From 14c1c2b9351f16d43ba4e6b6c9062edad44a6bec Mon Sep 17 00:00:00 2001
From: Alexandre Simard <as.simard@outlook.com>
Date: Wed, 19 Oct 2022 13:53:52 -0400
Subject: Show PB texts at same time and earlier

For big tasks (1000+ steps), waiting 1 minute to see ETA is long and this changes it so the number of steps done plays a role in showing the text as well.
---
 modules/ui.py | 11 +++++++----
 1 file changed, 7 insertions(+), 4 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index a2dbd41e..0abd177a 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -261,14 +261,14 @@ def wrap_gradio_call(func, extra_outputs=None):
     return f
 
 
-def calc_time_left(progress, threshold, label, force_display):
+def calc_time_left(progress, threshold, label, force_display, showTime):
     if progress == 0:
         return ""
     else:
         time_since_start = time.time() - shared.state.time_start
         eta = (time_since_start/progress)
         eta_relative = eta-time_since_start
-        if (eta_relative > threshold and progress > 0.02) or force_display:
+        if (eta_relative > threshold and showTime) or force_display:
             if eta_relative > 3600:
                 return label + time.strftime('%H:%M:%S', time.gmtime(eta_relative))
             elif eta_relative > 60:
@@ -290,7 +290,10 @@ def check_progress_call(id_part):
     if shared.state.sampling_steps > 0:
         progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps
 
-    time_left = calc_time_left( progress, 1, " ETA: ", shared.state.time_left_force_display )
+    # Show progress percentage and time left at the same moment, and base it also on steps done
+    showPBText = progress >= 0.01 or shared.state.sampling_step >= 10
+
+    time_left = calc_time_left( progress, 1, " ETA: ", shared.state.time_left_force_display, showPBText )
     if time_left != "":
         shared.state.time_left_force_display = True
 
@@ -298,7 +301,7 @@ def check_progress_call(id_part):
 
     progressbar = ""
     if opts.show_progressbar:
-        progressbar = f"""<div class='progressDiv'><div class='progress' style="overflow:visible;width:{progress * 100}%;white-space:nowrap;">{"&nbsp;" * 2 + str(int(progress*100))+"%" + time_left if progress > 0.01 else ""}</div></div>"""
+        progressbar = f"""<div class='progressDiv'><div class='progress' style="overflow:visible;width:{progress * 100}%;white-space:nowrap;">{"&nbsp;" * 2 + str(int(progress*100))+"%" + time_left if showPBText else ""}</div></div>"""
 
     image = gr_show(False)
     preview_visibility = gr_show(False)
-- 
cgit v1.2.3


From 2a25729623717cc499e873752d9f4ebebd1e1078 Mon Sep 17 00:00:00 2001
From: Muhammad Rizqi Nur <rizqinur2010@gmail.com>
Date: Fri, 28 Oct 2022 09:44:56 +0700
Subject: Gradient clipping in train tab

---
 modules/hypernetworks/hypernetwork.py | 10 +++++++++-
 modules/ui.py                         |  7 +++++++
 2 files changed, 16 insertions(+), 1 deletion(-)

(limited to 'modules/ui.py')

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 8113b35b..c5d60654 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -327,7 +327,7 @@ def report_statistics(loss_info:dict):
 
 
 
-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, clip_grad_mode, clip_grad_value, 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
 
@@ -384,6 +384,9 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
     if ititial_step > steps:
         return hypernetwork, filename
 
+    clip_grad_mode_value = clip_grad_mode == "value"
+    clip_grad_mode_norm = clip_grad_mode == "norm"
+
     scheduler = LearnRateScheduler(learn_rate, steps, ititial_step)
     # if optimizer == "AdamW": or else Adam / AdamW / SGD, etc...
     optimizer = torch.optim.AdamW(weights, lr=scheduler.learn_rate)
@@ -426,6 +429,11 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
                 steps_without_grad = 0
             assert steps_without_grad < 10, 'no gradient found for the trained weight after backward() for 10 steps in a row; this is a bug; training cannot continue'
 
+            if clip_grad_mode_value:
+                torch.nn.utils.clip_grad_value_(weights, clip_value=clip_grad_value)
+            elif clip_grad_mode_norm:
+                torch.nn.utils.clip_grad_norm_(weights, max_norm=clip_grad_value)
+
             optimizer.step()
 
         if torch.isnan(losses[hypernetwork.step % losses.shape[0]]):
diff --git a/modules/ui.py b/modules/ui.py
index 0a63e357..97de7da2 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1313,6 +1313,9 @@ def create_ui(wrap_gradio_gpu_call):
                     training_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
                     training_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
                     steps = gr.Number(label='Max steps', value=100000, precision=0)
+                    with gr.Row():
+                        clip_grad_mode = gr.Dropdown(value="disabled", label="Gradient Clipping", choices=["disabled", "value", "norm"])
+                        clip_grad_value = gr.Number(value=1.0, show_label=False)
                     create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0)
                     save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0)
                     save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True)
@@ -1406,6 +1409,8 @@ def create_ui(wrap_gradio_gpu_call):
                 training_width,
                 training_height,
                 steps,
+                clip_grad_mode,
+                clip_grad_value,
                 create_image_every,
                 save_embedding_every,
                 template_file,
@@ -1431,6 +1436,8 @@ def create_ui(wrap_gradio_gpu_call):
                 training_width,
                 training_height,
                 steps,
+                clip_grad_mode,
+                clip_grad_value,
                 create_image_every,
                 save_embedding_every,
                 template_file,
-- 
cgit v1.2.3


From a133042c669f666763f5da0f4440abdc839db653 Mon Sep 17 00:00:00 2001
From: Muhammad Rizqi Nur <rizqinur2010@gmail.com>
Date: Fri, 28 Oct 2022 10:01:46 +0700
Subject: Forgot to remove this from train_embedding

---
 modules/ui.py | 2 --
 1 file changed, 2 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index 97de7da2..ba5e92a7 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1409,8 +1409,6 @@ def create_ui(wrap_gradio_gpu_call):
                 training_width,
                 training_height,
                 steps,
-                clip_grad_mode,
-                clip_grad_value,
                 create_image_every,
                 save_embedding_every,
                 template_file,
-- 
cgit v1.2.3


From 1618df41bad092e068c61bf510b1e20856821ad5 Mon Sep 17 00:00:00 2001
From: Muhammad Rizqi Nur <rizqinur2010@gmail.com>
Date: Fri, 28 Oct 2022 10:31:27 +0700
Subject: Gradient clipping for textual embedding

---
 modules/textual_inversion/textual_inversion.py | 11 ++++++++++-
 modules/ui.py                                  |  2 ++
 2 files changed, 12 insertions(+), 1 deletion(-)

(limited to 'modules/ui.py')

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index ff002d3e..7bad73a6 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -206,7 +206,7 @@ def write_loss(log_directory, filename, step, epoch_len, values):
         })
 
 
-def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
+def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_directory, training_width, training_height, steps, clip_grad_mode, clip_grad_value, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
     assert embedding_name, 'embedding not selected'
 
     shared.state.textinfo = "Initializing textual inversion training..."
@@ -256,6 +256,9 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
     if ititial_step > steps:
         return embedding, filename
 
+    clip_grad_mode_value = clip_grad_mode == "value"
+    clip_grad_mode_norm = clip_grad_mode == "norm"
+
     scheduler = LearnRateScheduler(learn_rate, steps, ititial_step)
     optimizer = torch.optim.AdamW([embedding.vec], lr=scheduler.learn_rate)
 
@@ -280,6 +283,12 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
 
             optimizer.zero_grad()
             loss.backward()
+
+            if clip_grad_mode_value:
+                torch.nn.utils.clip_grad_value_(embedding.vec, clip_value=clip_grad_value)
+            elif clip_grad_mode_norm:
+                torch.nn.utils.clip_grad_norm_(embedding.vec, max_norm=clip_grad_value)
+
             optimizer.step()
 
 
diff --git a/modules/ui.py b/modules/ui.py
index ba5e92a7..97de7da2 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1409,6 +1409,8 @@ def create_ui(wrap_gradio_gpu_call):
                 training_width,
                 training_height,
                 steps,
+                clip_grad_mode,
+                clip_grad_value,
                 create_image_every,
                 save_embedding_every,
                 template_file,
-- 
cgit v1.2.3


From 16451ca573220e49f2eaaab97580b6b91287c8c4 Mon Sep 17 00:00:00 2001
From: Muhammad Rizqi Nur <rizqinur2010@gmail.com>
Date: Fri, 28 Oct 2022 17:16:23 +0700
Subject: Learning rate sched syntax support for grad clipping

---
 modules/hypernetworks/hypernetwork.py          | 13 ++++++++++---
 modules/textual_inversion/learn_schedule.py    | 11 ++++++++---
 modules/textual_inversion/textual_inversion.py | 12 +++++++++---
 modules/ui.py                                  |  7 +++----
 4 files changed, 30 insertions(+), 13 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index c5d60654..86532063 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -383,11 +383,15 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
     ititial_step = hypernetwork.step or 0
     if ititial_step > steps:
         return hypernetwork, filename
-
+    
     clip_grad_mode_value = clip_grad_mode == "value"
     clip_grad_mode_norm = clip_grad_mode == "norm"
+    clip_grad_enabled = clip_grad_mode_value or clip_grad_mode_norm
+    if clip_grad_enabled:
+        clip_grad_sched = LearnRateScheduler(clip_grad_value, steps, ititial_step, verbose=False)
 
     scheduler = LearnRateScheduler(learn_rate, steps, ititial_step)
+
     # if optimizer == "AdamW": or else Adam / AdamW / SGD, etc...
     optimizer = torch.optim.AdamW(weights, lr=scheduler.learn_rate)
 
@@ -407,6 +411,9 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
         if shared.state.interrupted:
             break
 
+        if clip_grad_enabled:
+            clip_grad_sched.step(hypernetwork.step)
+
         with torch.autocast("cuda"):
             c = stack_conds([entry.cond for entry in entries]).to(devices.device)
             # c = torch.vstack([entry.cond for entry in entries]).to(devices.device)
@@ -430,9 +437,9 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
             assert steps_without_grad < 10, 'no gradient found for the trained weight after backward() for 10 steps in a row; this is a bug; training cannot continue'
 
             if clip_grad_mode_value:
-                torch.nn.utils.clip_grad_value_(weights, clip_value=clip_grad_value)
+                torch.nn.utils.clip_grad_value_(weights, clip_value=clip_grad_sched.learn_rate)
             elif clip_grad_mode_norm:
-                torch.nn.utils.clip_grad_norm_(weights, max_norm=clip_grad_value)
+                torch.nn.utils.clip_grad_norm_(weights, max_norm=clip_grad_sched.learn_rate)
 
             optimizer.step()
 
diff --git a/modules/textual_inversion/learn_schedule.py b/modules/textual_inversion/learn_schedule.py
index 2062726a..ffec3e1b 100644
--- a/modules/textual_inversion/learn_schedule.py
+++ b/modules/textual_inversion/learn_schedule.py
@@ -51,14 +51,19 @@ class LearnRateScheduler:
 
         self.finished = False
 
-    def apply(self, optimizer, step_number):
+    def step(self, step_number):
         if step_number <= self.end_step:
-            return
+            return False
 
         try:
             (self.learn_rate, self.end_step) = next(self.schedules)
-        except Exception:
+        except StopIteration:
             self.finished = True
+            return False
+        return True
+
+    def apply(self, optimizer, step_number):
+        if not self.step(step_number):
             return
 
         if self.verbose:
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 7bad73a6..6b00c6a1 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -255,9 +255,12 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
     ititial_step = embedding.step or 0
     if ititial_step > steps:
         return embedding, filename
-
+    
     clip_grad_mode_value = clip_grad_mode == "value"
     clip_grad_mode_norm = clip_grad_mode == "norm"
+    clip_grad_enabled = clip_grad_mode_value or clip_grad_mode_norm
+    if clip_grad_enabled:
+        clip_grad_sched = LearnRateScheduler(clip_grad_value, steps, ititial_step, verbose=False)
 
     scheduler = LearnRateScheduler(learn_rate, steps, ititial_step)
     optimizer = torch.optim.AdamW([embedding.vec], lr=scheduler.learn_rate)
@@ -273,6 +276,9 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
         if shared.state.interrupted:
             break
 
+        if clip_grad_enabled:
+            clip_grad_sched.step(embedding.step)
+
         with torch.autocast("cuda"):
             c = cond_model([entry.cond_text for entry in entries])
             x = torch.stack([entry.latent for entry in entries]).to(devices.device)
@@ -285,9 +291,9 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
             loss.backward()
 
             if clip_grad_mode_value:
-                torch.nn.utils.clip_grad_value_(embedding.vec, clip_value=clip_grad_value)
+                torch.nn.utils.clip_grad_value_(embedding.vec, clip_value=clip_grad_sched.learn_rate)
             elif clip_grad_mode_norm:
-                torch.nn.utils.clip_grad_norm_(embedding.vec, max_norm=clip_grad_value)
+                torch.nn.utils.clip_grad_norm_(embedding.vec, max_norm=clip_grad_sched.learn_rate)
 
             optimizer.step()
 
diff --git a/modules/ui.py b/modules/ui.py
index 97de7da2..47d16429 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1305,7 +1305,9 @@ def create_ui(wrap_gradio_gpu_call):
                     with gr.Row():
                         embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005")
                         hypernetwork_learn_rate = gr.Textbox(label='Hypernetwork Learning rate', placeholder="Hypernetwork Learning rate", value="0.00001")
-
+                    with gr.Row():
+                        clip_grad_mode = gr.Dropdown(value="disabled", label="Gradient Clipping", choices=["disabled", "value", "norm"])
+                        clip_grad_value = gr.Textbox(placeholder="Gradient clip value", value="1.0", show_label=False)
                     batch_size = gr.Number(label='Batch size', value=1, precision=0)
                     dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images")
                     log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")
@@ -1313,9 +1315,6 @@ def create_ui(wrap_gradio_gpu_call):
                     training_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
                     training_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
                     steps = gr.Number(label='Max steps', value=100000, precision=0)
-                    with gr.Row():
-                        clip_grad_mode = gr.Dropdown(value="disabled", label="Gradient Clipping", choices=["disabled", "value", "norm"])
-                        clip_grad_value = gr.Number(value=1.0, show_label=False)
                     create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0)
                     save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0)
                     save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True)
-- 
cgit v1.2.3


From 840307f23738c38f7ac3ad636e53ccec66e71f8b Mon Sep 17 00:00:00 2001
From: Muhammad Rizqi Nur <rizqinur2010@gmail.com>
Date: Mon, 31 Oct 2022 13:49:24 +0700
Subject: Change default clip grad value to 0.1

It still defaults to disabled.

Ref for value: https://github.com/danielalcalde/stable-diffusion-webui/commit/732b15820a9bde9f47e075a6209c3d47d47acb08
---
 modules/ui.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index 98f9565f..364953aa 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1256,7 +1256,7 @@ def create_ui(wrap_gradio_gpu_call):
                         hypernetwork_learn_rate = gr.Textbox(label='Hypernetwork Learning rate', placeholder="Hypernetwork Learning rate", value="0.00001")
                     with gr.Row():
                         clip_grad_mode = gr.Dropdown(value="disabled", label="Gradient Clipping", choices=["disabled", "value", "norm"])
-                        clip_grad_value = gr.Textbox(placeholder="Gradient clip value", value="1.0", show_label=False)
+                        clip_grad_value = gr.Textbox(placeholder="Gradient clip value", value="0.1", show_label=False)
                     batch_size = gr.Number(label='Batch size', value=1, precision=0)
                     dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images")
                     log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")
-- 
cgit v1.2.3


From f55ac33d446185680604e872ceda2ae858821d5c Mon Sep 17 00:00:00 2001
From: Vladimir Mandic <mandic00@live.com>
Date: Sat, 31 Dec 2022 11:27:02 -0500
Subject: validate textual inversion embeddings

---
 modules/sd_models.py                           |  3 ++
 modules/textual_inversion/textual_inversion.py | 43 +++++++++++++++++++++++---
 modules/ui.py                                  |  2 --
 3 files changed, 41 insertions(+), 7 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/sd_models.py b/modules/sd_models.py
index ecdd91c5..ebd4dff7 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -325,6 +325,9 @@ def load_model(checkpoint_info=None):
     script_callbacks.model_loaded_callback(sd_model)
 
     print("Model loaded.")
+
+    sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings(force_reload = True) # Reload embeddings after model load as they may or may not fit the model
+
     return sd_model
 
 
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index f6112578..103ace60 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -23,6 +23,8 @@ class Embedding:
         self.vec = vec
         self.name = name
         self.step = step
+        self.shape = None
+        self.vectors = 0
         self.cached_checksum = None
         self.sd_checkpoint = None
         self.sd_checkpoint_name = None
@@ -57,8 +59,10 @@ class EmbeddingDatabase:
     def __init__(self, embeddings_dir):
         self.ids_lookup = {}
         self.word_embeddings = {}
+        self.skipped_embeddings = []
         self.dir_mtime = None
         self.embeddings_dir = embeddings_dir
+        self.expected_shape = -1
 
     def register_embedding(self, embedding, model):
 
@@ -75,14 +79,35 @@ class EmbeddingDatabase:
 
         return embedding
 
-    def load_textual_inversion_embeddings(self):
+    def get_expected_shape(self):
+        expected_shape = -1 # initialize with unknown
+        idx = torch.tensor(0).to(shared.device)
+        if expected_shape == -1:
+            try: # matches sd15 signature
+                first_embedding = shared.sd_model.cond_stage_model.wrapped.transformer.text_model.embeddings.token_embedding.wrapped(idx)
+                expected_shape = first_embedding.shape[0]
+            except:
+                pass
+        if expected_shape == -1:
+            try: # matches sd20 signature
+                first_embedding = shared.sd_model.cond_stage_model.wrapped.model.token_embedding.wrapped(idx)
+                expected_shape = first_embedding.shape[0]
+            except:
+                pass
+        if expected_shape == -1:
+            print('Could not determine expected embeddings shape from model')
+        return expected_shape
+
+    def load_textual_inversion_embeddings(self, force_reload = False):
         mt = os.path.getmtime(self.embeddings_dir)
-        if self.dir_mtime is not None and mt <= self.dir_mtime:
+        if not force_reload and self.dir_mtime is not None and mt <= self.dir_mtime:
             return
 
         self.dir_mtime = mt
         self.ids_lookup.clear()
         self.word_embeddings.clear()
+        self.skipped_embeddings = []
+        self.expected_shape = self.get_expected_shape()
 
         def process_file(path, filename):
             name = os.path.splitext(filename)[0]
@@ -122,7 +147,14 @@ class EmbeddingDatabase:
             embedding.step = data.get('step', None)
             embedding.sd_checkpoint = data.get('sd_checkpoint', None)
             embedding.sd_checkpoint_name = data.get('sd_checkpoint_name', None)
-            self.register_embedding(embedding, shared.sd_model)
+            embedding.vectors = vec.shape[0]
+            embedding.shape = vec.shape[-1]
+
+            if (self.expected_shape == -1) or (self.expected_shape == embedding.shape):
+                self.register_embedding(embedding, shared.sd_model)
+            else:
+                self.skipped_embeddings.append(name)
+                # print('Skipping embedding {name}: shape was {shape} expected {expected}'.format(name = name, shape = embedding.shape, expected = self.expected_shape))
 
         for fn in os.listdir(self.embeddings_dir):
             try:
@@ -137,8 +169,9 @@ class EmbeddingDatabase:
                 print(traceback.format_exc(), file=sys.stderr)
                 continue
 
-        print(f"Loaded a total of {len(self.word_embeddings)} textual inversion embeddings.")
-        print("Embeddings:", ', '.join(self.word_embeddings.keys()))
+        print("Textual inversion embeddings {num} loaded: {val}".format(num = len(self.word_embeddings), val = ', '.join(self.word_embeddings.keys())))
+        if (len(self.skipped_embeddings) > 0):
+            print("Textual inversion embeddings {num} skipped: {val}".format(num = len(self.skipped_embeddings), val = ', '.join(self.skipped_embeddings)))
 
     def find_embedding_at_position(self, tokens, offset):
         token = tokens[offset]
diff --git a/modules/ui.py b/modules/ui.py
index 57ee0465..397dd804 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1157,8 +1157,6 @@ def create_ui():
             with gr.Column(variant='panel'):
                 submit_result = gr.Textbox(elem_id="modelmerger_result", show_label=False)
 
-    sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings()
-
     with gr.Blocks(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>")
-- 
cgit v1.2.3


From f4535f6e4f001314bd155bc6e1b6908e02792b9a Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 31 Dec 2022 23:40:55 +0300
Subject: make it so that memory/embeddings info is displayed in a separate UI
 element from generation parameters, and is preserved when you change the
 displayed infotext by clicking on gallery images

---
 modules/img2img.py    |  2 +-
 modules/processing.py |  5 +++--
 modules/txt2img.py    |  2 +-
 modules/ui.py         | 31 +++++++++++++++++--------------
 4 files changed, 22 insertions(+), 18 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/img2img.py b/modules/img2img.py
index 81da4b13..ca58b5d8 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -162,4 +162,4 @@ def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, pro
     if opts.do_not_show_images:
         processed.images = []
 
-    return processed.images, generation_info_js, plaintext_to_html(processed.info)
+    return processed.images, generation_info_js, plaintext_to_html(processed.info), plaintext_to_html(processed.comments)
diff --git a/modules/processing.py b/modules/processing.py
index 0a9a8f95..42dc19ea 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -239,7 +239,7 @@ class StableDiffusionProcessing():
 
 
 class Processed:
-    def __init__(self, p: StableDiffusionProcessing, images_list, seed=-1, info="", subseed=None, all_prompts=None, all_negative_prompts=None, all_seeds=None, all_subseeds=None, index_of_first_image=0, infotexts=None):
+    def __init__(self, p: StableDiffusionProcessing, images_list, seed=-1, info="", subseed=None, all_prompts=None, all_negative_prompts=None, all_seeds=None, all_subseeds=None, index_of_first_image=0, infotexts=None, comments=""):
         self.images = images_list
         self.prompt = p.prompt
         self.negative_prompt = p.negative_prompt
@@ -247,6 +247,7 @@ class Processed:
         self.subseed = subseed
         self.subseed_strength = p.subseed_strength
         self.info = info
+        self.comments = comments
         self.width = p.width
         self.height = p.height
         self.sampler_name = p.sampler_name
@@ -646,7 +647,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
 
     devices.torch_gc()
 
-    res = Processed(p, output_images, p.all_seeds[0], infotext() + "".join(["\n\n" + x for x in comments]), subseed=p.all_subseeds[0], index_of_first_image=index_of_first_image, infotexts=infotexts)
+    res = Processed(p, output_images, p.all_seeds[0], infotext(), comments="".join(["\n\n" + x for x in comments]), subseed=p.all_subseeds[0], index_of_first_image=index_of_first_image, infotexts=infotexts)
 
     if p.scripts is not None:
         p.scripts.postprocess(p, res)
diff --git a/modules/txt2img.py b/modules/txt2img.py
index c8f81176..7f61e19a 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -59,4 +59,4 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2:
     if opts.do_not_show_images:
         processed.images = []
 
-    return processed.images, generation_info_js, plaintext_to_html(processed.info)
+    return processed.images, generation_info_js, plaintext_to_html(processed.info), plaintext_to_html(processed.comments)
diff --git a/modules/ui.py b/modules/ui.py
index 397dd804..f550ad00 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -159,7 +159,7 @@ def save_files(js_data, images, do_make_zip, index):
                     zip_file.writestr(filenames[i], f.read())
         fullfns.insert(0, zip_filepath)
 
-    return gr.File.update(value=fullfns, visible=True), '', '', plaintext_to_html(f"Saved: {filenames[0]}")
+    return gr.File.update(value=fullfns, visible=True), plaintext_to_html(f"Saved: {filenames[0]}")
 
 
 
@@ -593,6 +593,8 @@ Requested path was: {f}
 
                     with gr.Group():
                         html_info = gr.HTML()
+                        html_log = gr.HTML()
+
                         generation_info = gr.Textbox(visible=False)
                         if tabname == 'txt2img' or tabname == 'img2img':
                             generation_info_button = gr.Button(visible=False, elem_id=f"{tabname}_generation_info_button")
@@ -615,16 +617,16 @@ Requested path was: {f}
                             ],
                             outputs=[
                                 download_files,
-                                html_info,
-                                html_info,
-                                html_info,
+                                html_log,
                             ]
                         )
                 else:
                     html_info_x = gr.HTML()
                     html_info = gr.HTML()
+                    html_log = gr.HTML()
+
                 parameters_copypaste.bind_buttons(buttons, result_gallery, "txt2img" if tabname == "txt2img" else None)
-                return result_gallery, generation_info if tabname != "extras" else html_info_x, html_info
+                return result_gallery, generation_info if tabname != "extras" else html_info_x, html_info, html_log
 
 
 def create_ui():
@@ -686,14 +688,14 @@ def create_ui():
                 with gr.Group():
                     custom_inputs = modules.scripts.scripts_txt2img.setup_ui()
 
-            txt2img_gallery, generation_info, html_info = create_output_panel("txt2img", opts.outdir_txt2img_samples)
+            txt2img_gallery, generation_info, html_info, html_log = create_output_panel("txt2img", opts.outdir_txt2img_samples)
             parameters_copypaste.bind_buttons({"txt2img": txt2img_paste}, None, txt2img_prompt)
 
             connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
             connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
 
             txt2img_args = dict(
-                fn=wrap_gradio_gpu_call(modules.txt2img.txt2img),
+                fn=wrap_gradio_gpu_call(modules.txt2img.txt2img, extra_outputs=[None, '', '']),
                 _js="submit",
                 inputs=[
                     txt2img_prompt,
@@ -720,7 +722,8 @@ def create_ui():
                 outputs=[
                     txt2img_gallery,
                     generation_info,
-                    html_info
+                    html_info,
+                    html_log,
                 ],
                 show_progress=False,
             )
@@ -799,7 +802,6 @@ def create_ui():
     with gr.Blocks(analytics_enabled=False) as img2img_interface:
         img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,token_counter, token_button = create_toprow(is_img2img=True)
 
-
         with gr.Row(elem_id='img2img_progress_row'):
             img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False)
 
@@ -883,7 +885,7 @@ def create_ui():
                 with gr.Group():
                     custom_inputs = modules.scripts.scripts_img2img.setup_ui()
 
-            img2img_gallery, generation_info, html_info = create_output_panel("img2img", opts.outdir_img2img_samples)
+            img2img_gallery, generation_info, html_info, html_log = create_output_panel("img2img", opts.outdir_img2img_samples)
             parameters_copypaste.bind_buttons({"img2img": img2img_paste}, None, img2img_prompt)
 
             connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
@@ -915,7 +917,7 @@ def create_ui():
             )
 
             img2img_args = dict(
-                fn=wrap_gradio_gpu_call(modules.img2img.img2img),
+                fn=wrap_gradio_gpu_call(modules.img2img.img2img, extra_outputs=[None, '', '']),
                 _js="submit_img2img",
                 inputs=[
                     dummy_component,
@@ -954,7 +956,8 @@ def create_ui():
                 outputs=[
                     img2img_gallery,
                     generation_info,
-                    html_info
+                    html_info,
+                    html_log,
                 ],
                 show_progress=False,
             )
@@ -1078,10 +1081,10 @@ def create_ui():
                 with gr.Group():
                     upscale_before_face_fix = gr.Checkbox(label='Upscale Before Restoring Faces', value=False)
 
-            result_images, html_info_x, html_info = create_output_panel("extras", opts.outdir_extras_samples)
+            result_images, html_info_x, html_info, html_log = create_output_panel("extras", opts.outdir_extras_samples)
 
         submit.click(
-            fn=wrap_gradio_gpu_call(modules.extras.run_extras),
+            fn=wrap_gradio_gpu_call(modules.extras.run_extras, extra_outputs=[None, '']),
             _js="get_extras_tab_index",
             inputs=[
                 dummy_component,
-- 
cgit v1.2.3


From 360feed9b55fb03060c236773867b08b4265645d Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 1 Jan 2023 00:38:58 +0300
Subject: HAPPY NEW YEAR

make save to zip into its own button instead of a checkbox
---
 modules/ui.py | 30 ++++++++++++++++++++++--------
 style.css     |  6 ++++++
 2 files changed, 28 insertions(+), 8 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index f550ad00..279b5110 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -570,13 +570,14 @@ Requested path was: {f}
 
             generation_info = None
             with gr.Column():
-                with gr.Row():
+                with gr.Row(elem_id=f"image_buttons_{tabname}"):
+                    open_folder_button = gr.Button(folder_symbol, elem_id="hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder')
+
                     if tabname != "extras":
                         save = gr.Button('Save', elem_id=f'save_{tabname}')
+                        save_zip = gr.Button('Zip', elem_id=f'save_zip_{tabname}')
 
                     buttons = parameters_copypaste.create_buttons(["img2img", "inpaint", "extras"])
-                    button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder'
-                    open_folder_button = gr.Button(folder_symbol, elem_id=button_id)
 
                 open_folder_button.click(
                     fn=lambda: open_folder(opts.outdir_samples or outdir),
@@ -585,9 +586,6 @@ Requested path was: {f}
                 )
 
                 if tabname != "extras":
-                    with gr.Row():
-                        do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
-
                     with gr.Row():
                         download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
 
@@ -608,11 +606,11 @@ Requested path was: {f}
 
                         save.click(
                             fn=wrap_gradio_call(save_files),
-                            _js="(x, y, z, w) => [x, y, z, selected_gallery_index()]",
+                            _js="(x, y, z, w) => [x, y, false, selected_gallery_index()]",
                             inputs=[
                                 generation_info,
                                 result_gallery,
-                                do_make_zip,
+                                html_info,
                                 html_info,
                             ],
                             outputs=[
@@ -620,6 +618,22 @@ Requested path was: {f}
                                 html_log,
                             ]
                         )
+
+                        save_zip.click(
+                            fn=wrap_gradio_call(save_files),
+                            _js="(x, y, z, w) => [x, y, true, selected_gallery_index()]",
+                            inputs=[
+                                generation_info,
+                                result_gallery,
+                                html_info,
+                                html_info,
+                            ],
+                            outputs=[
+                                download_files,
+                                html_log,
+                            ]
+                        )
+
                 else:
                     html_info_x = gr.HTML()
                     html_info = gr.HTML()
diff --git a/style.css b/style.css
index 3ad78006..f245f674 100644
--- a/style.css
+++ b/style.css
@@ -568,6 +568,12 @@ img2maskimg, #img2maskimg > .h-60, #img2maskimg > .h-60 > div, #img2maskimg > .h
     font-size: 95%;
 }
 
+#image_buttons_txt2img button, #image_buttons_img2img button, #image_buttons_extras button{
+    min-width: auto;
+    padding-left: 0.5em;
+    padding-right: 0.5em;
+}
+
 /* The following handles localization for right-to-left (RTL) languages like Arabic.
 The rtl media type will only be activated by the logic in javascript/localization.js.
 If you change anything above, you need to make sure it is RTL compliant by just running
-- 
cgit v1.2.3


From 29a3a7eb13478297bc7093971b48827ab8246f45 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 1 Jan 2023 01:19:10 +0300
Subject: show sampler selection in dropdown, add option selection to revert to
 old radio group

---
 modules/shared.py |  1 +
 modules/ui.py     | 22 +++++++++++++++-------
 2 files changed, 16 insertions(+), 7 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/shared.py b/modules/shared.py
index 715b9169..948b9542 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -406,6 +406,7 @@ options_templates.update(options_section(('ui', "User interface"), {
     "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"),
     "js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),
     "show_progress_in_title": OptionInfo(True, "Show generation progress in window title."),
+    "samplers_in_dropdown": OptionInfo(True, "Use dropdown for sampler selection instead of radio group"),
     'quicksettings': OptionInfo("sd_model_checkpoint", "Quicksettings list"),
     'localization': OptionInfo("None", "Localization (requires restart)", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)),
 }))
diff --git a/modules/ui.py b/modules/ui.py
index 279b5110..c7b8ea5d 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -643,6 +643,19 @@ Requested path was: {f}
                 return result_gallery, generation_info if tabname != "extras" else html_info_x, html_info, html_log
 
 
+def create_sampler_and_steps_selection(choices, tabname):
+    if opts.samplers_in_dropdown:
+        with gr.Row(elem_id=f"sampler_selection_{tabname}"):
+            sampler_index = gr.Dropdown(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")
+            steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling Steps", value=20)
+    else:
+        with gr.Group(elem_id=f"sampler_selection_{tabname}"):
+            steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling Steps", value=20)
+            sampler_index = gr.Radio(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")
+
+    return steps, sampler_index
+
+
 def create_ui():
     import modules.img2img
     import modules.txt2img
@@ -660,9 +673,6 @@ def create_ui():
         dummy_component = gr.Label(visible=False)
         txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False)
 
-
-
-
         with gr.Row(elem_id='txt2img_progress_row'):
             with gr.Column(scale=1):
                 pass
@@ -674,8 +684,7 @@ def create_ui():
 
         with gr.Row().style(equal_height=False):
             with gr.Column(variant='panel', elem_id="txt2img_settings"):
-                steps = gr.Slider(minimum=1, maximum=150, step=1, label="Sampling Steps", value=20)
-                sampler_index = gr.Radio(label='Sampling method', elem_id="txt2img_sampling", choices=[x.name for x in samplers], value=samplers[0].name, type="index")
+                steps, sampler_index = create_sampler_and_steps_selection(samplers, "txt2img")
 
                 with gr.Group():
                     width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512)
@@ -875,8 +884,7 @@ def create_ui():
                 with gr.Row():
                     resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", show_label=False, choices=["Just resize", "Crop and resize", "Resize and fill", "Just resize (latent upscale)"], type="index", value="Just resize")
 
-                steps = gr.Slider(minimum=1, maximum=150, step=1, label="Sampling Steps", value=20)
-                sampler_index = gr.Radio(label='Sampling method', choices=[x.name for x in samplers_for_img2img], value=samplers_for_img2img[0].name, type="index")
+                steps, sampler_index = create_sampler_and_steps_selection(samplers_for_img2img, "img2img")
 
                 with gr.Group():
                     width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
-- 
cgit v1.2.3


From 11d432d92d63660c516540dcb48faac87669b4f0 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 1 Jan 2023 10:35:38 +0300
Subject: add refresh buttons to checkpoint merger

---
 modules/ui.py | 6 ++++++
 style.css     | 2 +-
 2 files changed, 7 insertions(+), 1 deletion(-)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index c7b8ea5d..4cc2ce4f 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1167,8 +1167,14 @@ def create_ui():
 
                 with gr.Row():
                     primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)")
+                    create_refresh_button(primary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_A")
+
                     secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary model (B)")
+                    create_refresh_button(secondary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_B")
+
                     tertiary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_tertiary_model_name", label="Tertiary model (C)")
+                    create_refresh_button(tertiary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_C")
+
                 custom_name = gr.Textbox(label="Custom Name (Optional)")
                 interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3)
                 interp_method = gr.Radio(choices=["Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method")
diff --git a/style.css b/style.css
index 4b98b84d..516ef7bf 100644
--- a/style.css
+++ b/style.css
@@ -496,7 +496,7 @@ input[type="range"]{
     padding: 0;
 }
 
-#refresh_sd_model_checkpoint, #refresh_sd_vae, #refresh_sd_hypernetwork, #refresh_train_hypernetwork_name, #refresh_train_embedding_name, #refresh_localization{
+#refresh_sd_model_checkpoint, #refresh_sd_vae, #refresh_sd_hypernetwork, #refresh_train_hypernetwork_name, #refresh_train_embedding_name, #refresh_localization, #refresh_checkpoint_A, #refresh_checkpoint_B, #refresh_checkpoint_C{
     max-width: 2.5em;
     min-width: 2.5em;
     height: 2.4em;
-- 
cgit v1.2.3


From e5f1a37cb9b537d95b2df47c96b4a4f7242fd294 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 1 Jan 2023 13:08:40 +0300
Subject: make refresh buttons look more nice

---
 modules/ui.py            |  6 +++---
 modules/ui_components.py | 18 ++++++++++++++++++
 style.css                | 28 +++++++++++++++++++++-------
 3 files changed, 42 insertions(+), 10 deletions(-)
 create mode 100644 modules/ui_components.py

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index 4cc2ce4f..32fa80d1 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -19,7 +19,7 @@ import numpy as np
 from PIL import Image, PngImagePlugin
 from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
 
-from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru
+from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, ui_components
 from modules.paths import script_path
 
 from modules.shared import opts, cmd_opts, restricted_opts
@@ -532,7 +532,7 @@ def create_refresh_button(refresh_component, refresh_method, refreshed_args, ele
 
         return gr.update(**(args or {}))
 
-    refresh_button = gr.Button(value=refresh_symbol, elem_id=elem_id)
+    refresh_button = ui_components.ToolButton(value=refresh_symbol, elem_id=elem_id)
     refresh_button.click(
         fn=refresh,
         inputs=[],
@@ -1476,7 +1476,7 @@ def create_ui():
                 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"):
+                with ui_components.FormRow():
                     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:
diff --git a/modules/ui_components.py b/modules/ui_components.py
new file mode 100644
index 00000000..d0519d2d
--- /dev/null
+++ b/modules/ui_components.py
@@ -0,0 +1,18 @@
+import gradio as gr
+
+
+class ToolButton(gr.Button, gr.components.FormComponent):
+    """Small button with single emoji as text, fits inside gradio forms"""
+
+    def __init__(self, **kwargs):
+        super().__init__(variant="tool", **kwargs)
+
+    def get_block_name(self):
+        return "button"
+
+
+class FormRow(gr.Row, gr.components.FormComponent):
+    """Same as gr.Row but fits inside gradio forms"""
+
+    def get_block_name(self):
+        return "row"
diff --git a/style.css b/style.css
index 516ef7bf..f168571e 100644
--- a/style.css
+++ b/style.css
@@ -496,13 +496,6 @@ input[type="range"]{
     padding: 0;
 }
 
-#refresh_sd_model_checkpoint, #refresh_sd_vae, #refresh_sd_hypernetwork, #refresh_train_hypernetwork_name, #refresh_train_embedding_name, #refresh_localization, #refresh_checkpoint_A, #refresh_checkpoint_B, #refresh_checkpoint_C{
-    max-width: 2.5em;
-    min-width: 2.5em;
-    height: 2.4em;
-}
-
-
 canvas[key="mask"] {
     z-index: 12 !important;
     filter: invert();
@@ -569,6 +562,27 @@ img2maskimg, #img2maskimg > .h-60, #img2maskimg > .h-60 > div, #img2maskimg > .h
     padding-right: 0.5em;
 }
 
+.gr-form{
+    background-color: white;
+}
+
+.dark .gr-form{
+    background-color: rgb(31 41 55 / var(--tw-bg-opacity));
+}
+
+.gr-button-tool{
+    max-width: 2.5em;
+    min-width: 2.5em !important;
+    height: 2.4em;
+    margin: 0.55em 0;
+}
+
+#quicksettings .gr-button-tool{
+    margin: 0;
+}
+
+
+
 /* The following handles localization for right-to-left (RTL) languages like Arabic.
 The rtl media type will only be activated by the logic in javascript/localization.js.
 If you change anything above, you need to make sure it is RTL compliant by just running
-- 
cgit v1.2.3


From 524d532b387732d4d32f237e792c7f201a934400 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 1 Jan 2023 14:07:40 +0300
Subject: moved roll artist to built-in extensions

---
 .../roll-artist/scripts/roll-artist.py             | 50 ++++++++++++++++++++++
 modules/ui.py                                      | 37 ++--------------
 2 files changed, 53 insertions(+), 34 deletions(-)
 create mode 100644 extensions-builtin/roll-artist/scripts/roll-artist.py

(limited to 'modules/ui.py')

diff --git a/extensions-builtin/roll-artist/scripts/roll-artist.py b/extensions-builtin/roll-artist/scripts/roll-artist.py
new file mode 100644
index 00000000..c3bc1fd0
--- /dev/null
+++ b/extensions-builtin/roll-artist/scripts/roll-artist.py
@@ -0,0 +1,50 @@
+import random
+
+from modules import script_callbacks, shared
+import gradio as gr
+
+art_symbol = '\U0001f3a8'  # 🎨
+global_prompt = None
+related_ids = {"txt2img_prompt", "txt2img_clear_prompt", "img2img_prompt", "img2img_clear_prompt" }
+
+
+def roll_artist(prompt):
+    allowed_cats = set([x for x in shared.artist_db.categories() if len(shared.opts.random_artist_categories)==0 or x in shared.opts.random_artist_categories])
+    artist = random.choice([x for x in shared.artist_db.artists if x.category in allowed_cats])
+
+    return prompt + ", " + artist.name if prompt != '' else artist.name
+
+
+def add_roll_button(prompt):
+    roll = gr.Button(value=art_symbol, elem_id="roll", visible=len(shared.artist_db.artists) > 0)
+
+    roll.click(
+        fn=roll_artist,
+        _js="update_txt2img_tokens",
+        inputs=[
+            prompt,
+        ],
+        outputs=[
+            prompt,
+        ]
+    )
+
+
+def after_component(component, **kwargs):
+    global global_prompt
+
+    elem_id = kwargs.get('elem_id', None)
+    if elem_id not in related_ids:
+        return
+
+    if elem_id == "txt2img_prompt":
+        global_prompt = component
+    elif elem_id == "txt2img_clear_prompt":
+        add_roll_button(global_prompt)
+    elif elem_id == "img2img_prompt":
+        global_prompt = component
+    elif elem_id == "img2img_clear_prompt":
+        add_roll_button(global_prompt)
+
+
+script_callbacks.on_after_component(after_component)
diff --git a/modules/ui.py b/modules/ui.py
index 32fa80d1..27da2c2c 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -80,7 +80,6 @@ css_hide_progressbar = """
 # Important that they exactly match script.js for tooltip to work.
 random_symbol = '\U0001f3b2\ufe0f'  # 🎲️
 reuse_symbol = '\u267b\ufe0f'  # ♻️
-art_symbol = '\U0001f3a8'  # 🎨
 paste_symbol = '\u2199\ufe0f'  # ↙
 folder_symbol = '\U0001f4c2'  # 📂
 refresh_symbol = '\U0001f504'  # 🔄
@@ -234,13 +233,6 @@ def check_progress_call_initial(id_part):
     return check_progress_call(id_part)
 
 
-def roll_artist(prompt):
-    allowed_cats = set([x for x in shared.artist_db.categories() if len(opts.random_artist_categories)==0 or x in opts.random_artist_categories])
-    artist = random.choice([x for x in shared.artist_db.artists if x.category in allowed_cats])
-
-    return prompt + ", " + artist.name if prompt != '' else artist.name
-
-
 def visit(x, func, path=""):
     if hasattr(x, 'children'):
         for c in x.children:
@@ -403,7 +395,6 @@ def create_toprow(is_img2img):
                         )
 
         with gr.Column(scale=1, elem_id="roll_col"):
-            roll = gr.Button(value=art_symbol, elem_id="roll", visible=len(shared.artist_db.artists) > 0)
             paste = gr.Button(value=paste_symbol, elem_id="paste")
             save_style = gr.Button(value=save_style_symbol, elem_id="style_create")
             prompt_style_apply = gr.Button(value=apply_style_symbol, elem_id="style_apply")
@@ -452,7 +443,7 @@ def create_toprow(is_img2img):
                     prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())))
                     prompt_style2.save_to_config = True
 
-    return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button
+    return prompt, prompt_style, negative_prompt, prompt_style2, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button
 
 
 def setup_progressbar(progressbar, preview, id_part, textinfo=None):
@@ -668,7 +659,7 @@ def create_ui():
     modules.scripts.scripts_txt2img.initialize_scripts(is_img2img=False)
 
     with gr.Blocks(analytics_enabled=False) as txt2img_interface:
-        txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _,txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False)
+        txt2img_prompt, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _,txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False)
 
         dummy_component = gr.Label(visible=False)
         txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False)
@@ -771,16 +762,6 @@ def create_ui():
                 outputs=[hr_options],
             )
 
-            roll.click(
-                fn=roll_artist,
-                _js="update_txt2img_tokens",
-                inputs=[
-                    txt2img_prompt,
-                ],
-                outputs=[
-                    txt2img_prompt,
-                ]
-            )
 
             txt2img_paste_fields = [
                 (txt2img_prompt, "Prompt"),
@@ -823,7 +804,7 @@ def create_ui():
     modules.scripts.scripts_img2img.initialize_scripts(is_img2img=True)
 
     with gr.Blocks(analytics_enabled=False) as img2img_interface:
-        img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,token_counter, token_button = create_toprow(is_img2img=True)
+        img2img_prompt, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,token_counter, token_button = create_toprow(is_img2img=True)
 
         with gr.Row(elem_id='img2img_progress_row'):
             img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False)
@@ -999,18 +980,6 @@ def create_ui():
                 outputs=[img2img_prompt],
             )
 
-
-            roll.click(
-                fn=roll_artist,
-                _js="update_img2img_tokens",
-                inputs=[
-                    img2img_prompt,
-                ],
-                outputs=[
-                    img2img_prompt,
-                ]
-            )
-
             prompts = [(txt2img_prompt, txt2img_negative_prompt), (img2img_prompt, img2img_negative_prompt)]
             style_dropdowns = [(txt2img_prompt_style, txt2img_prompt_style2), (img2img_prompt_style, img2img_prompt_style2)]
             style_js_funcs = ["update_txt2img_tokens", "update_img2img_tokens"]
-- 
cgit v1.2.3


From a005fccddd5a37c57f1afe5234660b59b9a41508 Mon Sep 17 00:00:00 2001
From: me <25877290+Kryptortio@users.noreply.github.com>
Date: Sun, 1 Jan 2023 14:51:12 +0100
Subject: Add a lot more elem_id/HTML id, modified some that were duplicates
 for seed section

---
 modules/generation_parameters_copypaste.py |   2 +-
 modules/ui.py                              | 254 ++++++++++++++---------------
 style.css                                  |  12 +-
 3 files changed, 134 insertions(+), 134 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py
index 54b3372d..8e7f0df0 100644
--- a/modules/generation_parameters_copypaste.py
+++ b/modules/generation_parameters_copypaste.py
@@ -93,7 +93,7 @@ def integrate_settings_paste_fields(component_dict):
 def create_buttons(tabs_list):
     buttons = {}
     for tab in tabs_list:
-        buttons[tab] = gr.Button(f"Send to {tab}")
+        buttons[tab] = gr.Button(f"Send to {tab}", elem_id=f"{tab}_tab")
     return buttons
 
 
diff --git a/modules/ui.py b/modules/ui.py
index 27da2c2c..7070ea15 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -272,17 +272,17 @@ def interrogate_deepbooru(image):
     return gr_show(True) if prompt is None else prompt
 
 
-def create_seed_inputs():
+def create_seed_inputs(target_interface):
     with gr.Row():
         with gr.Box():
-            with gr.Row(elem_id='seed_row'):
-                seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1)
+            with gr.Row(elem_id=target_interface + '_seed_row'):
+                seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1, elem_id=target_interface + '_seed')
                 seed.style(container=False)
-                random_seed = gr.Button(random_symbol, elem_id='random_seed')
-                reuse_seed = gr.Button(reuse_symbol, elem_id='reuse_seed')
+                random_seed = gr.Button(random_symbol, elem_id=target_interface + '_random_seed')
+                reuse_seed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_seed')
 
-        with gr.Box(elem_id='subseed_show_box'):
-            seed_checkbox = gr.Checkbox(label='Extra', elem_id='subseed_show', value=False)
+        with gr.Box(elem_id=target_interface + '_subseed_show_box'):
+            seed_checkbox = gr.Checkbox(label='Extra', elem_id=target_interface + '_subseed_show', value=False)
 
     # Components to show/hide based on the 'Extra' checkbox
     seed_extras = []
@@ -290,17 +290,17 @@ def create_seed_inputs():
     with gr.Row(visible=False) as seed_extra_row_1:
         seed_extras.append(seed_extra_row_1)
         with gr.Box():
-            with gr.Row(elem_id='subseed_row'):
-                subseed = gr.Number(label='Variation seed', value=-1)
+            with gr.Row(elem_id=target_interface + '_subseed_row'):
+                subseed = gr.Number(label='Variation seed', value=-1, elem_id=target_interface + '_subseed')
                 subseed.style(container=False)
-                random_subseed = gr.Button(random_symbol, elem_id='random_subseed')
-                reuse_subseed = gr.Button(reuse_symbol, elem_id='reuse_subseed')
-        subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01)
+                random_subseed = gr.Button(random_symbol, elem_id=target_interface + '_random_subseed')
+                reuse_subseed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_subseed')
+        subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=target_interface + '_subseed_strength')
 
     with gr.Row(visible=False) as seed_extra_row_2:
         seed_extras.append(seed_extra_row_2)
-        seed_resize_from_w = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from width", value=0)
-        seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from height", value=0)
+        seed_resize_from_w = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from width", value=0, elem_id=target_interface + '_seed_resize_from_w')
+        seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from height", value=0, elem_id=target_interface + '_seed_resize_from_h')
 
     random_seed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[seed])
     random_subseed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[subseed])
@@ -678,28 +678,28 @@ def create_ui():
                 steps, sampler_index = create_sampler_and_steps_selection(samplers, "txt2img")
 
                 with gr.Group():
-                    width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512)
-                    height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512)
+                    width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="txt2img_width")
+                    height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="txt2img_height")
 
                 with gr.Row():
-                    restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1)
-                    tiling = gr.Checkbox(label='Tiling', value=False)
-                    enable_hr = gr.Checkbox(label='Highres. fix', value=False)
+                    restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="txt2img_restore_faces")
+                    tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling")
+                    enable_hr = gr.Checkbox(label='Highres. fix', value=False, elem_id="txt2img_enable_hr")
 
                 with gr.Row(visible=False) as hr_options:
-                    firstphase_width = gr.Slider(minimum=0, maximum=1024, step=8, label="Firstpass width", value=0)
-                    firstphase_height = gr.Slider(minimum=0, maximum=1024, step=8, label="Firstpass height", value=0)
-                    denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7)
+                    firstphase_width = gr.Slider(minimum=0, maximum=1024, step=8, label="Firstpass width", value=0, elem_id="txt2img_firstphase_width")
+                    firstphase_height = gr.Slider(minimum=0, maximum=1024, step=8, label="Firstpass height", value=0, elem_id="txt2img_firstphase_height")
+                    denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7, elem_id="txt2img_denoising_strength")
 
                 with gr.Row(equal_height=True):
-                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1)
-                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1)
+                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
+                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
 
-                cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0)
+                cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="txt2img_cfg_scale")
 
-                seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs()
+                seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('txt2img')
 
-                with gr.Group():
+                with gr.Group(elem_id="txt2img_script_container"):
                     custom_inputs = modules.scripts.scripts_txt2img.setup_ui()
 
             txt2img_gallery, generation_info, html_info, html_log = create_output_panel("txt2img", opts.outdir_txt2img_samples)
@@ -821,10 +821,10 @@ def create_ui():
             with gr.Column(variant='panel', elem_id="img2img_settings"):
 
                 with gr.Tabs(elem_id="mode_img2img") as tabs_img2img_mode:
-                    with gr.TabItem('img2img', id='img2img'):
+                    with gr.TabItem('img2img', id='img2img', elem_id="img2img_img2img_tab"):
                         init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_img2img_tool, image_mode="RGBA").style(height=480)
 
-                    with gr.TabItem('Inpaint', id='inpaint'):
+                    with gr.TabItem('Inpaint', id='inpaint', elem_id="img2img_inpaint_tab"):
                         init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_inpaint_tool, image_mode="RGBA").style(height=480)
                         init_img_with_mask_orig = gr.State(None)
 
@@ -843,24 +843,24 @@ def create_ui():
                         init_mask_inpaint = gr.Image(label="Mask", source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_mask")
 
                         with gr.Row():
-                            mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4)
-                            mask_alpha = gr.Slider(label="Mask transparency", interactive=use_color_sketch, visible=use_color_sketch)
+                            mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id="img2img_mask_blur")
+                            mask_alpha = gr.Slider(label="Mask transparency", interactive=use_color_sketch, visible=use_color_sketch, elem_id="img2img_mask_alpha")
 
                         with gr.Row():
                             mask_mode = gr.Radio(label="Mask mode", show_label=False, choices=["Draw mask", "Upload mask"], type="index", value="Draw mask", elem_id="mask_mode")
-                            inpainting_mask_invert = gr.Radio(label='Masking mode', show_label=False, choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index")
+                            inpainting_mask_invert = gr.Radio(label='Masking mode', show_label=False, choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index", elem_id="img2img_mask_mode")
 
-                        inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='original', type="index")
+                        inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='original', type="index", elem_id="img2img_inpainting_fill")
 
                         with gr.Row():
-                            inpaint_full_res = gr.Checkbox(label='Inpaint at full resolution', value=False)
-                            inpaint_full_res_padding = gr.Slider(label='Inpaint at full resolution padding, pixels', minimum=0, maximum=256, step=4, value=32)
+                            inpaint_full_res = gr.Checkbox(label='Inpaint at full resolution', value=False, elem_id="img2img_inpaint_full_res")
+                            inpaint_full_res_padding = gr.Slider(label='Inpaint at full resolution padding, pixels', minimum=0, maximum=256, step=4, value=32, elem_id="img2img_inpaint_full_res_padding")
 
-                    with gr.TabItem('Batch img2img', id='batch'):
+                    with gr.TabItem('Batch img2img', id='batch', elem_id="img2img_batch_tab"):
                         hidden = '<br>Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else ''
                         gr.HTML(f"<p class=\"text-gray-500\">Process images in a directory on the same machine where the server is running.<br>Use an empty output directory to save pictures normally instead of writing to the output directory.{hidden}</p>")
-                        img2img_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs)
-                        img2img_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs)
+                        img2img_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, elem_id="img2img_batch_input_dir")
+                        img2img_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, elem_id="img2img_batch_output_dir")
 
                 with gr.Row():
                     resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", show_label=False, choices=["Just resize", "Crop and resize", "Resize and fill", "Just resize (latent upscale)"], type="index", value="Just resize")
@@ -872,20 +872,20 @@ def create_ui():
                     height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
 
                 with gr.Row():
-                    restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1)
-                    tiling = gr.Checkbox(label='Tiling', value=False)
+                    restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="img2img_restore_faces")
+                    tiling = gr.Checkbox(label='Tiling', value=False, elem_id="img2img_tiling")
 
                 with gr.Row():
-                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1)
-                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1)
+                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
+                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")
 
                 with gr.Group():
-                    cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0)
-                    denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75)
+                    cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="img2img_cfg_scale")
+                    denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75, elem_id="img2img_denoising_strength")
 
-                seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs()
+                seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('img2img')
 
-                with gr.Group():
+                with gr.Group(elem_id="img2img_script_container"):
                     custom_inputs = modules.scripts.scripts_img2img.setup_ui()
 
             img2img_gallery, generation_info, html_info, html_log = create_output_panel("img2img", opts.outdir_img2img_samples)
@@ -1032,45 +1032,45 @@ def create_ui():
         with gr.Row().style(equal_height=False):
             with gr.Column(variant='panel'):
                 with gr.Tabs(elem_id="mode_extras"):
-                    with gr.TabItem('Single Image'):
-                        extras_image = gr.Image(label="Source", source="upload", interactive=True, type="pil")
+                    with gr.TabItem('Single Image', elem_id="extras_single_tab"):
+                        extras_image = gr.Image(label="Source", source="upload", interactive=True, type="pil", elem_id="extras_image")
 
-                    with gr.TabItem('Batch Process'):
-                        image_batch = gr.File(label="Batch Process", file_count="multiple", interactive=True, type="file")
+                    with gr.TabItem('Batch Process', elem_id="extras_batch_process_tab"):
+                        image_batch = gr.File(label="Batch Process", file_count="multiple", interactive=True, type="file", elem_id="extras_image_batch")
 
-                    with gr.TabItem('Batch from Directory'):
-                        extras_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, placeholder="A directory on the same machine where the server is running.")
-                        extras_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, placeholder="Leave blank to save images to the default path.")
-                        show_extras_results = gr.Checkbox(label='Show result images', value=True)
+                    with gr.TabItem('Batch from Directory', elem_id="extras_batch_directory_tab"):
+                        extras_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, placeholder="A directory on the same machine where the server is running.", elem_id="extras_batch_input_dir")
+                        extras_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, placeholder="Leave blank to save images to the default path.", elem_id="extras_batch_output_dir")
+                        show_extras_results = gr.Checkbox(label='Show result images', value=True, elem_id="extras_show_extras_results")
 
                 submit = gr.Button('Generate', elem_id="extras_generate", variant='primary')
 
                 with gr.Tabs(elem_id="extras_resize_mode"):
-                    with gr.TabItem('Scale by'):
-                        upscaling_resize = gr.Slider(minimum=1.0, maximum=8.0, step=0.05, label="Resize", value=4)
-                    with gr.TabItem('Scale to'):
+                    with gr.TabItem('Scale by', elem_id="extras_scale_by_tab"):
+                        upscaling_resize = gr.Slider(minimum=1.0, maximum=8.0, step=0.05, label="Resize", value=4, elem_id="extras_upscaling_resize")
+                    with gr.TabItem('Scale to', elem_id="extras_scale_to_tab"):
                         with gr.Group():
                             with gr.Row():
-                                upscaling_resize_w = gr.Number(label="Width", value=512, precision=0)
-                                upscaling_resize_h = gr.Number(label="Height", value=512, precision=0)
-                            upscaling_crop = gr.Checkbox(label='Crop to fit', value=True)
+                                upscaling_resize_w = gr.Number(label="Width", value=512, precision=0, elem_id="extras_upscaling_resize_w")
+                                upscaling_resize_h = gr.Number(label="Height", value=512, precision=0, elem_id="extras_upscaling_resize_h")
+                            upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop")
 
                 with gr.Group():
                     extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
 
                 with gr.Group():
                     extras_upscaler_2 = gr.Radio(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
-                    extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=1)
+                    extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=1, elem_id="extras_upscaler_2_visibility")
 
                 with gr.Group():
-                    gfpgan_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="GFPGAN visibility", value=0, interactive=modules.gfpgan_model.have_gfpgan)
+                    gfpgan_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="GFPGAN visibility", value=0, interactive=modules.gfpgan_model.have_gfpgan, elem_id="extras_gfpgan_visibility")
 
                 with gr.Group():
-                    codeformer_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer visibility", value=0, interactive=modules.codeformer_model.have_codeformer)
-                    codeformer_weight = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer weight (0 = maximum effect, 1 = minimum effect)", value=0, interactive=modules.codeformer_model.have_codeformer)
+                    codeformer_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer visibility", value=0, interactive=modules.codeformer_model.have_codeformer, elem_id="extras_codeformer_visibility")
+                    codeformer_weight = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer weight (0 = maximum effect, 1 = minimum effect)", value=0, interactive=modules.codeformer_model.have_codeformer, elem_id="extras_codeformer_weight")
 
                 with gr.Group():
-                    upscale_before_face_fix = gr.Checkbox(label='Upscale Before Restoring Faces', value=False)
+                    upscale_before_face_fix = gr.Checkbox(label='Upscale Before Restoring Faces', value=False, elem_id="extras_upscale_before_face_fix")
 
             result_images, html_info_x, html_info, html_log = create_output_panel("extras", opts.outdir_extras_samples)
 
@@ -1117,7 +1117,7 @@ def create_ui():
 
             with gr.Column(variant='panel'):
                 html = gr.HTML()
-                generation_info = gr.Textbox(visible=False)
+                generation_info = gr.Textbox(visible=False, elem_id="pnginfo_generation_info")
                 html2 = gr.HTML()
                 with gr.Row():
                     buttons = parameters_copypaste.create_buttons(["txt2img", "img2img", "inpaint", "extras"])
@@ -1144,13 +1144,13 @@ def create_ui():
                     tertiary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_tertiary_model_name", label="Tertiary model (C)")
                     create_refresh_button(tertiary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_C")
 
-                custom_name = gr.Textbox(label="Custom Name (Optional)")
-                interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3)
-                interp_method = gr.Radio(choices=["Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method")
+                custom_name = gr.Textbox(label="Custom Name (Optional)", elem_id="modelmerger_custom_name")
+                interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3, elem_id="modelmerger_interp_amount")
+                interp_method = gr.Radio(choices=["Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method", elem_id="modelmerger_interp_method")
 
                 with gr.Row():
-                    checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format")
-                    save_as_half = gr.Checkbox(value=False, label="Save as float16")
+                    checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format", elem_id="modelmerger_checkpoint_format")
+                    save_as_half = gr.Checkbox(value=False, label="Save as float16", elem_id="modelmerger_save_as_half")
 
                 modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary')
 
@@ -1165,58 +1165,58 @@ def create_ui():
             with gr.Tabs(elem_id="train_tabs"):
 
                 with gr.Tab(label="Create embedding"):
-                    new_embedding_name = gr.Textbox(label="Name")
-                    initialization_text = gr.Textbox(label="Initialization text", value="*")
-                    nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1)
-                    overwrite_old_embedding = gr.Checkbox(value=False, label="Overwrite Old Embedding")
+                    new_embedding_name = gr.Textbox(label="Name", elem_id="train_new_embedding_name")
+                    initialization_text = gr.Textbox(label="Initialization text", value="*", elem_id="train_initialization_text")
+                    nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1, elem_id="train_nvpt")
+                    overwrite_old_embedding = gr.Checkbox(value=False, label="Overwrite Old Embedding", elem_id="train_overwrite_old_embedding")
 
                     with gr.Row():
                         with gr.Column(scale=3):
                             gr.HTML(value="")
 
                         with gr.Column():
-                            create_embedding = gr.Button(value="Create embedding", variant='primary')
+                            create_embedding = gr.Button(value="Create embedding", variant='primary', elem_id="train_create_embedding")
 
                 with gr.Tab(label="Create hypernetwork"):
-                    new_hypernetwork_name = gr.Textbox(label="Name")
-                    new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "1024", "320", "640", "1280"])
-                    new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'")
-                    new_hypernetwork_activation_func = gr.Dropdown(value="linear", label="Select activation function of hypernetwork. Recommended : Swish / Linear(none)", choices=modules.hypernetworks.ui.keys)
-                    new_hypernetwork_initialization_option = gr.Dropdown(value = "Normal", label="Select Layer weights initialization. Recommended: Kaiming for relu-like, Xavier for sigmoid-like, Normal otherwise", choices=["Normal", "KaimingUniform", "KaimingNormal", "XavierUniform", "XavierNormal"])
-                    new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization")
-                    new_hypernetwork_use_dropout = gr.Checkbox(label="Use dropout")
-                    overwrite_old_hypernetwork = gr.Checkbox(value=False, label="Overwrite Old Hypernetwork")
+                    new_hypernetwork_name = gr.Textbox(label="Name", elem_id="train_new_hypernetwork_name")
+                    new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "1024", "320", "640", "1280"], elem_id="train_new_hypernetwork_sizes")
+                    new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'", elem_id="train_new_hypernetwork_layer_structure")
+                    new_hypernetwork_activation_func = gr.Dropdown(value="linear", label="Select activation function of hypernetwork. Recommended : Swish / Linear(none)", choices=modules.hypernetworks.ui.keys, elem_id="train_new_hypernetwork_activation_func")
+                    new_hypernetwork_initialization_option = gr.Dropdown(value = "Normal", label="Select Layer weights initialization. Recommended: Kaiming for relu-like, Xavier for sigmoid-like, Normal otherwise", choices=["Normal", "KaimingUniform", "KaimingNormal", "XavierUniform", "XavierNormal"], elem_id="train_new_hypernetwork_initialization_option")
+                    new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization", elem_id="train_new_hypernetwork_add_layer_norm")
+                    new_hypernetwork_use_dropout = gr.Checkbox(label="Use dropout", elem_id="train_new_hypernetwork_use_dropout")
+                    overwrite_old_hypernetwork = gr.Checkbox(value=False, label="Overwrite Old Hypernetwork", elem_id="train_overwrite_old_hypernetwork")
 
                     with gr.Row():
                         with gr.Column(scale=3):
                             gr.HTML(value="")
 
                         with gr.Column():
-                            create_hypernetwork = gr.Button(value="Create hypernetwork", variant='primary')
+                            create_hypernetwork = gr.Button(value="Create hypernetwork", variant='primary', elem_id="train_create_hypernetwork")
 
                 with gr.Tab(label="Preprocess images"):
-                    process_src = gr.Textbox(label='Source directory')
-                    process_dst = gr.Textbox(label='Destination directory')
-                    process_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512)
-                    process_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512)
-                    preprocess_txt_action = gr.Dropdown(label='Existing Caption txt Action', value="ignore", choices=["ignore", "copy", "prepend", "append"])
+                    process_src = gr.Textbox(label='Source directory', elem_id="train_process_src")
+                    process_dst = gr.Textbox(label='Destination directory', elem_id="train_process_dst")
+                    process_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_process_width")
+                    process_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_process_height")
+                    preprocess_txt_action = gr.Dropdown(label='Existing Caption txt Action', value="ignore", choices=["ignore", "copy", "prepend", "append"], elem_id="train_preprocess_txt_action")
 
                     with gr.Row():
-                        process_flip = gr.Checkbox(label='Create flipped copies')
-                        process_split = gr.Checkbox(label='Split oversized images')
-                        process_focal_crop = gr.Checkbox(label='Auto focal point crop')
-                        process_caption = gr.Checkbox(label='Use BLIP for caption')
-                        process_caption_deepbooru = gr.Checkbox(label='Use deepbooru for caption', visible=True)
+                        process_flip = gr.Checkbox(label='Create flipped copies', elem_id="train_process_flip")
+                        process_split = gr.Checkbox(label='Split oversized images', elem_id="train_process_split")
+                        process_focal_crop = gr.Checkbox(label='Auto focal point crop', elem_id="train_process_focal_crop")
+                        process_caption = gr.Checkbox(label='Use BLIP for caption', elem_id="train_process_caption")
+                        process_caption_deepbooru = gr.Checkbox(label='Use deepbooru for caption', visible=True, elem_id="train_process_caption_deepbooru")
 
                     with gr.Row(visible=False) as process_split_extra_row:
-                        process_split_threshold = gr.Slider(label='Split image threshold', value=0.5, minimum=0.0, maximum=1.0, step=0.05)
-                        process_overlap_ratio = gr.Slider(label='Split image overlap ratio', value=0.2, minimum=0.0, maximum=0.9, step=0.05)
+                        process_split_threshold = gr.Slider(label='Split image threshold', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_split_threshold")
+                        process_overlap_ratio = gr.Slider(label='Split image overlap ratio', value=0.2, minimum=0.0, maximum=0.9, step=0.05, elem_id="train_process_overlap_ratio")
 
                     with gr.Row(visible=False) as process_focal_crop_row:
-                        process_focal_crop_face_weight = gr.Slider(label='Focal point face weight', value=0.9, minimum=0.0, maximum=1.0, step=0.05)
-                        process_focal_crop_entropy_weight = gr.Slider(label='Focal point entropy weight', value=0.15, minimum=0.0, maximum=1.0, step=0.05)
-                        process_focal_crop_edges_weight = gr.Slider(label='Focal point edges weight', value=0.5, minimum=0.0, maximum=1.0, step=0.05)
-                        process_focal_crop_debug = gr.Checkbox(label='Create debug image')
+                        process_focal_crop_face_weight = gr.Slider(label='Focal point face weight', value=0.9, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_face_weight")
+                        process_focal_crop_entropy_weight = gr.Slider(label='Focal point entropy weight', value=0.15, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_entropy_weight")
+                        process_focal_crop_edges_weight = gr.Slider(label='Focal point edges weight', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_edges_weight")
+                        process_focal_crop_debug = gr.Checkbox(label='Create debug image', elem_id="train_process_focal_crop_debug")
 
                     with gr.Row():
                         with gr.Column(scale=3):
@@ -1224,8 +1224,8 @@ def create_ui():
 
                         with gr.Column():
                             with gr.Row():
-                                interrupt_preprocessing = gr.Button("Interrupt")
-                            run_preprocess = gr.Button(value="Preprocess", variant='primary')
+                                interrupt_preprocessing = gr.Button("Interrupt", elem_id="train_interrupt_preprocessing")
+                            run_preprocess = gr.Button(value="Preprocess", variant='primary', elem_id="train_run_preprocess")
 
                     process_split.change(
                         fn=lambda show: gr_show(show),
@@ -1248,31 +1248,31 @@ def create_ui():
                         train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=[x for x in shared.hypernetworks.keys()])
                         create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted([x for x in shared.hypernetworks.keys()])}, "refresh_train_hypernetwork_name")
                     with gr.Row():
-                        embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005")
-                        hypernetwork_learn_rate = gr.Textbox(label='Hypernetwork Learning rate', placeholder="Hypernetwork Learning rate", value="0.00001")
-
-                    batch_size = gr.Number(label='Batch size', value=1, precision=0)
-                    gradient_step = gr.Number(label='Gradient accumulation steps', value=1, precision=0)
-                    dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images")
-                    log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")
-                    template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"))
-                    training_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512)
-                    training_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512)
-                    steps = gr.Number(label='Max steps', value=100000, precision=0)
-                    create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0)
-                    save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0)
-                    save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True)
-                    preview_from_txt2img = gr.Checkbox(label='Read parameters (prompt, etc...) from txt2img tab when making previews', value=False)
+                        embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005", elem_id="train_embedding_learn_rate")
+                        hypernetwork_learn_rate = gr.Textbox(label='Hypernetwork Learning rate', placeholder="Hypernetwork Learning rate", value="0.00001", elem_id="train_hypernetwork_learn_rate")
+
+                    batch_size = gr.Number(label='Batch size', value=1, precision=0, elem_id="train_batch_size")
+                    gradient_step = gr.Number(label='Gradient accumulation steps', value=1, precision=0, elem_id="train_gradient_step")
+                    dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images", elem_id="train_dataset_directory")
+                    log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion", elem_id="train_log_directory")
+                    template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"), elem_id="train_template_file")
+                    training_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_training_width")
+                    training_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_training_height")
+                    steps = gr.Number(label='Max steps', value=100000, precision=0, elem_id="train_steps")
+                    create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0, elem_id="train_create_image_every")
+                    save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0, elem_id="train_save_embedding_every")
+                    save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True, elem_id="train_save_image_with_stored_embedding")
+                    preview_from_txt2img = gr.Checkbox(label='Read parameters (prompt, etc...) from txt2img tab when making previews', value=False, elem_id="train_preview_from_txt2img")
                     with gr.Row():
-                        shuffle_tags = gr.Checkbox(label="Shuffle tags by ',' when creating prompts.", value=False)
-                        tag_drop_out = gr.Slider(minimum=0, maximum=1, step=0.1, label="Drop out tags when creating prompts.", value=0)
+                        shuffle_tags = gr.Checkbox(label="Shuffle tags by ',' when creating prompts.", value=False, elem_id="train_shuffle_tags")
+                        tag_drop_out = gr.Slider(minimum=0, maximum=1, step=0.1, label="Drop out tags when creating prompts.", value=0, elem_id="train_tag_drop_out")
                     with gr.Row():
-                        latent_sampling_method = gr.Radio(label='Choose latent sampling method', value="once", choices=['once', 'deterministic', 'random'])
+                        latent_sampling_method = gr.Radio(label='Choose latent sampling method', value="once", choices=['once', 'deterministic', 'random'], elem_id="train_latent_sampling_method")
 
                     with gr.Row():
-                        interrupt_training = gr.Button(value="Interrupt")
-                        train_hypernetwork = gr.Button(value="Train Hypernetwork", variant='primary')
-                        train_embedding = gr.Button(value="Train Embedding", variant='primary')
+                        interrupt_training = gr.Button(value="Interrupt", elem_id="train_interrupt_training")
+                        train_hypernetwork = gr.Button(value="Train Hypernetwork", variant='primary', elem_id="train_train_hypernetwork")
+                        train_embedding = gr.Button(value="Train Embedding", variant='primary', elem_id="train_train_embedding")
 
                 params = script_callbacks.UiTrainTabParams(txt2img_preview_params)
 
@@ -1490,7 +1490,7 @@ def create_ui():
         return gr.update(value=value), opts.dumpjson()
 
     with gr.Blocks(analytics_enabled=False) as settings_interface:
-        settings_submit = gr.Button(value="Apply settings", variant='primary')
+        settings_submit = gr.Button(value="Apply settings", variant='primary', elem_id="settings_submit")
         result = gr.HTML()
 
         settings_cols = 3
@@ -1541,8 +1541,8 @@ def create_ui():
             download_localization = gr.Button(value='Download localization template', elem_id="download_localization")
 
         with gr.Row():
-            reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary')
-            restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary')
+            reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary', elem_id="settings_reload_script_bodies")
+            restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary', elem_id="settings_restart_gradio")
 
         request_notifications.click(
             fn=lambda: None,
diff --git a/style.css b/style.css
index f168571e..924d4ae7 100644
--- a/style.css
+++ b/style.css
@@ -73,7 +73,7 @@
     margin-right: auto;
 }
 
-#random_seed, #random_subseed, #reuse_seed, #reuse_subseed, #open_folder{
+[id$=_random_seed], [id$=_random_subseed], [id$=_reuse_seed], [id$=_reuse_subseed], #open_folder{
     min-width: auto;
     flex-grow: 0;
     padding-left: 0.25em;
@@ -84,27 +84,27 @@
     display: none;
 }
 
-#seed_row, #subseed_row{
+[id$=_seed_row], [id$=_subseed_row]{
     gap: 0.5rem;
 }
 
-#subseed_show_box{
+[id$=_subseed_show_box]{
     min-width: auto;
     flex-grow: 0;
 }
 
-#subseed_show_box > div{
+[id$=_subseed_show_box] > div{
     border: 0;
     height: 100%;
 }
 
-#subseed_show{
+[id$=_subseed_show]{
     min-width: auto;
     flex-grow: 0;
     padding: 0;
 }
 
-#subseed_show label{
+[id$=_subseed_show] label{
     height: 100%;
 }
 
-- 
cgit v1.2.3


From ef27a18b6b7cb1a8eebdc9b2e88d25baf2c2414d Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 2 Jan 2023 19:42:10 +0300
Subject: Hires fix rework

---
 modules/generation_parameters_copypaste.py | 32 ++++++++++++++
 modules/images.py                          | 24 +++++++++--
 modules/processing.py                      | 68 ++++++++++++------------------
 modules/shared.py                          |  7 ++-
 modules/txt2img.py                         |  6 +--
 modules/ui.py                              | 15 +++----
 scripts/xy_grid.py                         |  4 +-
 7 files changed, 96 insertions(+), 60 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py
index 8e7f0df0..d6fa822b 100644
--- a/modules/generation_parameters_copypaste.py
+++ b/modules/generation_parameters_copypaste.py
@@ -1,5 +1,6 @@
 import base64
 import io
+import math
 import os
 import re
 from pathlib import Path
@@ -164,6 +165,35 @@ def find_hypernetwork_key(hypernet_name, hypernet_hash=None):
     return None
 
