ability to create extensions that add localizations

---
 modules/localization.py | 6 ++++++
 modules/scripts.py      | 1 -
 modules/shared.py       | 2 --
 modules/ui.py           | 3 +--
 4 files changed, 7 insertions(+), 5 deletions(-)

(limited to 'modules')

diff --git a/modules/localization.py b/modules/localization.py
index b1810cda..f6a6f2fb 100644
--- a/modules/localization.py
+++ b/modules/localization.py
@@ -3,6 +3,7 @@ import os
 import sys
 import traceback
 
+
 localizations = {}
 
 
@@ -16,6 +17,11 @@ def list_localizations(dirname):
 
         localizations[fn] = os.path.join(dirname, file)
 
+    from modules import scripts
+    for file in scripts.list_scripts("localizations", ".json"):
+        fn, ext = os.path.splitext(file.filename)
+        localizations[fn] = file.path
+
 
 def localization_js(current_localization_name):
     fn = localizations.get(current_localization_name, None)
diff --git a/modules/scripts.py b/modules/scripts.py
index 366c90d7..637b2329 100644
--- a/modules/scripts.py
+++ b/modules/scripts.py
@@ -3,7 +3,6 @@ import sys
 import traceback
 from collections import namedtuple
 
-import modules.ui as ui
 import gradio as gr
 
 from modules.processing import StableDiffusionProcessing
diff --git a/modules/shared.py b/modules/shared.py
index 70b998ff..e8bacd3c 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -221,8 +221,6 @@ interrogator = modules.interrogate.InterrogateModels("interrogate")
 
 face_restorers = []
 
-localization.list_localizations(cmd_opts.localizations_dir)
-
 
 def realesrgan_models_names():
     import modules.realesrgan_model
diff --git a/modules/ui.py b/modules/ui.py
index 76ca9b07..23643c22 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1563,11 +1563,10 @@ def create_ui(wrap_gradio_gpu_call):
             shared.state.need_restart = True
 
         restart_gradio.click(
-
             fn=request_restart,
+            _js='restart_reload',
             inputs=[],
             outputs=[],
-            _js='restart_reload'
         )
 
         if column is not None:
-- 
cgit v1.2.3


From e5b4e3f820cd09e751f1d168ab05d606d078a0d9 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 6 Nov 2022 10:12:53 +0300
Subject: add tags to extensions, and ability to filter out tags list changed
 Settings keys in UI do not print VRAM/etc stats everywhere but in calls that
 use GPU

---
 modules/ui.py            | 25 ++++++++++++----------
 modules/ui_extensions.py | 55 ++++++++++++++++++++++++++++++++++++++----------
 2 files changed, 58 insertions(+), 22 deletions(-)

(limited to 'modules')

diff --git a/modules/ui.py b/modules/ui.py
index 23643c22..c946ad59 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -174,9 +174,9 @@ def save_pil_to_file(pil_image, dir=None):
 gr.processing_utils.save_pil_to_file = save_pil_to_file
 
 
-def wrap_gradio_call(func, extra_outputs=None):
+def wrap_gradio_call(func, extra_outputs=None, add_stats=False):
     def f(*args, extra_outputs_array=extra_outputs, **kwargs):
-        run_memmon = opts.memmon_poll_rate > 0 and not shared.mem_mon.disabled
+        run_memmon = opts.memmon_poll_rate > 0 and not shared.mem_mon.disabled and add_stats
         if run_memmon:
             shared.mem_mon.monitor()
         t = time.perf_counter()
@@ -203,11 +203,18 @@ def wrap_gradio_call(func, extra_outputs=None):
 
             res = extra_outputs_array + [f"<div class='error'>{plaintext_to_html(type(e).__name__+': '+str(e))}</div>"]
 
+        shared.state.skipped = False
+        shared.state.interrupted = False
+        shared.state.job_count = 0
+
+        if not add_stats:
+            return tuple(res)
+
         elapsed = time.perf_counter() - t
         elapsed_m = int(elapsed // 60)
         elapsed_s = elapsed % 60
         elapsed_text = f"{elapsed_s:.2f}s"
-        if (elapsed_m > 0):
+        if elapsed_m > 0:
             elapsed_text = f"{elapsed_m}m "+elapsed_text
 
         if run_memmon:
@@ -225,10 +232,6 @@ def wrap_gradio_call(func, extra_outputs=None):
         # last item is always HTML
         res[-1] += f"<div class='performance'><p class='time'>Time taken: <wbr>{elapsed_text}</p>{vram_html}</div>"
 