 
+def restore_old_hires_fix_params(res):
+    """for infotexts that specify old First pass size parameter, convert it into
+    width, height, and hr scale"""
+
+    firstpass_width = res.get('First pass size-1', None)
+    firstpass_height = res.get('First pass size-2', None)
+
+    if firstpass_width is None or firstpass_height is None:
+        return
+
+    firstpass_width, firstpass_height = int(firstpass_width), int(firstpass_height)
+    width = int(res.get("Size-1", 512))
+    height = int(res.get("Size-2", 512))
+
+    if firstpass_width == 0 or firstpass_height == 0:
+        # old algorithm for auto-calculating first pass size
+        desired_pixel_count = 512 * 512
+        actual_pixel_count = width * height
+        scale = math.sqrt(desired_pixel_count / actual_pixel_count)
+        firstpass_width = math.ceil(scale * width / 64) * 64
+        firstpass_height = math.ceil(scale * height / 64) * 64
+
+    hr_scale = width / firstpass_width if firstpass_width > 0 else height / firstpass_height
+
+    res['Size-1'] = firstpass_width
+    res['Size-2'] = firstpass_height
+    res['Hires upscale'] = hr_scale
+
+
 def parse_generation_parameters(x: str):
     """parses generation parameters string, the one you see in text field under the picture in UI:
 ```
@@ -221,6 +251,8 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
         hypernet_hash = res.get("Hypernet hash", None)
         res["Hypernet"] = find_hypernetwork_key(hypernet_name, hypernet_hash)
 
+    restore_old_hires_fix_params(res)
+
     return res
 
 
diff --git a/modules/images.py b/modules/images.py
index f84fd485..c3a5fc8b 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -230,16 +230,32 @@ def draw_prompt_matrix(im, width, height, all_prompts):
     return draw_grid_annotations(im, width, height, hor_texts, ver_texts)
 
 
-def resize_image(resize_mode, im, width, height):
+def resize_image(resize_mode, im, width, height, upscaler_name=None):
+    """
+    Resizes an image with the specified resize_mode, width, and height.
+
+    Args:
+        resize_mode: The mode to use when resizing the image.
+            0: Resize the image to the specified width and height.
+            1: Resize the image to fill the specified width and height, maintaining the aspect ratio, and then center the image within the dimensions, cropping the excess.
+            2: Resize the image to fit within the specified width and height, maintaining the aspect ratio, and then center the image within the dimensions, filling empty with data from image.
+        im: The image to resize.
+        width: The width to resize the image to.
+        height: The height to resize the image to.
+        upscaler_name: The name of the upscaler to use. If not provided, defaults to opts.upscaler_for_img2img.
+    """
+
+    upscaler_name = upscaler_name or opts.upscaler_for_img2img
+
     def resize(im, w, h):
-        if opts.upscaler_for_img2img is None or opts.upscaler_for_img2img == "None" or im.mode == 'L':
+        if upscaler_name is None or upscaler_name == "None" or im.mode == 'L':
             return im.resize((w, h), resample=LANCZOS)
 
         scale = max(w / im.width, h / im.height)
 
         if scale > 1.0:
-            upscalers = [x for x in shared.sd_upscalers if x.name == opts.upscaler_for_img2img]
-            assert len(upscalers) > 0, f"could not find upscaler named {opts.upscaler_for_img2img}"
+            upscalers = [x for x in shared.sd_upscalers if x.name == upscaler_name]
+            assert len(upscalers) > 0, f"could not find upscaler named {upscaler_name}"
 
             upscaler = upscalers[0]
             im = upscaler.scaler.upscale(im, scale, upscaler.data_path)
diff --git a/modules/processing.py b/modules/processing.py
index 42dc19ea..4654570c 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -658,14 +658,18 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
 class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
     sampler = None
 
-    def __init__(self, enable_hr: bool=False, denoising_strength: float=0.75, firstphase_width: int=0, firstphase_height: int=0, **kwargs):
+    def __init__(self, enable_hr: bool = False, denoising_strength: float = 0.75, firstphase_width: int = 0, firstphase_height: int = 0, hr_scale: float = 2.0, hr_upscaler: str = None, **kwargs):
         super().__init__(**kwargs)
         self.enable_hr = enable_hr
         self.denoising_strength = denoising_strength
-        self.firstphase_width = firstphase_width
-        self.firstphase_height = firstphase_height
-        self.truncate_x = 0
-        self.truncate_y = 0
+        self.hr_scale = hr_scale
+        self.hr_upscaler = hr_upscaler
+
+        if firstphase_width != 0 or firstphase_height != 0:
+            print("firstphase_width/firstphase_height no longer supported; use hr_scale", file=sys.stderr)
+            self.hr_scale = self.width / firstphase_width
+            self.width = firstphase_width
+            self.height = firstphase_height
 
     def init(self, all_prompts, all_seeds, all_subseeds):
         if self.enable_hr:
@@ -674,47 +678,29 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
             else:
                 state.job_count = state.job_count * 2
 
-            self.extra_generation_params["First pass size"] = f"{self.firstphase_width}x{self.firstphase_height}"
-
-            if self.firstphase_width == 0 or self.firstphase_height == 0:
-                desired_pixel_count = 512 * 512
-                actual_pixel_count = self.width * self.height
-                scale = math.sqrt(desired_pixel_count / actual_pixel_count)
-                self.firstphase_width = math.ceil(scale * self.width / 64) * 64
-                self.firstphase_height = math.ceil(scale * self.height / 64) * 64
-                firstphase_width_truncated = int(scale * self.width)
-                firstphase_height_truncated = int(scale * self.height)
-
-            else:
-
-                width_ratio = self.width / self.firstphase_width
-                height_ratio = self.height / self.firstphase_height
-
-                if width_ratio > height_ratio:
-                    firstphase_width_truncated = self.firstphase_width
-                    firstphase_height_truncated = self.firstphase_width * self.height / self.width
-                else:
-                    firstphase_width_truncated = self.firstphase_height * self.width / self.height
-                    firstphase_height_truncated = self.firstphase_height
-
-            self.truncate_x = int(self.firstphase_width - firstphase_width_truncated) // opt_f
-            self.truncate_y = int(self.firstphase_height - firstphase_height_truncated) // opt_f
+            self.extra_generation_params["Hires upscale"] = self.hr_scale
+            if self.hr_upscaler is not None:
+                self.extra_generation_params["Hires upscaler"] = self.hr_upscaler
 
     def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength, prompts):
         self.sampler = sd_samplers.create_sampler(self.sampler_name, self.sd_model)
 
+        latent_scale_mode = shared.latent_upscale_modes.get(self.hr_upscaler, None) if self.hr_upscaler is not None else shared.latent_upscale_default_mode
+        if self.enable_hr and latent_scale_mode is None:
+            assert len([x for x in shared.sd_upscalers if x.name == self.hr_upscaler]) > 0, f"could not find upscaler named {self.hr_upscaler}"
+
+        x = create_random_tensors([opt_C, self.height // opt_f, self.width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self)
+        samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
+
         if not self.enable_hr:
-            x = create_random_tensors([opt_C, self.height // opt_f, self.width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self)
-            samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
             return samples
 
-        x = create_random_tensors([opt_C, self.firstphase_height // opt_f, self.firstphase_width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self)
-        samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x, self.firstphase_width, self.firstphase_height))
-
-        samples = samples[:, :, self.truncate_y//2:samples.shape[2]-self.truncate_y//2, self.truncate_x//2:samples.shape[3]-self.truncate_x//2]
+        target_width = int(self.width * self.hr_scale)
+        target_height = int(self.height * self.hr_scale)
 
-        """saves image before applying hires fix, if enabled in options; takes as an argument either an image or batch with latent space images"""
         def save_intermediate(image, index):
+            """saves image before applying hires fix, if enabled in options; takes as an argument either an image or batch with latent space images"""
+
             if not opts.save or self.do_not_save_samples or not opts.save_images_before_highres_fix:
                 return
 
@@ -723,11 +709,11 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
 
             images.save_image(image, self.outpath_samples, "", seeds[index], prompts[index], opts.samples_format, suffix="-before-highres-fix")
 
-        if opts.use_scale_latent_for_hires_fix:
+        if latent_scale_mode is not None:
             for i in range(samples.shape[0]):
                 save_intermediate(samples, i)
 
-            samples = torch.nn.functional.interpolate(samples, size=(self.height // opt_f, self.width // opt_f), mode="bilinear")
+            samples = torch.nn.functional.interpolate(samples, size=(target_height // opt_f, target_width // opt_f), mode=latent_scale_mode)
 
             # Avoid making the inpainting conditioning unless necessary as
             # this does need some extra compute to decode / encode the image again.
@@ -747,7 +733,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
 
                 save_intermediate(image, i)
 
-                image = images.resize_image(0, image, self.width, self.height)
+                image = images.resize_image(0, image, target_width, target_height, upscaler_name=self.hr_upscaler)
                 image = np.array(image).astype(np.float32) / 255.0
                 image = np.moveaxis(image, 2, 0)
                 batch_images.append(image)
@@ -764,7 +750,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
 
         self.sampler = sd_samplers.create_sampler(self.sampler_name, self.sd_model)
 
-        noise = create_random_tensors(samples.shape[1:], seeds=seeds, subseeds=subseeds, subseed_strength=subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self)
+        noise = create_random_tensors(samples.shape[1:], seeds=seeds, subseeds=subseeds, subseed_strength=subseed_strength, p=self)
 
         # GC now before running the next img2img to prevent running out of memory
         x = None
diff --git a/modules/shared.py b/modules/shared.py
index 7f430b93..b65559ee 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -327,7 +327,6 @@ options_templates.update(options_section(('upscaling', "Upscaling"), {
     "ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for ESRGAN upscalers. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}),
     "realesrgan_enabled_models": OptionInfo(["R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B"], "Select which Real-ESRGAN models to show in the web UI. (Requires restart)", gr.CheckboxGroup, lambda: {"choices": realesrgan_models_names()}),
     "upscaler_for_img2img": OptionInfo(None, "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in sd_upscalers]}),
-    "use_scale_latent_for_hires_fix": OptionInfo(False, "Upscale latent space image when doing hires. fix"),
 }))
 
 options_templates.update(options_section(('face-restoration', "Face restoration"), {
@@ -545,6 +544,12 @@ opts = Options()
 if os.path.exists(config_filename):
     opts.load(config_filename)
 
+latent_upscale_default_mode = "Latent"
+latent_upscale_modes = {
+    "Latent": "bilinear",
+    "Latent (nearest)": "nearest",
+}
+
 sd_upscalers = []
 
 sd_model = None
diff --git a/modules/txt2img.py b/modules/txt2img.py
index 7f61e19a..e189a899 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -8,7 +8,7 @@ import modules.processing as processing
 from modules.ui import plaintext_to_html
 
 
-def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, firstphase_width: int, firstphase_height: int, *args):
+def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, *args):
     p = StableDiffusionProcessingTxt2Img(
         sd_model=shared.sd_model,
         outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples,
@@ -33,8 +33,8 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2:
         tiling=tiling,
         enable_hr=enable_hr,
         denoising_strength=denoising_strength if enable_hr else None,
-        firstphase_width=firstphase_width if enable_hr else None,
-        firstphase_height=firstphase_height if enable_hr else None,
+        hr_scale=hr_scale,
+        hr_upscaler=hr_upscaler,
     )
 
     p.scripts = modules.scripts.scripts_txt2img
diff --git a/modules/ui.py b/modules/ui.py
index 7070ea15..27cd9ddd 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -684,11 +684,11 @@ def create_ui():
                 with gr.Row():
                     restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="txt2img_restore_faces")
                     tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling")
-                    enable_hr = gr.Checkbox(label='Highres. fix', value=False, elem_id="txt2img_enable_hr")
+                    enable_hr = gr.Checkbox(label='Hires. fix', value=False, elem_id="txt2img_enable_hr")
 
                 with gr.Row(visible=False) as hr_options:
-                    firstphase_width = gr.Slider(minimum=0, maximum=1024, step=8, label="Firstpass width", value=0, elem_id="txt2img_firstphase_width")
-                    firstphase_height = gr.Slider(minimum=0, maximum=1024, step=8, label="Firstpass height", value=0, elem_id="txt2img_firstphase_height")
+                    hr_upscaler = gr.Dropdown(label="Upscaler", elem_id="txt2img_hr_upscaler", choices=[*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]], value=shared.latent_upscale_default_mode)
+                    hr_scale = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Upscale by", value=2.0, elem_id="txt2img_hr_scale")
                     denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7, elem_id="txt2img_denoising_strength")
 
                 with gr.Row(equal_height=True):
@@ -729,8 +729,8 @@ def create_ui():
                     width,
                     enable_hr,
                     denoising_strength,
-                    firstphase_width,
-                    firstphase_height,
+                    hr_scale,
+                    hr_upscaler,
                 ] + custom_inputs,
 
                 outputs=[
@@ -762,7 +762,6 @@ def create_ui():
                 outputs=[hr_options],
             )
 
-
             txt2img_paste_fields = [
                 (txt2img_prompt, "Prompt"),
                 (txt2img_negative_prompt, "Negative prompt"),
@@ -781,8 +780,8 @@ def create_ui():
                 (denoising_strength, "Denoising strength"),
                 (enable_hr, lambda d: "Denoising strength" in d),
                 (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)),
-                (firstphase_width, "First pass size-1"),
-                (firstphase_height, "First pass size-2"),
+                (hr_scale, "Hires upscale"),
+                (hr_upscaler, "Hires upscaler"),
                 *modules.scripts.scripts_txt2img.infotext_fields
             ]
             parameters_copypaste.add_paste_fields("txt2img", None, txt2img_paste_fields)
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 3e0b2805..f92f9776 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -202,7 +202,7 @@ axis_options = [
     AxisOption("Eta", float, apply_field("eta"), format_value_add_label, None),
     AxisOption("Clip skip", int, apply_clip_skip, format_value_add_label, None),
     AxisOption("Denoising", float, apply_field("denoising_strength"), format_value_add_label, None),
-    AxisOption("Upscale latent space for hires.", str, apply_upscale_latent_space, format_value_add_label, None),
+    AxisOption("Hires upscaler", str, apply_field("hr_upscaler"), format_value_add_label, None),
     AxisOption("Cond. Image Mask Weight", float, apply_field("inpainting_mask_weight"), format_value_add_label, None),
     AxisOption("VAE", str, apply_vae, format_value_add_label, None),
     AxisOption("Styles", str, apply_styles, format_value_add_label, None),
@@ -267,7 +267,6 @@ class SharedSettingsStackHelper(object):
         self.CLIP_stop_at_last_layers = opts.CLIP_stop_at_last_layers
         self.hypernetwork = opts.sd_hypernetwork
         self.model = shared.sd_model
-        self.use_scale_latent_for_hires_fix = opts.use_scale_latent_for_hires_fix
         self.vae = opts.sd_vae
   
     def __exit__(self, exc_type, exc_value, tb):
@@ -278,7 +277,6 @@ class SharedSettingsStackHelper(object):
         hypernetwork.apply_strength()
 
         opts.data["CLIP_stop_at_last_layers"] = self.CLIP_stop_at_last_layers
-        opts.data["use_scale_latent_for_hires_fix"] = self.use_scale_latent_for_hires_fix
 
 
 re_range = re.compile(r"\s*([+-]?\s*\d+)\s*-\s*([+-]?\s*\d+)(?:\s*\(([+-]\d+)\s*\))?\s*")
-- 
cgit v1.2.3


From 84dd7e8e2495c4fc2997e97f8267aa831eb90d11 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 2 Jan 2023 20:30:02 +0300
Subject: error out with a readable message in chwewckpoint merger for
 incompatible tensor shapes (ie when trying to merge SD1.5 with SD2.0)

---
 modules/extras.py | 2 ++
 modules/ui.py     | 2 +-
 2 files changed, 3 insertions(+), 1 deletion(-)

(limited to 'modules/ui.py')

diff --git a/modules/extras.py b/modules/extras.py
index 68939dea..5e270250 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -303,6 +303,8 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
                 theta_0[key][:, 0:4, :, :] = theta_func2(a[:, 0:4, :, :], b, multiplier)
                 result_is_inpainting_model = True
             else:
+                assert a.shape == b.shape, f'Incompatible shapes for layer {key}: A is {a.shape}, and B is {b.shape}'
+
                 theta_0[key] = theta_func2(a, b, multiplier)
 
             if save_as_half:
diff --git a/modules/ui.py b/modules/ui.py
index 27cd9ddd..67a51888 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1663,7 +1663,7 @@ def create_ui():
                 print("Error loading/saving model file:", file=sys.stderr)
                 print(traceback.format_exc(), file=sys.stderr)
                 modules.sd_models.list_models()  # to remove the potentially missing models from the list
-                return ["Error loading/saving model file. It doesn't exist or the name contains illegal characters"] + [gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(3)]
+                return [f"Error merging checkpoints: {e}"] + [gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(4)]
             return results
 
         modelmerger_merge.click(
-- 
cgit v1.2.3


From 8d12a729b8b036cb765cf2d87576d5ae256135c8 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 2 Jan 2023 20:46:51 +0300
Subject: fix possible error with accessing nonexistent setting

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

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index 67a51888..9350a80f 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -491,7 +491,7 @@ def apply_setting(key, value):
         return
 
     valtype = type(opts.data_labels[key].default)
-    oldval = opts.data[key]
+    oldval = opts.data.get(key, None)
     opts.data[key] = valtype(value) if valtype != type(None) else value
     if oldval != value and opts.data_labels[key].onchange is not None:
         opts.data_labels[key].onchange()
-- 
cgit v1.2.3


From 269f6e867651cadef40d2c939a79d13291280bcd Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 3 Jan 2023 07:20:20 +0300
Subject: change settings UI to use vertical tabs

---
 modules/ui.py | 45 +++++++++++++++++----------------------------
 style.css     | 27 +++++++++++++++++++++++++++
 2 files changed, 44 insertions(+), 28 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index 9350a80f..f8c973ba 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1489,41 +1489,34 @@ def create_ui():
         return gr.update(value=value), opts.dumpjson()
 
     with gr.Blocks(analytics_enabled=False) as settings_interface:
-        settings_submit = gr.Button(value="Apply settings", variant='primary', elem_id="settings_submit")
-        result = gr.HTML()
+        with gr.Row():
+            settings_submit = gr.Button(value="Apply settings", variant='primary', elem_id="settings_submit")
+            restart_gradio = gr.Button(value='Restart UI', variant='primary', elem_id="settings_restart_gradio")
 
-        settings_cols = 3
-        items_per_col = int(len(opts.data_labels) * 0.9 / settings_cols)
+        result = gr.HTML(elem_id="settings_result")
 
         quicksettings_names = [x.strip() for x in opts.quicksettings.split(",")]
         quicksettings_names = set(x for x in quicksettings_names if x != 'quicksettings')
 
         quicksettings_list = []
 
-        cols_displayed = 0
-        items_displayed = 0
         previous_section = None
-        column = None
-        with gr.Row(elem_id="settings").style(equal_height=False):
+        current_tab = None
+        with gr.Tabs(elem_id="settings"):
             for i, (k, item) in enumerate(opts.data_labels.items()):
                 section_must_be_skipped = item.section[0] is None
 
                 if previous_section != item.section and not section_must_be_skipped:
-                    if cols_displayed < settings_cols and (items_displayed >= items_per_col or previous_section is None):
-                        if column is not None:
-                            column.__exit__()
+                    elem_id, text = item.section
 
-                        column = gr.Column(variant='panel')
-                        column.__enter__()
+                    if current_tab is not None:
+                        current_tab.__exit__()
 
-                        items_displayed = 0
-                        cols_displayed += 1
+                    current_tab = gr.TabItem(elem_id="settings_{}".format(elem_id), label=text)
+                    current_tab.__enter__()
 
                     previous_section = item.section
 
-                    elem_id, text = item.section
-                    gr.HTML(elem_id="settings_header_text_{}".format(elem_id), value='<h1 class="gr-button-lg">{}</h1>'.format(text))
-
                 if k in quicksettings_names and not shared.cmd_opts.freeze_settings:
                     quicksettings_list.append((i, k, item))
                     components.append(dummy_component)
@@ -1533,15 +1526,14 @@ def create_ui():
                     component = create_setting_component(k)
                     component_dict[k] = component
                     components.append(component)
-                    items_displayed += 1
 
-        with gr.Row():
-            request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications")
-            download_localization = gr.Button(value='Download localization template', elem_id="download_localization")
+            if current_tab is not None:
+                current_tab.__exit__()
 
-        with gr.Row():
-            reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary', elem_id="settings_reload_script_bodies")
-            restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary', elem_id="settings_restart_gradio")
+            with gr.TabItem("Actions"):
+                request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications")
+                download_localization = gr.Button(value='Download localization template', elem_id="download_localization")
+                reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary', elem_id="settings_reload_script_bodies")
 
         request_notifications.click(
             fn=lambda: None,
@@ -1578,9 +1570,6 @@ def create_ui():
             outputs=[],
         )
 
-        if column is not None:
-            column.__exit__()
-
     interfaces = [
         (txt2img_interface, "txt2img", "txt2img"),
         (img2img_interface, "img2img", "img2img"),
diff --git a/style.css b/style.css
index 77551dd7..7df4d960 100644
--- a/style.css
+++ b/style.css
@@ -241,6 +241,33 @@ fieldset span.text-gray-500, .gr-block.gr-box span.text-gray-500,  label.block s
     z-index: 200;
 }
 
+#settings{
+    display: block;
+}
+
+#settings > div{
+    border: none;
+    margin-left: 10em;
+}
+
+#settings > div.flex-wrap{
+    float: left;
+    display: block;
+    margin-left: 0;
+    width: 10em;
+}
+
+#settings > div.flex-wrap button{
+    display: block;
+    border: none;
+    text-align: left;
+}
+
+#settings_result{
+    height: 1.4em;
+    margin: 0 1.2em;
+}
+
 input[type="range"]{
     margin: 0.5em 0 -0.3em 0;
 }
-- 
cgit v1.2.3


From 18c03cdeac6272734b0c09afd3fbe47d1372dd07 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 3 Jan 2023 09:04:29 +0300
Subject: styling rework to make things more compact

---
 modules/ui.py            | 121 ++++++++++++++++++++++++-----------------------
 modules/ui_components.py |   7 +++
 style.css                |  35 ++++++++------
 3 files changed, 89 insertions(+), 74 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index f8c973ba..f787b518 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -19,7 +19,8 @@ import numpy as np
 from PIL import Image, PngImagePlugin
 from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
 
-from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, ui_components
+from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru
+from modules.ui_components import FormRow, FormGroup, ToolButton
 from modules.paths import script_path
 
 from modules.shared import opts, cmd_opts, restricted_opts
@@ -273,31 +274,27 @@ def interrogate_deepbooru(image):
 
 
 def create_seed_inputs(target_interface):
-    with gr.Row():
-        with gr.Box():
-            with gr.Row(elem_id=target_interface + '_seed_row'):
-                seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1, elem_id=target_interface + '_seed')
-                seed.style(container=False)
-                random_seed = gr.Button(random_symbol, elem_id=target_interface + '_random_seed')
-                reuse_seed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_seed')
-
-        with gr.Box(elem_id=target_interface + '_subseed_show_box'):
+    with FormRow(elem_id=target_interface + '_seed_row'):
+        seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1, elem_id=target_interface + '_seed')
+        seed.style(container=False)
+        random_seed = gr.Button(random_symbol, elem_id=target_interface + '_random_seed')
+        reuse_seed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_seed')
+
+        with gr.Group(elem_id=target_interface + '_subseed_show_box'):
             seed_checkbox = gr.Checkbox(label='Extra', elem_id=target_interface + '_subseed_show', value=False)
 
     # Components to show/hide based on the 'Extra' checkbox
     seed_extras = []
 
-    with gr.Row(visible=False) as seed_extra_row_1:
+    with FormRow(visible=False, elem_id=target_interface + '_subseed_row') as seed_extra_row_1:
         seed_extras.append(seed_extra_row_1)
-        with gr.Box():
-            with gr.Row(elem_id=target_interface + '_subseed_row'):
-                subseed = gr.Number(label='Variation seed', value=-1, elem_id=target_interface + '_subseed')
-                subseed.style(container=False)
-                random_subseed = gr.Button(random_symbol, elem_id=target_interface + '_random_subseed')
-                reuse_subseed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_subseed')
+        subseed = gr.Number(label='Variation seed', value=-1, elem_id=target_interface + '_subseed')
+        subseed.style(container=False)
+        random_subseed = gr.Button(random_symbol, elem_id=target_interface + '_random_subseed')
+        reuse_subseed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_subseed')
         subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=target_interface + '_subseed_strength')
 
-    with gr.Row(visible=False) as seed_extra_row_2:
+    with FormRow(visible=False) as seed_extra_row_2:
         seed_extras.append(seed_extra_row_2)
         seed_resize_from_w = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from width", value=0, elem_id=target_interface + '_seed_resize_from_w')
         seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from height", value=0, elem_id=target_interface + '_seed_resize_from_h')
@@ -523,7 +520,7 @@ def create_refresh_button(refresh_component, refresh_method, refreshed_args, ele
 
         return gr.update(**(args or {}))
 
-    refresh_button = ui_components.ToolButton(value=refresh_symbol, elem_id=elem_id)
+    refresh_button = ToolButton(value=refresh_symbol, elem_id=elem_id)
     refresh_button.click(
         fn=refresh,
         inputs=[],
@@ -636,11 +633,11 @@ Requested path was: {f}
 
 def create_sampler_and_steps_selection(choices, tabname):
     if opts.samplers_in_dropdown:
-        with gr.Row(elem_id=f"sampler_selection_{tabname}"):
+        with FormRow(elem_id=f"sampler_selection_{tabname}"):
             sampler_index = gr.Dropdown(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")
             steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling Steps", value=20)
     else:
-        with gr.Group(elem_id=f"sampler_selection_{tabname}"):
+        with FormGroup(elem_id=f"sampler_selection_{tabname}"):
             steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling Steps", value=20)
             sampler_index = gr.Radio(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")
 
@@ -677,29 +674,29 @@ def create_ui():
             with gr.Column(variant='panel', elem_id="txt2img_settings"):
                 steps, sampler_index = create_sampler_and_steps_selection(samplers, "txt2img")
 
-                with gr.Group():
-                    width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="txt2img_width")
-                    height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="txt2img_height")
+                with FormRow():
+                    with gr.Column(elem_id="txt2img_column_size", scale=4):
+                        width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="txt2img_width")
+                        height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="txt2img_height")
+                    with gr.Column(elem_id="txt2img_column_batch"):
+                        batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
+                        batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
 
-                with gr.Row():
+                cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="txt2img_cfg_scale")
+
+                seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('txt2img')
+
+                with FormRow(elem_id="txt2img_checkboxes"):
                     restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="txt2img_restore_faces")
                     tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling")
                     enable_hr = gr.Checkbox(label='Hires. fix', value=False, elem_id="txt2img_enable_hr")
 
-                with gr.Row(visible=False) as hr_options:
+                with FormRow(visible=False) as hr_options:
                     hr_upscaler = gr.Dropdown(label="Upscaler", elem_id="txt2img_hr_upscaler", choices=[*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]], value=shared.latent_upscale_default_mode)
                     hr_scale = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Upscale by", value=2.0, elem_id="txt2img_hr_scale")
                     denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7, elem_id="txt2img_denoising_strength")
 
-                with gr.Row(equal_height=True):
-                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
-                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
-
-                cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="txt2img_cfg_scale")
-
-                seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('txt2img')
-
-                with gr.Group(elem_id="txt2img_script_container"):
+                with FormGroup(elem_id="txt2img_script_container"):
                     custom_inputs = modules.scripts.scripts_txt2img.setup_ui()
 
             txt2img_gallery, generation_info, html_info, html_log = create_output_panel("txt2img", opts.outdir_txt2img_samples)
@@ -816,7 +813,7 @@ def create_ui():
                 img2img_preview = gr.Image(elem_id='img2img_preview', visible=False)
                 setup_progressbar(progressbar, img2img_preview, 'img2img')
 
-        with gr.Row().style(equal_height=False):
+        with FormRow().style(equal_height=False):
             with gr.Column(variant='panel', elem_id="img2img_settings"):
 
                 with gr.Tabs(elem_id="mode_img2img") as tabs_img2img_mode:
@@ -841,19 +838,23 @@ def create_ui():
                         init_img_inpaint = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_base")
                         init_mask_inpaint = gr.Image(label="Mask", source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_mask")
 
-                        with gr.Row():
+                        with FormRow():
                             mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id="img2img_mask_blur")
                             mask_alpha = gr.Slider(label="Mask transparency", interactive=use_color_sketch, visible=use_color_sketch, elem_id="img2img_mask_alpha")
 
-                        with gr.Row():
-                            mask_mode = gr.Radio(label="Mask mode", show_label=False, choices=["Draw mask", "Upload mask"], type="index", value="Draw mask", elem_id="mask_mode")
-                            inpainting_mask_invert = gr.Radio(label='Masking mode', show_label=False, choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index", elem_id="img2img_mask_mode")
+                        with FormRow():
+                            mask_mode = gr.Radio(label="Mask source", choices=["Draw mask", "Upload mask"], type="index", value="Draw mask", elem_id="mask_mode")
+                            inpainting_mask_invert = gr.Radio(label='Mask mode', choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index", elem_id="img2img_mask_mode")
 
-                        inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='original', type="index", elem_id="img2img_inpainting_fill")
+                        with FormRow():
+                            inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='original', type="index", elem_id="img2img_inpainting_fill")
 
-                        with gr.Row():
-                            inpaint_full_res = gr.Checkbox(label='Inpaint at full resolution', value=False, elem_id="img2img_inpaint_full_res")
-                            inpaint_full_res_padding = gr.Slider(label='Inpaint at full resolution padding, pixels', minimum=0, maximum=256, step=4, value=32, elem_id="img2img_inpaint_full_res_padding")
+                        with FormRow():
+                            with gr.Column():
+                                inpaint_full_res = gr.Radio(label="Inpaint area", choices=["Whole picture", "Only masked"], type="index", value="Whole picture", elem_id="img2img_inpaint_full_res")
+
+                            with gr.Column(scale=4):
+                                inpaint_full_res_padding = gr.Slider(label='Only masked padding, pixels', minimum=0, maximum=256, step=4, value=32, elem_id="img2img_inpaint_full_res_padding")
 
                     with gr.TabItem('Batch img2img', id='batch', elem_id="img2img_batch_tab"):
                         hidden = '<br>Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else ''
@@ -861,30 +862,30 @@ def create_ui():
                         img2img_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, elem_id="img2img_batch_input_dir")
                         img2img_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, elem_id="img2img_batch_output_dir")
 
-                with gr.Row():
-                    resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", show_label=False, choices=["Just resize", "Crop and resize", "Resize and fill", "Just resize (latent upscale)"], type="index", value="Just resize")
+                with FormRow():
+                    resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", choices=["Just resize", "Crop and resize", "Resize and fill", "Just resize (latent upscale)"], type="index", value="Just resize")
 
                 steps, sampler_index = create_sampler_and_steps_selection(samplers_for_img2img, "img2img")
 
-                with gr.Group():
-                    width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
-                    height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
-
-                with gr.Row():
-                    restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="img2img_restore_faces")
-                    tiling = gr.Checkbox(label='Tiling', value=False, elem_id="img2img_tiling")
+                with FormRow():
+                    with gr.Column(elem_id="img2img_column_size", scale=4):
+                        width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
+                        height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
+                    with gr.Column(elem_id="img2img_column_batch"):
+                        batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
+                        batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")
 
-                with gr.Row():
-                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
-                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")
-
-                with gr.Group():
+                with FormGroup():
                     cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="img2img_cfg_scale")
                     denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75, elem_id="img2img_denoising_strength")
 
                 seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('img2img')
 
-                with gr.Group(elem_id="img2img_script_container"):
+                with FormRow(elem_id="img2img_checkboxes"):
+                    restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="img2img_restore_faces")
+                    tiling = gr.Checkbox(label='Tiling', value=False, elem_id="img2img_tiling")
+
+                with FormGroup(elem_id="img2img_script_container"):
                     custom_inputs = modules.scripts.scripts_img2img.setup_ui()
 
             img2img_gallery, generation_info, html_info, html_log = create_output_panel("img2img", opts.outdir_img2img_samples)
@@ -1444,7 +1445,7 @@ def create_ui():
                 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 ui_components.FormRow():
+                with FormRow():
                     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:
diff --git a/modules/ui_components.py b/modules/ui_components.py
index d0519d2d..91eb0e3d 100644
--- a/modules/ui_components.py
+++ b/modules/ui_components.py
@@ -16,3 +16,10 @@ class FormRow(gr.Row, gr.components.FormComponent):
 
     def get_block_name(self):
         return "row"
+
+
+class FormGroup(gr.Group, gr.components.FormComponent):
+    """Same as gr.Row but fits inside gradio forms"""
+
+    def get_block_name(self):
+        return "group"
diff --git a/style.css b/style.css
index 7df4d960..86a265f6 100644
--- a/style.css
+++ b/style.css
@@ -74,7 +74,8 @@
 }
 
 [id$=_random_seed], [id$=_random_subseed], [id$=_reuse_seed], [id$=_reuse_subseed], #open_folder{
-    min-width: auto;
+    min-width: 2.3em;
+    height: 2.5em;
     flex-grow: 0;
     padding-left: 0.25em;
     padding-right: 0.25em;
@@ -86,6 +87,7 @@
 
 [id$=_seed_row], [id$=_subseed_row]{
     gap: 0.5rem;
+    padding: 0.6em;
 }
 
 [id$=_subseed_show_box]{
@@ -206,24 +208,24 @@ button{
 
 fieldset span.text-gray-500, .gr-block.gr-box span.text-gray-500,  label.block span{
     position: absolute;
-    top: -0.6em;
+    top: -0.5em;
     line-height: 1.2em;
-    padding: 0 0.5em;
-    margin: 0;
+    padding: 0;
+    margin: 0 0.5em;
 
     background-color: white;
-    border-top: 1px solid #eee;
-    border-left: 1px solid #eee;
-    border-right: 1px solid #eee;
+    box-shadow: 0 0 5px 5px white;
 
     z-index: 300;
 }
 
 .dark fieldset span.text-gray-500, .dark .gr-block.gr-box span.text-gray-500, .dark label.block span{
     background-color: rgb(31, 41, 55);
-    border-top: 1px solid rgb(55 65 81);
-    border-left: 1px solid rgb(55 65 81);
-    border-right: 1px solid rgb(55 65 81);
+    box-shadow: 0 0 5px 5px rgb(31, 41, 55);
+}
+
+#txt2img_column_batch, #img2img_column_batch{
+    min-width: min(13.5em, 100%) !important;
 }
 
 #settings fieldset span.text-gray-500, #settings .gr-block.gr-box span.text-gray-500, #settings label.block span{
@@ -232,10 +234,6 @@ fieldset span.text-gray-500, .gr-block.gr-box span.text-gray-500,  label.block s
     margin-right: 8em;
 }
 
-.gr-panel div.flex-col div.justify-between label span{
-    margin: 0;
-}
-
 #settings .gr-panel div.flex-col div.justify-between div{
     position: relative;
     z-index: 200;
@@ -609,6 +607,15 @@ img2maskimg, #img2maskimg > .h-60, #img2maskimg > .h-60 > div, #img2maskimg > .h
 }
 
 
+#img2img_settings > div.gr-form, #txt2img_settings > div.gr-form {
+    padding-top: 0.9em;
+}
+
+#img2img_settings div.gr-form .gr-form, #txt2img_settings div.gr-form .gr-form{
+    border: none;
+    padding-bottom: 0.5em;
+}
+
 
 /* The following handles localization for right-to-left (RTL) languages like Arabic.
 The rtl media type will only be activated by the logic in javascript/localization.js.
-- 
cgit v1.2.3


From 2bc86712ec16cada01a2353f1d978c1aabc84dbb Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 3 Jan 2023 09:13:35 +0300
Subject: make quicksettings UI elements appear in same order as they are
 listed in the setting

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

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index f787b518..d7b911da 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1497,7 +1497,7 @@ def create_ui():
         result = gr.HTML(elem_id="settings_result")
 
         quicksettings_names = [x.strip() for x in opts.quicksettings.split(",")]
-        quicksettings_names = set(x for x in quicksettings_names if x != 'quicksettings')
+        quicksettings_names = {x: i for i, x in enumerate(quicksettings_names) if x != 'quicksettings'}
 
         quicksettings_list = []
 
@@ -1604,7 +1604,7 @@ def create_ui():
 
     with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion") as demo:
         with gr.Row(elem_id="quicksettings"):
-            for i, k, item in quicksettings_list:
+            for i, k, item in sorted(quicksettings_list, key=lambda x: quicksettings_names.get(x[1], x[0])):
                 component = create_setting_component(k, is_quicksettings=True)
                 component_dict[k] = component
 
-- 
cgit v1.2.3


From 9d4eff097deff6153c4023f158bd9fbd4f3e88b3 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 3 Jan 2023 10:01:06 +0300
Subject: add a button to show all setting pages

---
 javascript/ui.js | 11 +++++++++++
 modules/ui.py    |  2 ++
 2 files changed, 13 insertions(+)

(limited to 'modules/ui.py')

diff --git a/javascript/ui.js b/javascript/ui.js
index d0c054d9..34406f3f 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -188,6 +188,17 @@ onUiUpdate(function(){
 		img2img_textarea = gradioApp().querySelector("#img2img_prompt > label > textarea");
 		img2img_textarea?.addEventListener("input", () => update_token_counter("img2img_token_button"));
 	}
+
+    show_all_pages = gradioApp().getElementById('settings_show_all_pages')
+    settings_tabs = gradioApp().querySelector('#settings div')
+    if(show_all_pages && settings_tabs){
+        settings_tabs.appendChild(show_all_pages)
+        show_all_pages.onclick = function(){
+            gradioApp().querySelectorAll('#settings > div').forEach(function(elem){
+                elem.style.display = "block";
+            })
+        }
+    }
 })
 
 let txt2img_textarea, img2img_textarea = undefined;
diff --git a/modules/ui.py b/modules/ui.py
index d7b911da..2c92c422 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1536,6 +1536,8 @@ def create_ui():
                 download_localization = gr.Button(value='Download localization template', elem_id="download_localization")
                 reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary', elem_id="settings_reload_script_bodies")
 
+            gr.Button(value="Show all pages", elem_id="settings_show_all_pages")
+
         request_notifications.click(
             fn=lambda: None,
             inputs=[],
-- 
cgit v1.2.3


From a1cf55a9d1c82f8e56c00d549bca5c8fa069f412 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 3 Jan 2023 10:39:21 +0300
Subject: add option to reorder items in main UI

---
 modules/shared.py |  13 ++++++
 modules/ui.py     | 130 +++++++++++++++++++++++++++++++++++-------------------
 2 files changed, 97 insertions(+), 46 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/shared.py b/modules/shared.py
index b65559ee..23657a93 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -109,6 +109,17 @@ restricted_opts = {
     "outdir_save",
 }
 
+ui_reorder_categories = [
+    "sampler",
+    "dimensions",
+    "cfg",
+    "seed",
+    "checkboxes",
+    "hires_fix",
+    "batch",
+    "scripts",
+]
+
 cmd_opts.disable_extension_access = (cmd_opts.share or cmd_opts.listen or cmd_opts.server_name) and not cmd_opts.enable_insecure_extension_access
 
 devices.device, devices.device_interrogate, devices.device_gfpgan, devices.device_esrgan, devices.device_codeformer = \
@@ -410,7 +421,9 @@ options_templates.update(options_section(('ui', "User interface"), {
     "js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),
     "show_progress_in_title": OptionInfo(True, "Show generation progress in window title."),
     "samplers_in_dropdown": OptionInfo(True, "Use dropdown for sampler selection instead of radio group"),
+    "dimensions_and_batch_together": OptionInfo(True, "Show Witdth/Height and Batch sliders in same row"),
     'quicksettings': OptionInfo("sd_model_checkpoint", "Quicksettings list"),
+    'ui_reorder': OptionInfo(", ".join(ui_reorder_categories), "txt2img/ing2img UI item order"),
     'localization': OptionInfo("None", "Localization (requires restart)", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)),
 }))
 
diff --git a/modules/ui.py b/modules/ui.py
index 2c92c422..f2e7c0d6 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -644,6 +644,13 @@ def create_sampler_and_steps_selection(choices, tabname):
     return steps, sampler_index
 
 
+def ordered_ui_categories():
+    user_order = {x.strip(): i for i, x in enumerate(shared.opts.ui_reorder.split(","))}
+
+    for i, category in sorted(enumerate(shared.ui_reorder_categories), key=lambda x: user_order.get(x[1], x[0] + 1000)):
+        yield category
+
+
 def create_ui():
     import modules.img2img
     import modules.txt2img
@@ -672,32 +679,48 @@ def create_ui():
 
         with gr.Row().style(equal_height=False):
             with gr.Column(variant='panel', elem_id="txt2img_settings"):
-                steps, sampler_index = create_sampler_and_steps_selection(samplers, "txt2img")
-
-                with FormRow():
-                    with gr.Column(elem_id="txt2img_column_size", scale=4):
-                        width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="txt2img_width")
-                        height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="txt2img_height")
-                    with gr.Column(elem_id="txt2img_column_batch"):
-                        batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
-                        batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
-
-                cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="txt2img_cfg_scale")
-
-                seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('txt2img')
-
-                with FormRow(elem_id="txt2img_checkboxes"):
-                    restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="txt2img_restore_faces")
-                    tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling")
-                    enable_hr = gr.Checkbox(label='Hires. fix', value=False, elem_id="txt2img_enable_hr")
+                for category in ordered_ui_categories():
+                    if category == "sampler":
+                        steps, sampler_index = create_sampler_and_steps_selection(samplers, "txt2img")
 
-                with FormRow(visible=False) as hr_options:
-                    hr_upscaler = gr.Dropdown(label="Upscaler", elem_id="txt2img_hr_upscaler", choices=[*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]], value=shared.latent_upscale_default_mode)
-                    hr_scale = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Upscale by", value=2.0, elem_id="txt2img_hr_scale")
-                    denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7, elem_id="txt2img_denoising_strength")
-
-                with FormGroup(elem_id="txt2img_script_container"):
-                    custom_inputs = modules.scripts.scripts_txt2img.setup_ui()
+                    elif category == "dimensions":
+                        with FormRow():
+                            with gr.Column(elem_id="txt2img_column_size", scale=4):
+                                width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="txt2img_width")
+                                height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="txt2img_height")
+
+                            if opts.dimensions_and_batch_together:
+                                with gr.Column(elem_id="txt2img_column_batch"):
+                                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
+                                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
+
+                    elif category == "cfg":
+                        cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="txt2img_cfg_scale")
+
+                    elif category == "seed":
+                        seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('txt2img')
+
+                    elif category == "checkboxes":
+                        with FormRow(elem_id="txt2img_checkboxes"):
+                            restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="txt2img_restore_faces")
+                            tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling")
+                            enable_hr = gr.Checkbox(label='Hires. fix', value=False, elem_id="txt2img_enable_hr")
+
+                    elif category == "hires_fix":
+                        with FormRow(visible=False, elem_id="txt2img_hires_fix") as hr_options:
+                            hr_upscaler = gr.Dropdown(label="Upscaler", elem_id="txt2img_hr_upscaler", choices=[*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]], value=shared.latent_upscale_default_mode)
+                            hr_scale = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Upscale by", value=2.0, elem_id="txt2img_hr_scale")
+                            denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7, elem_id="txt2img_denoising_strength")
+
+                    elif category == "batch":
+                        if not opts.dimensions_and_batch_together:
+                            with FormRow(elem_id="txt2img_column_batch"):
+                                batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
+                                batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
+
+                    elif category == "scripts":
+                        with FormGroup(elem_id="txt2img_script_container"):
+                            custom_inputs = modules.scripts.scripts_txt2img.setup_ui()
 
             txt2img_gallery, generation_info, html_info, html_log = create_output_panel("txt2img", opts.outdir_txt2img_samples)
             parameters_copypaste.bind_buttons({"txt2img": txt2img_paste}, None, txt2img_prompt)
@@ -865,28 +888,43 @@ def create_ui():
                 with FormRow():
                     resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", choices=["Just resize", "Crop and resize", "Resize and fill", "Just resize (latent upscale)"], type="index", value="Just resize")
 
-                steps, sampler_index = create_sampler_and_steps_selection(samplers_for_img2img, "img2img")
-
-                with FormRow():
-                    with gr.Column(elem_id="img2img_column_size", scale=4):
-                        width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
-                        height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
-                    with gr.Column(elem_id="img2img_column_batch"):
-                        batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
-                        batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")
-
-                with FormGroup():
-                    cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="img2img_cfg_scale")
-                    denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75, elem_id="img2img_denoising_strength")
-
-                seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('img2img')
+                for category in ordered_ui_categories():
+                    if category == "sampler":
+                        steps, sampler_index = create_sampler_and_steps_selection(samplers_for_img2img, "img2img")
 
-                with FormRow(elem_id="img2img_checkboxes"):
-                    restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="img2img_restore_faces")
-                    tiling = gr.Checkbox(label='Tiling', value=False, elem_id="img2img_tiling")
-
-                with FormGroup(elem_id="img2img_script_container"):
-                    custom_inputs = modules.scripts.scripts_img2img.setup_ui()
+                    elif category == "dimensions":
+                        with FormRow():
+                            with gr.Column(elem_id="img2img_column_size", scale=4):
+                                width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
+                                height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
+
+                            if opts.dimensions_and_batch_together:
+                                with gr.Column(elem_id="img2img_column_batch"):
+                                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
+                                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")
+
+                    elif category == "cfg":
+                        with FormGroup():
+                            cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="img2img_cfg_scale")
+                            denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75, elem_id="img2img_denoising_strength")
+
+                    elif category == "seed":
+                        seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('img2img')
+
+                    elif category == "checkboxes":
+                        with FormRow(elem_id="img2img_checkboxes"):
+                            restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="img2img_restore_faces")
+                            tiling = gr.Checkbox(label='Tiling', value=False, elem_id="img2img_tiling")
+
+                    elif category == "batch":
+                        if not opts.dimensions_and_batch_together:
+                            with FormRow(elem_id="img2img_column_batch"):
+                                batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
+                                batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")
+
+                    elif category == "scripts":
+                        with FormGroup(elem_id="img2img_script_container"):
+                            custom_inputs = modules.scripts.scripts_img2img.setup_ui()
 
             img2img_gallery, generation_info, html_info, html_log = create_output_panel("img2img", opts.outdir_img2img_samples)
             parameters_copypaste.bind_buttons({"img2img": img2img_paste}, None, img2img_prompt)
-- 
cgit v1.2.3


From 82cfc227d735c140447d5b8dca29a71ee9bde127 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 3 Jan 2023 20:23:17 +0300
Subject: added licenses screen to settings added footer removed unused
 inpainting code

---
 README.md                       |   2 +
 html/footer.html                |   9 +
 html/licenses.html              | 392 ++++++++++++++++++++++++++++++++++++++++
 modules/sd_hijack_inpainting.py | 232 ------------------------
 modules/ui.py                   |  15 +-
 style.css                       |  11 ++
 6 files changed, 427 insertions(+), 234 deletions(-)
 create mode 100644 html/footer.html
 create mode 100644 html/licenses.html

(limited to 'modules/ui.py')

diff --git a/README.md b/README.md
index 556000fb..88250a6b 100644
--- a/README.md
+++ b/README.md
@@ -127,6 +127,8 @@ Here's how to add code to this repo: [Contributing](https://github.com/AUTOMATIC
 The documentation was moved from this README over to the project's [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki).
 
 ## Credits
+Licenses for borrowed code can be found in `Settings -> Licenses` screen, and also in `html/licenses.html` file.
+
 - Stable Diffusion - https://github.com/CompVis/stable-diffusion, https://github.com/CompVis/taming-transformers
 - k-diffusion - https://github.com/crowsonkb/k-diffusion.git
 - GFPGAN - https://github.com/TencentARC/GFPGAN.git
diff --git a/html/footer.html b/html/footer.html
new file mode 100644
index 00000000..a8f2adf7
--- /dev/null
+++ b/html/footer.html
@@ -0,0 +1,9 @@
+<div>
+        <a href="/docs">API</a>
+         • 
+        <a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui">Github</a>
+         • 
+        <a href="https://gradio.app">Gradio</a>
+         • 
+        <a href="/" onclick="javascript:gradioApp().getElementById('settings_restart_gradio').click(); return false">Reload UI</a>
+</div>
diff --git a/html/licenses.html b/html/licenses.html
new file mode 100644
index 00000000..9eeaa072
--- /dev/null
+++ b/html/licenses.html
@@ -0,0 +1,392 @@
+<style>
+    #licenses h2 {font-size: 1.2em; font-weight: bold; margin-bottom: 0.2em;}
+    #licenses small {font-size: 0.95em; opacity: 0.85;}
+    #licenses pre { margin: 1em 0 2em 0;}
+</style>
+
+<h2><a href="https://github.com/sczhou/CodeFormer/blob/master/LICENSE">CodeFormer</a></h2>
+<small>Parts of CodeFormer code had to be copied to be compatible with GFPGAN.</small>
+<pre>
+S-Lab License 1.0
+
+Copyright 2022 S-Lab
+
+Redistribution and use for non-commercial purpose in source and
+binary forms, with or without modification, are permitted provided
+that the following conditions are met:
+
+1. Redistributions of source code must retain the above copyright
+   notice, this list of conditions and the following disclaimer.
+
+2. Redistributions in binary form must reproduce the above copyright
+   notice, this list of conditions and the following disclaimer in
+   the documentation and/or other materials provided with the
+   distribution.
+
+3. Neither the name of the copyright holder nor the names of its
+   contributors may be used to endorse or promote products derived
+   from this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+In the event that redistribution and/or use for commercial purpose in
+source or binary forms, with or without modification is required,
+please contact the contributor(s) of the work.
+</pre>
+
+
+<h2><a href="https://github.com/victorca25/iNNfer/blob/main/LICENSE">ESRGAN</a></h2>
+<small>Code for architecture and reading models copied.</small>
+<pre>
+MIT License
+
+Copyright (c) 2021 victorca25
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+</pre>
+
+<h2><a href="https://github.com/xinntao/Real-ESRGAN/blob/master/LICENSE">Real-ESRGAN</a></h2>
+<small>Some code is copied to support ESRGAN models.</small>
+<pre>
+BSD 3-Clause License
+
+Copyright (c) 2021, Xintao Wang
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+1. Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+
+2. Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+
+3. Neither the name of the copyright holder nor the names of its
+   contributors may be used to endorse or promote products derived from
+   this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+</pre>
+
+<h2><a href="https://github.com/invoke-ai/InvokeAI/blob/main/LICENSE">InvokeAI</a></h2>
+<small>Some code for compatibility with OSX is taken from lstein's repository.</small>
+<pre>
+MIT License
+
+Copyright (c) 2022 InvokeAI Team
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+</pre>
+
+<h2><a href="https://github.com/Hafiidz/latent-diffusion/blob/main/LICENSE">LDSR</a></h2>
+<small>Code added by contirubtors, most likely copied from this repository.</small>
+<pre>
+MIT License
+
+Copyright (c) 2022 Machine Vision and Learning Group, LMU Munich
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+</pre>
+
+<h2><a href="https://github.com/pharmapsychotic/clip-interrogator/blob/main/LICENSE">CLIP Interrogator</a></h2>
+<small>Some small amounts of code borrowed and reworked.</small>
+<pre>
+MIT License
+
+Copyright (c) 2022 pharmapsychotic
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+</pre>
+
+<h2><a href="https://github.com/JingyunLiang/SwinIR/blob/main/LICENSE">SwinIR</a></h2>
+<small>Code added by contirubtors, most likely copied from this repository.</small>
+
+<pre>
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+   5. Submission of Contributions. Unless You explicitly state otherwise,
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+   Copyright [2021] [SwinIR Authors]
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.
+</pre>
+
diff --git a/modules/sd_hijack_inpainting.py b/modules/sd_hijack_inpainting.py
index 06b75772..3c214a35 100644
--- a/modules/sd_hijack_inpainting.py
+++ b/modules/sd_hijack_inpainting.py
@@ -12,191 +12,6 @@ from ldm.models.diffusion.ddpm import LatentDiffusion
 from ldm.models.diffusion.plms import PLMSSampler
 from ldm.models.diffusion.ddim import DDIMSampler, noise_like
 
-# =================================================================================================
-# Monkey patch DDIMSampler methods from RunwayML repo directly.
-# Adapted from:
-# https://github.com/runwayml/stable-diffusion/blob/main/ldm/models/diffusion/ddim.py
-# =================================================================================================
-@torch.no_grad()
-def sample_ddim(self,
-            S,
-            batch_size,
-            shape,
-            conditioning=None,
-            callback=None,
-            normals_sequence=None,
-            img_callback=None,
-            quantize_x0=False,
-            eta=0.,
-            mask=None,
-            x0=None,
-            temperature=1.,
-            noise_dropout=0.,
-            score_corrector=None,
-            corrector_kwargs=None,
-            verbose=True,
-            x_T=None,
-            log_every_t=100,
-            unconditional_guidance_scale=1.,
-            unconditional_conditioning=None,
-            # this has to come in the same format as the conditioning, # e.g. as encoded tokens, ...
-            **kwargs
-            ):
-    if conditioning is not None:
-        if isinstance(conditioning, dict):
-            ctmp = conditioning[list(conditioning.keys())[0]]
-            while isinstance(ctmp, list):
-                ctmp = ctmp[0]
-            cbs = ctmp.shape[0]
-            if cbs != batch_size:
-                print(f"Warning: Got {cbs} conditionings but batch-size is {batch_size}")
-        else:
-            if conditioning.shape[0] != batch_size:
-                print(f"Warning: Got {conditioning.shape[0]} conditionings but batch-size is {batch_size}")
-
-    self.make_schedule(ddim_num_steps=S, ddim_eta=eta, verbose=verbose)
-    # sampling
-    C, H, W = shape
-    size = (batch_size, C, H, W)
-    print(f'Data shape for DDIM sampling is {size}, eta {eta}')
-
-    samples, intermediates = self.ddim_sampling(conditioning, size,
-                                                callback=callback,
-                                                img_callback=img_callback,
-                                                quantize_denoised=quantize_x0,
-                                                mask=mask, x0=x0,
-                                                ddim_use_original_steps=False,
-                                                noise_dropout=noise_dropout,
-                                                temperature=temperature,
-                                                score_corrector=score_corrector,
-                                                corrector_kwargs=corrector_kwargs,
-                                                x_T=x_T,
-                                                log_every_t=log_every_t,
-                                                unconditional_guidance_scale=unconditional_guidance_scale,
-                                                unconditional_conditioning=unconditional_conditioning,
-                                                )
-    return samples, intermediates
-
-@torch.no_grad()
-def p_sample_ddim(self, x, c, t, index, repeat_noise=False, use_original_steps=False, quantize_denoised=False,
-                    temperature=1., noise_dropout=0., score_corrector=None, corrector_kwargs=None,
-                    unconditional_guidance_scale=1., unconditional_conditioning=None):
-    b, *_, device = *x.shape, x.device
-
-    if unconditional_conditioning is None or unconditional_guidance_scale == 1.:
-        e_t = self.model.apply_model(x, t, c)
-    else:
-        x_in = torch.cat([x] * 2)
-        t_in = torch.cat([t] * 2)
-        if isinstance(c, dict):
-            assert isinstance(unconditional_conditioning, dict)
-            c_in = dict()
-            for k in c:
-                if isinstance(c[k], list):
-                    c_in[k] = [
-                        torch.cat([unconditional_conditioning[k][i], c[k][i]])
-                        for i in range(len(c[k]))
-                    ]
-                else:
-                    c_in[k] = torch.cat([unconditional_conditioning[k], c[k]])
-        else:
-            c_in = torch.cat([unconditional_conditioning, c])
-        e_t_uncond, e_t = self.model.apply_model(x_in, t_in, c_in).chunk(2)
-        e_t = e_t_uncond + unconditional_guidance_scale * (e_t - e_t_uncond)
-
-    if score_corrector is not None:
-        assert self.model.parameterization == "eps"
-        e_t = score_corrector.modify_score(self.model, e_t, x, t, c, **corrector_kwargs)
-
-    alphas = self.model.alphas_cumprod if use_original_steps else self.ddim_alphas
-    alphas_prev = self.model.alphas_cumprod_prev if use_original_steps else self.ddim_alphas_prev
-    sqrt_one_minus_alphas = self.model.sqrt_one_minus_alphas_cumprod if use_original_steps else self.ddim_sqrt_one_minus_alphas
-    sigmas = self.model.ddim_sigmas_for_original_num_steps if use_original_steps else self.ddim_sigmas
-    # select parameters corresponding to the currently considered timestep
-    a_t = torch.full((b, 1, 1, 1), alphas[index], device=device)
-    a_prev = torch.full((b, 1, 1, 1), alphas_prev[index], device=device)
-    sigma_t = torch.full((b, 1, 1, 1), sigmas[index], device=device)
-    sqrt_one_minus_at = torch.full((b, 1, 1, 1), sqrt_one_minus_alphas[index],device=device)
-
-    # current prediction for x_0
-    pred_x0 = (x - sqrt_one_minus_at * e_t) / a_t.sqrt()
-    if quantize_denoised:
-        pred_x0, _, *_ = self.model.first_stage_model.quantize(pred_x0)
-    # direction pointing to x_t
-    dir_xt = (1. - a_prev - sigma_t**2).sqrt() * e_t
-    noise = sigma_t * noise_like(x.shape, device, repeat_noise) * temperature
-    if noise_dropout > 0.:
-        noise = torch.nn.functional.dropout(noise, p=noise_dropout)
-    x_prev = a_prev.sqrt() * pred_x0 + dir_xt + noise
-    return x_prev, pred_x0
-
-
-# =================================================================================================
-# Monkey patch PLMSSampler methods.
-# This one was not actually patched correctly in the RunwayML repo, but we can replicate the changes.
-# Adapted from:
-# https://github.com/CompVis/stable-diffusion/blob/main/ldm/models/diffusion/plms.py
-# =================================================================================================
-@torch.no_grad()
-def sample_plms(self,
-            S,
-            batch_size,
-            shape,
-            conditioning=None,
-            callback=None,
-            normals_sequence=None,
-            img_callback=None,
-            quantize_x0=False,
-            eta=0.,
-            mask=None,
-            x0=None,
-            temperature=1.,
-            noise_dropout=0.,
-            score_corrector=None,
-            corrector_kwargs=None,
-            verbose=True,
-            x_T=None,
-            log_every_t=100,
-            unconditional_guidance_scale=1.,
-            unconditional_conditioning=None,
-            # this has to come in the same format as the conditioning, # e.g. as encoded tokens, ...
-            **kwargs
-            ):
-    if conditioning is not None:
-        if isinstance(conditioning, dict):
-            ctmp = conditioning[list(conditioning.keys())[0]]
-            while isinstance(ctmp, list):
-                ctmp = ctmp[0]
-            cbs = ctmp.shape[0]
-            if cbs != batch_size:
-                print(f"Warning: Got {cbs} conditionings but batch-size is {batch_size}")
-        else:
-            if conditioning.shape[0] != batch_size:
-                print(f"Warning: Got {conditioning.shape[0]} conditionings but batch-size is {batch_size}")
-
-    self.make_schedule(ddim_num_steps=S, ddim_eta=eta, verbose=verbose)
-    # sampling
-    C, H, W = shape
-    size = (batch_size, C, H, W)
-    # print(f'Data shape for PLMS sampling is {size}') # remove unnecessary message
-
-    samples, intermediates = self.plms_sampling(conditioning, size,
-                                                callback=callback,
-                                                img_callback=img_callback,
-                                                quantize_denoised=quantize_x0,
-                                                mask=mask, x0=x0,
-                                                ddim_use_original_steps=False,
-                                                noise_dropout=noise_dropout,
-                                                temperature=temperature,
-                                                score_corrector=score_corrector,
-                                                corrector_kwargs=corrector_kwargs,
-                                                x_T=x_T,
-                                                log_every_t=log_every_t,
-                                                unconditional_guidance_scale=unconditional_guidance_scale,
-                                                unconditional_conditioning=unconditional_conditioning,
-                                                )
-    return samples, intermediates
-
 
 @torch.no_grad()
 def p_sample_plms(self, x, c, t, index, repeat_noise=False, use_original_steps=False, quantize_denoised=False,
@@ -280,44 +95,6 @@ def p_sample_plms(self, x, c, t, index, repeat_noise=False, use_original_steps=F
 
     return x_prev, pred_x0, e_t
 
-# =================================================================================================
-# Monkey patch LatentInpaintDiffusion to load the checkpoint with a proper config.
-# Adapted from:
-# https://github.com/runwayml/stable-diffusion/blob/main/ldm/models/diffusion/ddpm.py
-# =================================================================================================
-
-@torch.no_grad()
-def get_unconditional_conditioning(self, batch_size, null_label=None):
-    if null_label is not None:
-        xc = null_label
-        if isinstance(xc, ListConfig):
-            xc = list(xc)
-        if isinstance(xc, dict) or isinstance(xc, list):
-            c = self.get_learned_conditioning(xc)
-        else:
-            if hasattr(xc, "to"):
-                xc = xc.to(self.device)
-            c = self.get_learned_conditioning(xc)
-    else:
-        # todo: get null label from cond_stage_model
-        raise NotImplementedError()
-    c = repeat(c, "1 ... -> b ...", b=batch_size).to(self.device)
-    return c
-
-
-class LatentInpaintDiffusion(LatentDiffusion):
-    def __init__(
-        self,
-        concat_keys=("mask", "masked_image"),
-        masked_image_key="masked_image",
-        *args,
-        **kwargs,
-    ):
-        super().__init__(*args, **kwargs)
-        self.masked_image_key = masked_image_key
-        assert self.masked_image_key in concat_keys
-        self.concat_keys = concat_keys
-
 
 def should_hijack_inpainting(checkpoint_info):
     ckpt_basename = os.path.basename(checkpoint_info.filename).lower()
@@ -326,15 +103,6 @@ def should_hijack_inpainting(checkpoint_info):
 
 
 def do_inpainting_hijack():
-    # most of this stuff seems to no longer be needed because it is already included into SD2.0
     # p_sample_plms is needed because PLMS can't work with dicts as conditionings
-    # this file should be cleaned up later if everything turns out to work fine
-
-    # ldm.models.diffusion.ddpm.get_unconditional_conditioning = get_unconditional_conditioning
-    # ldm.models.diffusion.ddpm.LatentInpaintDiffusion = LatentInpaintDiffusion
-
-    # ldm.models.diffusion.ddim.DDIMSampler.p_sample_ddim = p_sample_ddim
-    # ldm.models.diffusion.ddim.DDIMSampler.sample = sample_ddim
 
     ldm.models.diffusion.plms.PLMSSampler.p_sample_plms = p_sample_plms
-    # ldm.models.diffusion.plms.PLMSSampler.sample = sample_plms
diff --git a/modules/ui.py b/modules/ui.py
index f2e7c0d6..d941cb5f 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1529,8 +1529,10 @@ def create_ui():
 
     with gr.Blocks(analytics_enabled=False) as settings_interface:
         with gr.Row():
-            settings_submit = gr.Button(value="Apply settings", variant='primary', elem_id="settings_submit")
-            restart_gradio = gr.Button(value='Restart UI', variant='primary', elem_id="settings_restart_gradio")
+            with gr.Column(scale=6):
+                settings_submit = gr.Button(value="Apply settings", variant='primary', elem_id="settings_submit")
+            with gr.Column():
+                restart_gradio = gr.Button(value='Reload UI', variant='primary', elem_id="settings_restart_gradio")
 
         result = gr.HTML(elem_id="settings_result")
 
@@ -1574,6 +1576,11 @@ def create_ui():
                 download_localization = gr.Button(value='Download localization template', elem_id="download_localization")
                 reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary', elem_id="settings_reload_script_bodies")
 
+            if os.path.exists("html/licenses.html"):
+                with open("html/licenses.html", encoding="utf8") as file:
+                    with gr.TabItem("Licenses"):
+                        gr.HTML(file.read(), elem_id="licenses")
+
             gr.Button(value="Show all pages", elem_id="settings_show_all_pages")
 
         request_notifications.click(
@@ -1659,6 +1666,10 @@ def create_ui():
         if os.path.exists(os.path.join(script_path, "notification.mp3")):
             audio_notification = gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False)
 
+        if os.path.exists("html/footer.html"):
+            with open("html/footer.html", encoding="utf8") as file:
+                gr.HTML(file.read(), elem_id="footer")
+
         text_settings = gr.Textbox(elem_id="settings_json", value=lambda: opts.dumpjson(), visible=False)
         settings_submit.click(
             fn=wrap_gradio_call(run_settings, extra_outputs=[gr.update()]),
diff --git a/style.css b/style.css
index 7296ce91..2116ec3c 100644
--- a/style.css
+++ b/style.css
@@ -616,6 +616,17 @@ img2maskimg, #img2maskimg > .h-60, #img2maskimg > .h-60 > div, #img2maskimg > .h
     padding-bottom: 0.5em;
 }
 
+footer {
+    display: none !important;
+}
+
+#footer{
+    text-align: center;
+}
+
+#footer div{
+    display: inline-block;
+}
 
 /* The following handles localization for right-to-left (RTL) languages like Arabic.
 The rtl media type will only be activated by the logic in javascript/localization.js.
-- 
cgit v1.2.3


From 917b5bd8d0cd47c9dc241c1852ccd440a8c61668 Mon Sep 17 00:00:00 2001
From: Max Weber <mii7303@gmail.com>
Date: Tue, 3 Jan 2023 18:19:56 -0700
Subject: ui: save dropdown sampling method to the ui-config

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

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index d941cb5f..bfc93634 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -635,6 +635,7 @@ def create_sampler_and_steps_selection(choices, tabname):
     if opts.samplers_in_dropdown:
         with FormRow(elem_id=f"sampler_selection_{tabname}"):
             sampler_index = gr.Dropdown(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")
+            sampler_index.save_to_config = True
             steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling Steps", value=20)
     else:
         with FormGroup(elem_id=f"sampler_selection_{tabname}"):
-- 
cgit v1.2.3


From 3dae545a03f5102ba5d9c3f27bb6241824c5a916 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 4 Jan 2023 18:42:51 +0300
Subject: rename weirdly named variables from #3176

---
 modules/ui.py | 12 +++++-------
 1 file changed, 5 insertions(+), 7 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index e4859020..184af7ad 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -162,16 +162,14 @@ def save_files(js_data, images, do_make_zip, index):
     return gr.File.update(value=fullfns, visible=True), plaintext_to_html(f"Saved: {filenames[0]}")
 
 
-
-
-def calc_time_left(progress, threshold, label, force_display, showTime):
+def calc_time_left(progress, threshold, label, force_display, show_eta):
     if progress == 0:
         return ""
     else:
         time_since_start = time.time() - shared.state.time_start
         eta = (time_since_start/progress)
         eta_relative = eta-time_since_start
-        if (eta_relative > threshold and showTime) or force_display:
+        if (eta_relative > threshold and show_eta) or force_display:
             if eta_relative > 3600:
                 return label + time.strftime('%H:%M:%S', time.gmtime(eta_relative))
             elif eta_relative > 60:
@@ -194,9 +192,9 @@ def check_progress_call(id_part):
         progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps
 
     # Show progress percentage and time left at the same moment, and base it also on steps done
-    showPBText = progress >= 0.01 or shared.state.sampling_step >= 10
+    show_eta = progress >= 0.01 or shared.state.sampling_step >= 10
 
-    time_left = calc_time_left( progress, 1, " ETA: ", shared.state.time_left_force_display, showPBText )
+    time_left = calc_time_left(progress, 1, " ETA: ", shared.state.time_left_force_display, show_eta)
     if time_left != "":
         shared.state.time_left_force_display = True
 
@@ -204,7 +202,7 @@ def check_progress_call(id_part):
 
     progressbar = ""
     if opts.show_progressbar:
-        progressbar = f"""<div class='progressDiv'><div class='progress' style="overflow:visible;width:{progress * 100}%;white-space:nowrap;">{"&nbsp;" * 2 + str(int(progress*100))+"%" + time_left if showPBText else ""}</div></div>"""
+        progressbar = f"""<div class='progressDiv'><div class='progress' style="overflow:visible;width:{progress * 100}%;white-space:nowrap;">{"&nbsp;" * 2 + str(int(progress*100))+"%" + time_left if show_eta else ""}</div></div>"""
 
     image = gr_show(False)
     preview_visibility = gr_show(False)
-- 
cgit v1.2.3


From 24d4a0841d3cc0e5908b098f65a9caa3fa889af8 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 4 Jan 2023 20:10:40 +0300
Subject: train tab visual updates allow setting train tab values from
 ui-config.json

---
 modules/ui.py | 35 +++++++++++++++++++++--------------
 style.css     |  2 +-
 2 files changed, 22 insertions(+), 15 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index 72e7b7d2..44f4f3a4 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1281,42 +1281,48 @@ def create_ui():
 
                 with gr.Tab(label="Train"):
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images <a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\" style=\"font-weight:bold;\">[wiki]</a></p>")
-                    with gr.Row():
+                    with FormRow():
                         train_embedding_name = gr.Dropdown(label='Embedding', elem_id="train_embedding", choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
                         create_refresh_button(train_embedding_name, sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings, lambda: {"choices": sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())}, "refresh_train_embedding_name")
-                    with gr.Row():
+
                         train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=[x for x in shared.hypernetworks.keys()])
                         create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted([x for x in shared.hypernetworks.keys()])}, "refresh_train_hypernetwork_name")
-                    with gr.Row():
+
+                    with FormRow():
                         embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005", elem_id="train_embedding_learn_rate")
                         hypernetwork_learn_rate = gr.Textbox(label='Hypernetwork Learning rate', placeholder="Hypernetwork Learning rate", value="0.00001", elem_id="train_hypernetwork_learn_rate")
                     
-                    with gr.Row():
+                    with FormRow():
                         clip_grad_mode = gr.Dropdown(value="disabled", label="Gradient Clipping", choices=["disabled", "value", "norm"])
                         clip_grad_value = gr.Textbox(placeholder="Gradient clip value", value="0.1", show_label=False)
 
-                    batch_size = gr.Number(label='Batch size', value=1, precision=0, elem_id="train_batch_size")
-                    gradient_step = gr.Number(label='Gradient accumulation steps', value=1, precision=0, elem_id="train_gradient_step")
+                    with FormRow():
+                        batch_size = gr.Number(label='Batch size', value=1, precision=0, elem_id="train_batch_size")
+                        gradient_step = gr.Number(label='Gradient accumulation steps', value=1, precision=0, elem_id="train_gradient_step")
+
                     dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images", elem_id="train_dataset_directory")
                     log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion", elem_id="train_log_directory")
                     template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"), elem_id="train_template_file")
                     training_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_training_width")
                     training_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_training_height")
                     steps = gr.Number(label='Max steps', value=100000, precision=0, elem_id="train_steps")
-                    create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0, elem_id="train_create_image_every")
-                    save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0, elem_id="train_save_embedding_every")
+
+                    with FormRow():
+                        create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0, elem_id="train_create_image_every")
+                        save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0, elem_id="train_save_embedding_every")
+
                     save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True, elem_id="train_save_image_with_stored_embedding")
                     preview_from_txt2img = gr.Checkbox(label='Read parameters (prompt, etc...) from txt2img tab when making previews', value=False, elem_id="train_preview_from_txt2img")
-                    with gr.Row():
-                        shuffle_tags = gr.Checkbox(label="Shuffle tags by ',' when creating prompts.", value=False, elem_id="train_shuffle_tags")
-                        tag_drop_out = gr.Slider(minimum=0, maximum=1, step=0.1, label="Drop out tags when creating prompts.", value=0, elem_id="train_tag_drop_out")
-                    with gr.Row():
-                        latent_sampling_method = gr.Radio(label='Choose latent sampling method', value="once", choices=['once', 'deterministic', 'random'], elem_id="train_latent_sampling_method")
+
+                    shuffle_tags = gr.Checkbox(label="Shuffle tags by ',' when creating prompts.", value=False, elem_id="train_shuffle_tags")
+                    tag_drop_out = gr.Slider(minimum=0, maximum=1, step=0.1, label="Drop out tags when creating prompts.", value=0, elem_id="train_tag_drop_out")
+
+                    latent_sampling_method = gr.Radio(label='Choose latent sampling method', value="once", choices=['once', 'deterministic', 'random'], elem_id="train_latent_sampling_method")
 
                     with gr.Row():
+                        train_embedding = gr.Button(value="Train Embedding", variant='primary', elem_id="train_train_embedding")
                         interrupt_training = gr.Button(value="Interrupt", elem_id="train_interrupt_training")
                         train_hypernetwork = gr.Button(value="Train Hypernetwork", variant='primary', elem_id="train_train_hypernetwork")
-                        train_embedding = gr.Button(value="Train Embedding", variant='primary', elem_id="train_train_embedding")
 
                 params = script_callbacks.UiTrainTabParams(txt2img_preview_params)
 
@@ -1803,6 +1809,7 @@ def create_ui():
     visit(img2img_interface, loadsave, "img2img")
     visit(extras_interface, loadsave, "extras")
     visit(modelmerger_interface, loadsave, "modelmerger")
+    visit(train_interface, loadsave, "train")
 
     if not error_loading and (not os.path.exists(ui_config_file) or settings_count != len(ui_settings)):
         with open(ui_config_file, "w", encoding="utf8") as file:
diff --git a/style.css b/style.css
index 2116ec3c..09ee540b 100644
--- a/style.css
+++ b/style.css
@@ -611,7 +611,7 @@ img2maskimg, #img2maskimg > .h-60, #img2maskimg > .h-60 > div, #img2maskimg > .h
     padding-top: 0.9em;
 }
 
-#img2img_settings div.gr-form .gr-form, #txt2img_settings div.gr-form .gr-form{
+#img2img_settings div.gr-form .gr-form, #txt2img_settings div.gr-form .gr-form, #train_tabs div.gr-form .gr-form{
     border: none;
     padding-bottom: 0.5em;
 }
-- 
cgit v1.2.3


From 81490780949fffed77493b4bd741e96ec737fe27 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 4 Jan 2023 22:04:40 +0300
Subject: added the option to specify target resolution with possibility of
 truncating for hires fix; also sampling steps

---
 javascript/hints.js                        | 11 ++++---
 modules/generation_parameters_copypaste.py |  9 ++++--
 modules/processing.py                      | 51 +++++++++++++++++++++++++++---
 modules/txt2img.py                         |  5 ++-
 modules/ui.py                              | 24 ++++++++++----
 5 files changed, 81 insertions(+), 19 deletions(-)

(limited to 'modules/ui.py')

diff --git a/javascript/hints.js b/javascript/hints.js
index 63e17e05..dda66e09 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -81,9 +81,6 @@ titles = {
 
     "vram": "Torch active: Peak amount of VRAM used by Torch during generation, excluding cached data.\nTorch reserved: Peak amount of VRAM allocated by Torch, including all active and cached data.\nSys VRAM: Peak amount of VRAM allocation across all applications / total GPU VRAM (peak utilization%).",
 
-    "Highres. fix": "Use a two step process to partially create an image at smaller resolution, upscale, and then improve details in it without changing composition",
-    "Scale latent": "Uscale the image in latent space. Alternative is to produce the full image from latent representation, upscale that, and then move it back to latent space.",
-
     "Eta noise seed delta": "If this values is non-zero, it will be added to seed and used to initialize RNG for noises when using samplers with Eta. You can use this to produce even more variation of images, or you can use this to match images of other software if you know what you are doing.",
     "Do not add watermark to images": "If this option is enabled, watermark will not be added to created images. Warning: if you do not add watermark, you may be behaving in an unethical manner.",
 
@@ -100,7 +97,13 @@ titles = {
     "Clip skip": "Early stopping parameter for CLIP model; 1 is stop at last layer as usual, 2 is stop at penultimate layer, etc.",
 
     "Approx NN": "Cheap neural network approximation. Very fast compared to VAE, but produces pictures with 4 times smaller horizontal/vertical resoluton and lower quality.",
-    "Approx cheap": "Very cheap approximation. Very fast compared to VAE, but produces pictures with 8 times smaller horizontal/vertical resoluton and extremely low quality."
+    "Approx cheap": "Very cheap approximation. Very fast compared to VAE, but produces pictures with 8 times smaller horizontal/vertical resoluton and extremely low quality.",
+
+    "Hires. fix": "Use a two step process to partially create an image at smaller resolution, upscale, and then improve details in it without changing composition",
+    "Hires steps": "Number of sampling steps for upscaled picture. If 0, uses same as for original.",
+    "Upscale by": "Adjusts the size of the image by multiplying the original width and height by the selected value. Ignored if either Resize width to or Resize height to are non-zero.",
+    "Resize width to": "Resizes image to this width. If 0, width is inferred from either of two nearby sliders.",
+    "Resize height to": "Resizes image to this height. If 0, height is inferred from either of two nearby sliders."
 }
 
 
diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py
index 4baf4d9a..12a9de3d 100644
--- a/modules/generation_parameters_copypaste.py
+++ b/modules/generation_parameters_copypaste.py
@@ -212,11 +212,10 @@ def restore_old_hires_fix_params(res):
         firstpass_width = math.ceil(scale * width / 64) * 64
         firstpass_height = math.ceil(scale * height / 64) * 64
 
-    hr_scale = width / firstpass_width if firstpass_width > 0 else height / firstpass_height
-
     res['Size-1'] = firstpass_width
     res['Size-2'] = firstpass_height
-    res['Hires upscale'] = hr_scale
+    res['Hires resize-1'] = width
+    res['Hires resize-2'] = height
 
 
 def parse_generation_parameters(x: str):
@@ -276,6 +275,10 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
         hypernet_hash = res.get("Hypernet hash", None)
         res["Hypernet"] = find_hypernetwork_key(hypernet_name, hypernet_hash)
 
+    if "Hires resize-1" not in res:
+        res["Hires resize-1"] = 0
+        res["Hires resize-2"] = 0
+
     restore_old_hires_fix_params(res)
 
     return res
diff --git a/modules/processing.py b/modules/processing.py
index 47712159..9cad05f2 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -662,12 +662,17 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
 class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
     sampler = None
 
-    def __init__(self, enable_hr: bool = False, denoising_strength: float = 0.75, firstphase_width: int = 0, firstphase_height: int = 0, hr_scale: float = 2.0, hr_upscaler: str = None, **kwargs):
+    def __init__(self, enable_hr: bool = False, denoising_strength: float = 0.75, firstphase_width: int = 0, firstphase_height: int = 0, hr_scale: float = 2.0, hr_upscaler: str = None, hr_second_pass_steps: int = 0, hr_resize_x: int = 0, hr_resize_y: int = 0, **kwargs):
         super().__init__(**kwargs)
         self.enable_hr = enable_hr
         self.denoising_strength = denoising_strength
         self.hr_scale = hr_scale
         self.hr_upscaler = hr_upscaler
+        self.hr_second_pass_steps = hr_second_pass_steps
+        self.hr_resize_x = hr_resize_x
+        self.hr_resize_y = hr_resize_y
+        self.hr_upscale_to_x = hr_resize_x
+        self.hr_upscale_to_y = hr_resize_y
 
         if firstphase_width != 0 or firstphase_height != 0:
             print("firstphase_width/firstphase_height no longer supported; use hr_scale", file=sys.stderr)
@@ -675,6 +680,9 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
             self.width = firstphase_width
             self.height = firstphase_height
 
+        self.truncate_x = 0
+        self.truncate_y = 0
+
     def init(self, all_prompts, all_seeds, all_subseeds):
         if self.enable_hr:
             if state.job_count == -1:
@@ -682,7 +690,38 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
             else:
                 state.job_count = state.job_count * 2
 
-            self.extra_generation_params["Hires upscale"] = self.hr_scale
+            if self.hr_resize_x == 0 and self.hr_resize_y == 0:
+                self.extra_generation_params["Hires upscale"] = self.hr_scale
+                self.hr_upscale_to_x = int(self.width * self.hr_scale)
+                self.hr_upscale_to_y = int(self.height * self.hr_scale)
+            else:
+                self.extra_generation_params["Hires resize"] = f"{self.hr_resize_x}x{self.hr_resize_y}"
+
+                if self.hr_resize_y == 0:
+                    self.hr_upscale_to_x = self.hr_resize_x
+                    self.hr_upscale_to_y = self.hr_resize_x * self.height // self.width
+                elif self.hr_resize_x == 0:
+                    self.hr_upscale_to_x = self.hr_resize_y * self.width // self.height
+                    self.hr_upscale_to_y = self.hr_resize_y
+                else:
+                    target_w = self.hr_resize_x
+                    target_h = self.hr_resize_y
+                    src_ratio = self.width / self.height
+                    dst_ratio = self.hr_resize_x / self.hr_resize_y
+
+                    if src_ratio < dst_ratio:
+                        self.hr_upscale_to_x = self.hr_resize_x
+                        self.hr_upscale_to_y = self.hr_resize_x * self.height // self.width
+                    else:
+                        self.hr_upscale_to_x = self.hr_resize_y * self.width // self.height
+                        self.hr_upscale_to_y = self.hr_resize_y
+
+                    self.truncate_x = (self.hr_upscale_to_x - target_w) // opt_f
+                    self.truncate_y = (self.hr_upscale_to_y - target_h) // opt_f
+
+            if self.hr_second_pass_steps:
+                self.extra_generation_params["Hires steps"] = self.hr_second_pass_steps
+
             if self.hr_upscaler is not None:
                 self.extra_generation_params["Hires upscaler"] = self.hr_upscaler
 
@@ -699,8 +738,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
         if not self.enable_hr:
             return samples
 
-        target_width = int(self.width * self.hr_scale)
-        target_height = int(self.height * self.hr_scale)
+        target_width = self.hr_upscale_to_x
+        target_height = self.hr_upscale_to_y
 
         def save_intermediate(image, index):
             """saves image before applying hires fix, if enabled in options; takes as an argument either an image or batch with latent space images"""
@@ -755,13 +794,15 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
 
         self.sampler = sd_samplers.create_sampler(self.sampler_name, self.sd_model)
 
+        samples = samples[:, :, self.truncate_y//2:samples.shape[2]-(self.truncate_y+1)//2, self.truncate_x//2:samples.shape[3]-(self.truncate_x+1)//2]
+
         noise = create_random_tensors(samples.shape[1:], seeds=seeds, subseeds=subseeds, subseed_strength=subseed_strength, p=self)
 
         # GC now before running the next img2img to prevent running out of memory
         x = None
         devices.torch_gc()
 
-        samples = self.sampler.sample_img2img(self, samples, noise, conditioning, unconditional_conditioning, steps=self.steps, image_conditioning=image_conditioning)
+        samples = self.sampler.sample_img2img(self, samples, noise, conditioning, unconditional_conditioning, steps=self.hr_second_pass_steps or self.steps, image_conditioning=image_conditioning)
 
         return samples
 
diff --git a/modules/txt2img.py b/modules/txt2img.py
index e189a899..38b5f591 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -8,7 +8,7 @@ import modules.processing as processing
 from modules.ui import plaintext_to_html
 
 
-def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, *args):
+def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, *args):
     p = StableDiffusionProcessingTxt2Img(
         sd_model=shared.sd_model,
         outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples,
@@ -35,6 +35,9 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2:
         denoising_strength=denoising_strength if enable_hr else None,
         hr_scale=hr_scale,
         hr_upscaler=hr_upscaler,
+        hr_second_pass_steps=hr_second_pass_steps,
+        hr_resize_x=hr_resize_x,
+        hr_resize_y=hr_resize_y,
     )
 
     p.scripts = modules.scripts.scripts_txt2img
diff --git a/modules/ui.py b/modules/ui.py
index 44f4f3a4..04091e67 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -637,10 +637,10 @@ def create_sampler_and_steps_selection(choices, tabname):
         with FormRow(elem_id=f"sampler_selection_{tabname}"):
             sampler_index = gr.Dropdown(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")
             sampler_index.save_to_config = True
-            steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling Steps", value=20)
+            steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling steps", value=20)
     else:
         with FormGroup(elem_id=f"sampler_selection_{tabname}"):
-            steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling Steps", value=20)
+            steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling steps", value=20)
             sampler_index = gr.Radio(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")
 
     return steps, sampler_index
@@ -709,10 +709,16 @@ def create_ui():
                             enable_hr = gr.Checkbox(label='Hires. fix', value=False, elem_id="txt2img_enable_hr")
 
                     elif category == "hires_fix":
-                        with FormRow(visible=False, elem_id="txt2img_hires_fix") as hr_options:
-                            hr_upscaler = gr.Dropdown(label="Upscaler", elem_id="txt2img_hr_upscaler", choices=[*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]], value=shared.latent_upscale_default_mode)
-                            hr_scale = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Upscale by", value=2.0, elem_id="txt2img_hr_scale")
-                            denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7, elem_id="txt2img_denoising_strength")
+                        with FormGroup(visible=False, elem_id="txt2img_hires_fix") as hr_options:
+                            with FormRow(elem_id="txt2img_hires_fix_row1"):
+                                hr_upscaler = gr.Dropdown(label="Upscaler", elem_id="txt2img_hr_upscaler", choices=[*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]], value=shared.latent_upscale_default_mode)
+                                hr_second_pass_steps = gr.Slider(minimum=0, maximum=150, step=1, label='Hires steps', value=0, elem_id="txt2img_hires_steps")
+                                denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7, elem_id="txt2img_denoising_strength")
+
+                            with FormRow(elem_id="txt2img_hires_fix_row2"):
+                                hr_scale = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Upscale by", value=2.0, elem_id="txt2img_hr_scale")
+                                hr_resize_x = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize width to", value=0, elem_id="txt2img_hr_resize_x")
+                                hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y")
 
                     elif category == "batch":
                         if not opts.dimensions_and_batch_together:
@@ -753,6 +759,9 @@ def create_ui():
                     denoising_strength,
                     hr_scale,
                     hr_upscaler,
+                    hr_second_pass_steps,
+                    hr_resize_x,
+                    hr_resize_y,
                 ] + custom_inputs,
 
                 outputs=[
@@ -804,6 +813,9 @@ def create_ui():
                 (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)),
                 (hr_scale, "Hires upscale"),
                 (hr_upscaler, "Hires upscaler"),
+                (hr_second_pass_steps, "Hires steps"),
+                (hr_resize_x, "Hires resize-1"),
+                (hr_resize_y, "Hires resize-2"),
                 *modules.scripts.scripts_txt2img.infotext_fields
             ]
             parameters_copypaste.add_paste_fields("txt2img", None, txt2img_paste_fields)
-- 
cgit v1.2.3


From 5851bc839b6f639cda59e84eb1ee8c706986633d Mon Sep 17 00:00:00 2001
From: me <25877290+Kryptortio@users.noreply.github.com>
Date: Wed, 4 Jan 2023 22:03:32 +0100
Subject: Add element ids for script components and a few more in ui.py

---
 modules/ui.py                    | 16 ++++++++--------
 scripts/custom_code.py           |  4 +++-
 scripts/img2imgalt.py            | 22 ++++++++++++----------
 scripts/loopback.py              |  6 ++++--
 scripts/outpainting_mk_2.py      | 12 +++++++-----
 scripts/poor_mans_outpainting.py | 10 ++++++----
 scripts/prompt_matrix.py         |  6 ++++--
 scripts/prompts_from_file.py     | 10 ++++++----
 scripts/sd_upscale.py            |  8 +++++---
 scripts/xy_grid.py               | 15 ++++++++-------
 10 files changed, 63 insertions(+), 46 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index 04091e67..bb64fe20 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -560,7 +560,7 @@ Requested path was: {f}
             generation_info = None
             with gr.Column():
                 with gr.Row(elem_id=f"image_buttons_{tabname}"):
-                    open_folder_button = gr.Button(folder_symbol, elem_id="hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder')
+                    open_folder_button = gr.Button(folder_symbol, elem_id="hidden_element" if shared.cmd_opts.hide_ui_dir_config else f'open_folder_{tabname}')
 
                     if tabname != "extras":
                         save = gr.Button('Save', elem_id=f'save_{tabname}')
@@ -576,13 +576,13 @@ Requested path was: {f}
 
                 if tabname != "extras":
                     with gr.Row():
-                        download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
+                        download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False, elem_id=f'download_files_{tabname}')
 
                     with gr.Group():
-                        html_info = gr.HTML()
-                        html_log = gr.HTML()
+                        html_info = gr.HTML(elem_id=f'html_info_{tabname}')
+                        html_log = gr.HTML(elem_id=f'html_log_{tabname}')
 
-                        generation_info = gr.Textbox(visible=False)
+                        generation_info = gr.Textbox(visible=False, elem_id=f'generation_info_{tabname}')
                         if tabname == 'txt2img' or tabname == 'img2img':
                             generation_info_button = gr.Button(visible=False, elem_id=f"{tabname}_generation_info_button")
                             generation_info_button.click(
@@ -624,9 +624,9 @@ Requested path was: {f}
                         )
 
                 else:
-                    html_info_x = gr.HTML()
-                    html_info = gr.HTML()
-                    html_log = gr.HTML()
+                    html_info_x = gr.HTML(elem_id=f'html_info_x_{tabname}')
+                    html_info = gr.HTML(elem_id=f'html_info_{tabname}')
+                    html_log = gr.HTML(elem_id=f'html_log_{tabname}')
 
                 parameters_copypaste.bind_buttons(buttons, result_gallery, "txt2img" if tabname == "txt2img" else None)
                 return result_gallery, generation_info if tabname != "extras" else html_info_x, html_info, html_log
diff --git a/scripts/custom_code.py b/scripts/custom_code.py
index 22e7b77a..841fed97 100644
--- a/scripts/custom_code.py
+++ b/scripts/custom_code.py
@@ -14,7 +14,9 @@ class Script(scripts.Script):
         return cmd_opts.allow_code
 
     def ui(self, is_img2img):
-        code = gr.Textbox(label="Python code", lines=1)
+        elem_prefix = ('i2i' if is_img2img else 't2i') + '_script_custom_code_'
+        
+        code = gr.Textbox(label="Python code", lines=1, elem_id=elem_prefix + "code")
 
         return [code]
 
diff --git a/scripts/img2imgalt.py b/scripts/img2imgalt.py
index 1229f61b..cddd46e7 100644
--- a/scripts/img2imgalt.py
+++ b/scripts/img2imgalt.py
@@ -126,24 +126,26 @@ class Script(scripts.Script):
         return is_img2img
 
     def ui(self, is_img2img):
+        elem_prefix = ('i2i' if is_img2img else 't2i') + '_script_i2i_alternative_test_'
+        
         info = gr.Markdown('''
         * `CFG Scale` should be 2 or lower.
         ''')
 
-        override_sampler = gr.Checkbox(label="Override `Sampling method` to Euler?(this method is built for it)", value=True)
+        override_sampler = gr.Checkbox(label="Override `Sampling method` to Euler?(this method is built for it)", value=True, elem_id=elem_prefix + "override_sampler")
 
-        override_prompt = gr.Checkbox(label="Override `prompt` to the same value as `original prompt`?(and `negative prompt`)", value=True)
-        original_prompt = gr.Textbox(label="Original prompt", lines=1)
-        original_negative_prompt = gr.Textbox(label="Original negative prompt", lines=1)
+        override_prompt = gr.Checkbox(label="Override `prompt` to the same value as `original prompt`?(and `negative prompt`)", value=True, elem_id=elem_prefix + "override_prompt")
+        original_prompt = gr.Textbox(label="Original prompt", lines=1, elem_id=elem_prefix + "original_prompt")
+        original_negative_prompt = gr.Textbox(label="Original negative prompt", lines=1, elem_id=elem_prefix + "original_negative_prompt")
 
-        override_steps = gr.Checkbox(label="Override `Sampling Steps` to the same value as `Decode steps`?", value=True)
-        st = gr.Slider(label="Decode steps", minimum=1, maximum=150, step=1, value=50)
+        override_steps = gr.Checkbox(label="Override `Sampling Steps` to the same value as `Decode steps`?", value=True, elem_id=elem_prefix + "override_steps")
+        st = gr.Slider(label="Decode steps", minimum=1, maximum=150, step=1, value=50, elem_id=elem_prefix + "st")
 
-        override_strength = gr.Checkbox(label="Override `Denoising strength` to 1?", value=True)
+        override_strength = gr.Checkbox(label="Override `Denoising strength` to 1?", value=True, elem_id=elem_prefix + "override_strength")
 
-        cfg = gr.Slider(label="Decode CFG scale", minimum=0.0, maximum=15.0, step=0.1, value=1.0)
-        randomness = gr.Slider(label="Randomness", minimum=0.0, maximum=1.0, step=0.01, value=0.0)
-        sigma_adjustment = gr.Checkbox(label="Sigma adjustment for finding noise for image", value=False)
+        cfg = gr.Slider(label="Decode CFG scale", minimum=0.0, maximum=15.0, step=0.1, value=1.0, elem_id=elem_prefix + "cfg")
+        randomness = gr.Slider(label="Randomness", minimum=0.0, maximum=1.0, step=0.01, value=0.0, elem_id=elem_prefix + "randomness")
+        sigma_adjustment = gr.Checkbox(label="Sigma adjustment for finding noise for image", value=False, elem_id=elem_prefix + "sigma_adjustment")
 
         return [
             info, 
diff --git a/scripts/loopback.py b/scripts/loopback.py
index d8c68af8..5c1265a0 100644
--- a/scripts/loopback.py
+++ b/scripts/loopback.py
@@ -17,8 +17,10 @@ class Script(scripts.Script):
         return is_img2img
 
     def ui(self, is_img2img):
-        loops = gr.Slider(minimum=1, maximum=32, step=1, label='Loops', value=4)
-        denoising_strength_change_factor = gr.Slider(minimum=0.9, maximum=1.1, step=0.01, label='Denoising strength change factor', value=1)
+        elem_prefix = ('i2i' if is_img2img else 't2i') + '_script_loopback_'
+        
+        loops = gr.Slider(minimum=1, maximum=32, step=1, label='Loops', value=4, elem_id=elem_prefix + "loops")
+        denoising_strength_change_factor = gr.Slider(minimum=0.9, maximum=1.1, step=0.01, label='Denoising strength change factor', value=1, elem_id=elem_prefix + "denoising_strength_change_factor")
 
         return [loops, denoising_strength_change_factor]
 
diff --git a/scripts/outpainting_mk_2.py b/scripts/outpainting_mk_2.py
index cf71cb92..760cce64 100644
--- a/scripts/outpainting_mk_2.py
+++ b/scripts/outpainting_mk_2.py
@@ -129,13 +129,15 @@ class Script(scripts.Script):
         if not is_img2img:
             return None
 
+        elem_prefix = ('i2i' if is_img2img else 't2i') + '_script_outpainting_mk_2_'
+        
         info = gr.HTML("<p style=\"margin-bottom:0.75em\">Recommended settings: Sampling Steps: 80-100, Sampler: Euler a, Denoising strength: 0.8</p>")
 
-        pixels = gr.Slider(label="Pixels to expand", minimum=8, maximum=256, step=8, value=128)
-        mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=8)
-        direction = gr.CheckboxGroup(label="Outpainting direction", choices=['left', 'right', 'up', 'down'], value=['left', 'right', 'up', 'down'])
-        noise_q = gr.Slider(label="Fall-off exponent (lower=higher detail)", minimum=0.0, maximum=4.0, step=0.01, value=1.0)
-        color_variation = gr.Slider(label="Color variation", minimum=0.0, maximum=1.0, step=0.01, value=0.05)
+        pixels = gr.Slider(label="Pixels to expand", minimum=8, maximum=256, step=8, value=128, elem_id=elem_prefix + "pixels")
+        mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=8, elem_id=elem_prefix + "mask_blur")
+        direction = gr.CheckboxGroup(label="Outpainting direction", choices=['left', 'right', 'up', 'down'], value=['left', 'right', 'up', 'down'], elem_id=elem_prefix + "direction")
+        noise_q = gr.Slider(label="Fall-off exponent (lower=higher detail)", minimum=0.0, maximum=4.0, step=0.01, value=1.0, elem_id=elem_prefix + "noise_q")
+        color_variation = gr.Slider(label="Color variation", minimum=0.0, maximum=1.0, step=0.01, value=0.05, elem_id=elem_prefix + "color_variation")
 
         return [info, pixels, mask_blur, direction, noise_q, color_variation]
 
diff --git a/scripts/poor_mans_outpainting.py b/scripts/poor_mans_outpainting.py
index ea45beb0..6bcdcc02 100644
--- a/scripts/poor_mans_outpainting.py
+++ b/scripts/poor_mans_outpainting.py
@@ -21,10 +21,12 @@ class Script(scripts.Script):
         if not is_img2img:
             return None
 
-        pixels = gr.Slider(label="Pixels to expand", minimum=8, maximum=256, step=8, value=128)
-        mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4)
-        inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='fill', type="index")
-        direction = gr.CheckboxGroup(label="Outpainting direction", choices=['left', 'right', 'up', 'down'], value=['left', 'right', 'up', 'down'])
+        elem_prefix = ('i2i' if is_img2img else 't2i') + '_script_poor_mans_outpainting_'
+        
+        pixels = gr.Slider(label="Pixels to expand", minimum=8, maximum=256, step=8, value=128, elem_id=elem_prefix + "pixels")
+        mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id=elem_prefix + "mask_blur")
+        inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='fill', type="index", elem_id=elem_prefix + "inpainting_fill")
+        direction = gr.CheckboxGroup(label="Outpainting direction", choices=['left', 'right', 'up', 'down'], value=['left', 'right', 'up', 'down'], elem_id=elem_prefix + "direction")
 
         return [pixels, mask_blur, inpainting_fill, direction]
 
diff --git a/scripts/prompt_matrix.py b/scripts/prompt_matrix.py
index 4c79eaef..59172315 100644
--- a/scripts/prompt_matrix.py
+++ b/scripts/prompt_matrix.py
@@ -45,8 +45,10 @@ class Script(scripts.Script):
         return "Prompt matrix"
 
     def ui(self, is_img2img):
-        put_at_start = gr.Checkbox(label='Put variable parts at start of prompt', value=False)
-        different_seeds = gr.Checkbox(label='Use different seed for each picture', value=False)
+        elem_prefix = ('i2i' if is_img2img else 't2i') + '_script_prompt_matrix_'
+        
+        put_at_start = gr.Checkbox(label='Put variable parts at start of prompt', value=False, elem_id=elem_prefix + "put_at_start")
+        different_seeds = gr.Checkbox(label='Use different seed for each picture', value=False, elem_id=elem_prefix + "different_seeds")
 
         return [put_at_start, different_seeds]
 
diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py
index e8386ed2..fc8ddd8a 100644
--- a/scripts/prompts_from_file.py
+++ b/scripts/prompts_from_file.py
@@ -112,11 +112,13 @@ class Script(scripts.Script):
         return "Prompts from file or textbox"
 
     def ui(self, is_img2img):
-        checkbox_iterate = gr.Checkbox(label="Iterate seed every line", value=False)
-        checkbox_iterate_batch = gr.Checkbox(label="Use same random seed for all lines", value=False)
+        elem_prefix = ('i2i' if is_img2img else 't2i') + '_script_prompt_from_file_'
+        
+        checkbox_iterate = gr.Checkbox(label="Iterate seed every line", value=False, elem_id=elem_prefix + "checkbox_iterate")
+        checkbox_iterate_batch = gr.Checkbox(label="Use same random seed for all lines", value=False, elem_id=elem_prefix + "checkbox_iterate_batch")
 
-        prompt_txt = gr.Textbox(label="List of prompt inputs", lines=1)
-        file = gr.File(label="Upload prompt inputs", type='bytes')
+        prompt_txt = gr.Textbox(label="List of prompt inputs", lines=1, elem_id=elem_prefix + "prompt_txt")
+        file = gr.File(label="Upload prompt inputs", type='bytes', elem_id=elem_prefix + "file")
 
         file.change(fn=load_prompt_file, inputs=[file], outputs=[file, prompt_txt, prompt_txt])
 
diff --git a/scripts/sd_upscale.py b/scripts/sd_upscale.py
index 9739545c..9f483a67 100644
--- a/scripts/sd_upscale.py
+++ b/scripts/sd_upscale.py
@@ -17,10 +17,12 @@ class Script(scripts.Script):
         return is_img2img
 
     def ui(self, is_img2img):
+        elem_prefix = ('i2i' if is_img2img else 't2i') + '_script_sd_upscale_'
+        
         info = gr.HTML("<p style=\"margin-bottom:0.75em\">Will upscale the image by the selected scale factor; use width and height sliders to set tile size</p>")
-        overlap = gr.Slider(minimum=0, maximum=256, step=16, label='Tile overlap', value=64)
-        scale_factor = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label='Scale Factor', value=2.0)
-        upscaler_index = gr.Radio(label='Upscaler', choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
+        overlap = gr.Slider(minimum=0, maximum=256, step=16, label='Tile overlap', value=64, elem_id=elem_prefix + "overlap")
+        scale_factor = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label='Scale Factor', value=2.0, elem_id=elem_prefix + "scale_factor")
+        upscaler_index = gr.Radio(label='Upscaler', choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index", elem_id=elem_prefix + "upscaler_index")
 
         return [info, overlap, upscaler_index, scale_factor]
 
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 78ff12c5..90226ccd 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -292,18 +292,19 @@ class Script(scripts.Script):
 
     def ui(self, is_img2img):
         current_axis_options = [x for x in axis_options if type(x) == AxisOption or type(x) == AxisOptionImg2Img and is_img2img]
+        elem_prefix = ('i2i' if is_img2img else 't2i') + '_script_xy_grid_'
 
         with gr.Row():
-            x_type = gr.Dropdown(label="X type", choices=[x.label for x in current_axis_options], value=current_axis_options[1].label, type="index", elem_id="x_type")
-            x_values = gr.Textbox(label="X values", lines=1)
+            x_type = gr.Dropdown(label="X type", choices=[x.label for x in current_axis_options], value=current_axis_options[1].label, type="index", elem_id=elem_prefix + "x_type")
+            x_values = gr.Textbox(label="X values", lines=1, elem_id=elem_prefix + "x_values")
 
         with gr.Row():
-            y_type = gr.Dropdown(label="Y type", choices=[x.label for x in current_axis_options], value=current_axis_options[0].label, type="index", elem_id="y_type")
-            y_values = gr.Textbox(label="Y values", lines=1)
+            y_type = gr.Dropdown(label="Y type", choices=[x.label for x in current_axis_options], value=current_axis_options[0].label, type="index", elem_id=elem_prefix + "y_type")
+            y_values = gr.Textbox(label="Y values", lines=1, elem_id=elem_prefix + "y_values")
         
-        draw_legend = gr.Checkbox(label='Draw legend', value=True)
-        include_lone_images = gr.Checkbox(label='Include Separate Images', value=False)
-        no_fixed_seeds = gr.Checkbox(label='Keep -1 for seeds', value=False)
+        draw_legend = gr.Checkbox(label='Draw legend', value=True, elem_id=elem_prefix + "draw_legend")
+        include_lone_images = gr.Checkbox(label='Include Separate Images', value=False, elem_id=elem_prefix + "include_lone_images")
+        no_fixed_seeds = gr.Checkbox(label='Keep -1 for seeds', value=False, elem_id=elem_prefix + "no_fixed_seeds")
 
         return [x_type, x_values, y_type, y_values, draw_legend, include_lone_images, no_fixed_seeds]
 
-- 
cgit v1.2.3


From 997461d3dd86f51c06ea0c2eff17ce8b8b48c0af Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 5 Jan 2023 11:57:01 +0300
Subject: add footer with versions

---
 html/footer.html |  4 ++++
 launch.py        | 20 ++++++++++++++++----
 modules/ui.py    | 31 ++++++++++++++++++++++++++++++-
 style.css        |  5 +++++
 4 files changed, 55 insertions(+), 5 deletions(-)

(limited to 'modules/ui.py')

diff --git a/html/footer.html b/html/footer.html
index a8f2adf7..bad87ff6 100644
--- a/html/footer.html
+++ b/html/footer.html
@@ -7,3 +7,7 @@
          • 
         <a href="/" onclick="javascript:gradioApp().getElementById('settings_restart_gradio').click(); return false">Reload UI</a>
 </div>
+<br />
+<div class="versions">
+{versions}
+</div>
diff --git a/launch.py b/launch.py
index af0d418b..49b91b1f 100644
--- a/launch.py
+++ b/launch.py
@@ -13,6 +13,21 @@ dir_extensions = "extensions"
 python = sys.executable
 git = os.environ.get('GIT', "git")
 index_url = os.environ.get('INDEX_URL', "")
+stored_commit_hash = None
+
+
+def commit_hash():
+    global stored_commit_hash
+
+    if stored_commit_hash is not None:
+        return stored_commit_hash
+
+    try:
+        stored_commit_hash = run(f"{git} rev-parse HEAD").strip()
+    except Exception:
+        stored_commit_hash = "<none>"
+
+    return stored_commit_hash
 
 
 def extract_arg(args, name):
@@ -194,10 +209,7 @@ def prepare_environment():
     xformers = '--xformers' in sys.argv
     ngrok = '--ngrok' in sys.argv
 
-    try:
-        commit = run(f"{git} rev-parse HEAD").strip()
-    except Exception:
-        commit = "<none>"
+    commit = commit_hash()
 
     print(f"Python {sys.version}")
     print(f"Commit hash: {commit}")
diff --git a/modules/ui.py b/modules/ui.py
index bb64fe20..81d96c5b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1696,7 +1696,9 @@ def create_ui():
 
         if os.path.exists("html/footer.html"):
             with open("html/footer.html", encoding="utf8") as file:
-                gr.HTML(file.read(), elem_id="footer")
+                footer = file.read()
+                footer = footer.format(versions=versions_html())
+                gr.HTML(footer, elem_id="footer")
 
         text_settings = gr.Textbox(elem_id="settings_json", value=lambda: opts.dumpjson(), visible=False)
         settings_submit.click(
@@ -1857,3 +1859,30 @@ def reload_javascript():
 
 if not hasattr(shared, 'GradioTemplateResponseOriginal'):
     shared.GradioTemplateResponseOriginal = gradio.routes.templates.TemplateResponse
+
+
+def versions_html():
+    import torch
+    import launch
+
+    python_version = ".".join([str(x) for x in sys.version_info[0:3]])
+    commit = launch.commit_hash()
+    short_commit = commit[0:8]
+
+    if shared.xformers_available:
+        import xformers
+        xformers_version = xformers.__version__
+    else:
+        xformers_version = "N/A"
+
+    return f"""
+python: <span title="{sys.version}">{python_version}</span>
+ • 
+torch: {torch.__version__}
+ • 
+xformers: {xformers_version}
+ • 
+gradio: {gr.__version__}
+ • 
+commit: <a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui/commit/{commit}">{short_commit}</a>
+"""
diff --git a/style.css b/style.css
index 09ee540b..ee74d79e 100644
--- a/style.css
+++ b/style.css
@@ -628,6 +628,11 @@ footer {
     display: inline-block;
 }
 
+#footer .versions{
+    font-size: 85%;
+    opacity: 0.85;
+}
+
 /* The following handles localization for right-to-left (RTL) languages like Arabic.
 The rtl media type will only be activated by the logic in javascript/localization.js.
 If you change anything above, you need to make sure it is RTL compliant by just running
-- 
cgit v1.2.3


From d61a5aa4f623f6630670241aca8fc5c2a6381769 Mon Sep 17 00:00:00 2001
From: acncagua <acncagua@gmail.com>
Date: Fri, 6 Jan 2023 10:58:22 +0900
Subject: Add files via upload

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

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index 81d96c5b..030f0685 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -550,6 +550,8 @@ Requested path was: {f}
                 os.startfile(path)
             elif platform.system() == "Darwin":
                 sp.Popen(["open", path])
+            elif "microsoft-standard-WSL2" in platform.uname().release:
+                sp.Popen(["wsl-open", path])
             else:
                 sp.Popen(["xdg-open", path])
 
-- 
cgit v1.2.3


From 3246a2d6b898da6a98fe9df4dc67944635a41bd3 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 6 Jan 2023 16:03:43 +0300
Subject: remove restriction for saving dropdowns to ui-config.json

---
 modules/scripts.py |  1 -
 modules/ui.py      | 10 ++--------
 2 files changed, 2 insertions(+), 9 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/scripts.py b/modules/scripts.py
index 0c44f191..35164093 100644
--- a/modules/scripts.py
+++ b/modules/scripts.py
@@ -290,7 +290,6 @@ class ScriptRunner:
             script.group = group
 
         dropdown = gr.Dropdown(label="Script", elem_id="script_list", choices=["None"] + self.titles, value="None", type="index")
-        dropdown.save_to_config = True
         inputs[0] = dropdown
 
         for script in self.selectable_scripts:
diff --git a/modules/ui.py b/modules/ui.py
index 030f0685..b79d24ee 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -435,11 +435,9 @@ def create_toprow(is_img2img):
             with gr.Row():
                 with gr.Column(scale=1, elem_id="style_pos_col"):
                     prompt_style = gr.Dropdown(label="Style 1", elem_id=f"{id_part}_style_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())))
-                    prompt_style.save_to_config = True
 
                 with gr.Column(scale=1, elem_id="style_neg_col"):
                     prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())))
-                    prompt_style2.save_to_config = True
 
     return prompt, prompt_style, negative_prompt, prompt_style2, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button
 
@@ -638,7 +636,6 @@ def create_sampler_and_steps_selection(choices, tabname):
     if opts.samplers_in_dropdown:
         with FormRow(elem_id=f"sampler_selection_{tabname}"):
             sampler_index = gr.Dropdown(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")
-            sampler_index.save_to_config = True
             steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling steps", value=20)
     else:
         with FormGroup(elem_id=f"sampler_selection_{tabname}"):
@@ -1794,7 +1791,7 @@ def create_ui():
                 if init_field is not None:
                     init_field(saved_value)
 
-        if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number] and x.visible:
+        if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number, gr.Dropdown] and x.visible:
             apply_field(x, 'visible')
 
         if type(x) == gr.Slider:
@@ -1815,11 +1812,8 @@ def create_ui():
         if type(x) == gr.Number:
             apply_field(x, 'value')
 
-        # Since there are many dropdowns that shouldn't be saved,
-        # we only mark dropdowns that should be saved.
-        if type(x) == gr.Dropdown and getattr(x, 'save_to_config', False):
+        if type(x) == gr.Dropdown:
             apply_field(x, 'value', lambda val: val in x.choices, getattr(x, 'init_field', None))
-            apply_field(x, 'visible')
 
     visit(txt2img_interface, loadsave, "txt2img")
     visit(img2img_interface, loadsave, "img2img")
-- 
cgit v1.2.3


From 3992ecbe6e46a465062508c677964534e7397f72 Mon Sep 17 00:00:00 2001
From: Mitchell Boot <47387831+Mitchell1711@users.noreply.github.com>
Date: Fri, 6 Jan 2023 18:02:46 +0100
Subject: Added UI elements

Added a new row to hires fix that shows the new resolution after scaling
---
 modules/ui.py | 12 ++++++++++++
 1 file changed, 12 insertions(+)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index b79d24ee..20f7d2a2 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -255,6 +255,12 @@ def add_style(name: str, prompt: str, negative_prompt: str):
 
     return [gr.Dropdown.update(visible=True, choices=list(shared.prompt_styles.styles)) for _ in range(4)]
 
+def calc_resolution_hires(x, y, scale):
+    #final res can only be a multiple of 8
+    scaled_x = int(x * scale // 8) * 8
+    scaled_y = int(y * scale // 8) * 8
+    
+    return "<p style='margin: -1em 0em 0.7em 1.35em'>Upscaled Resolution: "+str(scaled_x)+"x"+str(scaled_y)+"</p>"
 
 def apply_styles(prompt, prompt_neg, style1_name, style2_name):
     prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, [style1_name, style2_name])
@@ -718,6 +724,12 @@ def create_ui():
                                 hr_scale = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Upscale by", value=2.0, elem_id="txt2img_hr_scale")
                                 hr_resize_x = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize width to", value=0, elem_id="txt2img_hr_resize_x")
                                 hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y")
+                            
+                            with FormRow(elem_id="txt2img_hires_fix_row3"):        
+                                hr_final_resolution = gr.HTML(value=calc_resolution_hires(width.value, height.value, hr_scale.value), elem_id="txtimg_hr_finalres")
+                                hr_scale.change(fn=calc_resolution_hires, inputs=[width, height, hr_scale], outputs=hr_final_resolution, show_progress=False)
+                                width.change(fn=calc_resolution_hires, inputs=[width, height, hr_scale], outputs=hr_final_resolution, show_progress=False)
+                                height.change(fn=calc_resolution_hires, inputs=[width, height, hr_scale], outputs=hr_final_resolution, show_progress=False)
 
                     elif category == "batch":
                         if not opts.dimensions_and_batch_together:
-- 
cgit v1.2.3


From 991368c8d54404d8e13d4c6e76a0f32644e65ad4 Mon Sep 17 00:00:00 2001
From: Mitchell Boot <47387831+Mitchell1711@users.noreply.github.com>
Date: Fri, 6 Jan 2023 18:24:29 +0100
Subject: remove camelcase

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

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index 20f7d2a2..6fc8b7d7 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -260,7 +260,7 @@ def calc_resolution_hires(x, y, scale):
     scaled_x = int(x * scale // 8) * 8
     scaled_y = int(y * scale // 8) * 8
     
-    return "<p style='margin: -1em 0em 0.7em 1.35em'>Upscaled Resolution: "+str(scaled_x)+"x"+str(scaled_y)+"</p>"
+    return "<p style='margin: -1em 0em 0.7em 1.35em'>Upscaled resolution: "+str(scaled_x)+"x"+str(scaled_y)+"</p>"
 
 def apply_styles(prompt, prompt_neg, style1_name, style2_name):
     prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, [style1_name, style2_name])
-- 
cgit v1.2.3


From 79e39fae6110c20a3ee6255e2841c877f65e8cbd Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 7 Jan 2023 01:45:28 +0300
Subject: CLIP hijack rework

---
 modules/sd_hijack.py                           |   6 +-
 modules/sd_hijack_clip.py                      | 348 ++++++++++++-------------
 modules/sd_hijack_clip_old.py                  |  81 ++++++
 modules/textual_inversion/textual_inversion.py |   1 -
 modules/ui.py                                  |   2 +-
 5 files changed, 256 insertions(+), 182 deletions(-)
 create mode 100644 modules/sd_hijack_clip_old.py

(limited to 'modules/ui.py')

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index fa2cd4bb..71cc145a 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -150,10 +150,10 @@ class StableDiffusionModelHijack:
     def clear_comments(self):
         self.comments = []
 
-    def tokenize(self, text):
-        _, remade_batch_tokens, _, _, _, token_count = self.clip.process_text([text])
+    def get_prompt_lengths(self, text):
+        _, token_count = self.clip.process_texts([text])
 
-        return remade_batch_tokens[0], token_count, sd_hijack_clip.get_target_prompt_token_count(token_count)
+        return token_count, self.clip.get_target_prompt_token_count(token_count)
 
 
 class EmbeddingsWithFixes(torch.nn.Module):
diff --git a/modules/sd_hijack_clip.py b/modules/sd_hijack_clip.py
index ca92b142..ac3020d7 100644
--- a/modules/sd_hijack_clip.py
+++ b/modules/sd_hijack_clip.py
@@ -1,12 +1,28 @@
 import math
+from collections import namedtuple
 
 import torch
 
 from modules import prompt_parser, devices
 from modules.shared import opts
 
-def get_target_prompt_token_count(token_count):
-    return math.ceil(max(token_count, 1) / 75) * 75
+
+class PromptChunk:
+    """
+    This object contains token ids, weight (multipliers:1.4) and textual inversion embedding info for a chunk of prompt.
+    If a prompt is short, it is represented by one PromptChunk, otherwise, multiple are necessary.
+    Each PromptChunk contains an exact amount of tokens - 77, which includes one for start and end token,
+    so just 75 tokens from prompt.
+    """
+
+    def __init__(self):
+        self.tokens = []
+        self.multipliers = []
+        self.fixes = []
+
+
+PromptChunkFix = namedtuple('PromptChunkFix', ['offset', 'embedding'])
+"""This is a marker showing that textual inversion embedding's vectors have to placed at offset in the prompt chunk"""
 
 
 class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
@@ -14,17 +30,49 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
         super().__init__()
         self.wrapped = wrapped
         self.hijack = hijack
+        self.chunk_length = 75
+
+    def empty_chunk(self):
+        """creates an empty PromptChunk and returns it"""
+
+        chunk = PromptChunk()
+        chunk.tokens = [self.id_start] + [self.id_end] * (self.chunk_length + 1)
+        chunk.multipliers = [1.0] * (self.chunk_length + 2)
+        return chunk
+
+    def get_target_prompt_token_count(self, token_count):
+        """returns the maximum number of tokens a prompt of a known length can have before it requires one more PromptChunk to be represented"""
+
+        return math.ceil(max(token_count, 1) / self.chunk_length) * self.chunk_length
 
     def tokenize(self, texts):
+        """Converts a batch of texts into a batch of token ids"""
+
         raise NotImplementedError
 
     def encode_with_transformers(self, tokens):
+        """
+        converts a batch of token ids (in python lists) into a single tensor with numeric respresentation of those tokens;
+        All python lists with tokens are assumed to have same length, usually 77.
+        if input is a list with B elements and each element has T tokens, expected output shape is (B, T, C), where C depends on
+        model - can be 768 and 1024
+        """
+
         raise NotImplementedError
 
     def encode_embedding_init_text(self, init_text, nvpt):
+        """Converts text into a tensor with this text's tokens' embeddings. Note that those are embeddings before they are passed through
+        transformers. nvpt is used as a maximum length in tokens. If text produces less teokens than nvpt, only this many is returned."""
+
         raise NotImplementedError
 
-    def tokenize_line(self, line, used_custom_terms, hijack_comments):
+    def tokenize_line(self, line):
+        """
+        this transforms a single prompt into a list of PromptChunk objects - as many as needed to
+        represent the prompt.
+        Returns the list and the total number of tokens in the prompt.
+        """
+
         if opts.enable_emphasis:
             parsed = prompt_parser.parse_prompt_attention(line)
         else:
@@ -32,205 +80,152 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
 
         tokenized = self.tokenize([text for text, _ in parsed])
 
-        fixes = []
-        remade_tokens = []
-        multipliers = []
+        chunks = []
+        chunk = PromptChunk()
+        token_count = 0
         last_comma = -1
 
-        for tokens, (text, weight) in zip(tokenized, parsed):
-            i = 0
-            while i < len(tokens):
-                token = tokens[i]
+        def next_chunk():
+            """puts current chunk into the list of results and produces the next one - empty"""
+            nonlocal token_count
+            nonlocal last_comma
+            nonlocal chunk
+
+            token_count += len(chunk.tokens)
+            to_add = self.chunk_length - len(chunk.tokens)
+            if to_add > 0:
+                chunk.tokens += [self.id_end] * to_add
+                chunk.multipliers += [1.0] * to_add
 
-                embedding, embedding_length_in_tokens = self.hijack.embedding_db.find_embedding_at_position(tokens, i)
+            chunk.tokens = [self.id_start] + chunk.tokens + [self.id_end]
+            chunk.multipliers = [1.0] + chunk.multipliers + [1.0]
+
+            last_comma = -1
+            chunks.append(chunk)
+            chunk = PromptChunk()
+
+        for tokens, (text, weight) in zip(tokenized, parsed):
+            position = 0
+            while position < len(tokens):
+                token = tokens[position]
 
                 if token == self.comma_token:
-                    last_comma = len(remade_tokens)
-                elif opts.comma_padding_backtrack != 0 and max(len(remade_tokens), 1) % 75 == 0 and last_comma != -1 and len(remade_tokens) - last_comma <= opts.comma_padding_backtrack:
-                    last_comma += 1
-                    reloc_tokens = remade_tokens[last_comma:]
-                    reloc_mults = multipliers[last_comma:]
+                    last_comma = len(chunk.tokens)
+
+                # this is when we are at the end of alloted 75 tokens for the current chunk, and the current token is not a comma. opts.comma_padding_backtrack
+                # is a setting that specifies that is there is a comma nearby, the text after comma should be moved out of this chunk and into the next.
+                elif opts.comma_padding_backtrack != 0 and len(chunk.tokens) == self.chunk_length and last_comma != -1 and len(chunk.tokens) - last_comma <= opts.comma_padding_backtrack:
+                    break_location = last_comma + 1
+
+                    reloc_tokens = chunk.tokens[break_location:]
+                    reloc_mults = chunk.multipliers[break_location:]
 
-                    remade_tokens = remade_tokens[:last_comma]
-                    length = len(remade_tokens)
+                    chunk.tokens = chunk.tokens[:break_location]
+                    chunk.multipliers = chunk.multipliers[:break_location]
 
-                    rem = int(math.ceil(length / 75)) * 75 - length
-                    remade_tokens += [self.id_end] * rem + reloc_tokens
-                    multipliers = multipliers[:last_comma] + [1.0] * rem + reloc_mults
+                    next_chunk()
+                    chunk.tokens = reloc_tokens
+                    chunk.multipliers = reloc_mults
 
+                if len(chunk.tokens) == self.chunk_length:
+                    next_chunk()
+
+                embedding, embedding_length_in_tokens = self.hijack.embedding_db.find_embedding_at_position(tokens, position)
                 if embedding is None:
-                    remade_tokens.append(token)
-                    multipliers.append(weight)
-                    i += 1
-                else:
-                    emb_len = int(embedding.vec.shape[0])
-                    iteration = len(remade_tokens) // 75
-                    if (len(remade_tokens) + emb_len) // 75 != iteration:
-                        rem = (75 * (iteration + 1) - len(remade_tokens))
-                        remade_tokens += [self.id_end] * rem
-                        multipliers += [1.0] * rem
-                        iteration += 1
-                    fixes.append((iteration, (len(remade_tokens) % 75, embedding)))
-                    remade_tokens += [0] * emb_len
-                    multipliers += [weight] * emb_len
-                    used_custom_terms.append((embedding.name, embedding.checksum()))
-                    i += embedding_length_in_tokens
-
-        token_count = len(remade_tokens)
-        prompt_target_length = get_target_prompt_token_count(token_count)
-        tokens_to_add = prompt_target_length - len(remade_tokens)
-
-        remade_tokens = remade_tokens + [self.id_end] * tokens_to_add
-        multipliers = multipliers + [1.0] * tokens_to_add
-
-        return remade_tokens, fixes, multipliers, token_count
-
-    def process_text(self, texts):
-        used_custom_terms = []
-        remade_batch_tokens = []
-        hijack_comments = []
-        hijack_fixes = []
+                    chunk.tokens.append(token)
+                    chunk.multipliers.append(weight)
+                    position += 1
+                    continue
+
+                emb_len = int(embedding.vec.shape[0])
+                if len(chunk.tokens) + emb_len > self.chunk_length:
+                    next_chunk()
+
+                chunk.fixes.append(PromptChunkFix(len(chunk.tokens), embedding))
+
+                chunk.tokens += [0] * emb_len
+                chunk.multipliers += [weight] * emb_len
+                position += embedding_length_in_tokens
+
+        if len(chunk.tokens) > 0:
+            next_chunk()
+
+        return chunks, token_count
+
+    def process_texts(self, texts):
+        """
+        Accepts a list of texts and calls tokenize_line() on each, with cache. Returns the list of results and maximum
+        length, in tokens, of all texts.
+        """
+
         token_count = 0
 
         cache = {}
-        batch_multipliers = []
+        batch_chunks = []
         for line in texts:
             if line in cache:
-                remade_tokens, fixes, multipliers = cache[line]
+                chunks = cache[line]
             else:
-                remade_tokens, fixes, multipliers, current_token_count = self.tokenize_line(line, used_custom_terms, hijack_comments)
+                chunks, current_token_count = self.tokenize_line(line)
                 token_count = max(current_token_count, token_count)
 
-                cache[line] = (remade_tokens, fixes, multipliers)
+                cache[line] = chunks
 
-            remade_batch_tokens.append(remade_tokens)
-            hijack_fixes.append(fixes)
-            batch_multipliers.append(multipliers)
+            batch_chunks.append(chunks)
 
-        return batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count
+        return batch_chunks, token_count
 
-    def process_text_old(self, texts):
-        id_start = self.id_start
-        id_end = self.id_end
-        maxlen = self.wrapped.max_length  # you get to stay at 77
-        used_custom_terms = []
-        remade_batch_tokens = []
-        hijack_comments = []
-        hijack_fixes = []
-        token_count = 0
+    def forward(self, texts):
+        """
+        Accepts an array of texts; Passes texts through transformers network to create a tensor with numerical representation of those texts.
+        Returns a tensor with shape of (B, T, C), where B is length of the array; T is length, in tokens, of texts (including padding) - T will
+        be a multiple of 77; and C is dimensionality of each token - for SD1 it's 768, and for SD2 it's 1024.
+        An example shape returned by this function can be: (2, 77, 768).
+        Webui usually sends just one text at a time through this function - the only time when texts is an array with more than one elemenet
+        is when you do prompt editing: "a picture of a [cat:dog:0.4] eating ice cream"
+        """
 
-        cache = {}
-        batch_tokens = self.tokenize(texts)
-        batch_multipliers = []
-        for tokens in batch_tokens:
-            tuple_tokens = tuple(tokens)
+        if opts.use_old_emphasis_implementation:
+            import modules.sd_hijack_clip_old
+            return modules.sd_hijack_clip_old.forward_old(self, texts)
 
-            if tuple_tokens in cache:
-                remade_tokens, fixes, multipliers = cache[tuple_tokens]
-            else:
-                fixes = []
-                remade_tokens = []
-                multipliers = []
-                mult = 1.0
-
-                i = 0
-                while i < len(tokens):
-                    token = tokens[i]
-
-                    embedding, embedding_length_in_tokens = self.hijack.embedding_db.find_embedding_at_position(tokens, i)
-
-                    mult_change = self.token_mults.get(token) if opts.enable_emphasis else None
-                    if mult_change is not None:
-                        mult *= mult_change
-                        i += 1
-                    elif embedding is None:
-                        remade_tokens.append(token)
-                        multipliers.append(mult)
-                        i += 1
-                    else:
-                        emb_len = int(embedding.vec.shape[0])
-                        fixes.append((len(remade_tokens), embedding))
-                        remade_tokens += [0] * emb_len
-                        multipliers += [mult] * emb_len
-                        used_custom_terms.append((embedding.name, embedding.checksum()))
-                        i += embedding_length_in_tokens
-
-                if len(remade_tokens) > maxlen - 2:
-                    vocab = {v: k for k, v in self.wrapped.tokenizer.get_vocab().items()}
-                    ovf = remade_tokens[maxlen - 2:]
-                    overflowing_words = [vocab.get(int(x), "") for x in ovf]
-                    overflowing_text = self.wrapped.tokenizer.convert_tokens_to_string(''.join(overflowing_words))
-                    hijack_comments.append(f"Warning: too many input tokens; some ({len(overflowing_words)}) have been truncated:\n{overflowing_text}\n")
-
-                token_count = len(remade_tokens)
-                remade_tokens = remade_tokens + [id_end] * (maxlen - 2 - len(remade_tokens))
-                remade_tokens = [id_start] + remade_tokens[0:maxlen - 2] + [id_end]
-                cache[tuple_tokens] = (remade_tokens, fixes, multipliers)
-
-            multipliers = multipliers + [1.0] * (maxlen - 2 - len(multipliers))
-            multipliers = [1.0] + multipliers[0:maxlen - 2] + [1.0]
-
-            remade_batch_tokens.append(remade_tokens)
-            hijack_fixes.append(fixes)
-            batch_multipliers.append(multipliers)
-        return batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count
-
-    def forward(self, text):
-        use_old = opts.use_old_emphasis_implementation
-        if use_old:
-            batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = self.process_text_old(text)
-        else:
-            batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = self.process_text(text)
-
-        self.hijack.comments += hijack_comments
-
-        if len(used_custom_terms) > 0:
-            self.hijack.comments.append("Used embeddings: " + ", ".join([f'{word} [{checksum}]' for word, checksum in used_custom_terms]))
-
-        if use_old:
-            self.hijack.fixes = hijack_fixes
-            return self.process_tokens(remade_batch_tokens, batch_multipliers)
-
-        z = None
-        i = 0
-        while max(map(len, remade_batch_tokens)) != 0:
-            rem_tokens = [x[75:] for x in remade_batch_tokens]
-            rem_multipliers = [x[75:] for x in batch_multipliers]
-
-            self.hijack.fixes = []
-            for unfiltered in hijack_fixes:
-                fixes = []
-                for fix in unfiltered:
-                    if fix[0] == i:
-                        fixes.append(fix[1])
-                self.hijack.fixes.append(fixes)
-
-            tokens = []
-            multipliers = []
-            for j in range(len(remade_batch_tokens)):
-                if len(remade_batch_tokens[j]) > 0:
-                    tokens.append(remade_batch_tokens[j][:75])
-                    multipliers.append(batch_multipliers[j][:75])
-                else:
-                    tokens.append([self.id_end] * 75)
-                    multipliers.append([1.0] * 75)
-
-            z1 = self.process_tokens(tokens, multipliers)
-            z = z1 if z is None else torch.cat((z, z1), axis=-2)
-
-            remade_batch_tokens = rem_tokens
-            batch_multipliers = rem_multipliers
-            i += 1
+        batch_chunks, token_count = self.process_texts(texts)
 
-        return z
+        used_embeddings = {}
+        chunk_count = max([len(x) for x in batch_chunks])
 
-    def process_tokens(self, remade_batch_tokens, batch_multipliers):
-        if not opts.use_old_emphasis_implementation:
-            remade_batch_tokens = [[self.id_start] + x[:75] + [self.id_end] for x in remade_batch_tokens]
-            batch_multipliers = [[1.0] + x[:75] + [1.0] for x in batch_multipliers]
+        zs = []
+        for i in range(chunk_count):
+            batch_chunk = [chunks[i] if i < len(chunks) else self.empty_chunk() for chunks in batch_chunks]
+
+            tokens = [x.tokens for x in batch_chunk]
+            multipliers = [x.multipliers for x in batch_chunk]
+            self.hijack.fixes = [x.fixes for x in batch_chunk]
 
+            for fixes in self.hijack.fixes:
+                for position, embedding in fixes:
+                    used_embeddings[embedding.name] = embedding
+
+            z = self.process_tokens(tokens, multipliers)
+            zs.append(z)
+
+        if len(used_embeddings) > 0:
+            embeddings_list = ", ".join([f'{name} [{embedding.checksum()}]' for name, embedding in used_embeddings.items()])
+            self.hijack.comments.append(f"Used embeddings: {embeddings_list}")
+
+        return torch.hstack(zs)
+
+    def process_tokens(self, remade_batch_tokens, batch_multipliers):
+        """
+        sends one single prompt chunk to be encoded by transformers neural network.
+        remade_batch_tokens is a batch of tokens - a list, where every element is a list of tokens; usually
+        there are exactly 77 tokens in the list. batch_multipliers is the same but for multipliers instead of tokens.
+        Multipliers are used to give more or less weight to the outputs of transformers network. Each multiplier
+        corresponds to one token.
+        """
         tokens = torch.asarray(remade_batch_tokens).to(devices.device)
 
+        # this is for SD2: SD1 uses the same token for padding and end of text, while SD2 uses different ones.
         if self.id_end != self.id_pad:
             for batch_pos in range(len(remade_batch_tokens)):
                 index = remade_batch_tokens[batch_pos].index(self.id_end)
@@ -239,8 +234,7 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
         z = self.encode_with_transformers(tokens)
 
         # restoring original mean is likely not correct, but it seems to work well to prevent artifacts that happen otherwise
-        batch_multipliers_of_same_length = [x + [1.0] * (75 - len(x)) for x in batch_multipliers]
-        batch_multipliers = torch.asarray(batch_multipliers_of_same_length).to(devices.device)
+        batch_multipliers = torch.asarray(batch_multipliers).to(devices.device)
         original_mean = z.mean()
         z *= batch_multipliers.reshape(batch_multipliers.shape + (1,)).expand(z.shape)
         new_mean = z.mean()
diff --git a/modules/sd_hijack_clip_old.py b/modules/sd_hijack_clip_old.py
new file mode 100644
index 00000000..6d9fbbe6
--- /dev/null
+++ b/modules/sd_hijack_clip_old.py
@@ -0,0 +1,81 @@
+from modules import sd_hijack_clip
+from modules import shared
+
+
+def process_text_old(self: sd_hijack_clip.FrozenCLIPEmbedderWithCustomWordsBase, texts):
+    id_start = self.id_start
+    id_end = self.id_end
+    maxlen = self.wrapped.max_length  # you get to stay at 77
+    used_custom_terms = []
+    remade_batch_tokens = []
+    hijack_comments = []
+    hijack_fixes = []
+    token_count = 0
+
+    cache = {}
+    batch_tokens = self.tokenize(texts)
+    batch_multipliers = []
+    for tokens in batch_tokens:
+        tuple_tokens = tuple(tokens)
+
+        if tuple_tokens in cache:
+            remade_tokens, fixes, multipliers = cache[tuple_tokens]
+        else:
+            fixes = []
+            remade_tokens = []
+            multipliers = []
+            mult = 1.0
+
+            i = 0
+            while i < len(tokens):
+                token = tokens[i]
+
+                embedding, embedding_length_in_tokens = self.hijack.embedding_db.find_embedding_at_position(tokens, i)
+
+                mult_change = self.token_mults.get(token) if shared.opts.enable_emphasis else None
+                if mult_change is not None:
+                    mult *= mult_change
+                    i += 1
+                elif embedding is None:
+                    remade_tokens.append(token)
+                    multipliers.append(mult)
+                    i += 1
+                else:
+                    emb_len = int(embedding.vec.shape[0])
+                    fixes.append((len(remade_tokens), embedding))
+                    remade_tokens += [0] * emb_len
+                    multipliers += [mult] * emb_len
+                    used_custom_terms.append((embedding.name, embedding.checksum()))
+                    i += embedding_length_in_tokens
+
+            if len(remade_tokens) > maxlen - 2:
+                vocab = {v: k for k, v in self.wrapped.tokenizer.get_vocab().items()}
+                ovf = remade_tokens[maxlen - 2:]
+                overflowing_words = [vocab.get(int(x), "") for x in ovf]
+                overflowing_text = self.wrapped.tokenizer.convert_tokens_to_string(''.join(overflowing_words))
+                hijack_comments.append(f"Warning: too many input tokens; some ({len(overflowing_words)}) have been truncated:\n{overflowing_text}\n")
+
+            token_count = len(remade_tokens)
+            remade_tokens = remade_tokens + [id_end] * (maxlen - 2 - len(remade_tokens))
+            remade_tokens = [id_start] + remade_tokens[0:maxlen - 2] + [id_end]
+            cache[tuple_tokens] = (remade_tokens, fixes, multipliers)
+
+        multipliers = multipliers + [1.0] * (maxlen - 2 - len(multipliers))
+        multipliers = [1.0] + multipliers[0:maxlen - 2] + [1.0]
+
+        remade_batch_tokens.append(remade_tokens)
+        hijack_fixes.append(fixes)
+        batch_multipliers.append(multipliers)
+    return batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count
+
+
+def forward_old(self: sd_hijack_clip.FrozenCLIPEmbedderWithCustomWordsBase, texts):
+    batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = process_text_old(self, texts)
+
+    self.hijack.comments += hijack_comments
+
+    if len(used_custom_terms) > 0:
+        self.hijack.comments.append("Used embeddings: " + ", ".join([f'{word} [{checksum}]' for word, checksum in used_custom_terms]))
+
+    self.hijack.fixes = hijack_fixes
+    return self.process_tokens(remade_batch_tokens, batch_multipliers)
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index f9f5e8cd..45882ed6 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -79,7 +79,6 @@ class EmbeddingDatabase:
 
         self.word_embeddings[embedding.name] = embedding
 
-        # TODO changing between clip and open clip changes tokenization, which will cause embeddings to stop working
         ids = model.cond_stage_model.tokenize([embedding.name])[0]
 
         first_id = ids[0]
diff --git a/modules/ui.py b/modules/ui.py
index b79d24ee..5d2f5bad 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -368,7 +368,7 @@ def update_token_counter(text, steps):
 
     flat_prompts = reduce(lambda list1, list2: list1+list2, prompt_schedules)
     prompts = [prompt_text for step, prompt_text in flat_prompts]
-    tokens, token_count, max_length = max([model_hijack.tokenize(prompt) for prompt in prompts], key=lambda args: args[1])
+    token_count, max_length = max([model_hijack.get_prompt_lengths(prompt) for prompt in prompts], key=lambda args: args[0])
     style_class = ' class="red"' if (token_count > max_length) else ""
     return f"<span {style_class}>{token_count}/{max_length}</span>"
 
-- 
cgit v1.2.3


From f94cfc563bbedd923d5e95563a5e8d93c8516ac3 Mon Sep 17 00:00:00 2001
From: Mitchell Boot <47387831+Mitchell1711@users.noreply.github.com>
Date: Sat, 7 Jan 2023 01:15:22 +0100
Subject: Changed HTML to textbox instead

Using HTML caused an issue where the row would expand for a frame when changing the sliders because of the loading animation. This solution also doesn't use any additional HTML padding
---
 modules/ui.py | 7 +++++--
 1 file changed, 5 insertions(+), 2 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index 6fc8b7d7..6ea1b5d7 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -260,7 +260,7 @@ def calc_resolution_hires(x, y, scale):
     scaled_x = int(x * scale // 8) * 8
     scaled_y = int(y * scale // 8) * 8
     
-    return "<p style='margin: -1em 0em 0.7em 1.35em'>Upscaled resolution: "+str(scaled_x)+"x"+str(scaled_y)+"</p>"
+    return str(scaled_x)+"x"+str(scaled_y)
 
 def apply_styles(prompt, prompt_neg, style1_name, style2_name):
     prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, [style1_name, style2_name])
@@ -726,7 +726,10 @@ def create_ui():
                                 hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y")
                             
                             with FormRow(elem_id="txt2img_hires_fix_row3"):        
-                                hr_final_resolution = gr.HTML(value=calc_resolution_hires(width.value, height.value, hr_scale.value), elem_id="txtimg_hr_finalres")
+                                hr_final_resolution = gr.Textbox(value=calc_resolution_hires(width.value, height.value, hr_scale.value), 
+                                    elem_id="txtimg_hr_finalres", 
+                                    label="Upscaled resolution",
+                                    interactive=False)
                                 hr_scale.change(fn=calc_resolution_hires, inputs=[width, height, hr_scale], outputs=hr_final_resolution, show_progress=False)
                                 width.change(fn=calc_resolution_hires, inputs=[width, height, hr_scale], outputs=hr_final_resolution, show_progress=False)
                                 height.change(fn=calc_resolution_hires, inputs=[width, height, hr_scale], outputs=hr_final_resolution, show_progress=False)
-- 
cgit v1.2.3


From de9738044571877450d1038e18f1ecce93d24af3 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 7 Jan 2023 08:53:53 +0300
Subject: this breaks on default config because width, height, hr_scale are
 None at that point.

---
 modules/ui.py | 14 ++++++--------
 1 file changed, 6 insertions(+), 8 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index f946382d..a18b9007 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -725,14 +725,8 @@ def create_ui():
                                 hr_resize_x = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize width to", value=0, elem_id="txt2img_hr_resize_x")
                                 hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y")
                             
-                            with FormRow(elem_id="txt2img_hires_fix_row3"):        
-                                hr_final_resolution = gr.Textbox(value=calc_resolution_hires(width.value, height.value, hr_scale.value), 
-                                    elem_id="txtimg_hr_finalres", 
-                                    label="Upscaled resolution",
-                                    interactive=False)
-                                hr_scale.change(fn=calc_resolution_hires, inputs=[width, height, hr_scale], outputs=hr_final_resolution, show_progress=False)
-                                width.change(fn=calc_resolution_hires, inputs=[width, height, hr_scale], outputs=hr_final_resolution, show_progress=False)
-                                height.change(fn=calc_resolution_hires, inputs=[width, height, hr_scale], outputs=hr_final_resolution, show_progress=False)
+                            with FormRow(elem_id="txt2img_hires_fix_row3"):
+                                hr_final_resolution = gr.Textbox(value="", elem_id="txtimg_hr_finalres", label="Upscaled resolution", interactive=False)
 
                     elif category == "batch":
                         if not opts.dimensions_and_batch_together:
@@ -744,6 +738,10 @@ def create_ui():
                         with FormGroup(elem_id="txt2img_script_container"):
                             custom_inputs = modules.scripts.scripts_txt2img.setup_ui()
 
+            hr_scale.change(fn=calc_resolution_hires, inputs=[width, height, hr_scale], outputs=hr_final_resolution, show_progress=False)
+            width.change(fn=calc_resolution_hires, inputs=[width, height, hr_scale], outputs=hr_final_resolution, show_progress=False)
+            height.change(fn=calc_resolution_hires, inputs=[width, height, hr_scale], outputs=hr_final_resolution, show_progress=False)
+
             txt2img_gallery, generation_info, html_info, html_log = create_output_panel("txt2img", opts.outdir_txt2img_samples)
             parameters_copypaste.bind_buttons({"txt2img": txt2img_paste}, None, txt2img_prompt)
 
-- 
cgit v1.2.3


From 1a5b86ad65fd738eadea1ad72f4abad3a4aabf17 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 7 Jan 2023 09:56:37 +0300
Subject: rework hires fix preview for #6437: movie it to where it takes less
 place, make it actually account for all relevant sliders and calculate
 dimensions correctly

---
 modules/processing.py    |  1 -
 modules/ui.py            | 40 +++++++++++++++++++++++++++-------------
 modules/ui_components.py |  8 ++++++++
 style.css                | 17 +++++++++++++++++
 4 files changed, 52 insertions(+), 14 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/processing.py b/modules/processing.py
index a408d622..82157bc9 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -711,7 +711,6 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
         self.truncate_x = 0
         self.truncate_y = 0
 
-
     def init(self, all_prompts, all_seeds, all_subseeds):
         if self.enable_hr:
             if self.hr_resize_x == 0 and self.hr_resize_y == 0:
diff --git a/modules/ui.py b/modules/ui.py
index a18b9007..6c765262 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -20,7 +20,7 @@ from PIL import Image, PngImagePlugin
 from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
 
 from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru
-from modules.ui_components import FormRow, FormGroup, ToolButton
+from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
 from modules.paths import script_path
 
 from modules.shared import opts, cmd_opts, restricted_opts
@@ -255,12 +255,20 @@ def add_style(name: str, prompt: str, negative_prompt: str):
 
     return [gr.Dropdown.update(visible=True, choices=list(shared.prompt_styles.styles)) for _ in range(4)]
 
-def calc_resolution_hires(x, y, scale):
-    #final res can only be a multiple of 8
-    scaled_x = int(x * scale // 8) * 8
-    scaled_y = int(y * scale // 8) * 8
-    
-    return str(scaled_x)+"x"+str(scaled_y)
+
+def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resize_y):
+    from modules import processing, devices
+
+    if not enable:
+        return ""
+
+    p = processing.StableDiffusionProcessingTxt2Img(width=width, height=height, enable_hr=True, hr_scale=hr_scale, hr_resize_x=hr_resize_x, hr_resize_y=hr_resize_y)
+
+    with devices.autocast():
+        p.init([""], [0], [0])
+
+    return f"resize to: <span class='resolution'>{p.hr_upscale_to_x}x{p.hr_upscale_to_y}</span>"
+
 
 def apply_styles(prompt, prompt_neg, style1_name, style2_name):
     prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, [style1_name, style2_name])
@@ -712,6 +720,7 @@ def create_ui():
                             restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="txt2img_restore_faces")
                             tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling")
                             enable_hr = gr.Checkbox(label='Hires. fix', value=False, elem_id="txt2img_enable_hr")
+                            hr_final_resolution = FormHTML(value="", elem_id="txtimg_hr_finalres", label="Upscaled resolution", interactive=False)
 
                     elif category == "hires_fix":
                         with FormGroup(visible=False, elem_id="txt2img_hires_fix") as hr_options:
@@ -724,9 +733,6 @@ def create_ui():
                                 hr_scale = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Upscale by", value=2.0, elem_id="txt2img_hr_scale")
                                 hr_resize_x = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize width to", value=0, elem_id="txt2img_hr_resize_x")
                                 hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y")
-                            
-                            with FormRow(elem_id="txt2img_hires_fix_row3"):
-                                hr_final_resolution = gr.Textbox(value="", elem_id="txtimg_hr_finalres", label="Upscaled resolution", interactive=False)
 
                     elif category == "batch":
                         if not opts.dimensions_and_batch_together:
@@ -738,9 +744,16 @@ def create_ui():
                         with FormGroup(elem_id="txt2img_script_container"):
                             custom_inputs = modules.scripts.scripts_txt2img.setup_ui()
 
-            hr_scale.change(fn=calc_resolution_hires, inputs=[width, height, hr_scale], outputs=hr_final_resolution, show_progress=False)
-            width.change(fn=calc_resolution_hires, inputs=[width, height, hr_scale], outputs=hr_final_resolution, show_progress=False)
-            height.change(fn=calc_resolution_hires, inputs=[width, height, hr_scale], outputs=hr_final_resolution, show_progress=False)
+            hr_resolution_preview_inputs = [enable_hr, width, height, hr_scale, hr_resize_x, hr_resize_y]
+            hr_resolution_preview_args = dict(
+                fn=calc_resolution_hires,
+                inputs=hr_resolution_preview_inputs,
+                outputs=[hr_final_resolution],
+                show_progress=False
+            )
+
+            for input in hr_resolution_preview_inputs:
+                input.change(**hr_resolution_preview_args)
 
             txt2img_gallery, generation_info, html_info, html_log = create_output_panel("txt2img", opts.outdir_txt2img_samples)
             parameters_copypaste.bind_buttons({"txt2img": txt2img_paste}, None, txt2img_prompt)
@@ -803,6 +816,7 @@ def create_ui():
                 fn=lambda x: gr_show(x),
                 inputs=[enable_hr],
                 outputs=[hr_options],
+                show_progress = False,
             )
 
             txt2img_paste_fields = [
diff --git a/modules/ui_components.py b/modules/ui_components.py
index 91eb0e3d..cac001dc 100644
--- a/modules/ui_components.py
+++ b/modules/ui_components.py
@@ -23,3 +23,11 @@ class FormGroup(gr.Group, gr.components.FormComponent):
 
     def get_block_name(self):
         return "group"
+
+
+class FormHTML(gr.HTML, gr.components.FormComponent):
+    """Same as gr.HTML but fits inside gradio forms"""
+
+    def get_block_name(self):
+        return "html"
+
diff --git a/style.css b/style.css
index f1b23b53..76721756 100644
--- a/style.css
+++ b/style.css
@@ -642,6 +642,23 @@ footer {
     opacity: 0.85;
 }
 
+#txtimg_hr_finalres{
+    min-height: 0 !important;
+    padding: .625rem .75rem;
+    margin-left: -0.75em
+
+}
+
+#txtimg_hr_finalres .resolution{
+    font-weight: bold;
+}
+
+#txt2img_checkboxes > div > div{
+    flex: 0;
+    white-space: nowrap;
+    min-width: auto;
+}
+
 /* The following handles localization for right-to-left (RTL) languages like Arabic.
 The rtl media type will only be activated by the logic in javascript/localization.js.
 If you change anything above, you need to make sure it is RTL compliant by just running
-- 
cgit v1.2.3


From fdfce4711076c2ebac1089bac8169d043eb7978f Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 7 Jan 2023 13:29:47 +0300
Subject: add "from" resolution for hires fix to be less confusing.

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

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index 6c765262..99483130 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -267,7 +267,7 @@ def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resiz
     with devices.autocast():
         p.init([""], [0], [0])
 
-    return f"resize to: <span class='resolution'>{p.hr_upscale_to_x}x{p.hr_upscale_to_y}</span>"
+    return f"resize: from <span class='resolution'>{width}x{height}</span> to <span class='resolution'>{p.hr_upscale_to_x}x{p.hr_upscale_to_y}</span>"
 
 
 def apply_styles(prompt, prompt_neg, style1_name, style2_name):
-- 
cgit v1.2.3


From 669fb18d5222f53ae48abe0f30393d846c50ad91 Mon Sep 17 00:00:00 2001
From: dan <guaneec@gmail.com>
Date: Sun, 8 Jan 2023 01:34:52 +0800
Subject: Add checkbox for variable training dims

---
 modules/hypernetworks/hypernetwork.py          | 2 +-
 modules/textual_inversion/dataset.py           | 4 ++--
 modules/textual_inversion/textual_inversion.py | 4 ++--
 modules/ui.py                                  | 3 +++
 4 files changed, 8 insertions(+), 5 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index b0cfbe71..dba52841 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -403,7 +403,7 @@ def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None,
     shared.reload_hypernetworks()
 
 
-def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_hypernetwork_every, template_file, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
+def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_hypernetwork_every, template_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
 
diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index 375178ed..7f8a314f 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -29,7 +29,7 @@ class DatasetEntry:
 
 
 class PersonalizedBase(Dataset):
-    def __init__(self, data_root, width, height, repeats, flip_p=0.5, placeholder_token="*", model=None, cond_model=None, device=None, template_file=None, include_cond=False, batch_size=1, gradient_step=1, shuffle_tags=False, tag_drop_out=0, latent_sampling_method='once'):
+    def __init__(self, data_root, width, height, repeats, flip_p=0.5, placeholder_token="*", model=None, cond_model=None, device=None, template_file=None, include_cond=False, batch_size=1, gradient_step=1, shuffle_tags=False, tag_drop_out=0, latent_sampling_method='once', varsize=False):
         re_word = re.compile(shared.opts.dataset_filename_word_regex) if len(shared.opts.dataset_filename_word_regex) > 0 else None
 
         self.placeholder_token = placeholder_token
@@ -59,7 +59,7 @@ class PersonalizedBase(Dataset):
                 raise Exception("interrupted")
             try:
                 image = Image.open(path).convert('RGB')
-                if width < 2000:
+                if not varsize:
                     image = image.resize((width, height), PIL.Image.BICUBIC)
                 else:
                     assert batch_size == 1, 'variable img size must have batch size 1'
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 9f96d0fd..110efd19 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -255,7 +255,7 @@ def validate_train_inputs(model_name, learn_rate, batch_size, gradient_step, dat
     if save_model_every or create_image_every:
         assert log_directory, "Log directory is empty"
 
-def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
+def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
     save_embedding_every = save_embedding_every or 0
     create_image_every = create_image_every or 0
     validate_train_inputs(embedding_name, learn_rate, batch_size, gradient_step, data_root, template_file, steps, save_embedding_every, create_image_every, log_directory, name="embedding")
@@ -309,7 +309,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_
 
     pin_memory = shared.opts.pin_memory
 
-    ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, height=training_height, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=embedding_name, model=shared.sd_model, cond_model=shared.sd_model.cond_stage_model, device=devices.device, template_file=template_file, batch_size=batch_size, gradient_step=gradient_step, shuffle_tags=shuffle_tags, tag_drop_out=tag_drop_out, latent_sampling_method=latent_sampling_method)
+    ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, height=training_height, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=embedding_name, model=shared.sd_model, cond_model=shared.sd_model.cond_stage_model, device=devices.device, template_file=template_file, batch_size=batch_size, gradient_step=gradient_step, shuffle_tags=shuffle_tags, tag_drop_out=tag_drop_out, latent_sampling_method=latent_sampling_method, varsize=varsize)
 
     if shared.opts.save_training_settings_to_txt:
         save_settings_to_file(log_directory, {**dict(model_name=checkpoint.model_name, model_hash=checkpoint.hash, num_of_dataset_images=len(ds), num_vectors_per_token=len(embedding.vec)), **locals()})
diff --git a/modules/ui.py b/modules/ui.py
index 99483130..4e709a71 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1343,6 +1343,7 @@ def create_ui():
                     template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"), elem_id="train_template_file")
                     training_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_training_width")
                     training_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_training_height")
+                    varsize = gr.Checkbox(label="Ignore dimension settings and do not resize images", value=False, elem_id="train_varsize")
                     steps = gr.Number(label='Max steps', value=100000, precision=0, elem_id="train_steps")
 
                     with FormRow():
@@ -1449,6 +1450,7 @@ def create_ui():
                 log_directory,
                 training_width,
                 training_height,
+                varsize,
                 steps,
                 clip_grad_mode,
                 clip_grad_value,
@@ -1480,6 +1482,7 @@ def create_ui():
                 log_directory,
                 training_width,
                 training_height,
+                varsize,
                 steps,
                 clip_grad_mode,
                 clip_grad_value,
-- 
cgit v1.2.3


From d4fd2418efb0986a8226add0b800fb5c73ffb58c Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 9 Jan 2023 14:57:47 +0300
Subject: add an option to use old hiresfix width/height behavior add a visual
 effect to inactive hires fix elements

---
 javascript/hires_fix.js                    | 25 +++++++++++++++++++++++++
 modules/generation_parameters_copypaste.py | 17 +++++++++++------
 modules/processing.py                      | 26 ++++++++++++++++++++++++--
 modules/shared.py                          |  1 +
 modules/ui.py                              | 23 ++++++++++++++---------
 style.css                                  |  4 ++++
 6 files changed, 79 insertions(+), 17 deletions(-)
 create mode 100644 javascript/hires_fix.js

(limited to 'modules/ui.py')

diff --git a/javascript/hires_fix.js b/javascript/hires_fix.js
new file mode 100644
index 00000000..07fba549
--- /dev/null
+++ b/javascript/hires_fix.js
@@ -0,0 +1,25 @@
+
+function setInactive(elem, inactive){
+    console.log(elem)
+    if(inactive){
+        elem.classList.add('inactive')
+    } else{
+        elem.classList.remove('inactive')
+    }
+}
+
+function onCalcResolutionHires(enable, width, height, hr_scale, hr_resize_x, hr_resize_y){
+    console.log(enable, width, height, hr_scale, hr_resize_x, hr_resize_y)
+
+    hrUpscaleBy = gradioApp().getElementById('txt2img_hr_scale')
+    hrResizeX = gradioApp().getElementById('txt2img_hr_resize_x')
+    hrResizeY = gradioApp().getElementById('txt2img_hr_resize_y')
+
+    gradioApp().getElementById('txt2img_hires_fix_row2').style.display = opts.use_old_hires_fix_width_height ? "none" : ""
+
+    setInactive(hrUpscaleBy, opts.use_old_hires_fix_width_height || hr_resize_x > 0 || hr_resize_y > 0)
+    setInactive(hrResizeX, opts.use_old_hires_fix_width_height || hr_resize_x == 0)
+    setInactive(hrResizeY, opts.use_old_hires_fix_width_height || hr_resize_y == 0)
+
+    return [enable, width, height, hr_scale, hr_resize_x, hr_resize_y]
+}
diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py
index 12a9de3d..f7f68b67 100644
--- a/modules/generation_parameters_copypaste.py
+++ b/modules/generation_parameters_copypaste.py
@@ -197,6 +197,15 @@ def restore_old_hires_fix_params(res):
     firstpass_width = res.get('First pass size-1', None)
     firstpass_height = res.get('First pass size-2', None)
 
+    if shared.opts.use_old_hires_fix_width_height:
+        hires_width = int(res.get("Hires resize-1", None))
+        hires_height = int(res.get("Hires resize-2", None))
+
+        if hires_width is not None and hires_height is not None:
+            res['Size-1'] = hires_width
+            res['Size-2'] = hires_height
+            return
+
     if firstpass_width is None or firstpass_height is None:
         return
 
@@ -205,12 +214,8 @@ def restore_old_hires_fix_params(res):
     height = int(res.get("Size-2", 512))
 
     if firstpass_width == 0 or firstpass_height == 0:
-        # old algorithm for auto-calculating first pass size
-        desired_pixel_count = 512 * 512
-        actual_pixel_count = width * height
-        scale = math.sqrt(desired_pixel_count / actual_pixel_count)
-        firstpass_width = math.ceil(scale * width / 64) * 64
-        firstpass_height = math.ceil(scale * height / 64) * 64
+        from modules import processing
+        firstpass_width, firstpass_height = processing.old_hires_fix_first_pass_dimensions(width, height)
 
     res['Size-1'] = firstpass_width
     res['Size-2'] = firstpass_height
diff --git a/modules/processing.py b/modules/processing.py
index 1d23b15f..f04a0e1e 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -687,6 +687,18 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
     return res
 
 
+def old_hires_fix_first_pass_dimensions(width, height):
+    """old algorithm for auto-calculating first pass size"""
+
+    desired_pixel_count = 512 * 512
+    actual_pixel_count = width * height
+    scale = math.sqrt(desired_pixel_count / actual_pixel_count)
+    width = math.ceil(scale * width / 64) * 64
+    height = math.ceil(scale * height / 64) * 64
+
+    return width, height
+
+
 class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
     sampler = None
 
@@ -703,16 +715,26 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
         self.hr_upscale_to_y = hr_resize_y
 
         if firstphase_width != 0 or firstphase_height != 0:
-            print("firstphase_width/firstphase_height no longer supported; use hr_scale", file=sys.stderr)
-            self.hr_scale = self.width / firstphase_width
+            self.hr_upscale_to_x = self.width
+            self.hr_upscale_to_y = self.height
             self.width = firstphase_width
             self.height = firstphase_height
 
         self.truncate_x = 0
         self.truncate_y = 0
+        self.applied_old_hires_behavior_to = None
 
     def init(self, all_prompts, all_seeds, all_subseeds):
         if self.enable_hr:
+            if opts.use_old_hires_fix_width_height and self.applied_old_hires_behavior_to != (self.width, self.height):
+                self.hr_resize_x = self.width
+                self.hr_resize_y = self.height
+                self.hr_upscale_to_x = self.width
+                self.hr_upscale_to_y = self.height
+
+                self.width, self.height = old_hires_fix_first_pass_dimensions(self.width, self.height)
+                self.applied_old_hires_behavior_to = (self.width, self.height)
+
             if self.hr_resize_x == 0 and self.hr_resize_y == 0:
                 self.extra_generation_params["Hires upscale"] = self.hr_scale
                 self.hr_upscale_to_x = int(self.width * self.hr_scale)
diff --git a/modules/shared.py b/modules/shared.py
index a6712dae..a1e10201 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -398,6 +398,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
 options_templates.update(options_section(('compatibility', "Compatibility"), {
     "use_old_emphasis_implementation": OptionInfo(False, "Use old emphasis implementation. Can be useful to reproduce old seeds."),
     "use_old_karras_scheduler_sigmas": OptionInfo(False, "Use old karras scheduler sigmas (0.1 to 10)."),
+    "use_old_hires_fix_width_height": OptionInfo(False, "For hires fix, use width/height sliders to set final resolution rather than first pass (disables Upscale by, Resize width/height to)."),
 }))
 
 options_templates.update(options_section(('interrogate', "Interrogate Options"), {
diff --git a/modules/ui.py b/modules/ui.py
index 99483130..719c26b3 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -267,7 +267,7 @@ def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resiz
     with devices.autocast():
         p.init([""], [0], [0])
 
-    return f"resize: from <span class='resolution'>{width}x{height}</span> to <span class='resolution'>{p.hr_upscale_to_x}x{p.hr_upscale_to_y}</span>"
+    return f"resize: from <span class='resolution'>{p.width}x{p.height}</span> to <span class='resolution'>{p.hr_resize_x or p.hr_upscale_to_x}x{p.hr_resize_y or p.hr_upscale_to_y}</span>"
 
 
 def apply_styles(prompt, prompt_neg, style1_name, style2_name):
@@ -745,15 +745,20 @@ def create_ui():
                             custom_inputs = modules.scripts.scripts_txt2img.setup_ui()
 
             hr_resolution_preview_inputs = [enable_hr, width, height, hr_scale, hr_resize_x, hr_resize_y]
-            hr_resolution_preview_args = dict(
-                fn=calc_resolution_hires,
-                inputs=hr_resolution_preview_inputs,
-                outputs=[hr_final_resolution],
-                show_progress=False
-            )
-
             for input in hr_resolution_preview_inputs:
-                input.change(**hr_resolution_preview_args)
+                input.change(
+                    fn=calc_resolution_hires,
+                    inputs=hr_resolution_preview_inputs,
+                    outputs=[hr_final_resolution],
+                    show_progress=False,
+                )
+                input.change(
+                    None,
+                    _js="onCalcResolutionHires",
+                    inputs=hr_resolution_preview_inputs,
+                    outputs=[],
+                    show_progress=False,
+                )
 
             txt2img_gallery, generation_info, html_info, html_log = create_output_panel("txt2img", opts.outdir_txt2img_samples)
             parameters_copypaste.bind_buttons({"txt2img": txt2img_paste}, None, txt2img_prompt)
diff --git a/style.css b/style.css
index d796cbe9..ec5e4182 100644
--- a/style.css
+++ b/style.css
@@ -670,6 +670,10 @@ footer {
     min-width: auto;
 }
 
+.inactive{
+    opacity: 0.5;
+}
+
 /* The following handles localization for right-to-left (RTL) languages like Arabic.
 The rtl media type will only be activated by the logic in javascript/localization.js.
 If you change anything above, you need to make sure it is RTL compliant by just running
-- 
cgit v1.2.3


From 43bb5190fc9e7ae479a5dc6640be202c9a71e464 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 9 Jan 2023 22:52:23 +0300
Subject: remove/simplify some changes from #6481

---
 modules/textual_inversion/dataset.py           | 14 +++++---------
 modules/textual_inversion/textual_inversion.py |  4 ++--
 modules/ui.py                                  |  2 +-
 3 files changed, 8 insertions(+), 12 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index bcad6848..fa48708e 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -17,7 +17,7 @@ re_numbers_at_start = re.compile(r"^[-\d]+\s*")
 
 
 class DatasetEntry:
-    def __init__(self, filename=None, filename_text=None, latent_dist=None, latent_sample=None, cond=None, cond_text=None, pixel_values=None, img_shape=None):
+    def __init__(self, filename=None, filename_text=None, latent_dist=None, latent_sample=None, cond=None, cond_text=None, pixel_values=None):
         self.filename = filename
         self.filename_text = filename_text
         self.latent_dist = latent_dist
@@ -25,7 +25,6 @@ class DatasetEntry:
         self.cond = cond
         self.cond_text = cond_text
         self.pixel_values = pixel_values
-        self.img_shape = img_shape
 
 
 class PersonalizedBase(Dataset):
@@ -46,12 +45,10 @@ class PersonalizedBase(Dataset):
         assert data_root, 'dataset directory not specified'
         assert os.path.isdir(data_root), "Dataset directory doesn't exist"
         assert os.listdir(data_root), "Dataset directory is empty"
-        if varsize:
-            assert batch_size == 1, 'variable img size must have batch size 1'
+        assert batch_size == 1 or not varsize, 'variable img size must have batch size 1'
 
         self.image_paths = [os.path.join(data_root, file_path) for file_path in os.listdir(data_root)]
 
-
         self.shuffle_tags = shuffle_tags
         self.tag_drop_out = tag_drop_out
 
@@ -91,14 +88,14 @@ class PersonalizedBase(Dataset):
             if latent_sampling_method == "once" or (latent_sampling_method == "deterministic" and not isinstance(latent_dist, DiagonalGaussianDistribution)):
                 latent_sample = model.get_first_stage_encoding(latent_dist).squeeze().to(devices.cpu)
                 latent_sampling_method = "once"
-                entry = DatasetEntry(filename=path, filename_text=filename_text, latent_sample=latent_sample, img_shape=image.size)
+                entry = DatasetEntry(filename=path, filename_text=filename_text, latent_sample=latent_sample)
             elif latent_sampling_method == "deterministic":
                 # Works only for DiagonalGaussianDistribution
                 latent_dist.std = 0
                 latent_sample = model.get_first_stage_encoding(latent_dist).squeeze().to(devices.cpu)
-                entry = DatasetEntry(filename=path, filename_text=filename_text, latent_sample=latent_sample, img_shape=image.size)
+                entry = DatasetEntry(filename=path, filename_text=filename_text, latent_sample=latent_sample)
             elif latent_sampling_method == "random":
-                entry = DatasetEntry(filename=path, filename_text=filename_text, latent_dist=latent_dist, img_shape=image.size)
+                entry = DatasetEntry(filename=path, filename_text=filename_text, latent_dist=latent_dist)
 
             if not (self.tag_drop_out != 0 or self.shuffle_tags):
                 entry.cond_text = self.create_text(filename_text)
@@ -154,7 +151,6 @@ class BatchLoader:
         self.cond_text = [entry.cond_text for entry in data]
         self.cond = [entry.cond for entry in data]
         self.latent_sample = torch.stack([entry.latent_sample for entry in data]).squeeze(1)
-        self.img_shape = [entry.img_shape for entry in data]
         #self.emb_index = [entry.emb_index for entry in data]
         #print(self.latent_sample.device)
 
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index ad76297e..14be2c96 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -492,8 +492,8 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_
                     else:
                         p.prompt = batch.cond_text[0]
                         p.steps = 20
-                        p.width = batch.img_shape[0][0]
-                        p.height = batch.img_shape[0][1]
+                        p.width = training_width
+                        p.height = training_height
 
                     preview_text = p.prompt
 
diff --git a/modules/ui.py b/modules/ui.py
index 9d6b141e..ddfe1b1a 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1348,7 +1348,7 @@ def create_ui():
                     template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"), elem_id="train_template_file")
                     training_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_training_width")
                     training_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_training_height")
-                    varsize = gr.Checkbox(label="Ignore dimension settings and do not resize images", value=False, elem_id="train_varsize")
+                    varsize = gr.Checkbox(label="Do not resize images", value=False, elem_id="train_varsize")
                     steps = gr.Number(label='Max steps', value=100000, precision=0, elem_id="train_steps")
 
                     with FormRow():
-- 
cgit v1.2.3


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

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

(limited to 'modules/ui.py')

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 32c67ccc..ea3f1db9 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -24,6 +24,7 @@ from statistics import stdev, mean
 
 optimizer_dict = {optim_name : cls_obj for optim_name, cls_obj in inspect.getmembers(torch.optim, inspect.isclass) if optim_name != "Optimizer"}
 
+
 class HypernetworkModule(torch.nn.Module):
     multiplier = 1.0
     activation_dict = {
@@ -403,13 +404,15 @@ def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None,
     shared.reload_hypernetworks()
 
 
-def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_hypernetwork_every, template_file, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
+def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_hypernetwork_every, template_filename, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
     # images allows training previews to have infotext. Importing it at the top causes a circular import problem.
     from modules import images
 
     save_hypernetwork_every = save_hypernetwork_every or 0
     create_image_every = create_image_every or 0
-    textual_inversion.validate_train_inputs(hypernetwork_name, learn_rate, batch_size, gradient_step, data_root, template_file, steps, save_hypernetwork_every, create_image_every, log_directory, name="hypernetwork")
+    template_file = textual_inversion.textual_inversion_templates.get(template_filename, None)
+    textual_inversion.validate_train_inputs(hypernetwork_name, learn_rate, batch_size, gradient_step, data_root, template_file, template_filename, steps, save_hypernetwork_every, create_image_every, log_directory, name="hypernetwork")
+    template_file = template_file.path
 
     path = shared.hypernetworks.get(hypernetwork_name, None)
     shared.loaded_hypernetwork = Hypernetwork()
diff --git a/modules/shared.py b/modules/shared.py
index a1e10201..aa37c8ce 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -33,6 +33,7 @@ parser.add_argument("--no-half-vae", action='store_true', help="do not switch th
 parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware acceleration in browser)")
 parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI")
 parser.add_argument("--embeddings-dir", type=str, default=os.path.join(script_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)")
+parser.add_argument("--textual-inversion-templates-dir", type=str, default=os.path.join(script_path, 'textual_inversion_templates'), help="directory with textual inversion templates")
 parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_path, 'hypernetworks'), help="hypernetwork directory")
 parser.add_argument("--localizations-dir", type=str, default=os.path.join(script_path, 'localizations'), help="localizations directory")
 parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui")
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 14be2c96..5420903f 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -2,6 +2,7 @@ import os
 import sys
 import traceback
 import inspect
+from collections import namedtuple
 
 import torch
 import tqdm
@@ -15,12 +16,26 @@ from modules import shared, devices, sd_hijack, processing, sd_models, images, s
 import modules.textual_inversion.dataset
 from modules.textual_inversion.learn_schedule import LearnRateScheduler
 
-from modules.textual_inversion.image_embedding import (embedding_to_b64, embedding_from_b64,
-                                                       insert_image_data_embed, extract_image_data_embed,
-                                                       caption_image_overlay)
+from modules.textual_inversion.image_embedding import embedding_to_b64, embedding_from_b64, insert_image_data_embed, extract_image_data_embed, caption_image_overlay
 from modules.textual_inversion.logging import save_settings_to_file
 
 
+TextualInversionTemplate = namedtuple("TextualInversionTemplate", ["name", "path"])
+textual_inversion_templates = {}
+
+
+def list_textual_inversion_templates():
+    textual_inversion_templates.clear()
+
+    for root, dirs, fns in os.walk(shared.cmd_opts.textual_inversion_templates_dir):
+        for fn in fns:
+            path = os.path.join(root, fn)
+
+            textual_inversion_templates[fn] = TextualInversionTemplate(fn, path)
+
+    return textual_inversion_templates
+
+
 class Embedding:
     def __init__(self, vec, name, step=None):
         self.vec = vec
@@ -274,7 +289,7 @@ def write_loss(log_directory, filename, step, epoch_len, values):
         })
 
 
-def validate_train_inputs(model_name, learn_rate, batch_size, gradient_step, data_root, template_file, steps, save_model_every, create_image_every, log_directory, name="embedding"):
+def validate_train_inputs(model_name, learn_rate, batch_size, gradient_step, data_root, template_file, template_filename, steps, save_model_every, create_image_every, log_directory, name="embedding"):
     assert model_name, f"{name} not selected"
     assert learn_rate, "Learning rate is empty or 0"
     assert isinstance(batch_size, int), "Batch size must be integer"
@@ -284,8 +299,9 @@ def validate_train_inputs(model_name, learn_rate, batch_size, gradient_step, dat
     assert data_root, "Dataset directory is empty"
     assert os.path.isdir(data_root), "Dataset directory doesn't exist"
     assert os.listdir(data_root), "Dataset directory is empty"
-    assert template_file, "Prompt template file is empty"
-    assert os.path.isfile(template_file), "Prompt template file doesn't exist"
+    assert template_filename, "Prompt template file not selected"
+    assert template_file, f"Prompt template file {template_filename} not found"
+    assert os.path.isfile(template_file.path), f"Prompt template file {template_filename} doesn't exist"
     assert steps, "Max steps is empty or 0"
     assert isinstance(steps, int), "Max steps must be integer"
     assert steps > 0, "Max steps must be positive"
@@ -296,10 +312,13 @@ def validate_train_inputs(model_name, learn_rate, batch_size, gradient_step, dat
     if save_model_every or create_image_every:
         assert log_directory, "Log directory is empty"
 
-def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
+
+def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_embedding_every, template_filename, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
     save_embedding_every = save_embedding_every or 0
     create_image_every = create_image_every or 0
-    validate_train_inputs(embedding_name, learn_rate, batch_size, gradient_step, data_root, template_file, steps, save_embedding_every, create_image_every, log_directory, name="embedding")
+    template_file = textual_inversion_templates.get(template_filename, None)
+    validate_train_inputs(embedding_name, learn_rate, batch_size, gradient_step, data_root, template_file, template_filename, steps, save_embedding_every, create_image_every, log_directory, name="embedding")
+    template_file = template_file.path
 
     shared.state.job = "train-embedding"
     shared.state.textinfo = "Initializing textual inversion training..."
diff --git a/modules/ui.py b/modules/ui.py
index ddfe1b1a..b6079aec 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -37,7 +37,7 @@ from modules import prompt_parser
 from modules.images import save_image
 from modules.sd_hijack import model_hijack
 from modules.sd_samplers import samplers, samplers_for_img2img
-import modules.textual_inversion.ui
+from modules.textual_inversion import textual_inversion
 import modules.hypernetworks.ui
 from modules.generation_parameters_copypaste import image_from_url_text
 
@@ -1322,6 +1322,9 @@ def create_ui():
                         outputs=[process_focal_crop_row],
                     )
 
+                def get_textual_inversion_template_names():
+                    return sorted([x for x in textual_inversion.textual_inversion_templates])
+
                 with gr.Tab(label="Train"):
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images <a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\" style=\"font-weight:bold;\">[wiki]</a></p>")
                     with FormRow():
@@ -1345,7 +1348,11 @@ def create_ui():
 
                     dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images", elem_id="train_dataset_directory")
                     log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion", elem_id="train_log_directory")
-                    template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"), elem_id="train_template_file")
+
+                    with FormRow():
+                        template_file = gr.Dropdown(label='Prompt template', value="style_filewords.txt", elem_id="train_template_file", choices=get_textual_inversion_template_names())
+                        create_refresh_button(template_file, textual_inversion.list_textual_inversion_templates, lambda: {"choices": get_textual_inversion_template_names()}, "refrsh_train_template_file")
+
                     training_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_training_width")
                     training_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_training_height")
                     varsize = gr.Checkbox(label="Do not resize images", value=False, elem_id="train_varsize")
diff --git a/webui.py b/webui.py
index 8737e593..47d372c7 100644
--- a/webui.py
+++ b/webui.py
@@ -33,6 +33,7 @@ import modules.sd_models
 import modules.sd_vae
 import modules.txt2img
 import modules.script_callbacks
+import modules.textual_inversion.textual_inversion
 
 import modules.ui
 from modules import modelloader
@@ -67,6 +68,8 @@ def initialize():
 
     modules.sd_vae.refresh_vae_list()
 
+    modules.textual_inversion.textual_inversion.list_textual_inversion_templates()
+
     try:
         modules.sd_models.load_model()
     except Exception as e:
-- 
cgit v1.2.3


From a4a5475cfa3c68af6cb046081002a72f862ce4be Mon Sep 17 00:00:00 2001
From: aria1th <35677394+aria1th@users.noreply.github.com>
Date: Tue, 10 Jan 2023 14:56:57 +0900
Subject: Variable dropout rate

Implements variable dropout rate from #4549

Fixes hypernetwork multiplier being able to modified during training, also fixes user-errors by setting multiplier value to lower values for training.

Changes function name to match torch.nn.module standard

Fixes RNG reset issue when generating previews by restoring RNG state
---
 modules/hypernetworks/hypernetwork.py | 101 +++++++++++++++++++++++++---------
 modules/hypernetworks/ui.py           |   4 +-
 modules/ui.py                         |   4 +-
 3 files changed, 81 insertions(+), 28 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index ea3f1db9..300d3975 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -39,7 +39,7 @@ class HypernetworkModule(torch.nn.Module):
     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, activate_output=False, last_layer_dropout=False):
+                 add_layer_norm=False, activate_output=False, dropout_structure=None):
         super().__init__()
 
         assert layer_structure is not None, "layer_structure must not be None"
@@ -64,9 +64,12 @@ class HypernetworkModule(torch.nn.Module):
             if add_layer_norm:
                 linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i+1])))
 
-            # Add dropout except last layer
-            if use_dropout and (i < len(layer_structure) - 3 or last_layer_dropout and i < len(layer_structure) - 2):
-                linears.append(torch.nn.Dropout(p=0.3))
+            # Everything should be now parsed into dropout structure, and applied here.
+            # Since we only have dropouts after layers, dropout structure should start with 0 and end with 0.
+            if dropout_structure is not None and dropout_structure[i+1] > 0:
+                assert 0 < dropout_structure[i+1] < 1, "Dropout probability should be 0 or float between 0 and 1!"
+                linears.append(torch.nn.Dropout(p=dropout_structure[i+1]))
+            # Code explanation : [1, 2, 1] -> dropout is missing when last_layer_dropout is false. [1, 2, 2, 1] -> [0, 0.3, 0, 0], when its True, [0, 0.3, 0.3, 0].
 
         self.linear = torch.nn.Sequential(*linears)
 
@@ -113,7 +116,7 @@ class HypernetworkModule(torch.nn.Module):
             state_dict[to] = x
 
     def forward(self, x):
-        return x + self.linear(x) * self.multiplier
+        return x + self.linear(x) * (HypernetworkModule.multiplier if not self.training else 1)
 
     def trainables(self):
         layer_structure = []
@@ -126,6 +129,21 @@ class HypernetworkModule(torch.nn.Module):
 def apply_strength(value=None):
     HypernetworkModule.multiplier = value if value is not None else shared.opts.sd_hypernetwork_strength
 
+#param layer_structure : sequence used for length, use_dropout : controlling boolean, last_layer_dropout : for compatibility check.
+def parse_dropout_structure(layer_structure, use_dropout, last_layer_dropout):
+    if layer_structure is None:
+        layer_structure = [1, 2, 1]
+    if not use_dropout:
+        return [0] * len(layer_structure)
+    dropout_values = [0]
+    dropout_values.extend([0.3] * (len(layer_structure) - 3))
+    if last_layer_dropout:
+        dropout_values.append(0.3)
+    else:
+        dropout_values.append(0)
+    dropout_values.append(0)
+    return dropout_values
+
 
 class Hypernetwork:
     filename = None
@@ -144,18 +162,22 @@ class Hypernetwork:
         self.add_layer_norm = add_layer_norm
         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.last_layer_dropout = kwargs.get('last_layer_dropout', True)
+        self.dropout_structure = kwargs.get('dropout_structure', None)
+        if self.dropout_structure is None:
+            self.dropout_structure = parse_dropout_structure(self.layer_structure, self.use_dropout, self.last_layer_dropout)
         self.optimizer_name = None
         self.optimizer_state_dict = None
+        self.optional_info = 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, self.activate_output, last_layer_dropout=self.last_layer_dropout),
+                                   self.add_layer_norm, self.activate_output, dropout_structure=self.dropout_structure),
                 HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init,
-                                   self.add_layer_norm, self.use_dropout, self.activate_output, last_layer_dropout=self.last_layer_dropout),
+                                   self.add_layer_norm, self.activate_output, dropout_structure=self.dropout_structure),
             )
-        self.eval_mode()
+        self.eval()
 
     def weights(self):
         res = []
@@ -164,14 +186,14 @@ class Hypernetwork:
                 res += layer.parameters()
         return res
 
-    def train_mode(self):
+    def train(self, mode=True):
         for k, layers in self.layers.items():
             for layer in layers:
-                layer.train()
+                layer.train(mode=mode)
                 for param in layer.parameters():
-                    param.requires_grad = True
+                    param.requires_grad = mode
 
-    def eval_mode(self):
+    def eval(self):
         for k, layers in self.layers.items():
             for layer in layers:
                 layer.eval()
@@ -191,11 +213,13 @@ class Hypernetwork:
         state_dict['activation_func'] = self.activation_func
         state_dict['is_layer_norm'] = self.add_layer_norm
         state_dict['weight_initialization'] = self.weight_init
-        state_dict['use_dropout'] = self.use_dropout
         state_dict['sd_checkpoint'] = self.sd_checkpoint
         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
+        state_dict['use_dropout'] = self.use_dropout
+        state_dict['dropout_structure'] = self.dropout_structure
+        state_dict['last_layer_dropout'] = (self.dropout_structure[-2] != 0) if self.dropout_structure is not None else self.last_layer_dropout
+        state_dict['optional_info'] = self.optional_info if self.optional_info else None
 
         if self.optimizer_name is not None:
             optimizer_saved_dict['optimizer_name'] = self.optimizer_name
@@ -215,43 +239,56 @@ class Hypernetwork:
 
         self.layer_structure = state_dict.get('layer_structure', [1, 2, 1])
         print(self.layer_structure)
+        optional_info = state_dict.get('optional_info', None)
+        if optional_info is not None:
+            print(f"INFO:\n {optional_info}\n")
+            self.optional_info = optional_info
         self.activation_func = state_dict.get('activation_func', None)
         print(f"Activation function is {self.activation_func}")
         self.weight_init = state_dict.get('weight_initialization', 'Normal')
         print(f"Weight initialization is {self.weight_init}")
         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)
+        self.dropout_structure = state_dict.get('dropout_structure', None)
+        self.use_dropout = True if self.dropout_structure is not None and any(self.dropout_structure) else state_dict.get('use_dropout', False)
         print(f"Dropout usage is set to {self.use_dropout}" )
         self.activate_output = state_dict.get('activate_output', True)
         print(f"Activate last layer is set to {self.activate_output}")
         self.last_layer_dropout = state_dict.get('last_layer_dropout', False)
+        # Dropout structure should have same length as layer structure, Every digits should be in [0,1), and last digit must be 0.
+        if self.dropout_structure is None:
+            print("Using previous dropout structure")
+            self.dropout_structure = parse_dropout_structure(self.layer_structure, self.use_dropout, self.last_layer_dropout)
+        print(f"Dropout structure is set to {self.dropout_structure}")
 
         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:
+            self.optimizer_name = optimizer_saved_dict.get('optimizer_name', 'AdamW')
             print("Loaded existing optimizer from checkpoint")
+            print(f"Optimizer name is {self.optimizer_name}")
         else:
+            self.optimizer_name = "AdamW"
             print("No saved optimizer exists in checkpoint")
 
         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, self.activate_output, last_layer_dropout=self.last_layer_dropout),
+                                       self.add_layer_norm, self.activate_output, self.dropout_structure),
                     HypernetworkModule(size, sd[1], self.layer_structure, self.activation_func, self.weight_init,
-                                       self.add_layer_norm, self.use_dropout, self.activate_output, last_layer_dropout=self.last_layer_dropout),
+                                       self.add_layer_norm, self.activate_output, self.dropout_structure),
                 )
 
         self.name = state_dict.get('name', self.name)
         self.step = state_dict.get('step', 0)
         self.sd_checkpoint = state_dict.get('sd_checkpoint', None)
         self.sd_checkpoint_name = state_dict.get('sd_checkpoint_name', None)
+        self.eval()
 
 
 def list_hypernetworks(path):
@@ -379,9 +416,10 @@ def report_statistics(loss_info:dict):
             print(e)
 
 
-def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False):
+def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False, dropout_structure=None):
     # Remove illegal characters from name.
     name = "".join( x for x in name if (x.isalnum() or x in "._- "))
+    assert name, "Name cannot be empty!"
 
     fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt")
     if not overwrite_old:
@@ -390,6 +428,11 @@ def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None,
     if type(layer_structure) == str:
         layer_structure = [float(x.strip()) for x in layer_structure.split(",")]
 
+    if use_dropout and dropout_structure and type(dropout_structure) == str:
+        dropout_structure = [float(x.strip()) for x in dropout_structure.split(",")]
+    else:
+        dropout_structure = [0] * len(layer_structure)
+
     hypernet = modules.hypernetworks.hypernetwork.Hypernetwork(
         name=name,
         enable_sizes=[int(x) for x in enable_sizes],
@@ -398,6 +441,7 @@ def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None,
         weight_init=weight_init,
         add_layer_norm=add_layer_norm,
         use_dropout=use_dropout,
+        dropout_structure=dropout_structure
     )
     hypernet.save(fn)
 
@@ -480,7 +524,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step,
         shared.sd_model.first_stage_model.to(devices.cpu)
 
     weights = hypernetwork.weights()