-        shared.state.skipped = False
-        shared.state.interrupted = False
-        shared.state.job_count = 0
-
         return tuple(res)
 
     return f
@@ -1436,7 +1439,7 @@ def create_ui(wrap_gradio_gpu_call):
     opts.reorder()
 
     def run_settings(*args):
-        changed = 0
+        changed = []
 
         for key, value, comp in zip(opts.data_labels.keys(), args, components):
             assert comp == dummy_component or opts.same_type(value, opts.data_labels[key].default), f"Bad value for setting {key}: {value}; expecting {type(opts.data_labels[key].default).__name__}"
@@ -1454,12 +1457,12 @@ def create_ui(wrap_gradio_gpu_call):
                 if opts.data_labels[key].onchange is not None:
                     opts.data_labels[key].onchange()
 
-                changed += 1
+                changed.append(key)
         try:
             opts.save(shared.config_filename)
         except RuntimeError:
-            return opts.dumpjson(), f'{changed} settings changed without save.'
-        return opts.dumpjson(), f'{changed} settings changed.'
+            return opts.dumpjson(), f'{len(changed)} settings changed without save: {", ".join(changed)}.'
+        return opts.dumpjson(), f'{len(changed)} settings changed: {", ".join(changed)}.'
 
     def run_settings_single(value, key):
         if not opts.same_type(value, opts.data_labels[key].default):
diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py
index 8e0d41d5..02ab9643 100644
--- a/modules/ui_extensions.py
+++ b/modules/ui_extensions.py
@@ -140,13 +140,15 @@ def install_extension_from_url(dirname, url):
         shutil.rmtree(tmpdir, True)
 
 
-def install_extension_from_index(url):
+def install_extension_from_index(url, hide_tags):
     ext_table, message = install_extension_from_url(None, url)
 
-    return refresh_available_extensions_from_data(), ext_table, message
+    code, _ = refresh_available_extensions_from_data(hide_tags)
 
+    return code, ext_table, message
 
-def refresh_available_extensions(url):
+
+def refresh_available_extensions(url, hide_tags):
     global available_extensions
 
     import urllib.request
@@ -155,13 +157,25 @@ def refresh_available_extensions(url):
 
     available_extensions = json.loads(text)
 
-    return url, refresh_available_extensions_from_data(), ''
+    code, tags = refresh_available_extensions_from_data(hide_tags)
+
+    return url, code, gr.CheckboxGroup.update(choices=tags), ''
+
+
+def refresh_available_extensions_for_tags(hide_tags):
+    code, _ = refresh_available_extensions_from_data(hide_tags)
 
+    return code, ''
 
-def refresh_available_extensions_from_data():
+
+def refresh_available_extensions_from_data(hide_tags):
     extlist = available_extensions["extensions"]
     installed_extension_urls = {normalize_git_url(extension.remote): extension.name for extension in extensions.extensions}
 
+    tags = available_extensions.get("tags", {})
+    tags_to_hide = set(hide_tags)
+    hidden = 0
+
     code = f"""<!-- {time.time()} -->
     <table id="available_extensions">
         <thead>
@@ -178,17 +192,24 @@ def refresh_available_extensions_from_data():
         name = ext.get("name", "noname")
         url = ext.get("url", None)
         description = ext.get("description", "")
+        extension_tags = ext.get("tags", [])
 
         if url is None:
             continue
 
+        if len([x for x in extension_tags if x in tags_to_hide]) > 0:
+            hidden += 1
+            continue
+
         existing = installed_extension_urls.get(normalize_git_url(url), None)
 
         install_code = f"""<input onclick="install_extension_from_index(this, '{html.escape(url)}')" type="button" value="{"Install" if not existing else "Installed"}" {"disabled=disabled" if existing else ""} class="gr-button gr-button-lg gr-button-secondary">"""
 