-    hypernetwork.train_mode()
+    hypernetwork.train()
 
     # Here we use optimizer from saved HN, or we can specify as UI option.
     if hypernetwork.optimizer_name in optimizer_dict:
@@ -594,7 +638,11 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step,
                 if images_dir is not None and steps_done % create_image_every == 0:
                     forced_filename = f'{hypernetwork_name}-{steps_done}'
                     last_saved_image = os.path.join(images_dir, forced_filename)
-                    hypernetwork.eval_mode()
+                    hypernetwork.eval()
+                    rng_state = torch.get_rng_state()
+                    cuda_rng_state = None
+                    if torch.cuda.is_available():
+                        cuda_rng_state = torch.cuda.get_rng_state_all()
                     shared.sd_model.cond_stage_model.to(devices.device)
                     shared.sd_model.first_stage_model.to(devices.device)
 
@@ -627,7 +675,10 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step,
                     if unload:
                         shared.sd_model.cond_stage_model.to(devices.cpu)
                         shared.sd_model.first_stage_model.to(devices.cpu)
-                    hypernetwork.train_mode()
+                    torch.set_rng_state(rng_state)
+                    if torch.cuda.is_available():
+                        torch.cuda.set_rng_state_all(cuda_rng_state)
+                    hypernetwork.train()
                     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)
@@ -649,7 +700,7 @@ Last saved image: {html.escape(last_saved_image)}<br/>
     finally:
         pbar.leave = False
         pbar.close()
-        hypernetwork.eval_mode()
+        hypernetwork.eval()
         #report_statistics(loss_dict)
 
     filename = os.path.join(shared.cmd_opts.hypernetwork_dir, f'{hypernetwork_name}.pt')
diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py
index e7f9e593..81e3f519 100644
--- a/modules/hypernetworks/ui.py
+++ b/modules/hypernetworks/ui.py
@@ -9,8 +9,8 @@ from modules import devices, sd_hijack, shared
 not_available = ["hardswish", "multiheadattention"]
 keys = list(x for x in modules.hypernetworks.hypernetwork.HypernetworkModule.activation_dict.keys() if x not in not_available)
 
-def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False):
-    filename = modules.hypernetworks.hypernetwork.create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure, activation_func, weight_init, add_layer_norm, use_dropout)
+def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False, dropout_structure=None):
+    filename = modules.hypernetworks.hypernetwork.create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure, activation_func, weight_init, add_layer_norm, use_dropout, dropout_structure)
 
     return gr.Dropdown.update(choices=sorted([x for x in shared.hypernetworks.keys()])), f"Created: {filename}", ""
 
diff --git a/modules/ui.py b/modules/ui.py
index b6079aec..9b9081b5 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1268,6 +1268,7 @@ def create_ui():
                     new_hypernetwork_initialization_option = gr.Dropdown(value = "Normal", label="Select Layer weights initialization. Recommended: Kaiming for relu-like, Xavier for sigmoid-like, Normal otherwise", choices=["Normal", "KaimingUniform", "KaimingNormal", "XavierUniform", "XavierNormal"], elem_id="train_new_hypernetwork_initialization_option")
                     new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization", elem_id="train_new_hypernetwork_add_layer_norm")
                     new_hypernetwork_use_dropout = gr.Checkbox(label="Use dropout", elem_id="train_new_hypernetwork_use_dropout")
+                    new_hypernetwork_dropout_structure = gr.Textbox("0, 0, 0", label="Enter hypernetwork Dropout structure (or empty). Recommended : 0~0.35 incrementing sequence: 0, 0.05, 0.15", placeholder="1st and last digit must be 0 and values should be between 0 and 1. ex:'0, 0.01, 0'")
                     overwrite_old_hypernetwork = gr.Checkbox(value=False, label="Overwrite Old Hypernetwork", elem_id="train_overwrite_old_hypernetwork")
 
                     with gr.Row():
@@ -1414,7 +1415,8 @@ def create_ui():
                 new_hypernetwork_activation_func,
                 new_hypernetwork_initialization_option,
                 new_hypernetwork_add_layer_norm,
-                new_hypernetwork_use_dropout
+                new_hypernetwork_use_dropout,
+                new_hypernetwork_dropout_structure
             ],
             outputs=[
                 train_hypernetwork_name,
-- 
cgit v1.2.3


From 27ea6949d3206c9a52fa77db587bac0012cb0b52 Mon Sep 17 00:00:00 2001
From: Andrey <16777216c@gmail.com>
Date: Tue, 10 Jan 2023 11:54:48 +0300
Subject: Split history ui.py to ui_progress.py

---
 modules/temp  | 1928 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 modules/ui.py | 1928 ---------------------------------------------------------
 2 files changed, 1928 insertions(+), 1928 deletions(-)
 create mode 100644 modules/temp
 delete mode 100644 modules/ui.py

(limited to 'modules/ui.py')

diff --git a/modules/temp b/modules/temp
new file mode 100644
index 00000000..9b9081b5
--- /dev/null
+++ b/modules/temp
@@ -0,0 +1,1928 @@
+import html
+import json
+import math
+import mimetypes
+import os
+import platform
+import random
+import subprocess as sp
+import sys
+import tempfile
+import time
+import traceback
+from functools import partial, reduce
+
+import gradio as gr
+import gradio.routes
+import gradio.utils
+import numpy as np
+from PIL import Image, PngImagePlugin
+from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
+
+from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru
+from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
+from modules.paths import script_path
+
+from modules.shared import opts, cmd_opts, restricted_opts
+
+import modules.codeformer_model
+import modules.generation_parameters_copypaste as parameters_copypaste
+import modules.gfpgan_model
+import modules.hypernetworks.ui
+import modules.scripts
+import modules.shared as shared
+import modules.styles
+import modules.textual_inversion.ui
+from modules import prompt_parser
+from modules.images import save_image
+from modules.sd_hijack import model_hijack
+from modules.sd_samplers import samplers, samplers_for_img2img
+from modules.textual_inversion import textual_inversion
+import modules.hypernetworks.ui
+from modules.generation_parameters_copypaste import image_from_url_text
+
+# this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI
+mimetypes.init()
+mimetypes.add_type('application/javascript', '.js')
+
+if not cmd_opts.share and not cmd_opts.listen:
+    # fix gradio phoning home
+    gradio.utils.version_check = lambda: None
+    gradio.utils.get_local_ip_address = lambda: '127.0.0.1'
+
+if cmd_opts.ngrok is not None:
+    import modules.ngrok as ngrok
+    print('ngrok authtoken detected, trying to connect...')
+    ngrok.connect(
+        cmd_opts.ngrok,
+        cmd_opts.port if cmd_opts.port is not None else 7860,
+        cmd_opts.ngrok_region
+        )
+
+
+def gr_show(visible=True):
+    return {"visible": visible, "__type__": "update"}
+
+
+sample_img2img = "assets/stable-samples/img2img/sketch-mountains-input.jpg"
+sample_img2img = sample_img2img if os.path.exists(sample_img2img) else None
+
+css_hide_progressbar = """
+.wrap .m-12 svg { display:none!important; }
+.wrap .m-12::before { content:"Loading..." }
+.wrap .z-20 svg { display:none!important; }
+.wrap .z-20::before { content:"Loading..." }
+.progress-bar { display:none!important; }
+.meta-text { display:none!important; }
+.meta-text-center { display:none!important; }
+"""
+
+# Using constants for these since the variation selector isn't visible.
+# Important that they exactly match script.js for tooltip to work.
+random_symbol = '\U0001f3b2\ufe0f'  # 🎲️
+reuse_symbol = '\u267b\ufe0f'  # ♻️
+paste_symbol = '\u2199\ufe0f'  # ↙
+folder_symbol = '\U0001f4c2'  # 📂
+refresh_symbol = '\U0001f504'  # 🔄
+save_style_symbol = '\U0001f4be'  # 💾
+apply_style_symbol = '\U0001f4cb'  # 📋
+clear_prompt_symbol = '\U0001F5D1'  # 🗑️
+
+
+def plaintext_to_html(text):
+    text = "<p>" + "<br>\n".join([f"{html.escape(x)}" for x in text.split('\n')]) + "</p>"
+    return text
+
+def send_gradio_gallery_to_image(x):
+    if len(x) == 0:
+        return None
+    return image_from_url_text(x[0])
+
+def save_files(js_data, images, do_make_zip, index):
+    import csv
+    filenames = []
+    fullfns = []
+
+    #quick dictionary to class object conversion. Its necessary due apply_filename_pattern requiring it
+    class MyObject:
+        def __init__(self, d=None):
+            if d is not None:
+                for key, value in d.items():
+                    setattr(self, key, value)
+
+    data = json.loads(js_data)
+
+    p = MyObject(data)
+    path = opts.outdir_save
+    save_to_dirs = opts.use_save_to_dirs_for_ui
+    extension: str = opts.samples_format
+    start_index = 0
+
+    if index > -1 and opts.save_selected_only and (index >= data["index_of_first_image"]):  # ensures we are looking at a specific non-grid picture, and we have save_selected_only
+
+        images = [images[index]]
+        start_index = index
+
+    os.makedirs(opts.outdir_save, exist_ok=True)
+
+    with open(os.path.join(opts.outdir_save, "log.csv"), "a", encoding="utf8", newline='') as file:
+        at_start = file.tell() == 0
+        writer = csv.writer(file)
+        if at_start:
+            writer.writerow(["prompt", "seed", "width", "height", "sampler", "cfgs", "steps", "filename", "negative_prompt"])
+
+        for image_index, filedata in enumerate(images, start_index):
+            image = image_from_url_text(filedata)
+
+            is_grid = image_index < p.index_of_first_image
+            i = 0 if is_grid else (image_index - p.index_of_first_image)
+
+            fullfn, txt_fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
+
+            filename = os.path.relpath(fullfn, path)
+            filenames.append(filename)
+            fullfns.append(fullfn)
+            if txt_fullfn:
+                filenames.append(os.path.basename(txt_fullfn))
+                fullfns.append(txt_fullfn)
+
+        writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler_name"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]])
+
+    # Make Zip
+    if do_make_zip:
+        zip_filepath = os.path.join(path, "images.zip")
+
+        from zipfile import ZipFile
+        with ZipFile(zip_filepath, "w") as zip_file:
+            for i in range(len(fullfns)):
+                with open(fullfns[i], mode="rb") as f:
+                    zip_file.writestr(filenames[i], f.read())
+        fullfns.insert(0, zip_filepath)
+
+    return gr.File.update(value=fullfns, visible=True), plaintext_to_html(f"Saved: {filenames[0]}")
+
+
+def calc_time_left(progress, threshold, label, force_display, show_eta):
+    if progress == 0:
+        return ""
+    else:
+        time_since_start = time.time() - shared.state.time_start
+        eta = (time_since_start/progress)
+        eta_relative = eta-time_since_start
+        if (eta_relative > threshold and show_eta) or force_display:
+            if eta_relative > 3600:
+                return label + time.strftime('%H:%M:%S', time.gmtime(eta_relative))
+            elif eta_relative > 60:
+                return label + time.strftime('%M:%S',  time.gmtime(eta_relative))
+            else:
+                return label + time.strftime('%Ss',  time.gmtime(eta_relative))
+        else:
+            return ""
+
+
+def check_progress_call(id_part):
+    if shared.state.job_count == 0:
+        return "", gr_show(False), gr_show(False), gr_show(False)
+
+    progress = 0
+
+    if shared.state.job_count > 0:
+        progress += shared.state.job_no / shared.state.job_count
+    if shared.state.sampling_steps > 0:
+        progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps
+
+    # Show progress percentage and time left at the same moment, and base it also on steps done
+    show_eta = progress >= 0.01 or shared.state.sampling_step >= 10
+
+    time_left = calc_time_left(progress, 1, " ETA: ", shared.state.time_left_force_display, show_eta)
+    if time_left != "":
+        shared.state.time_left_force_display = True
+
+    progress = min(progress, 1)
+
+    progressbar = ""
+    if opts.show_progressbar:
+        progressbar = f"""<div class='progressDiv'><div class='progress' style="overflow:visible;width:{progress * 100}%;white-space:nowrap;">{"&nbsp;" * 2 + str(int(progress*100))+"%" + time_left if show_eta else ""}</div></div>"""
+
+    image = gr_show(False)
+    preview_visibility = gr_show(False)
+
+    if opts.show_progress_every_n_steps != 0:
+        shared.state.set_current_image()
+        image = shared.state.current_image
+
+        if image is None:
+            image = gr.update(value=None)
+        else:
+            preview_visibility = gr_show(True)
+
+    if shared.state.textinfo is not None:
+        textinfo_result = gr.HTML.update(value=shared.state.textinfo, visible=True)
+    else:
+        textinfo_result = gr_show(False)
+
+    return f"<span id='{id_part}_progress_span' style='display: none'>{time.time()}</span><p>{progressbar}</p>", preview_visibility, image, textinfo_result
+
+
+def check_progress_call_initial(id_part):
+    shared.state.job_count = -1
+    shared.state.current_latent = None
+    shared.state.current_image = None
+    shared.state.textinfo = None
+    shared.state.time_start = time.time()
+    shared.state.time_left_force_display = False
+
+    return check_progress_call(id_part)
+
+
+def visit(x, func, path=""):
+    if hasattr(x, 'children'):
+        for c in x.children:
+            visit(c, func, path)
+    elif x.label is not None:
+        func(path + "/" + str(x.label), x)
+
+
+def add_style(name: str, prompt: str, negative_prompt: str):
+    if name is None:
+        return [gr_show() for x in range(4)]
+
+    style = modules.styles.PromptStyle(name, prompt, negative_prompt)
+    shared.prompt_styles.styles[style.name] = style
+    # Save all loaded prompt styles: this allows us to update the storage format in the future more easily, because we
+    # reserialize all styles every time we save them
+    shared.prompt_styles.save_styles(shared.styles_filename)
+
+    return [gr.Dropdown.update(visible=True, choices=list(shared.prompt_styles.styles)) for _ in range(4)]
+
+
+def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resize_y):
+    from modules import processing, devices
+
+    if not enable:
+        return ""
+
+    p = processing.StableDiffusionProcessingTxt2Img(width=width, height=height, enable_hr=True, hr_scale=hr_scale, hr_resize_x=hr_resize_x, hr_resize_y=hr_resize_y)
+
+    with devices.autocast():
+        p.init([""], [0], [0])
+
+    return f"resize: from <span class='resolution'>{p.width}x{p.height}</span> to <span class='resolution'>{p.hr_resize_x or p.hr_upscale_to_x}x{p.hr_resize_y or p.hr_upscale_to_y}</span>"
+
+
+def apply_styles(prompt, prompt_neg, style1_name, style2_name):
+    prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, [style1_name, style2_name])
+    prompt_neg = shared.prompt_styles.apply_negative_styles_to_prompt(prompt_neg, [style1_name, style2_name])
+
+    return [gr.Textbox.update(value=prompt), gr.Textbox.update(value=prompt_neg), gr.Dropdown.update(value="None"), gr.Dropdown.update(value="None")]
+
+
+def interrogate(image):
+    prompt = shared.interrogator.interrogate(image.convert("RGB"))
+
+    return gr_show(True) if prompt is None else prompt
+
+
+def interrogate_deepbooru(image):
+    prompt = deepbooru.model.tag(image)
+    return gr_show(True) if prompt is None else prompt
+
+
+def create_seed_inputs(target_interface):
+    with FormRow(elem_id=target_interface + '_seed_row'):
+        seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1, elem_id=target_interface + '_seed')
+        seed.style(container=False)
+        random_seed = gr.Button(random_symbol, elem_id=target_interface + '_random_seed')
+        reuse_seed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_seed')
+
+        with gr.Group(elem_id=target_interface + '_subseed_show_box'):
+            seed_checkbox = gr.Checkbox(label='Extra', elem_id=target_interface + '_subseed_show', value=False)
+
+    # Components to show/hide based on the 'Extra' checkbox
+    seed_extras = []
+
+    with FormRow(visible=False, elem_id=target_interface + '_subseed_row') as seed_extra_row_1:
+        seed_extras.append(seed_extra_row_1)
+        subseed = gr.Number(label='Variation seed', value=-1, elem_id=target_interface + '_subseed')
+        subseed.style(container=False)
+        random_subseed = gr.Button(random_symbol, elem_id=target_interface + '_random_subseed')
+        reuse_subseed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_subseed')
+        subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=target_interface + '_subseed_strength')
+
+    with FormRow(visible=False) as seed_extra_row_2:
+        seed_extras.append(seed_extra_row_2)
+        seed_resize_from_w = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from width", value=0, elem_id=target_interface + '_seed_resize_from_w')
+        seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from height", value=0, elem_id=target_interface + '_seed_resize_from_h')
+
+    random_seed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[seed])
+    random_subseed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[subseed])
+
+    def change_visibility(show):
+        return {comp: gr_show(show) for comp in seed_extras}
+
+    seed_checkbox.change(change_visibility, show_progress=False, inputs=[seed_checkbox], outputs=seed_extras)
+
+    return seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox
+
+
+
+def connect_clear_prompt(button):
+    """Given clear button, prompt, and token_counter objects, setup clear prompt button click event"""
+    button.click(
+        _js="clear_prompt",
+        fn=None,
+        inputs=[],
+        outputs=[],
+    )
+
+
+def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: gr.Textbox, dummy_component, is_subseed):
+    """ Connects a 'reuse (sub)seed' button's click event so that it copies last used
+        (sub)seed value from generation info the to the seed field. If copying subseed and subseed strength
+        was 0, i.e. no variation seed was used, it copies the normal seed value instead."""
+    def copy_seed(gen_info_string: str, index):
+        res = -1
+
+        try:
+            gen_info = json.loads(gen_info_string)
+            index -= gen_info.get('index_of_first_image', 0)
+
+            if is_subseed and gen_info.get('subseed_strength', 0) > 0:
+                all_subseeds = gen_info.get('all_subseeds', [-1])
+                res = all_subseeds[index if 0 <= index < len(all_subseeds) else 0]
+            else:
+                all_seeds = gen_info.get('all_seeds', [-1])
+                res = all_seeds[index if 0 <= index < len(all_seeds) else 0]
+
+        except json.decoder.JSONDecodeError as e:
+            if gen_info_string != '':
+                print("Error parsing JSON generation info:", file=sys.stderr)
+                print(gen_info_string, file=sys.stderr)
+
+        return [res, gr_show(False)]
+
+    reuse_seed.click(
+        fn=copy_seed,
+        _js="(x, y) => [x, selected_gallery_index()]",
+        show_progress=False,
+        inputs=[generation_info, dummy_component],
+        outputs=[seed, dummy_component]
+    )
+
+
+def update_token_counter(text, steps):
+    try:
+        _, prompt_flat_list, _ = prompt_parser.get_multicond_prompt_list([text])
+        prompt_schedules = prompt_parser.get_learned_conditioning_prompt_schedules(prompt_flat_list, steps)
+
+    except Exception:
+        # a parsing error can happen here during typing, and we don't want to bother the user with
+        # messages related to it in console
+        prompt_schedules = [[[steps, text]]]
+
+    flat_prompts = reduce(lambda list1, list2: list1+list2, prompt_schedules)
+    prompts = [prompt_text for step, prompt_text in flat_prompts]
+    token_count, max_length = max([model_hijack.get_prompt_lengths(prompt) for prompt in prompts], key=lambda args: args[0])
+    style_class = ' class="red"' if (token_count > max_length) else ""
+    return f"<span {style_class}>{token_count}/{max_length}</span>"
+
+
+def create_toprow(is_img2img):
+    id_part = "img2img" if is_img2img else "txt2img"
+
+    with gr.Row(elem_id="toprow"):
+        with gr.Column(scale=6):
+            with gr.Row():
+                with gr.Column(scale=80):
+                    with gr.Row():
+                        prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=2,
+                            placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)"
+                        )
+
+            with gr.Row():
+                with gr.Column(scale=80):
+                    with gr.Row():
+                        negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2,
+                            placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)"
+                        )
+
+        with gr.Column(scale=1, elem_id="roll_col"):
+            paste = gr.Button(value=paste_symbol, elem_id="paste")
+            save_style = gr.Button(value=save_style_symbol, elem_id="style_create")
+            prompt_style_apply = gr.Button(value=apply_style_symbol, elem_id="style_apply")
+            clear_prompt_button = gr.Button(value=clear_prompt_symbol, elem_id=f"{id_part}_clear_prompt")
+            token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_token_counter")
+            token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button")
+
+            clear_prompt_button.click(
+                fn=lambda *x: x,
+                _js="confirm_clear_prompt",
+                inputs=[prompt, negative_prompt],
+                outputs=[prompt, negative_prompt],
+            )
+
+        button_interrogate = None
+        button_deepbooru = None
+        if is_img2img:
+            with gr.Column(scale=1, elem_id="interrogate_col"):
+                button_interrogate = gr.Button('Interrogate\nCLIP', elem_id="interrogate")
+                button_deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru")
+
+        with gr.Column(scale=1):
+            with gr.Row():
+                skip = gr.Button('Skip', elem_id=f"{id_part}_skip")
+                interrupt = gr.Button('Interrupt', elem_id=f"{id_part}_interrupt")
+                submit = gr.Button('Generate', elem_id=f"{id_part}_generate", variant='primary')
+
+                skip.click(
+                    fn=lambda: shared.state.skip(),
+                    inputs=[],
+                    outputs=[],
+                )
+
+                interrupt.click(
+                    fn=lambda: shared.state.interrupt(),
+                    inputs=[],
+                    outputs=[],
+                )
+
+            with gr.Row():
+                with gr.Column(scale=1, elem_id="style_pos_col"):
+                    prompt_style = gr.Dropdown(label="Style 1", elem_id=f"{id_part}_style_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())))
+
+                with gr.Column(scale=1, elem_id="style_neg_col"):
+                    prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())))
+
+    return prompt, prompt_style, negative_prompt, prompt_style2, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button
+
+
+def setup_progressbar(progressbar, preview, id_part, textinfo=None):
+    if textinfo is None:
+        textinfo = gr.HTML(visible=False)
+
+    check_progress = gr.Button('Check progress', elem_id=f"{id_part}_check_progress", visible=False)
+    check_progress.click(
+        fn=lambda: check_progress_call(id_part),
+        show_progress=False,
+        inputs=[],
+        outputs=[progressbar, preview, preview, textinfo],
+    )
+
+    check_progress_initial = gr.Button('Check progress (first)', elem_id=f"{id_part}_check_progress_initial", visible=False)
+    check_progress_initial.click(
+        fn=lambda: check_progress_call_initial(id_part),
+        show_progress=False,
+        inputs=[],
+        outputs=[progressbar, preview, preview, textinfo],
+    )
+
+
+def apply_setting(key, value):
+    if value is None:
+        return gr.update()
+
+    if shared.cmd_opts.freeze_settings:
+        return gr.update()
+
+    # dont allow model to be swapped when model hash exists in prompt
+    if key == "sd_model_checkpoint" and opts.disable_weights_auto_swap:
+        return gr.update()
+
+    if key == "sd_model_checkpoint":
+        ckpt_info = sd_models.get_closet_checkpoint_match(value)
+
+        if ckpt_info is not None:
+            value = ckpt_info.title
+        else:
+            return gr.update()
+
+    comp_args = opts.data_labels[key].component_args
+    if comp_args and isinstance(comp_args, dict) and comp_args.get('visible') is False:
+        return
+
+    valtype = type(opts.data_labels[key].default)
+    oldval = opts.data.get(key, None)
+    opts.data[key] = valtype(value) if valtype != type(None) else value
+    if oldval != value and opts.data_labels[key].onchange is not None:
+        opts.data_labels[key].onchange()
+
+    opts.save(shared.config_filename)
+    return value
+
+
+def update_generation_info(args):
+    generation_info, html_info, img_index = args
+    try:
+        generation_info = json.loads(generation_info)
+        if img_index < 0 or img_index >= len(generation_info["infotexts"]):
+            return html_info
+        return plaintext_to_html(generation_info["infotexts"][img_index])
+    except Exception:
+        pass
+    # if the json parse or anything else fails, just return the old html_info
+    return html_info
+
+
+def create_refresh_button(refresh_component, refresh_method, refreshed_args, elem_id):
+    def refresh():
+        refresh_method()
+        args = refreshed_args() if callable(refreshed_args) else refreshed_args
+
+        for k, v in args.items():
+            setattr(refresh_component, k, v)
+
+        return gr.update(**(args or {}))
+
+    refresh_button = ToolButton(value=refresh_symbol, elem_id=elem_id)
+    refresh_button.click(
+        fn=refresh,
+        inputs=[],
+        outputs=[refresh_component]
+    )
+    return refresh_button
+
+
+def create_output_panel(tabname, outdir):
+    def open_folder(f):
+        if not os.path.exists(f):
+            print(f'Folder "{f}" does not exist. After you create an image, the folder will be created.')
+            return
+        elif not os.path.isdir(f):
+            print(f"""
+WARNING
+An open_folder request was made with an argument that is not a folder.
+This could be an error or a malicious attempt to run code on your computer.
+Requested path was: {f}
+""", file=sys.stderr)
+            return
+
+        if not shared.cmd_opts.hide_ui_dir_config:
+            path = os.path.normpath(f)
+            if platform.system() == "Windows":
+                os.startfile(path)
+            elif platform.system() == "Darwin":
+                sp.Popen(["open", path])
+            elif "microsoft-standard-WSL2" in platform.uname().release:
+                sp.Popen(["wsl-open", path])
+            else:
+                sp.Popen(["xdg-open", path])
+
+    with gr.Column(variant='panel'):
+            with gr.Group():
+                result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery").style(grid=4)
+
+            generation_info = None
+            with gr.Column():
+                with gr.Row(elem_id=f"image_buttons_{tabname}"):
+                    open_folder_button = gr.Button(folder_symbol, elem_id="hidden_element" if shared.cmd_opts.hide_ui_dir_config else f'open_folder_{tabname}')
+
+                    if tabname != "extras":
+                        save = gr.Button('Save', elem_id=f'save_{tabname}')
+                        save_zip = gr.Button('Zip', elem_id=f'save_zip_{tabname}')
+
+                    buttons = parameters_copypaste.create_buttons(["img2img", "inpaint", "extras"])
+
+                open_folder_button.click(
+                    fn=lambda: open_folder(opts.outdir_samples or outdir),
+                    inputs=[],
+                    outputs=[],
+                )
+
+                if tabname != "extras":
+                    with gr.Row():
+                        download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False, elem_id=f'download_files_{tabname}')
+
+                    with gr.Group():
+                        html_info = gr.HTML(elem_id=f'html_info_{tabname}')
+                        html_log = gr.HTML(elem_id=f'html_log_{tabname}')
+
+                        generation_info = gr.Textbox(visible=False, elem_id=f'generation_info_{tabname}')
+                        if tabname == 'txt2img' or tabname == 'img2img':
+                            generation_info_button = gr.Button(visible=False, elem_id=f"{tabname}_generation_info_button")
+                            generation_info_button.click(
+                                fn=update_generation_info,
+                                _js="(x, y) => [x, y, selected_gallery_index()]",
+                                inputs=[generation_info, html_info],
+                                outputs=[html_info],
+                                preprocess=False
+                            )
+
+                        save.click(
+                            fn=wrap_gradio_call(save_files),
+                            _js="(x, y, z, w) => [x, y, false, selected_gallery_index()]",
+                            inputs=[
+                                generation_info,
+                                result_gallery,
+                                html_info,
+                                html_info,
+                            ],
+                            outputs=[
+                                download_files,
+                                html_log,
+                            ]
+                        )
+
+                        save_zip.click(
+                            fn=wrap_gradio_call(save_files),
+                            _js="(x, y, z, w) => [x, y, true, selected_gallery_index()]",
+                            inputs=[
+                                generation_info,
+                                result_gallery,
+                                html_info,
+                                html_info,
+                            ],
+                            outputs=[
+                                download_files,
+                                html_log,
+                            ]
+                        )
+
+                else:
+                    html_info_x = gr.HTML(elem_id=f'html_info_x_{tabname}')
+                    html_info = gr.HTML(elem_id=f'html_info_{tabname}')
+                    html_log = gr.HTML(elem_id=f'html_log_{tabname}')
+
+                parameters_copypaste.bind_buttons(buttons, result_gallery, "txt2img" if tabname == "txt2img" else None)
+                return result_gallery, generation_info if tabname != "extras" else html_info_x, html_info, html_log
+
+
+def create_sampler_and_steps_selection(choices, tabname):
+    if opts.samplers_in_dropdown:
+        with FormRow(elem_id=f"sampler_selection_{tabname}"):
+            sampler_index = gr.Dropdown(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")
+            steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling steps", value=20)
+    else:
+        with FormGroup(elem_id=f"sampler_selection_{tabname}"):
+            steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling steps", value=20)
+            sampler_index = gr.Radio(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")
+
+    return steps, sampler_index
+
+
+def ordered_ui_categories():
+    user_order = {x.strip(): i for i, x in enumerate(shared.opts.ui_reorder.split(","))}
+
+    for i, category in sorted(enumerate(shared.ui_reorder_categories), key=lambda x: user_order.get(x[1], x[0] + 1000)):
+        yield category
+
+
+def create_ui():
+    import modules.img2img
+    import modules.txt2img
+
+    reload_javascript()
+
+    parameters_copypaste.reset()
+
+    modules.scripts.scripts_current = modules.scripts.scripts_txt2img
+    modules.scripts.scripts_txt2img.initialize_scripts(is_img2img=False)
+
+    with gr.Blocks(analytics_enabled=False) as txt2img_interface:
+        txt2img_prompt, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _,txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False)
+
+        dummy_component = gr.Label(visible=False)
+        txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False)
+
+        with gr.Row(elem_id='txt2img_progress_row'):
+            with gr.Column(scale=1):
+                pass
+
+            with gr.Column(scale=1):
+                progressbar = gr.HTML(elem_id="txt2img_progressbar")
+                txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False)
+                setup_progressbar(progressbar, txt2img_preview, 'txt2img')
+
+        with gr.Row().style(equal_height=False):
+            with gr.Column(variant='panel', elem_id="txt2img_settings"):
+                for category in ordered_ui_categories():
+                    if category == "sampler":
+                        steps, sampler_index = create_sampler_and_steps_selection(samplers, "txt2img")
+
+                    elif category == "dimensions":
+                        with FormRow():
+                            with gr.Column(elem_id="txt2img_column_size", scale=4):
+                                width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="txt2img_width")
+                                height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="txt2img_height")
+
+                            if opts.dimensions_and_batch_together:
+                                with gr.Column(elem_id="txt2img_column_batch"):
+                                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
+                                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
+
+                    elif category == "cfg":
+                        cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="txt2img_cfg_scale")
+
+                    elif category == "seed":
+                        seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('txt2img')
+
+                    elif category == "checkboxes":
+                        with FormRow(elem_id="txt2img_checkboxes"):
+                            restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="txt2img_restore_faces")
+                            tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling")
+                            enable_hr = gr.Checkbox(label='Hires. fix', value=False, elem_id="txt2img_enable_hr")
+                            hr_final_resolution = FormHTML(value="", elem_id="txtimg_hr_finalres", label="Upscaled resolution", interactive=False)
+
+                    elif category == "hires_fix":
+                        with FormGroup(visible=False, elem_id="txt2img_hires_fix") as hr_options:
+                            with FormRow(elem_id="txt2img_hires_fix_row1"):
+                                hr_upscaler = gr.Dropdown(label="Upscaler", elem_id="txt2img_hr_upscaler", choices=[*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]], value=shared.latent_upscale_default_mode)
+                                hr_second_pass_steps = gr.Slider(minimum=0, maximum=150, step=1, label='Hires steps', value=0, elem_id="txt2img_hires_steps")
+                                denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7, elem_id="txt2img_denoising_strength")
+
+                            with FormRow(elem_id="txt2img_hires_fix_row2"):
+                                hr_scale = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Upscale by", value=2.0, elem_id="txt2img_hr_scale")
+                                hr_resize_x = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize width to", value=0, elem_id="txt2img_hr_resize_x")
+                                hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y")
+
+                    elif category == "batch":
+                        if not opts.dimensions_and_batch_together:
+                            with FormRow(elem_id="txt2img_column_batch"):
+                                batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
+                                batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
+
+                    elif category == "scripts":
+                        with FormGroup(elem_id="txt2img_script_container"):
+                            custom_inputs = modules.scripts.scripts_txt2img.setup_ui()
+
+            hr_resolution_preview_inputs = [enable_hr, width, height, hr_scale, hr_resize_x, hr_resize_y]
+            for input in hr_resolution_preview_inputs:
+                input.change(
+                    fn=calc_resolution_hires,
+                    inputs=hr_resolution_preview_inputs,
+                    outputs=[hr_final_resolution],
+                    show_progress=False,
+                )
+                input.change(
+                    None,
+                    _js="onCalcResolutionHires",
+                    inputs=hr_resolution_preview_inputs,
+                    outputs=[],
+                    show_progress=False,
+                )
+
+            txt2img_gallery, generation_info, html_info, html_log = create_output_panel("txt2img", opts.outdir_txt2img_samples)
+            parameters_copypaste.bind_buttons({"txt2img": txt2img_paste}, None, txt2img_prompt)
+
+            connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
+            connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
+
+            txt2img_args = dict(
+                fn=wrap_gradio_gpu_call(modules.txt2img.txt2img, extra_outputs=[None, '', '']),
+                _js="submit",
+                inputs=[
+                    txt2img_prompt,
+                    txt2img_negative_prompt,
+                    txt2img_prompt_style,
+                    txt2img_prompt_style2,
+                    steps,
+                    sampler_index,
+                    restore_faces,
+                    tiling,
+                    batch_count,
+                    batch_size,
+                    cfg_scale,
+                    seed,
+                    subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox,
+                    height,
+                    width,
+                    enable_hr,
+                    denoising_strength,
+                    hr_scale,
+                    hr_upscaler,
+                    hr_second_pass_steps,
+                    hr_resize_x,
+                    hr_resize_y,
+                ] + custom_inputs,
+
+                outputs=[
+                    txt2img_gallery,
+                    generation_info,
+                    html_info,
+                    html_log,
+                ],
+                show_progress=False,
+            )
+
+            txt2img_prompt.submit(**txt2img_args)
+            submit.click(**txt2img_args)
+
+            txt_prompt_img.change(
+                fn=modules.images.image_data,
+                inputs=[
+                    txt_prompt_img
+                ],
+                outputs=[
+                    txt2img_prompt,
+                    txt_prompt_img
+                ]
+            )
+
+            enable_hr.change(
+                fn=lambda x: gr_show(x),
+                inputs=[enable_hr],
+                outputs=[hr_options],
+                show_progress = False,
+            )
+
+            txt2img_paste_fields = [
+                (txt2img_prompt, "Prompt"),
+                (txt2img_negative_prompt, "Negative prompt"),
+                (steps, "Steps"),
+                (sampler_index, "Sampler"),
+                (restore_faces, "Face restoration"),
+                (cfg_scale, "CFG scale"),
+                (seed, "Seed"),
+                (width, "Size-1"),
+                (height, "Size-2"),
+                (batch_size, "Batch size"),
+                (subseed, "Variation seed"),
+                (subseed_strength, "Variation seed strength"),
+                (seed_resize_from_w, "Seed resize from-1"),
+                (seed_resize_from_h, "Seed resize from-2"),
+                (denoising_strength, "Denoising strength"),
+                (enable_hr, lambda d: "Denoising strength" in d),
+                (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)),
+                (hr_scale, "Hires upscale"),
+                (hr_upscaler, "Hires upscaler"),
+                (hr_second_pass_steps, "Hires steps"),
+                (hr_resize_x, "Hires resize-1"),
+                (hr_resize_y, "Hires resize-2"),
+                *modules.scripts.scripts_txt2img.infotext_fields
+            ]
+            parameters_copypaste.add_paste_fields("txt2img", None, txt2img_paste_fields)
+
+            txt2img_preview_params = [
+                txt2img_prompt,
+                txt2img_negative_prompt,
+                steps,
+                sampler_index,
+                cfg_scale,
+                seed,
+                width,
+                height,
+            ]
+
+            token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[txt2img_prompt, steps], outputs=[token_counter])
+
+    modules.scripts.scripts_current = modules.scripts.scripts_img2img
+    modules.scripts.scripts_img2img.initialize_scripts(is_img2img=True)
+
+    with gr.Blocks(analytics_enabled=False) as img2img_interface:
+        img2img_prompt, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,token_counter, token_button = create_toprow(is_img2img=True)
+
+        with gr.Row(elem_id='img2img_progress_row'):
+            img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False)
+
+            with gr.Column(scale=1):
+                pass
+
+            with gr.Column(scale=1):
+                progressbar = gr.HTML(elem_id="img2img_progressbar")
+                img2img_preview = gr.Image(elem_id='img2img_preview', visible=False)
+                setup_progressbar(progressbar, img2img_preview, 'img2img')
+
+        with FormRow().style(equal_height=False):
+            with gr.Column(variant='panel', elem_id="img2img_settings"):
+
+                with gr.Tabs(elem_id="mode_img2img") as tabs_img2img_mode:
+                    with gr.TabItem('img2img', id='img2img', elem_id="img2img_img2img_tab"):
+                        init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_img2img_tool, image_mode="RGBA").style(height=480)
+
+                    with gr.TabItem('Inpaint', id='inpaint', elem_id="img2img_inpaint_tab"):
+                        init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_inpaint_tool, image_mode="RGBA").style(height=480)
+                        init_img_with_mask_orig = gr.State(None)
+
+                        use_color_sketch = cmd_opts.gradio_inpaint_tool == "color-sketch"
+                        if use_color_sketch:
+                            def update_orig(image, state):
+                                if image is not None:
+                                    same_size = state is not None and state.size == image.size
+                                    has_exact_match = np.any(np.all(np.array(image) == np.array(state), axis=-1))
+                                    edited = same_size and has_exact_match
+                                    return image if not edited or state is None else state
+
+                            init_img_with_mask.change(update_orig, [init_img_with_mask, init_img_with_mask_orig], init_img_with_mask_orig)
+
+                        init_img_inpaint = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_base")
+                        init_mask_inpaint = gr.Image(label="Mask", source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_mask")
+
+                        with FormRow():
+                            mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id="img2img_mask_blur")
+                            mask_alpha = gr.Slider(label="Mask transparency", interactive=use_color_sketch, visible=use_color_sketch, elem_id="img2img_mask_alpha")
+
+                        with FormRow():
+                            mask_mode = gr.Radio(label="Mask source", choices=["Draw mask", "Upload mask"], type="index", value="Draw mask", elem_id="mask_mode")
+                            inpainting_mask_invert = gr.Radio(label='Mask mode', choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index", elem_id="img2img_mask_mode")
+
+                        with FormRow():
+                            inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='original', type="index", elem_id="img2img_inpainting_fill")
+
+                        with FormRow():
+                            with gr.Column():
+                                inpaint_full_res = gr.Radio(label="Inpaint area", choices=["Whole picture", "Only masked"], type="index", value="Whole picture", elem_id="img2img_inpaint_full_res")
+
+                            with gr.Column(scale=4):
+                                inpaint_full_res_padding = gr.Slider(label='Only masked padding, pixels', minimum=0, maximum=256, step=4, value=32, elem_id="img2img_inpaint_full_res_padding")
+
+                    with gr.TabItem('Batch img2img', id='batch', elem_id="img2img_batch_tab"):
+                        hidden = '<br>Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else ''
+                        gr.HTML(f"<p class=\"text-gray-500\">Process images in a directory on the same machine where the server is running.<br>Use an empty output directory to save pictures normally instead of writing to the output directory.{hidden}</p>")
+                        img2img_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, elem_id="img2img_batch_input_dir")
+                        img2img_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, elem_id="img2img_batch_output_dir")
+
+                with FormRow():
+                    resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", choices=["Just resize", "Crop and resize", "Resize and fill", "Just resize (latent upscale)"], type="index", value="Just resize")
+
+                for category in ordered_ui_categories():
+                    if category == "sampler":
+                        steps, sampler_index = create_sampler_and_steps_selection(samplers_for_img2img, "img2img")
+
+                    elif category == "dimensions":
+                        with FormRow():
+                            with gr.Column(elem_id="img2img_column_size", scale=4):
+                                width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
+                                height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
+
+                            if opts.dimensions_and_batch_together:
+                                with gr.Column(elem_id="img2img_column_batch"):
+                                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
+                                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")
+
+                    elif category == "cfg":
+                        with FormGroup():
+                            cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="img2img_cfg_scale")
+                            denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75, elem_id="img2img_denoising_strength")
+
+                    elif category == "seed":
+                        seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('img2img')
+
+                    elif category == "checkboxes":
+                        with FormRow(elem_id="img2img_checkboxes"):
+                            restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="img2img_restore_faces")
+                            tiling = gr.Checkbox(label='Tiling', value=False, elem_id="img2img_tiling")
+
+                    elif category == "batch":
+                        if not opts.dimensions_and_batch_together:
+                            with FormRow(elem_id="img2img_column_batch"):
+                                batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
+                                batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")
+
+                    elif category == "scripts":
+                        with FormGroup(elem_id="img2img_script_container"):
+                            custom_inputs = modules.scripts.scripts_img2img.setup_ui()
+
+            img2img_gallery, generation_info, html_info, html_log = create_output_panel("img2img", opts.outdir_img2img_samples)
+            parameters_copypaste.bind_buttons({"img2img": img2img_paste}, None, img2img_prompt)
+
+            connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
+            connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
+
+            img2img_prompt_img.change(
+                fn=modules.images.image_data,
+                inputs=[
+                    img2img_prompt_img
+                ],
+                outputs=[
+                    img2img_prompt,
+                    img2img_prompt_img
+                ]
+            )
+
+            mask_mode.change(
+                lambda mode, img: {
+                    init_img_with_mask: gr_show(mode == 0),
+                    init_img_inpaint: gr_show(mode == 1),
+                    init_mask_inpaint: gr_show(mode == 1),
+                },
+                inputs=[mask_mode, init_img_with_mask],
+                outputs=[
+                    init_img_with_mask,
+                    init_img_inpaint,
+                    init_mask_inpaint,
+                ],
+            )
+
+            img2img_args = dict(
+                fn=wrap_gradio_gpu_call(modules.img2img.img2img, extra_outputs=[None, '', '']),
+                _js="submit_img2img",
+                inputs=[
+                    dummy_component,
+                    img2img_prompt,
+                    img2img_negative_prompt,
+                    img2img_prompt_style,
+                    img2img_prompt_style2,
+                    init_img,
+                    init_img_with_mask,
+                    init_img_with_mask_orig,
+                    init_img_inpaint,
+                    init_mask_inpaint,
+                    mask_mode,
+                    steps,
+                    sampler_index,
+                    mask_blur,
+                    mask_alpha,
+                    inpainting_fill,
+                    restore_faces,
+                    tiling,
+                    batch_count,
+                    batch_size,
+                    cfg_scale,
+                    denoising_strength,
+                    seed,
+                    subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox,
+                    height,
+                    width,
+                    resize_mode,
+                    inpaint_full_res,
+                    inpaint_full_res_padding,
+                    inpainting_mask_invert,
+                    img2img_batch_input_dir,
+                    img2img_batch_output_dir,
+                ] + custom_inputs,
+                outputs=[
+                    img2img_gallery,
+                    generation_info,
+                    html_info,
+                    html_log,
+                ],
+                show_progress=False,
+            )
+
+            img2img_prompt.submit(**img2img_args)
+            submit.click(**img2img_args)
+
+            img2img_interrogate.click(
+                fn=interrogate,
+                inputs=[init_img],
+                outputs=[img2img_prompt],
+            )
+
+            img2img_deepbooru.click(
+                fn=interrogate_deepbooru,
+                inputs=[init_img],
+                outputs=[img2img_prompt],
+            )
+
+            prompts = [(txt2img_prompt, txt2img_negative_prompt), (img2img_prompt, img2img_negative_prompt)]
+            style_dropdowns = [(txt2img_prompt_style, txt2img_prompt_style2), (img2img_prompt_style, img2img_prompt_style2)]
+            style_js_funcs = ["update_txt2img_tokens", "update_img2img_tokens"]
+
+            for button, (prompt, negative_prompt) in zip([txt2img_save_style, img2img_save_style], prompts):
+                button.click(
+                    fn=add_style,
+                    _js="ask_for_style_name",
+                    # Have to pass empty dummy component here, because the JavaScript and Python function have to accept
+                    # the same number of parameters, but we only know the style-name after the JavaScript prompt
+                    inputs=[dummy_component, prompt, negative_prompt],
+                    outputs=[txt2img_prompt_style, img2img_prompt_style, txt2img_prompt_style2, img2img_prompt_style2],
+                )
+
+            for button, (prompt, negative_prompt), (style1, style2), js_func in zip([txt2img_prompt_style_apply, img2img_prompt_style_apply], prompts, style_dropdowns, style_js_funcs):
+                button.click(
+                    fn=apply_styles,
+                    _js=js_func,
+                    inputs=[prompt, negative_prompt, style1, style2],
+                    outputs=[prompt, negative_prompt, style1, style2],
+                )
+
+            token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter])
+
+            img2img_paste_fields = [
+                (img2img_prompt, "Prompt"),
+                (img2img_negative_prompt, "Negative prompt"),
+                (steps, "Steps"),
+                (sampler_index, "Sampler"),
+                (restore_faces, "Face restoration"),
+                (cfg_scale, "CFG scale"),
+                (seed, "Seed"),
+                (width, "Size-1"),
+                (height, "Size-2"),
+                (batch_size, "Batch size"),
+                (subseed, "Variation seed"),
+                (subseed_strength, "Variation seed strength"),
+                (seed_resize_from_w, "Seed resize from-1"),
+                (seed_resize_from_h, "Seed resize from-2"),
+                (denoising_strength, "Denoising strength"),
+                (mask_blur, "Mask blur"),
+                *modules.scripts.scripts_img2img.infotext_fields
+            ]
+            parameters_copypaste.add_paste_fields("img2img", init_img, img2img_paste_fields)
+            parameters_copypaste.add_paste_fields("inpaint", init_img_with_mask, img2img_paste_fields)
+
+    modules.scripts.scripts_current = None
+
+    with gr.Blocks(analytics_enabled=False) as extras_interface:
+        with gr.Row().style(equal_height=False):
+            with gr.Column(variant='panel'):
+                with gr.Tabs(elem_id="mode_extras"):
+                    with gr.TabItem('Single Image', elem_id="extras_single_tab"):
+                        extras_image = gr.Image(label="Source", source="upload", interactive=True, type="pil", elem_id="extras_image")
+
+                    with gr.TabItem('Batch Process', elem_id="extras_batch_process_tab"):
+                        image_batch = gr.File(label="Batch Process", file_count="multiple", interactive=True, type="file", elem_id="extras_image_batch")
+
+                    with gr.TabItem('Batch from Directory', elem_id="extras_batch_directory_tab"):
+                        extras_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, placeholder="A directory on the same machine where the server is running.", elem_id="extras_batch_input_dir")
+                        extras_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, placeholder="Leave blank to save images to the default path.", elem_id="extras_batch_output_dir")
+                        show_extras_results = gr.Checkbox(label='Show result images', value=True, elem_id="extras_show_extras_results")
+
+                submit = gr.Button('Generate', elem_id="extras_generate", variant='primary')
+
+                with gr.Tabs(elem_id="extras_resize_mode"):
+                    with gr.TabItem('Scale by', elem_id="extras_scale_by_tab"):
+                        upscaling_resize = gr.Slider(minimum=1.0, maximum=8.0, step=0.05, label="Resize", value=4, elem_id="extras_upscaling_resize")
+                    with gr.TabItem('Scale to', elem_id="extras_scale_to_tab"):
+                        with gr.Group():
+                            with gr.Row():
+                                upscaling_resize_w = gr.Number(label="Width", value=512, precision=0, elem_id="extras_upscaling_resize_w")
+                                upscaling_resize_h = gr.Number(label="Height", value=512, precision=0, elem_id="extras_upscaling_resize_h")
+                            upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop")
+
+                with gr.Group():
+                    extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
+
+                with gr.Group():
+                    extras_upscaler_2 = gr.Radio(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
+                    extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=1, elem_id="extras_upscaler_2_visibility")
+
+                with gr.Group():
+                    gfpgan_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="GFPGAN visibility", value=0, interactive=modules.gfpgan_model.have_gfpgan, elem_id="extras_gfpgan_visibility")
+
+                with gr.Group():
+                    codeformer_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer visibility", value=0, interactive=modules.codeformer_model.have_codeformer, elem_id="extras_codeformer_visibility")
+                    codeformer_weight = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer weight (0 = maximum effect, 1 = minimum effect)", value=0, interactive=modules.codeformer_model.have_codeformer, elem_id="extras_codeformer_weight")
+
+                with gr.Group():
+                    upscale_before_face_fix = gr.Checkbox(label='Upscale Before Restoring Faces', value=False, elem_id="extras_upscale_before_face_fix")
+
+            result_images, html_info_x, html_info, html_log = create_output_panel("extras", opts.outdir_extras_samples)
+
+        submit.click(
+            fn=wrap_gradio_gpu_call(modules.extras.run_extras, extra_outputs=[None, '']),
+            _js="get_extras_tab_index",
+            inputs=[
+                dummy_component,
+                dummy_component,
+                extras_image,
+                image_batch,
+                extras_batch_input_dir,
+                extras_batch_output_dir,
+                show_extras_results,
+                gfpgan_visibility,
+                codeformer_visibility,
+                codeformer_weight,
+                upscaling_resize,
+                upscaling_resize_w,
+                upscaling_resize_h,
+                upscaling_crop,
+                extras_upscaler_1,
+                extras_upscaler_2,
+                extras_upscaler_2_visibility,
+                upscale_before_face_fix,
+            ],
+            outputs=[
+                result_images,
+                html_info_x,
+                html_info,
+            ]
+        )
+        parameters_copypaste.add_paste_fields("extras", extras_image, None)
+
+        extras_image.change(
+            fn=modules.extras.clear_cache,
+            inputs=[], outputs=[]
+        )
+
+    with gr.Blocks(analytics_enabled=False) as pnginfo_interface:
+        with gr.Row().style(equal_height=False):
+            with gr.Column(variant='panel'):
+                image = gr.Image(elem_id="pnginfo_image", label="Source", source="upload", interactive=True, type="pil")
+
+            with gr.Column(variant='panel'):
+                html = gr.HTML()
+                generation_info = gr.Textbox(visible=False, elem_id="pnginfo_generation_info")
+                html2 = gr.HTML()
+                with gr.Row():
+                    buttons = parameters_copypaste.create_buttons(["txt2img", "img2img", "inpaint", "extras"])
+                parameters_copypaste.bind_buttons(buttons, image, generation_info)
+
+        image.change(
+            fn=wrap_gradio_call(modules.extras.run_pnginfo),
+            inputs=[image],
+            outputs=[html, generation_info, html2],
+        )
+
+    with gr.Blocks(analytics_enabled=False) as modelmerger_interface:
+        with gr.Row().style(equal_height=False):
+            with gr.Column(variant='panel'):
+                gr.HTML(value="<p>A merger of the two checkpoints will be generated in your <b>checkpoint</b> directory.</p>")
+
+                with gr.Row():
+                    primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)")
+                    create_refresh_button(primary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_A")
+
+                    secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary model (B)")
+                    create_refresh_button(secondary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_B")
+
+                    tertiary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_tertiary_model_name", label="Tertiary model (C)")
+                    create_refresh_button(tertiary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_C")
+
+                custom_name = gr.Textbox(label="Custom Name (Optional)", elem_id="modelmerger_custom_name")
+                interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3, elem_id="modelmerger_interp_amount")
+                interp_method = gr.Radio(choices=["Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method", elem_id="modelmerger_interp_method")
+
+                with gr.Row():
+                    checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format", elem_id="modelmerger_checkpoint_format")
+                    save_as_half = gr.Checkbox(value=False, label="Save as float16", elem_id="modelmerger_save_as_half")
+
+                modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary')
+
+            with gr.Column(variant='panel'):
+                submit_result = gr.Textbox(elem_id="modelmerger_result", show_label=False)
+
+    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>")
+
+        with gr.Row().style(equal_height=False):
+            with gr.Tabs(elem_id="train_tabs"):
+
+                with gr.Tab(label="Create embedding"):
+                    new_embedding_name = gr.Textbox(label="Name", elem_id="train_new_embedding_name")
+                    initialization_text = gr.Textbox(label="Initialization text", value="*", elem_id="train_initialization_text")
+                    nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1, elem_id="train_nvpt")
+                    overwrite_old_embedding = gr.Checkbox(value=False, label="Overwrite Old Embedding", elem_id="train_overwrite_old_embedding")
+
+                    with gr.Row():
+                        with gr.Column(scale=3):
+                            gr.HTML(value="")
+
+                        with gr.Column():
+                            create_embedding = gr.Button(value="Create embedding", variant='primary', elem_id="train_create_embedding")
+
+                with gr.Tab(label="Create hypernetwork"):
+                    new_hypernetwork_name = gr.Textbox(label="Name", elem_id="train_new_hypernetwork_name")
+                    new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "1024", "320", "640", "1280"], elem_id="train_new_hypernetwork_sizes")
+                    new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'", elem_id="train_new_hypernetwork_layer_structure")
+                    new_hypernetwork_activation_func = gr.Dropdown(value="linear", label="Select activation function of hypernetwork. Recommended : Swish / Linear(none)", choices=modules.hypernetworks.ui.keys, elem_id="train_new_hypernetwork_activation_func")
+                    new_hypernetwork_initialization_option = gr.Dropdown(value = "Normal", label="Select Layer weights initialization. Recommended: Kaiming for relu-like, Xavier for sigmoid-like, Normal otherwise", choices=["Normal", "KaimingUniform", "KaimingNormal", "XavierUniform", "XavierNormal"], elem_id="train_new_hypernetwork_initialization_option")
+                    new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization", elem_id="train_new_hypernetwork_add_layer_norm")
+                    new_hypernetwork_use_dropout = gr.Checkbox(label="Use dropout", elem_id="train_new_hypernetwork_use_dropout")
+                    new_hypernetwork_dropout_structure = gr.Textbox("0, 0, 0", label="Enter hypernetwork Dropout structure (or empty). Recommended : 0~0.35 incrementing sequence: 0, 0.05, 0.15", placeholder="1st and last digit must be 0 and values should be between 0 and 1. ex:'0, 0.01, 0'")
+                    overwrite_old_hypernetwork = gr.Checkbox(value=False, label="Overwrite Old Hypernetwork", elem_id="train_overwrite_old_hypernetwork")
+
+                    with gr.Row():
+                        with gr.Column(scale=3):
+                            gr.HTML(value="")
+
+                        with gr.Column():
+                            create_hypernetwork = gr.Button(value="Create hypernetwork", variant='primary', elem_id="train_create_hypernetwork")
+
+                with gr.Tab(label="Preprocess images"):
+                    process_src = gr.Textbox(label='Source directory', elem_id="train_process_src")
+                    process_dst = gr.Textbox(label='Destination directory', elem_id="train_process_dst")
+                    process_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_process_width")
+                    process_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_process_height")
+                    preprocess_txt_action = gr.Dropdown(label='Existing Caption txt Action', value="ignore", choices=["ignore", "copy", "prepend", "append"], elem_id="train_preprocess_txt_action")
+
+                    with gr.Row():
+                        process_flip = gr.Checkbox(label='Create flipped copies', elem_id="train_process_flip")
+                        process_split = gr.Checkbox(label='Split oversized images', elem_id="train_process_split")
+                        process_focal_crop = gr.Checkbox(label='Auto focal point crop', elem_id="train_process_focal_crop")
+                        process_caption = gr.Checkbox(label='Use BLIP for caption', elem_id="train_process_caption")
+                        process_caption_deepbooru = gr.Checkbox(label='Use deepbooru for caption', visible=True, elem_id="train_process_caption_deepbooru")
+
+                    with gr.Row(visible=False) as process_split_extra_row:
+                        process_split_threshold = gr.Slider(label='Split image threshold', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_split_threshold")
+                        process_overlap_ratio = gr.Slider(label='Split image overlap ratio', value=0.2, minimum=0.0, maximum=0.9, step=0.05, elem_id="train_process_overlap_ratio")
+
+                    with gr.Row(visible=False) as process_focal_crop_row:
+                        process_focal_crop_face_weight = gr.Slider(label='Focal point face weight', value=0.9, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_face_weight")
+                        process_focal_crop_entropy_weight = gr.Slider(label='Focal point entropy weight', value=0.15, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_entropy_weight")
+                        process_focal_crop_edges_weight = gr.Slider(label='Focal point edges weight', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_edges_weight")
+                        process_focal_crop_debug = gr.Checkbox(label='Create debug image', elem_id="train_process_focal_crop_debug")
+
+                    with gr.Row():
+                        with gr.Column(scale=3):
+                            gr.HTML(value="")
+
+                        with gr.Column():
+                            with gr.Row():
+                                interrupt_preprocessing = gr.Button("Interrupt", elem_id="train_interrupt_preprocessing")
+                            run_preprocess = gr.Button(value="Preprocess", variant='primary', elem_id="train_run_preprocess")
+
+                    process_split.change(
+                        fn=lambda show: gr_show(show),
+                        inputs=[process_split],
+                        outputs=[process_split_extra_row],
+                    )
+
+                    process_focal_crop.change(
+                        fn=lambda show: gr_show(show),
+                        inputs=[process_focal_crop],
+                        outputs=[process_focal_crop_row],
+                    )
+
+                def get_textual_inversion_template_names():
+                    return sorted([x for x in textual_inversion.textual_inversion_templates])
+
+                with gr.Tab(label="Train"):
+                    gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images <a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\" style=\"font-weight:bold;\">[wiki]</a></p>")
+                    with FormRow():
+                        train_embedding_name = gr.Dropdown(label='Embedding', elem_id="train_embedding", choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
+                        create_refresh_button(train_embedding_name, sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings, lambda: {"choices": sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())}, "refresh_train_embedding_name")
+
+                        train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=[x for x in shared.hypernetworks.keys()])
+                        create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted([x for x in shared.hypernetworks.keys()])}, "refresh_train_hypernetwork_name")
+
+                    with FormRow():
+                        embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005", elem_id="train_embedding_learn_rate")
+                        hypernetwork_learn_rate = gr.Textbox(label='Hypernetwork Learning rate', placeholder="Hypernetwork Learning rate", value="0.00001", elem_id="train_hypernetwork_learn_rate")
+                    
+                    with FormRow():
+                        clip_grad_mode = gr.Dropdown(value="disabled", label="Gradient Clipping", choices=["disabled", "value", "norm"])
+                        clip_grad_value = gr.Textbox(placeholder="Gradient clip value", value="0.1", show_label=False)
+
+                    with FormRow():
+                        batch_size = gr.Number(label='Batch size', value=1, precision=0, elem_id="train_batch_size")
+                        gradient_step = gr.Number(label='Gradient accumulation steps', value=1, precision=0, elem_id="train_gradient_step")
+
+                    dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images", elem_id="train_dataset_directory")
+                    log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion", elem_id="train_log_directory")
+
+                    with FormRow():
+                        template_file = gr.Dropdown(label='Prompt template', value="style_filewords.txt", elem_id="train_template_file", choices=get_textual_inversion_template_names())
+                        create_refresh_button(template_file, textual_inversion.list_textual_inversion_templates, lambda: {"choices": get_textual_inversion_template_names()}, "refrsh_train_template_file")
+
+                    training_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_training_width")
+                    training_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_training_height")
+                    varsize = gr.Checkbox(label="Do not resize images", value=False, elem_id="train_varsize")
+                    steps = gr.Number(label='Max steps', value=100000, precision=0, elem_id="train_steps")
+
+                    with FormRow():
+                        create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0, elem_id="train_create_image_every")
+                        save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0, elem_id="train_save_embedding_every")
+
+                    save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True, elem_id="train_save_image_with_stored_embedding")
+                    preview_from_txt2img = gr.Checkbox(label='Read parameters (prompt, etc...) from txt2img tab when making previews', value=False, elem_id="train_preview_from_txt2img")
+
+                    shuffle_tags = gr.Checkbox(label="Shuffle tags by ',' when creating prompts.", value=False, elem_id="train_shuffle_tags")
+                    tag_drop_out = gr.Slider(minimum=0, maximum=1, step=0.1, label="Drop out tags when creating prompts.", value=0, elem_id="train_tag_drop_out")
+
+                    latent_sampling_method = gr.Radio(label='Choose latent sampling method', value="once", choices=['once', 'deterministic', 'random'], elem_id="train_latent_sampling_method")
+
+                    with gr.Row():
+                        train_embedding = gr.Button(value="Train Embedding", variant='primary', elem_id="train_train_embedding")
+                        interrupt_training = gr.Button(value="Interrupt", elem_id="train_interrupt_training")
+                        train_hypernetwork = gr.Button(value="Train Hypernetwork", variant='primary', elem_id="train_train_hypernetwork")
+
+                params = script_callbacks.UiTrainTabParams(txt2img_preview_params)
+
+                script_callbacks.ui_train_tabs_callback(params)
+
+            with gr.Column():
+                progressbar = gr.HTML(elem_id="ti_progressbar")
+                ti_output = gr.Text(elem_id="ti_output", value="", show_label=False)
+
+                ti_gallery = gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(grid=4)
+                ti_preview = gr.Image(elem_id='ti_preview', visible=False)
+                ti_progress = gr.HTML(elem_id="ti_progress", value="")
+                ti_outcome = gr.HTML(elem_id="ti_error", value="")
+                setup_progressbar(progressbar, ti_preview, 'ti', textinfo=ti_progress)
+
+        create_embedding.click(
+            fn=modules.textual_inversion.ui.create_embedding,
+            inputs=[
+                new_embedding_name,
+                initialization_text,
+                nvpt,
+                overwrite_old_embedding,
+            ],
+            outputs=[
+                train_embedding_name,
+                ti_output,
+                ti_outcome,
+            ]
+        )
+
+        create_hypernetwork.click(
+            fn=modules.hypernetworks.ui.create_hypernetwork,
+            inputs=[
+                new_hypernetwork_name,
+                new_hypernetwork_sizes,
+                overwrite_old_hypernetwork,
+                new_hypernetwork_layer_structure,
+                new_hypernetwork_activation_func,
+                new_hypernetwork_initialization_option,
+                new_hypernetwork_add_layer_norm,
+                new_hypernetwork_use_dropout,
+                new_hypernetwork_dropout_structure
+            ],
+            outputs=[
+                train_hypernetwork_name,
+                ti_output,
+                ti_outcome,
+            ]
+        )
+
+        run_preprocess.click(
+            fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]),
+            _js="start_training_textual_inversion",
+            inputs=[
+                process_src,
+                process_dst,
+                process_width,
+                process_height,
+                preprocess_txt_action,
+                process_flip,
+                process_split,
+                process_caption,
+                process_caption_deepbooru,
+                process_split_threshold,
+                process_overlap_ratio,
+                process_focal_crop,
+                process_focal_crop_face_weight,
+                process_focal_crop_entropy_weight,
+                process_focal_crop_edges_weight,
+                process_focal_crop_debug,
+            ],
+            outputs=[
+                ti_output,
+                ti_outcome,
+            ],
+        )
+
+        train_embedding.click(
+            fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.train_embedding, extra_outputs=[gr.update()]),
+            _js="start_training_textual_inversion",
+            inputs=[
+                train_embedding_name,
+                embedding_learn_rate,
+                batch_size,
+                gradient_step,
+                dataset_directory,
+                log_directory,
+                training_width,
+                training_height,
+                varsize,
+                steps,
+                clip_grad_mode,
+                clip_grad_value,
+                shuffle_tags,
+                tag_drop_out,
+                latent_sampling_method,
+                create_image_every,
+                save_embedding_every,
+                template_file,
+                save_image_with_stored_embedding,
+                preview_from_txt2img,
+                *txt2img_preview_params,
+            ],
+            outputs=[
+                ti_output,
+                ti_outcome,
+            ]
+        )
+
+        train_hypernetwork.click(
+            fn=wrap_gradio_gpu_call(modules.hypernetworks.ui.train_hypernetwork, extra_outputs=[gr.update()]),
+            _js="start_training_textual_inversion",
+            inputs=[
+                train_hypernetwork_name,
+                hypernetwork_learn_rate,
+                batch_size,
+                gradient_step,
+                dataset_directory,
+                log_directory,
+                training_width,
+                training_height,
+                varsize,
+                steps,
+                clip_grad_mode,
+                clip_grad_value,
+                shuffle_tags,
+                tag_drop_out,
+                latent_sampling_method,
+                create_image_every,
+                save_embedding_every,
+                template_file,
+                preview_from_txt2img,
+                *txt2img_preview_params,
+            ],
+            outputs=[
+                ti_output,
+                ti_outcome,
+            ]
+        )
+
+        interrupt_training.click(
+            fn=lambda: shared.state.interrupt(),
+            inputs=[],
+            outputs=[],
+        )
+
+        interrupt_preprocessing.click(
+            fn=lambda: shared.state.interrupt(),
+            inputs=[],
+            outputs=[],
+        )
+
+    def create_setting_component(key, is_quicksettings=False):
+        def fun():
+            return opts.data[key] if key in opts.data else opts.data_labels[key].default
+
+        info = opts.data_labels[key]
+        t = type(info.default)
+
+        args = info.component_args() if callable(info.component_args) else info.component_args
+
+        if info.component is not None:
+            comp = info.component
+        elif t == str:
+            comp = gr.Textbox
+        elif t == int:
+            comp = gr.Number
+        elif t == bool:
+            comp = gr.Checkbox
+        else:
+            raise Exception(f'bad options item type: {str(t)} for key {key}')
+
+        elem_id = "setting_"+key
+
+        if info.refresh is not None:
+            if is_quicksettings:
+                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 FormRow():
+                    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 {}))
+
+        return res
+
+    components = []
+    component_dict = {}
+
+    script_callbacks.ui_settings_callback()
+    opts.reorder()
+
+    def run_settings(*args):
+        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__}"
+
+        for key, value, comp in zip(opts.data_labels.keys(), args, components):
+            if comp == dummy_component:
+                continue
+
+            if opts.set(key, value):
+                changed.append(key)
+
+        try:
+            opts.save(shared.config_filename)
+        except RuntimeError:
+            return opts.dumpjson(), f'{len(changed)} settings changed without save: {", ".join(changed)}.'
+        return opts.dumpjson(), f'{len(changed)} settings changed{": " if len(changed) > 0 else ""}{", ".join(changed)}.'
+
+    def run_settings_single(value, key):
+        if not opts.same_type(value, opts.data_labels[key].default):
+            return gr.update(visible=True), opts.dumpjson()
+
+        if not opts.set(key, value):
+            return gr.update(value=getattr(opts, key)), opts.dumpjson()
+
+        opts.save(shared.config_filename)
+
+        return gr.update(value=value), opts.dumpjson()
+
+    with gr.Blocks(analytics_enabled=False) as settings_interface:
+        with gr.Row():
+            with gr.Column(scale=6):
+                settings_submit = gr.Button(value="Apply settings", variant='primary', elem_id="settings_submit")
+            with gr.Column():
+                restart_gradio = gr.Button(value='Reload UI', variant='primary', elem_id="settings_restart_gradio")
+
+        result = gr.HTML(elem_id="settings_result")
+
+        quicksettings_names = [x.strip() for x in opts.quicksettings.split(",")]
+        quicksettings_names = {x: i for i, x in enumerate(quicksettings_names) if x != 'quicksettings'}
+
+        quicksettings_list = []
+
+        previous_section = None
+        current_tab = None
+        with gr.Tabs(elem_id="settings"):
+            for i, (k, item) in enumerate(opts.data_labels.items()):
+                section_must_be_skipped = item.section[0] is None
+
+                if previous_section != item.section and not section_must_be_skipped:
+                    elem_id, text = item.section
+
+                    if current_tab is not None:
+                        current_tab.__exit__()
+
+                    current_tab = gr.TabItem(elem_id="settings_{}".format(elem_id), label=text)
+                    current_tab.__enter__()
+
+                    previous_section = item.section
+
+                if k in quicksettings_names and not shared.cmd_opts.freeze_settings:
+                    quicksettings_list.append((i, k, item))
+                    components.append(dummy_component)
+                elif section_must_be_skipped:
+                    components.append(dummy_component)
+                else:
+                    component = create_setting_component(k)
+                    component_dict[k] = component
+                    components.append(component)
+
+            if current_tab is not None:
+                current_tab.__exit__()
+
+            with gr.TabItem("Actions"):
+                request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications")
+                download_localization = gr.Button(value='Download localization template', elem_id="download_localization")
+                reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary', elem_id="settings_reload_script_bodies")
+
+            if os.path.exists("html/licenses.html"):
+                with open("html/licenses.html", encoding="utf8") as file:
+                    with gr.TabItem("Licenses"):
+                        gr.HTML(file.read(), elem_id="licenses")
+
+            gr.Button(value="Show all pages", elem_id="settings_show_all_pages")
+
+        request_notifications.click(
+            fn=lambda: None,
+            inputs=[],
+            outputs=[],
+            _js='function(){}'
+        )
+
+        download_localization.click(
+            fn=lambda: None,
+            inputs=[],
+            outputs=[],
+            _js='download_localization'
+        )
+
+        def reload_scripts():
+            modules.scripts.reload_script_body_only()
+            reload_javascript()  # need to refresh the html page
+
+        reload_script_bodies.click(
+            fn=reload_scripts,
+            inputs=[],
+            outputs=[]
+        )
+
+        def request_restart():
+            shared.state.interrupt()
+            shared.state.need_restart = True
+
+        restart_gradio.click(
+            fn=request_restart,
+            _js='restart_reload',
+            inputs=[],
+            outputs=[],
+        )
+
+    interfaces = [
+        (txt2img_interface, "txt2img", "txt2img"),
+        (img2img_interface, "img2img", "img2img"),
+        (extras_interface, "Extras", "extras"),
+        (pnginfo_interface, "PNG Info", "pnginfo"),
+        (modelmerger_interface, "Checkpoint Merger", "modelmerger"),
+        (train_interface, "Train", "ti"),
+    ]
+
+    css = ""
+
+    for cssfile in modules.scripts.list_files_with_name("style.css"):
+        if not os.path.isfile(cssfile):
+            continue
+
+        with open(cssfile, "r", encoding="utf8") as file:
+            css += file.read() + "\n"
+
+    if os.path.exists(os.path.join(script_path, "user.css")):
+        with open(os.path.join(script_path, "user.css"), "r", encoding="utf8") as file:
+            css += file.read() + "\n"
+
+    if not cmd_opts.no_progressbar_hiding:
+        css += css_hide_progressbar
+
+    interfaces += script_callbacks.ui_tabs_callback()
+    interfaces += [(settings_interface, "Settings", "settings")]
+
+    extensions_interface = ui_extensions.create_ui()
+    interfaces += [(extensions_interface, "Extensions", "extensions")]
+
+    with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion") as demo:
+        with gr.Row(elem_id="quicksettings"):
+            for i, k, item in sorted(quicksettings_list, key=lambda x: quicksettings_names.get(x[1], x[0])):
+                component = create_setting_component(k, is_quicksettings=True)
+                component_dict[k] = component
+
+        parameters_copypaste.integrate_settings_paste_fields(component_dict)
+        parameters_copypaste.run_bind()
+
+        with gr.Tabs(elem_id="tabs") as tabs:
+            for interface, label, ifid in interfaces:
+                with gr.TabItem(label, id=ifid, elem_id='tab_' + ifid):
+                    interface.render()
+
+        if os.path.exists(os.path.join(script_path, "notification.mp3")):
+            audio_notification = gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False)
+
+        if os.path.exists("html/footer.html"):
+            with open("html/footer.html", encoding="utf8") as file:
+                footer = file.read()
+                footer = footer.format(versions=versions_html())
+                gr.HTML(footer, elem_id="footer")
+
+        text_settings = gr.Textbox(elem_id="settings_json", value=lambda: opts.dumpjson(), visible=False)
+        settings_submit.click(
+            fn=wrap_gradio_call(run_settings, extra_outputs=[gr.update()]),
+            inputs=components,
+            outputs=[text_settings, result],
+        )
+
+        for i, k, item in quicksettings_list:
+            component = component_dict[k]
+
+            component.change(
+                fn=lambda value, k=k: run_settings_single(value, key=k),
+                inputs=[component],
+                outputs=[component, text_settings],
+            )
+
+        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)
+            except Exception as e:
+                print("Error loading/saving model file:", file=sys.stderr)
+                print(traceback.format_exc(), file=sys.stderr)
+                modules.sd_models.list_models()  # to remove the potentially missing models from the list
+                return [f"Error merging checkpoints: {e}"] + [gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(4)]
+            return results
+
+        modelmerger_merge.click(
+            fn=modelmerger,
+            inputs=[
+                primary_model_name,
+                secondary_model_name,
+                tertiary_model_name,
+                interp_method,
+                interp_amount,
+                save_as_half,
+                custom_name,
+                checkpoint_format,
+            ],
+            outputs=[
+                submit_result,
+                primary_model_name,
+                secondary_model_name,
+                tertiary_model_name,
+                component_dict['sd_model_checkpoint'],
+            ]
+        )
+
+    ui_config_file = cmd_opts.ui_config_file
+    ui_settings = {}
+    settings_count = len(ui_settings)
+    error_loading = False
+
+    try:
+        if os.path.exists(ui_config_file):
+            with open(ui_config_file, "r", encoding="utf8") as file:
+                ui_settings = json.load(file)
+    except Exception:
+        error_loading = True
+        print("Error loading settings:", file=sys.stderr)
+        print(traceback.format_exc(), file=sys.stderr)
+
+    def loadsave(path, x):
+        def apply_field(obj, field, condition=None, init_field=None):
+            key = path + "/" + field
+
+            if getattr(obj, 'custom_script_source', None) is not None:
+              key = 'customscript/' + obj.custom_script_source + '/' + key
+
+            if getattr(obj, 'do_not_save_to_config', False):
+                return
+
+            saved_value = ui_settings.get(key, None)
+            if saved_value is None:
+                ui_settings[key] = getattr(obj, field)
+            elif condition and not condition(saved_value):
+                print(f'Warning: Bad ui setting value: {key}: {saved_value}; Default value "{getattr(obj, field)}" will be used instead.')
+            else:
+                setattr(obj, field, saved_value)
+                if init_field is not None:
+                    init_field(saved_value)
+
+        if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number, gr.Dropdown] and x.visible:
+            apply_field(x, 'visible')
+
+        if type(x) == gr.Slider:
+            apply_field(x, 'value')
+            apply_field(x, 'minimum')
+            apply_field(x, 'maximum')
+            apply_field(x, 'step')
+
+        if type(x) == gr.Radio:
+            apply_field(x, 'value', lambda val: val in x.choices)
+
+        if type(x) == gr.Checkbox:
+            apply_field(x, 'value')
+
+        if type(x) == gr.Textbox:
+            apply_field(x, 'value')
+
+        if type(x) == gr.Number:
+            apply_field(x, 'value')
+
+        if type(x) == gr.Dropdown:
+            apply_field(x, 'value', lambda val: val in x.choices, getattr(x, 'init_field', None))
+
+    visit(txt2img_interface, loadsave, "txt2img")
+    visit(img2img_interface, loadsave, "img2img")
+    visit(extras_interface, loadsave, "extras")
+    visit(modelmerger_interface, loadsave, "modelmerger")
+    visit(train_interface, loadsave, "train")
+
+    if not error_loading and (not os.path.exists(ui_config_file) or settings_count != len(ui_settings)):
+        with open(ui_config_file, "w", encoding="utf8") as file:
+            json.dump(ui_settings, file, indent=4)
+
+    return demo
+
+
+def reload_javascript():
+    with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile:
+        javascript = f'<script>{jsfile.read()}</script>'
+
+    scripts_list = modules.scripts.list_scripts("javascript", ".js")
+
+    for basedir, filename, path in scripts_list:
+        with open(path, "r", encoding="utf8") as jsfile:
+            javascript += f"\n<!-- {filename} --><script>{jsfile.read()}</script>"
+
+    if cmd_opts.theme is not None:
+        javascript += f"\n<script>set_theme('{cmd_opts.theme}');</script>\n"
+
+    javascript += f"\n<script>{localization.localization_js(shared.opts.localization)}</script>"
+
+    def template_response(*args, **kwargs):
+        res = shared.GradioTemplateResponseOriginal(*args, **kwargs)
+        res.body = res.body.replace(
+            b'</head>', f'{javascript}</head>'.encode("utf8"))
+        res.init_headers()
+        return res
+
+    gradio.routes.templates.TemplateResponse = template_response
+
+
+if not hasattr(shared, 'GradioTemplateResponseOriginal'):
+    shared.GradioTemplateResponseOriginal = gradio.routes.templates.TemplateResponse
+
+
+def versions_html():
+    import torch
+    import launch
+
+    python_version = ".".join([str(x) for x in sys.version_info[0:3]])
+    commit = launch.commit_hash()
+    short_commit = commit[0:8]
+
+    if shared.xformers_available:
+        import xformers
+        xformers_version = xformers.__version__
+    else:
+        xformers_version = "N/A"
+
+    return f"""
+python: <span title="{sys.version}">{python_version}</span>
+ • 
+torch: {torch.__version__}
+ • 
+xformers: {xformers_version}
+ • 
+gradio: {gr.__version__}
+ • 
+commit: <a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui/commit/{commit}">{short_commit}</a>
+"""
diff --git a/modules/ui.py b/modules/ui.py
deleted file mode 100644
index 9b9081b5..00000000
--- a/modules/ui.py
+++ /dev/null
@@ -1,1928 +0,0 @@
-import html
-import json
-import math
-import mimetypes
-import os
-import platform
-import random
-import subprocess as sp
-import sys
-import tempfile
-import time
-import traceback
-from functools import partial, reduce
-
-import gradio as gr
-import gradio.routes
-import gradio.utils
-import numpy as np
-from PIL import Image, PngImagePlugin
-from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
-
-from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru
-from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
-from modules.paths import script_path
-
-from modules.shared import opts, cmd_opts, restricted_opts
-
-import modules.codeformer_model
-import modules.generation_parameters_copypaste as parameters_copypaste
-import modules.gfpgan_model
-import modules.hypernetworks.ui
-import modules.scripts
-import modules.shared as shared
-import modules.styles
-import modules.textual_inversion.ui
-from modules import prompt_parser
-from modules.images import save_image
-from modules.sd_hijack import model_hijack
-from modules.sd_samplers import samplers, samplers_for_img2img
-from modules.textual_inversion import textual_inversion
-import modules.hypernetworks.ui
-from modules.generation_parameters_copypaste import image_from_url_text
-
-# this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI
-mimetypes.init()
-mimetypes.add_type('application/javascript', '.js')
-
-if not cmd_opts.share and not cmd_opts.listen:
-    # fix gradio phoning home
-    gradio.utils.version_check = lambda: None
-    gradio.utils.get_local_ip_address = lambda: '127.0.0.1'
-
-if cmd_opts.ngrok is not None:
-    import modules.ngrok as ngrok
-    print('ngrok authtoken detected, trying to connect...')
-    ngrok.connect(
-        cmd_opts.ngrok,
-        cmd_opts.port if cmd_opts.port is not None else 7860,
-        cmd_opts.ngrok_region
-        )
-
-
-def gr_show(visible=True):
-    return {"visible": visible, "__type__": "update"}
-
-
-sample_img2img = "assets/stable-samples/img2img/sketch-mountains-input.jpg"
-sample_img2img = sample_img2img if os.path.exists(sample_img2img) else None
-
-css_hide_progressbar = """
-.wrap .m-12 svg { display:none!important; }
-.wrap .m-12::before { content:"Loading..." }
-.wrap .z-20 svg { display:none!important; }
-.wrap .z-20::before { content:"Loading..." }
-.progress-bar { display:none!important; }
-.meta-text { display:none!important; }
-.meta-text-center { display:none!important; }
-"""
-
-# Using constants for these since the variation selector isn't visible.
-# Important that they exactly match script.js for tooltip to work.
-random_symbol = '\U0001f3b2\ufe0f'  # 🎲️
-reuse_symbol = '\u267b\ufe0f'  # ♻️
-paste_symbol = '\u2199\ufe0f'  # ↙
-folder_symbol = '\U0001f4c2'  # 📂
-refresh_symbol = '\U0001f504'  # 🔄
-save_style_symbol = '\U0001f4be'  # 💾
-apply_style_symbol = '\U0001f4cb'  # 📋
-clear_prompt_symbol = '\U0001F5D1'  # 🗑️
-
-
-def plaintext_to_html(text):
-    text = "<p>" + "<br>\n".join([f"{html.escape(x)}" for x in text.split('\n')]) + "</p>"
-    return text
-
-def send_gradio_gallery_to_image(x):
-    if len(x) == 0:
-        return None
-    return image_from_url_text(x[0])
-
-def save_files(js_data, images, do_make_zip, index):
-    import csv
-    filenames = []
-    fullfns = []
-
-    #quick dictionary to class object conversion. Its necessary due apply_filename_pattern requiring it
-    class MyObject:
-        def __init__(self, d=None):
-            if d is not None:
-                for key, value in d.items():
-                    setattr(self, key, value)
-
-    data = json.loads(js_data)
-
-    p = MyObject(data)
-    path = opts.outdir_save
-    save_to_dirs = opts.use_save_to_dirs_for_ui
-    extension: str = opts.samples_format
-    start_index = 0
-
-    if index > -1 and opts.save_selected_only and (index >= data["index_of_first_image"]):  # ensures we are looking at a specific non-grid picture, and we have save_selected_only
-
-        images = [images[index]]
-        start_index = index
-
-    os.makedirs(opts.outdir_save, exist_ok=True)
-
-    with open(os.path.join(opts.outdir_save, "log.csv"), "a", encoding="utf8", newline='') as file:
-        at_start = file.tell() == 0
-        writer = csv.writer(file)
-        if at_start:
-            writer.writerow(["prompt", "seed", "width", "height", "sampler", "cfgs", "steps", "filename", "negative_prompt"])
-
-        for image_index, filedata in enumerate(images, start_index):
-            image = image_from_url_text(filedata)
-
-            is_grid = image_index < p.index_of_first_image
-            i = 0 if is_grid else (image_index - p.index_of_first_image)
-
-            fullfn, txt_fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
-
-            filename = os.path.relpath(fullfn, path)
-            filenames.append(filename)
-            fullfns.append(fullfn)
-            if txt_fullfn:
-                filenames.append(os.path.basename(txt_fullfn))
-                fullfns.append(txt_fullfn)
-
-        writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler_name"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]])
-
-    # Make Zip
-    if do_make_zip:
-        zip_filepath = os.path.join(path, "images.zip")
-
-        from zipfile import ZipFile
-        with ZipFile(zip_filepath, "w") as zip_file:
-            for i in range(len(fullfns)):
-                with open(fullfns[i], mode="rb") as f:
-                    zip_file.writestr(filenames[i], f.read())
-        fullfns.insert(0, zip_filepath)
-
-    return gr.File.update(value=fullfns, visible=True), plaintext_to_html(f"Saved: {filenames[0]}")
-
-
-def calc_time_left(progress, threshold, label, force_display, show_eta):
-    if progress == 0:
-        return ""
-    else:
-        time_since_start = time.time() - shared.state.time_start
-        eta = (time_since_start/progress)
-        eta_relative = eta-time_since_start
-        if (eta_relative > threshold and show_eta) or force_display:
-            if eta_relative > 3600:
-                return label + time.strftime('%H:%M:%S', time.gmtime(eta_relative))
-            elif eta_relative > 60:
-                return label + time.strftime('%M:%S',  time.gmtime(eta_relative))
-            else:
-                return label + time.strftime('%Ss',  time.gmtime(eta_relative))
-        else:
-            return ""
-
-
-def check_progress_call(id_part):
-    if shared.state.job_count == 0:
-        return "", gr_show(False), gr_show(False), gr_show(False)
-
-    progress = 0
-
-    if shared.state.job_count > 0:
-        progress += shared.state.job_no / shared.state.job_count
-    if shared.state.sampling_steps > 0:
-        progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps
-
-    # Show progress percentage and time left at the same moment, and base it also on steps done
-    show_eta = progress >= 0.01 or shared.state.sampling_step >= 10
-
-    time_left = calc_time_left(progress, 1, " ETA: ", shared.state.time_left_force_display, show_eta)
-    if time_left != "":
-        shared.state.time_left_force_display = True
-
-    progress = min(progress, 1)
-
-    progressbar = ""
-    if opts.show_progressbar:
-        progressbar = f"""<div class='progressDiv'><div class='progress' style="overflow:visible;width:{progress * 100}%;white-space:nowrap;">{"&nbsp;" * 2 + str(int(progress*100))+"%" + time_left if show_eta else ""}</div></div>"""
-
-    image = gr_show(False)
-    preview_visibility = gr_show(False)
-
-    if opts.show_progress_every_n_steps != 0:
-        shared.state.set_current_image()
-        image = shared.state.current_image
-
-        if image is None:
-            image = gr.update(value=None)
-        else:
-            preview_visibility = gr_show(True)
-
-    if shared.state.textinfo is not None:
-        textinfo_result = gr.HTML.update(value=shared.state.textinfo, visible=True)
-    else:
-        textinfo_result = gr_show(False)
-
-    return f"<span id='{id_part}_progress_span' style='display: none'>{time.time()}</span><p>{progressbar}</p>", preview_visibility, image, textinfo_result
-
-
-def check_progress_call_initial(id_part):
-    shared.state.job_count = -1
-    shared.state.current_latent = None
-    shared.state.current_image = None
-    shared.state.textinfo = None
-    shared.state.time_start = time.time()
-    shared.state.time_left_force_display = False
-
-    return check_progress_call(id_part)
-
-
-def visit(x, func, path=""):
-    if hasattr(x, 'children'):
-        for c in x.children:
-            visit(c, func, path)
-    elif x.label is not None:
-        func(path + "/" + str(x.label), x)
-
-
-def add_style(name: str, prompt: str, negative_prompt: str):
-    if name is None:
-        return [gr_show() for x in range(4)]
-
-    style = modules.styles.PromptStyle(name, prompt, negative_prompt)
-    shared.prompt_styles.styles[style.name] = style
-    # Save all loaded prompt styles: this allows us to update the storage format in the future more easily, because we
-    # reserialize all styles every time we save them
-    shared.prompt_styles.save_styles(shared.styles_filename)
-
-    return [gr.Dropdown.update(visible=True, choices=list(shared.prompt_styles.styles)) for _ in range(4)]
-
-
-def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resize_y):
-    from modules import processing, devices
-
-    if not enable:
-        return ""
-
-    p = processing.StableDiffusionProcessingTxt2Img(width=width, height=height, enable_hr=True, hr_scale=hr_scale, hr_resize_x=hr_resize_x, hr_resize_y=hr_resize_y)
-
-    with devices.autocast():
-        p.init([""], [0], [0])
-
-    return f"resize: from <span class='resolution'>{p.width}x{p.height}</span> to <span class='resolution'>{p.hr_resize_x or p.hr_upscale_to_x}x{p.hr_resize_y or p.hr_upscale_to_y}</span>"
-
-
-def apply_styles(prompt, prompt_neg, style1_name, style2_name):
-    prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, [style1_name, style2_name])
-    prompt_neg = shared.prompt_styles.apply_negative_styles_to_prompt(prompt_neg, [style1_name, style2_name])
-
-    return [gr.Textbox.update(value=prompt), gr.Textbox.update(value=prompt_neg), gr.Dropdown.update(value="None"), gr.Dropdown.update(value="None")]
-
-
-def interrogate(image):
-    prompt = shared.interrogator.interrogate(image.convert("RGB"))
-
-    return gr_show(True) if prompt is None else prompt
-
-
-def interrogate_deepbooru(image):
-    prompt = deepbooru.model.tag(image)
-    return gr_show(True) if prompt is None else prompt
-
-
-def create_seed_inputs(target_interface):
-    with FormRow(elem_id=target_interface + '_seed_row'):
-        seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1, elem_id=target_interface + '_seed')
-        seed.style(container=False)
-        random_seed = gr.Button(random_symbol, elem_id=target_interface + '_random_seed')
-        reuse_seed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_seed')
-
-        with gr.Group(elem_id=target_interface + '_subseed_show_box'):
-            seed_checkbox = gr.Checkbox(label='Extra', elem_id=target_interface + '_subseed_show', value=False)
-
-    # Components to show/hide based on the 'Extra' checkbox
-    seed_extras = []
-
-    with FormRow(visible=False, elem_id=target_interface + '_subseed_row') as seed_extra_row_1:
-        seed_extras.append(seed_extra_row_1)
-        subseed = gr.Number(label='Variation seed', value=-1, elem_id=target_interface + '_subseed')
-        subseed.style(container=False)
-        random_subseed = gr.Button(random_symbol, elem_id=target_interface + '_random_subseed')
-        reuse_subseed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_subseed')
-        subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=target_interface + '_subseed_strength')
-
-    with FormRow(visible=False) as seed_extra_row_2:
-        seed_extras.append(seed_extra_row_2)
-        seed_resize_from_w = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from width", value=0, elem_id=target_interface + '_seed_resize_from_w')
-        seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from height", value=0, elem_id=target_interface + '_seed_resize_from_h')
-
-    random_seed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[seed])
-    random_subseed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[subseed])
-
-    def change_visibility(show):
-        return {comp: gr_show(show) for comp in seed_extras}
-
-    seed_checkbox.change(change_visibility, show_progress=False, inputs=[seed_checkbox], outputs=seed_extras)
-
-    return seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox
-
-
-
-def connect_clear_prompt(button):
-    """Given clear button, prompt, and token_counter objects, setup clear prompt button click event"""
-    button.click(
-        _js="clear_prompt",
-        fn=None,
-        inputs=[],
-        outputs=[],
-    )
-
-
-def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: gr.Textbox, dummy_component, is_subseed):
-    """ Connects a 'reuse (sub)seed' button's click event so that it copies last used
-        (sub)seed value from generation info the to the seed field. If copying subseed and subseed strength
-        was 0, i.e. no variation seed was used, it copies the normal seed value instead."""
-    def copy_seed(gen_info_string: str, index):
-        res = -1
-
-        try:
-            gen_info = json.loads(gen_info_string)
-            index -= gen_info.get('index_of_first_image', 0)
-
-            if is_subseed and gen_info.get('subseed_strength', 0) > 0:
-                all_subseeds = gen_info.get('all_subseeds', [-1])
-                res = all_subseeds[index if 0 <= index < len(all_subseeds) else 0]
-            else:
-                all_seeds = gen_info.get('all_seeds', [-1])
-                res = all_seeds[index if 0 <= index < len(all_seeds) else 0]
-
-        except json.decoder.JSONDecodeError as e:
-            if gen_info_string != '':
-                print("Error parsing JSON generation info:", file=sys.stderr)
-                print(gen_info_string, file=sys.stderr)
-
-        return [res, gr_show(False)]
-
-    reuse_seed.click(
-        fn=copy_seed,
-        _js="(x, y) => [x, selected_gallery_index()]",
-        show_progress=False,
-        inputs=[generation_info, dummy_component],
-        outputs=[seed, dummy_component]
-    )
-
-
-def update_token_counter(text, steps):
-    try:
-        _, prompt_flat_list, _ = prompt_parser.get_multicond_prompt_list([text])
-        prompt_schedules = prompt_parser.get_learned_conditioning_prompt_schedules(prompt_flat_list, steps)
-
-    except Exception:
-        # a parsing error can happen here during typing, and we don't want to bother the user with
-        # messages related to it in console
-        prompt_schedules = [[[steps, text]]]
-
-    flat_prompts = reduce(lambda list1, list2: list1+list2, prompt_schedules)
-    prompts = [prompt_text for step, prompt_text in flat_prompts]
-    token_count, max_length = max([model_hijack.get_prompt_lengths(prompt) for prompt in prompts], key=lambda args: args[0])
-    style_class = ' class="red"' if (token_count > max_length) else ""
-    return f"<span {style_class}>{token_count}/{max_length}</span>"
-
-
-def create_toprow(is_img2img):
-    id_part = "img2img" if is_img2img else "txt2img"
-
-    with gr.Row(elem_id="toprow"):
-        with gr.Column(scale=6):
-            with gr.Row():
-                with gr.Column(scale=80):
-                    with gr.Row():
-                        prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=2,
-                            placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)"
-                        )
-
-            with gr.Row():
-                with gr.Column(scale=80):
-                    with gr.Row():
-                        negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2,
-                            placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)"
-                        )
-
-        with gr.Column(scale=1, elem_id="roll_col"):
-            paste = gr.Button(value=paste_symbol, elem_id="paste")
-            save_style = gr.Button(value=save_style_symbol, elem_id="style_create")
-            prompt_style_apply = gr.Button(value=apply_style_symbol, elem_id="style_apply")
-            clear_prompt_button = gr.Button(value=clear_prompt_symbol, elem_id=f"{id_part}_clear_prompt")
-            token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_token_counter")
-            token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button")
-
-            clear_prompt_button.click(
-                fn=lambda *x: x,
-                _js="confirm_clear_prompt",
-                inputs=[prompt, negative_prompt],
-                outputs=[prompt, negative_prompt],
-            )
-
-        button_interrogate = None
-        button_deepbooru = None
-        if is_img2img:
-            with gr.Column(scale=1, elem_id="interrogate_col"):
-                button_interrogate = gr.Button('Interrogate\nCLIP', elem_id="interrogate")
-                button_deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru")
-
-        with gr.Column(scale=1):
-            with gr.Row():
-                skip = gr.Button('Skip', elem_id=f"{id_part}_skip")
-                interrupt = gr.Button('Interrupt', elem_id=f"{id_part}_interrupt")
-                submit = gr.Button('Generate', elem_id=f"{id_part}_generate", variant='primary')
-
-                skip.click(
-                    fn=lambda: shared.state.skip(),
-                    inputs=[],
-                    outputs=[],
-                )
-
-                interrupt.click(
-                    fn=lambda: shared.state.interrupt(),
-                    inputs=[],
-                    outputs=[],
-                )
-
-            with gr.Row():
-                with gr.Column(scale=1, elem_id="style_pos_col"):
-                    prompt_style = gr.Dropdown(label="Style 1", elem_id=f"{id_part}_style_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())))
-
-                with gr.Column(scale=1, elem_id="style_neg_col"):
-                    prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())))
-
-    return prompt, prompt_style, negative_prompt, prompt_style2, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button
-
-
-def setup_progressbar(progressbar, preview, id_part, textinfo=None):
-    if textinfo is None:
-        textinfo = gr.HTML(visible=False)
-
-    check_progress = gr.Button('Check progress', elem_id=f"{id_part}_check_progress", visible=False)
-    check_progress.click(
-        fn=lambda: check_progress_call(id_part),
-        show_progress=False,
-        inputs=[],
-        outputs=[progressbar, preview, preview, textinfo],
-    )
-
-    check_progress_initial = gr.Button('Check progress (first)', elem_id=f"{id_part}_check_progress_initial", visible=False)
-    check_progress_initial.click(
-        fn=lambda: check_progress_call_initial(id_part),
-        show_progress=False,
-        inputs=[],
-        outputs=[progressbar, preview, preview, textinfo],
-    )
-
-
-def apply_setting(key, value):
-    if value is None:
-        return gr.update()
-
-    if shared.cmd_opts.freeze_settings:
-        return gr.update()
-
-    # dont allow model to be swapped when model hash exists in prompt
-    if key == "sd_model_checkpoint" and opts.disable_weights_auto_swap:
-        return gr.update()
-
-    if key == "sd_model_checkpoint":
-        ckpt_info = sd_models.get_closet_checkpoint_match(value)
-
-        if ckpt_info is not None:
-            value = ckpt_info.title
-        else:
-            return gr.update()
-
-    comp_args = opts.data_labels[key].component_args
-    if comp_args and isinstance(comp_args, dict) and comp_args.get('visible') is False:
-        return
-
-    valtype = type(opts.data_labels[key].default)
-    oldval = opts.data.get(key, None)
-    opts.data[key] = valtype(value) if valtype != type(None) else value
-    if oldval != value and opts.data_labels[key].onchange is not None:
-        opts.data_labels[key].onchange()
-
-    opts.save(shared.config_filename)
-    return value
-
-
-def update_generation_info(args):
-    generation_info, html_info, img_index = args
-    try:
-        generation_info = json.loads(generation_info)
-        if img_index < 0 or img_index >= len(generation_info["infotexts"]):
-            return html_info
-        return plaintext_to_html(generation_info["infotexts"][img_index])
-    except Exception:
-        pass
-    # if the json parse or anything else fails, just return the old html_info
-    return html_info
-
-
-def create_refresh_button(refresh_component, refresh_method, refreshed_args, elem_id):
-    def refresh():
-        refresh_method()
-        args = refreshed_args() if callable(refreshed_args) else refreshed_args
-
-        for k, v in args.items():
-            setattr(refresh_component, k, v)
-
-        return gr.update(**(args or {}))
-
-    refresh_button = ToolButton(value=refresh_symbol, elem_id=elem_id)
-    refresh_button.click(
-        fn=refresh,
-        inputs=[],
-        outputs=[refresh_component]
-    )
-    return refresh_button
-
-
-def create_output_panel(tabname, outdir):
-    def open_folder(f):
-        if not os.path.exists(f):
-            print(f'Folder "{f}" does not exist. After you create an image, the folder will be created.')
-            return
-        elif not os.path.isdir(f):
-            print(f"""
-WARNING
-An open_folder request was made with an argument that is not a folder.
-This could be an error or a malicious attempt to run code on your computer.
-Requested path was: {f}
-""", file=sys.stderr)
-            return
-
-        if not shared.cmd_opts.hide_ui_dir_config:
-            path = os.path.normpath(f)
-            if platform.system() == "Windows":
-                os.startfile(path)
-            elif platform.system() == "Darwin":
-                sp.Popen(["open", path])
-            elif "microsoft-standard-WSL2" in platform.uname().release:
-                sp.Popen(["wsl-open", path])
-            else:
-                sp.Popen(["xdg-open", path])
-
-    with gr.Column(variant='panel'):
-            with gr.Group():
-                result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery").style(grid=4)
-
-            generation_info = None
-            with gr.Column():
-                with gr.Row(elem_id=f"image_buttons_{tabname}"):
-                    open_folder_button = gr.Button(folder_symbol, elem_id="hidden_element" if shared.cmd_opts.hide_ui_dir_config else f'open_folder_{tabname}')
-
-                    if tabname != "extras":
-                        save = gr.Button('Save', elem_id=f'save_{tabname}')
-                        save_zip = gr.Button('Zip', elem_id=f'save_zip_{tabname}')
-
-                    buttons = parameters_copypaste.create_buttons(["img2img", "inpaint", "extras"])
-
-                open_folder_button.click(
-                    fn=lambda: open_folder(opts.outdir_samples or outdir),
-                    inputs=[],
-                    outputs=[],
-                )
-
-                if tabname != "extras":
-                    with gr.Row():
-                        download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False, elem_id=f'download_files_{tabname}')
-
-                    with gr.Group():
-                        html_info = gr.HTML(elem_id=f'html_info_{tabname}')
-                        html_log = gr.HTML(elem_id=f'html_log_{tabname}')
-
-                        generation_info = gr.Textbox(visible=False, elem_id=f'generation_info_{tabname}')
-                        if tabname == 'txt2img' or tabname == 'img2img':
-                            generation_info_button = gr.Button(visible=False, elem_id=f"{tabname}_generation_info_button")
-                            generation_info_button.click(
-                                fn=update_generation_info,
-                                _js="(x, y) => [x, y, selected_gallery_index()]",
-                                inputs=[generation_info, html_info],
-                                outputs=[html_info],
-                                preprocess=False
-                            )
-
-                        save.click(
-                            fn=wrap_gradio_call(save_files),
-                            _js="(x, y, z, w) => [x, y, false, selected_gallery_index()]",
-                            inputs=[
-                                generation_info,
-                                result_gallery,
-                                html_info,
-                                html_info,
-                            ],
-                            outputs=[
-                                download_files,
-                                html_log,
-                            ]
-                        )
-
-                        save_zip.click(
-                            fn=wrap_gradio_call(save_files),
-                            _js="(x, y, z, w) => [x, y, true, selected_gallery_index()]",
-                            inputs=[
-                                generation_info,
-                                result_gallery,
-                                html_info,
-                                html_info,
-                            ],
-                            outputs=[
-                                download_files,
-                                html_log,
-                            ]
-                        )
-
-                else:
-                    html_info_x = gr.HTML(elem_id=f'html_info_x_{tabname}')
-                    html_info = gr.HTML(elem_id=f'html_info_{tabname}')
-                    html_log = gr.HTML(elem_id=f'html_log_{tabname}')
-
-                parameters_copypaste.bind_buttons(buttons, result_gallery, "txt2img" if tabname == "txt2img" else None)
-                return result_gallery, generation_info if tabname != "extras" else html_info_x, html_info, html_log
-
-
-def create_sampler_and_steps_selection(choices, tabname):
-    if opts.samplers_in_dropdown:
-        with FormRow(elem_id=f"sampler_selection_{tabname}"):
-            sampler_index = gr.Dropdown(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")
-            steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling steps", value=20)
-    else:
-        with FormGroup(elem_id=f"sampler_selection_{tabname}"):
-            steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling steps", value=20)
-            sampler_index = gr.Radio(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")
-
-    return steps, sampler_index
-
-
-def ordered_ui_categories():
-    user_order = {x.strip(): i for i, x in enumerate(shared.opts.ui_reorder.split(","))}
-
-    for i, category in sorted(enumerate(shared.ui_reorder_categories), key=lambda x: user_order.get(x[1], x[0] + 1000)):
-        yield category
-
-
-def create_ui():
-    import modules.img2img
-    import modules.txt2img
-
-    reload_javascript()
-
-    parameters_copypaste.reset()
-
-    modules.scripts.scripts_current = modules.scripts.scripts_txt2img
-    modules.scripts.scripts_txt2img.initialize_scripts(is_img2img=False)
-
-    with gr.Blocks(analytics_enabled=False) as txt2img_interface:
-        txt2img_prompt, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _,txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False)
-
-        dummy_component = gr.Label(visible=False)
-        txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False)
-
-        with gr.Row(elem_id='txt2img_progress_row'):
-            with gr.Column(scale=1):
-                pass
-
-            with gr.Column(scale=1):
-                progressbar = gr.HTML(elem_id="txt2img_progressbar")
-                txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False)
-                setup_progressbar(progressbar, txt2img_preview, 'txt2img')
-
-        with gr.Row().style(equal_height=False):
-            with gr.Column(variant='panel', elem_id="txt2img_settings"):
-                for category in ordered_ui_categories():
-                    if category == "sampler":
-                        steps, sampler_index = create_sampler_and_steps_selection(samplers, "txt2img")
-
-                    elif category == "dimensions":
-                        with FormRow():
-                            with gr.Column(elem_id="txt2img_column_size", scale=4):
-                                width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="txt2img_width")
-                                height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="txt2img_height")
-
-                            if opts.dimensions_and_batch_together:
-                                with gr.Column(elem_id="txt2img_column_batch"):
-                                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
-                                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
-
-                    elif category == "cfg":
-                        cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="txt2img_cfg_scale")
-
-                    elif category == "seed":
-                        seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('txt2img')
-
-                    elif category == "checkboxes":
-                        with FormRow(elem_id="txt2img_checkboxes"):
-                            restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="txt2img_restore_faces")
-                            tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling")
-                            enable_hr = gr.Checkbox(label='Hires. fix', value=False, elem_id="txt2img_enable_hr")
-                            hr_final_resolution = FormHTML(value="", elem_id="txtimg_hr_finalres", label="Upscaled resolution", interactive=False)
-
-                    elif category == "hires_fix":
-                        with FormGroup(visible=False, elem_id="txt2img_hires_fix") as hr_options:
-                            with FormRow(elem_id="txt2img_hires_fix_row1"):
-                                hr_upscaler = gr.Dropdown(label="Upscaler", elem_id="txt2img_hr_upscaler", choices=[*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]], value=shared.latent_upscale_default_mode)
-                                hr_second_pass_steps = gr.Slider(minimum=0, maximum=150, step=1, label='Hires steps', value=0, elem_id="txt2img_hires_steps")
-                                denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7, elem_id="txt2img_denoising_strength")
-
-                            with FormRow(elem_id="txt2img_hires_fix_row2"):
-                                hr_scale = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Upscale by", value=2.0, elem_id="txt2img_hr_scale")
-                                hr_resize_x = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize width to", value=0, elem_id="txt2img_hr_resize_x")
-                                hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y")
-
-                    elif category == "batch":
-                        if not opts.dimensions_and_batch_together:
-                            with FormRow(elem_id="txt2img_column_batch"):
-                                batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
-                                batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
-
-                    elif category == "scripts":
-                        with FormGroup(elem_id="txt2img_script_container"):
-                            custom_inputs = modules.scripts.scripts_txt2img.setup_ui()
-
-            hr_resolution_preview_inputs = [enable_hr, width, height, hr_scale, hr_resize_x, hr_resize_y]
-            for input in hr_resolution_preview_inputs:
-                input.change(
-                    fn=calc_resolution_hires,
-                    inputs=hr_resolution_preview_inputs,
-                    outputs=[hr_final_resolution],
-                    show_progress=False,
-                )
-                input.change(
-                    None,
-                    _js="onCalcResolutionHires",
-                    inputs=hr_resolution_preview_inputs,
-                    outputs=[],
-                    show_progress=False,
-                )
-
-            txt2img_gallery, generation_info, html_info, html_log = create_output_panel("txt2img", opts.outdir_txt2img_samples)
-            parameters_copypaste.bind_buttons({"txt2img": txt2img_paste}, None, txt2img_prompt)
-
-            connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
-            connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
-
-            txt2img_args = dict(
-                fn=wrap_gradio_gpu_call(modules.txt2img.txt2img, extra_outputs=[None, '', '']),
-                _js="submit",
-                inputs=[
-                    txt2img_prompt,
-                    txt2img_negative_prompt,
-                    txt2img_prompt_style,
-                    txt2img_prompt_style2,
-                    steps,
-                    sampler_index,
-                    restore_faces,
-                    tiling,
-                    batch_count,
-                    batch_size,
-                    cfg_scale,
-                    seed,
-                    subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox,
-                    height,
-                    width,
-                    enable_hr,
-                    denoising_strength,
-                    hr_scale,
-                    hr_upscaler,
-                    hr_second_pass_steps,
-                    hr_resize_x,
-                    hr_resize_y,
-                ] + custom_inputs,
-
-                outputs=[
-                    txt2img_gallery,
-                    generation_info,
-                    html_info,
-                    html_log,
-                ],
-                show_progress=False,
-            )
-
-            txt2img_prompt.submit(**txt2img_args)
-            submit.click(**txt2img_args)
-
-            txt_prompt_img.change(
-                fn=modules.images.image_data,
-                inputs=[
-                    txt_prompt_img
-                ],
-                outputs=[
-                    txt2img_prompt,
-                    txt_prompt_img
-                ]
-            )
-
-            enable_hr.change(
-                fn=lambda x: gr_show(x),
-                inputs=[enable_hr],
-                outputs=[hr_options],
-                show_progress = False,
-            )
-
-            txt2img_paste_fields = [
-                (txt2img_prompt, "Prompt"),
-                (txt2img_negative_prompt, "Negative prompt"),
-                (steps, "Steps"),
-                (sampler_index, "Sampler"),
-                (restore_faces, "Face restoration"),
-                (cfg_scale, "CFG scale"),
-                (seed, "Seed"),
-                (width, "Size-1"),
-                (height, "Size-2"),
-                (batch_size, "Batch size"),
-                (subseed, "Variation seed"),
-                (subseed_strength, "Variation seed strength"),
-                (seed_resize_from_w, "Seed resize from-1"),
-                (seed_resize_from_h, "Seed resize from-2"),
-                (denoising_strength, "Denoising strength"),
-                (enable_hr, lambda d: "Denoising strength" in d),
-                (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)),
-                (hr_scale, "Hires upscale"),
-                (hr_upscaler, "Hires upscaler"),
-                (hr_second_pass_steps, "Hires steps"),
-                (hr_resize_x, "Hires resize-1"),
-                (hr_resize_y, "Hires resize-2"),
-                *modules.scripts.scripts_txt2img.infotext_fields
-            ]
-            parameters_copypaste.add_paste_fields("txt2img", None, txt2img_paste_fields)
-
-            txt2img_preview_params = [
-                txt2img_prompt,
-                txt2img_negative_prompt,
-                steps,
-                sampler_index,
-                cfg_scale,
-                seed,
-                width,
-                height,
-            ]
-
-            token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[txt2img_prompt, steps], outputs=[token_counter])
-
-    modules.scripts.scripts_current = modules.scripts.scripts_img2img
-    modules.scripts.scripts_img2img.initialize_scripts(is_img2img=True)
-
-    with gr.Blocks(analytics_enabled=False) as img2img_interface:
-        img2img_prompt, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,token_counter, token_button = create_toprow(is_img2img=True)
-
-        with gr.Row(elem_id='img2img_progress_row'):
-            img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False)
-
-            with gr.Column(scale=1):
-                pass
-
-            with gr.Column(scale=1):
-                progressbar = gr.HTML(elem_id="img2img_progressbar")
-                img2img_preview = gr.Image(elem_id='img2img_preview', visible=False)
-                setup_progressbar(progressbar, img2img_preview, 'img2img')
-
-        with FormRow().style(equal_height=False):
-            with gr.Column(variant='panel', elem_id="img2img_settings"):
-
-                with gr.Tabs(elem_id="mode_img2img") as tabs_img2img_mode:
-                    with gr.TabItem('img2img', id='img2img', elem_id="img2img_img2img_tab"):
-                        init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_img2img_tool, image_mode="RGBA").style(height=480)
-
-                    with gr.TabItem('Inpaint', id='inpaint', elem_id="img2img_inpaint_tab"):
-                        init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_inpaint_tool, image_mode="RGBA").style(height=480)
-                        init_img_with_mask_orig = gr.State(None)
-
-                        use_color_sketch = cmd_opts.gradio_inpaint_tool == "color-sketch"
-                        if use_color_sketch:
-                            def update_orig(image, state):
-                                if image is not None:
-                                    same_size = state is not None and state.size == image.size
-                                    has_exact_match = np.any(np.all(np.array(image) == np.array(state), axis=-1))
-                                    edited = same_size and has_exact_match
-                                    return image if not edited or state is None else state
-
-                            init_img_with_mask.change(update_orig, [init_img_with_mask, init_img_with_mask_orig], init_img_with_mask_orig)
-
-                        init_img_inpaint = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_base")
-                        init_mask_inpaint = gr.Image(label="Mask", source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_mask")
-
-                        with FormRow():
-                            mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id="img2img_mask_blur")
-                            mask_alpha = gr.Slider(label="Mask transparency", interactive=use_color_sketch, visible=use_color_sketch, elem_id="img2img_mask_alpha")
-
-                        with FormRow():
-                            mask_mode = gr.Radio(label="Mask source", choices=["Draw mask", "Upload mask"], type="index", value="Draw mask", elem_id="mask_mode")
-                            inpainting_mask_invert = gr.Radio(label='Mask mode', choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index", elem_id="img2img_mask_mode")
-
-                        with FormRow():
-                            inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='original', type="index", elem_id="img2img_inpainting_fill")
-
-                        with FormRow():
-                            with gr.Column():
-                                inpaint_full_res = gr.Radio(label="Inpaint area", choices=["Whole picture", "Only masked"], type="index", value="Whole picture", elem_id="img2img_inpaint_full_res")
-
-                            with gr.Column(scale=4):
-                                inpaint_full_res_padding = gr.Slider(label='Only masked padding, pixels', minimum=0, maximum=256, step=4, value=32, elem_id="img2img_inpaint_full_res_padding")
-
-                    with gr.TabItem('Batch img2img', id='batch', elem_id="img2img_batch_tab"):
-                        hidden = '<br>Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else ''
-                        gr.HTML(f"<p class=\"text-gray-500\">Process images in a directory on the same machine where the server is running.<br>Use an empty output directory to save pictures normally instead of writing to the output directory.{hidden}</p>")
-                        img2img_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, elem_id="img2img_batch_input_dir")
-                        img2img_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, elem_id="img2img_batch_output_dir")
-
-                with FormRow():
-                    resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", choices=["Just resize", "Crop and resize", "Resize and fill", "Just resize (latent upscale)"], type="index", value="Just resize")
-
-                for category in ordered_ui_categories():
-                    if category == "sampler":
-                        steps, sampler_index = create_sampler_and_steps_selection(samplers_for_img2img, "img2img")
-
-                    elif category == "dimensions":
-                        with FormRow():
-                            with gr.Column(elem_id="img2img_column_size", scale=4):
-                                width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
-                                height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
-
-                            if opts.dimensions_and_batch_together:
-                                with gr.Column(elem_id="img2img_column_batch"):
-                                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
-                                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")
-
-                    elif category == "cfg":
-                        with FormGroup():
-                            cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="img2img_cfg_scale")
-                            denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75, elem_id="img2img_denoising_strength")
-
-                    elif category == "seed":
-                        seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('img2img')
-
-                    elif category == "checkboxes":
-                        with FormRow(elem_id="img2img_checkboxes"):
-                            restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="img2img_restore_faces")
-                            tiling = gr.Checkbox(label='Tiling', value=False, elem_id="img2img_tiling")
-
-                    elif category == "batch":
-                        if not opts.dimensions_and_batch_together:
-                            with FormRow(elem_id="img2img_column_batch"):
-                                batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
-                                batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")
-
-                    elif category == "scripts":
-                        with FormGroup(elem_id="img2img_script_container"):
-                            custom_inputs = modules.scripts.scripts_img2img.setup_ui()
-
-            img2img_gallery, generation_info, html_info, html_log = create_output_panel("img2img", opts.outdir_img2img_samples)
-            parameters_copypaste.bind_buttons({"img2img": img2img_paste}, None, img2img_prompt)
-
-            connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
-            connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
-
-            img2img_prompt_img.change(
-                fn=modules.images.image_data,
-                inputs=[
-                    img2img_prompt_img
-                ],
-                outputs=[
-                    img2img_prompt,
-                    img2img_prompt_img
-                ]
-            )
-
-            mask_mode.change(
-                lambda mode, img: {
-                    init_img_with_mask: gr_show(mode == 0),
-                    init_img_inpaint: gr_show(mode == 1),
-                    init_mask_inpaint: gr_show(mode == 1),
-                },
-                inputs=[mask_mode, init_img_with_mask],
-                outputs=[
-                    init_img_with_mask,
-                    init_img_inpaint,
-                    init_mask_inpaint,
-                ],
-            )
-
-            img2img_args = dict(
-                fn=wrap_gradio_gpu_call(modules.img2img.img2img, extra_outputs=[None, '', '']),
-                _js="submit_img2img",
-                inputs=[
-                    dummy_component,
-                    img2img_prompt,
-                    img2img_negative_prompt,
-                    img2img_prompt_style,
-                    img2img_prompt_style2,
-                    init_img,
-                    init_img_with_mask,
-                    init_img_with_mask_orig,
-                    init_img_inpaint,
-                    init_mask_inpaint,
-                    mask_mode,
-                    steps,
-                    sampler_index,
-                    mask_blur,
-                    mask_alpha,
-                    inpainting_fill,
-                    restore_faces,
-                    tiling,
-                    batch_count,
-                    batch_size,
-                    cfg_scale,
-                    denoising_strength,
-                    seed,
-                    subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox,
-                    height,
-                    width,
-                    resize_mode,
-                    inpaint_full_res,
-                    inpaint_full_res_padding,
-                    inpainting_mask_invert,
-                    img2img_batch_input_dir,
-                    img2img_batch_output_dir,
-                ] + custom_inputs,
-                outputs=[
-                    img2img_gallery,
-                    generation_info,
-                    html_info,
-                    html_log,
-                ],
-                show_progress=False,
-            )
-
-            img2img_prompt.submit(**img2img_args)
-            submit.click(**img2img_args)
-
-            img2img_interrogate.click(
-                fn=interrogate,
-                inputs=[init_img],
-                outputs=[img2img_prompt],
-            )
-
-            img2img_deepbooru.click(
-                fn=interrogate_deepbooru,
-                inputs=[init_img],
-                outputs=[img2img_prompt],
-            )
-
-            prompts = [(txt2img_prompt, txt2img_negative_prompt), (img2img_prompt, img2img_negative_prompt)]
-            style_dropdowns = [(txt2img_prompt_style, txt2img_prompt_style2), (img2img_prompt_style, img2img_prompt_style2)]
-            style_js_funcs = ["update_txt2img_tokens", "update_img2img_tokens"]
-
-            for button, (prompt, negative_prompt) in zip([txt2img_save_style, img2img_save_style], prompts):
-                button.click(
-                    fn=add_style,
-                    _js="ask_for_style_name",
-                    # Have to pass empty dummy component here, because the JavaScript and Python function have to accept
-                    # the same number of parameters, but we only know the style-name after the JavaScript prompt
-                    inputs=[dummy_component, prompt, negative_prompt],
-                    outputs=[txt2img_prompt_style, img2img_prompt_style, txt2img_prompt_style2, img2img_prompt_style2],
-                )
-
-            for button, (prompt, negative_prompt), (style1, style2), js_func in zip([txt2img_prompt_style_apply, img2img_prompt_style_apply], prompts, style_dropdowns, style_js_funcs):
-                button.click(
-                    fn=apply_styles,
-                    _js=js_func,
-                    inputs=[prompt, negative_prompt, style1, style2],
-                    outputs=[prompt, negative_prompt, style1, style2],
-                )
-
-            token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter])
-
-            img2img_paste_fields = [
-                (img2img_prompt, "Prompt"),
-                (img2img_negative_prompt, "Negative prompt"),
-                (steps, "Steps"),
-                (sampler_index, "Sampler"),
-                (restore_faces, "Face restoration"),
-                (cfg_scale, "CFG scale"),
-                (seed, "Seed"),
-                (width, "Size-1"),
-                (height, "Size-2"),
-                (batch_size, "Batch size"),
-                (subseed, "Variation seed"),
-                (subseed_strength, "Variation seed strength"),
-                (seed_resize_from_w, "Seed resize from-1"),
-                (seed_resize_from_h, "Seed resize from-2"),
-                (denoising_strength, "Denoising strength"),
-                (mask_blur, "Mask blur"),
-                *modules.scripts.scripts_img2img.infotext_fields
-            ]
-            parameters_copypaste.add_paste_fields("img2img", init_img, img2img_paste_fields)
-            parameters_copypaste.add_paste_fields("inpaint", init_img_with_mask, img2img_paste_fields)
-
-    modules.scripts.scripts_current = None
-
-    with gr.Blocks(analytics_enabled=False) as extras_interface:
-        with gr.Row().style(equal_height=False):
-            with gr.Column(variant='panel'):
-                with gr.Tabs(elem_id="mode_extras"):
-                    with gr.TabItem('Single Image', elem_id="extras_single_tab"):
-                        extras_image = gr.Image(label="Source", source="upload", interactive=True, type="pil", elem_id="extras_image")
-
-                    with gr.TabItem('Batch Process', elem_id="extras_batch_process_tab"):
-                        image_batch = gr.File(label="Batch Process", file_count="multiple", interactive=True, type="file", elem_id="extras_image_batch")
-
-                    with gr.TabItem('Batch from Directory', elem_id="extras_batch_directory_tab"):
-                        extras_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, placeholder="A directory on the same machine where the server is running.", elem_id="extras_batch_input_dir")
-                        extras_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, placeholder="Leave blank to save images to the default path.", elem_id="extras_batch_output_dir")
-                        show_extras_results = gr.Checkbox(label='Show result images', value=True, elem_id="extras_show_extras_results")
-
-                submit = gr.Button('Generate', elem_id="extras_generate", variant='primary')
-
-                with gr.Tabs(elem_id="extras_resize_mode"):
-                    with gr.TabItem('Scale by', elem_id="extras_scale_by_tab"):
-                        upscaling_resize = gr.Slider(minimum=1.0, maximum=8.0, step=0.05, label="Resize", value=4, elem_id="extras_upscaling_resize")
-                    with gr.TabItem('Scale to', elem_id="extras_scale_to_tab"):
-                        with gr.Group():
-                            with gr.Row():
-                                upscaling_resize_w = gr.Number(label="Width", value=512, precision=0, elem_id="extras_upscaling_resize_w")
-                                upscaling_resize_h = gr.Number(label="Height", value=512, precision=0, elem_id="extras_upscaling_resize_h")
-                            upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop")
-
-                with gr.Group():
-                    extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
-
-                with gr.Group():
-                    extras_upscaler_2 = gr.Radio(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
-                    extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=1, elem_id="extras_upscaler_2_visibility")
-
-                with gr.Group():
-                    gfpgan_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="GFPGAN visibility", value=0, interactive=modules.gfpgan_model.have_gfpgan, elem_id="extras_gfpgan_visibility")
-
-                with gr.Group():
-                    codeformer_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer visibility", value=0, interactive=modules.codeformer_model.have_codeformer, elem_id="extras_codeformer_visibility")
-                    codeformer_weight = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer weight (0 = maximum effect, 1 = minimum effect)", value=0, interactive=modules.codeformer_model.have_codeformer, elem_id="extras_codeformer_weight")
-
-                with gr.Group():
-                    upscale_before_face_fix = gr.Checkbox(label='Upscale Before Restoring Faces', value=False, elem_id="extras_upscale_before_face_fix")
-
-            result_images, html_info_x, html_info, html_log = create_output_panel("extras", opts.outdir_extras_samples)
-
-        submit.click(
-            fn=wrap_gradio_gpu_call(modules.extras.run_extras, extra_outputs=[None, '']),
-            _js="get_extras_tab_index",
-            inputs=[
-                dummy_component,
-                dummy_component,
-                extras_image,
-                image_batch,
-                extras_batch_input_dir,
-                extras_batch_output_dir,
-                show_extras_results,
-                gfpgan_visibility,
-                codeformer_visibility,
-                codeformer_weight,
-                upscaling_resize,
-                upscaling_resize_w,
-                upscaling_resize_h,
-                upscaling_crop,
-                extras_upscaler_1,
-                extras_upscaler_2,
-                extras_upscaler_2_visibility,
-                upscale_before_face_fix,
-            ],
-            outputs=[
-                result_images,
-                html_info_x,
-                html_info,
-            ]
-        )
-        parameters_copypaste.add_paste_fields("extras", extras_image, None)
-
-        extras_image.change(
-            fn=modules.extras.clear_cache,
-            inputs=[], outputs=[]
-        )
-
-    with gr.Blocks(analytics_enabled=False) as pnginfo_interface:
-        with gr.Row().style(equal_height=False):
-            with gr.Column(variant='panel'):
-                image = gr.Image(elem_id="pnginfo_image", label="Source", source="upload", interactive=True, type="pil")
-
-            with gr.Column(variant='panel'):
-                html = gr.HTML()
-                generation_info = gr.Textbox(visible=False, elem_id="pnginfo_generation_info")
-                html2 = gr.HTML()
-                with gr.Row():
-                    buttons = parameters_copypaste.create_buttons(["txt2img", "img2img", "inpaint", "extras"])
-                parameters_copypaste.bind_buttons(buttons, image, generation_info)
-
-        image.change(
-            fn=wrap_gradio_call(modules.extras.run_pnginfo),
-            inputs=[image],
-            outputs=[html, generation_info, html2],
-        )
-
-    with gr.Blocks(analytics_enabled=False) as modelmerger_interface:
-        with gr.Row().style(equal_height=False):
-            with gr.Column(variant='panel'):
-                gr.HTML(value="<p>A merger of the two checkpoints will be generated in your <b>checkpoint</b> directory.</p>")
-
-                with gr.Row():
-                    primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)")
-                    create_refresh_button(primary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_A")
-
-                    secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary model (B)")
-                    create_refresh_button(secondary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_B")
-
-                    tertiary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_tertiary_model_name", label="Tertiary model (C)")
-                    create_refresh_button(tertiary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_C")
-
-                custom_name = gr.Textbox(label="Custom Name (Optional)", elem_id="modelmerger_custom_name")
-                interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3, elem_id="modelmerger_interp_amount")
-                interp_method = gr.Radio(choices=["Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method", elem_id="modelmerger_interp_method")
-
-                with gr.Row():
-                    checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format", elem_id="modelmerger_checkpoint_format")
-                    save_as_half = gr.Checkbox(value=False, label="Save as float16", elem_id="modelmerger_save_as_half")
-
-                modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary')
-
-            with gr.Column(variant='panel'):
-                submit_result = gr.Textbox(elem_id="modelmerger_result", show_label=False)
-
-    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>")
-
-        with gr.Row().style(equal_height=False):
-            with gr.Tabs(elem_id="train_tabs"):
-
-                with gr.Tab(label="Create embedding"):
-                    new_embedding_name = gr.Textbox(label="Name", elem_id="train_new_embedding_name")
-                    initialization_text = gr.Textbox(label="Initialization text", value="*", elem_id="train_initialization_text")
-                    nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1, elem_id="train_nvpt")
-                    overwrite_old_embedding = gr.Checkbox(value=False, label="Overwrite Old Embedding", elem_id="train_overwrite_old_embedding")
-
-                    with gr.Row():
-                        with gr.Column(scale=3):
-                            gr.HTML(value="")
-
-                        with gr.Column():
-                            create_embedding = gr.Button(value="Create embedding", variant='primary', elem_id="train_create_embedding")
-
-                with gr.Tab(label="Create hypernetwork"):
-                    new_hypernetwork_name = gr.Textbox(label="Name", elem_id="train_new_hypernetwork_name")
-                    new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "1024", "320", "640", "1280"], elem_id="train_new_hypernetwork_sizes")
-                    new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'", elem_id="train_new_hypernetwork_layer_structure")
-                    new_hypernetwork_activation_func = gr.Dropdown(value="linear", label="Select activation function of hypernetwork. Recommended : Swish / Linear(none)", choices=modules.hypernetworks.ui.keys, elem_id="train_new_hypernetwork_activation_func")
-                    new_hypernetwork_initialization_option = gr.Dropdown(value = "Normal", label="Select Layer weights initialization. Recommended: Kaiming for relu-like, Xavier for sigmoid-like, Normal otherwise", choices=["Normal", "KaimingUniform", "KaimingNormal", "XavierUniform", "XavierNormal"], elem_id="train_new_hypernetwork_initialization_option")
-                    new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization", elem_id="train_new_hypernetwork_add_layer_norm")
-                    new_hypernetwork_use_dropout = gr.Checkbox(label="Use dropout", elem_id="train_new_hypernetwork_use_dropout")
-                    new_hypernetwork_dropout_structure = gr.Textbox("0, 0, 0", label="Enter hypernetwork Dropout structure (or empty). Recommended : 0~0.35 incrementing sequence: 0, 0.05, 0.15", placeholder="1st and last digit must be 0 and values should be between 0 and 1. ex:'0, 0.01, 0'")
-                    overwrite_old_hypernetwork = gr.Checkbox(value=False, label="Overwrite Old Hypernetwork", elem_id="train_overwrite_old_hypernetwork")
-
-                    with gr.Row():
-                        with gr.Column(scale=3):
-                            gr.HTML(value="")
-
-                        with gr.Column():
-                            create_hypernetwork = gr.Button(value="Create hypernetwork", variant='primary', elem_id="train_create_hypernetwork")
-
-                with gr.Tab(label="Preprocess images"):
-                    process_src = gr.Textbox(label='Source directory', elem_id="train_process_src")
-                    process_dst = gr.Textbox(label='Destination directory', elem_id="train_process_dst")
-                    process_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_process_width")
-                    process_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_process_height")
-                    preprocess_txt_action = gr.Dropdown(label='Existing Caption txt Action', value="ignore", choices=["ignore", "copy", "prepend", "append"], elem_id="train_preprocess_txt_action")
-
-                    with gr.Row():
-                        process_flip = gr.Checkbox(label='Create flipped copies', elem_id="train_process_flip")
-                        process_split = gr.Checkbox(label='Split oversized images', elem_id="train_process_split")
-                        process_focal_crop = gr.Checkbox(label='Auto focal point crop', elem_id="train_process_focal_crop")
-                        process_caption = gr.Checkbox(label='Use BLIP for caption', elem_id="train_process_caption")
-                        process_caption_deepbooru = gr.Checkbox(label='Use deepbooru for caption', visible=True, elem_id="train_process_caption_deepbooru")
-
-                    with gr.Row(visible=False) as process_split_extra_row:
-                        process_split_threshold = gr.Slider(label='Split image threshold', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_split_threshold")
-                        process_overlap_ratio = gr.Slider(label='Split image overlap ratio', value=0.2, minimum=0.0, maximum=0.9, step=0.05, elem_id="train_process_overlap_ratio")
-
-                    with gr.Row(visible=False) as process_focal_crop_row:
-                        process_focal_crop_face_weight = gr.Slider(label='Focal point face weight', value=0.9, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_face_weight")
-                        process_focal_crop_entropy_weight = gr.Slider(label='Focal point entropy weight', value=0.15, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_entropy_weight")
-                        process_focal_crop_edges_weight = gr.Slider(label='Focal point edges weight', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_edges_weight")
-                        process_focal_crop_debug = gr.Checkbox(label='Create debug image', elem_id="train_process_focal_crop_debug")
-
-                    with gr.Row():
-                        with gr.Column(scale=3):
-                            gr.HTML(value="")
-
-                        with gr.Column():
-                            with gr.Row():
-                                interrupt_preprocessing = gr.Button("Interrupt", elem_id="train_interrupt_preprocessing")
-                            run_preprocess = gr.Button(value="Preprocess", variant='primary', elem_id="train_run_preprocess")
-
-                    process_split.change(
-                        fn=lambda show: gr_show(show),
-                        inputs=[process_split],
-                        outputs=[process_split_extra_row],
-                    )
-
-                    process_focal_crop.change(
-                        fn=lambda show: gr_show(show),
-                        inputs=[process_focal_crop],
-                        outputs=[process_focal_crop_row],
-                    )
-
-                def get_textual_inversion_template_names():
-                    return sorted([x for x in textual_inversion.textual_inversion_templates])
-
-                with gr.Tab(label="Train"):
-                    gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images <a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\" style=\"font-weight:bold;\">[wiki]</a></p>")
-                    with FormRow():
-                        train_embedding_name = gr.Dropdown(label='Embedding', elem_id="train_embedding", choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
-                        create_refresh_button(train_embedding_name, sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings, lambda: {"choices": sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())}, "refresh_train_embedding_name")
-
-                        train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=[x for x in shared.hypernetworks.keys()])
-                        create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted([x for x in shared.hypernetworks.keys()])}, "refresh_train_hypernetwork_name")
-
-                    with FormRow():
-                        embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005", elem_id="train_embedding_learn_rate")
-                        hypernetwork_learn_rate = gr.Textbox(label='Hypernetwork Learning rate', placeholder="Hypernetwork Learning rate", value="0.00001", elem_id="train_hypernetwork_learn_rate")
-                    
-                    with FormRow():
-                        clip_grad_mode = gr.Dropdown(value="disabled", label="Gradient Clipping", choices=["disabled", "value", "norm"])
-                        clip_grad_value = gr.Textbox(placeholder="Gradient clip value", value="0.1", show_label=False)
-
-                    with FormRow():
-                        batch_size = gr.Number(label='Batch size', value=1, precision=0, elem_id="train_batch_size")
-                        gradient_step = gr.Number(label='Gradient accumulation steps', value=1, precision=0, elem_id="train_gradient_step")
-
-                    dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images", elem_id="train_dataset_directory")
-                    log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion", elem_id="train_log_directory")
-
-                    with FormRow():
-                        template_file = gr.Dropdown(label='Prompt template', value="style_filewords.txt", elem_id="train_template_file", choices=get_textual_inversion_template_names())
-                        create_refresh_button(template_file, textual_inversion.list_textual_inversion_templates, lambda: {"choices": get_textual_inversion_template_names()}, "refrsh_train_template_file")
-
-                    training_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_training_width")
-                    training_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_training_height")
-                    varsize = gr.Checkbox(label="Do not resize images", value=False, elem_id="train_varsize")
-                    steps = gr.Number(label='Max steps', value=100000, precision=0, elem_id="train_steps")
-
-                    with FormRow():
-                        create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0, elem_id="train_create_image_every")
-                        save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0, elem_id="train_save_embedding_every")
-
-                    save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True, elem_id="train_save_image_with_stored_embedding")
-                    preview_from_txt2img = gr.Checkbox(label='Read parameters (prompt, etc...) from txt2img tab when making previews', value=False, elem_id="train_preview_from_txt2img")
-
-                    shuffle_tags = gr.Checkbox(label="Shuffle tags by ',' when creating prompts.", value=False, elem_id="train_shuffle_tags")
-                    tag_drop_out = gr.Slider(minimum=0, maximum=1, step=0.1, label="Drop out tags when creating prompts.", value=0, elem_id="train_tag_drop_out")
-
-                    latent_sampling_method = gr.Radio(label='Choose latent sampling method', value="once", choices=['once', 'deterministic', 'random'], elem_id="train_latent_sampling_method")
-
-                    with gr.Row():
-                        train_embedding = gr.Button(value="Train Embedding", variant='primary', elem_id="train_train_embedding")
-                        interrupt_training = gr.Button(value="Interrupt", elem_id="train_interrupt_training")
-                        train_hypernetwork = gr.Button(value="Train Hypernetwork", variant='primary', elem_id="train_train_hypernetwork")
-
-                params = script_callbacks.UiTrainTabParams(txt2img_preview_params)
-
-                script_callbacks.ui_train_tabs_callback(params)
-
-            with gr.Column():
-                progressbar = gr.HTML(elem_id="ti_progressbar")
-                ti_output = gr.Text(elem_id="ti_output", value="", show_label=False)
-
-                ti_gallery = gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(grid=4)
-                ti_preview = gr.Image(elem_id='ti_preview', visible=False)
-                ti_progress = gr.HTML(elem_id="ti_progress", value="")
-                ti_outcome = gr.HTML(elem_id="ti_error", value="")
-                setup_progressbar(progressbar, ti_preview, 'ti', textinfo=ti_progress)
-
-        create_embedding.click(
-            fn=modules.textual_inversion.ui.create_embedding,
-            inputs=[
-                new_embedding_name,
-                initialization_text,
-                nvpt,
-                overwrite_old_embedding,
-            ],
-            outputs=[
-                train_embedding_name,
-                ti_output,
-                ti_outcome,
-            ]
-        )
-
-        create_hypernetwork.click(
-            fn=modules.hypernetworks.ui.create_hypernetwork,
-            inputs=[
-                new_hypernetwork_name,
-                new_hypernetwork_sizes,
-                overwrite_old_hypernetwork,
-                new_hypernetwork_layer_structure,
-                new_hypernetwork_activation_func,
-                new_hypernetwork_initialization_option,
-                new_hypernetwork_add_layer_norm,
-                new_hypernetwork_use_dropout,
-                new_hypernetwork_dropout_structure
-            ],
-            outputs=[
-                train_hypernetwork_name,
-                ti_output,
-                ti_outcome,
-            ]
-        )
-
-        run_preprocess.click(
-            fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]),
-            _js="start_training_textual_inversion",
-            inputs=[
-                process_src,
-                process_dst,
-                process_width,
-                process_height,
-                preprocess_txt_action,
-                process_flip,
-                process_split,
-                process_caption,
-                process_caption_deepbooru,
-                process_split_threshold,
-                process_overlap_ratio,
-                process_focal_crop,
-                process_focal_crop_face_weight,
-                process_focal_crop_entropy_weight,
-                process_focal_crop_edges_weight,
-                process_focal_crop_debug,
-            ],
-            outputs=[
-                ti_output,
-                ti_outcome,
-            ],
-        )
-
-        train_embedding.click(
-            fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.train_embedding, extra_outputs=[gr.update()]),
-            _js="start_training_textual_inversion",
-            inputs=[
-                train_embedding_name,
-                embedding_learn_rate,
-                batch_size,
-                gradient_step,
-                dataset_directory,
-                log_directory,
-                training_width,
-                training_height,
-                varsize,
-                steps,
-                clip_grad_mode,
-                clip_grad_value,
-                shuffle_tags,
-                tag_drop_out,
-                latent_sampling_method,
-                create_image_every,
-                save_embedding_every,
-                template_file,
-                save_image_with_stored_embedding,
-                preview_from_txt2img,
-                *txt2img_preview_params,
-            ],
-            outputs=[
-                ti_output,
-                ti_outcome,
-            ]
-        )
-
-        train_hypernetwork.click(
-            fn=wrap_gradio_gpu_call(modules.hypernetworks.ui.train_hypernetwork, extra_outputs=[gr.update()]),
-            _js="start_training_textual_inversion",
-            inputs=[
-                train_hypernetwork_name,
-                hypernetwork_learn_rate,
-                batch_size,
-                gradient_step,
-                dataset_directory,
-                log_directory,
-                training_width,
-                training_height,
-                varsize,
-                steps,
-                clip_grad_mode,
-                clip_grad_value,
-                shuffle_tags,
-                tag_drop_out,
-                latent_sampling_method,
-                create_image_every,
-                save_embedding_every,
-                template_file,
-                preview_from_txt2img,
-                *txt2img_preview_params,
-            ],
-            outputs=[
-                ti_output,
-                ti_outcome,
-            ]
-        )
-
-        interrupt_training.click(
-            fn=lambda: shared.state.interrupt(),
-            inputs=[],
-            outputs=[],
-        )
-
-        interrupt_preprocessing.click(
-            fn=lambda: shared.state.interrupt(),
-            inputs=[],
-            outputs=[],
-        )
-
-    def create_setting_component(key, is_quicksettings=False):
-        def fun():
-            return opts.data[key] if key in opts.data else opts.data_labels[key].default
-
-        info = opts.data_labels[key]
-        t = type(info.default)
-
-        args = info.component_args() if callable(info.component_args) else info.component_args
-
-        if info.component is not None:
-            comp = info.component
-        elif t == str:
-            comp = gr.Textbox
-        elif t == int:
-            comp = gr.Number
-        elif t == bool:
-            comp = gr.Checkbox
-        else:
-            raise Exception(f'bad options item type: {str(t)} for key {key}')
-
-        elem_id = "setting_"+key
-
-        if info.refresh is not None:
-            if is_quicksettings:
-                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 FormRow():
-                    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 {}))
-
-        return res
-
-    components = []
-    component_dict = {}
-
-    script_callbacks.ui_settings_callback()
-    opts.reorder()
-
-    def run_settings(*args):
-        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__}"
-
-        for key, value, comp in zip(opts.data_labels.keys(), args, components):
-            if comp == dummy_component:
-                continue
-
-            if opts.set(key, value):
-                changed.append(key)
-
-        try:
-            opts.save(shared.config_filename)
-        except RuntimeError:
-            return opts.dumpjson(), f'{len(changed)} settings changed without save: {", ".join(changed)}.'
-        return opts.dumpjson(), f'{len(changed)} settings changed{": " if len(changed) > 0 else ""}{", ".join(changed)}.'
-
-    def run_settings_single(value, key):
-        if not opts.same_type(value, opts.data_labels[key].default):
-            return gr.update(visible=True), opts.dumpjson()
-
-        if not opts.set(key, value):
-            return gr.update(value=getattr(opts, key)), opts.dumpjson()
-
-        opts.save(shared.config_filename)
-
-        return gr.update(value=value), opts.dumpjson()
-
-    with gr.Blocks(analytics_enabled=False) as settings_interface:
-        with gr.Row():
-            with gr.Column(scale=6):
-                settings_submit = gr.Button(value="Apply settings", variant='primary', elem_id="settings_submit")
-            with gr.Column():
-                restart_gradio = gr.Button(value='Reload UI', variant='primary', elem_id="settings_restart_gradio")
-
-        result = gr.HTML(elem_id="settings_result")
-
-        quicksettings_names = [x.strip() for x in opts.quicksettings.split(",")]
-        quicksettings_names = {x: i for i, x in enumerate(quicksettings_names) if x != 'quicksettings'}
-
-        quicksettings_list = []
-
-        previous_section = None
-        current_tab = None
-        with gr.Tabs(elem_id="settings"):
-            for i, (k, item) in enumerate(opts.data_labels.items()):
-                section_must_be_skipped = item.section[0] is None
-
-                if previous_section != item.section and not section_must_be_skipped:
-                    elem_id, text = item.section
-
-                    if current_tab is not None:
-                        current_tab.__exit__()
-
-                    current_tab = gr.TabItem(elem_id="settings_{}".format(elem_id), label=text)
-                    current_tab.__enter__()
-
-                    previous_section = item.section
-
-                if k in quicksettings_names and not shared.cmd_opts.freeze_settings:
-                    quicksettings_list.append((i, k, item))
-                    components.append(dummy_component)
-                elif section_must_be_skipped:
-                    components.append(dummy_component)
-                else:
-                    component = create_setting_component(k)
-                    component_dict[k] = component
-                    components.append(component)
-
-            if current_tab is not None:
-                current_tab.__exit__()
-
-            with gr.TabItem("Actions"):
-                request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications")
-                download_localization = gr.Button(value='Download localization template', elem_id="download_localization")
-                reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary', elem_id="settings_reload_script_bodies")
-
-            if os.path.exists("html/licenses.html"):
-                with open("html/licenses.html", encoding="utf8") as file:
-                    with gr.TabItem("Licenses"):
-                        gr.HTML(file.read(), elem_id="licenses")
-
-            gr.Button(value="Show all pages", elem_id="settings_show_all_pages")
-
-        request_notifications.click(
-            fn=lambda: None,
-            inputs=[],
-            outputs=[],
-            _js='function(){}'
-        )
-
-        download_localization.click(
-            fn=lambda: None,
-            inputs=[],
-            outputs=[],
-            _js='download_localization'
-        )
-
-        def reload_scripts():
-            modules.scripts.reload_script_body_only()
-            reload_javascript()  # need to refresh the html page
-
-        reload_script_bodies.click(
-            fn=reload_scripts,
-            inputs=[],
-            outputs=[]
-        )
-
-        def request_restart():
-            shared.state.interrupt()
-            shared.state.need_restart = True
-
-        restart_gradio.click(
-            fn=request_restart,
-            _js='restart_reload',
-            inputs=[],
-            outputs=[],
-        )
-
-    interfaces = [
-        (txt2img_interface, "txt2img", "txt2img"),
-        (img2img_interface, "img2img", "img2img"),
-        (extras_interface, "Extras", "extras"),
-        (pnginfo_interface, "PNG Info", "pnginfo"),
-        (modelmerger_interface, "Checkpoint Merger", "modelmerger"),
-        (train_interface, "Train", "ti"),
-    ]
-
-    css = ""
-
-    for cssfile in modules.scripts.list_files_with_name("style.css"):
-        if not os.path.isfile(cssfile):
-            continue
-
-        with open(cssfile, "r", encoding="utf8") as file:
-            css += file.read() + "\n"
-
-    if os.path.exists(os.path.join(script_path, "user.css")):
-        with open(os.path.join(script_path, "user.css"), "r", encoding="utf8") as file:
-            css += file.read() + "\n"
-
-    if not cmd_opts.no_progressbar_hiding:
-        css += css_hide_progressbar
-
-    interfaces += script_callbacks.ui_tabs_callback()
-    interfaces += [(settings_interface, "Settings", "settings")]
-
-    extensions_interface = ui_extensions.create_ui()
-    interfaces += [(extensions_interface, "Extensions", "extensions")]
-
-    with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion") as demo:
-        with gr.Row(elem_id="quicksettings"):
-            for i, k, item in sorted(quicksettings_list, key=lambda x: quicksettings_names.get(x[1], x[0])):
-                component = create_setting_component(k, is_quicksettings=True)
-                component_dict[k] = component
-
-        parameters_copypaste.integrate_settings_paste_fields(component_dict)
-        parameters_copypaste.run_bind()
-
-        with gr.Tabs(elem_id="tabs") as tabs:
-            for interface, label, ifid in interfaces:
-                with gr.TabItem(label, id=ifid, elem_id='tab_' + ifid):
-                    interface.render()
-
-        if os.path.exists(os.path.join(script_path, "notification.mp3")):
-            audio_notification = gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False)
-
-        if os.path.exists("html/footer.html"):
-            with open("html/footer.html", encoding="utf8") as file:
-                footer = file.read()
-                footer = footer.format(versions=versions_html())
-                gr.HTML(footer, elem_id="footer")
-
-        text_settings = gr.Textbox(elem_id="settings_json", value=lambda: opts.dumpjson(), visible=False)
-        settings_submit.click(
-            fn=wrap_gradio_call(run_settings, extra_outputs=[gr.update()]),
-            inputs=components,
-            outputs=[text_settings, result],
-        )
-
-        for i, k, item in quicksettings_list:
-            component = component_dict[k]
-
-            component.change(
-                fn=lambda value, k=k: run_settings_single(value, key=k),
-                inputs=[component],
-                outputs=[component, text_settings],
-            )
-
-        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)
-            except Exception as e:
-                print("Error loading/saving model file:", file=sys.stderr)
-                print(traceback.format_exc(), file=sys.stderr)
-                modules.sd_models.list_models()  # to remove the potentially missing models from the list
-                return [f"Error merging checkpoints: {e}"] + [gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(4)]
-            return results
-
-        modelmerger_merge.click(
-            fn=modelmerger,
-            inputs=[
-                primary_model_name,
-                secondary_model_name,
-                tertiary_model_name,
-                interp_method,
-                interp_amount,
-                save_as_half,
-                custom_name,
-                checkpoint_format,
-            ],
-            outputs=[
-                submit_result,
-                primary_model_name,
-                secondary_model_name,
-                tertiary_model_name,
-                component_dict['sd_model_checkpoint'],
-            ]
-        )
-
-    ui_config_file = cmd_opts.ui_config_file
-    ui_settings = {}
-    settings_count = len(ui_settings)
-    error_loading = False
-
-    try:
-        if os.path.exists(ui_config_file):
-            with open(ui_config_file, "r", encoding="utf8") as file:
-                ui_settings = json.load(file)
-    except Exception:
-        error_loading = True
-        print("Error loading settings:", file=sys.stderr)
-        print(traceback.format_exc(), file=sys.stderr)
-
-    def loadsave(path, x):
-        def apply_field(obj, field, condition=None, init_field=None):
-            key = path + "/" + field
-
-            if getattr(obj, 'custom_script_source', None) is not None:
-              key = 'customscript/' + obj.custom_script_source + '/' + key
-
-            if getattr(obj, 'do_not_save_to_config', False):
-                return
-
-            saved_value = ui_settings.get(key, None)
-            if saved_value is None:
-                ui_settings[key] = getattr(obj, field)
-            elif condition and not condition(saved_value):
-                print(f'Warning: Bad ui setting value: {key}: {saved_value}; Default value "{getattr(obj, field)}" will be used instead.')
-            else:
-                setattr(obj, field, saved_value)
-                if init_field is not None:
-                    init_field(saved_value)
-
-        if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number, gr.Dropdown] and x.visible:
-            apply_field(x, 'visible')
-
-        if type(x) == gr.Slider:
-            apply_field(x, 'value')
-            apply_field(x, 'minimum')
-            apply_field(x, 'maximum')
-            apply_field(x, 'step')
-
-        if type(x) == gr.Radio:
-            apply_field(x, 'value', lambda val: val in x.choices)
-
-        if type(x) == gr.Checkbox:
-            apply_field(x, 'value')
-
-        if type(x) == gr.Textbox:
-            apply_field(x, 'value')
-
-        if type(x) == gr.Number:
-            apply_field(x, 'value')
-
-        if type(x) == gr.Dropdown:
-            apply_field(x, 'value', lambda val: val in x.choices, getattr(x, 'init_field', None))
-
-    visit(txt2img_interface, loadsave, "txt2img")
-    visit(img2img_interface, loadsave, "img2img")
-    visit(extras_interface, loadsave, "extras")
-    visit(modelmerger_interface, loadsave, "modelmerger")
-    visit(train_interface, loadsave, "train")
-
-    if not error_loading and (not os.path.exists(ui_config_file) or settings_count != len(ui_settings)):
-        with open(ui_config_file, "w", encoding="utf8") as file:
-            json.dump(ui_settings, file, indent=4)
-
-    return demo
-
-
-def reload_javascript():
-    with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile:
-        javascript = f'<script>{jsfile.read()}</script>'
-
-    scripts_list = modules.scripts.list_scripts("javascript", ".js")
-
-    for basedir, filename, path in scripts_list:
-        with open(path, "r", encoding="utf8") as jsfile:
-            javascript += f"\n<!-- {filename} --><script>{jsfile.read()}</script>"
-
-    if cmd_opts.theme is not None:
-        javascript += f"\n<script>set_theme('{cmd_opts.theme}');</script>\n"
-
-    javascript += f"\n<script>{localization.localization_js(shared.opts.localization)}</script>"
-
-    def template_response(*args, **kwargs):
-        res = shared.GradioTemplateResponseOriginal(*args, **kwargs)
-        res.body = res.body.replace(
-            b'</head>', f'{javascript}</head>'.encode("utf8"))
-        res.init_headers()
-        return res
-
-    gradio.routes.templates.TemplateResponse = template_response
-
-
-if not hasattr(shared, 'GradioTemplateResponseOriginal'):
-    shared.GradioTemplateResponseOriginal = gradio.routes.templates.TemplateResponse
-
-
-def versions_html():
-    import torch
-    import launch
-
-    python_version = ".".join([str(x) for x in sys.version_info[0:3]])
-    commit = launch.commit_hash()
-    short_commit = commit[0:8]
-
-    if shared.xformers_available:
-        import xformers
-        xformers_version = xformers.__version__
-    else:
-        xformers_version = "N/A"
-
-    return f"""
-python: <span title="{sys.version}">{python_version}</span>
- • 
-torch: {torch.__version__}
- • 
-xformers: {xformers_version}
- • 
-gradio: {gr.__version__}
- • 
-commit: <a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui/commit/{commit}">{short_commit}</a>
-"""
-- 
cgit v1.2.3


From 54dd5d6634ead25311a8bea0484675607601a21a Mon Sep 17 00:00:00 2001
From: Andrey <16777216c@gmail.com>
Date: Tue, 10 Jan 2023 11:54:49 +0300
Subject: Split history ui.py to ui_progress.py

---
 modules/temp  | 1928 ---------------------------------------------------------
 modules/ui.py | 1928 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 2 files changed, 1928 insertions(+), 1928 deletions(-)
 delete mode 100644 modules/temp
 create mode 100644 modules/ui.py

(limited to 'modules/ui.py')

diff --git a/modules/temp b/modules/temp
deleted file mode 100644
index 9b9081b5..00000000
--- a/modules/temp
+++ /dev/null
@@ -1,1928 +0,0 @@
-import html
-import json
-import math
-import mimetypes
-import os
-import platform
-import random
-import subprocess as sp
-import sys
-import tempfile
-import time
-import traceback
-from functools import partial, reduce
-
-import gradio as gr
-import gradio.routes
-import gradio.utils
-import numpy as np
-from PIL import Image, PngImagePlugin
-from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
-
-from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru
-from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
-from modules.paths import script_path
-
-from modules.shared import opts, cmd_opts, restricted_opts
-
-import modules.codeformer_model
-import modules.generation_parameters_copypaste as parameters_copypaste
-import modules.gfpgan_model
-import modules.hypernetworks.ui
-import modules.scripts
-import modules.shared as shared
-import modules.styles
-import modules.textual_inversion.ui
-from modules import prompt_parser
-from modules.images import save_image
-from modules.sd_hijack import model_hijack
-from modules.sd_samplers import samplers, samplers_for_img2img
-from modules.textual_inversion import textual_inversion
-import modules.hypernetworks.ui
-from modules.generation_parameters_copypaste import image_from_url_text
-
-# this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI
-mimetypes.init()
-mimetypes.add_type('application/javascript', '.js')
-
-if not cmd_opts.share and not cmd_opts.listen:
-    # fix gradio phoning home
-    gradio.utils.version_check = lambda: None
-    gradio.utils.get_local_ip_address = lambda: '127.0.0.1'
-
-if cmd_opts.ngrok is not None:
-    import modules.ngrok as ngrok
-    print('ngrok authtoken detected, trying to connect...')
-    ngrok.connect(
-        cmd_opts.ngrok,
-        cmd_opts.port if cmd_opts.port is not None else 7860,
-        cmd_opts.ngrok_region
-        )
-
-
-def gr_show(visible=True):
-    return {"visible": visible, "__type__": "update"}
-
-
-sample_img2img = "assets/stable-samples/img2img/sketch-mountains-input.jpg"
-sample_img2img = sample_img2img if os.path.exists(sample_img2img) else None
-
-css_hide_progressbar = """
-.wrap .m-12 svg { display:none!important; }
-.wrap .m-12::before { content:"Loading..." }
-.wrap .z-20 svg { display:none!important; }
-.wrap .z-20::before { content:"Loading..." }
-.progress-bar { display:none!important; }
-.meta-text { display:none!important; }
-.meta-text-center { display:none!important; }
-"""
-
-# Using constants for these since the variation selector isn't visible.
-# Important that they exactly match script.js for tooltip to work.
-random_symbol = '\U0001f3b2\ufe0f'  # 🎲️
-reuse_symbol = '\u267b\ufe0f'  # ♻️
-paste_symbol = '\u2199\ufe0f'  # ↙
-folder_symbol = '\U0001f4c2'  # 📂
-refresh_symbol = '\U0001f504'  # 🔄
-save_style_symbol = '\U0001f4be'  # 💾
-apply_style_symbol = '\U0001f4cb'  # 📋
-clear_prompt_symbol = '\U0001F5D1'  # 🗑️
-
-
-def plaintext_to_html(text):
-    text = "<p>" + "<br>\n".join([f"{html.escape(x)}" for x in text.split('\n')]) + "</p>"
-    return text
-
-def send_gradio_gallery_to_image(x):
-    if len(x) == 0:
-        return None
-    return image_from_url_text(x[0])
-
-def save_files(js_data, images, do_make_zip, index):
-    import csv
-    filenames = []
-    fullfns = []
-
-    #quick dictionary to class object conversion. Its necessary due apply_filename_pattern requiring it
-    class MyObject:
-        def __init__(self, d=None):
-            if d is not None:
-                for key, value in d.items():
-                    setattr(self, key, value)
-
-    data = json.loads(js_data)
-
-    p = MyObject(data)
-    path = opts.outdir_save
-    save_to_dirs = opts.use_save_to_dirs_for_ui
-    extension: str = opts.samples_format
-    start_index = 0
-
-    if index > -1 and opts.save_selected_only and (index >= data["index_of_first_image"]):  # ensures we are looking at a specific non-grid picture, and we have save_selected_only
-
-        images = [images[index]]
-        start_index = index
-
-    os.makedirs(opts.outdir_save, exist_ok=True)
-
-    with open(os.path.join(opts.outdir_save, "log.csv"), "a", encoding="utf8", newline='') as file:
-        at_start = file.tell() == 0
-        writer = csv.writer(file)
-        if at_start:
-            writer.writerow(["prompt", "seed", "width", "height", "sampler", "cfgs", "steps", "filename", "negative_prompt"])
-
-        for image_index, filedata in enumerate(images, start_index):
-            image = image_from_url_text(filedata)
-
-            is_grid = image_index < p.index_of_first_image
-            i = 0 if is_grid else (image_index - p.index_of_first_image)
-
-            fullfn, txt_fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
-
-            filename = os.path.relpath(fullfn, path)
-            filenames.append(filename)
-            fullfns.append(fullfn)
-            if txt_fullfn:
-                filenames.append(os.path.basename(txt_fullfn))
-                fullfns.append(txt_fullfn)
-
-        writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler_name"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]])
-
-    # Make Zip
-    if do_make_zip:
-        zip_filepath = os.path.join(path, "images.zip")
-
-        from zipfile import ZipFile
-        with ZipFile(zip_filepath, "w") as zip_file:
-            for i in range(len(fullfns)):
-                with open(fullfns[i], mode="rb") as f:
-                    zip_file.writestr(filenames[i], f.read())
-        fullfns.insert(0, zip_filepath)
-
-    return gr.File.update(value=fullfns, visible=True), plaintext_to_html(f"Saved: {filenames[0]}")
-
-
-def calc_time_left(progress, threshold, label, force_display, show_eta):
-    if progress == 0:
-        return ""
-    else:
-        time_since_start = time.time() - shared.state.time_start
-        eta = (time_since_start/progress)
-        eta_relative = eta-time_since_start
-        if (eta_relative > threshold and show_eta) or force_display:
-            if eta_relative > 3600:
-                return label + time.strftime('%H:%M:%S', time.gmtime(eta_relative))
-            elif eta_relative > 60:
-                return label + time.strftime('%M:%S',  time.gmtime(eta_relative))
-            else:
-                return label + time.strftime('%Ss',  time.gmtime(eta_relative))
-        else:
-            return ""
-
-
-def check_progress_call(id_part):
-    if shared.state.job_count == 0:
-        return "", gr_show(False), gr_show(False), gr_show(False)
-
-    progress = 0
-
-    if shared.state.job_count > 0:
-        progress += shared.state.job_no / shared.state.job_count
-    if shared.state.sampling_steps > 0:
-        progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps
-
-    # Show progress percentage and time left at the same moment, and base it also on steps done
-    show_eta = progress >= 0.01 or shared.state.sampling_step >= 10
-
-    time_left = calc_time_left(progress, 1, " ETA: ", shared.state.time_left_force_display, show_eta)
-    if time_left != "":
-        shared.state.time_left_force_display = True
-
-    progress = min(progress, 1)
-
-    progressbar = ""
-    if opts.show_progressbar:
-        progressbar = f"""<div class='progressDiv'><div class='progress' style="overflow:visible;width:{progress * 100}%;white-space:nowrap;">{"&nbsp;" * 2 + str(int(progress*100))+"%" + time_left if show_eta else ""}</div></div>"""
-
-    image = gr_show(False)
-    preview_visibility = gr_show(False)
-
-    if opts.show_progress_every_n_steps != 0:
-        shared.state.set_current_image()
-        image = shared.state.current_image
-
-        if image is None:
-            image = gr.update(value=None)
-        else:
-            preview_visibility = gr_show(True)
-
-    if shared.state.textinfo is not None:
-        textinfo_result = gr.HTML.update(value=shared.state.textinfo, visible=True)
-    else:
-        textinfo_result = gr_show(False)
-
-    return f"<span id='{id_part}_progress_span' style='display: none'>{time.time()}</span><p>{progressbar}</p>", preview_visibility, image, textinfo_result
-
-
-def check_progress_call_initial(id_part):
-    shared.state.job_count = -1
-    shared.state.current_latent = None
-    shared.state.current_image = None
-    shared.state.textinfo = None
-    shared.state.time_start = time.time()
-    shared.state.time_left_force_display = False
-
-    return check_progress_call(id_part)
-
-
-def visit(x, func, path=""):
-    if hasattr(x, 'children'):
-        for c in x.children:
-            visit(c, func, path)
-    elif x.label is not None:
-        func(path + "/" + str(x.label), x)
-
-
-def add_style(name: str, prompt: str, negative_prompt: str):
-    if name is None:
-        return [gr_show() for x in range(4)]
-
-    style = modules.styles.PromptStyle(name, prompt, negative_prompt)
-    shared.prompt_styles.styles[style.name] = style
-    # Save all loaded prompt styles: this allows us to update the storage format in the future more easily, because we
-    # reserialize all styles every time we save them
-    shared.prompt_styles.save_styles(shared.styles_filename)
-
-    return [gr.Dropdown.update(visible=True, choices=list(shared.prompt_styles.styles)) for _ in range(4)]
-
-
-def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resize_y):
-    from modules import processing, devices
-
-    if not enable:
-        return ""
-
-    p = processing.StableDiffusionProcessingTxt2Img(width=width, height=height, enable_hr=True, hr_scale=hr_scale, hr_resize_x=hr_resize_x, hr_resize_y=hr_resize_y)
-
-    with devices.autocast():
-        p.init([""], [0], [0])
-
-    return f"resize: from <span class='resolution'>{p.width}x{p.height}</span> to <span class='resolution'>{p.hr_resize_x or p.hr_upscale_to_x}x{p.hr_resize_y or p.hr_upscale_to_y}</span>"
-
-
-def apply_styles(prompt, prompt_neg, style1_name, style2_name):
-    prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, [style1_name, style2_name])
-    prompt_neg = shared.prompt_styles.apply_negative_styles_to_prompt(prompt_neg, [style1_name, style2_name])
-
-    return [gr.Textbox.update(value=prompt), gr.Textbox.update(value=prompt_neg), gr.Dropdown.update(value="None"), gr.Dropdown.update(value="None")]
-
-
-def interrogate(image):
-    prompt = shared.interrogator.interrogate(image.convert("RGB"))
-
-    return gr_show(True) if prompt is None else prompt
-
-
-def interrogate_deepbooru(image):
-    prompt = deepbooru.model.tag(image)
-    return gr_show(True) if prompt is None else prompt
-
-
-def create_seed_inputs(target_interface):
-    with FormRow(elem_id=target_interface + '_seed_row'):
-        seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1, elem_id=target_interface + '_seed')
-        seed.style(container=False)
-        random_seed = gr.Button(random_symbol, elem_id=target_interface + '_random_seed')
-        reuse_seed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_seed')
-
-        with gr.Group(elem_id=target_interface + '_subseed_show_box'):
-            seed_checkbox = gr.Checkbox(label='Extra', elem_id=target_interface + '_subseed_show', value=False)
-
-    # Components to show/hide based on the 'Extra' checkbox
-    seed_extras = []
-
-    with FormRow(visible=False, elem_id=target_interface + '_subseed_row') as seed_extra_row_1:
-        seed_extras.append(seed_extra_row_1)
-        subseed = gr.Number(label='Variation seed', value=-1, elem_id=target_interface + '_subseed')
-        subseed.style(container=False)
-        random_subseed = gr.Button(random_symbol, elem_id=target_interface + '_random_subseed')
-        reuse_subseed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_subseed')
-        subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=target_interface + '_subseed_strength')
-
-    with FormRow(visible=False) as seed_extra_row_2:
-        seed_extras.append(seed_extra_row_2)
-        seed_resize_from_w = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from width", value=0, elem_id=target_interface + '_seed_resize_from_w')
-        seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from height", value=0, elem_id=target_interface + '_seed_resize_from_h')
-
-    random_seed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[seed])
-    random_subseed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[subseed])
-
-    def change_visibility(show):
-        return {comp: gr_show(show) for comp in seed_extras}
-
-    seed_checkbox.change(change_visibility, show_progress=False, inputs=[seed_checkbox], outputs=seed_extras)
-
-    return seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox
-
-
-
-def connect_clear_prompt(button):
-    """Given clear button, prompt, and token_counter objects, setup clear prompt button click event"""
-    button.click(
-        _js="clear_prompt",
-        fn=None,
-        inputs=[],
-        outputs=[],
-    )
-
-
-def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: gr.Textbox, dummy_component, is_subseed):
-    """ Connects a 'reuse (sub)seed' button's click event so that it copies last used
-        (sub)seed value from generation info the to the seed field. If copying subseed and subseed strength
-        was 0, i.e. no variation seed was used, it copies the normal seed value instead."""
-    def copy_seed(gen_info_string: str, index):
-        res = -1
-
-        try:
-            gen_info = json.loads(gen_info_string)
-            index -= gen_info.get('index_of_first_image', 0)
-
-            if is_subseed and gen_info.get('subseed_strength', 0) > 0:
-                all_subseeds = gen_info.get('all_subseeds', [-1])
-                res = all_subseeds[index if 0 <= index < len(all_subseeds) else 0]
-            else:
-                all_seeds = gen_info.get('all_seeds', [-1])
-                res = all_seeds[index if 0 <= index < len(all_seeds) else 0]
-
-        except json.decoder.JSONDecodeError as e:
-            if gen_info_string != '':
-                print("Error parsing JSON generation info:", file=sys.stderr)
-                print(gen_info_string, file=sys.stderr)
-
-        return [res, gr_show(False)]
-
-    reuse_seed.click(
-        fn=copy_seed,
-        _js="(x, y) => [x, selected_gallery_index()]",
-        show_progress=False,
-        inputs=[generation_info, dummy_component],
-        outputs=[seed, dummy_component]
-    )
-
-
-def update_token_counter(text, steps):
-    try:
-        _, prompt_flat_list, _ = prompt_parser.get_multicond_prompt_list([text])
-        prompt_schedules = prompt_parser.get_learned_conditioning_prompt_schedules(prompt_flat_list, steps)
-
-    except Exception:
-        # a parsing error can happen here during typing, and we don't want to bother the user with
-        # messages related to it in console
-        prompt_schedules = [[[steps, text]]]
-
-    flat_prompts = reduce(lambda list1, list2: list1+list2, prompt_schedules)
-    prompts = [prompt_text for step, prompt_text in flat_prompts]
-    token_count, max_length = max([model_hijack.get_prompt_lengths(prompt) for prompt in prompts], key=lambda args: args[0])
-    style_class = ' class="red"' if (token_count > max_length) else ""
-    return f"<span {style_class}>{token_count}/{max_length}</span>"
-
-
-def create_toprow(is_img2img):
-    id_part = "img2img" if is_img2img else "txt2img"
-
-    with gr.Row(elem_id="toprow"):
-        with gr.Column(scale=6):
-            with gr.Row():
-                with gr.Column(scale=80):
-                    with gr.Row():
-                        prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=2,
-                            placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)"
-                        )
-
-            with gr.Row():
-                with gr.Column(scale=80):
-                    with gr.Row():
-                        negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2,
-                            placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)"
-                        )
-
-        with gr.Column(scale=1, elem_id="roll_col"):
-            paste = gr.Button(value=paste_symbol, elem_id="paste")
-            save_style = gr.Button(value=save_style_symbol, elem_id="style_create")
-            prompt_style_apply = gr.Button(value=apply_style_symbol, elem_id="style_apply")
-            clear_prompt_button = gr.Button(value=clear_prompt_symbol, elem_id=f"{id_part}_clear_prompt")
-            token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_token_counter")
-            token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button")
-
-            clear_prompt_button.click(
-                fn=lambda *x: x,
-                _js="confirm_clear_prompt",
-                inputs=[prompt, negative_prompt],
-                outputs=[prompt, negative_prompt],
-            )
-
-        button_interrogate = None
-        button_deepbooru = None
-        if is_img2img:
-            with gr.Column(scale=1, elem_id="interrogate_col"):
-                button_interrogate = gr.Button('Interrogate\nCLIP', elem_id="interrogate")
-                button_deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru")
-
-        with gr.Column(scale=1):
-            with gr.Row():
-                skip = gr.Button('Skip', elem_id=f"{id_part}_skip")
-                interrupt = gr.Button('Interrupt', elem_id=f"{id_part}_interrupt")
-                submit = gr.Button('Generate', elem_id=f"{id_part}_generate", variant='primary')
-
-                skip.click(
-                    fn=lambda: shared.state.skip(),
-                    inputs=[],
-                    outputs=[],
-                )
-
-                interrupt.click(
-                    fn=lambda: shared.state.interrupt(),
-                    inputs=[],
-                    outputs=[],
-                )
-
-            with gr.Row():
-                with gr.Column(scale=1, elem_id="style_pos_col"):
-                    prompt_style = gr.Dropdown(label="Style 1", elem_id=f"{id_part}_style_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())))
-
-                with gr.Column(scale=1, elem_id="style_neg_col"):
-                    prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())))
-
-    return prompt, prompt_style, negative_prompt, prompt_style2, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button
-
-
-def setup_progressbar(progressbar, preview, id_part, textinfo=None):
-    if textinfo is None:
-        textinfo = gr.HTML(visible=False)
-
-    check_progress = gr.Button('Check progress', elem_id=f"{id_part}_check_progress", visible=False)
-    check_progress.click(
-        fn=lambda: check_progress_call(id_part),
-        show_progress=False,
-        inputs=[],
-        outputs=[progressbar, preview, preview, textinfo],
-    )
-
-    check_progress_initial = gr.Button('Check progress (first)', elem_id=f"{id_part}_check_progress_initial", visible=False)
-    check_progress_initial.click(
-        fn=lambda: check_progress_call_initial(id_part),
-        show_progress=False,
-        inputs=[],
-        outputs=[progressbar, preview, preview, textinfo],
-    )
-
-
-def apply_setting(key, value):
-    if value is None:
-        return gr.update()
-
-    if shared.cmd_opts.freeze_settings:
-        return gr.update()
-
-    # dont allow model to be swapped when model hash exists in prompt
-    if key == "sd_model_checkpoint" and opts.disable_weights_auto_swap:
-        return gr.update()
-
-    if key == "sd_model_checkpoint":
-        ckpt_info = sd_models.get_closet_checkpoint_match(value)
-
-        if ckpt_info is not None:
-            value = ckpt_info.title
-        else:
-            return gr.update()
-
-    comp_args = opts.data_labels[key].component_args
-    if comp_args and isinstance(comp_args, dict) and comp_args.get('visible') is False:
-        return
-
-    valtype = type(opts.data_labels[key].default)
-    oldval = opts.data.get(key, None)
-    opts.data[key] = valtype(value) if valtype != type(None) else value
-    if oldval != value and opts.data_labels[key].onchange is not None:
-        opts.data_labels[key].onchange()
-
-    opts.save(shared.config_filename)
-    return value
-
-
-def update_generation_info(args):
-    generation_info, html_info, img_index = args
-    try:
-        generation_info = json.loads(generation_info)
-        if img_index < 0 or img_index >= len(generation_info["infotexts"]):
-            return html_info
-        return plaintext_to_html(generation_info["infotexts"][img_index])
-    except Exception:
-        pass
-    # if the json parse or anything else fails, just return the old html_info
-    return html_info
-
-
-def create_refresh_button(refresh_component, refresh_method, refreshed_args, elem_id):
-    def refresh():
-        refresh_method()
-        args = refreshed_args() if callable(refreshed_args) else refreshed_args
-
-        for k, v in args.items():
-            setattr(refresh_component, k, v)
-
-        return gr.update(**(args or {}))
-
-    refresh_button = ToolButton(value=refresh_symbol, elem_id=elem_id)
-    refresh_button.click(
-        fn=refresh,
-        inputs=[],
-        outputs=[refresh_component]
-    )
-    return refresh_button
-
-
-def create_output_panel(tabname, outdir):
-    def open_folder(f):
-        if not os.path.exists(f):
-            print(f'Folder "{f}" does not exist. After you create an image, the folder will be created.')
-            return
-        elif not os.path.isdir(f):
-            print(f"""
-WARNING
-An open_folder request was made with an argument that is not a folder.
-This could be an error or a malicious attempt to run code on your computer.
-Requested path was: {f}
-""", file=sys.stderr)
-            return
-
-        if not shared.cmd_opts.hide_ui_dir_config:
-            path = os.path.normpath(f)
-            if platform.system() == "Windows":
-                os.startfile(path)
-            elif platform.system() == "Darwin":
-                sp.Popen(["open", path])
-            elif "microsoft-standard-WSL2" in platform.uname().release:
-                sp.Popen(["wsl-open", path])
-            else:
-                sp.Popen(["xdg-open", path])
-
-    with gr.Column(variant='panel'):
-            with gr.Group():
-                result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery").style(grid=4)
-
-            generation_info = None
-            with gr.Column():
-                with gr.Row(elem_id=f"image_buttons_{tabname}"):
-                    open_folder_button = gr.Button(folder_symbol, elem_id="hidden_element" if shared.cmd_opts.hide_ui_dir_config else f'open_folder_{tabname}')
-
-                    if tabname != "extras":
-                        save = gr.Button('Save', elem_id=f'save_{tabname}')
-                        save_zip = gr.Button('Zip', elem_id=f'save_zip_{tabname}')
-
-                    buttons = parameters_copypaste.create_buttons(["img2img", "inpaint", "extras"])
-
-                open_folder_button.click(
-                    fn=lambda: open_folder(opts.outdir_samples or outdir),
-                    inputs=[],
-                    outputs=[],
-                )
-
-                if tabname != "extras":
-                    with gr.Row():
-                        download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False, elem_id=f'download_files_{tabname}')
-
-                    with gr.Group():
-                        html_info = gr.HTML(elem_id=f'html_info_{tabname}')
-                        html_log = gr.HTML(elem_id=f'html_log_{tabname}')
-
-                        generation_info = gr.Textbox(visible=False, elem_id=f'generation_info_{tabname}')
-                        if tabname == 'txt2img' or tabname == 'img2img':
-                            generation_info_button = gr.Button(visible=False, elem_id=f"{tabname}_generation_info_button")
-                            generation_info_button.click(
-                                fn=update_generation_info,
-                                _js="(x, y) => [x, y, selected_gallery_index()]",
-                                inputs=[generation_info, html_info],
-                                outputs=[html_info],
-                                preprocess=False
-                            )
-
-                        save.click(
-                            fn=wrap_gradio_call(save_files),
-                            _js="(x, y, z, w) => [x, y, false, selected_gallery_index()]",
-                            inputs=[
-                                generation_info,
-                                result_gallery,
-                                html_info,
-                                html_info,
-                            ],
-                            outputs=[
-                                download_files,
-                                html_log,
-                            ]
-                        )
-
-                        save_zip.click(
-                            fn=wrap_gradio_call(save_files),
-                            _js="(x, y, z, w) => [x, y, true, selected_gallery_index()]",
-                            inputs=[
-                                generation_info,
-                                result_gallery,
-                                html_info,
-                                html_info,
-                            ],
-                            outputs=[
-                                download_files,
-                                html_log,
-                            ]
-                        )
-
-                else:
-                    html_info_x = gr.HTML(elem_id=f'html_info_x_{tabname}')
-                    html_info = gr.HTML(elem_id=f'html_info_{tabname}')
-                    html_log = gr.HTML(elem_id=f'html_log_{tabname}')
-
-                parameters_copypaste.bind_buttons(buttons, result_gallery, "txt2img" if tabname == "txt2img" else None)
-                return result_gallery, generation_info if tabname != "extras" else html_info_x, html_info, html_log
-
-
-def create_sampler_and_steps_selection(choices, tabname):
-    if opts.samplers_in_dropdown:
-        with FormRow(elem_id=f"sampler_selection_{tabname}"):
-            sampler_index = gr.Dropdown(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")
-            steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling steps", value=20)
-    else:
-        with FormGroup(elem_id=f"sampler_selection_{tabname}"):
-            steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling steps", value=20)
-            sampler_index = gr.Radio(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")
-
-    return steps, sampler_index
-
-
-def ordered_ui_categories():
-    user_order = {x.strip(): i for i, x in enumerate(shared.opts.ui_reorder.split(","))}
-