+        tags_text = ", ".join([f"<span class='extension-tag' title='{tags.get(x, '')}'>{x}</span>" for x in extension_tags])
+
         code += f"""
             <tr>
-                <td><a href="{html.escape(url)}" target="_blank">{html.escape(name)}</a></td>
+                <td><a href="{html.escape(url)}" target="_blank">{html.escape(name)}</a><br />{tags_text}</td>
                 <td>{html.escape(description)}</td>
                 <td>{install_code}</td>
             </tr>
@@ -199,7 +220,10 @@ def refresh_available_extensions_from_data():
     </table>
     """
 
-    return code
+    if hidden > 0:
+        code += f"<p>Extension hidden: {hidden}</p>"
+
+    return code, list(tags)
 
 
 def create_ui():
@@ -238,21 +262,30 @@ def create_ui():
                     extension_to_install = gr.Text(elem_id="extension_to_install", visible=False)
                     install_extension_button = gr.Button(elem_id="install_extension_button", visible=False)
 
+                with gr.Row():
+                    hide_tags = gr.CheckboxGroup(value=["ads", "localization"], label="Hide extensions with tags", choices=["script", "ads", "localization"])
+
                 install_result = gr.HTML()
                 available_extensions_table = gr.HTML()
 
                 refresh_available_extensions_button.click(
-                    fn=modules.ui.wrap_gradio_call(refresh_available_extensions, extra_outputs=[gr.update(), gr.update()]),
-                    inputs=[available_extensions_index],
-                    outputs=[available_extensions_index, available_extensions_table, install_result],
+                    fn=modules.ui.wrap_gradio_call(refresh_available_extensions, extra_outputs=[gr.update(), gr.update(), gr.update()]),
+                    inputs=[available_extensions_index, hide_tags],
+                    outputs=[available_extensions_index, available_extensions_table, hide_tags, install_result],
                 )
 
                 install_extension_button.click(
                     fn=modules.ui.wrap_gradio_call(install_extension_from_index, extra_outputs=[gr.update(), gr.update()]),
-                    inputs=[extension_to_install],
+                    inputs=[extension_to_install, hide_tags],
                     outputs=[available_extensions_table, extensions_table, install_result],
                 )
 
+                hide_tags.change(
+                    fn=modules.ui.wrap_gradio_call(refresh_available_extensions_for_tags, extra_outputs=[gr.update()]),
+                    inputs=[hide_tags],
+                    outputs=[available_extensions_table, install_result]
+                )
+
             with gr.TabItem("Install from URL"):
                 install_url = gr.Text(label="URL for extension's git repository")
                 install_dirname = gr.Text(label="Local directory name", placeholder="Leave empty for auto")
-- 
cgit v1.2.3


From 6e4de5b4422dfc0d45063b2c8c78b19f00321615 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 6 Nov 2022 11:20:23 +0300
Subject: add load_with_extra function for modules to load checkpoints with
 extended whitelist

---
 modules/safe.py | 40 +++++++++++++++++++++++++++++++++++++---
 1 file changed, 37 insertions(+), 3 deletions(-)

(limited to 'modules')

diff --git a/modules/safe.py b/modules/safe.py
index 348a24fc..a9209e38 100644
--- a/modules/safe.py
+++ b/modules/safe.py
@@ -23,11 +23,18 @@ def encode(*args):
 
 
 class RestrictedUnpickler(pickle.Unpickler):
+    extra_handler = None
+
     def persistent_load(self, saved_id):
         assert saved_id[0] == 'storage'
         return TypedStorage()
 
     def find_class(self, module, name):
+        if self.extra_handler is not None:
+            res = self.extra_handler(module, name)
+            if res is not None:
+                return res
+
         if module == 'collections' and name == 'OrderedDict':
             return getattr(collections, name)
         if module == 'torch._utils' and name in ['_rebuild_tensor_v2', '_rebuild_parameter']:
@@ -52,7 +59,7 @@ class RestrictedUnpickler(pickle.Unpickler):
             return set
 
         # Forbid everything else.
-        raise pickle.UnpicklingError(f"global '{module}/{name}' is forbidden")
+        raise Exception(f"global '{module}/{name}' is forbidden")
 
 
 allowed_zip_names = ["archive/data.pkl", "archive/version"]
@@ -69,7 +76,7 @@ def check_zip_filenames(filename, names):
         raise Exception(f"bad file inside {filename}: {name}")
 