-    for i, category in sorted(enumerate(shared.ui_reorder_categories), key=lambda x: user_order.get(x[1], x[0] + 1000)):
-        yield category
-
-
-def create_ui():
-    import modules.img2img
-    import modules.txt2img
-
-    reload_javascript()
-
-    parameters_copypaste.reset()
-
-    modules.scripts.scripts_current = modules.scripts.scripts_txt2img
-    modules.scripts.scripts_txt2img.initialize_scripts(is_img2img=False)
-
-    with gr.Blocks(analytics_enabled=False) as txt2img_interface:
-        txt2img_prompt, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _,txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False)
-
-        dummy_component = gr.Label(visible=False)
-        txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False)
-
-        with gr.Row(elem_id='txt2img_progress_row'):
-            with gr.Column(scale=1):
-                pass
-
-            with gr.Column(scale=1):
-                progressbar = gr.HTML(elem_id="txt2img_progressbar")
-                txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False)
-                setup_progressbar(progressbar, txt2img_preview, 'txt2img')
-
-        with gr.Row().style(equal_height=False):
-            with gr.Column(variant='panel', elem_id="txt2img_settings"):
-                for category in ordered_ui_categories():
-                    if category == "sampler":
-                        steps, sampler_index = create_sampler_and_steps_selection(samplers, "txt2img")
-
-                    elif category == "dimensions":
-                        with FormRow():
-                            with gr.Column(elem_id="txt2img_column_size", scale=4):
-                                width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="txt2img_width")
-                                height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="txt2img_height")
-
-                            if opts.dimensions_and_batch_together:
-                                with gr.Column(elem_id="txt2img_column_batch"):
-                                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
-                                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
-
-                    elif category == "cfg":
-                        cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="txt2img_cfg_scale")
-
-                    elif category == "seed":
-                        seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('txt2img')
-
-                    elif category == "checkboxes":
-                        with FormRow(elem_id="txt2img_checkboxes"):
-                            restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="txt2img_restore_faces")
-                            tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling")
-                            enable_hr = gr.Checkbox(label='Hires. fix', value=False, elem_id="txt2img_enable_hr")
-                            hr_final_resolution = FormHTML(value="", elem_id="txtimg_hr_finalres", label="Upscaled resolution", interactive=False)
-
-                    elif category == "hires_fix":
-                        with FormGroup(visible=False, elem_id="txt2img_hires_fix") as hr_options:
-                            with FormRow(elem_id="txt2img_hires_fix_row1"):
-                                hr_upscaler = gr.Dropdown(label="Upscaler", elem_id="txt2img_hr_upscaler", choices=[*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]], value=shared.latent_upscale_default_mode)
-                                hr_second_pass_steps = gr.Slider(minimum=0, maximum=150, step=1, label='Hires steps', value=0, elem_id="txt2img_hires_steps")
-                                denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7, elem_id="txt2img_denoising_strength")
-
-                            with FormRow(elem_id="txt2img_hires_fix_row2"):
-                                hr_scale = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Upscale by", value=2.0, elem_id="txt2img_hr_scale")
-                                hr_resize_x = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize width to", value=0, elem_id="txt2img_hr_resize_x")
-                                hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y")
-
-                    elif category == "batch":
-                        if not opts.dimensions_and_batch_together:
-                            with FormRow(elem_id="txt2img_column_batch"):
-                                batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
-                                batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
-
-                    elif category == "scripts":
-                        with FormGroup(elem_id="txt2img_script_container"):
-                            custom_inputs = modules.scripts.scripts_txt2img.setup_ui()
-
-            hr_resolution_preview_inputs = [enable_hr, width, height, hr_scale, hr_resize_x, hr_resize_y]
-            for input in hr_resolution_preview_inputs:
-                input.change(
-                    fn=calc_resolution_hires,
-                    inputs=hr_resolution_preview_inputs,
-                    outputs=[hr_final_resolution],
-                    show_progress=False,
-                )
-                input.change(
-                    None,
-                    _js="onCalcResolutionHires",
-                    inputs=hr_resolution_preview_inputs,
-                    outputs=[],
-                    show_progress=False,
-                )
-
-            txt2img_gallery, generation_info, html_info, html_log = create_output_panel("txt2img", opts.outdir_txt2img_samples)
-            parameters_copypaste.bind_buttons({"txt2img": txt2img_paste}, None, txt2img_prompt)
-
-            connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
-            connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
-
-            txt2img_args = dict(
-                fn=wrap_gradio_gpu_call(modules.txt2img.txt2img, extra_outputs=[None, '', '']),
-                _js="submit",
-                inputs=[
-                    txt2img_prompt,
-                    txt2img_negative_prompt,
-                    txt2img_prompt_style,
-                    txt2img_prompt_style2,
-                    steps,
-                    sampler_index,
-                    restore_faces,
-                    tiling,
-                    batch_count,
-                    batch_size,
-                    cfg_scale,
-                    seed,
-                    subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox,
-                    height,
-                    width,
-                    enable_hr,
-                    denoising_strength,
-                    hr_scale,
-                    hr_upscaler,
-                    hr_second_pass_steps,
-                    hr_resize_x,
-                    hr_resize_y,
-                ] + custom_inputs,
-
-                outputs=[
-                    txt2img_gallery,
-                    generation_info,
-                    html_info,
-                    html_log,
-                ],
-                show_progress=False,
-            )
-
-            txt2img_prompt.submit(**txt2img_args)
-            submit.click(**txt2img_args)
-
-            txt_prompt_img.change(
-                fn=modules.images.image_data,
-                inputs=[
-                    txt_prompt_img
-                ],
-                outputs=[
-                    txt2img_prompt,
-                    txt_prompt_img
-                ]
-            )
-
-            enable_hr.change(
-                fn=lambda x: gr_show(x),
-                inputs=[enable_hr],
-                outputs=[hr_options],
-                show_progress = False,
-            )
-
-            txt2img_paste_fields = [
-                (txt2img_prompt, "Prompt"),
-                (txt2img_negative_prompt, "Negative prompt"),
-                (steps, "Steps"),
-                (sampler_index, "Sampler"),
-                (restore_faces, "Face restoration"),
-                (cfg_scale, "CFG scale"),
-                (seed, "Seed"),
-                (width, "Size-1"),
-                (height, "Size-2"),
-                (batch_size, "Batch size"),
-                (subseed, "Variation seed"),
-                (subseed_strength, "Variation seed strength"),
-                (seed_resize_from_w, "Seed resize from-1"),
-                (seed_resize_from_h, "Seed resize from-2"),
-                (denoising_strength, "Denoising strength"),
-                (enable_hr, lambda d: "Denoising strength" in d),
-                (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)),
-                (hr_scale, "Hires upscale"),
-                (hr_upscaler, "Hires upscaler"),
-                (hr_second_pass_steps, "Hires steps"),
-                (hr_resize_x, "Hires resize-1"),
-                (hr_resize_y, "Hires resize-2"),
-                *modules.scripts.scripts_txt2img.infotext_fields
-            ]
-            parameters_copypaste.add_paste_fields("txt2img", None, txt2img_paste_fields)
-
-            txt2img_preview_params = [
-                txt2img_prompt,
-                txt2img_negative_prompt,
-                steps,
-                sampler_index,
-                cfg_scale,
-                seed,
-                width,
-                height,
-            ]
-
-            token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[txt2img_prompt, steps], outputs=[token_counter])
-
-    modules.scripts.scripts_current = modules.scripts.scripts_img2img
-    modules.scripts.scripts_img2img.initialize_scripts(is_img2img=True)
-
-    with gr.Blocks(analytics_enabled=False) as img2img_interface:
-        img2img_prompt, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,token_counter, token_button = create_toprow(is_img2img=True)
-
-        with gr.Row(elem_id='img2img_progress_row'):
-            img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False)
-
-            with gr.Column(scale=1):
-                pass
-
-            with gr.Column(scale=1):
-                progressbar = gr.HTML(elem_id="img2img_progressbar")
-                img2img_preview = gr.Image(elem_id='img2img_preview', visible=False)
-                setup_progressbar(progressbar, img2img_preview, 'img2img')
-
-        with FormRow().style(equal_height=False):
-            with gr.Column(variant='panel', elem_id="img2img_settings"):
-
-                with gr.Tabs(elem_id="mode_img2img") as tabs_img2img_mode:
-                    with gr.TabItem('img2img', id='img2img', elem_id="img2img_img2img_tab"):
-                        init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_img2img_tool, image_mode="RGBA").style(height=480)
-
-                    with gr.TabItem('Inpaint', id='inpaint', elem_id="img2img_inpaint_tab"):
-                        init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_inpaint_tool, image_mode="RGBA").style(height=480)
-                        init_img_with_mask_orig = gr.State(None)
-
-                        use_color_sketch = cmd_opts.gradio_inpaint_tool == "color-sketch"
-                        if use_color_sketch:
-                            def update_orig(image, state):
-                                if image is not None:
-                                    same_size = state is not None and state.size == image.size
-                                    has_exact_match = np.any(np.all(np.array(image) == np.array(state), axis=-1))
-                                    edited = same_size and has_exact_match
-                                    return image if not edited or state is None else state
-
-                            init_img_with_mask.change(update_orig, [init_img_with_mask, init_img_with_mask_orig], init_img_with_mask_orig)
-
-                        init_img_inpaint = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_base")
-                        init_mask_inpaint = gr.Image(label="Mask", source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_mask")
-
-                        with FormRow():
-                            mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id="img2img_mask_blur")
-                            mask_alpha = gr.Slider(label="Mask transparency", interactive=use_color_sketch, visible=use_color_sketch, elem_id="img2img_mask_alpha")
-
-                        with FormRow():
-                            mask_mode = gr.Radio(label="Mask source", choices=["Draw mask", "Upload mask"], type="index", value="Draw mask", elem_id="mask_mode")
-                            inpainting_mask_invert = gr.Radio(label='Mask mode', choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index", elem_id="img2img_mask_mode")
-
-                        with FormRow():
-                            inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='original', type="index", elem_id="img2img_inpainting_fill")
-
-                        with FormRow():
-                            with gr.Column():
-                                inpaint_full_res = gr.Radio(label="Inpaint area", choices=["Whole picture", "Only masked"], type="index", value="Whole picture", elem_id="img2img_inpaint_full_res")
-
-                            with gr.Column(scale=4):
-                                inpaint_full_res_padding = gr.Slider(label='Only masked padding, pixels', minimum=0, maximum=256, step=4, value=32, elem_id="img2img_inpaint_full_res_padding")
-
-                    with gr.TabItem('Batch img2img', id='batch', elem_id="img2img_batch_tab"):
-                        hidden = '<br>Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else ''
-                        gr.HTML(f"<p class=\"text-gray-500\">Process images in a directory on the same machine where the server is running.<br>Use an empty output directory to save pictures normally instead of writing to the output directory.{hidden}</p>")
-                        img2img_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, elem_id="img2img_batch_input_dir")
-                        img2img_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, elem_id="img2img_batch_output_dir")
-
-                with FormRow():
-                    resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", choices=["Just resize", "Crop and resize", "Resize and fill", "Just resize (latent upscale)"], type="index", value="Just resize")
-
-                for category in ordered_ui_categories():
-                    if category == "sampler":
-                        steps, sampler_index = create_sampler_and_steps_selection(samplers_for_img2img, "img2img")
-
-                    elif category == "dimensions":
-                        with FormRow():
-                            with gr.Column(elem_id="img2img_column_size", scale=4):
-                                width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
-                                height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
-
-                            if opts.dimensions_and_batch_together:
-                                with gr.Column(elem_id="img2img_column_batch"):
-                                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
-                                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")
-
-                    elif category == "cfg":
-                        with FormGroup():
-                            cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="img2img_cfg_scale")
-                            denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75, elem_id="img2img_denoising_strength")
-
-                    elif category == "seed":
-                        seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('img2img')
-
-                    elif category == "checkboxes":
-                        with FormRow(elem_id="img2img_checkboxes"):
-                            restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="img2img_restore_faces")
-                            tiling = gr.Checkbox(label='Tiling', value=False, elem_id="img2img_tiling")
-
-                    elif category == "batch":
-                        if not opts.dimensions_and_batch_together:
-                            with FormRow(elem_id="img2img_column_batch"):
-                                batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
-                                batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")
-
-                    elif category == "scripts":
-                        with FormGroup(elem_id="img2img_script_container"):
-                            custom_inputs = modules.scripts.scripts_img2img.setup_ui()
-
-            img2img_gallery, generation_info, html_info, html_log = create_output_panel("img2img", opts.outdir_img2img_samples)
-            parameters_copypaste.bind_buttons({"img2img": img2img_paste}, None, img2img_prompt)
-
-            connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
-            connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
-
-            img2img_prompt_img.change(
-                fn=modules.images.image_data,
-                inputs=[
-                    img2img_prompt_img
-                ],
-                outputs=[
-                    img2img_prompt,
-                    img2img_prompt_img
-                ]
-            )
-
-            mask_mode.change(
-                lambda mode, img: {
-                    init_img_with_mask: gr_show(mode == 0),
-                    init_img_inpaint: gr_show(mode == 1),
-                    init_mask_inpaint: gr_show(mode == 1),
-                },
-                inputs=[mask_mode, init_img_with_mask],
-                outputs=[
-                    init_img_with_mask,
-                    init_img_inpaint,
-                    init_mask_inpaint,
-                ],
-            )
-
-            img2img_args = dict(
-                fn=wrap_gradio_gpu_call(modules.img2img.img2img, extra_outputs=[None, '', '']),
-                _js="submit_img2img",
-                inputs=[
-                    dummy_component,
-                    img2img_prompt,
-                    img2img_negative_prompt,
-                    img2img_prompt_style,
-                    img2img_prompt_style2,
-                    init_img,
-                    init_img_with_mask,
-                    init_img_with_mask_orig,
-                    init_img_inpaint,
-                    init_mask_inpaint,
-                    mask_mode,
-                    steps,
-                    sampler_index,
-                    mask_blur,
-                    mask_alpha,
-                    inpainting_fill,
-                    restore_faces,
-                    tiling,
-                    batch_count,
-                    batch_size,
-                    cfg_scale,
-                    denoising_strength,
-                    seed,
-                    subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox,
-                    height,
-                    width,
-                    resize_mode,
-                    inpaint_full_res,
-                    inpaint_full_res_padding,
-                    inpainting_mask_invert,
-                    img2img_batch_input_dir,
-                    img2img_batch_output_dir,
-                ] + custom_inputs,
-                outputs=[
-                    img2img_gallery,
-                    generation_info,
-                    html_info,
-                    html_log,
-                ],
-                show_progress=False,
-            )
-
-            img2img_prompt.submit(**img2img_args)
-            submit.click(**img2img_args)
-
-            img2img_interrogate.click(
-                fn=interrogate,
-                inputs=[init_img],
-                outputs=[img2img_prompt],
-            )
-
-            img2img_deepbooru.click(
-                fn=interrogate_deepbooru,
-                inputs=[init_img],
-                outputs=[img2img_prompt],
-            )
-
-            prompts = [(txt2img_prompt, txt2img_negative_prompt), (img2img_prompt, img2img_negative_prompt)]
-            style_dropdowns = [(txt2img_prompt_style, txt2img_prompt_style2), (img2img_prompt_style, img2img_prompt_style2)]
-            style_js_funcs = ["update_txt2img_tokens", "update_img2img_tokens"]
-
-            for button, (prompt, negative_prompt) in zip([txt2img_save_style, img2img_save_style], prompts):
-                button.click(
-                    fn=add_style,
-                    _js="ask_for_style_name",
-                    # Have to pass empty dummy component here, because the JavaScript and Python function have to accept
-                    # the same number of parameters, but we only know the style-name after the JavaScript prompt
-                    inputs=[dummy_component, prompt, negative_prompt],
-                    outputs=[txt2img_prompt_style, img2img_prompt_style, txt2img_prompt_style2, img2img_prompt_style2],
-                )
-
-            for button, (prompt, negative_prompt), (style1, style2), js_func in zip([txt2img_prompt_style_apply, img2img_prompt_style_apply], prompts, style_dropdowns, style_js_funcs):
-                button.click(
-                    fn=apply_styles,
-                    _js=js_func,
-                    inputs=[prompt, negative_prompt, style1, style2],
-                    outputs=[prompt, negative_prompt, style1, style2],
-                )
-
-            token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter])
-
-            img2img_paste_fields = [
-                (img2img_prompt, "Prompt"),
-                (img2img_negative_prompt, "Negative prompt"),
-                (steps, "Steps"),
-                (sampler_index, "Sampler"),
-                (restore_faces, "Face restoration"),
-                (cfg_scale, "CFG scale"),
-                (seed, "Seed"),
-                (width, "Size-1"),
-                (height, "Size-2"),
-                (batch_size, "Batch size"),
-                (subseed, "Variation seed"),
-                (subseed_strength, "Variation seed strength"),
-                (seed_resize_from_w, "Seed resize from-1"),
-                (seed_resize_from_h, "Seed resize from-2"),
-                (denoising_strength, "Denoising strength"),
-                (mask_blur, "Mask blur"),
-                *modules.scripts.scripts_img2img.infotext_fields
-            ]
-            parameters_copypaste.add_paste_fields("img2img", init_img, img2img_paste_fields)
-            parameters_copypaste.add_paste_fields("inpaint", init_img_with_mask, img2img_paste_fields)
-
-    modules.scripts.scripts_current = None
-
-    with gr.Blocks(analytics_enabled=False) as extras_interface:
-        with gr.Row().style(equal_height=False):
-            with gr.Column(variant='panel'):
-                with gr.Tabs(elem_id="mode_extras"):
-                    with gr.TabItem('Single Image', elem_id="extras_single_tab"):
-                        extras_image = gr.Image(label="Source", source="upload", interactive=True, type="pil", elem_id="extras_image")
-
-                    with gr.TabItem('Batch Process', elem_id="extras_batch_process_tab"):
-                        image_batch = gr.File(label="Batch Process", file_count="multiple", interactive=True, type="file", elem_id="extras_image_batch")
-
-                    with gr.TabItem('Batch from Directory', elem_id="extras_batch_directory_tab"):
-                        extras_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, placeholder="A directory on the same machine where the server is running.", elem_id="extras_batch_input_dir")
-                        extras_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, placeholder="Leave blank to save images to the default path.", elem_id="extras_batch_output_dir")
-                        show_extras_results = gr.Checkbox(label='Show result images', value=True, elem_id="extras_show_extras_results")
-
-                submit = gr.Button('Generate', elem_id="extras_generate", variant='primary')
-
-                with gr.Tabs(elem_id="extras_resize_mode"):
-                    with gr.TabItem('Scale by', elem_id="extras_scale_by_tab"):
-                        upscaling_resize = gr.Slider(minimum=1.0, maximum=8.0, step=0.05, label="Resize", value=4, elem_id="extras_upscaling_resize")
-                    with gr.TabItem('Scale to', elem_id="extras_scale_to_tab"):
-                        with gr.Group():
-                            with gr.Row():
-                                upscaling_resize_w = gr.Number(label="Width", value=512, precision=0, elem_id="extras_upscaling_resize_w")
-                                upscaling_resize_h = gr.Number(label="Height", value=512, precision=0, elem_id="extras_upscaling_resize_h")
-                            upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop")
-
-                with gr.Group():
-                    extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
-
-                with gr.Group():
-                    extras_upscaler_2 = gr.Radio(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
-                    extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=1, elem_id="extras_upscaler_2_visibility")
-
-                with gr.Group():
-                    gfpgan_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="GFPGAN visibility", value=0, interactive=modules.gfpgan_model.have_gfpgan, elem_id="extras_gfpgan_visibility")
-
-                with gr.Group():
-                    codeformer_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer visibility", value=0, interactive=modules.codeformer_model.have_codeformer, elem_id="extras_codeformer_visibility")
-                    codeformer_weight = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer weight (0 = maximum effect, 1 = minimum effect)", value=0, interactive=modules.codeformer_model.have_codeformer, elem_id="extras_codeformer_weight")
-
-                with gr.Group():
-                    upscale_before_face_fix = gr.Checkbox(label='Upscale Before Restoring Faces', value=False, elem_id="extras_upscale_before_face_fix")
-
-            result_images, html_info_x, html_info, html_log = create_output_panel("extras", opts.outdir_extras_samples)
-
-        submit.click(
-            fn=wrap_gradio_gpu_call(modules.extras.run_extras, extra_outputs=[None, '']),
-            _js="get_extras_tab_index",
-            inputs=[
-                dummy_component,
-                dummy_component,
-                extras_image,
-                image_batch,
-                extras_batch_input_dir,
-                extras_batch_output_dir,
-                show_extras_results,
-                gfpgan_visibility,
-                codeformer_visibility,
-                codeformer_weight,
-                upscaling_resize,
-                upscaling_resize_w,
-                upscaling_resize_h,
-                upscaling_crop,
-                extras_upscaler_1,
-                extras_upscaler_2,
-                extras_upscaler_2_visibility,
-                upscale_before_face_fix,
-            ],
-            outputs=[
-                result_images,
-                html_info_x,
-                html_info,
-            ]
-        )
-        parameters_copypaste.add_paste_fields("extras", extras_image, None)
-
-        extras_image.change(
-            fn=modules.extras.clear_cache,
-            inputs=[], outputs=[]
-        )
-
-    with gr.Blocks(analytics_enabled=False) as pnginfo_interface:
-        with gr.Row().style(equal_height=False):
-            with gr.Column(variant='panel'):
-                image = gr.Image(elem_id="pnginfo_image", label="Source", source="upload", interactive=True, type="pil")
-
-            with gr.Column(variant='panel'):
-                html = gr.HTML()
-                generation_info = gr.Textbox(visible=False, elem_id="pnginfo_generation_info")
-                html2 = gr.HTML()
-                with gr.Row():
-                    buttons = parameters_copypaste.create_buttons(["txt2img", "img2img", "inpaint", "extras"])
-                parameters_copypaste.bind_buttons(buttons, image, generation_info)
-
-        image.change(
-            fn=wrap_gradio_call(modules.extras.run_pnginfo),
-            inputs=[image],
-            outputs=[html, generation_info, html2],
-        )
-
-    with gr.Blocks(analytics_enabled=False) as modelmerger_interface:
-        with gr.Row().style(equal_height=False):
-            with gr.Column(variant='panel'):
-                gr.HTML(value="<p>A merger of the two checkpoints will be generated in your <b>checkpoint</b> directory.</p>")
-
-                with gr.Row():
-                    primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)")
-                    create_refresh_button(primary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_A")
-
-                    secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary model (B)")
-                    create_refresh_button(secondary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_B")
-
-                    tertiary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_tertiary_model_name", label="Tertiary model (C)")
-                    create_refresh_button(tertiary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_C")
-
-                custom_name = gr.Textbox(label="Custom Name (Optional)", elem_id="modelmerger_custom_name")
-                interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3, elem_id="modelmerger_interp_amount")
-                interp_method = gr.Radio(choices=["Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method", elem_id="modelmerger_interp_method")
-
-                with gr.Row():
-                    checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format", elem_id="modelmerger_checkpoint_format")
-                    save_as_half = gr.Checkbox(value=False, label="Save as float16", elem_id="modelmerger_save_as_half")
-
-                modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary')
-
-            with gr.Column(variant='panel'):
-                submit_result = gr.Textbox(elem_id="modelmerger_result", show_label=False)
-
-    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>")
-
-        with gr.Row().style(equal_height=False):
-            with gr.Tabs(elem_id="train_tabs"):
-
-                with gr.Tab(label="Create embedding"):
-                    new_embedding_name = gr.Textbox(label="Name", elem_id="train_new_embedding_name")
-                    initialization_text = gr.Textbox(label="Initialization text", value="*", elem_id="train_initialization_text")
-                    nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1, elem_id="train_nvpt")
-                    overwrite_old_embedding = gr.Checkbox(value=False, label="Overwrite Old Embedding", elem_id="train_overwrite_old_embedding")
-
-                    with gr.Row():
-                        with gr.Column(scale=3):
-                            gr.HTML(value="")
-
-                        with gr.Column():
-                            create_embedding = gr.Button(value="Create embedding", variant='primary', elem_id="train_create_embedding")
-
-                with gr.Tab(label="Create hypernetwork"):
-                    new_hypernetwork_name = gr.Textbox(label="Name", elem_id="train_new_hypernetwork_name")
-                    new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "1024", "320", "640", "1280"], elem_id="train_new_hypernetwork_sizes")
-                    new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'", elem_id="train_new_hypernetwork_layer_structure")
-                    new_hypernetwork_activation_func = gr.Dropdown(value="linear", label="Select activation function of hypernetwork. Recommended : Swish / Linear(none)", choices=modules.hypernetworks.ui.keys, elem_id="train_new_hypernetwork_activation_func")
-                    new_hypernetwork_initialization_option = gr.Dropdown(value = "Normal", label="Select Layer weights initialization. Recommended: Kaiming for relu-like, Xavier for sigmoid-like, Normal otherwise", choices=["Normal", "KaimingUniform", "KaimingNormal", "XavierUniform", "XavierNormal"], elem_id="train_new_hypernetwork_initialization_option")
-                    new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization", elem_id="train_new_hypernetwork_add_layer_norm")
-                    new_hypernetwork_use_dropout = gr.Checkbox(label="Use dropout", elem_id="train_new_hypernetwork_use_dropout")
-                    new_hypernetwork_dropout_structure = gr.Textbox("0, 0, 0", label="Enter hypernetwork Dropout structure (or empty). Recommended : 0~0.35 incrementing sequence: 0, 0.05, 0.15", placeholder="1st and last digit must be 0 and values should be between 0 and 1. ex:'0, 0.01, 0'")
-                    overwrite_old_hypernetwork = gr.Checkbox(value=False, label="Overwrite Old Hypernetwork", elem_id="train_overwrite_old_hypernetwork")
-
-                    with gr.Row():
-                        with gr.Column(scale=3):
-                            gr.HTML(value="")
-
-                        with gr.Column():
-                            create_hypernetwork = gr.Button(value="Create hypernetwork", variant='primary', elem_id="train_create_hypernetwork")
-
-                with gr.Tab(label="Preprocess images"):
-                    process_src = gr.Textbox(label='Source directory', elem_id="train_process_src")
-                    process_dst = gr.Textbox(label='Destination directory', elem_id="train_process_dst")
-                    process_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_process_width")
-                    process_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_process_height")
-                    preprocess_txt_action = gr.Dropdown(label='Existing Caption txt Action', value="ignore", choices=["ignore", "copy", "prepend", "append"], elem_id="train_preprocess_txt_action")
-
-                    with gr.Row():
-                        process_flip = gr.Checkbox(label='Create flipped copies', elem_id="train_process_flip")
-                        process_split = gr.Checkbox(label='Split oversized images', elem_id="train_process_split")
-                        process_focal_crop = gr.Checkbox(label='Auto focal point crop', elem_id="train_process_focal_crop")
-                        process_caption = gr.Checkbox(label='Use BLIP for caption', elem_id="train_process_caption")
-                        process_caption_deepbooru = gr.Checkbox(label='Use deepbooru for caption', visible=True, elem_id="train_process_caption_deepbooru")
-
-                    with gr.Row(visible=False) as process_split_extra_row:
-                        process_split_threshold = gr.Slider(label='Split image threshold', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_split_threshold")
-                        process_overlap_ratio = gr.Slider(label='Split image overlap ratio', value=0.2, minimum=0.0, maximum=0.9, step=0.05, elem_id="train_process_overlap_ratio")
-
-                    with gr.Row(visible=False) as process_focal_crop_row:
-                        process_focal_crop_face_weight = gr.Slider(label='Focal point face weight', value=0.9, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_face_weight")
-                        process_focal_crop_entropy_weight = gr.Slider(label='Focal point entropy weight', value=0.15, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_entropy_weight")
-                        process_focal_crop_edges_weight = gr.Slider(label='Focal point edges weight', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_edges_weight")
-                        process_focal_crop_debug = gr.Checkbox(label='Create debug image', elem_id="train_process_focal_crop_debug")
-
-                    with gr.Row():
-                        with gr.Column(scale=3):
-                            gr.HTML(value="")
-
-                        with gr.Column():
-                            with gr.Row():
-                                interrupt_preprocessing = gr.Button("Interrupt", elem_id="train_interrupt_preprocessing")
-                            run_preprocess = gr.Button(value="Preprocess", variant='primary', elem_id="train_run_preprocess")
-
-                    process_split.change(
-                        fn=lambda show: gr_show(show),
-                        inputs=[process_split],
-                        outputs=[process_split_extra_row],
-                    )
-
-                    process_focal_crop.change(
-                        fn=lambda show: gr_show(show),
-                        inputs=[process_focal_crop],
-                        outputs=[process_focal_crop_row],
-                    )
-
-                def get_textual_inversion_template_names():
-                    return sorted([x for x in textual_inversion.textual_inversion_templates])
-
-                with gr.Tab(label="Train"):
-                    gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images <a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\" style=\"font-weight:bold;\">[wiki]</a></p>")
-                    with FormRow():
-                        train_embedding_name = gr.Dropdown(label='Embedding', elem_id="train_embedding", choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
-                        create_refresh_button(train_embedding_name, sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings, lambda: {"choices": sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())}, "refresh_train_embedding_name")
-
-                        train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=[x for x in shared.hypernetworks.keys()])
-                        create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted([x for x in shared.hypernetworks.keys()])}, "refresh_train_hypernetwork_name")
-
-                    with FormRow():
-                        embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005", elem_id="train_embedding_learn_rate")
-                        hypernetwork_learn_rate = gr.Textbox(label='Hypernetwork Learning rate', placeholder="Hypernetwork Learning rate", value="0.00001", elem_id="train_hypernetwork_learn_rate")
-                    
-                    with FormRow():
-                        clip_grad_mode = gr.Dropdown(value="disabled", label="Gradient Clipping", choices=["disabled", "value", "norm"])
-                        clip_grad_value = gr.Textbox(placeholder="Gradient clip value", value="0.1", show_label=False)
-
-                    with FormRow():
-                        batch_size = gr.Number(label='Batch size', value=1, precision=0, elem_id="train_batch_size")
-                        gradient_step = gr.Number(label='Gradient accumulation steps', value=1, precision=0, elem_id="train_gradient_step")
-
-                    dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images", elem_id="train_dataset_directory")
-                    log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion", elem_id="train_log_directory")
-
-                    with FormRow():
-                        template_file = gr.Dropdown(label='Prompt template', value="style_filewords.txt", elem_id="train_template_file", choices=get_textual_inversion_template_names())
-                        create_refresh_button(template_file, textual_inversion.list_textual_inversion_templates, lambda: {"choices": get_textual_inversion_template_names()}, "refrsh_train_template_file")
-
-                    training_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_training_width")
-                    training_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_training_height")
-                    varsize = gr.Checkbox(label="Do not resize images", value=False, elem_id="train_varsize")
-                    steps = gr.Number(label='Max steps', value=100000, precision=0, elem_id="train_steps")
-
-                    with FormRow():
-                        create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0, elem_id="train_create_image_every")
-                        save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0, elem_id="train_save_embedding_every")
-
-                    save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True, elem_id="train_save_image_with_stored_embedding")
-                    preview_from_txt2img = gr.Checkbox(label='Read parameters (prompt, etc...) from txt2img tab when making previews', value=False, elem_id="train_preview_from_txt2img")
-
-                    shuffle_tags = gr.Checkbox(label="Shuffle tags by ',' when creating prompts.", value=False, elem_id="train_shuffle_tags")
-                    tag_drop_out = gr.Slider(minimum=0, maximum=1, step=0.1, label="Drop out tags when creating prompts.", value=0, elem_id="train_tag_drop_out")
-
-                    latent_sampling_method = gr.Radio(label='Choose latent sampling method', value="once", choices=['once', 'deterministic', 'random'], elem_id="train_latent_sampling_method")
-
-                    with gr.Row():
-                        train_embedding = gr.Button(value="Train Embedding", variant='primary', elem_id="train_train_embedding")
-                        interrupt_training = gr.Button(value="Interrupt", elem_id="train_interrupt_training")
-                        train_hypernetwork = gr.Button(value="Train Hypernetwork", variant='primary', elem_id="train_train_hypernetwork")
-
-                params = script_callbacks.UiTrainTabParams(txt2img_preview_params)
-
-                script_callbacks.ui_train_tabs_callback(params)
-
-            with gr.Column():
-                progressbar = gr.HTML(elem_id="ti_progressbar")
-                ti_output = gr.Text(elem_id="ti_output", value="", show_label=False)
-
-                ti_gallery = gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(grid=4)
-                ti_preview = gr.Image(elem_id='ti_preview', visible=False)
-                ti_progress = gr.HTML(elem_id="ti_progress", value="")
-                ti_outcome = gr.HTML(elem_id="ti_error", value="")
-                setup_progressbar(progressbar, ti_preview, 'ti', textinfo=ti_progress)
-
-        create_embedding.click(
-            fn=modules.textual_inversion.ui.create_embedding,
-            inputs=[
-                new_embedding_name,
-                initialization_text,
-                nvpt,
-                overwrite_old_embedding,
-            ],
-            outputs=[
-                train_embedding_name,
-                ti_output,
-                ti_outcome,
-            ]
-        )
-
-        create_hypernetwork.click(
-            fn=modules.hypernetworks.ui.create_hypernetwork,
-            inputs=[
-                new_hypernetwork_name,
-                new_hypernetwork_sizes,
-                overwrite_old_hypernetwork,
-                new_hypernetwork_layer_structure,
-                new_hypernetwork_activation_func,
-                new_hypernetwork_initialization_option,
-                new_hypernetwork_add_layer_norm,
-                new_hypernetwork_use_dropout,
-                new_hypernetwork_dropout_structure
-            ],
-            outputs=[
-                train_hypernetwork_name,
-                ti_output,
-                ti_outcome,
-            ]
-        )
-
-        run_preprocess.click(
-            fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]),
-            _js="start_training_textual_inversion",
-            inputs=[
-                process_src,
-                process_dst,
-                process_width,
-                process_height,
-                preprocess_txt_action,
-                process_flip,
-                process_split,
-                process_caption,
-                process_caption_deepbooru,
-                process_split_threshold,
-                process_overlap_ratio,
-                process_focal_crop,
-                process_focal_crop_face_weight,
-                process_focal_crop_entropy_weight,
-                process_focal_crop_edges_weight,
-                process_focal_crop_debug,
-            ],
-            outputs=[
-                ti_output,
-                ti_outcome,
-            ],
-        )
-
-        train_embedding.click(
-            fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.train_embedding, extra_outputs=[gr.update()]),
-            _js="start_training_textual_inversion",
-            inputs=[
-                train_embedding_name,
-                embedding_learn_rate,
-                batch_size,
-                gradient_step,
-                dataset_directory,
-                log_directory,
-                training_width,
-                training_height,
-                varsize,
-                steps,
-                clip_grad_mode,
-                clip_grad_value,
-                shuffle_tags,
-                tag_drop_out,
-                latent_sampling_method,
-                create_image_every,
-                save_embedding_every,
-                template_file,
-                save_image_with_stored_embedding,
-                preview_from_txt2img,
-                *txt2img_preview_params,
-            ],
-            outputs=[
-                ti_output,
-                ti_outcome,
-            ]
-        )
-
-        train_hypernetwork.click(
-            fn=wrap_gradio_gpu_call(modules.hypernetworks.ui.train_hypernetwork, extra_outputs=[gr.update()]),
-            _js="start_training_textual_inversion",
-            inputs=[
-                train_hypernetwork_name,
-                hypernetwork_learn_rate,
-                batch_size,
-                gradient_step,
-                dataset_directory,
-                log_directory,
-                training_width,
-                training_height,
-                varsize,
-                steps,
-                clip_grad_mode,
-                clip_grad_value,
-                shuffle_tags,
-                tag_drop_out,
-                latent_sampling_method,
-                create_image_every,
-                save_embedding_every,
-                template_file,
-                preview_from_txt2img,
-                *txt2img_preview_params,
-            ],
-            outputs=[
-                ti_output,
-                ti_outcome,
-            ]
-        )
-
-        interrupt_training.click(
-            fn=lambda: shared.state.interrupt(),
-            inputs=[],
-            outputs=[],
-        )
-
-        interrupt_preprocessing.click(
-            fn=lambda: shared.state.interrupt(),
-            inputs=[],
-            outputs=[],
-        )
-
-    def create_setting_component(key, is_quicksettings=False):
-        def fun():
-            return opts.data[key] if key in opts.data else opts.data_labels[key].default
-
-        info = opts.data_labels[key]
-        t = type(info.default)
-
-        args = info.component_args() if callable(info.component_args) else info.component_args
-
-        if info.component is not None:
-            comp = info.component
-        elif t == str:
-            comp = gr.Textbox
-        elif t == int:
-            comp = gr.Number
-        elif t == bool:
-            comp = gr.Checkbox
-        else:
-            raise Exception(f'bad options item type: {str(t)} for key {key}')
-
-        elem_id = "setting_"+key
-
-        if info.refresh is not None:
-            if is_quicksettings:
-                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 FormRow():
-                    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 {}))
-
-        return res
-
-    components = []
-    component_dict = {}
-
-    script_callbacks.ui_settings_callback()
-    opts.reorder()
-
-    def run_settings(*args):
-        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__}"
-
-        for key, value, comp in zip(opts.data_labels.keys(), args, components):
-            if comp == dummy_component:
-                continue
-
-            if opts.set(key, value):
-                changed.append(key)
-
-        try:
-            opts.save(shared.config_filename)
-        except RuntimeError:
-            return opts.dumpjson(), f'{len(changed)} settings changed without save: {", ".join(changed)}.'
-        return opts.dumpjson(), f'{len(changed)} settings changed{": " if len(changed) > 0 else ""}{", ".join(changed)}.'
-
-    def run_settings_single(value, key):
-        if not opts.same_type(value, opts.data_labels[key].default):
-            return gr.update(visible=True), opts.dumpjson()
-
-        if not opts.set(key, value):
-            return gr.update(value=getattr(opts, key)), opts.dumpjson()
-
-        opts.save(shared.config_filename)
-
-        return gr.update(value=value), opts.dumpjson()
-
-    with gr.Blocks(analytics_enabled=False) as settings_interface:
-        with gr.Row():
-            with gr.Column(scale=6):
-                settings_submit = gr.Button(value="Apply settings", variant='primary', elem_id="settings_submit")
-            with gr.Column():
-                restart_gradio = gr.Button(value='Reload UI', variant='primary', elem_id="settings_restart_gradio")
-
-        result = gr.HTML(elem_id="settings_result")
-
-        quicksettings_names = [x.strip() for x in opts.quicksettings.split(",")]
-        quicksettings_names = {x: i for i, x in enumerate(quicksettings_names) if x != 'quicksettings'}
-
-        quicksettings_list = []
-
-        previous_section = None
-        current_tab = None
-        with gr.Tabs(elem_id="settings"):
-            for i, (k, item) in enumerate(opts.data_labels.items()):
-                section_must_be_skipped = item.section[0] is None
-
-                if previous_section != item.section and not section_must_be_skipped:
-                    elem_id, text = item.section
-
-                    if current_tab is not None:
-                        current_tab.__exit__()
-
-                    current_tab = gr.TabItem(elem_id="settings_{}".format(elem_id), label=text)
-                    current_tab.__enter__()
-
-                    previous_section = item.section
-
-                if k in quicksettings_names and not shared.cmd_opts.freeze_settings:
-                    quicksettings_list.append((i, k, item))
-                    components.append(dummy_component)
-                elif section_must_be_skipped:
-                    components.append(dummy_component)
-                else:
-                    component = create_setting_component(k)
-                    component_dict[k] = component
-                    components.append(component)
-
-            if current_tab is not None:
-                current_tab.__exit__()
-
-            with gr.TabItem("Actions"):
-                request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications")
-                download_localization = gr.Button(value='Download localization template', elem_id="download_localization")
-                reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary', elem_id="settings_reload_script_bodies")
-
-            if os.path.exists("html/licenses.html"):
-                with open("html/licenses.html", encoding="utf8") as file:
-                    with gr.TabItem("Licenses"):
-                        gr.HTML(file.read(), elem_id="licenses")
-
-            gr.Button(value="Show all pages", elem_id="settings_show_all_pages")
-
-        request_notifications.click(
-            fn=lambda: None,
-            inputs=[],
-            outputs=[],
-            _js='function(){}'
-        )
-
-        download_localization.click(
-            fn=lambda: None,
-            inputs=[],
-            outputs=[],
-            _js='download_localization'
-        )
-
-        def reload_scripts():
-            modules.scripts.reload_script_body_only()
-            reload_javascript()  # need to refresh the html page
-
-        reload_script_bodies.click(
-            fn=reload_scripts,
-            inputs=[],
-            outputs=[]
-        )
-
-        def request_restart():
-            shared.state.interrupt()
-            shared.state.need_restart = True
-
-        restart_gradio.click(
-            fn=request_restart,
-            _js='restart_reload',
-            inputs=[],
-            outputs=[],
-        )
-
-    interfaces = [
-        (txt2img_interface, "txt2img", "txt2img"),
-        (img2img_interface, "img2img", "img2img"),
-        (extras_interface, "Extras", "extras"),
-        (pnginfo_interface, "PNG Info", "pnginfo"),
-        (modelmerger_interface, "Checkpoint Merger", "modelmerger"),
-        (train_interface, "Train", "ti"),
-    ]
-
-    css = ""
-
-    for cssfile in modules.scripts.list_files_with_name("style.css"):
-        if not os.path.isfile(cssfile):
-            continue
-
-        with open(cssfile, "r", encoding="utf8") as file:
-            css += file.read() + "\n"
-
-    if os.path.exists(os.path.join(script_path, "user.css")):
-        with open(os.path.join(script_path, "user.css"), "r", encoding="utf8") as file:
-            css += file.read() + "\n"
-
-    if not cmd_opts.no_progressbar_hiding:
-        css += css_hide_progressbar
-
-    interfaces += script_callbacks.ui_tabs_callback()
-    interfaces += [(settings_interface, "Settings", "settings")]
-
-    extensions_interface = ui_extensions.create_ui()
-    interfaces += [(extensions_interface, "Extensions", "extensions")]
-
-    with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion") as demo:
-        with gr.Row(elem_id="quicksettings"):
-            for i, k, item in sorted(quicksettings_list, key=lambda x: quicksettings_names.get(x[1], x[0])):
-                component = create_setting_component(k, is_quicksettings=True)
-                component_dict[k] = component
-
-        parameters_copypaste.integrate_settings_paste_fields(component_dict)
-        parameters_copypaste.run_bind()
-
-        with gr.Tabs(elem_id="tabs") as tabs:
-            for interface, label, ifid in interfaces:
-                with gr.TabItem(label, id=ifid, elem_id='tab_' + ifid):
-                    interface.render()
-
-        if os.path.exists(os.path.join(script_path, "notification.mp3")):
-            audio_notification = gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False)
-
-        if os.path.exists("html/footer.html"):
-            with open("html/footer.html", encoding="utf8") as file:
-                footer = file.read()
-                footer = footer.format(versions=versions_html())
-                gr.HTML(footer, elem_id="footer")
-
-        text_settings = gr.Textbox(elem_id="settings_json", value=lambda: opts.dumpjson(), visible=False)
-        settings_submit.click(
-            fn=wrap_gradio_call(run_settings, extra_outputs=[gr.update()]),
-            inputs=components,
-            outputs=[text_settings, result],
-        )
-
-        for i, k, item in quicksettings_list:
-            component = component_dict[k]
-
-            component.change(
-                fn=lambda value, k=k: run_settings_single(value, key=k),
-                inputs=[component],
-                outputs=[component, text_settings],
-            )
-
-        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)
-            except Exception as e:
-                print("Error loading/saving model file:", file=sys.stderr)
-                print(traceback.format_exc(), file=sys.stderr)
-                modules.sd_models.list_models()  # to remove the potentially missing models from the list
-                return [f"Error merging checkpoints: {e}"] + [gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(4)]
-            return results
-
-        modelmerger_merge.click(
-            fn=modelmerger,
-            inputs=[
-                primary_model_name,
-                secondary_model_name,
-                tertiary_model_name,
-                interp_method,
-                interp_amount,
-                save_as_half,
-                custom_name,
-                checkpoint_format,
-            ],
-            outputs=[
-                submit_result,
-                primary_model_name,
-                secondary_model_name,
-                tertiary_model_name,
-                component_dict['sd_model_checkpoint'],
-            ]
-        )
-
-    ui_config_file = cmd_opts.ui_config_file
-    ui_settings = {}
-    settings_count = len(ui_settings)
-    error_loading = False
-
-    try:
-        if os.path.exists(ui_config_file):
-            with open(ui_config_file, "r", encoding="utf8") as file:
-                ui_settings = json.load(file)
-    except Exception:
-        error_loading = True
-        print("Error loading settings:", file=sys.stderr)
-        print(traceback.format_exc(), file=sys.stderr)
-
-    def loadsave(path, x):
-        def apply_field(obj, field, condition=None, init_field=None):
-            key = path + "/" + field
-
-            if getattr(obj, 'custom_script_source', None) is not None:
-              key = 'customscript/' + obj.custom_script_source + '/' + key
-
-            if getattr(obj, 'do_not_save_to_config', False):
-                return
-
-            saved_value = ui_settings.get(key, None)
-            if saved_value is None:
-                ui_settings[key] = getattr(obj, field)
-            elif condition and not condition(saved_value):
-                print(f'Warning: Bad ui setting value: {key}: {saved_value}; Default value "{getattr(obj, field)}" will be used instead.')
-            else:
-                setattr(obj, field, saved_value)
-                if init_field is not None:
-                    init_field(saved_value)
-
-        if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number, gr.Dropdown] and x.visible:
-            apply_field(x, 'visible')
-
-        if type(x) == gr.Slider:
-            apply_field(x, 'value')
-            apply_field(x, 'minimum')
-            apply_field(x, 'maximum')
-            apply_field(x, 'step')
-
-        if type(x) == gr.Radio:
-            apply_field(x, 'value', lambda val: val in x.choices)
-
-        if type(x) == gr.Checkbox:
-            apply_field(x, 'value')
-
-        if type(x) == gr.Textbox:
-            apply_field(x, 'value')
-
-        if type(x) == gr.Number:
-            apply_field(x, 'value')
-
-        if type(x) == gr.Dropdown:
-            apply_field(x, 'value', lambda val: val in x.choices, getattr(x, 'init_field', None))
-
-    visit(txt2img_interface, loadsave, "txt2img")
-    visit(img2img_interface, loadsave, "img2img")
-    visit(extras_interface, loadsave, "extras")
-    visit(modelmerger_interface, loadsave, "modelmerger")
-    visit(train_interface, loadsave, "train")
-
-    if not error_loading and (not os.path.exists(ui_config_file) or settings_count != len(ui_settings)):
-        with open(ui_config_file, "w", encoding="utf8") as file:
-            json.dump(ui_settings, file, indent=4)
-
-    return demo
-
-
-def reload_javascript():
-    with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile:
-        javascript = f'<script>{jsfile.read()}</script>'
-
-    scripts_list = modules.scripts.list_scripts("javascript", ".js")
-
-    for basedir, filename, path in scripts_list:
-        with open(path, "r", encoding="utf8") as jsfile:
-            javascript += f"\n<!-- {filename} --><script>{jsfile.read()}</script>"
-
-    if cmd_opts.theme is not None:
-        javascript += f"\n<script>set_theme('{cmd_opts.theme}');</script>\n"
-
-    javascript += f"\n<script>{localization.localization_js(shared.opts.localization)}</script>"
-
-    def template_response(*args, **kwargs):
-        res = shared.GradioTemplateResponseOriginal(*args, **kwargs)
-        res.body = res.body.replace(
-            b'</head>', f'{javascript}</head>'.encode("utf8"))
-        res.init_headers()
-        return res
-
-    gradio.routes.templates.TemplateResponse = template_response
-
-
-if not hasattr(shared, 'GradioTemplateResponseOriginal'):
-    shared.GradioTemplateResponseOriginal = gradio.routes.templates.TemplateResponse
-
-
-def versions_html():
-    import torch
-    import launch
-
-    python_version = ".".join([str(x) for x in sys.version_info[0:3]])
-    commit = launch.commit_hash()
-    short_commit = commit[0:8]
-
-    if shared.xformers_available:
-        import xformers
-        xformers_version = xformers.__version__
-    else:
-        xformers_version = "N/A"
-
-    return f"""
-python: <span title="{sys.version}">{python_version}</span>
- • 
-torch: {torch.__version__}
- • 
-xformers: {xformers_version}
- • 
-gradio: {gr.__version__}
- • 
-commit: <a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui/commit/{commit}">{short_commit}</a>
-"""
diff --git a/modules/ui.py b/modules/ui.py
new file mode 100644
index 00000000..9b9081b5
--- /dev/null
+++ b/modules/ui.py
@@ -0,0 +1,1928 @@
+import html
+import json
+import math
+import mimetypes
+import os
+import platform
+import random
+import subprocess as sp
+import sys
+import tempfile
+import time
+import traceback
+from functools import partial, reduce
+
+import gradio as gr
+import gradio.routes
+import gradio.utils
+import numpy as np
+from PIL import Image, PngImagePlugin
+from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
+
+from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru
+from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
+from modules.paths import script_path
+
+from modules.shared import opts, cmd_opts, restricted_opts
+
+import modules.codeformer_model
+import modules.generation_parameters_copypaste as parameters_copypaste
+import modules.gfpgan_model
+import modules.hypernetworks.ui
+import modules.scripts
+import modules.shared as shared
+import modules.styles
+import modules.textual_inversion.ui
+from modules import prompt_parser
+from modules.images import save_image
+from modules.sd_hijack import model_hijack
+from modules.sd_samplers import samplers, samplers_for_img2img
+from modules.textual_inversion import textual_inversion
+import modules.hypernetworks.ui
+from modules.generation_parameters_copypaste import image_from_url_text
+
+# this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI
+mimetypes.init()
+mimetypes.add_type('application/javascript', '.js')
+
+if not cmd_opts.share and not cmd_opts.listen:
+    # fix gradio phoning home
+    gradio.utils.version_check = lambda: None
+    gradio.utils.get_local_ip_address = lambda: '127.0.0.1'
+
+if cmd_opts.ngrok is not None:
+    import modules.ngrok as ngrok
+    print('ngrok authtoken detected, trying to connect...')
+    ngrok.connect(
+        cmd_opts.ngrok,
+        cmd_opts.port if cmd_opts.port is not None else 7860,
+        cmd_opts.ngrok_region
+        )
+
+
+def gr_show(visible=True):
+    return {"visible": visible, "__type__": "update"}
+
+
+sample_img2img = "assets/stable-samples/img2img/sketch-mountains-input.jpg"
+sample_img2img = sample_img2img if os.path.exists(sample_img2img) else None
+
+css_hide_progressbar = """
+.wrap .m-12 svg { display:none!important; }
+.wrap .m-12::before { content:"Loading..." }
+.wrap .z-20 svg { display:none!important; }
+.wrap .z-20::before { content:"Loading..." }
+.progress-bar { display:none!important; }
+.meta-text { display:none!important; }
+.meta-text-center { display:none!important; }
+"""
+
+# Using constants for these since the variation selector isn't visible.
+# Important that they exactly match script.js for tooltip to work.
+random_symbol = '\U0001f3b2\ufe0f'  # 🎲️
+reuse_symbol = '\u267b\ufe0f'  # ♻️
+paste_symbol = '\u2199\ufe0f'  # ↙
+folder_symbol = '\U0001f4c2'  # 📂
+refresh_symbol = '\U0001f504'  # 🔄
+save_style_symbol = '\U0001f4be'  # 💾
+apply_style_symbol = '\U0001f4cb'  # 📋
+clear_prompt_symbol = '\U0001F5D1'  # 🗑️
+
+
+def plaintext_to_html(text):
+    text = "<p>" + "<br>\n".join([f"{html.escape(x)}" for x in text.split('\n')]) + "</p>"
+    return text
+
+def send_gradio_gallery_to_image(x):
+    if len(x) == 0:
+        return None
+    return image_from_url_text(x[0])
+
+def save_files(js_data, images, do_make_zip, index):
+    import csv
+    filenames = []
+    fullfns = []
+
+    #quick dictionary to class object conversion. Its necessary due apply_filename_pattern requiring it
+    class MyObject:
+        def __init__(self, d=None):
+            if d is not None:
+                for key, value in d.items():
+                    setattr(self, key, value)
+
+    data = json.loads(js_data)
+
+    p = MyObject(data)
+    path = opts.outdir_save
+    save_to_dirs = opts.use_save_to_dirs_for_ui
+    extension: str = opts.samples_format
+    start_index = 0
+
+    if index > -1 and opts.save_selected_only and (index >= data["index_of_first_image"]):  # ensures we are looking at a specific non-grid picture, and we have save_selected_only
+
+        images = [images[index]]
+        start_index = index
+
+    os.makedirs(opts.outdir_save, exist_ok=True)
+
+    with open(os.path.join(opts.outdir_save, "log.csv"), "a", encoding="utf8", newline='') as file:
+        at_start = file.tell() == 0
+        writer = csv.writer(file)
+        if at_start:
+            writer.writerow(["prompt", "seed", "width", "height", "sampler", "cfgs", "steps", "filename", "negative_prompt"])
+
+        for image_index, filedata in enumerate(images, start_index):
+            image = image_from_url_text(filedata)
+
+            is_grid = image_index < p.index_of_first_image
+            i = 0 if is_grid else (image_index - p.index_of_first_image)
+
+            fullfn, txt_fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
+
+            filename = os.path.relpath(fullfn, path)
+            filenames.append(filename)
+            fullfns.append(fullfn)
+            if txt_fullfn:
+                filenames.append(os.path.basename(txt_fullfn))
+                fullfns.append(txt_fullfn)
+
+        writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler_name"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]])
+
+    # Make Zip
+    if do_make_zip:
+        zip_filepath = os.path.join(path, "images.zip")
+
+        from zipfile import ZipFile
+        with ZipFile(zip_filepath, "w") as zip_file:
+            for i in range(len(fullfns)):
+                with open(fullfns[i], mode="rb") as f:
+                    zip_file.writestr(filenames[i], f.read())
+        fullfns.insert(0, zip_filepath)
+
+    return gr.File.update(value=fullfns, visible=True), plaintext_to_html(f"Saved: {filenames[0]}")
+
+
+def calc_time_left(progress, threshold, label, force_display, show_eta):
+    if progress == 0:
+        return ""
+    else:
+        time_since_start = time.time() - shared.state.time_start
+        eta = (time_since_start/progress)
+        eta_relative = eta-time_since_start
+        if (eta_relative > threshold and show_eta) or force_display:
+            if eta_relative > 3600:
+                return label + time.strftime('%H:%M:%S', time.gmtime(eta_relative))
+            elif eta_relative > 60:
+                return label + time.strftime('%M:%S',  time.gmtime(eta_relative))
+            else:
+                return label + time.strftime('%Ss',  time.gmtime(eta_relative))
+        else:
+            return ""
+
+
+def check_progress_call(id_part):
+    if shared.state.job_count == 0:
+        return "", gr_show(False), gr_show(False), gr_show(False)
+
+    progress = 0
+
+    if shared.state.job_count > 0:
+        progress += shared.state.job_no / shared.state.job_count
+    if shared.state.sampling_steps > 0:
+        progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps
+
+    # Show progress percentage and time left at the same moment, and base it also on steps done
+    show_eta = progress >= 0.01 or shared.state.sampling_step >= 10
+
+    time_left = calc_time_left(progress, 1, " ETA: ", shared.state.time_left_force_display, show_eta)
+    if time_left != "":
+        shared.state.time_left_force_display = True
+
+    progress = min(progress, 1)
+
+    progressbar = ""
+    if opts.show_progressbar:
+        progressbar = f"""<div class='progressDiv'><div class='progress' style="overflow:visible;width:{progress * 100}%;white-space:nowrap;">{"&nbsp;" * 2 + str(int(progress*100))+"%" + time_left if show_eta else ""}</div></div>"""
+
+    image = gr_show(False)
+    preview_visibility = gr_show(False)
+
+    if opts.show_progress_every_n_steps != 0:
+        shared.state.set_current_image()
+        image = shared.state.current_image
+
+        if image is None:
+            image = gr.update(value=None)
+        else:
+            preview_visibility = gr_show(True)
+
+    if shared.state.textinfo is not None:
+        textinfo_result = gr.HTML.update(value=shared.state.textinfo, visible=True)
+    else:
+        textinfo_result = gr_show(False)
+
+    return f"<span id='{id_part}_progress_span' style='display: none'>{time.time()}</span><p>{progressbar}</p>", preview_visibility, image, textinfo_result
+
+
+def check_progress_call_initial(id_part):
+    shared.state.job_count = -1
+    shared.state.current_latent = None
+    shared.state.current_image = None
+    shared.state.textinfo = None
+    shared.state.time_start = time.time()
+    shared.state.time_left_force_display = False
+
+    return check_progress_call(id_part)
+
+
+def visit(x, func, path=""):
+    if hasattr(x, 'children'):
+        for c in x.children:
+            visit(c, func, path)
+    elif x.label is not None:
+        func(path + "/" + str(x.label), x)
+
+
+def add_style(name: str, prompt: str, negative_prompt: str):
+    if name is None:
+        return [gr_show() for x in range(4)]
+
+    style = modules.styles.PromptStyle(name, prompt, negative_prompt)
+    shared.prompt_styles.styles[style.name] = style
+    # Save all loaded prompt styles: this allows us to update the storage format in the future more easily, because we
+    # reserialize all styles every time we save them
+    shared.prompt_styles.save_styles(shared.styles_filename)
+
+    return [gr.Dropdown.update(visible=True, choices=list(shared.prompt_styles.styles)) for _ in range(4)]
+
+
+def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resize_y):
+    from modules import processing, devices
+
+    if not enable:
+        return ""
+
+    p = processing.StableDiffusionProcessingTxt2Img(width=width, height=height, enable_hr=True, hr_scale=hr_scale, hr_resize_x=hr_resize_x, hr_resize_y=hr_resize_y)
+
+    with devices.autocast():
+        p.init([""], [0], [0])
+
+    return f"resize: from <span class='resolution'>{p.width}x{p.height}</span> to <span class='resolution'>{p.hr_resize_x or p.hr_upscale_to_x}x{p.hr_resize_y or p.hr_upscale_to_y}</span>"
+
+
+def apply_styles(prompt, prompt_neg, style1_name, style2_name):
+    prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, [style1_name, style2_name])
+    prompt_neg = shared.prompt_styles.apply_negative_styles_to_prompt(prompt_neg, [style1_name, style2_name])
+
+    return [gr.Textbox.update(value=prompt), gr.Textbox.update(value=prompt_neg), gr.Dropdown.update(value="None"), gr.Dropdown.update(value="None")]
+
+
+def interrogate(image):
+    prompt = shared.interrogator.interrogate(image.convert("RGB"))
+
+    return gr_show(True) if prompt is None else prompt
+
+
+def interrogate_deepbooru(image):
+    prompt = deepbooru.model.tag(image)
+    return gr_show(True) if prompt is None else prompt
+
+
+def create_seed_inputs(target_interface):
+    with FormRow(elem_id=target_interface + '_seed_row'):
+        seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1, elem_id=target_interface + '_seed')
+        seed.style(container=False)
+        random_seed = gr.Button(random_symbol, elem_id=target_interface + '_random_seed')
+        reuse_seed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_seed')
+
+        with gr.Group(elem_id=target_interface + '_subseed_show_box'):
+            seed_checkbox = gr.Checkbox(label='Extra', elem_id=target_interface + '_subseed_show', value=False)
+
+    # Components to show/hide based on the 'Extra' checkbox
+    seed_extras = []
+
+    with FormRow(visible=False, elem_id=target_interface + '_subseed_row') as seed_extra_row_1:
+        seed_extras.append(seed_extra_row_1)
+        subseed = gr.Number(label='Variation seed', value=-1, elem_id=target_interface + '_subseed')
+        subseed.style(container=False)
+        random_subseed = gr.Button(random_symbol, elem_id=target_interface + '_random_subseed')
+        reuse_subseed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_subseed')
+        subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=target_interface + '_subseed_strength')
+
+    with FormRow(visible=False) as seed_extra_row_2:
+        seed_extras.append(seed_extra_row_2)
+        seed_resize_from_w = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from width", value=0, elem_id=target_interface + '_seed_resize_from_w')
+        seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from height", value=0, elem_id=target_interface + '_seed_resize_from_h')
+
+    random_seed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[seed])
+    random_subseed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[subseed])
+
+    def change_visibility(show):
+        return {comp: gr_show(show) for comp in seed_extras}
+
+    seed_checkbox.change(change_visibility, show_progress=False, inputs=[seed_checkbox], outputs=seed_extras)
+
+    return seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox
+
+
+
+def connect_clear_prompt(button):
+    """Given clear button, prompt, and token_counter objects, setup clear prompt button click event"""
+    button.click(
+        _js="clear_prompt",
+        fn=None,
+        inputs=[],
+        outputs=[],
+    )
+
+
+def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: gr.Textbox, dummy_component, is_subseed):
+    """ Connects a 'reuse (sub)seed' button's click event so that it copies last used
+        (sub)seed value from generation info the to the seed field. If copying subseed and subseed strength
+        was 0, i.e. no variation seed was used, it copies the normal seed value instead."""
+    def copy_seed(gen_info_string: str, index):
+        res = -1
+
+        try:
+            gen_info = json.loads(gen_info_string)
+            index -= gen_info.get('index_of_first_image', 0)
+
+            if is_subseed and gen_info.get('subseed_strength', 0) > 0:
+                all_subseeds = gen_info.get('all_subseeds', [-1])
+                res = all_subseeds[index if 0 <= index < len(all_subseeds) else 0]
+            else:
+                all_seeds = gen_info.get('all_seeds', [-1])
+                res = all_seeds[index if 0 <= index < len(all_seeds) else 0]
+
+        except json.decoder.JSONDecodeError as e:
+            if gen_info_string != '':
+                print("Error parsing JSON generation info:", file=sys.stderr)
+                print(gen_info_string, file=sys.stderr)
+
+        return [res, gr_show(False)]
+
+    reuse_seed.click(
+        fn=copy_seed,
+        _js="(x, y) => [x, selected_gallery_index()]",
+        show_progress=False,
+        inputs=[generation_info, dummy_component],
+        outputs=[seed, dummy_component]
+    )
+
+
+def update_token_counter(text, steps):
+    try:
+        _, prompt_flat_list, _ = prompt_parser.get_multicond_prompt_list([text])
+        prompt_schedules = prompt_parser.get_learned_conditioning_prompt_schedules(prompt_flat_list, steps)
+
+    except Exception:
+        # a parsing error can happen here during typing, and we don't want to bother the user with
+        # messages related to it in console
+        prompt_schedules = [[[steps, text]]]
+
+    flat_prompts = reduce(lambda list1, list2: list1+list2, prompt_schedules)
+    prompts = [prompt_text for step, prompt_text in flat_prompts]
+    token_count, max_length = max([model_hijack.get_prompt_lengths(prompt) for prompt in prompts], key=lambda args: args[0])
+    style_class = ' class="red"' if (token_count > max_length) else ""
+    return f"<span {style_class}>{token_count}/{max_length}</span>"
+
+
+def create_toprow(is_img2img):
+    id_part = "img2img" if is_img2img else "txt2img"
+
+    with gr.Row(elem_id="toprow"):
+        with gr.Column(scale=6):
+            with gr.Row():
+                with gr.Column(scale=80):
+                    with gr.Row():
+                        prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=2,
+                            placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)"
+                        )
+
+            with gr.Row():
+                with gr.Column(scale=80):
+                    with gr.Row():
+                        negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2,
+                            placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)"
+                        )
+
+        with gr.Column(scale=1, elem_id="roll_col"):
+            paste = gr.Button(value=paste_symbol, elem_id="paste")
+            save_style = gr.Button(value=save_style_symbol, elem_id="style_create")
+            prompt_style_apply = gr.Button(value=apply_style_symbol, elem_id="style_apply")
+            clear_prompt_button = gr.Button(value=clear_prompt_symbol, elem_id=f"{id_part}_clear_prompt")
+            token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_token_counter")
+            token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button")
+
+            clear_prompt_button.click(
+                fn=lambda *x: x,
+                _js="confirm_clear_prompt",
+                inputs=[prompt, negative_prompt],
+                outputs=[prompt, negative_prompt],
+            )
+
+        button_interrogate = None
+        button_deepbooru = None
+        if is_img2img:
+            with gr.Column(scale=1, elem_id="interrogate_col"):
+                button_interrogate = gr.Button('Interrogate\nCLIP', elem_id="interrogate")
+                button_deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru")
+
+        with gr.Column(scale=1):
+            with gr.Row():
+                skip = gr.Button('Skip', elem_id=f"{id_part}_skip")
+                interrupt = gr.Button('Interrupt', elem_id=f"{id_part}_interrupt")
+                submit = gr.Button('Generate', elem_id=f"{id_part}_generate", variant='primary')
+
+                skip.click(
+                    fn=lambda: shared.state.skip(),
+                    inputs=[],
+                    outputs=[],
+                )
+
+                interrupt.click(
+                    fn=lambda: shared.state.interrupt(),
+                    inputs=[],
+                    outputs=[],
+                )
+
+            with gr.Row():
+                with gr.Column(scale=1, elem_id="style_pos_col"):
+                    prompt_style = gr.Dropdown(label="Style 1", elem_id=f"{id_part}_style_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())))
+
+                with gr.Column(scale=1, elem_id="style_neg_col"):
+                    prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())))
+
+    return prompt, prompt_style, negative_prompt, prompt_style2, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button
+
+
+def setup_progressbar(progressbar, preview, id_part, textinfo=None):
+    if textinfo is None:
+        textinfo = gr.HTML(visible=False)
+
+    check_progress = gr.Button('Check progress', elem_id=f"{id_part}_check_progress", visible=False)
+    check_progress.click(
+        fn=lambda: check_progress_call(id_part),
+        show_progress=False,
+        inputs=[],
+        outputs=[progressbar, preview, preview, textinfo],
+    )
+
+    check_progress_initial = gr.Button('Check progress (first)', elem_id=f"{id_part}_check_progress_initial", visible=False)
+    check_progress_initial.click(
+        fn=lambda: check_progress_call_initial(id_part),
+        show_progress=False,
+        inputs=[],
+        outputs=[progressbar, preview, preview, textinfo],
+    )
+
+
+def apply_setting(key, value):
+    if value is None:
+        return gr.update()
+
+    if shared.cmd_opts.freeze_settings:
+        return gr.update()
+
+    # dont allow model to be swapped when model hash exists in prompt
+    if key == "sd_model_checkpoint" and opts.disable_weights_auto_swap:
+        return gr.update()
+
+    if key == "sd_model_checkpoint":
+        ckpt_info = sd_models.get_closet_checkpoint_match(value)
+
+        if ckpt_info is not None:
+            value = ckpt_info.title
+        else:
+            return gr.update()
+
+    comp_args = opts.data_labels[key].component_args
+    if comp_args and isinstance(comp_args, dict) and comp_args.get('visible') is False:
+        return
+
+    valtype = type(opts.data_labels[key].default)
+    oldval = opts.data.get(key, None)
+    opts.data[key] = valtype(value) if valtype != type(None) else value
+    if oldval != value and opts.data_labels[key].onchange is not None:
+        opts.data_labels[key].onchange()
+
+    opts.save(shared.config_filename)
+    return value
+
+
+def update_generation_info(args):
+    generation_info, html_info, img_index = args
+    try:
+        generation_info = json.loads(generation_info)
+        if img_index < 0 or img_index >= len(generation_info["infotexts"]):
+            return html_info
+        return plaintext_to_html(generation_info["infotexts"][img_index])
+    except Exception:
+        pass
+    # if the json parse or anything else fails, just return the old html_info
+    return html_info
+
+
+def create_refresh_button(refresh_component, refresh_method, refreshed_args, elem_id):
+    def refresh():
+        refresh_method()
+        args = refreshed_args() if callable(refreshed_args) else refreshed_args
+
+        for k, v in args.items():
+            setattr(refresh_component, k, v)
+
+        return gr.update(**(args or {}))
+
+    refresh_button = ToolButton(value=refresh_symbol, elem_id=elem_id)
+    refresh_button.click(
+        fn=refresh,
+        inputs=[],
+        outputs=[refresh_component]
+    )
+    return refresh_button
+
+
+def create_output_panel(tabname, outdir):
+    def open_folder(f):
+        if not os.path.exists(f):
+            print(f'Folder "{f}" does not exist. After you create an image, the folder will be created.')
+            return
+        elif not os.path.isdir(f):
+            print(f"""
+WARNING
+An open_folder request was made with an argument that is not a folder.
+This could be an error or a malicious attempt to run code on your computer.
+Requested path was: {f}
+""", file=sys.stderr)
+            return
+
+        if not shared.cmd_opts.hide_ui_dir_config:
+            path = os.path.normpath(f)
+            if platform.system() == "Windows":
+                os.startfile(path)
+            elif platform.system() == "Darwin":
+                sp.Popen(["open", path])
+            elif "microsoft-standard-WSL2" in platform.uname().release:
+                sp.Popen(["wsl-open", path])
+            else:
+                sp.Popen(["xdg-open", path])
+
+    with gr.Column(variant='panel'):
+            with gr.Group():
+                result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery").style(grid=4)
+
+            generation_info = None
+            with gr.Column():
+                with gr.Row(elem_id=f"image_buttons_{tabname}"):
+                    open_folder_button = gr.Button(folder_symbol, elem_id="hidden_element" if shared.cmd_opts.hide_ui_dir_config else f'open_folder_{tabname}')
+
+                    if tabname != "extras":
+                        save = gr.Button('Save', elem_id=f'save_{tabname}')
+                        save_zip = gr.Button('Zip', elem_id=f'save_zip_{tabname}')
+
+                    buttons = parameters_copypaste.create_buttons(["img2img", "inpaint", "extras"])
+
+                open_folder_button.click(
+                    fn=lambda: open_folder(opts.outdir_samples or outdir),
+                    inputs=[],
+                    outputs=[],
+                )
+
+                if tabname != "extras":
+                    with gr.Row():
+                        download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False, elem_id=f'download_files_{tabname}')
+
+                    with gr.Group():
+                        html_info = gr.HTML(elem_id=f'html_info_{tabname}')
+                        html_log = gr.HTML(elem_id=f'html_log_{tabname}')
+
+                        generation_info = gr.Textbox(visible=False, elem_id=f'generation_info_{tabname}')
+                        if tabname == 'txt2img' or tabname == 'img2img':
+                            generation_info_button = gr.Button(visible=False, elem_id=f"{tabname}_generation_info_button")
+                            generation_info_button.click(
+                                fn=update_generation_info,
+                                _js="(x, y) => [x, y, selected_gallery_index()]",
+                                inputs=[generation_info, html_info],
+                                outputs=[html_info],
+                                preprocess=False
+                            )
+
+                        save.click(
+                            fn=wrap_gradio_call(save_files),
+                            _js="(x, y, z, w) => [x, y, false, selected_gallery_index()]",
+                            inputs=[
+                                generation_info,
+                                result_gallery,
+                                html_info,
+                                html_info,
+                            ],
+                            outputs=[
+                                download_files,
+                                html_log,
+                            ]
+                        )
+
+                        save_zip.click(
+                            fn=wrap_gradio_call(save_files),
+                            _js="(x, y, z, w) => [x, y, true, selected_gallery_index()]",
+                            inputs=[
+                                generation_info,
+                                result_gallery,
+                                html_info,
+                                html_info,
+                            ],
+                            outputs=[
+                                download_files,
+                                html_log,
+                            ]
+                        )
+
+                else:
+                    html_info_x = gr.HTML(elem_id=f'html_info_x_{tabname}')
+                    html_info = gr.HTML(elem_id=f'html_info_{tabname}')
+                    html_log = gr.HTML(elem_id=f'html_log_{tabname}')
+
+                parameters_copypaste.bind_buttons(buttons, result_gallery, "txt2img" if tabname == "txt2img" else None)
+                return result_gallery, generation_info if tabname != "extras" else html_info_x, html_info, html_log
+
+
+def create_sampler_and_steps_selection(choices, tabname):
+    if opts.samplers_in_dropdown:
+        with FormRow(elem_id=f"sampler_selection_{tabname}"):
+            sampler_index = gr.Dropdown(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")
+            steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling steps", value=20)
+    else:
+        with FormGroup(elem_id=f"sampler_selection_{tabname}"):
+            steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling steps", value=20)
+            sampler_index = gr.Radio(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")
+
+    return steps, sampler_index
+
+
+def ordered_ui_categories():
+    user_order = {x.strip(): i for i, x in enumerate(shared.opts.ui_reorder.split(","))}
+
+    for i, category in sorted(enumerate(shared.ui_reorder_categories), key=lambda x: user_order.get(x[1], x[0] + 1000)):
+        yield category
+
+
+def create_ui():
+    import modules.img2img
+    import modules.txt2img
+
+    reload_javascript()
+
+    parameters_copypaste.reset()
+
+    modules.scripts.scripts_current = modules.scripts.scripts_txt2img
+    modules.scripts.scripts_txt2img.initialize_scripts(is_img2img=False)
+
+    with gr.Blocks(analytics_enabled=False) as txt2img_interface:
+        txt2img_prompt, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _,txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False)
+
+        dummy_component = gr.Label(visible=False)
+        txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False)
+
+        with gr.Row(elem_id='txt2img_progress_row'):
+            with gr.Column(scale=1):
+                pass
+
+            with gr.Column(scale=1):
+                progressbar = gr.HTML(elem_id="txt2img_progressbar")
+                txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False)
+                setup_progressbar(progressbar, txt2img_preview, 'txt2img')
+
+        with gr.Row().style(equal_height=False):
+            with gr.Column(variant='panel', elem_id="txt2img_settings"):
+                for category in ordered_ui_categories():
+                    if category == "sampler":
+                        steps, sampler_index = create_sampler_and_steps_selection(samplers, "txt2img")
+
+                    elif category == "dimensions":
+                        with FormRow():
+                            with gr.Column(elem_id="txt2img_column_size", scale=4):
+                                width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="txt2img_width")
+                                height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="txt2img_height")
+
+                            if opts.dimensions_and_batch_together:
+                                with gr.Column(elem_id="txt2img_column_batch"):
+                                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
+                                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
+
+                    elif category == "cfg":
+                        cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="txt2img_cfg_scale")
+
+                    elif category == "seed":
+                        seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('txt2img')
+
+                    elif category == "checkboxes":
+                        with FormRow(elem_id="txt2img_checkboxes"):
+                            restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="txt2img_restore_faces")
+                            tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling")
+                            enable_hr = gr.Checkbox(label='Hires. fix', value=False, elem_id="txt2img_enable_hr")
+                            hr_final_resolution = FormHTML(value="", elem_id="txtimg_hr_finalres", label="Upscaled resolution", interactive=False)
+
+                    elif category == "hires_fix":
+                        with FormGroup(visible=False, elem_id="txt2img_hires_fix") as hr_options:
+                            with FormRow(elem_id="txt2img_hires_fix_row1"):
+                                hr_upscaler = gr.Dropdown(label="Upscaler", elem_id="txt2img_hr_upscaler", choices=[*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]], value=shared.latent_upscale_default_mode)
+                                hr_second_pass_steps = gr.Slider(minimum=0, maximum=150, step=1, label='Hires steps', value=0, elem_id="txt2img_hires_steps")
+                                denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7, elem_id="txt2img_denoising_strength")
+
+                            with FormRow(elem_id="txt2img_hires_fix_row2"):
+                                hr_scale = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Upscale by", value=2.0, elem_id="txt2img_hr_scale")
+                                hr_resize_x = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize width to", value=0, elem_id="txt2img_hr_resize_x")
+                                hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y")
+
+                    elif category == "batch":
+                        if not opts.dimensions_and_batch_together:
+                            with FormRow(elem_id="txt2img_column_batch"):
+                                batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
+                                batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
+
+                    elif category == "scripts":
+                        with FormGroup(elem_id="txt2img_script_container"):
+                            custom_inputs = modules.scripts.scripts_txt2img.setup_ui()
+
+            hr_resolution_preview_inputs = [enable_hr, width, height, hr_scale, hr_resize_x, hr_resize_y]
+            for input in hr_resolution_preview_inputs:
+                input.change(
+                    fn=calc_resolution_hires,
+                    inputs=hr_resolution_preview_inputs,
+                    outputs=[hr_final_resolution],
+                    show_progress=False,
+                )
+                input.change(
+                    None,
+                    _js="onCalcResolutionHires",
+                    inputs=hr_resolution_preview_inputs,
+                    outputs=[],
+                    show_progress=False,
+                )
+
+            txt2img_gallery, generation_info, html_info, html_log = create_output_panel("txt2img", opts.outdir_txt2img_samples)
+            parameters_copypaste.bind_buttons({"txt2img": txt2img_paste}, None, txt2img_prompt)
+
+            connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
+            connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
+
+            txt2img_args = dict(
+                fn=wrap_gradio_gpu_call(modules.txt2img.txt2img, extra_outputs=[None, '', '']),
+                _js="submit",
+                inputs=[
+                    txt2img_prompt,
+                    txt2img_negative_prompt,
+                    txt2img_prompt_style,
+                    txt2img_prompt_style2,
+                    steps,
+                    sampler_index,
+                    restore_faces,
+                    tiling,
+                    batch_count,
+                    batch_size,
+                    cfg_scale,
+                    seed,
+                    subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox,
+                    height,
+                    width,
+                    enable_hr,
+                    denoising_strength,
+                    hr_scale,
+                    hr_upscaler,
+                    hr_second_pass_steps,
+                    hr_resize_x,
+                    hr_resize_y,
+                ] + custom_inputs,
+
+                outputs=[
+                    txt2img_gallery,
+                    generation_info,
+                    html_info,
+                    html_log,
+                ],
+                show_progress=False,
+            )
+
+            txt2img_prompt.submit(**txt2img_args)
+            submit.click(**txt2img_args)
+
+            txt_prompt_img.change(
+                fn=modules.images.image_data,
+                inputs=[
+                    txt_prompt_img
+                ],
+                outputs=[
+                    txt2img_prompt,
+                    txt_prompt_img
+                ]
+            )
+
+            enable_hr.change(
+                fn=lambda x: gr_show(x),
+                inputs=[enable_hr],
+                outputs=[hr_options],
+                show_progress = False,
+            )
+
+            txt2img_paste_fields = [
+                (txt2img_prompt, "Prompt"),
+                (txt2img_negative_prompt, "Negative prompt"),
+                (steps, "Steps"),
+                (sampler_index, "Sampler"),
+                (restore_faces, "Face restoration"),
+                (cfg_scale, "CFG scale"),
+                (seed, "Seed"),
+                (width, "Size-1"),
+                (height, "Size-2"),
+                (batch_size, "Batch size"),
+                (subseed, "Variation seed"),
+                (subseed_strength, "Variation seed strength"),
+                (seed_resize_from_w, "Seed resize from-1"),
+                (seed_resize_from_h, "Seed resize from-2"),
+                (denoising_strength, "Denoising strength"),
+                (enable_hr, lambda d: "Denoising strength" in d),
+                (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)),
+                (hr_scale, "Hires upscale"),
+                (hr_upscaler, "Hires upscaler"),
+                (hr_second_pass_steps, "Hires steps"),
+                (hr_resize_x, "Hires resize-1"),
+                (hr_resize_y, "Hires resize-2"),
+                *modules.scripts.scripts_txt2img.infotext_fields
+            ]
+            parameters_copypaste.add_paste_fields("txt2img", None, txt2img_paste_fields)
+
+            txt2img_preview_params = [
+                txt2img_prompt,
+                txt2img_negative_prompt,
+                steps,
+                sampler_index,
+                cfg_scale,
+                seed,
+                width,
+                height,
+            ]
+
+            token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[txt2img_prompt, steps], outputs=[token_counter])
+
+    modules.scripts.scripts_current = modules.scripts.scripts_img2img
+    modules.scripts.scripts_img2img.initialize_scripts(is_img2img=True)
+
+    with gr.Blocks(analytics_enabled=False) as img2img_interface:
+        img2img_prompt, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,token_counter, token_button = create_toprow(is_img2img=True)
+
+        with gr.Row(elem_id='img2img_progress_row'):
+            img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False)
+
+            with gr.Column(scale=1):
+                pass
+
+            with gr.Column(scale=1):
+                progressbar = gr.HTML(elem_id="img2img_progressbar")
+                img2img_preview = gr.Image(elem_id='img2img_preview', visible=False)
+                setup_progressbar(progressbar, img2img_preview, 'img2img')
+
+        with FormRow().style(equal_height=False):
+            with gr.Column(variant='panel', elem_id="img2img_settings"):
+
+                with gr.Tabs(elem_id="mode_img2img") as tabs_img2img_mode:
+                    with gr.TabItem('img2img', id='img2img', elem_id="img2img_img2img_tab"):
+                        init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_img2img_tool, image_mode="RGBA").style(height=480)
+
+                    with gr.TabItem('Inpaint', id='inpaint', elem_id="img2img_inpaint_tab"):
+                        init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_inpaint_tool, image_mode="RGBA").style(height=480)
+                        init_img_with_mask_orig = gr.State(None)
+
+                        use_color_sketch = cmd_opts.gradio_inpaint_tool == "color-sketch"
+                        if use_color_sketch:
+                            def update_orig(image, state):
+                                if image is not None:
+                                    same_size = state is not None and state.size == image.size
+                                    has_exact_match = np.any(np.all(np.array(image) == np.array(state), axis=-1))
+                                    edited = same_size and has_exact_match
+                                    return image if not edited or state is None else state
+
+                            init_img_with_mask.change(update_orig, [init_img_with_mask, init_img_with_mask_orig], init_img_with_mask_orig)
+
+                        init_img_inpaint = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_base")
+                        init_mask_inpaint = gr.Image(label="Mask", source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_mask")
+
+                        with FormRow():
+                            mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id="img2img_mask_blur")
+                            mask_alpha = gr.Slider(label="Mask transparency", interactive=use_color_sketch, visible=use_color_sketch, elem_id="img2img_mask_alpha")
+
+                        with FormRow():
+                            mask_mode = gr.Radio(label="Mask source", choices=["Draw mask", "Upload mask"], type="index", value="Draw mask", elem_id="mask_mode")
+                            inpainting_mask_invert = gr.Radio(label='Mask mode', choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index", elem_id="img2img_mask_mode")
+
+                        with FormRow():
+                            inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='original', type="index", elem_id="img2img_inpainting_fill")
+
+                        with FormRow():
+                            with gr.Column():
+                                inpaint_full_res = gr.Radio(label="Inpaint area", choices=["Whole picture", "Only masked"], type="index", value="Whole picture", elem_id="img2img_inpaint_full_res")
+
+                            with gr.Column(scale=4):
+                                inpaint_full_res_padding = gr.Slider(label='Only masked padding, pixels', minimum=0, maximum=256, step=4, value=32, elem_id="img2img_inpaint_full_res_padding")
+
+                    with gr.TabItem('Batch img2img', id='batch', elem_id="img2img_batch_tab"):
+                        hidden = '<br>Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else ''
+                        gr.HTML(f"<p class=\"text-gray-500\">Process images in a directory on the same machine where the server is running.<br>Use an empty output directory to save pictures normally instead of writing to the output directory.{hidden}</p>")
+                        img2img_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, elem_id="img2img_batch_input_dir")
+                        img2img_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, elem_id="img2img_batch_output_dir")
+
+                with FormRow():
+                    resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", choices=["Just resize", "Crop and resize", "Resize and fill", "Just resize (latent upscale)"], type="index", value="Just resize")
+
+                for category in ordered_ui_categories():
+                    if category == "sampler":
+                        steps, sampler_index = create_sampler_and_steps_selection(samplers_for_img2img, "img2img")
+
+                    elif category == "dimensions":
+                        with FormRow():
+                            with gr.Column(elem_id="img2img_column_size", scale=4):
+                                width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
+                                height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
+
+                            if opts.dimensions_and_batch_together:
+                                with gr.Column(elem_id="img2img_column_batch"):
+                                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
+                                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")
+
+                    elif category == "cfg":
+                        with FormGroup():
+                            cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="img2img_cfg_scale")
+                            denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75, elem_id="img2img_denoising_strength")
+
+                    elif category == "seed":
+                        seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('img2img')
+
+                    elif category == "checkboxes":
+                        with FormRow(elem_id="img2img_checkboxes"):
+                            restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="img2img_restore_faces")
+                            tiling = gr.Checkbox(label='Tiling', value=False, elem_id="img2img_tiling")
+
+                    elif category == "batch":
+                        if not opts.dimensions_and_batch_together:
+                            with FormRow(elem_id="img2img_column_batch"):
+                                batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
+                                batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")
+
+                    elif category == "scripts":
+                        with FormGroup(elem_id="img2img_script_container"):
+                            custom_inputs = modules.scripts.scripts_img2img.setup_ui()
+
+            img2img_gallery, generation_info, html_info, html_log = create_output_panel("img2img", opts.outdir_img2img_samples)
+            parameters_copypaste.bind_buttons({"img2img": img2img_paste}, None, img2img_prompt)
+
+            connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
+            connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
+
+            img2img_prompt_img.change(
+                fn=modules.images.image_data,
+                inputs=[
+                    img2img_prompt_img
+                ],
+                outputs=[
+                    img2img_prompt,
+                    img2img_prompt_img
+                ]
+            )
+
+            mask_mode.change(
+                lambda mode, img: {
+                    init_img_with_mask: gr_show(mode == 0),
+                    init_img_inpaint: gr_show(mode == 1),
+                    init_mask_inpaint: gr_show(mode == 1),
+                },
+                inputs=[mask_mode, init_img_with_mask],
+                outputs=[
+                    init_img_with_mask,
+                    init_img_inpaint,
+                    init_mask_inpaint,
+                ],
+            )
+
+            img2img_args = dict(
+                fn=wrap_gradio_gpu_call(modules.img2img.img2img, extra_outputs=[None, '', '']),
+                _js="submit_img2img",
+                inputs=[
+                    dummy_component,
+                    img2img_prompt,
+                    img2img_negative_prompt,
+                    img2img_prompt_style,
+                    img2img_prompt_style2,
+                    init_img,
+                    init_img_with_mask,
+                    init_img_with_mask_orig,
+                    init_img_inpaint,
+                    init_mask_inpaint,
+                    mask_mode,
+                    steps,
+                    sampler_index,
+                    mask_blur,
+                    mask_alpha,
+                    inpainting_fill,
+                    restore_faces,
+                    tiling,
+                    batch_count,
+                    batch_size,
+                    cfg_scale,
+                    denoising_strength,
+                    seed,
+                    subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox,
+                    height,
+                    width,
+                    resize_mode,
+                    inpaint_full_res,
+                    inpaint_full_res_padding,
+                    inpainting_mask_invert,
+                    img2img_batch_input_dir,
+                    img2img_batch_output_dir,
+                ] + custom_inputs,
+                outputs=[
+                    img2img_gallery,
+                    generation_info,
+                    html_info,
+                    html_log,
+                ],
+                show_progress=False,
+            )
+
+            img2img_prompt.submit(**img2img_args)
+            submit.click(**img2img_args)
+
+            img2img_interrogate.click(
+                fn=interrogate,
+                inputs=[init_img],
+                outputs=[img2img_prompt],
+            )
+
+            img2img_deepbooru.click(
+                fn=interrogate_deepbooru,
+                inputs=[init_img],
+                outputs=[img2img_prompt],
+            )
+
+            prompts = [(txt2img_prompt, txt2img_negative_prompt), (img2img_prompt, img2img_negative_prompt)]
+            style_dropdowns = [(txt2img_prompt_style, txt2img_prompt_style2), (img2img_prompt_style, img2img_prompt_style2)]
+            style_js_funcs = ["update_txt2img_tokens", "update_img2img_tokens"]
+
+            for button, (prompt, negative_prompt) in zip([txt2img_save_style, img2img_save_style], prompts):
+                button.click(
+                    fn=add_style,
+                    _js="ask_for_style_name",
+                    # Have to pass empty dummy component here, because the JavaScript and Python function have to accept
+                    # the same number of parameters, but we only know the style-name after the JavaScript prompt
+                    inputs=[dummy_component, prompt, negative_prompt],
+                    outputs=[txt2img_prompt_style, img2img_prompt_style, txt2img_prompt_style2, img2img_prompt_style2],
+                )
+
+            for button, (prompt, negative_prompt), (style1, style2), js_func in zip([txt2img_prompt_style_apply, img2img_prompt_style_apply], prompts, style_dropdowns, style_js_funcs):
+                button.click(
+                    fn=apply_styles,
+                    _js=js_func,
+                    inputs=[prompt, negative_prompt, style1, style2],
+                    outputs=[prompt, negative_prompt, style1, style2],
+                )
+
+            token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter])
+
+            img2img_paste_fields = [
+                (img2img_prompt, "Prompt"),
+                (img2img_negative_prompt, "Negative prompt"),
+                (steps, "Steps"),
+                (sampler_index, "Sampler"),
+                (restore_faces, "Face restoration"),
+                (cfg_scale, "CFG scale"),
+                (seed, "Seed"),
+                (width, "Size-1"),
+                (height, "Size-2"),
+                (batch_size, "Batch size"),
+                (subseed, "Variation seed"),
+                (subseed_strength, "Variation seed strength"),
+                (seed_resize_from_w, "Seed resize from-1"),
+                (seed_resize_from_h, "Seed resize from-2"),
+                (denoising_strength, "Denoising strength"),
+                (mask_blur, "Mask blur"),
+                *modules.scripts.scripts_img2img.infotext_fields
+            ]
+            parameters_copypaste.add_paste_fields("img2img", init_img, img2img_paste_fields)
+            parameters_copypaste.add_paste_fields("inpaint", init_img_with_mask, img2img_paste_fields)
+
+    modules.scripts.scripts_current = None
+
+    with gr.Blocks(analytics_enabled=False) as extras_interface:
+        with gr.Row().style(equal_height=False):
+            with gr.Column(variant='panel'):
+                with gr.Tabs(elem_id="mode_extras"):
+                    with gr.TabItem('Single Image', elem_id="extras_single_tab"):
+                        extras_image = gr.Image(label="Source", source="upload", interactive=True, type="pil", elem_id="extras_image")
+
+                    with gr.TabItem('Batch Process', elem_id="extras_batch_process_tab"):
+                        image_batch = gr.File(label="Batch Process", file_count="multiple", interactive=True, type="file", elem_id="extras_image_batch")
+
+                    with gr.TabItem('Batch from Directory', elem_id="extras_batch_directory_tab"):
+                        extras_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, placeholder="A directory on the same machine where the server is running.", elem_id="extras_batch_input_dir")
+                        extras_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, placeholder="Leave blank to save images to the default path.", elem_id="extras_batch_output_dir")
+                        show_extras_results = gr.Checkbox(label='Show result images', value=True, elem_id="extras_show_extras_results")
+
+                submit = gr.Button('Generate', elem_id="extras_generate", variant='primary')
+
+                with gr.Tabs(elem_id="extras_resize_mode"):
+                    with gr.TabItem('Scale by', elem_id="extras_scale_by_tab"):
+                        upscaling_resize = gr.Slider(minimum=1.0, maximum=8.0, step=0.05, label="Resize", value=4, elem_id="extras_upscaling_resize")
+                    with gr.TabItem('Scale to', elem_id="extras_scale_to_tab"):
+                        with gr.Group():
+                            with gr.Row():
+                                upscaling_resize_w = gr.Number(label="Width", value=512, precision=0, elem_id="extras_upscaling_resize_w")
+                                upscaling_resize_h = gr.Number(label="Height", value=512, precision=0, elem_id="extras_upscaling_resize_h")
+                            upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop")
+
+                with gr.Group():
+                    extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
+
+                with gr.Group():
+                    extras_upscaler_2 = gr.Radio(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
+                    extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=1, elem_id="extras_upscaler_2_visibility")
+
+                with gr.Group():
+                    gfpgan_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="GFPGAN visibility", value=0, interactive=modules.gfpgan_model.have_gfpgan, elem_id="extras_gfpgan_visibility")
+
+                with gr.Group():
+                    codeformer_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer visibility", value=0, interactive=modules.codeformer_model.have_codeformer, elem_id="extras_codeformer_visibility")
+                    codeformer_weight = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer weight (0 = maximum effect, 1 = minimum effect)", value=0, interactive=modules.codeformer_model.have_codeformer, elem_id="extras_codeformer_weight")
+
+                with gr.Group():
+                    upscale_before_face_fix = gr.Checkbox(label='Upscale Before Restoring Faces', value=False, elem_id="extras_upscale_before_face_fix")
+
+            result_images, html_info_x, html_info, html_log = create_output_panel("extras", opts.outdir_extras_samples)
+
+        submit.click(
+            fn=wrap_gradio_gpu_call(modules.extras.run_extras, extra_outputs=[None, '']),
+            _js="get_extras_tab_index",
+            inputs=[
+                dummy_component,
+                dummy_component,
+                extras_image,
+                image_batch,
+                extras_batch_input_dir,
+                extras_batch_output_dir,
+                show_extras_results,
+                gfpgan_visibility,
+                codeformer_visibility,
+                codeformer_weight,
+                upscaling_resize,
+                upscaling_resize_w,
+                upscaling_resize_h,
+                upscaling_crop,
+                extras_upscaler_1,
+                extras_upscaler_2,
+                extras_upscaler_2_visibility,
+                upscale_before_face_fix,
+            ],
+            outputs=[
+                result_images,
+                html_info_x,
+                html_info,
+            ]
+        )
+        parameters_copypaste.add_paste_fields("extras", extras_image, None)
+
+        extras_image.change(
+            fn=modules.extras.clear_cache,
+            inputs=[], outputs=[]
+        )
+
+    with gr.Blocks(analytics_enabled=False) as pnginfo_interface:
+        with gr.Row().style(equal_height=False):
+            with gr.Column(variant='panel'):
+                image = gr.Image(elem_id="pnginfo_image", label="Source", source="upload", interactive=True, type="pil")
+
+            with gr.Column(variant='panel'):
+                html = gr.HTML()
+                generation_info = gr.Textbox(visible=False, elem_id="pnginfo_generation_info")
+                html2 = gr.HTML()
+                with gr.Row():
+                    buttons = parameters_copypaste.create_buttons(["txt2img", "img2img", "inpaint", "extras"])
+                parameters_copypaste.bind_buttons(buttons, image, generation_info)
+
+        image.change(
+            fn=wrap_gradio_call(modules.extras.run_pnginfo),
+            inputs=[image],
+            outputs=[html, generation_info, html2],
+        )
+
+    with gr.Blocks(analytics_enabled=False) as modelmerger_interface:
+        with gr.Row().style(equal_height=False):
+            with gr.Column(variant='panel'):
+                gr.HTML(value="<p>A merger of the two checkpoints will be generated in your <b>checkpoint</b> directory.</p>")
+
+                with gr.Row():
+                    primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)")
+                    create_refresh_button(primary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_A")
+
+                    secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary model (B)")
+                    create_refresh_button(secondary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_B")
+
+                    tertiary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_tertiary_model_name", label="Tertiary model (C)")
+                    create_refresh_button(tertiary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_C")
+
+                custom_name = gr.Textbox(label="Custom Name (Optional)", elem_id="modelmerger_custom_name")
+                interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3, elem_id="modelmerger_interp_amount")
+                interp_method = gr.Radio(choices=["Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method", elem_id="modelmerger_interp_method")
+
+                with gr.Row():
+                    checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format", elem_id="modelmerger_checkpoint_format")
+                    save_as_half = gr.Checkbox(value=False, label="Save as float16", elem_id="modelmerger_save_as_half")
+
+                modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary')
+
+            with gr.Column(variant='panel'):
+                submit_result = gr.Textbox(elem_id="modelmerger_result", show_label=False)
+
+    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>")
+
+        with gr.Row().style(equal_height=False):
+            with gr.Tabs(elem_id="train_tabs"):
+
+                with gr.Tab(label="Create embedding"):
+                    new_embedding_name = gr.Textbox(label="Name", elem_id="train_new_embedding_name")
+                    initialization_text = gr.Textbox(label="Initialization text", value="*", elem_id="train_initialization_text")
+                    nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1, elem_id="train_nvpt")
+                    overwrite_old_embedding = gr.Checkbox(value=False, label="Overwrite Old Embedding", elem_id="train_overwrite_old_embedding")
+
+                    with gr.Row():
+                        with gr.Column(scale=3):
+                            gr.HTML(value="")
+
+                        with gr.Column():
+                            create_embedding = gr.Button(value="Create embedding", variant='primary', elem_id="train_create_embedding")
+
+                with gr.Tab(label="Create hypernetwork"):
+                    new_hypernetwork_name = gr.Textbox(label="Name", elem_id="train_new_hypernetwork_name")
+                    new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "1024", "320", "640", "1280"], elem_id="train_new_hypernetwork_sizes")
+                    new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'", elem_id="train_new_hypernetwork_layer_structure")
+                    new_hypernetwork_activation_func = gr.Dropdown(value="linear", label="Select activation function of hypernetwork. Recommended : Swish / Linear(none)", choices=modules.hypernetworks.ui.keys, elem_id="train_new_hypernetwork_activation_func")
+                    new_hypernetwork_initialization_option = gr.Dropdown(value = "Normal", label="Select Layer weights initialization. Recommended: Kaiming for relu-like, Xavier for sigmoid-like, Normal otherwise", choices=["Normal", "KaimingUniform", "KaimingNormal", "XavierUniform", "XavierNormal"], elem_id="train_new_hypernetwork_initialization_option")
+                    new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization", elem_id="train_new_hypernetwork_add_layer_norm")
+                    new_hypernetwork_use_dropout = gr.Checkbox(label="Use dropout", elem_id="train_new_hypernetwork_use_dropout")
+                    new_hypernetwork_dropout_structure = gr.Textbox("0, 0, 0", label="Enter hypernetwork Dropout structure (or empty). Recommended : 0~0.35 incrementing sequence: 0, 0.05, 0.15", placeholder="1st and last digit must be 0 and values should be between 0 and 1. ex:'0, 0.01, 0'")
+                    overwrite_old_hypernetwork = gr.Checkbox(value=False, label="Overwrite Old Hypernetwork", elem_id="train_overwrite_old_hypernetwork")
+
+                    with gr.Row():
+                        with gr.Column(scale=3):
+                            gr.HTML(value="")
+
+                        with gr.Column():
+                            create_hypernetwork = gr.Button(value="Create hypernetwork", variant='primary', elem_id="train_create_hypernetwork")
+
+                with gr.Tab(label="Preprocess images"):
+                    process_src = gr.Textbox(label='Source directory', elem_id="train_process_src")
+                    process_dst = gr.Textbox(label='Destination directory', elem_id="train_process_dst")
+                    process_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_process_width")
+                    process_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_process_height")
+                    preprocess_txt_action = gr.Dropdown(label='Existing Caption txt Action', value="ignore", choices=["ignore", "copy", "prepend", "append"], elem_id="train_preprocess_txt_action")
+
+                    with gr.Row():
+                        process_flip = gr.Checkbox(label='Create flipped copies', elem_id="train_process_flip")
+                        process_split = gr.Checkbox(label='Split oversized images', elem_id="train_process_split")
+                        process_focal_crop = gr.Checkbox(label='Auto focal point crop', elem_id="train_process_focal_crop")
+                        process_caption = gr.Checkbox(label='Use BLIP for caption', elem_id="train_process_caption")
+                        process_caption_deepbooru = gr.Checkbox(label='Use deepbooru for caption', visible=True, elem_id="train_process_caption_deepbooru")
+
+                    with gr.Row(visible=False) as process_split_extra_row:
+                        process_split_threshold = gr.Slider(label='Split image threshold', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_split_threshold")
+                        process_overlap_ratio = gr.Slider(label='Split image overlap ratio', value=0.2, minimum=0.0, maximum=0.9, step=0.05, elem_id="train_process_overlap_ratio")
+
+                    with gr.Row(visible=False) as process_focal_crop_row:
+                        process_focal_crop_face_weight = gr.Slider(label='Focal point face weight', value=0.9, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_face_weight")
+                        process_focal_crop_entropy_weight = gr.Slider(label='Focal point entropy weight', value=0.15, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_entropy_weight")
+                        process_focal_crop_edges_weight = gr.Slider(label='Focal point edges weight', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_edges_weight")
+                        process_focal_crop_debug = gr.Checkbox(label='Create debug image', elem_id="train_process_focal_crop_debug")
+
+                    with gr.Row():
+                        with gr.Column(scale=3):
+                            gr.HTML(value="")
+
+                        with gr.Column():
+                            with gr.Row():
+                                interrupt_preprocessing = gr.Button("Interrupt", elem_id="train_interrupt_preprocessing")
+                            run_preprocess = gr.Button(value="Preprocess", variant='primary', elem_id="train_run_preprocess")
+
+                    process_split.change(
+                        fn=lambda show: gr_show(show),
+                        inputs=[process_split],
+                        outputs=[process_split_extra_row],
+                    )
+
+                    process_focal_crop.change(
+                        fn=lambda show: gr_show(show),
+                        inputs=[process_focal_crop],
+                        outputs=[process_focal_crop_row],
+                    )
+
+                def get_textual_inversion_template_names():
+                    return sorted([x for x in textual_inversion.textual_inversion_templates])
+
+                with gr.Tab(label="Train"):
+                    gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images <a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\" style=\"font-weight:bold;\">[wiki]</a></p>")
+                    with FormRow():
+                        train_embedding_name = gr.Dropdown(label='Embedding', elem_id="train_embedding", choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
+                        create_refresh_button(train_embedding_name, sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings, lambda: {"choices": sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())}, "refresh_train_embedding_name")
+
+                        train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=[x for x in shared.hypernetworks.keys()])
+                        create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted([x for x in shared.hypernetworks.keys()])}, "refresh_train_hypernetwork_name")
+
+                    with FormRow():
+                        embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005", elem_id="train_embedding_learn_rate")
+                        hypernetwork_learn_rate = gr.Textbox(label='Hypernetwork Learning rate', placeholder="Hypernetwork Learning rate", value="0.00001", elem_id="train_hypernetwork_learn_rate")
+                    
+                    with FormRow():
+                        clip_grad_mode = gr.Dropdown(value="disabled", label="Gradient Clipping", choices=["disabled", "value", "norm"])
+                        clip_grad_value = gr.Textbox(placeholder="Gradient clip value", value="0.1", show_label=False)
+
+                    with FormRow():
+                        batch_size = gr.Number(label='Batch size', value=1, precision=0, elem_id="train_batch_size")
+                        gradient_step = gr.Number(label='Gradient accumulation steps', value=1, precision=0, elem_id="train_gradient_step")
+
+                    dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images", elem_id="train_dataset_directory")
+                    log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion", elem_id="train_log_directory")
+
+                    with FormRow():
+                        template_file = gr.Dropdown(label='Prompt template', value="style_filewords.txt", elem_id="train_template_file", choices=get_textual_inversion_template_names())
+                        create_refresh_button(template_file, textual_inversion.list_textual_inversion_templates, lambda: {"choices": get_textual_inversion_template_names()}, "refrsh_train_template_file")
+
+                    training_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_training_width")
+                    training_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_training_height")
+                    varsize = gr.Checkbox(label="Do not resize images", value=False, elem_id="train_varsize")
+                    steps = gr.Number(label='Max steps', value=100000, precision=0, elem_id="train_steps")
+
+                    with FormRow():
+                        create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0, elem_id="train_create_image_every")
+                        save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0, elem_id="train_save_embedding_every")
+
+                    save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True, elem_id="train_save_image_with_stored_embedding")
+                    preview_from_txt2img = gr.Checkbox(label='Read parameters (prompt, etc...) from txt2img tab when making previews', value=False, elem_id="train_preview_from_txt2img")
+
+                    shuffle_tags = gr.Checkbox(label="Shuffle tags by ',' when creating prompts.", value=False, elem_id="train_shuffle_tags")
+                    tag_drop_out = gr.Slider(minimum=0, maximum=1, step=0.1, label="Drop out tags when creating prompts.", value=0, elem_id="train_tag_drop_out")
+
+                    latent_sampling_method = gr.Radio(label='Choose latent sampling method', value="once", choices=['once', 'deterministic', 'random'], elem_id="train_latent_sampling_method")
+
+                    with gr.Row():
+                        train_embedding = gr.Button(value="Train Embedding", variant='primary', elem_id="train_train_embedding")
+                        interrupt_training = gr.Button(value="Interrupt", elem_id="train_interrupt_training")
+                        train_hypernetwork = gr.Button(value="Train Hypernetwork", variant='primary', elem_id="train_train_hypernetwork")
+
+                params = script_callbacks.UiTrainTabParams(txt2img_preview_params)
+
+                script_callbacks.ui_train_tabs_callback(params)
+
+            with gr.Column():
+                progressbar = gr.HTML(elem_id="ti_progressbar")
+                ti_output = gr.Text(elem_id="ti_output", value="", show_label=False)
+
+                ti_gallery = gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(grid=4)
+                ti_preview = gr.Image(elem_id='ti_preview', visible=False)
+                ti_progress = gr.HTML(elem_id="ti_progress", value="")
+                ti_outcome = gr.HTML(elem_id="ti_error", value="")
+                setup_progressbar(progressbar, ti_preview, 'ti', textinfo=ti_progress)
+
+        create_embedding.click(
+            fn=modules.textual_inversion.ui.create_embedding,
+            inputs=[
+                new_embedding_name,
+                initialization_text,
+                nvpt,
+                overwrite_old_embedding,
+            ],
+            outputs=[
+                train_embedding_name,
+                ti_output,
+                ti_outcome,
+            ]
+        )
+
+        create_hypernetwork.click(
+            fn=modules.hypernetworks.ui.create_hypernetwork,
+            inputs=[
+                new_hypernetwork_name,
+                new_hypernetwork_sizes,
+                overwrite_old_hypernetwork,
+                new_hypernetwork_layer_structure,
+                new_hypernetwork_activation_func,
+                new_hypernetwork_initialization_option,
+                new_hypernetwork_add_layer_norm,
+                new_hypernetwork_use_dropout,
+                new_hypernetwork_dropout_structure
+            ],
+            outputs=[
+                train_hypernetwork_name,
+                ti_output,
+                ti_outcome,
+            ]
+        )
+
+        run_preprocess.click(
+            fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]),
+            _js="start_training_textual_inversion",
+            inputs=[
+                process_src,
+                process_dst,
+                process_width,
+                process_height,
+                preprocess_txt_action,
+                process_flip,
+                process_split,
+                process_caption,
+                process_caption_deepbooru,
+                process_split_threshold,
+                process_overlap_ratio,
+                process_focal_crop,
+                process_focal_crop_face_weight,
+                process_focal_crop_entropy_weight,
+                process_focal_crop_edges_weight,
+                process_focal_crop_debug,
+            ],
+            outputs=[
+                ti_output,
+                ti_outcome,
+            ],
+        )
+
+        train_embedding.click(
+            fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.train_embedding, extra_outputs=[gr.update()]),
+            _js="start_training_textual_inversion",
+            inputs=[
+                train_embedding_name,
+                embedding_learn_rate,
+                batch_size,
+                gradient_step,
+                dataset_directory,
+                log_directory,
+                training_width,
+                training_height,
+                varsize,
+                steps,
+                clip_grad_mode,
+                clip_grad_value,
+                shuffle_tags,
+                tag_drop_out,
+                latent_sampling_method,
+                create_image_every,
+                save_embedding_every,
+                template_file,
+                save_image_with_stored_embedding,
+                preview_from_txt2img,
+                *txt2img_preview_params,
+            ],
+            outputs=[
+                ti_output,
+                ti_outcome,
+            ]
+        )
+
+        train_hypernetwork.click(
+            fn=wrap_gradio_gpu_call(modules.hypernetworks.ui.train_hypernetwork, extra_outputs=[gr.update()]),
+            _js="start_training_textual_inversion",
+            inputs=[
+                train_hypernetwork_name,
+                hypernetwork_learn_rate,
+                batch_size,
+                gradient_step,
+                dataset_directory,
+                log_directory,
+                training_width,
+                training_height,
+                varsize,
+                steps,
+                clip_grad_mode,
+                clip_grad_value,
+                shuffle_tags,
+                tag_drop_out,
+                latent_sampling_method,
+                create_image_every,
+                save_embedding_every,
+                template_file,
+                preview_from_txt2img,
+                *txt2img_preview_params,
+            ],
+            outputs=[
+                ti_output,
+                ti_outcome,
+            ]
+        )
+
+        interrupt_training.click(
+            fn=lambda: shared.state.interrupt(),
+            inputs=[],
+            outputs=[],
+        )
+
+        interrupt_preprocessing.click(
+            fn=lambda: shared.state.interrupt(),
+            inputs=[],
+            outputs=[],
+        )
+
+    def create_setting_component(key, is_quicksettings=False):
+        def fun():
+            return opts.data[key] if key in opts.data else opts.data_labels[key].default
+
+        info = opts.data_labels[key]
+        t = type(info.default)
+
+        args = info.component_args() if callable(info.component_args) else info.component_args
+
+        if info.component is not None:
+            comp = info.component
+        elif t == str:
+            comp = gr.Textbox
+        elif t == int:
+            comp = gr.Number
+        elif t == bool:
+            comp = gr.Checkbox
+        else:
+            raise Exception(f'bad options item type: {str(t)} for key {key}')
+
+        elem_id = "setting_"+key
+
+        if info.refresh is not None:
+            if is_quicksettings:
+                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 FormRow():
+                    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 {}))
+
+        return res
+
+    components = []
+    component_dict = {}
+
+    script_callbacks.ui_settings_callback()
+    opts.reorder()
+
+    def run_settings(*args):
+        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__}"
+
+        for key, value, comp in zip(opts.data_labels.keys(), args, components):
+            if comp == dummy_component:
+                continue
+
+            if opts.set(key, value):
+                changed.append(key)
+
+        try:
+            opts.save(shared.config_filename)
+        except RuntimeError:
+            return opts.dumpjson(), f'{len(changed)} settings changed without save: {", ".join(changed)}.'
+        return opts.dumpjson(), f'{len(changed)} settings changed{": " if len(changed) > 0 else ""}{", ".join(changed)}.'
+
+    def run_settings_single(value, key):
+        if not opts.same_type(value, opts.data_labels[key].default):
+            return gr.update(visible=True), opts.dumpjson()
+
+        if not opts.set(key, value):
+            return gr.update(value=getattr(opts, key)), opts.dumpjson()
+
+        opts.save(shared.config_filename)
+
+        return gr.update(value=value), opts.dumpjson()
+
+    with gr.Blocks(analytics_enabled=False) as settings_interface:
+        with gr.Row():
+            with gr.Column(scale=6):
+                settings_submit = gr.Button(value="Apply settings", variant='primary', elem_id="settings_submit")
+            with gr.Column():
+                restart_gradio = gr.Button(value='Reload UI', variant='primary', elem_id="settings_restart_gradio")
+
+        result = gr.HTML(elem_id="settings_result")
+
+        quicksettings_names = [x.strip() for x in opts.quicksettings.split(",")]
+        quicksettings_names = {x: i for i, x in enumerate(quicksettings_names) if x != 'quicksettings'}
+
+        quicksettings_list = []
+
+        previous_section = None
+        current_tab = None
+        with gr.Tabs(elem_id="settings"):
+            for i, (k, item) in enumerate(opts.data_labels.items()):
+                section_must_be_skipped = item.section[0] is None
+
+                if previous_section != item.section and not section_must_be_skipped:
+                    elem_id, text = item.section
+
+                    if current_tab is not None:
+                        current_tab.__exit__()
+
+                    current_tab = gr.TabItem(elem_id="settings_{}".format(elem_id), label=text)
+                    current_tab.__enter__()
+
+                    previous_section = item.section
+
+                if k in quicksettings_names and not shared.cmd_opts.freeze_settings:
+                    quicksettings_list.append((i, k, item))
+                    components.append(dummy_component)
+                elif section_must_be_skipped:
+                    components.append(dummy_component)
+                else:
+                    component = create_setting_component(k)
+                    component_dict[k] = component
+                    components.append(component)
+
+            if current_tab is not None:
+                current_tab.__exit__()
+
+            with gr.TabItem("Actions"):
+                request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications")
+                download_localization = gr.Button(value='Download localization template', elem_id="download_localization")
+                reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary', elem_id="settings_reload_script_bodies")
+
+            if os.path.exists("html/licenses.html"):
+                with open("html/licenses.html", encoding="utf8") as file:
+                    with gr.TabItem("Licenses"):
+                        gr.HTML(file.read(), elem_id="licenses")
+
+            gr.Button(value="Show all pages", elem_id="settings_show_all_pages")
+
+        request_notifications.click(
+            fn=lambda: None,
+            inputs=[],
+            outputs=[],
+            _js='function(){}'
+        )
+
+        download_localization.click(
+            fn=lambda: None,
+            inputs=[],
+            outputs=[],
+            _js='download_localization'
+        )
+
+        def reload_scripts():
+            modules.scripts.reload_script_body_only()
+            reload_javascript()  # need to refresh the html page
+
+        reload_script_bodies.click(
+            fn=reload_scripts,
+            inputs=[],
+            outputs=[]
+        )
+
+        def request_restart():
+            shared.state.interrupt()
+            shared.state.need_restart = True
+
+        restart_gradio.click(
+            fn=request_restart,
+            _js='restart_reload',
+            inputs=[],
+            outputs=[],
+        )
+
+    interfaces = [
+        (txt2img_interface, "txt2img", "txt2img"),
+        (img2img_interface, "img2img", "img2img"),
+        (extras_interface, "Extras", "extras"),
+        (pnginfo_interface, "PNG Info", "pnginfo"),
+        (modelmerger_interface, "Checkpoint Merger", "modelmerger"),
+        (train_interface, "Train", "ti"),
+    ]
+
+    css = ""
+
+    for cssfile in modules.scripts.list_files_with_name("style.css"):
+        if not os.path.isfile(cssfile):
+            continue
+
+        with open(cssfile, "r", encoding="utf8") as file:
+            css += file.read() + "\n"
+
+    if os.path.exists(os.path.join(script_path, "user.css")):
+        with open(os.path.join(script_path, "user.css"), "r", encoding="utf8") as file:
+            css += file.read() + "\n"
+
+    if not cmd_opts.no_progressbar_hiding:
+        css += css_hide_progressbar
+
+    interfaces += script_callbacks.ui_tabs_callback()
+    interfaces += [(settings_interface, "Settings", "settings")]
+
+    extensions_interface = ui_extensions.create_ui()
+    interfaces += [(extensions_interface, "Extensions", "extensions")]
+
+    with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion") as demo:
+        with gr.Row(elem_id="quicksettings"):
+            for i, k, item in sorted(quicksettings_list, key=lambda x: quicksettings_names.get(x[1], x[0])):
+                component = create_setting_component(k, is_quicksettings=True)
+                component_dict[k] = component
+
+        parameters_copypaste.integrate_settings_paste_fields(component_dict)
+        parameters_copypaste.run_bind()
+
+        with gr.Tabs(elem_id="tabs") as tabs:
+            for interface, label, ifid in interfaces:
+                with gr.TabItem(label, id=ifid, elem_id='tab_' + ifid):
+                    interface.render()
+
+        if os.path.exists(os.path.join(script_path, "notification.mp3")):
+            audio_notification = gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False)
+
+        if os.path.exists("html/footer.html"):
+            with open("html/footer.html", encoding="utf8") as file:
+                footer = file.read()
+                footer = footer.format(versions=versions_html())
+                gr.HTML(footer, elem_id="footer")
+
+        text_settings = gr.Textbox(elem_id="settings_json", value=lambda: opts.dumpjson(), visible=False)
+        settings_submit.click(
+            fn=wrap_gradio_call(run_settings, extra_outputs=[gr.update()]),
+            inputs=components,
+            outputs=[text_settings, result],
+        )
+
+        for i, k, item in quicksettings_list:
+            component = component_dict[k]
+
+            component.change(
+                fn=lambda value, k=k: run_settings_single(value, key=k),
+                inputs=[component],
+                outputs=[component, text_settings],
+            )
+
+        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)
+            except Exception as e:
+                print("Error loading/saving model file:", file=sys.stderr)
+                print(traceback.format_exc(), file=sys.stderr)
+                modules.sd_models.list_models()  # to remove the potentially missing models from the list
+                return [f"Error merging checkpoints: {e}"] + [gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(4)]
+            return results
+
+        modelmerger_merge.click(
+            fn=modelmerger,
+            inputs=[
+                primary_model_name,
+                secondary_model_name,
+                tertiary_model_name,
+                interp_method,
+                interp_amount,
+                save_as_half,
+                custom_name,
+                checkpoint_format,
+            ],
+            outputs=[
+                submit_result,
+                primary_model_name,
+                secondary_model_name,
+                tertiary_model_name,
+                component_dict['sd_model_checkpoint'],
+            ]
+        )
+
+    ui_config_file = cmd_opts.ui_config_file
+    ui_settings = {}
+    settings_count = len(ui_settings)
+    error_loading = False
+
+    try:
+        if os.path.exists(ui_config_file):
+            with open(ui_config_file, "r", encoding="utf8") as file:
+                ui_settings = json.load(file)
+    except Exception:
+        error_loading = True
+        print("Error loading settings:", file=sys.stderr)
+        print(traceback.format_exc(), file=sys.stderr)
+
+    def loadsave(path, x):
+        def apply_field(obj, field, condition=None, init_field=None):
+            key = path + "/" + field
+
+            if getattr(obj, 'custom_script_source', None) is not None:
+              key = 'customscript/' + obj.custom_script_source + '/' + key
+
+            if getattr(obj, 'do_not_save_to_config', False):
+                return
+
+            saved_value = ui_settings.get(key, None)
+            if saved_value is None:
+                ui_settings[key] = getattr(obj, field)
+            elif condition and not condition(saved_value):
+                print(f'Warning: Bad ui setting value: {key}: {saved_value}; Default value "{getattr(obj, field)}" will be used instead.')
+            else:
+                setattr(obj, field, saved_value)
+                if init_field is not None:
+                    init_field(saved_value)
+
+        if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number, gr.Dropdown] and x.visible:
+            apply_field(x, 'visible')
+
+        if type(x) == gr.Slider:
+            apply_field(x, 'value')
+            apply_field(x, 'minimum')
+            apply_field(x, 'maximum')
+            apply_field(x, 'step')
+
+        if type(x) == gr.Radio:
+            apply_field(x, 'value', lambda val: val in x.choices)
+
+        if type(x) == gr.Checkbox:
+            apply_field(x, 'value')
+
+        if type(x) == gr.Textbox:
+            apply_field(x, 'value')
+
+        if type(x) == gr.Number:
+            apply_field(x, 'value')
+
+        if type(x) == gr.Dropdown:
+            apply_field(x, 'value', lambda val: val in x.choices, getattr(x, 'init_field', None))
+
+    visit(txt2img_interface, loadsave, "txt2img")
+    visit(img2img_interface, loadsave, "img2img")
+    visit(extras_interface, loadsave, "extras")
+    visit(modelmerger_interface, loadsave, "modelmerger")
+    visit(train_interface, loadsave, "train")
+
+    if not error_loading and (not os.path.exists(ui_config_file) or settings_count != len(ui_settings)):
+        with open(ui_config_file, "w", encoding="utf8") as file:
+            json.dump(ui_settings, file, indent=4)
+
+    return demo
+
+
+def reload_javascript():
+    with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile:
+        javascript = f'<script>{jsfile.read()}</script>'
+
+    scripts_list = modules.scripts.list_scripts("javascript", ".js")
+
+    for basedir, filename, path in scripts_list:
+        with open(path, "r", encoding="utf8") as jsfile:
+            javascript += f"\n<!-- {filename} --><script>{jsfile.read()}</script>"
+
+    if cmd_opts.theme is not None:
+        javascript += f"\n<script>set_theme('{cmd_opts.theme}');</script>\n"
+
+    javascript += f"\n<script>{localization.localization_js(shared.opts.localization)}</script>"
+
+    def template_response(*args, **kwargs):
+        res = shared.GradioTemplateResponseOriginal(*args, **kwargs)
+        res.body = res.body.replace(
+            b'</head>', f'{javascript}</head>'.encode("utf8"))
+        res.init_headers()
+        return res
+
+    gradio.routes.templates.TemplateResponse = template_response
+
+
+if not hasattr(shared, 'GradioTemplateResponseOriginal'):
+    shared.GradioTemplateResponseOriginal = gradio.routes.templates.TemplateResponse
+
+
+def versions_html():
+    import torch
+    import launch
+
+    python_version = ".".join([str(x) for x in sys.version_info[0:3]])
+    commit = launch.commit_hash()
+    short_commit = commit[0:8]
+
+    if shared.xformers_available:
+        import xformers
+        xformers_version = xformers.__version__
+    else:
+        xformers_version = "N/A"
+
+    return f"""
+python: <span title="{sys.version}">{python_version}</span>
+ • 
+torch: {torch.__version__}
+ • 
+xformers: {xformers_version}
+ • 
+gradio: {gr.__version__}
+ • 
+commit: <a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui/commit/{commit}">{short_commit}</a>
+"""
-- 
cgit v1.2.3


From ef75c980536471c0729a2319440e3083cd57a4f0 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 10 Jan 2023 12:29:45 +0300
Subject: Split history ui.py to ui_progress.py

---
 modules/ui.py          |   94 +--
 modules/ui_progress.py | 1839 +-----------------------------------------------
 2 files changed, 9 insertions(+), 1924 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index 9b9081b5..3c458ce8 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -162,79 +162,6 @@ def save_files(js_data, images, do_make_zip, index):
     return gr.File.update(value=fullfns, visible=True), plaintext_to_html(f"Saved: {filenames[0]}")
 
 
-def calc_time_left(progress, threshold, label, force_display, show_eta):
-    if progress == 0:
-        return ""
-    else:
-        time_since_start = time.time() - shared.state.time_start
-        eta = (time_since_start/progress)
-        eta_relative = eta-time_since_start
-        if (eta_relative > threshold and show_eta) or force_display:
-            if eta_relative > 3600:
-                return label + time.strftime('%H:%M:%S', time.gmtime(eta_relative))
-            elif eta_relative > 60:
-                return label + time.strftime('%M:%S',  time.gmtime(eta_relative))
-            else:
-                return label + time.strftime('%Ss',  time.gmtime(eta_relative))
-        else:
-            return ""
-
-
-def check_progress_call(id_part):
-    if shared.state.job_count == 0:
-        return "", gr_show(False), gr_show(False), gr_show(False)
-
-    progress = 0
-
-    if shared.state.job_count > 0:
-        progress += shared.state.job_no / shared.state.job_count
-    if shared.state.sampling_steps > 0:
-        progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps
-
-    # Show progress percentage and time left at the same moment, and base it also on steps done
-    show_eta = progress >= 0.01 or shared.state.sampling_step >= 10
-
-    time_left = calc_time_left(progress, 1, " ETA: ", shared.state.time_left_force_display, show_eta)
-    if time_left != "":
-        shared.state.time_left_force_display = True
-
-    progress = min(progress, 1)
-
-    progressbar = ""
-    if opts.show_progressbar:
-        progressbar = f"""<div class='progressDiv'><div class='progress' style="overflow:visible;width:{progress * 100}%;white-space:nowrap;">{"&nbsp;" * 2 + str(int(progress*100))+"%" + time_left if show_eta else ""}</div></div>"""
-
-    image = gr_show(False)
-    preview_visibility = gr_show(False)
-
-    if opts.show_progress_every_n_steps != 0:
-        shared.state.set_current_image()
-        image = shared.state.current_image
-
-        if image is None:
-            image = gr.update(value=None)
-        else:
-            preview_visibility = gr_show(True)
-
-    if shared.state.textinfo is not None:
-        textinfo_result = gr.HTML.update(value=shared.state.textinfo, visible=True)
-    else:
-        textinfo_result = gr_show(False)
-
-    return f"<span id='{id_part}_progress_span' style='display: none'>{time.time()}</span><p>{progressbar}</p>", preview_visibility, image, textinfo_result
-
-
-def check_progress_call_initial(id_part):
-    shared.state.job_count = -1
-    shared.state.current_latent = None
-    shared.state.current_image = None
-    shared.state.textinfo = None
-    shared.state.time_start = time.time()
-    shared.state.time_left_force_display = False
-
-    return check_progress_call(id_part)
-
-
 def visit(x, func, path=""):
     if hasattr(x, 'children'):
         for c in x.children:
@@ -456,25 +383,10 @@ def create_toprow(is_img2img):
     return prompt, prompt_style, negative_prompt, prompt_style2, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button
 
 
-def setup_progressbar(progressbar, preview, id_part, textinfo=None):
-    if textinfo is None:
-        textinfo = gr.HTML(visible=False)
+def setup_progressbar(*args, **kwargs):
+    import modules.ui_progress
 
-    check_progress = gr.Button('Check progress', elem_id=f"{id_part}_check_progress", visible=False)
-    check_progress.click(
-        fn=lambda: check_progress_call(id_part),
-        show_progress=False,
-        inputs=[],
-        outputs=[progressbar, preview, preview, textinfo],
-    )
-
-    check_progress_initial = gr.Button('Check progress (first)', elem_id=f"{id_part}_check_progress_initial", visible=False)
-    check_progress_initial.click(
-        fn=lambda: check_progress_call_initial(id_part),
-        show_progress=False,
-        inputs=[],
-        outputs=[progressbar, preview, preview, textinfo],
-    )
+    modules.ui_progress.setup_progressbar(*args, **kwargs)
 
 
 def apply_setting(key, value):
diff --git a/modules/ui_progress.py b/modules/ui_progress.py
index 9b9081b5..592fda55 100644
--- a/modules/ui_progress.py
+++ b/modules/ui_progress.py
@@ -1,165 +1,10 @@
-import html
-import json
-import math
-import mimetypes
-import os
-import platform
-import random
-import subprocess as sp
-import sys
-import tempfile
 import time
-import traceback
-from functools import partial, reduce
 
 import gradio as gr
-import gradio.routes
-import gradio.utils
-import numpy as np
-from PIL import Image, PngImagePlugin
-from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
 
-from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru
-from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
-from modules.paths import script_path
+from modules.shared import opts
 
-from modules.shared import opts, cmd_opts, restricted_opts
-
-import modules.codeformer_model
-import modules.generation_parameters_copypaste as parameters_copypaste
-import modules.gfpgan_model
-import modules.hypernetworks.ui
-import modules.scripts
 import modules.shared as shared
-import modules.styles
-import modules.textual_inversion.ui
-from modules import prompt_parser
-from modules.images import save_image
-from modules.sd_hijack import model_hijack
-from modules.sd_samplers import samplers, samplers_for_img2img
-from modules.textual_inversion import textual_inversion
-import modules.hypernetworks.ui
-from modules.generation_parameters_copypaste import image_from_url_text
-
-# this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI
-mimetypes.init()
-mimetypes.add_type('application/javascript', '.js')
-
-if not cmd_opts.share and not cmd_opts.listen:
-    # fix gradio phoning home
-    gradio.utils.version_check = lambda: None
-    gradio.utils.get_local_ip_address = lambda: '127.0.0.1'
-
-if cmd_opts.ngrok is not None:
-    import modules.ngrok as ngrok
-    print('ngrok authtoken detected, trying to connect...')
-    ngrok.connect(
-        cmd_opts.ngrok,
-        cmd_opts.port if cmd_opts.port is not None else 7860,
-        cmd_opts.ngrok_region
-        )
-
-
-def gr_show(visible=True):
-    return {"visible": visible, "__type__": "update"}
-
-
-sample_img2img = "assets/stable-samples/img2img/sketch-mountains-input.jpg"
-sample_img2img = sample_img2img if os.path.exists(sample_img2img) else None
-
-css_hide_progressbar = """
-.wrap .m-12 svg { display:none!important; }
-.wrap .m-12::before { content:"Loading..." }
-.wrap .z-20 svg { display:none!important; }
-.wrap .z-20::before { content:"Loading..." }
-.progress-bar { display:none!important; }
-.meta-text { display:none!important; }
-.meta-text-center { display:none!important; }
-"""
-
-# Using constants for these since the variation selector isn't visible.
-# Important that they exactly match script.js for tooltip to work.
-random_symbol = '\U0001f3b2\ufe0f'  # 🎲️
-reuse_symbol = '\u267b\ufe0f'  # ♻️
-paste_symbol = '\u2199\ufe0f'  # ↙
-folder_symbol = '\U0001f4c2'  # 📂
-refresh_symbol = '\U0001f504'  # 🔄
-save_style_symbol = '\U0001f4be'  # 💾
-apply_style_symbol = '\U0001f4cb'  # 📋
-clear_prompt_symbol = '\U0001F5D1'  # 🗑️
-
-
-def plaintext_to_html(text):
-    text = "<p>" + "<br>\n".join([f"{html.escape(x)}" for x in text.split('\n')]) + "</p>"
-    return text
-
-def send_gradio_gallery_to_image(x):
-    if len(x) == 0:
-        return None
-    return image_from_url_text(x[0])
-
-def save_files(js_data, images, do_make_zip, index):
-    import csv
-    filenames = []
-    fullfns = []
-
-    #quick dictionary to class object conversion. Its necessary due apply_filename_pattern requiring it
-    class MyObject:
-        def __init__(self, d=None):
-            if d is not None:
-                for key, value in d.items():
-                    setattr(self, key, value)
-
-    data = json.loads(js_data)
-
-    p = MyObject(data)
-    path = opts.outdir_save
-    save_to_dirs = opts.use_save_to_dirs_for_ui
-    extension: str = opts.samples_format
-    start_index = 0
-
-    if index > -1 and opts.save_selected_only and (index >= data["index_of_first_image"]):  # ensures we are looking at a specific non-grid picture, and we have save_selected_only
-
-        images = [images[index]]
-        start_index = index
-
-    os.makedirs(opts.outdir_save, exist_ok=True)
-
-    with open(os.path.join(opts.outdir_save, "log.csv"), "a", encoding="utf8", newline='') as file:
-        at_start = file.tell() == 0
-        writer = csv.writer(file)
-        if at_start:
-            writer.writerow(["prompt", "seed", "width", "height", "sampler", "cfgs", "steps", "filename", "negative_prompt"])
-
-        for image_index, filedata in enumerate(images, start_index):
-            image = image_from_url_text(filedata)
-
-            is_grid = image_index < p.index_of_first_image
-            i = 0 if is_grid else (image_index - p.index_of_first_image)
-
-            fullfn, txt_fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
-
-            filename = os.path.relpath(fullfn, path)
-            filenames.append(filename)
-            fullfns.append(fullfn)
-            if txt_fullfn:
-                filenames.append(os.path.basename(txt_fullfn))
-                fullfns.append(txt_fullfn)
-
-        writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler_name"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]])
-
-    # Make Zip
-    if do_make_zip:
-        zip_filepath = os.path.join(path, "images.zip")
-
-        from zipfile import ZipFile
-        with ZipFile(zip_filepath, "w") as zip_file:
-            for i in range(len(fullfns)):
-                with open(fullfns[i], mode="rb") as f:
-                    zip_file.writestr(filenames[i], f.read())
-        fullfns.insert(0, zip_filepath)
-
-    return gr.File.update(value=fullfns, visible=True), plaintext_to_html(f"Saved: {filenames[0]}")
 
 
 def calc_time_left(progress, threshold, label, force_display, show_eta):
@@ -182,7 +27,7 @@ def calc_time_left(progress, threshold, label, force_display, show_eta):
 
 def check_progress_call(id_part):
     if shared.state.job_count == 0:
-        return "", gr_show(False), gr_show(False), gr_show(False)
+        return "", gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
 
     progress = 0
 
@@ -204,8 +49,8 @@ def check_progress_call(id_part):
     if opts.show_progressbar:
         progressbar = f"""<div class='progressDiv'><div class='progress' style="overflow:visible;width:{progress * 100}%;white-space:nowrap;">{"&nbsp;" * 2 + str(int(progress*100))+"%" + time_left if show_eta else ""}</div></div>"""
 
-    image = gr_show(False)
-    preview_visibility = gr_show(False)
+    image = gr.update(visible=False)
+    preview_visibility = gr.update(visible=False)
 
     if opts.show_progress_every_n_steps != 0:
         shared.state.set_current_image()
@@ -214,12 +59,12 @@ def check_progress_call(id_part):
         if image is None:
             image = gr.update(value=None)
         else:
-            preview_visibility = gr_show(True)
+            preview_visibility = gr.update(visible=True)
 
     if shared.state.textinfo is not None:
         textinfo_result = gr.HTML.update(value=shared.state.textinfo, visible=True)
     else:
-        textinfo_result = gr_show(False)
+        textinfo_result = gr.update(visible=False)
 
     return f"<span id='{id_part}_progress_span' style='display: none'>{time.time()}</span><p>{progressbar}</p>", preview_visibility, image, textinfo_result
 
@@ -235,227 +80,6 @@ def check_progress_call_initial(id_part):
     return check_progress_call(id_part)
 
 
-def visit(x, func, path=""):
-    if hasattr(x, 'children'):
-        for c in x.children:
-            visit(c, func, path)
-    elif x.label is not None:
-        func(path + "/" + str(x.label), x)
-
-
-def add_style(name: str, prompt: str, negative_prompt: str):
-    if name is None:
-        return [gr_show() for x in range(4)]
-
-    style = modules.styles.PromptStyle(name, prompt, negative_prompt)
-    shared.prompt_styles.styles[style.name] = style
-    # Save all loaded prompt styles: this allows us to update the storage format in the future more easily, because we
-    # reserialize all styles every time we save them
-    shared.prompt_styles.save_styles(shared.styles_filename)
-
-    return [gr.Dropdown.update(visible=True, choices=list(shared.prompt_styles.styles)) for _ in range(4)]
-
-
-def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resize_y):
-    from modules import processing, devices
-
-    if not enable:
-        return ""
-
-    p = processing.StableDiffusionProcessingTxt2Img(width=width, height=height, enable_hr=True, hr_scale=hr_scale, hr_resize_x=hr_resize_x, hr_resize_y=hr_resize_y)
-
-    with devices.autocast():
-        p.init([""], [0], [0])
-
-    return f"resize: from <span class='resolution'>{p.width}x{p.height}</span> to <span class='resolution'>{p.hr_resize_x or p.hr_upscale_to_x}x{p.hr_resize_y or p.hr_upscale_to_y}</span>"
-
-
-def apply_styles(prompt, prompt_neg, style1_name, style2_name):
-    prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, [style1_name, style2_name])
-    prompt_neg = shared.prompt_styles.apply_negative_styles_to_prompt(prompt_neg, [style1_name, style2_name])
-
-    return [gr.Textbox.update(value=prompt), gr.Textbox.update(value=prompt_neg), gr.Dropdown.update(value="None"), gr.Dropdown.update(value="None")]
-
-
-def interrogate(image):
-    prompt = shared.interrogator.interrogate(image.convert("RGB"))
-
-    return gr_show(True) if prompt is None else prompt
-
-
-def interrogate_deepbooru(image):
-    prompt = deepbooru.model.tag(image)
-    return gr_show(True) if prompt is None else prompt
-
-
-def create_seed_inputs(target_interface):
-    with FormRow(elem_id=target_interface + '_seed_row'):
-        seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1, elem_id=target_interface + '_seed')
-        seed.style(container=False)
-        random_seed = gr.Button(random_symbol, elem_id=target_interface + '_random_seed')
-        reuse_seed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_seed')
-
-        with gr.Group(elem_id=target_interface + '_subseed_show_box'):
-            seed_checkbox = gr.Checkbox(label='Extra', elem_id=target_interface + '_subseed_show', value=False)
-
-    # Components to show/hide based on the 'Extra' checkbox
-    seed_extras = []
-
-    with FormRow(visible=False, elem_id=target_interface + '_subseed_row') as seed_extra_row_1:
-        seed_extras.append(seed_extra_row_1)
-        subseed = gr.Number(label='Variation seed', value=-1, elem_id=target_interface + '_subseed')
-        subseed.style(container=False)
-        random_subseed = gr.Button(random_symbol, elem_id=target_interface + '_random_subseed')
-        reuse_subseed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_subseed')
-        subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=target_interface + '_subseed_strength')
-
-    with FormRow(visible=False) as seed_extra_row_2:
-        seed_extras.append(seed_extra_row_2)
-        seed_resize_from_w = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from width", value=0, elem_id=target_interface + '_seed_resize_from_w')
-        seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from height", value=0, elem_id=target_interface + '_seed_resize_from_h')
-
-    random_seed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[seed])
-    random_subseed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[subseed])
-
-    def change_visibility(show):
-        return {comp: gr_show(show) for comp in seed_extras}
-
-    seed_checkbox.change(change_visibility, show_progress=False, inputs=[seed_checkbox], outputs=seed_extras)
-
-    return seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox
-
-
-
-def connect_clear_prompt(button):
-    """Given clear button, prompt, and token_counter objects, setup clear prompt button click event"""
-    button.click(
-        _js="clear_prompt",
-        fn=None,
-        inputs=[],
-        outputs=[],
-    )
-
-
-def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: gr.Textbox, dummy_component, is_subseed):
-    """ Connects a 'reuse (sub)seed' button's click event so that it copies last used
-        (sub)seed value from generation info the to the seed field. If copying subseed and subseed strength
-        was 0, i.e. no variation seed was used, it copies the normal seed value instead."""
-    def copy_seed(gen_info_string: str, index):
-        res = -1
-
-        try:
-            gen_info = json.loads(gen_info_string)
-            index -= gen_info.get('index_of_first_image', 0)
-
-            if is_subseed and gen_info.get('subseed_strength', 0) > 0:
-                all_subseeds = gen_info.get('all_subseeds', [-1])
-                res = all_subseeds[index if 0 <= index < len(all_subseeds) else 0]
-            else:
-                all_seeds = gen_info.get('all_seeds', [-1])
-                res = all_seeds[index if 0 <= index < len(all_seeds) else 0]
-
-        except json.decoder.JSONDecodeError as e:
-            if gen_info_string != '':
-                print("Error parsing JSON generation info:", file=sys.stderr)
-                print(gen_info_string, file=sys.stderr)
-
-        return [res, gr_show(False)]
-
-    reuse_seed.click(
-        fn=copy_seed,
-        _js="(x, y) => [x, selected_gallery_index()]",
-        show_progress=False,
-        inputs=[generation_info, dummy_component],
-        outputs=[seed, dummy_component]
-    )
-
-
-def update_token_counter(text, steps):
-    try:
-        _, prompt_flat_list, _ = prompt_parser.get_multicond_prompt_list([text])
-        prompt_schedules = prompt_parser.get_learned_conditioning_prompt_schedules(prompt_flat_list, steps)
-
-    except Exception:
-        # a parsing error can happen here during typing, and we don't want to bother the user with
-        # messages related to it in console
-        prompt_schedules = [[[steps, text]]]
-
-    flat_prompts = reduce(lambda list1, list2: list1+list2, prompt_schedules)
-    prompts = [prompt_text for step, prompt_text in flat_prompts]
-    token_count, max_length = max([model_hijack.get_prompt_lengths(prompt) for prompt in prompts], key=lambda args: args[0])
-    style_class = ' class="red"' if (token_count > max_length) else ""
-    return f"<span {style_class}>{token_count}/{max_length}</span>"
-
-
-def create_toprow(is_img2img):
-    id_part = "img2img" if is_img2img else "txt2img"
-
-    with gr.Row(elem_id="toprow"):
-        with gr.Column(scale=6):
-            with gr.Row():
-                with gr.Column(scale=80):
-                    with gr.Row():
-                        prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=2,
-                            placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)"
-                        )
-
-            with gr.Row():
-                with gr.Column(scale=80):
-                    with gr.Row():
-                        negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2,
-                            placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)"
-                        )
-
-        with gr.Column(scale=1, elem_id="roll_col"):
-            paste = gr.Button(value=paste_symbol, elem_id="paste")
-            save_style = gr.Button(value=save_style_symbol, elem_id="style_create")
-            prompt_style_apply = gr.Button(value=apply_style_symbol, elem_id="style_apply")
-            clear_prompt_button = gr.Button(value=clear_prompt_symbol, elem_id=f"{id_part}_clear_prompt")
-            token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_token_counter")
-            token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button")
-
-            clear_prompt_button.click(
-                fn=lambda *x: x,
-                _js="confirm_clear_prompt",
-                inputs=[prompt, negative_prompt],
-                outputs=[prompt, negative_prompt],
-            )
-
-        button_interrogate = None
-        button_deepbooru = None
-        if is_img2img:
-            with gr.Column(scale=1, elem_id="interrogate_col"):
-                button_interrogate = gr.Button('Interrogate\nCLIP', elem_id="interrogate")
-                button_deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru")
-
-        with gr.Column(scale=1):
-            with gr.Row():
-                skip = gr.Button('Skip', elem_id=f"{id_part}_skip")
-                interrupt = gr.Button('Interrupt', elem_id=f"{id_part}_interrupt")
-                submit = gr.Button('Generate', elem_id=f"{id_part}_generate", variant='primary')
-
-                skip.click(
-                    fn=lambda: shared.state.skip(),
-                    inputs=[],
-                    outputs=[],
-                )
-
-                interrupt.click(
-                    fn=lambda: shared.state.interrupt(),
-                    inputs=[],
-                    outputs=[],
-                )
-
-            with gr.Row():
-                with gr.Column(scale=1, elem_id="style_pos_col"):
-                    prompt_style = gr.Dropdown(label="Style 1", elem_id=f"{id_part}_style_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())))
-
-                with gr.Column(scale=1, elem_id="style_neg_col"):
-                    prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())))
-
-    return prompt, prompt_style, negative_prompt, prompt_style2, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button
-
-
 def setup_progressbar(progressbar, preview, id_part, textinfo=None):
     if textinfo is None:
         textinfo = gr.HTML(visible=False)
@@ -475,1454 +99,3 @@ def setup_progressbar(progressbar, preview, id_part, textinfo=None):
         inputs=[],
         outputs=[progressbar, preview, preview, textinfo],
     )
-
-
-def apply_setting(key, value):
-    if value is None:
-        return gr.update()
-
-    if shared.cmd_opts.freeze_settings:
-        return gr.update()
-
-    # dont allow model to be swapped when model hash exists in prompt
-    if key == "sd_model_checkpoint" and opts.disable_weights_auto_swap:
-        return gr.update()
-
-    if key == "sd_model_checkpoint":
-        ckpt_info = sd_models.get_closet_checkpoint_match(value)
-
-        if ckpt_info is not None:
-            value = ckpt_info.title
-        else:
-            return gr.update()
-
-    comp_args = opts.data_labels[key].component_args
-    if comp_args and isinstance(comp_args, dict) and comp_args.get('visible') is False:
-        return
-
-    valtype = type(opts.data_labels[key].default)
-    oldval = opts.data.get(key, None)
-    opts.data[key] = valtype(value) if valtype != type(None) else value
-    if oldval != value and opts.data_labels[key].onchange is not None:
-        opts.data_labels[key].onchange()
-
-    opts.save(shared.config_filename)
-    return value
-
-
-def update_generation_info(args):
-    generation_info, html_info, img_index = args
-    try:
-        generation_info = json.loads(generation_info)
-        if img_index < 0 or img_index >= len(generation_info["infotexts"]):
-            return html_info
-        return plaintext_to_html(generation_info["infotexts"][img_index])
-    except Exception:
-        pass
-    # if the json parse or anything else fails, just return the old html_info
-    return html_info
-
-
-def create_refresh_button(refresh_component, refresh_method, refreshed_args, elem_id):
-    def refresh():
-        refresh_method()
-        args = refreshed_args() if callable(refreshed_args) else refreshed_args
-
-        for k, v in args.items():
-            setattr(refresh_component, k, v)
-
-        return gr.update(**(args or {}))
-
-    refresh_button = ToolButton(value=refresh_symbol, elem_id=elem_id)
-    refresh_button.click(
-        fn=refresh,
-        inputs=[],
-        outputs=[refresh_component]
-    )
-    return refresh_button
-
-
-def create_output_panel(tabname, outdir):
-    def open_folder(f):
-        if not os.path.exists(f):
-            print(f'Folder "{f}" does not exist. After you create an image, the folder will be created.')
-            return
-        elif not os.path.isdir(f):
-            print(f"""
-WARNING
-An open_folder request was made with an argument that is not a folder.
-This could be an error or a malicious attempt to run code on your computer.
-Requested path was: {f}
-""", file=sys.stderr)
-            return
-
-        if not shared.cmd_opts.hide_ui_dir_config:
-            path = os.path.normpath(f)
-            if platform.system() == "Windows":
-                os.startfile(path)
-            elif platform.system() == "Darwin":
-                sp.Popen(["open", path])
-            elif "microsoft-standard-WSL2" in platform.uname().release:
-                sp.Popen(["wsl-open", path])
-            else:
-                sp.Popen(["xdg-open", path])
-
-    with gr.Column(variant='panel'):
-            with gr.Group():
-                result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery").style(grid=4)
-
-            generation_info = None
-            with gr.Column():
-                with gr.Row(elem_id=f"image_buttons_{tabname}"):
-                    open_folder_button = gr.Button(folder_symbol, elem_id="hidden_element" if shared.cmd_opts.hide_ui_dir_config else f'open_folder_{tabname}')
-
-                    if tabname != "extras":
-                        save = gr.Button('Save', elem_id=f'save_{tabname}')
-                        save_zip = gr.Button('Zip', elem_id=f'save_zip_{tabname}')
-
-                    buttons = parameters_copypaste.create_buttons(["img2img", "inpaint", "extras"])
-
-                open_folder_button.click(
-                    fn=lambda: open_folder(opts.outdir_samples or outdir),
-                    inputs=[],
-                    outputs=[],
-                )
-
-                if tabname != "extras":
-                    with gr.Row():
-                        download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False, elem_id=f'download_files_{tabname}')
-
-                    with gr.Group():
-                        html_info = gr.HTML(elem_id=f'html_info_{tabname}')
-                        html_log = gr.HTML(elem_id=f'html_log_{tabname}')
-
-                        generation_info = gr.Textbox(visible=False, elem_id=f'generation_info_{tabname}')
-                        if tabname == 'txt2img' or tabname == 'img2img':
-                            generation_info_button = gr.Button(visible=False, elem_id=f"{tabname}_generation_info_button")
-                            generation_info_button.click(
-                                fn=update_generation_info,
-                                _js="(x, y) => [x, y, selected_gallery_index()]",
-                                inputs=[generation_info, html_info],
-                                outputs=[html_info],
-                                preprocess=False
-                            )
-
-                        save.click(
-                            fn=wrap_gradio_call(save_files),
-                            _js="(x, y, z, w) => [x, y, false, selected_gallery_index()]",
-                            inputs=[
-                                generation_info,
-                                result_gallery,
-                                html_info,
-                                html_info,
-                            ],
-                            outputs=[
-                                download_files,
-                                html_log,
-                            ]
-                        )
-
-                        save_zip.click(
-                            fn=wrap_gradio_call(save_files),
-                            _js="(x, y, z, w) => [x, y, true, selected_gallery_index()]",
-                            inputs=[
-                                generation_info,
-                                result_gallery,
-                                html_info,
-                                html_info,
-                            ],
-                            outputs=[
-                                download_files,
-                                html_log,
-                            ]
-                        )
-
-                else:
-                    html_info_x = gr.HTML(elem_id=f'html_info_x_{tabname}')
-                    html_info = gr.HTML(elem_id=f'html_info_{tabname}')
-                    html_log = gr.HTML(elem_id=f'html_log_{tabname}')
-
-                parameters_copypaste.bind_buttons(buttons, result_gallery, "txt2img" if tabname == "txt2img" else None)
-                return result_gallery, generation_info if tabname != "extras" else html_info_x, html_info, html_log
-
-
-def create_sampler_and_steps_selection(choices, tabname):
-    if opts.samplers_in_dropdown:
-        with FormRow(elem_id=f"sampler_selection_{tabname}"):
-            sampler_index = gr.Dropdown(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")
-            steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling steps", value=20)
-    else:
-        with FormGroup(elem_id=f"sampler_selection_{tabname}"):
-            steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling steps", value=20)
-            sampler_index = gr.Radio(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")
-
-    return steps, sampler_index
-
-
-def ordered_ui_categories():
-    user_order = {x.strip(): i for i, x in enumerate(shared.opts.ui_reorder.split(","))}
-
-    for i, category in sorted(enumerate(shared.ui_reorder_categories), key=lambda x: user_order.get(x[1], x[0] + 1000)):
-        yield category
-
-
-def create_ui():
-    import modules.img2img
-    import modules.txt2img
-
-    reload_javascript()
-
-    parameters_copypaste.reset()
-
-    modules.scripts.scripts_current = modules.scripts.scripts_txt2img
-    modules.scripts.scripts_txt2img.initialize_scripts(is_img2img=False)
-
-    with gr.Blocks(analytics_enabled=False) as txt2img_interface:
-        txt2img_prompt, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _,txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False)
-
-        dummy_component = gr.Label(visible=False)
-        txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False)
-
-        with gr.Row(elem_id='txt2img_progress_row'):
-            with gr.Column(scale=1):
-                pass
-
-            with gr.Column(scale=1):
-                progressbar = gr.HTML(elem_id="txt2img_progressbar")
-                txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False)
-                setup_progressbar(progressbar, txt2img_preview, 'txt2img')
-
-        with gr.Row().style(equal_height=False):
-            with gr.Column(variant='panel', elem_id="txt2img_settings"):
-                for category in ordered_ui_categories():
-                    if category == "sampler":
-                        steps, sampler_index = create_sampler_and_steps_selection(samplers, "txt2img")
-
-                    elif category == "dimensions":
-                        with FormRow():
-                            with gr.Column(elem_id="txt2img_column_size", scale=4):
-                                width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="txt2img_width")
-                                height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="txt2img_height")
-
-                            if opts.dimensions_and_batch_together:
-                                with gr.Column(elem_id="txt2img_column_batch"):
-                                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
-                                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
-
-                    elif category == "cfg":
-                        cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="txt2img_cfg_scale")
-
-                    elif category == "seed":
-                        seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('txt2img')
-
-                    elif category == "checkboxes":
-                        with FormRow(elem_id="txt2img_checkboxes"):
-                            restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="txt2img_restore_faces")
-                            tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling")
-                            enable_hr = gr.Checkbox(label='Hires. fix', value=False, elem_id="txt2img_enable_hr")
-                            hr_final_resolution = FormHTML(value="", elem_id="txtimg_hr_finalres", label="Upscaled resolution", interactive=False)
-
-                    elif category == "hires_fix":
-                        with FormGroup(visible=False, elem_id="txt2img_hires_fix") as hr_options:
-                            with FormRow(elem_id="txt2img_hires_fix_row1"):
-                                hr_upscaler = gr.Dropdown(label="Upscaler", elem_id="txt2img_hr_upscaler", choices=[*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]], value=shared.latent_upscale_default_mode)
-                                hr_second_pass_steps = gr.Slider(minimum=0, maximum=150, step=1, label='Hires steps', value=0, elem_id="txt2img_hires_steps")
-                                denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7, elem_id="txt2img_denoising_strength")
-
-                            with FormRow(elem_id="txt2img_hires_fix_row2"):
-                                hr_scale = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Upscale by", value=2.0, elem_id="txt2img_hr_scale")
-                                hr_resize_x = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize width to", value=0, elem_id="txt2img_hr_resize_x")
-                                hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y")
-
-                    elif category == "batch":
-                        if not opts.dimensions_and_batch_together:
-                            with FormRow(elem_id="txt2img_column_batch"):
-                                batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
-                                batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
-
-                    elif category == "scripts":
-                        with FormGroup(elem_id="txt2img_script_container"):
-                            custom_inputs = modules.scripts.scripts_txt2img.setup_ui()
-
-            hr_resolution_preview_inputs = [enable_hr, width, height, hr_scale, hr_resize_x, hr_resize_y]
-            for input in hr_resolution_preview_inputs:
-                input.change(
-                    fn=calc_resolution_hires,
-                    inputs=hr_resolution_preview_inputs,
-                    outputs=[hr_final_resolution],
-                    show_progress=False,
-                )
-                input.change(
-                    None,
-                    _js="onCalcResolutionHires",
-                    inputs=hr_resolution_preview_inputs,
-                    outputs=[],
-                    show_progress=False,
-                )
-
-            txt2img_gallery, generation_info, html_info, html_log = create_output_panel("txt2img", opts.outdir_txt2img_samples)
-            parameters_copypaste.bind_buttons({"txt2img": txt2img_paste}, None, txt2img_prompt)
-
-            connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
-            connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
-
-            txt2img_args = dict(
-                fn=wrap_gradio_gpu_call(modules.txt2img.txt2img, extra_outputs=[None, '', '']),
-                _js="submit",
-                inputs=[
-                    txt2img_prompt,
-                    txt2img_negative_prompt,
-                    txt2img_prompt_style,
-                    txt2img_prompt_style2,
-                    steps,
-                    sampler_index,
-                    restore_faces,
-                    tiling,
-                    batch_count,
-                    batch_size,
-                    cfg_scale,
-                    seed,
-                    subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox,
-                    height,
-                    width,
-                    enable_hr,
-                    denoising_strength,
-                    hr_scale,
-                    hr_upscaler,
-                    hr_second_pass_steps,
-                    hr_resize_x,
-                    hr_resize_y,
-                ] + custom_inputs,
-
-                outputs=[
-                    txt2img_gallery,
-                    generation_info,
-                    html_info,
-                    html_log,
-                ],
-                show_progress=False,
-            )
-
-            txt2img_prompt.submit(**txt2img_args)
-            submit.click(**txt2img_args)
-
-            txt_prompt_img.change(
-                fn=modules.images.image_data,
-                inputs=[
-                    txt_prompt_img
-                ],
-                outputs=[
-                    txt2img_prompt,
-                    txt_prompt_img
-                ]
-            )
-
-            enable_hr.change(
-                fn=lambda x: gr_show(x),
-                inputs=[enable_hr],
-                outputs=[hr_options],
-                show_progress = False,
-            )
-
-            txt2img_paste_fields = [
-                (txt2img_prompt, "Prompt"),
-                (txt2img_negative_prompt, "Negative prompt"),
-                (steps, "Steps"),
-                (sampler_index, "Sampler"),
-                (restore_faces, "Face restoration"),
-                (cfg_scale, "CFG scale"),
-                (seed, "Seed"),
-                (width, "Size-1"),
-                (height, "Size-2"),
-                (batch_size, "Batch size"),
-                (subseed, "Variation seed"),
-                (subseed_strength, "Variation seed strength"),
-                (seed_resize_from_w, "Seed resize from-1"),
-                (seed_resize_from_h, "Seed resize from-2"),
-                (denoising_strength, "Denoising strength"),
-                (enable_hr, lambda d: "Denoising strength" in d),
-                (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)),
-                (hr_scale, "Hires upscale"),
-                (hr_upscaler, "Hires upscaler"),
-                (hr_second_pass_steps, "Hires steps"),
-                (hr_resize_x, "Hires resize-1"),
-                (hr_resize_y, "Hires resize-2"),
-                *modules.scripts.scripts_txt2img.infotext_fields
-            ]
-            parameters_copypaste.add_paste_fields("txt2img", None, txt2img_paste_fields)
-
-            txt2img_preview_params = [
-                txt2img_prompt,
-                txt2img_negative_prompt,
-                steps,
-                sampler_index,
-                cfg_scale,
-                seed,
-                width,
-                height,
-            ]
-
-            token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[txt2img_prompt, steps], outputs=[token_counter])
-
-    modules.scripts.scripts_current = modules.scripts.scripts_img2img
-    modules.scripts.scripts_img2img.initialize_scripts(is_img2img=True)
-
-    with gr.Blocks(analytics_enabled=False) as img2img_interface:
-        img2img_prompt, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,token_counter, token_button = create_toprow(is_img2img=True)
-
-        with gr.Row(elem_id='img2img_progress_row'):
-            img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False)
-
-            with gr.Column(scale=1):
-                pass
-
-            with gr.Column(scale=1):
-                progressbar = gr.HTML(elem_id="img2img_progressbar")
-                img2img_preview = gr.Image(elem_id='img2img_preview', visible=False)
-                setup_progressbar(progressbar, img2img_preview, 'img2img')
-
-        with FormRow().style(equal_height=False):
-            with gr.Column(variant='panel', elem_id="img2img_settings"):
-
-                with gr.Tabs(elem_id="mode_img2img") as tabs_img2img_mode:
-                    with gr.TabItem('img2img', id='img2img', elem_id="img2img_img2img_tab"):
-                        init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_img2img_tool, image_mode="RGBA").style(height=480)
-
-                    with gr.TabItem('Inpaint', id='inpaint', elem_id="img2img_inpaint_tab"):
-                        init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_inpaint_tool, image_mode="RGBA").style(height=480)
-                        init_img_with_mask_orig = gr.State(None)
-
-                        use_color_sketch = cmd_opts.gradio_inpaint_tool == "color-sketch"
-                        if use_color_sketch:
-                            def update_orig(image, state):
-                                if image is not None:
-                                    same_size = state is not None and state.size == image.size
-                                    has_exact_match = np.any(np.all(np.array(image) == np.array(state), axis=-1))
-                                    edited = same_size and has_exact_match
-                                    return image if not edited or state is None else state
-
-                            init_img_with_mask.change(update_orig, [init_img_with_mask, init_img_with_mask_orig], init_img_with_mask_orig)
-
-                        init_img_inpaint = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_base")
-                        init_mask_inpaint = gr.Image(label="Mask", source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_mask")
-
-                        with FormRow():
-                            mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id="img2img_mask_blur")
-                            mask_alpha = gr.Slider(label="Mask transparency", interactive=use_color_sketch, visible=use_color_sketch, elem_id="img2img_mask_alpha")
-
-                        with FormRow():
-                            mask_mode = gr.Radio(label="Mask source", choices=["Draw mask", "Upload mask"], type="index", value="Draw mask", elem_id="mask_mode")
-                            inpainting_mask_invert = gr.Radio(label='Mask mode', choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index", elem_id="img2img_mask_mode")
-
-                        with FormRow():
-                            inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='original', type="index", elem_id="img2img_inpainting_fill")
-
-                        with FormRow():
-                            with gr.Column():
-                                inpaint_full_res = gr.Radio(label="Inpaint area", choices=["Whole picture", "Only masked"], type="index", value="Whole picture", elem_id="img2img_inpaint_full_res")
-
-                            with gr.Column(scale=4):
-                                inpaint_full_res_padding = gr.Slider(label='Only masked padding, pixels', minimum=0, maximum=256, step=4, value=32, elem_id="img2img_inpaint_full_res_padding")
-
-                    with gr.TabItem('Batch img2img', id='batch', elem_id="img2img_batch_tab"):
-                        hidden = '<br>Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else ''
-                        gr.HTML(f"<p class=\"text-gray-500\">Process images in a directory on the same machine where the server is running.<br>Use an empty output directory to save pictures normally instead of writing to the output directory.{hidden}</p>")
-                        img2img_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, elem_id="img2img_batch_input_dir")
-                        img2img_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, elem_id="img2img_batch_output_dir")
-
-                with FormRow():
-                    resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", choices=["Just resize", "Crop and resize", "Resize and fill", "Just resize (latent upscale)"], type="index", value="Just resize")
-
-                for category in ordered_ui_categories():
-                    if category == "sampler":
-                        steps, sampler_index = create_sampler_and_steps_selection(samplers_for_img2img, "img2img")
-
-                    elif category == "dimensions":
-                        with FormRow():
-                            with gr.Column(elem_id="img2img_column_size", scale=4):
-                                width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
-                                height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
-
-                            if opts.dimensions_and_batch_together:
-                                with gr.Column(elem_id="img2img_column_batch"):
-                                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
-                                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")
-
-                    elif category == "cfg":
-                        with FormGroup():
-                            cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="img2img_cfg_scale")
-                            denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75, elem_id="img2img_denoising_strength")
-
-                    elif category == "seed":
-                        seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('img2img')
-
-                    elif category == "checkboxes":
-                        with FormRow(elem_id="img2img_checkboxes"):
-                            restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="img2img_restore_faces")
-                            tiling = gr.Checkbox(label='Tiling', value=False, elem_id="img2img_tiling")
-
-                    elif category == "batch":
-                        if not opts.dimensions_and_batch_together:
-                            with FormRow(elem_id="img2img_column_batch"):
-                                batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
-                                batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")
-
-                    elif category == "scripts":
-                        with FormGroup(elem_id="img2img_script_container"):
-                            custom_inputs = modules.scripts.scripts_img2img.setup_ui()
-
-            img2img_gallery, generation_info, html_info, html_log = create_output_panel("img2img", opts.outdir_img2img_samples)
-            parameters_copypaste.bind_buttons({"img2img": img2img_paste}, None, img2img_prompt)
-
-            connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
-            connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
-
-            img2img_prompt_img.change(
-                fn=modules.images.image_data,
-                inputs=[
-                    img2img_prompt_img
-                ],
-                outputs=[
-                    img2img_prompt,
-                    img2img_prompt_img
-                ]
-            )
-
-            mask_mode.change(
-                lambda mode, img: {
-                    init_img_with_mask: gr_show(mode == 0),
-                    init_img_inpaint: gr_show(mode == 1),
-                    init_mask_inpaint: gr_show(mode == 1),
-                },
-                inputs=[mask_mode, init_img_with_mask],
-                outputs=[
-                    init_img_with_mask,
-                    init_img_inpaint,
-                    init_mask_inpaint,
-                ],
-            )
-
-            img2img_args = dict(
-                fn=wrap_gradio_gpu_call(modules.img2img.img2img, extra_outputs=[None, '', '']),
-                _js="submit_img2img",
-                inputs=[
-                    dummy_component,
-                    img2img_prompt,
-                    img2img_negative_prompt,
-                    img2img_prompt_style,
-                    img2img_prompt_style2,
-                    init_img,
-                    init_img_with_mask,
-                    init_img_with_mask_orig,
-                    init_img_inpaint,
-                    init_mask_inpaint,
-                    mask_mode,
-                    steps,
-                    sampler_index,
-                    mask_blur,
-                    mask_alpha,
-                    inpainting_fill,
-                    restore_faces,
-                    tiling,
-                    batch_count,
-                    batch_size,
-                    cfg_scale,
-                    denoising_strength,
-                    seed,
-                    subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox,
-                    height,
-                    width,
-                    resize_mode,
-                    inpaint_full_res,
-                    inpaint_full_res_padding,
-                    inpainting_mask_invert,
-                    img2img_batch_input_dir,
-                    img2img_batch_output_dir,
-                ] + custom_inputs,
-                outputs=[
-                    img2img_gallery,
-                    generation_info,
-                    html_info,
-                    html_log,
-                ],
-                show_progress=False,
-            )
-
-            img2img_prompt.submit(**img2img_args)
-            submit.click(**img2img_args)
-
-            img2img_interrogate.click(
-                fn=interrogate,
-                inputs=[init_img],
-                outputs=[img2img_prompt],
-            )
-
-            img2img_deepbooru.click(
-                fn=interrogate_deepbooru,
-                inputs=[init_img],
-                outputs=[img2img_prompt],
-            )
-
-            prompts = [(txt2img_prompt, txt2img_negative_prompt), (img2img_prompt, img2img_negative_prompt)]
-            style_dropdowns = [(txt2img_prompt_style, txt2img_prompt_style2), (img2img_prompt_style, img2img_prompt_style2)]
-            style_js_funcs = ["update_txt2img_tokens", "update_img2img_tokens"]
-
-            for button, (prompt, negative_prompt) in zip([txt2img_save_style, img2img_save_style], prompts):
-                button.click(
-                    fn=add_style,
-                    _js="ask_for_style_name",
-                    # Have to pass empty dummy component here, because the JavaScript and Python function have to accept
-                    # the same number of parameters, but we only know the style-name after the JavaScript prompt
-                    inputs=[dummy_component, prompt, negative_prompt],
-                    outputs=[txt2img_prompt_style, img2img_prompt_style, txt2img_prompt_style2, img2img_prompt_style2],
-                )
-
-            for button, (prompt, negative_prompt), (style1, style2), js_func in zip([txt2img_prompt_style_apply, img2img_prompt_style_apply], prompts, style_dropdowns, style_js_funcs):
-                button.click(
-                    fn=apply_styles,
-                    _js=js_func,
-                    inputs=[prompt, negative_prompt, style1, style2],
-                    outputs=[prompt, negative_prompt, style1, style2],
-                )
-
-            token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter])
-
-            img2img_paste_fields = [
-                (img2img_prompt, "Prompt"),
-                (img2img_negative_prompt, "Negative prompt"),
-                (steps, "Steps"),
-                (sampler_index, "Sampler"),
-                (restore_faces, "Face restoration"),
-                (cfg_scale, "CFG scale"),
-                (seed, "Seed"),
-                (width, "Size-1"),
-                (height, "Size-2"),
-                (batch_size, "Batch size"),
-                (subseed, "Variation seed"),
-                (subseed_strength, "Variation seed strength"),
-                (seed_resize_from_w, "Seed resize from-1"),
-                (seed_resize_from_h, "Seed resize from-2"),
-                (denoising_strength, "Denoising strength"),
-                (mask_blur, "Mask blur"),
-                *modules.scripts.scripts_img2img.infotext_fields
-            ]
-            parameters_copypaste.add_paste_fields("img2img", init_img, img2img_paste_fields)
-            parameters_copypaste.add_paste_fields("inpaint", init_img_with_mask, img2img_paste_fields)
-
-    modules.scripts.scripts_current = None
-
-    with gr.Blocks(analytics_enabled=False) as extras_interface:
-        with gr.Row().style(equal_height=False):
-            with gr.Column(variant='panel'):
-                with gr.Tabs(elem_id="mode_extras"):
-                    with gr.TabItem('Single Image', elem_id="extras_single_tab"):
-                        extras_image = gr.Image(label="Source", source="upload", interactive=True, type="pil", elem_id="extras_image")
-
-                    with gr.TabItem('Batch Process', elem_id="extras_batch_process_tab"):
-                        image_batch = gr.File(label="Batch Process", file_count="multiple", interactive=True, type="file", elem_id="extras_image_batch")
-
-                    with gr.TabItem('Batch from Directory', elem_id="extras_batch_directory_tab"):
-                        extras_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, placeholder="A directory on the same machine where the server is running.", elem_id="extras_batch_input_dir")
-                        extras_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, placeholder="Leave blank to save images to the default path.", elem_id="extras_batch_output_dir")
-                        show_extras_results = gr.Checkbox(label='Show result images', value=True, elem_id="extras_show_extras_results")
-
-                submit = gr.Button('Generate', elem_id="extras_generate", variant='primary')
-
-                with gr.Tabs(elem_id="extras_resize_mode"):
-                    with gr.TabItem('Scale by', elem_id="extras_scale_by_tab"):
-                        upscaling_resize = gr.Slider(minimum=1.0, maximum=8.0, step=0.05, label="Resize", value=4, elem_id="extras_upscaling_resize")
-                    with gr.TabItem('Scale to', elem_id="extras_scale_to_tab"):
-                        with gr.Group():
-                            with gr.Row():
-                                upscaling_resize_w = gr.Number(label="Width", value=512, precision=0, elem_id="extras_upscaling_resize_w")
-                                upscaling_resize_h = gr.Number(label="Height", value=512, precision=0, elem_id="extras_upscaling_resize_h")
-                            upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop")
-
-                with gr.Group():
-                    extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
-
-                with gr.Group():
-                    extras_upscaler_2 = gr.Radio(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
-                    extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=1, elem_id="extras_upscaler_2_visibility")
-
-                with gr.Group():
-                    gfpgan_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="GFPGAN visibility", value=0, interactive=modules.gfpgan_model.have_gfpgan, elem_id="extras_gfpgan_visibility")
-
-                with gr.Group():
-                    codeformer_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer visibility", value=0, interactive=modules.codeformer_model.have_codeformer, elem_id="extras_codeformer_visibility")
-                    codeformer_weight = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer weight (0 = maximum effect, 1 = minimum effect)", value=0, interactive=modules.codeformer_model.have_codeformer, elem_id="extras_codeformer_weight")
-
-                with gr.Group():
-                    upscale_before_face_fix = gr.Checkbox(label='Upscale Before Restoring Faces', value=False, elem_id="extras_upscale_before_face_fix")
-
-            result_images, html_info_x, html_info, html_log = create_output_panel("extras", opts.outdir_extras_samples)
-
-        submit.click(
-            fn=wrap_gradio_gpu_call(modules.extras.run_extras, extra_outputs=[None, '']),
-            _js="get_extras_tab_index",
-            inputs=[
-                dummy_component,
-                dummy_component,
-                extras_image,
-                image_batch,
-                extras_batch_input_dir,
-                extras_batch_output_dir,
-                show_extras_results,
-                gfpgan_visibility,
-                codeformer_visibility,
-                codeformer_weight,
-                upscaling_resize,
-                upscaling_resize_w,
-                upscaling_resize_h,
-                upscaling_crop,
-                extras_upscaler_1,
-                extras_upscaler_2,
-                extras_upscaler_2_visibility,
-                upscale_before_face_fix,
-            ],
-            outputs=[
-                result_images,
-                html_info_x,
-                html_info,
-            ]
-        )
-        parameters_copypaste.add_paste_fields("extras", extras_image, None)
-
-        extras_image.change(
-            fn=modules.extras.clear_cache,
-            inputs=[], outputs=[]
-        )
-
-    with gr.Blocks(analytics_enabled=False) as pnginfo_interface:
-        with gr.Row().style(equal_height=False):
-            with gr.Column(variant='panel'):
-                image = gr.Image(elem_id="pnginfo_image", label="Source", source="upload", interactive=True, type="pil")
-
-            with gr.Column(variant='panel'):
-                html = gr.HTML()
-                generation_info = gr.Textbox(visible=False, elem_id="pnginfo_generation_info")
-                html2 = gr.HTML()
-                with gr.Row():
-                    buttons = parameters_copypaste.create_buttons(["txt2img", "img2img", "inpaint", "extras"])
-                parameters_copypaste.bind_buttons(buttons, image, generation_info)
-
-        image.change(
-            fn=wrap_gradio_call(modules.extras.run_pnginfo),
-            inputs=[image],
-            outputs=[html, generation_info, html2],
-        )
-
-    with gr.Blocks(analytics_enabled=False) as modelmerger_interface:
-        with gr.Row().style(equal_height=False):
-            with gr.Column(variant='panel'):
-                gr.HTML(value="<p>A merger of the two checkpoints will be generated in your <b>checkpoint</b> directory.</p>")
-
-                with gr.Row():
-                    primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)")
-                    create_refresh_button(primary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_A")
-
-                    secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary model (B)")
-                    create_refresh_button(secondary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_B")
-
-                    tertiary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_tertiary_model_name", label="Tertiary model (C)")
-                    create_refresh_button(tertiary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_C")
-