 
-def check_pt(filename):
+def check_pt(filename, extra_handler):
     try:
 
         # new pytorch format is a zip file
@@ -78,6 +85,7 @@ def check_pt(filename):
 
             with z.open('archive/data.pkl') as file:
                 unpickler = RestrictedUnpickler(file)
+                unpickler.extra_handler = extra_handler
                 unpickler.load()
 
     except zipfile.BadZipfile:
@@ -85,16 +93,42 @@ def check_pt(filename):
         # if it's not a zip file, it's an olf pytorch format, with five objects written to pickle
         with open(filename, "rb") as file:
             unpickler = RestrictedUnpickler(file)
+            unpickler.extra_handler = extra_handler
             for i in range(5):
                 unpickler.load()
 
 
 def load(filename, *args, **kwargs):
+    return load_with_extra(filename, *args, **kwargs)
+
+
+def load_with_extra(filename, extra_handler=None, *args, **kwargs):
+    """
+    this functon is intended to be used by extensions that want to load models with
+    some extra classes in them that the usual unpickler would find suspicious.
+
+    Use the extra_handler argument to specify a function that takes module and field name as text,
+    and returns that field's value:
+
+    ```python
+    def extra(module, name):
+        if module == 'collections' and name == 'OrderedDict':
+            return collections.OrderedDict
+
+        return None
+
+    safe.load_with_extra('model.pt', extra_handler=extra)
+    ```
+
+    The alternative to this is just to use safe.unsafe_torch_load('model.pt'), which as the name implies is
+    definitely unsafe.
+    """
+
     from modules import shared
 
     try:
         if not shared.cmd_opts.disable_safe_unpickle:
-            check_pt(filename)
+            check_pt(filename, extra_handler)
 
     except pickle.UnpicklingError:
         print(f"Error verifying pickled file from {filename}:", file=sys.stderr)
-- 
cgit v1.2.3


From 32c0eab89538ba3900bf499291720f80ae4b43e5 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 6 Nov 2022 14:39:41 +0300
Subject: load all settings in one call instead of one by one when the page
 loads

---
 modules/ui.py | 22 ++++++++++++++++------
 1 file changed, 16 insertions(+), 6 deletions(-)

(limited to 'modules')

diff --git a/modules/ui.py b/modules/ui.py
index c946ad59..34c31ef1 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1141,7 +1141,7 @@ def create_ui(wrap_gradio_gpu_call):
             outputs=[html, generation_info, html2],
         )
 
-    with gr.Blocks() as modelmerger_interface:
+    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>")
@@ -1161,7 +1161,7 @@ def create_ui(wrap_gradio_gpu_call):
 
     sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings()
 
-    with gr.Blocks() as train_interface:
+    with gr.Blocks(analytics_enabled=False) as train_interface:
         with gr.Row().style(equal_height=False):
             gr.HTML(value="<p style='margin-bottom: 0.7em'>See <b><a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\">wiki</a></b> for detailed explanation.</p>")
 
@@ -1420,15 +1420,14 @@ def create_ui(wrap_gradio_gpu_call):
 
         if info.refresh is not None:
             if is_quicksettings:
-                res = comp(label=info.label, value=fun, elem_id=elem_id, **(args or {}))
+                res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {}))
                 create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key)
             else:
                 with gr.Row(variant="compact"):
-                    res = comp(label=info.label, value=fun, elem_id=elem_id, **(args or {}))
+                    res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {}))
                     create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key)
         else:
-            res = comp(label=info.label, value=fun, elem_id=elem_id, **(args or {}))
-
+            res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {}))
 
         return res
 
@@ -1639,6 +1638,17 @@ def create_ui(wrap_gradio_gpu_call):
                 outputs=[component, text_settings],
             )
 
+        component_keys = [k for k in opts.data_labels.keys() if k in component_dict]
+
+        def get_settings_values():
+            return [getattr(opts, key) for key in component_keys]
+
+        demo.load(
+            fn=get_settings_values,
+            inputs=[],
+            outputs=[component_dict[k] for k in component_keys],
+        )
+
         def modelmerger(*args):
             try:
                 results = modules.extras.run_modelmerger(*args)
-- 
cgit v1.2.3