-                custom_name = gr.Textbox(label="Custom Name (Optional)", elem_id="modelmerger_custom_name")
-                interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3, elem_id="modelmerger_interp_amount")
-                interp_method = gr.Radio(choices=["Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method", elem_id="modelmerger_interp_method")
-
-                with gr.Row():
-                    checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format", elem_id="modelmerger_checkpoint_format")
-                    save_as_half = gr.Checkbox(value=False, label="Save as float16", elem_id="modelmerger_save_as_half")
-
-                modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary')
-
-            with gr.Column(variant='panel'):
-                submit_result = gr.Textbox(elem_id="modelmerger_result", show_label=False)
-
-    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>")
-
-        with gr.Row().style(equal_height=False):
-            with gr.Tabs(elem_id="train_tabs"):
-
-                with gr.Tab(label="Create embedding"):
-                    new_embedding_name = gr.Textbox(label="Name", elem_id="train_new_embedding_name")
-                    initialization_text = gr.Textbox(label="Initialization text", value="*", elem_id="train_initialization_text")
-                    nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1, elem_id="train_nvpt")
-                    overwrite_old_embedding = gr.Checkbox(value=False, label="Overwrite Old Embedding", elem_id="train_overwrite_old_embedding")
-
-                    with gr.Row():
-                        with gr.Column(scale=3):
-                            gr.HTML(value="")
-
-                        with gr.Column():
-                            create_embedding = gr.Button(value="Create embedding", variant='primary', elem_id="train_create_embedding")
-
-                with gr.Tab(label="Create hypernetwork"):
-                    new_hypernetwork_name = gr.Textbox(label="Name", elem_id="train_new_hypernetwork_name")
-                    new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "1024", "320", "640", "1280"], elem_id="train_new_hypernetwork_sizes")
-                    new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'", elem_id="train_new_hypernetwork_layer_structure")
-                    new_hypernetwork_activation_func = gr.Dropdown(value="linear", label="Select activation function of hypernetwork. Recommended : Swish / Linear(none)", choices=modules.hypernetworks.ui.keys, elem_id="train_new_hypernetwork_activation_func")
-                    new_hypernetwork_initialization_option = gr.Dropdown(value = "Normal", label="Select Layer weights initialization. Recommended: Kaiming for relu-like, Xavier for sigmoid-like, Normal otherwise", choices=["Normal", "KaimingUniform", "KaimingNormal", "XavierUniform", "XavierNormal"], elem_id="train_new_hypernetwork_initialization_option")
-                    new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization", elem_id="train_new_hypernetwork_add_layer_norm")
-                    new_hypernetwork_use_dropout = gr.Checkbox(label="Use dropout", elem_id="train_new_hypernetwork_use_dropout")
-                    new_hypernetwork_dropout_structure = gr.Textbox("0, 0, 0", label="Enter hypernetwork Dropout structure (or empty). Recommended : 0~0.35 incrementing sequence: 0, 0.05, 0.15", placeholder="1st and last digit must be 0 and values should be between 0 and 1. ex:'0, 0.01, 0'")
-                    overwrite_old_hypernetwork = gr.Checkbox(value=False, label="Overwrite Old Hypernetwork", elem_id="train_overwrite_old_hypernetwork")
-
-                    with gr.Row():
-                        with gr.Column(scale=3):
-                            gr.HTML(value="")
-
-                        with gr.Column():
-                            create_hypernetwork = gr.Button(value="Create hypernetwork", variant='primary', elem_id="train_create_hypernetwork")
-
-                with gr.Tab(label="Preprocess images"):
-                    process_src = gr.Textbox(label='Source directory', elem_id="train_process_src")
-                    process_dst = gr.Textbox(label='Destination directory', elem_id="train_process_dst")
-                    process_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_process_width")
-                    process_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_process_height")
-                    preprocess_txt_action = gr.Dropdown(label='Existing Caption txt Action', value="ignore", choices=["ignore", "copy", "prepend", "append"], elem_id="train_preprocess_txt_action")
-
-                    with gr.Row():
-                        process_flip = gr.Checkbox(label='Create flipped copies', elem_id="train_process_flip")
-                        process_split = gr.Checkbox(label='Split oversized images', elem_id="train_process_split")
-                        process_focal_crop = gr.Checkbox(label='Auto focal point crop', elem_id="train_process_focal_crop")
-                        process_caption = gr.Checkbox(label='Use BLIP for caption', elem_id="train_process_caption")
-                        process_caption_deepbooru = gr.Checkbox(label='Use deepbooru for caption', visible=True, elem_id="train_process_caption_deepbooru")
-
-                    with gr.Row(visible=False) as process_split_extra_row:
-                        process_split_threshold = gr.Slider(label='Split image threshold', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_split_threshold")
-                        process_overlap_ratio = gr.Slider(label='Split image overlap ratio', value=0.2, minimum=0.0, maximum=0.9, step=0.05, elem_id="train_process_overlap_ratio")
-
-                    with gr.Row(visible=False) as process_focal_crop_row:
-                        process_focal_crop_face_weight = gr.Slider(label='Focal point face weight', value=0.9, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_face_weight")
-                        process_focal_crop_entropy_weight = gr.Slider(label='Focal point entropy weight', value=0.15, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_entropy_weight")
-                        process_focal_crop_edges_weight = gr.Slider(label='Focal point edges weight', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_edges_weight")
-                        process_focal_crop_debug = gr.Checkbox(label='Create debug image', elem_id="train_process_focal_crop_debug")
-
-                    with gr.Row():
-                        with gr.Column(scale=3):
-                            gr.HTML(value="")
-
-                        with gr.Column():
-                            with gr.Row():
-                                interrupt_preprocessing = gr.Button("Interrupt", elem_id="train_interrupt_preprocessing")
-                            run_preprocess = gr.Button(value="Preprocess", variant='primary', elem_id="train_run_preprocess")
-
-                    process_split.change(
-                        fn=lambda show: gr_show(show),
-                        inputs=[process_split],
-                        outputs=[process_split_extra_row],
-                    )
-
-                    process_focal_crop.change(
-                        fn=lambda show: gr_show(show),
-                        inputs=[process_focal_crop],
-                        outputs=[process_focal_crop_row],
-                    )
-
-                def get_textual_inversion_template_names():
-                    return sorted([x for x in textual_inversion.textual_inversion_templates])
-
-                with gr.Tab(label="Train"):
-                    gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images <a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\" style=\"font-weight:bold;\">[wiki]</a></p>")
-                    with FormRow():
-                        train_embedding_name = gr.Dropdown(label='Embedding', elem_id="train_embedding", choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
-                        create_refresh_button(train_embedding_name, sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings, lambda: {"choices": sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())}, "refresh_train_embedding_name")
-
-                        train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=[x for x in shared.hypernetworks.keys()])
-                        create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted([x for x in shared.hypernetworks.keys()])}, "refresh_train_hypernetwork_name")
-
-                    with FormRow():
-                        embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005", elem_id="train_embedding_learn_rate")
-                        hypernetwork_learn_rate = gr.Textbox(label='Hypernetwork Learning rate', placeholder="Hypernetwork Learning rate", value="0.00001", elem_id="train_hypernetwork_learn_rate")
-                    
-                    with FormRow():
-                        clip_grad_mode = gr.Dropdown(value="disabled", label="Gradient Clipping", choices=["disabled", "value", "norm"])
-                        clip_grad_value = gr.Textbox(placeholder="Gradient clip value", value="0.1", show_label=False)
-
-                    with FormRow():
-                        batch_size = gr.Number(label='Batch size', value=1, precision=0, elem_id="train_batch_size")
-                        gradient_step = gr.Number(label='Gradient accumulation steps', value=1, precision=0, elem_id="train_gradient_step")
-
-                    dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images", elem_id="train_dataset_directory")
-                    log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion", elem_id="train_log_directory")
-
-                    with FormRow():
-                        template_file = gr.Dropdown(label='Prompt template', value="style_filewords.txt", elem_id="train_template_file", choices=get_textual_inversion_template_names())
-                        create_refresh_button(template_file, textual_inversion.list_textual_inversion_templates, lambda: {"choices": get_textual_inversion_template_names()}, "refrsh_train_template_file")
-
-                    training_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_training_width")
-                    training_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_training_height")
-                    varsize = gr.Checkbox(label="Do not resize images", value=False, elem_id="train_varsize")
-                    steps = gr.Number(label='Max steps', value=100000, precision=0, elem_id="train_steps")
-
-                    with FormRow():
-                        create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0, elem_id="train_create_image_every")
-                        save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0, elem_id="train_save_embedding_every")
-
-                    save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True, elem_id="train_save_image_with_stored_embedding")
-                    preview_from_txt2img = gr.Checkbox(label='Read parameters (prompt, etc...) from txt2img tab when making previews', value=False, elem_id="train_preview_from_txt2img")
-
-                    shuffle_tags = gr.Checkbox(label="Shuffle tags by ',' when creating prompts.", value=False, elem_id="train_shuffle_tags")
-                    tag_drop_out = gr.Slider(minimum=0, maximum=1, step=0.1, label="Drop out tags when creating prompts.", value=0, elem_id="train_tag_drop_out")
-
-                    latent_sampling_method = gr.Radio(label='Choose latent sampling method', value="once", choices=['once', 'deterministic', 'random'], elem_id="train_latent_sampling_method")
-
-                    with gr.Row():
-                        train_embedding = gr.Button(value="Train Embedding", variant='primary', elem_id="train_train_embedding")
-                        interrupt_training = gr.Button(value="Interrupt", elem_id="train_interrupt_training")
-                        train_hypernetwork = gr.Button(value="Train Hypernetwork", variant='primary', elem_id="train_train_hypernetwork")
-
-                params = script_callbacks.UiTrainTabParams(txt2img_preview_params)
-
-                script_callbacks.ui_train_tabs_callback(params)
-
-            with gr.Column():
-                progressbar = gr.HTML(elem_id="ti_progressbar")
-                ti_output = gr.Text(elem_id="ti_output", value="", show_label=False)
-
-                ti_gallery = gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(grid=4)
-                ti_preview = gr.Image(elem_id='ti_preview', visible=False)
-                ti_progress = gr.HTML(elem_id="ti_progress", value="")
-                ti_outcome = gr.HTML(elem_id="ti_error", value="")
-                setup_progressbar(progressbar, ti_preview, 'ti', textinfo=ti_progress)
-
-        create_embedding.click(
-            fn=modules.textual_inversion.ui.create_embedding,
-            inputs=[
-                new_embedding_name,
-                initialization_text,
-                nvpt,
-                overwrite_old_embedding,
-            ],
-            outputs=[
-                train_embedding_name,
-                ti_output,
-                ti_outcome,
-            ]
-        )
-
-        create_hypernetwork.click(
-            fn=modules.hypernetworks.ui.create_hypernetwork,
-            inputs=[
-                new_hypernetwork_name,
-                new_hypernetwork_sizes,
-                overwrite_old_hypernetwork,
-                new_hypernetwork_layer_structure,
-                new_hypernetwork_activation_func,
-                new_hypernetwork_initialization_option,
-                new_hypernetwork_add_layer_norm,
-                new_hypernetwork_use_dropout,
-                new_hypernetwork_dropout_structure
-            ],
-            outputs=[
-                train_hypernetwork_name,
-                ti_output,
-                ti_outcome,
-            ]
-        )
-
-        run_preprocess.click(
-            fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]),
-            _js="start_training_textual_inversion",
-            inputs=[
-                process_src,
-                process_dst,
-                process_width,
-                process_height,
-                preprocess_txt_action,
-                process_flip,
-                process_split,
-                process_caption,
-                process_caption_deepbooru,
-                process_split_threshold,
-                process_overlap_ratio,
-                process_focal_crop,
-                process_focal_crop_face_weight,
-                process_focal_crop_entropy_weight,
-                process_focal_crop_edges_weight,
-                process_focal_crop_debug,
-            ],
-            outputs=[
-                ti_output,
-                ti_outcome,
-            ],
-        )
-
-        train_embedding.click(
-            fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.train_embedding, extra_outputs=[gr.update()]),
-            _js="start_training_textual_inversion",
-            inputs=[
-                train_embedding_name,
-                embedding_learn_rate,
-                batch_size,
-                gradient_step,
-                dataset_directory,
-                log_directory,
-                training_width,
-                training_height,
-                varsize,
-                steps,
-                clip_grad_mode,
-                clip_grad_value,
-                shuffle_tags,
-                tag_drop_out,
-                latent_sampling_method,
-                create_image_every,
-                save_embedding_every,
-                template_file,
-                save_image_with_stored_embedding,
-                preview_from_txt2img,
-                *txt2img_preview_params,
-            ],
-            outputs=[
-                ti_output,
-                ti_outcome,
-            ]
-        )
-
-        train_hypernetwork.click(
-            fn=wrap_gradio_gpu_call(modules.hypernetworks.ui.train_hypernetwork, extra_outputs=[gr.update()]),
-            _js="start_training_textual_inversion",
-            inputs=[
-                train_hypernetwork_name,
-                hypernetwork_learn_rate,
-                batch_size,
-                gradient_step,
-                dataset_directory,
-                log_directory,
-                training_width,
-                training_height,
-                varsize,
-                steps,
-                clip_grad_mode,
-                clip_grad_value,
-                shuffle_tags,
-                tag_drop_out,
-                latent_sampling_method,
-                create_image_every,
-                save_embedding_every,
-                template_file,
-                preview_from_txt2img,
-                *txt2img_preview_params,
-            ],
-            outputs=[
-                ti_output,
-                ti_outcome,
-            ]
-        )
-
-        interrupt_training.click(
-            fn=lambda: shared.state.interrupt(),
-            inputs=[],
-            outputs=[],
-        )
-
-        interrupt_preprocessing.click(
-            fn=lambda: shared.state.interrupt(),
-            inputs=[],
-            outputs=[],
-        )
-
-    def create_setting_component(key, is_quicksettings=False):
-        def fun():
-            return opts.data[key] if key in opts.data else opts.data_labels[key].default
-
-        info = opts.data_labels[key]
-        t = type(info.default)
-
-        args = info.component_args() if callable(info.component_args) else info.component_args
-
-        if info.component is not None:
-            comp = info.component
-        elif t == str:
-            comp = gr.Textbox
-        elif t == int:
-            comp = gr.Number
-        elif t == bool:
-            comp = gr.Checkbox
-        else:
-            raise Exception(f'bad options item type: {str(t)} for key {key}')
-
-        elem_id = "setting_"+key
-
-        if info.refresh is not None:
-            if is_quicksettings:
-                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 FormRow():
-                    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 {}))
-
-        return res
-
-    components = []
-    component_dict = {}
-
-    script_callbacks.ui_settings_callback()
-    opts.reorder()
-
-    def run_settings(*args):
-        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__}"
-
-        for key, value, comp in zip(opts.data_labels.keys(), args, components):
-            if comp == dummy_component:
-                continue
-
-            if opts.set(key, value):
-                changed.append(key)
-
-        try:
-            opts.save(shared.config_filename)
-        except RuntimeError:
-            return opts.dumpjson(), f'{len(changed)} settings changed without save: {", ".join(changed)}.'
-        return opts.dumpjson(), f'{len(changed)} settings changed{": " if len(changed) > 0 else ""}{", ".join(changed)}.'
-
-    def run_settings_single(value, key):
-        if not opts.same_type(value, opts.data_labels[key].default):
-            return gr.update(visible=True), opts.dumpjson()
-
-        if not opts.set(key, value):
-            return gr.update(value=getattr(opts, key)), opts.dumpjson()
-
-        opts.save(shared.config_filename)
-
-        return gr.update(value=value), opts.dumpjson()
-
-    with gr.Blocks(analytics_enabled=False) as settings_interface:
-        with gr.Row():
-            with gr.Column(scale=6):
-                settings_submit = gr.Button(value="Apply settings", variant='primary', elem_id="settings_submit")
-            with gr.Column():
-                restart_gradio = gr.Button(value='Reload UI', variant='primary', elem_id="settings_restart_gradio")
-
-        result = gr.HTML(elem_id="settings_result")
-
-        quicksettings_names = [x.strip() for x in opts.quicksettings.split(",")]
-        quicksettings_names = {x: i for i, x in enumerate(quicksettings_names) if x != 'quicksettings'}
-
-        quicksettings_list = []
-
-        previous_section = None
-        current_tab = None
-        with gr.Tabs(elem_id="settings"):
-            for i, (k, item) in enumerate(opts.data_labels.items()):
-                section_must_be_skipped = item.section[0] is None
-
-                if previous_section != item.section and not section_must_be_skipped:
-                    elem_id, text = item.section
-
-                    if current_tab is not None:
-                        current_tab.__exit__()
-
-                    current_tab = gr.TabItem(elem_id="settings_{}".format(elem_id), label=text)
-                    current_tab.__enter__()
-
-                    previous_section = item.section
-
-                if k in quicksettings_names and not shared.cmd_opts.freeze_settings:
-                    quicksettings_list.append((i, k, item))
-                    components.append(dummy_component)
-                elif section_must_be_skipped:
-                    components.append(dummy_component)
-                else:
-                    component = create_setting_component(k)
-                    component_dict[k] = component
-                    components.append(component)
-
-            if current_tab is not None:
-                current_tab.__exit__()
-
-            with gr.TabItem("Actions"):
-                request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications")
-                download_localization = gr.Button(value='Download localization template', elem_id="download_localization")
-                reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary', elem_id="settings_reload_script_bodies")
-
-            if os.path.exists("html/licenses.html"):
-                with open("html/licenses.html", encoding="utf8") as file:
-                    with gr.TabItem("Licenses"):
-                        gr.HTML(file.read(), elem_id="licenses")
-
-            gr.Button(value="Show all pages", elem_id="settings_show_all_pages")
-
-        request_notifications.click(
-            fn=lambda: None,
-            inputs=[],
-            outputs=[],
-            _js='function(){}'
-        )
-
-        download_localization.click(
-            fn=lambda: None,
-            inputs=[],
-            outputs=[],
-            _js='download_localization'
-        )
-
-        def reload_scripts():
-            modules.scripts.reload_script_body_only()
-            reload_javascript()  # need to refresh the html page
-
-        reload_script_bodies.click(
-            fn=reload_scripts,
-            inputs=[],
-            outputs=[]
-        )
-
-        def request_restart():
-            shared.state.interrupt()
-            shared.state.need_restart = True
-
-        restart_gradio.click(
-            fn=request_restart,
-            _js='restart_reload',
-            inputs=[],
-            outputs=[],
-        )
-
-    interfaces = [
-        (txt2img_interface, "txt2img", "txt2img"),
-        (img2img_interface, "img2img", "img2img"),
-        (extras_interface, "Extras", "extras"),
-        (pnginfo_interface, "PNG Info", "pnginfo"),
-        (modelmerger_interface, "Checkpoint Merger", "modelmerger"),
-        (train_interface, "Train", "ti"),
-    ]
-
-    css = ""
-
-    for cssfile in modules.scripts.list_files_with_name("style.css"):
-        if not os.path.isfile(cssfile):
-            continue
-
-        with open(cssfile, "r", encoding="utf8") as file:
-            css += file.read() + "\n"
-
-    if os.path.exists(os.path.join(script_path, "user.css")):
-        with open(os.path.join(script_path, "user.css"), "r", encoding="utf8") as file:
-            css += file.read() + "\n"
-
-    if not cmd_opts.no_progressbar_hiding:
-        css += css_hide_progressbar
-
-    interfaces += script_callbacks.ui_tabs_callback()
-    interfaces += [(settings_interface, "Settings", "settings")]
-
-    extensions_interface = ui_extensions.create_ui()
-    interfaces += [(extensions_interface, "Extensions", "extensions")]
-
-    with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion") as demo:
-        with gr.Row(elem_id="quicksettings"):
-            for i, k, item in sorted(quicksettings_list, key=lambda x: quicksettings_names.get(x[1], x[0])):
-                component = create_setting_component(k, is_quicksettings=True)
-                component_dict[k] = component
-
-        parameters_copypaste.integrate_settings_paste_fields(component_dict)
-        parameters_copypaste.run_bind()
-
-        with gr.Tabs(elem_id="tabs") as tabs:
-            for interface, label, ifid in interfaces:
-                with gr.TabItem(label, id=ifid, elem_id='tab_' + ifid):
-                    interface.render()
-
-        if os.path.exists(os.path.join(script_path, "notification.mp3")):
-            audio_notification = gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False)
-
-        if os.path.exists("html/footer.html"):
-            with open("html/footer.html", encoding="utf8") as file:
-                footer = file.read()
-                footer = footer.format(versions=versions_html())
-                gr.HTML(footer, elem_id="footer")
-
-        text_settings = gr.Textbox(elem_id="settings_json", value=lambda: opts.dumpjson(), visible=False)
-        settings_submit.click(
-            fn=wrap_gradio_call(run_settings, extra_outputs=[gr.update()]),
-            inputs=components,
-            outputs=[text_settings, result],
-        )
-
-        for i, k, item in quicksettings_list:
-            component = component_dict[k]
-
-            component.change(
-                fn=lambda value, k=k: run_settings_single(value, key=k),
-                inputs=[component],
-                outputs=[component, text_settings],
-            )
-
-        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)
-            except Exception as e:
-                print("Error loading/saving model file:", file=sys.stderr)
-                print(traceback.format_exc(), file=sys.stderr)
-                modules.sd_models.list_models()  # to remove the potentially missing models from the list
-                return [f"Error merging checkpoints: {e}"] + [gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(4)]
-            return results
-
-        modelmerger_merge.click(
-            fn=modelmerger,
-            inputs=[
-                primary_model_name,
-                secondary_model_name,
-                tertiary_model_name,
-                interp_method,
-                interp_amount,
-                save_as_half,
-                custom_name,
-                checkpoint_format,
-            ],
-            outputs=[
-                submit_result,
-                primary_model_name,
-                secondary_model_name,
-                tertiary_model_name,
-                component_dict['sd_model_checkpoint'],
-            ]
-        )
-
-    ui_config_file = cmd_opts.ui_config_file
-    ui_settings = {}
-    settings_count = len(ui_settings)
-    error_loading = False
-
-    try:
-        if os.path.exists(ui_config_file):
-            with open(ui_config_file, "r", encoding="utf8") as file:
-                ui_settings = json.load(file)
-    except Exception:
-        error_loading = True
-        print("Error loading settings:", file=sys.stderr)
-        print(traceback.format_exc(), file=sys.stderr)
-
-    def loadsave(path, x):
-        def apply_field(obj, field, condition=None, init_field=None):
-            key = path + "/" + field
-
-            if getattr(obj, 'custom_script_source', None) is not None:
-              key = 'customscript/' + obj.custom_script_source + '/' + key
-
-            if getattr(obj, 'do_not_save_to_config', False):
-                return
-
-            saved_value = ui_settings.get(key, None)
-            if saved_value is None:
-                ui_settings[key] = getattr(obj, field)
-            elif condition and not condition(saved_value):
-                print(f'Warning: Bad ui setting value: {key}: {saved_value}; Default value "{getattr(obj, field)}" will be used instead.')
-            else:
-                setattr(obj, field, saved_value)
-                if init_field is not None:
-                    init_field(saved_value)
-
-        if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number, gr.Dropdown] and x.visible:
-            apply_field(x, 'visible')
-
-        if type(x) == gr.Slider:
-            apply_field(x, 'value')
-            apply_field(x, 'minimum')
-            apply_field(x, 'maximum')
-            apply_field(x, 'step')
-
-        if type(x) == gr.Radio:
-            apply_field(x, 'value', lambda val: val in x.choices)
-
-        if type(x) == gr.Checkbox:
-            apply_field(x, 'value')
-
-        if type(x) == gr.Textbox:
-            apply_field(x, 'value')
-
-        if type(x) == gr.Number:
-            apply_field(x, 'value')
-
-        if type(x) == gr.Dropdown:
-            apply_field(x, 'value', lambda val: val in x.choices, getattr(x, 'init_field', None))
-
-    visit(txt2img_interface, loadsave, "txt2img")
-    visit(img2img_interface, loadsave, "img2img")
-    visit(extras_interface, loadsave, "extras")
-    visit(modelmerger_interface, loadsave, "modelmerger")
-    visit(train_interface, loadsave, "train")
-
-    if not error_loading and (not os.path.exists(ui_config_file) or settings_count != len(ui_settings)):
-        with open(ui_config_file, "w", encoding="utf8") as file:
-            json.dump(ui_settings, file, indent=4)
-
-    return demo
-
-
-def reload_javascript():
-    with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile:
-        javascript = f'<script>{jsfile.read()}</script>'
-
-    scripts_list = modules.scripts.list_scripts("javascript", ".js")
-
-    for basedir, filename, path in scripts_list:
-        with open(path, "r", encoding="utf8") as jsfile:
-            javascript += f"\n<!-- {filename} --><script>{jsfile.read()}</script>"
-
-    if cmd_opts.theme is not None:
-        javascript += f"\n<script>set_theme('{cmd_opts.theme}');</script>\n"
-
-    javascript += f"\n<script>{localization.localization_js(shared.opts.localization)}</script>"
-
-    def template_response(*args, **kwargs):
-        res = shared.GradioTemplateResponseOriginal(*args, **kwargs)
-        res.body = res.body.replace(
-            b'</head>', f'{javascript}</head>'.encode("utf8"))
-        res.init_headers()
-        return res
-
-    gradio.routes.templates.TemplateResponse = template_response
-
-
-if not hasattr(shared, 'GradioTemplateResponseOriginal'):
-    shared.GradioTemplateResponseOriginal = gradio.routes.templates.TemplateResponse
-
-
-def versions_html():
-    import torch
-    import launch
-
-    python_version = ".".join([str(x) for x in sys.version_info[0:3]])
-    commit = launch.commit_hash()
-    short_commit = commit[0:8]
-
-    if shared.xformers_available:
-        import xformers
-        xformers_version = xformers.__version__
-    else:
-        xformers_version = "N/A"
-
-    return f"""
-python: <span title="{sys.version}">{python_version}</span>
- • 
-torch: {torch.__version__}
- • 
-xformers: {xformers_version}
- • 
-gradio: {gr.__version__}
- • 
-commit: <a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui/commit/{commit}">{short_commit}</a>
-"""
-- 
cgit v1.2.3


From 954091697fce7a1b7997d5f3d73551f793f6bebc Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 11 Jan 2023 09:10:07 +0300
Subject: add an option to copy config from one of models in checkpoint merger

---
 modules/extras.py | 30 +++++++++++++++++++++++++++++-
 modules/ui.py     |  9 ++++++---
 2 files changed, 35 insertions(+), 4 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/extras.py b/modules/extras.py
index 7407bfe3..a03d558e 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -3,6 +3,7 @@ import math
 import os
 import sys
 import traceback
+import shutil
 
 import numpy as np
 from PIL import Image
@@ -248,7 +249,32 @@ def run_pnginfo(image):
     return '', geninfo, info
 
 
-def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format):
+def create_config(ckpt_result, config_source, a, b, c):
+    def config(x):
+        return sd_models.find_checkpoint_config(x) if x else None
+
+    if config_source == 0:
+        cfg = config(a) or config(b) or config(c)
+    elif config_source == 1:
+        cfg = config(b)
+    elif config_source == 2:
+        cfg = config(c)
+    else:
+        cfg = None
+
+    if cfg is None:
+        return
+
+    filename, _ = os.path.splitext(ckpt_result)
+    checkpoint_filename = filename + ".yaml"
+
+    print("Copying config:")
+    print("   from:", cfg)
+    print("     to:", checkpoint_filename)
+    shutil.copyfile(cfg, checkpoint_filename)
+
+
+def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format, config_source):
     shared.state.begin()
     shared.state.job = 'model-merge'
 
@@ -356,6 +382,8 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
 
     sd_models.list_models()
 
+    create_config(output_modelname, config_source, primary_model_info, secondary_model_info, tertiary_model_info)
+
     print("Checkpoint saved.")
     shared.state.textinfo = "Checkpoint saved to " + output_modelname
     shared.state.end()
diff --git a/modules/ui.py b/modules/ui.py
index 3c458ce8..82f5dd7c 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1129,7 +1129,7 @@ def create_ui():
             with gr.Column(variant='panel'):
                 gr.HTML(value="<p>A merger of the two checkpoints will be generated in your <b>checkpoint</b> directory.</p>")
 
-                with gr.Row():
+                with FormRow():
                     primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)")
                     create_refresh_button(primary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_A")
 
@@ -1143,11 +1143,13 @@ def create_ui():
                 interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3, elem_id="modelmerger_interp_amount")
                 interp_method = gr.Radio(choices=["Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method", elem_id="modelmerger_interp_method")
 
-                with gr.Row():
+                with FormRow():
                     checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format", elem_id="modelmerger_checkpoint_format")
                     save_as_half = gr.Checkbox(value=False, label="Save as float16", elem_id="modelmerger_save_as_half")
 
-                modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary')
+                config_source = gr.Radio(choices=["A, B or C", "B", "C", "Don't"], value="A, B or C", label="Copy config from", type="index", elem_id="modelmerger_config_method")
+
+                modelmerger_merge = gr.Button(elem_id="modelmerger_merge", value="Merge", variant='primary')
 
             with gr.Column(variant='panel'):
                 submit_result = gr.Textbox(elem_id="modelmerger_result", show_label=False)
@@ -1703,6 +1705,7 @@ def create_ui():
                 save_as_half,
                 custom_name,
                 checkpoint_format,
+                config_source,
             ],
             outputs=[
                 submit_result,
-- 
cgit v1.2.3


From 0b8911d883118daa54f7735c5b753b5575d9f943 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 11 Jan 2023 20:33:24 +0300
Subject: img2img UI rework: obsolete --gradio-img2img-tool
 --gradio-inpaint-tool and always show all tools each in own tab

---
 modules/img2img.py |  58 ++++++++++++++----------------
 modules/shared.py  |   4 +--
 modules/ui.py      | 103 +++++++++++++++++++++++++++--------------------------
 style.css          |   4 ++-
 4 files changed, 84 insertions(+), 85 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/img2img.py b/modules/img2img.py
index ca58b5d8..f62783c6 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -59,38 +59,34 @@ def process_batch(p, input_dir, output_dir, args):
                 processed_image.save(os.path.join(output_dir, filename))
 
 
-def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, init_img, init_img_with_mask, init_img_with_mask_orig, init_img_inpaint, init_mask_inpaint, mask_mode, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, *args):
-    is_inpaint = mode == 1
-    is_batch = mode == 2
-
-    if is_inpaint:
-        # Drawn mask
-        if mask_mode == 0:
-            is_mask_sketch = isinstance(init_img_with_mask, dict)
-            is_mask_paint = not is_mask_sketch
-            if is_mask_sketch:
-                # Sketch: mask iff. not transparent
-                image, mask = init_img_with_mask["image"], init_img_with_mask["mask"]
-                alpha_mask = ImageOps.invert(image.split()[-1]).convert('L').point(lambda x: 255 if x > 0 else 0, mode='1')
-                mask = ImageChops.lighter(alpha_mask, mask.convert('L')).convert('L')
-            else:
-                # Color-sketch: mask iff. painted over
-                image = init_img_with_mask
-                orig = init_img_with_mask_orig or init_img_with_mask
-                pred = np.any(np.array(image) != np.array(orig), axis=-1)
-                mask = Image.fromarray(pred.astype(np.uint8) * 255, "L")
-                mask = ImageEnhance.Brightness(mask).enhance(1 - mask_alpha / 100)
-                blur = ImageFilter.GaussianBlur(mask_blur)
-                image = Image.composite(image.filter(blur), orig, mask.filter(blur))
-
-            image = image.convert("RGB")
-        # Uploaded mask
-        else:
-            image = init_img_inpaint
-            mask = init_mask_inpaint
-    # No mask
+def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, *args):
+    is_batch = mode == 5
+
+    if mode == 0:  # img2img
+        image = init_img.convert("RGB")
+        mask = None
+    elif mode == 1:  # img2img sketch
+        image = sketch.convert("RGB")
+        mask = None
+    elif mode == 2:  # inpaint
+        image, mask = init_img_with_mask["image"], init_img_with_mask["mask"]
+        alpha_mask = ImageOps.invert(image.split()[-1]).convert('L').point(lambda x: 255 if x > 0 else 0, mode='1')
+        mask = ImageChops.lighter(alpha_mask, mask.convert('L')).convert('L')
+        image = image.convert("RGB")
+    elif mode == 3:  # inpaint sketch
+        image = inpaint_color_sketch
+        orig = inpaint_color_sketch_orig or inpaint_color_sketch
+        pred = np.any(np.array(image) != np.array(orig), axis=-1)
+        mask = Image.fromarray(pred.astype(np.uint8) * 255, "L")
+        mask = ImageEnhance.Brightness(mask).enhance(1 - mask_alpha / 100)
+        blur = ImageFilter.GaussianBlur(mask_blur)
+        image = Image.composite(image.filter(blur), orig, mask.filter(blur))
+        image = image.convert("RGB")
+    elif mode == 4:  # inpaint upload mask
+        image = init_img_inpaint
+        mask = init_mask_inpaint
     else:
-        image = init_img
+        image = None
         mask = None
 
     # Use the EXIF orientation of photos taken by smartphones.
diff --git a/modules/shared.py b/modules/shared.py
index 264264a6..1c964237 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -74,8 +74,8 @@ parser.add_argument("--freeze-settings", action='store_true', help="disable edit
 parser.add_argument("--ui-settings-file", type=str, help="filename to use for ui settings", default=os.path.join(script_path, 'config.json'))
 parser.add_argument("--gradio-debug",  action='store_true', help="launch gradio with --debug option")
 parser.add_argument("--gradio-auth", type=str, help='set gradio authentication like "username:password"; or comma-delimit multiple like "u1:p1,u2:p2,u3:p3"', default=None)
-parser.add_argument("--gradio-img2img-tool", type=str, help='gradio image uploader tool: can be either editor for ctopping, or color-sketch for drawing', choices=["color-sketch", "editor"], default="editor")
-parser.add_argument("--gradio-inpaint-tool", type=str, choices=["sketch", "color-sketch"], default="sketch", help="gradio inpainting editor: can be either sketch to only blur/noise the input, or color-sketch to paint over it")
+parser.add_argument("--gradio-img2img-tool", type=str, help='does not do anything')
+parser.add_argument("--gradio-inpaint-tool", type=str, help="does not do anything")
 parser.add_argument("--opt-channelslast", action='store_true', help="change memory type for stable diffusion to channels last")
 parser.add_argument("--styles-file", type=str, help="filename to use for styles", default=os.path.join(script_path, 'styles.csv'))
 parser.add_argument("--autolaunch", action='store_true', help="open the webui URL in the system's default browser upon launch", default=False)
diff --git a/modules/ui.py b/modules/ui.py
index 82f5dd7c..e86a624b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -795,53 +795,67 @@ def create_ui():
 
         with FormRow().style(equal_height=False):
             with gr.Column(variant='panel', elem_id="img2img_settings"):
+                with gr.Tabs(elem_id="mode_img2img"):
+                    with gr.TabItem('img2img', id='img2img', elem_id="img2img_img2img_tab") as tab_img2img:
+                        init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool="editor", image_mode="RGBA").style(height=480)
 
-                with gr.Tabs(elem_id="mode_img2img") as tabs_img2img_mode:
-                    with gr.TabItem('img2img', id='img2img', elem_id="img2img_img2img_tab"):
-                        init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_img2img_tool, image_mode="RGBA").style(height=480)
+                    with gr.TabItem('Sketch', id='img2img_sketch', elem_id="img2img_img2img_sketch_tab") as tab_sketch:
+                        sketch = gr.Image(label="Image for img2img", elem_id="img2img_sketch", show_label=False, source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA").style(height=480)
 
-                    with gr.TabItem('Inpaint', id='inpaint', elem_id="img2img_inpaint_tab"):
-                        init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_inpaint_tool, image_mode="RGBA").style(height=480)
-                        init_img_with_mask_orig = gr.State(None)
+                    with gr.TabItem('Inpaint', id='inpaint', elem_id="img2img_inpaint_tab") as tab_inpaint:
+                        init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", image_mode="RGBA").style(height=480)
 
-                        use_color_sketch = cmd_opts.gradio_inpaint_tool == "color-sketch"
-                        if use_color_sketch:
-                            def update_orig(image, state):
-                                if image is not None:
-                                    same_size = state is not None and state.size == image.size
-                                    has_exact_match = np.any(np.all(np.array(image) == np.array(state), axis=-1))
-                                    edited = same_size and has_exact_match
-                                    return image if not edited or state is None else state
+                    with gr.TabItem('Inpaint sketch', id='inpaint_sketch', elem_id="img2img_inpaint_sketch_tab") as tab_inpaint_color:
+                        inpaint_color_sketch = gr.Image(label="Color sketch inpainting", show_label=False, elem_id="inpaint_sketch", source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA").style(height=480)
+                        inpaint_color_sketch_orig = gr.State(None)
 
-                            init_img_with_mask.change(update_orig, [init_img_with_mask, init_img_with_mask_orig], init_img_with_mask_orig)
+                        def update_orig(image, state):
+                            if image is not None:
+                                same_size = state is not None and state.size == image.size
+                                has_exact_match = np.any(np.all(np.array(image) == np.array(state), axis=-1))
+                                edited = same_size and has_exact_match
+                                return image if not edited or state is None else state
 
-                        init_img_inpaint = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_base")
-                        init_mask_inpaint = gr.Image(label="Mask", source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_mask")
+                        inpaint_color_sketch.change(update_orig, [inpaint_color_sketch, inpaint_color_sketch_orig], inpaint_color_sketch_orig)
 
-                        with FormRow():
-                            mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id="img2img_mask_blur")
-                            mask_alpha = gr.Slider(label="Mask transparency", interactive=use_color_sketch, visible=use_color_sketch, elem_id="img2img_mask_alpha")
-
-                        with FormRow():
-                            mask_mode = gr.Radio(label="Mask source", choices=["Draw mask", "Upload mask"], type="index", value="Draw mask", elem_id="mask_mode")
-                            inpainting_mask_invert = gr.Radio(label='Mask mode', choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index", elem_id="img2img_mask_mode")
-
-                        with FormRow():
-                            inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='original', type="index", elem_id="img2img_inpainting_fill")
-
-                        with FormRow():
-                            with gr.Column():
-                                inpaint_full_res = gr.Radio(label="Inpaint area", choices=["Whole picture", "Only masked"], type="index", value="Whole picture", elem_id="img2img_inpaint_full_res")
+                    with gr.TabItem('Inpaint upload', id='inpaint_upload', elem_id="img2img_inpaint_upload_tab") as tab_inpaint_upload:
+                        init_img_inpaint = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil", elem_id="img_inpaint_base")
+                        init_mask_inpaint = gr.Image(label="Mask", source="upload", interactive=True, type="pil", elem_id="img_inpaint_mask")
 
-                            with gr.Column(scale=4):
-                                inpaint_full_res_padding = gr.Slider(label='Only masked padding, pixels', minimum=0, maximum=256, step=4, value=32, elem_id="img2img_inpaint_full_res_padding")
-
-                    with gr.TabItem('Batch img2img', id='batch', elem_id="img2img_batch_tab"):
+                    with gr.TabItem('Batch', id='batch', elem_id="img2img_batch_tab") as tab_batch:
                         hidden = '<br>Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else ''
                         gr.HTML(f"<p class=\"text-gray-500\">Process images in a directory on the same machine where the server is running.<br>Use an empty output directory to save pictures normally instead of writing to the output directory.{hidden}</p>")
                         img2img_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, elem_id="img2img_batch_input_dir")
                         img2img_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, elem_id="img2img_batch_output_dir")
 
+                with FormGroup(elem_id="inpaint_controls", visible=False) as inpaint_controls:
+                    with FormRow():
+                        mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id="img2img_mask_blur")
+                        mask_alpha = gr.Slider(label="Mask transparency", visible=False, elem_id="img2img_mask_alpha")
+
+                    with FormRow():
+                        inpainting_mask_invert = gr.Radio(label='Mask mode', choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index", elem_id="img2img_mask_mode")
+
+                    with FormRow():
+                        inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='original', type="index", elem_id="img2img_inpainting_fill")
+
+                    with FormRow():
+                        with gr.Column():
+                            inpaint_full_res = gr.Radio(label="Inpaint area", choices=["Whole picture", "Only masked"], type="index", value="Whole picture", elem_id="img2img_inpaint_full_res")
+
+                        with gr.Column(scale=4):
+                            inpaint_full_res_padding = gr.Slider(label='Only masked padding, pixels', minimum=0, maximum=256, step=4, value=32, elem_id="img2img_inpaint_full_res_padding")
+
+                def select_img2img_tab(tab):
+                    return gr.update(visible=tab in [2, 3, 4]), gr.update(visible=tab == 3),
+
+                for i, elem in enumerate([tab_img2img, tab_sketch, tab_inpaint, tab_inpaint_color, tab_inpaint_upload, tab_batch]):
+                    elem.select(
+                        fn=lambda tab=i: select_img2img_tab(tab),
+                        inputs=[],
+                        outputs=[inpaint_controls, mask_alpha],
+                    )
+
                 with FormRow():
                     resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", choices=["Just resize", "Crop and resize", "Resize and fill", "Just resize (latent upscale)"], type="index", value="Just resize")
 
@@ -900,20 +914,6 @@ def create_ui():
                 ]
             )
 
-            mask_mode.change(
-                lambda mode, img: {
-                    init_img_with_mask: gr_show(mode == 0),
-                    init_img_inpaint: gr_show(mode == 1),
-                    init_mask_inpaint: gr_show(mode == 1),
-                },
-                inputs=[mask_mode, init_img_with_mask],
-                outputs=[
-                    init_img_with_mask,
-                    init_img_inpaint,
-                    init_mask_inpaint,
-                ],
-            )
-
             img2img_args = dict(
                 fn=wrap_gradio_gpu_call(modules.img2img.img2img, extra_outputs=[None, '', '']),
                 _js="submit_img2img",
@@ -924,11 +924,12 @@ def create_ui():
                     img2img_prompt_style,
                     img2img_prompt_style2,
                     init_img,
+                    sketch,
                     init_img_with_mask,
-                    init_img_with_mask_orig,
+                    inpaint_color_sketch,
+                    inpaint_color_sketch_orig,
                     init_img_inpaint,
                     init_mask_inpaint,
-                    mask_mode,
                     steps,
                     sampler_index,
                     mask_blur,
diff --git a/style.css b/style.css
index ec5e4182..ffd6307f 100644
--- a/style.css
+++ b/style.css
@@ -557,7 +557,9 @@ canvas[key="mask"] {
 }
 
 #img2img_image, #img2img_image > .h-60, #img2img_image > .h-60 > div, #img2img_image > .h-60 > div > img,
-img2maskimg, #img2maskimg > .h-60, #img2maskimg > .h-60 > div, #img2maskimg > .h-60 > div > img
+#img2img_sketch, #img2img_sketch > .h-60, #img2img_sketch > .h-60 > div, #img2img_sketch > .h-60 > div > img,
+#img2maskimg, #img2maskimg > .h-60, #img2maskimg > .h-60 > div, #img2maskimg > .h-60 > div > img,
+#inpaint_sketch, #inpaint_sketch > .h-60, #inpaint_sketch > .h-60 > div, #inpaint_sketch > .h-60 > div > img
 {
     height: 480px !important;
     max-height: 480px !important;
-- 
cgit v1.2.3


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

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

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index e86a624b..202e84e5 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -605,7 +605,7 @@ def create_ui():
                 setup_progressbar(progressbar, txt2img_preview, 'txt2img')
 
         with gr.Row().style(equal_height=False):
-            with gr.Column(variant='panel', elem_id="txt2img_settings"):
+            with gr.Column(variant='compact', elem_id="txt2img_settings"):
                 for category in ordered_ui_categories():
                     if category == "sampler":
                         steps, sampler_index = create_sampler_and_steps_selection(samplers, "txt2img")
@@ -794,7 +794,7 @@ def create_ui():
                 setup_progressbar(progressbar, img2img_preview, 'img2img')
 
         with FormRow().style(equal_height=False):
-            with gr.Column(variant='panel', elem_id="img2img_settings"):
+            with gr.Column(variant='compact', elem_id="img2img_settings"):
                 with gr.Tabs(elem_id="mode_img2img"):
                     with gr.TabItem('img2img', id='img2img', elem_id="img2img_img2img_tab") as tab_img2img:
                         init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool="editor", image_mode="RGBA").style(height=480)
@@ -1026,7 +1026,7 @@ def create_ui():
 
     with gr.Blocks(analytics_enabled=False) as extras_interface:
         with gr.Row().style(equal_height=False):
-            with gr.Column(variant='panel'):
+            with gr.Column(variant='compact'):
                 with gr.Tabs(elem_id="mode_extras"):
                     with gr.TabItem('Single Image', elem_id="extras_single_tab"):
                         extras_image = gr.Image(label="Source", source="upload", interactive=True, type="pil", elem_id="extras_image")
@@ -1127,8 +1127,8 @@ def create_ui():
 
     with gr.Blocks(analytics_enabled=False) as modelmerger_interface:
         with gr.Row().style(equal_height=False):
-            with gr.Column(variant='panel'):
-                gr.HTML(value="<p>A merger of the two checkpoints will be generated in your <b>checkpoint</b> directory.</p>")
+            with gr.Column(variant='compact'):
+                gr.HTML(value="<p style='margin-bottom: 2.5em'>A merger of the two checkpoints will be generated in your <b>checkpoint</b> directory.</p>")
 
                 with FormRow():
                     primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)")
@@ -1150,7 +1150,8 @@ def create_ui():
 
                 config_source = gr.Radio(choices=["A, B or C", "B", "C", "Don't"], value="A, B or C", label="Copy config from", type="index", elem_id="modelmerger_config_method")
 
-                modelmerger_merge = gr.Button(elem_id="modelmerger_merge", value="Merge", variant='primary')
+                with gr.Row():
+                    modelmerger_merge = gr.Button(elem_id="modelmerger_merge", value="Merge", variant='primary')
 
             with gr.Column(variant='panel'):
                 submit_result = gr.Textbox(elem_id="modelmerger_result", show_label=False)
diff --git a/requirements.txt b/requirements.txt
index e1dbf8e5..6cdea781 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -5,7 +5,7 @@ fairscale==0.4.4
 fonts
 font-roboto
 gfpgan
-gradio==3.15.0
+gradio==3.16.1
 invisible-watermark
 numpy
 omegaconf
diff --git a/requirements_versions.txt b/requirements_versions.txt
index d2899292..cc06d2b4 100644
--- a/requirements_versions.txt
+++ b/requirements_versions.txt
@@ -3,7 +3,7 @@ transformers==4.19.2
 accelerate==0.12.0
 basicsr==1.4.2
 gfpgan==1.3.8
-gradio==3.15.0
+gradio==3.16.1
 numpy==1.23.3
 Pillow==9.4.0
 realesrgan==0.3.0
diff --git a/style.css b/style.css
index ffd6307f..14b15191 100644
--- a/style.css
+++ b/style.css
@@ -20,7 +20,7 @@
     padding-right: 0.25em;
     margin: 0.1em 0;
     opacity: 0%;
-    cursor: default;	
+    cursor: default;
 }
 
 .output-html p {margin: 0 0.5em;}
@@ -221,7 +221,10 @@ fieldset span.text-gray-500, .gr-block.gr-box span.text-gray-500,  label.block s
 
 .dark fieldset span.text-gray-500, .dark .gr-block.gr-box span.text-gray-500, .dark label.block span{
     background-color: rgb(31, 41, 55);
-    box-shadow: 6px 0 6px 0px rgb(31, 41, 55), -6px 0 6px 0px rgb(31, 41, 55);
+    box-shadow: none;
+    border: 1px solid rgba(128, 128, 128, 0.1);
+    border-radius: 6px;
+    padding: 0.1em 0.5em;
 }
 
 #txt2img_column_batch, #img2img_column_batch{
@@ -371,7 +374,7 @@ input[type="range"]{
     grid-area: tile;
 }
 
-.modalClose, 
+.modalClose,
 .modalZoom,
 .modalTileImage {
   color: white;
@@ -509,29 +512,20 @@ input[type="range"]{
 }
 
 #quicksettings > div{
-    border: none;
-    background: none;
-    flex: unset;
-    gap: 1em;
-}
-
-#quicksettings > div > div{
-    max-width: 32em;
+    max-width: 24em;
     min-width: 24em;
     padding: 0;
+    border: none;
+    box-shadow: none;
+    background: none;
 }
 
-#quicksettings > div > div > div > div > label > span {
+#quicksettings > div > div > div > label > span {
     position: relative;
     margin-right: 9em;
     margin-bottom: -1em;
 }
 
-#quicksettings > div > div > label > span {
-    position: relative;
-    margin-bottom: -1em;
-}
-
 canvas[key="mask"] {
     z-index: 12 !important;
     filter: invert();
@@ -666,7 +660,10 @@ footer {
     font-weight: bold;
 }
 
-#txt2img_checkboxes > div > div{
+#txt2img_checkboxes, #img2img_checkboxes{
+    margin-bottom: 0.5em;
+}
+#txt2img_checkboxes > div > div, #img2img_checkboxes > div > div{
     flex: 0;
     white-space: nowrap;
     min-width: auto;
@@ -676,6 +673,30 @@ footer {
     opacity: 0.5;
 }
 
+.gr-compact {
+    border: none;
+    padding-top: 1em;
+}
+
+.dark .gr-compact{
+    background-color: rgb(31 41 55 / var(--tw-bg-opacity));
+    margin-left: 0.8em;
+}
+
+.gr-compact > *{
+    margin-top: 0.5em !important;
+}
+
+.gr-compact .gr-block, .gr-compact .gr-form{
+    border: none;
+    box-shadow: none;
+}
+
+.gr-compact .gr-box{
+    border-radius: .5rem !important;
+    border-width: 1px !important;
+}
+
 /* The following handles localization for right-to-left (RTL) languages like Arabic.
 The rtl media type will only be activated by the logic in javascript/localization.js.
 If you change anything above, you need to make sure it is RTL compliant by just running
diff --git a/webui.py b/webui.py
index 1fff80da..84159515 100644
--- a/webui.py
+++ b/webui.py
@@ -157,7 +157,7 @@ def webui():
 
         shared.demo = modules.ui.create_ui()
 
-        app, local_url, share_url = shared.demo.queue(default_enabled=False).launch(
+        app, local_url, share_url = shared.demo.launch(
             share=cmd_opts.share,
             server_name=server_name,
             server_port=cmd_opts.port,
@@ -185,7 +185,6 @@ def webui():
             create_api(app)
 
         modules.script_callbacks.app_started_callback(shared.demo, app)
-        modules.script_callbacks.app_started_callback(shared.demo, app)
 
         wait_on_server(shared.demo)
         print('Restarting UI...')
-- 
cgit v1.2.3


From 865228a83736bea9ede33e98041f2a7d0ca5daaa Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 14 Jan 2023 14:56:39 +0300
Subject: change style dropdowns to multiselect

---
 javascript/localization.js |  6 ++----
 modules/img2img.py         |  4 ++--
 modules/styles.py          | 12 ++++++++---
 modules/txt2img.py         |  4 ++--
 modules/ui.py              | 53 ++++++++++++++++++++++++++--------------------
 style.css                  | 15 ++++++++++---
 6 files changed, 57 insertions(+), 37 deletions(-)

(limited to 'modules/ui.py')

diff --git a/javascript/localization.js b/javascript/localization.js
index f92d2d24..bf9e1506 100644
--- a/javascript/localization.js
+++ b/javascript/localization.js
@@ -10,10 +10,8 @@ ignore_ids_for_localization={
     modelmerger_tertiary_model_name: 'OPTION',
     train_embedding: 'OPTION',
     train_hypernetwork: 'OPTION',
-    txt2img_style_index: 'OPTION',
-    txt2img_style2_index: 'OPTION',
-    img2img_style_index: 'OPTION',
-    img2img_style2_index: 'OPTION',
+    txt2img_styles: 'OPTION',
+    img2img_styles 'OPTION',
     setting_random_artist_categories: 'SPAN',
     setting_face_restoration_model: 'SPAN',
     setting_realesrgan_enabled_models: 'SPAN',
diff --git a/modules/img2img.py b/modules/img2img.py
index f62783c6..79382cc1 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -59,7 +59,7 @@ def process_batch(p, input_dir, output_dir, args):
                 processed_image.save(os.path.join(output_dir, filename))
 
 
-def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, *args):
+def img2img(mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, *args):
     is_batch = mode == 5
 
     if mode == 0:  # img2img
@@ -101,7 +101,7 @@ def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, pro
         outpath_grids=opts.outdir_grids or opts.outdir_img2img_grids,
         prompt=prompt,
         negative_prompt=negative_prompt,
-        styles=[prompt_style, prompt_style2],
+        styles=prompt_styles,
         seed=seed,
         subseed=subseed,
         subseed_strength=subseed_strength,
diff --git a/modules/styles.py b/modules/styles.py
index ce6e71ca..990d5623 100644
--- a/modules/styles.py
+++ b/modules/styles.py
@@ -40,12 +40,18 @@ def apply_styles_to_prompt(prompt, styles):
 class StyleDatabase:
     def __init__(self, path: str):
         self.no_style = PromptStyle("None", "", "")
-        self.styles = {"None": self.no_style}
+        self.styles = {}
+        self.path = path
 
-        if not os.path.exists(path):
+        self.reload()
+
+    def reload(self):
+        self.styles.clear()
+
+        if not os.path.exists(self.path):
             return
 
-        with open(path, "r", encoding="utf-8-sig", newline='') as file:
+        with open(self.path, "r", encoding="utf-8-sig", newline='') as file:
             reader = csv.DictReader(file)
             for row in reader:
                 # Support loading old CSV format with "name, text"-columns
diff --git a/modules/txt2img.py b/modules/txt2img.py
index 38b5f591..5a71793b 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -8,13 +8,13 @@ import modules.processing as processing
 from modules.ui import plaintext_to_html
 
 
-def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, *args):
+def txt2img(prompt: str, negative_prompt: str, prompt_styles,  steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, *args):
     p = StableDiffusionProcessingTxt2Img(
         sd_model=shared.sd_model,
         outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples,
         outpath_grids=opts.outdir_grids or opts.outdir_txt2img_grids,
         prompt=prompt,
-        styles=[prompt_style, prompt_style2],
+        styles=prompt_styles,
         negative_prompt=negative_prompt,
         seed=seed,
         subseed=subseed,
diff --git a/modules/ui.py b/modules/ui.py
index 202e84e5..db198a47 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -180,7 +180,7 @@ def add_style(name: str, prompt: str, negative_prompt: str):
     # reserialize all styles every time we save them
     shared.prompt_styles.save_styles(shared.styles_filename)
 
-    return [gr.Dropdown.update(visible=True, choices=list(shared.prompt_styles.styles)) for _ in range(4)]
+    return [gr.Dropdown.update(visible=True, choices=list(shared.prompt_styles.styles)) for _ in range(2)]
 
 
 def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resize_y):
@@ -197,11 +197,11 @@ def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resiz
     return f"resize: from <span class='resolution'>{p.width}x{p.height}</span> to <span class='resolution'>{p.hr_resize_x or p.hr_upscale_to_x}x{p.hr_resize_y or p.hr_upscale_to_y}</span>"
 
 
-def apply_styles(prompt, prompt_neg, style1_name, style2_name):
-    prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, [style1_name, style2_name])
-    prompt_neg = shared.prompt_styles.apply_negative_styles_to_prompt(prompt_neg, [style1_name, style2_name])
+def apply_styles(prompt, prompt_neg, styles):
+    prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, styles)
+    prompt_neg = shared.prompt_styles.apply_negative_styles_to_prompt(prompt_neg, styles)
 
-    return [gr.Textbox.update(value=prompt), gr.Textbox.update(value=prompt_neg), gr.Dropdown.update(value="None"), gr.Dropdown.update(value="None")]
+    return [gr.Textbox.update(value=prompt), gr.Textbox.update(value=prompt_neg), gr.Dropdown.update(value=[])]
 
 
 def interrogate(image):
@@ -374,13 +374,10 @@ def create_toprow(is_img2img):
                 )
 
             with gr.Row():
-                with gr.Column(scale=1, elem_id="style_pos_col"):
-                    prompt_style = gr.Dropdown(label="Style 1", elem_id=f"{id_part}_style_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())))
+                prompt_styles = gr.Dropdown(label="Styles", elem_id=f"{id_part}_styles", choices=[k for k, v in shared.prompt_styles.styles.items()], value=[], multiselect=True)
+                create_refresh_button(prompt_styles, shared.prompt_styles.reload, lambda: {"choices": [k for k, v in shared.prompt_styles.styles.items()]}, f"refresh_{id_part}_styles")
 
-                with gr.Column(scale=1, elem_id="style_neg_col"):
-                    prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())))
-
-    return prompt, prompt_style, negative_prompt, prompt_style2, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button
+    return prompt, prompt_styles, negative_prompt, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button
 
 
 def setup_progressbar(*args, **kwargs):
@@ -590,7 +587,7 @@ def create_ui():
     modules.scripts.scripts_txt2img.initialize_scripts(is_img2img=False)
 
     with gr.Blocks(analytics_enabled=False) as txt2img_interface:
-        txt2img_prompt, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _,txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False)
+        txt2img_prompt, txt2img_prompt_styles, txt2img_negative_prompt, submit, _, _,txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False)
 
         dummy_component = gr.Label(visible=False)
         txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False)
@@ -684,8 +681,7 @@ def create_ui():
                 inputs=[
                     txt2img_prompt,
                     txt2img_negative_prompt,
-                    txt2img_prompt_style,
-                    txt2img_prompt_style2,
+                    txt2img_prompt_styles,
                     steps,
                     sampler_index,
                     restore_faces,
@@ -780,7 +776,7 @@ def create_ui():
     modules.scripts.scripts_img2img.initialize_scripts(is_img2img=True)
 
     with gr.Blocks(analytics_enabled=False) as img2img_interface:
-        img2img_prompt, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,token_counter, token_button = create_toprow(is_img2img=True)
+        img2img_prompt, img2img_prompt_styles, img2img_negative_prompt, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,token_counter, token_button = create_toprow(is_img2img=True)
 
         with gr.Row(elem_id='img2img_progress_row'):
             img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False)
@@ -921,8 +917,7 @@ def create_ui():
                     dummy_component,
                     img2img_prompt,
                     img2img_negative_prompt,
-                    img2img_prompt_style,
-                    img2img_prompt_style2,
+                    img2img_prompt_styles,
                     init_img,
                     sketch,
                     init_img_with_mask,
@@ -977,7 +972,7 @@ def create_ui():
             )
 
             prompts = [(txt2img_prompt, txt2img_negative_prompt), (img2img_prompt, img2img_negative_prompt)]
-            style_dropdowns = [(txt2img_prompt_style, txt2img_prompt_style2), (img2img_prompt_style, img2img_prompt_style2)]
+            style_dropdowns = [txt2img_prompt_styles, img2img_prompt_styles]
             style_js_funcs = ["update_txt2img_tokens", "update_img2img_tokens"]
 
             for button, (prompt, negative_prompt) in zip([txt2img_save_style, img2img_save_style], prompts):
@@ -987,15 +982,15 @@ def create_ui():
                     # Have to pass empty dummy component here, because the JavaScript and Python function have to accept
                     # the same number of parameters, but we only know the style-name after the JavaScript prompt
                     inputs=[dummy_component, prompt, negative_prompt],
-                    outputs=[txt2img_prompt_style, img2img_prompt_style, txt2img_prompt_style2, img2img_prompt_style2],
+                    outputs=[txt2img_prompt_styles, img2img_prompt_styles],
                 )
 
-            for button, (prompt, negative_prompt), (style1, style2), js_func in zip([txt2img_prompt_style_apply, img2img_prompt_style_apply], prompts, style_dropdowns, style_js_funcs):
+            for button, (prompt, negative_prompt), styles, js_func in zip([txt2img_prompt_style_apply, img2img_prompt_style_apply], prompts, style_dropdowns, style_js_funcs):
                 button.click(
                     fn=apply_styles,
                     _js=js_func,
-                    inputs=[prompt, negative_prompt, style1, style2],
-                    outputs=[prompt, negative_prompt, style1, style2],
+                    inputs=[prompt, negative_prompt, styles],
+                    outputs=[prompt, negative_prompt, styles],
                 )
 
             token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter])
@@ -1530,6 +1525,7 @@ def create_ui():
 
         previous_section = None
         current_tab = None
+        current_row = None
         with gr.Tabs(elem_id="settings"):
             for i, (k, item) in enumerate(opts.data_labels.items()):
                 section_must_be_skipped = item.section[0] is None
@@ -1538,10 +1534,14 @@ def create_ui():
                     elem_id, text = item.section
 
                     if current_tab is not None:
+                        current_row.__exit__()
                         current_tab.__exit__()
 
+                    gr.Group()
                     current_tab = gr.TabItem(elem_id="settings_{}".format(elem_id), label=text)
                     current_tab.__enter__()
+                    current_row = gr.Column(variant='compact')
+                    current_row.__enter__()
 
                     previous_section = item.section
 
@@ -1556,6 +1556,7 @@ def create_ui():
                     components.append(component)
 
             if current_tab is not None:
+                current_row.__exit__()
                 current_tab.__exit__()
 
             with gr.TabItem("Actions"):
@@ -1774,7 +1775,13 @@ def create_ui():
             apply_field(x, 'value')
 
         if type(x) == gr.Dropdown:
-            apply_field(x, 'value', lambda val: val in x.choices, getattr(x, 'init_field', None))
+            def check_dropdown(val):
+                if x.multiselect:
+                    return all([value in x.choices for value in val])
+                else:
+                    return val in x.choices
+
+            apply_field(x, 'value', check_dropdown, getattr(x, 'init_field', None))
 
     visit(txt2img_interface, loadsave, "txt2img")
     visit(img2img_interface, loadsave, "img2img")
diff --git a/style.css b/style.css
index 14b15191..c1ebd501 100644
--- a/style.css
+++ b/style.css
@@ -114,6 +114,7 @@
     min-width: unset !important;
     flex-grow: 0 !important;
     padding: 0.4em 0;
+    gap: 0;
 }
 
 #roll_col > button {
@@ -141,10 +142,14 @@
     min-width: 8em !important;
 }
 
-#txt2img_style_index, #txt2img_style2_index, #img2img_style_index, #img2img_style2_index{
+#txt2img_styles, #img2img_styles{
     margin-top: 1em;
 }
 
+#txt2img_styles ul, #img2img_styles ul{
+    max-height: 35em;
+}
+
 .gr-form{
     background: transparent;
 }
@@ -154,10 +159,14 @@
     margin-bottom: 0;
 }
 
-#toprow div{
+#toprow div.gr-box, #toprow div.gr-form{
     border: none;
     gap: 0;
     background: transparent;
+    box-shadow: none;
+}
+#toprow div{
+    gap: 0;
 }
 
 #resize_mode{
@@ -615,7 +624,7 @@ canvas[key="mask"] {
     max-width: 2.5em;
     min-width: 2.5em !important;
     height: 2.4em;
-    margin: 0.55em 0;
+    margin: 1.6em 0 0 0;
 }
 
 #quicksettings .gr-button-tool{
-- 
cgit v1.2.3


From 08c6f009a5ee92dd3218a942c08e8337c26352be Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 14 Jan 2023 15:55:40 +0300
Subject: load hashes from cache for checkpoints that have them add checkpoint
 hash to footer

---
 javascript/ui.js     | 25 ++++++++++++++++---------
 modules/hashes.py    | 26 +++++++++++++++++++-------
 modules/sd_models.py |  9 ++++++---
 modules/shared.py    |  1 +
 modules/ui.py        |  2 ++
 script.js            |  4 ++++
 6 files changed, 48 insertions(+), 19 deletions(-)

(limited to 'modules/ui.py')

diff --git a/javascript/ui.js b/javascript/ui.js
index a41dd26f..1e04a8f4 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -143,14 +143,6 @@ function confirm_clear_prompt(prompt, negative_prompt) {
 
 
 opts = {}
-function apply_settings(jsdata){
-    console.log(jsdata)
-
-    opts = JSON.parse(jsdata)
-
-    return jsdata
-}
-
 onUiUpdate(function(){
 	if(Object.keys(opts).length != 0) return;
 
@@ -160,7 +152,7 @@ onUiUpdate(function(){
     textarea = json_elem.querySelector('textarea')
     jsdata = textarea.value
     opts = JSON.parse(jsdata)
-
+    executeCallbacks(optionsChangedCallbacks);
 
     Object.defineProperty(textarea, 'value', {
         set: function(newValue) {
@@ -171,6 +163,8 @@ onUiUpdate(function(){
             if (oldValue != newValue) {
                 opts = JSON.parse(textarea.value)
             }
+
+            executeCallbacks(optionsChangedCallbacks);
         },
         get: function() {
             var valueProp = Object.getOwnPropertyDescriptor(HTMLTextAreaElement.prototype, 'value');
@@ -201,6 +195,19 @@ onUiUpdate(function(){
     }
 })
 
+
+onOptionsChanged(function(){
+    elem = gradioApp().getElementById('sd_checkpoint_hash')
+    sd_checkpoint_hash = opts.sd_checkpoint_hash || ""
+    shorthash = sd_checkpoint_hash.substr(0,10)
+
+	if(elem && elem.textContent != shorthash){
+	    elem.textContent = shorthash
+	    elem.title = sd_checkpoint_hash
+	    elem.href = "https://google.com/search?q=" + sd_checkpoint_hash
+	}
+})
+
 let txt2img_textarea, img2img_textarea = undefined;
 let wait_time = 800
 let token_timeout;
diff --git a/modules/hashes.py b/modules/hashes.py
index ebfbd90c..14231771 100644
--- a/modules/hashes.py
+++ b/modules/hashes.py
@@ -42,23 +42,35 @@ def calculate_sha256(filename):
     return hash_sha256.hexdigest()
 
 
-def sha256(filename, title):
+def sha256_from_cache(filename, title):
     hashes = cache("hashes")
     ondisk_mtime = os.path.getmtime(filename)
 
-    if title in hashes:
-        cached_sha256 = hashes[title].get("sha256", None)
-        cached_mtime = hashes[title].get("mtime", 0)
+    if title not in hashes:
+        return None
+
+    cached_sha256 = hashes[title].get("sha256", None)
+    cached_mtime = hashes[title].get("mtime", 0)
+
+    if ondisk_mtime > cached_mtime or cached_sha256 is None:
+        return None
+
+    return cached_sha256
+
+
+def sha256(filename, title):
+    hashes = cache("hashes")
 
-        if ondisk_mtime <= cached_mtime and cached_sha256 is not None:
-            return cached_sha256
+    sha256_value = sha256_from_cache(filename, title)
+    if sha256_value is not None:
+        return sha256_value
 
     print(f"Calculating sha256 for {filename}: ", end='')
     sha256_value = calculate_sha256(filename)
     print(f"{sha256_value}")
 
     hashes[title] = {
-        "mtime": ondisk_mtime,
+        "mtime": os.path.getmtime(filename),
         "sha256": sha256_value,
     }
 
diff --git a/modules/sd_models.py b/modules/sd_models.py
index 1fe6d11b..e5a0bc63 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -44,9 +44,11 @@ class CheckpointInfo:
         self.title = name
         self.model_name = os.path.splitext(name.replace("/", "_").replace("\\", "_"))[0]
         self.hash = model_hash(filename)
-        self.ids = [self.hash, self.model_name, self.title, f'{name} [{self.hash}]']
-        self.shorthash = None
-        self.sha256 = None
+
+        self.sha256 = hashes.sha256_from_cache(self.filename, "checkpoint/" + self.title)
+        self.shorthash = self.sha256[0:10] if self.sha256 else None
+
+        self.ids = [self.hash, self.model_name, self.title, f'{name} [{self.hash}]'] + ([self.shorthash, self.sha256] if self.shorthash else [])
 
     def register(self):
         checkpoints_list[self.title] = self
@@ -269,6 +271,7 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, vae_file="auto"):
     model.sd_model_hash = sd_model_hash
     model.sd_model_checkpoint = checkpoint_info.filename
     model.sd_checkpoint_info = checkpoint_info
+    shared.opts.data["sd_checkpoint_hash"] = checkpoint_info.sha256
 
     model.logvar = model.logvar.to(devices.device)  # fix for training
 
diff --git a/modules/shared.py b/modules/shared.py
index a6c61db3..c9988d4d 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -458,6 +458,7 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters"
 
 options_templates.update(options_section((None, "Hidden options"), {
     "disabled_extensions": OptionInfo([], "Disable those extensions"),
+    "sd_checkpoint_hash": OptionInfo("", "SHA256 hash of the current checkpoint"),
 }))
 
 options_templates.update()
diff --git a/modules/ui.py b/modules/ui.py
index e86a624b..2625ae32 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1841,4 +1841,6 @@ xformers: {xformers_version}
 gradio: {gr.__version__}
  • 
 commit: <a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui/commit/{commit}">{short_commit}</a>
+ • 
+checkpoint: <a id="sd_checkpoint_hash">N/A</a>
 """
diff --git a/script.js b/script.js
index 21960d91..3345e32b 100644
--- a/script.js
+++ b/script.js
@@ -14,6 +14,7 @@ function get_uiCurrentTabContent() {
 
 uiUpdateCallbacks = []
 uiTabChangeCallbacks = []
+optionsChangedCallbacks = []
 let uiCurrentTab = null
 
 function onUiUpdate(callback){
@@ -22,6 +23,9 @@ function onUiUpdate(callback){
 function onUiTabChange(callback){
     uiTabChangeCallbacks.push(callback)
 }
+function onOptionsChanged(callback){
+    optionsChangedCallbacks.push(callback)
+}
 
 function runCallback(x, m){
     try {
-- 
cgit v1.2.3


From 86359535d6fb0899fa9e838d27f2006b929331d5 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 14 Jan 2023 22:43:01 +0300
Subject: add buttons to copy images between img2img tabs

---
 javascript/ui.js | 21 +++++++++++++++++++--
 modules/ui.py    | 42 +++++++++++++++++++++++++++++++++++++++++-
 style.css        | 18 ++++++++++++++++++
 3 files changed, 78 insertions(+), 3 deletions(-)

(limited to 'modules/ui.py')

diff --git a/javascript/ui.js b/javascript/ui.js
index 1e04a8f4..f8279124 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -45,10 +45,27 @@ function switch_to_txt2img(){
     return args_to_array(arguments);
 }
 
-function switch_to_img2img(){
+function switch_to_img2img_tab(no){
     gradioApp().querySelector('#tabs').querySelectorAll('button')[1].click();
-    gradioApp().getElementById('mode_img2img').querySelectorAll('button')[0].click();
+    gradioApp().getElementById('mode_img2img').querySelectorAll('button')[no].click();
+}
+function switch_to_img2img(){
+    switch_to_img2img_tab(0);
+    return args_to_array(arguments);
+}
+
+function switch_to_sketch(){
+    switch_to_img2img_tab(1);
+    return args_to_array(arguments);
+}
+
+function switch_to_inpaint(){
+    switch_to_img2img_tab(2);
+    return args_to_array(arguments);
+}
 
+function switch_to_inpaint_sketch(){
+    switch_to_img2img_tab(3);
     return args_to_array(arguments);
 }
 
diff --git a/modules/ui.py b/modules/ui.py
index 2625ae32..2425c66f 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -795,19 +795,39 @@ def create_ui():
 
         with FormRow().style(equal_height=False):
             with gr.Column(variant='panel', elem_id="img2img_settings"):
+                copy_image_buttons = []
+                copy_image_destinations = {}
+
+                def add_copy_image_controls(tab_name, elem):
+                    with gr.Row(variant="compact", elem_id=f"img2img_copy_to_{tab_name}"):
+                        gr.HTML("Copy image to: ", elem_id=f"img2img_label_copy_to_{tab_name}")
+
+                        for title, name in zip(['img2img', 'sketch', 'inpaint', 'inpaint sketch'], ['img2img', 'sketch', 'inpaint', 'inpaint_sketch']):
+                            if name == tab_name:
+                                gr.Button(title, interactive=False)
+                                copy_image_destinations[name] = elem
+                                continue
+
+                            button = gr.Button(title)
+                            copy_image_buttons.append((button, name, elem))
+
                 with gr.Tabs(elem_id="mode_img2img"):
                     with gr.TabItem('img2img', id='img2img', elem_id="img2img_img2img_tab") as tab_img2img:
                         init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool="editor", image_mode="RGBA").style(height=480)
+                        add_copy_image_controls('img2img', init_img)
 
                     with gr.TabItem('Sketch', id='img2img_sketch', elem_id="img2img_img2img_sketch_tab") as tab_sketch:
                         sketch = gr.Image(label="Image for img2img", elem_id="img2img_sketch", show_label=False, source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA").style(height=480)
+                        add_copy_image_controls('sketch', sketch)
 
                     with gr.TabItem('Inpaint', id='inpaint', elem_id="img2img_inpaint_tab") as tab_inpaint:
                         init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", image_mode="RGBA").style(height=480)
+                        add_copy_image_controls('inpaint', init_img_with_mask)
 
                     with gr.TabItem('Inpaint sketch', id='inpaint_sketch', elem_id="img2img_inpaint_sketch_tab") as tab_inpaint_color:
                         inpaint_color_sketch = gr.Image(label="Color sketch inpainting", show_label=False, elem_id="inpaint_sketch", source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA").style(height=480)
                         inpaint_color_sketch_orig = gr.State(None)
+                        add_copy_image_controls('inpaint_sketch', inpaint_color_sketch)
 
                         def update_orig(image, state):
                             if image is not None:
@@ -824,10 +844,29 @@ def create_ui():
 
                     with gr.TabItem('Batch', id='batch', elem_id="img2img_batch_tab") as tab_batch:
                         hidden = '<br>Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else ''
-                        gr.HTML(f"<p class=\"text-gray-500\">Process images in a directory on the same machine where the server is running.<br>Use an empty output directory to save pictures normally instead of writing to the output directory.{hidden}</p>")
+                        gr.HTML(f"<p style='padding-bottom: 1em;' class=\"text-gray-500\">Process images in a directory on the same machine where the server is running.<br>Use an empty output directory to save pictures normally instead of writing to the output directory.{hidden}</p>")
                         img2img_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, elem_id="img2img_batch_input_dir")
                         img2img_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, elem_id="img2img_batch_output_dir")
 
+                def copy_image(img):
+                    if isinstance(img, dict) and 'image' in img:
+                        return img['image']
+
+                    return img
+
+                for button, name, elem in copy_image_buttons:
+                    button.click(
+                        fn=copy_image,
+                        inputs=[elem],
+                        outputs=[copy_image_destinations[name]],
+                    )
+                    button.click(
+                        fn=lambda: None,
+                        _js="switch_to_"+name.replace(" ", "_"),
+                        inputs=[],
+                        outputs=[],
+                    )
+
                 with FormGroup(elem_id="inpaint_controls", visible=False) as inpaint_controls:
                     with FormRow():
                         mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id="img2img_mask_blur")
@@ -856,6 +895,7 @@ def create_ui():
                         outputs=[inpaint_controls, mask_alpha],
                     )
 
+
                 with FormRow():
                     resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", choices=["Just resize", "Crop and resize", "Resize and fill", "Just resize (latent upscale)"], type="index", value="Just resize")
 
diff --git a/style.css b/style.css
index ffd6307f..2d484e06 100644
--- a/style.css
+++ b/style.css
@@ -676,6 +676,24 @@ footer {
     opacity: 0.5;
 }
 
+#mode_img2img > div > div{
+    gap: 0 !important;
+}
+
+[id*='img2img_copy_to_'] {
+    border: none;
+}
+
+[id*='img2img_copy_to_'] > button {
+}
+
+[id*='img2img_label_copy_to_'] {
+    font-size: 1.0em;
+    font-weight: bold;
+    text-align: center;
+    line-height: 2.4em;
+}
+
 /* The following handles localization for right-to-left (RTL) languages like Arabic.
 The rtl media type will only be activated by the logic in javascript/localization.js.
 If you change anything above, you need to make sure it is RTL compliant by just running
-- 
cgit v1.2.3


From 9ef41df6f9043d58fbbeea1f06be8e5c8622248b Mon Sep 17 00:00:00 2001
From: Josh R <josh@joshrubenstein.com>
Date: Sat, 14 Jan 2023 15:26:45 -0800
Subject: add inpaint masking controls to orderable section that the settings
 can order

---
 modules/shared.py |  1 +
 modules/ui.py     | 58 +++++++++++++++++++++++++++----------------------------
 2 files changed, 30 insertions(+), 29 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/shared.py b/modules/shared.py
index 51df056c..7ce8003f 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -116,6 +116,7 @@ restricted_opts = {
 }
 
 ui_reorder_categories = [
+    "masking",
     "sampler",
     "dimensions",
     "cfg",
diff --git a/modules/ui.py b/modules/ui.py
index 2425c66f..174930ab 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -867,35 +867,6 @@ def create_ui():
                         outputs=[],
                     )
 
-                with FormGroup(elem_id="inpaint_controls", visible=False) as inpaint_controls:
-                    with FormRow():
-                        mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id="img2img_mask_blur")
-                        mask_alpha = gr.Slider(label="Mask transparency", visible=False, elem_id="img2img_mask_alpha")
-
-                    with FormRow():
-                        inpainting_mask_invert = gr.Radio(label='Mask mode', choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index", elem_id="img2img_mask_mode")
-
-                    with FormRow():
-                        inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='original', type="index", elem_id="img2img_inpainting_fill")
-
-                    with FormRow():
-                        with gr.Column():
-                            inpaint_full_res = gr.Radio(label="Inpaint area", choices=["Whole picture", "Only masked"], type="index", value="Whole picture", elem_id="img2img_inpaint_full_res")
-
-                        with gr.Column(scale=4):
-                            inpaint_full_res_padding = gr.Slider(label='Only masked padding, pixels', minimum=0, maximum=256, step=4, value=32, elem_id="img2img_inpaint_full_res_padding")
-
-                def select_img2img_tab(tab):
-                    return gr.update(visible=tab in [2, 3, 4]), gr.update(visible=tab == 3),
-
-                for i, elem in enumerate([tab_img2img, tab_sketch, tab_inpaint, tab_inpaint_color, tab_inpaint_upload, tab_batch]):
-                    elem.select(
-                        fn=lambda tab=i: select_img2img_tab(tab),
-                        inputs=[],
-                        outputs=[inpaint_controls, mask_alpha],
-                    )
-
-
                 with FormRow():
                     resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", choices=["Just resize", "Crop and resize", "Resize and fill", "Just resize (latent upscale)"], type="index", value="Just resize")
 
@@ -937,6 +908,35 @@ def create_ui():
                         with FormGroup(elem_id="img2img_script_container"):
                             custom_inputs = modules.scripts.scripts_img2img.setup_ui()
 
+                    elif category == "masking":
+                        with FormGroup(elem_id="inpaint_controls", visible=False) as inpaint_controls:
+                            with FormRow():
+                                mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id="img2img_mask_blur")
+                                mask_alpha = gr.Slider(label="Mask transparency", visible=False, elem_id="img2img_mask_alpha")
+
+                            with FormRow():
+                                inpainting_mask_invert = gr.Radio(label='Mask mode', choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index", elem_id="img2img_mask_mode")
+
+                            with FormRow():
+                                inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='original', type="index", elem_id="img2img_inpainting_fill")
+
+                            with FormRow():
+                                with gr.Column():
+                                    inpaint_full_res = gr.Radio(label="Inpaint area", choices=["Whole picture", "Only masked"], type="index", value="Whole picture", elem_id="img2img_inpaint_full_res")
+
+                                with gr.Column(scale=4):
+                                    inpaint_full_res_padding = gr.Slider(label='Only masked padding, pixels', minimum=0, maximum=256, step=4, value=32, elem_id="img2img_inpaint_full_res_padding")
+
+                            def select_img2img_tab(tab):
+                                return gr.update(visible=tab in [2, 3, 4]), gr.update(visible=tab == 3),
+
+                            for i, elem in enumerate([tab_img2img, tab_sketch, tab_inpaint, tab_inpaint_color, tab_inpaint_upload, tab_batch]):
+                                elem.select(
+                                    fn=lambda tab=i: select_img2img_tab(tab),
+                                    inputs=[],
+                                    outputs=[inpaint_controls, mask_alpha],
+                                )
+
             img2img_gallery, generation_info, html_info, html_log = create_output_panel("img2img", opts.outdir_img2img_samples)
             parameters_copypaste.bind_buttons({"img2img": img2img_paste}, None, img2img_prompt)
 
-- 
cgit v1.2.3


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

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

(limited to 'modules/ui.py')

diff --git a/javascript/progressbar.js b/javascript/progressbar.js
index d6323ed9..b7524ef7 100644
--- a/javascript/progressbar.js
+++ b/javascript/progressbar.js
@@ -1,82 +1,25 @@
 // code related to showing and updating progressbar shown as the image is being made
-global_progressbars = {}
-galleries = {}
-galleryObservers = {}
-
-// this tracks launches of window.setTimeout for progressbar to prevent starting a new timeout when the previous is still running
-timeoutIds = {}
 
-function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_skip, id_interrupt, id_preview, id_gallery){
-    // gradio 3.8's enlightened approach allows them to create two nested div elements inside each other with same id
-    // every time you use gr.HTML(elem_id='xxx'), so we handle this here
-    var progressbar = gradioApp().querySelector("#"+id_progressbar+" #"+id_progressbar)
-    var progressbarParent
-    if(progressbar){
-        progressbarParent = gradioApp().querySelector("#"+id_progressbar)
-    } else{
-        progressbar = gradioApp().getElementById(id_progressbar)
-        progressbarParent = null
-    }
 
-    var skip = id_skip ? gradioApp().getElementById(id_skip) : null
-    var interrupt = gradioApp().getElementById(id_interrupt)
-
-    if(opts.show_progress_in_title && progressbar && progressbar.offsetParent){
-        if(progressbar.innerText){
-            let newtitle = '[' + progressbar.innerText.trim() + '] Stable Diffusion';
-            if(document.title != newtitle){
-                document.title =  newtitle;
-            }
-        }else{
-            let newtitle = 'Stable Diffusion'
-            if(document.title != newtitle){
-                document.title =  newtitle;
-            }
-        }
-    }
-
-	if(progressbar!= null && progressbar != global_progressbars[id_progressbar]){
-	    global_progressbars[id_progressbar] = progressbar
-
-        var mutationObserver = new MutationObserver(function(m){
-            if(timeoutIds[id_part]) return;
-
-            preview = gradioApp().getElementById(id_preview)
-            gallery = gradioApp().getElementById(id_gallery)
+galleries = {}
+storedGallerySelections = {}
+galleryObservers = {}
 
-            if(preview != null && gallery != null){
-                preview.style.width = gallery.clientWidth + "px"
-                preview.style.height = gallery.clientHeight + "px"
-                if(progressbarParent) progressbar.style.width = progressbarParent.clientWidth + "px"
+function rememberGallerySelection(id_gallery){
+    storedGallerySelections[id_gallery] = getGallerySelectedIndex(id_gallery)
+}
 
-				//only watch gallery if there is a generation process going on
-                check_gallery(id_gallery);
+function getGallerySelectedIndex(id_gallery){
+    let galleryButtons = gradioApp().querySelectorAll('#'+id_gallery+' .gallery-item')
+    let galleryBtnSelected = gradioApp().querySelector('#'+id_gallery+' .gallery-item.\\!ring-2')
 
-                var progressDiv = gradioApp().querySelectorAll('#' + id_progressbar_span).length > 0;
-                if(progressDiv){
-                    timeoutIds[id_part] = window.setTimeout(function() {
-                        timeoutIds[id_part] = null
-                        requestMoreProgress(id_part, id_progressbar_span, id_skip, id_interrupt)
-                    }, 500)
-                } else{
-                    if (skip) {
-                        skip.style.display = "none"
-                    }
-                    interrupt.style.display = "none"
+     let currentlySelectedIndex = -1
+     galleryButtons.forEach(function(v, i){ if(v==galleryBtnSelected) { currentlySelectedIndex = i } })
 
-                    //disconnect observer once generation finished, so user can close selected image if they want
-                    if (galleryObservers[id_gallery]) {
-                        galleryObservers[id_gallery].disconnect();
-                        galleries[id_gallery] = null;
-                    }
-                }
-            }
-
-        });
-        mutationObserver.observe( progressbar, { childList:true, subtree:true })
-	}
+     return currentlySelectedIndex
 }
 
+// this is a workaround for https://github.com/gradio-app/gradio/issues/2984
 function check_gallery(id_gallery){
     let gallery = gradioApp().getElementById(id_gallery)
     // if gallery has no change, no need to setting up observer again.
@@ -85,10 +28,16 @@ function check_gallery(id_gallery){
         if(galleryObservers[id_gallery]){
             galleryObservers[id_gallery].disconnect();
         }
-        let prevSelectedIndex = selected_gallery_index();
+
+        storedGallerySelections[id_gallery] = -1
+
         galleryObservers[id_gallery] = new MutationObserver(function (){
             let galleryButtons = gradioApp().querySelectorAll('#'+id_gallery+' .gallery-item')
             let galleryBtnSelected = gradioApp().querySelector('#'+id_gallery+' .gallery-item.\\!ring-2')
+            let currentlySelectedIndex = getGallerySelectedIndex(id_gallery)
+            prevSelectedIndex = storedGallerySelections[id_gallery]
+            storedGallerySelections[id_gallery] = -1
+
             if (prevSelectedIndex !== -1 && galleryButtons.length>prevSelectedIndex && !galleryBtnSelected) {
                 // automatically re-open previously selected index (if exists)
                 activeElement = gradioApp().activeElement;
@@ -120,30 +69,150 @@ function check_gallery(id_gallery){
 }
 
 onUiUpdate(function(){
-    check_progressbar('txt2img', 'txt2img_progressbar', 'txt2img_progress_span', 'txt2img_skip', 'txt2img_interrupt', 'txt2img_preview', 'txt2img_gallery')
-    check_progressbar('img2img', 'img2img_progressbar', 'img2img_progress_span', 'img2img_skip', 'img2img_interrupt', 'img2img_preview', 'img2img_gallery')
-    check_progressbar('ti', 'ti_progressbar', 'ti_progress_span', '', 'ti_interrupt', 'ti_preview', 'ti_gallery')
+    check_gallery('txt2img_gallery')
+    check_gallery('img2img_gallery')
 })
 
-function requestMoreProgress(id_part, id_progressbar_span, id_skip, id_interrupt){
-    btn = gradioApp().getElementById(id_part+"_check_progress");
-    if(btn==null) return;
-
-    btn.click();
-    var progressDiv = gradioApp().querySelectorAll('#' + id_progressbar_span).length > 0;
-    var skip = id_skip ? gradioApp().getElementById(id_skip) : null
-    var interrupt = gradioApp().getElementById(id_interrupt)
-    if(progressDiv && interrupt){
-        if (skip) {
-            skip.style.display = "block"
+function request(url, data, handler, errorHandler){
+    var xhr = new XMLHttpRequest();
+    var url = url;
+    xhr.open("POST", url, true);
+    xhr.setRequestHeader("Content-Type", "application/json");
+    xhr.onreadystatechange = function () {
+        if (xhr.readyState === 4) {
+            if (xhr.status === 200) {
+                var js = JSON.parse(xhr.responseText);
+                handler(js)
+            } else{
+                errorHandler()
+            }
         }
-        interrupt.style.display = "block"
+    };
+    var js = JSON.stringify(data);
+    xhr.send(js);
+}
+
+function pad2(x){
+    return x<10 ? '0'+x : x
+}
+
+function formatTime(secs){
+    if(secs > 3600){
+        return pad2(Math.floor(secs/60/60)) + ":" + pad2(Math.floor(secs/60)%60) + ":" + pad2(Math.floor(secs)%60)
+    } else if(secs > 60){
+        return pad2(Math.floor(secs/60)) + ":" + pad2(Math.floor(secs)%60)
+    } else{
+        return Math.floor(secs) + "s"
     }
 }
 
-function requestProgress(id_part){
-    btn = gradioApp().getElementById(id_part+"_check_progress_initial");
-    if(btn==null) return;
+function randomId(){
+    return "task(" + Math.random().toString(36).slice(2, 7) + Math.random().toString(36).slice(2, 7) + Math.random().toString(36).slice(2, 7)+")"
+}
+
+// starts sending progress requests to "/internal/progress" uri, creating progressbar above progressbarContainer element and
+// preview inside gallery element. Cleans up all created stuff when the task is over and calls atEnd.
+// calls onProgress every time there is a progress update
+function requestProgress(id_task, progressbarContainer, gallery, atEnd, onProgress){
+    var dateStart = new Date()
+    var wasEverActive = false
+    var parentProgressbar = progressbarContainer.parentNode
+    var parentGallery = gallery.parentNode
+
+    var divProgress = document.createElement('div')
+    divProgress.className='progressDiv'
+    var divInner = document.createElement('div')
+    divInner.className='progress'
+
+    divProgress.appendChild(divInner)
+    parentProgressbar.insertBefore(divProgress, progressbarContainer)
+
+    var livePreview = document.createElement('div')
+    livePreview.className='livePreview'
+    parentGallery.insertBefore(livePreview, gallery)
+
+    var removeProgressBar = function(){
+        parentProgressbar.removeChild(divProgress)
+        parentGallery.removeChild(livePreview)
+        atEnd()
+    }
+
+    var fun = function(id_task, id_live_preview){
+        request("/internal/progress", {"id_task": id_task, "id_live_preview": id_live_preview}, function(res){
+            console.log(res)
+
+            if(res.completed){
+                removeProgressBar()
+                return
+            }
+
+            var rect = progressbarContainer.getBoundingClientRect()
+
+            if(rect.width){
+                divProgress.style.width = rect.width + "px";
+            }
+
+            progressText = ""
+
+            divInner.style.width = ((res.progress || 0) * 100.0) + '%'
+
+            if(res.progress > 0){
+                progressText = ((res.progress || 0) * 100.0).toFixed(0) + '%'
+            }
+
+            if(res.eta){
+                progressText += " ETA: " + formatTime(res.eta)
+            } else if(res.textinfo){
+                progressText += " " + res.textinfo
+            }
+
+            divInner.textContent = progressText
+
+            var elapsedFromStart = (new Date() - dateStart) / 1000
+
+            if(res.active) wasEverActive = true;
+
+            if(! res.active && wasEverActive){
+                removeProgressBar()
+                return
+            }
+
+            if(elapsedFromStart > 5 && !res.queued && !res.active){
+                removeProgressBar()
+                return
+            }
+
+
+            if(res.live_preview){
+                var img = new Image();
+                img.onload = function() {
+                    var rect = gallery.getBoundingClientRect()
+                    if(rect.width){
+                        livePreview.style.width = rect.width + "px"
+                        livePreview.style.height = rect.height + "px"
+                    }
+
+                    livePreview.innerHTML = ''
+                    livePreview.appendChild(img)
+                    if(livePreview.childElementCount > 2){
+                        livePreview.removeChild(livePreview.firstElementChild)
+                    }
+                }
+                img.src = res.live_preview;
+            }
+
+
+            if(onProgress){
+                onProgress(res)
+            }
+
+            setTimeout(() => {
+                fun(id_task, res.id_live_preview);
+            }, 500)
+        }, function(){
+            removeProgressBar()
+        })
+    }
 
-    btn.click();
+    fun(id_task, 0)
 }
diff --git a/javascript/textualInversion.js b/javascript/textualInversion.js
index 8061be08..0354b860 100644
--- a/javascript/textualInversion.js
+++ b/javascript/textualInversion.js
@@ -1,8 +1,17 @@
 
 
+
 function start_training_textual_inversion(){
-    requestProgress('ti')
     gradioApp().querySelector('#ti_error').innerHTML=''
 
-    return args_to_array(arguments)
+    var id = randomId()
+    requestProgress(id, gradioApp().getElementById('ti_output'), gradioApp().getElementById('ti_gallery'), function(){}, function(progress){
+        gradioApp().getElementById('ti_progress').innerHTML = progress.textinfo
+    })
+
+    var res = args_to_array(arguments)
+
+    res[0] = id
+
+    return res
 }
diff --git a/javascript/ui.js b/javascript/ui.js
index f8279124..ecf97cb3 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -126,18 +126,41 @@ function create_submit_args(args){
     return res
 }
 
+function showSubmitButtons(tabname, show){
+    gradioApp().getElementById(tabname+'_interrupt').style.display = show ? "none" : "block"
+    gradioApp().getElementById(tabname+'_skip').style.display = show ? "none" : "block"
+}
+
 function submit(){
-    requestProgress('txt2img')
+    rememberGallerySelection('txt2img_gallery')
+    showSubmitButtons('txt2img', false)
+
+    var id = randomId()
+    requestProgress(id, gradioApp().getElementById('txt2img_gallery_container'), gradioApp().getElementById('txt2img_gallery'), function(){
+        showSubmitButtons('txt2img', true)
+
+    })
 
-    return create_submit_args(arguments)
+    var res = create_submit_args(arguments)
+
+    res[0] = id
+
+    return res
 }
 
 function submit_img2img(){
-    requestProgress('img2img')
+    rememberGallerySelection('img2img_gallery')
+    showSubmitButtons('img2img', false)
+
+    var id = randomId()
+    requestProgress(id, gradioApp().getElementById('img2img_gallery_container'), gradioApp().getElementById('img2img_gallery'), function(){
+        showSubmitButtons('img2img', true)
+    })
 
-    res = create_submit_args(arguments)
+    var res = create_submit_args(arguments)
 
-    res[0] = get_tab_index('mode_img2img')
+    res[0] = id
+    res[1] = get_tab_index('mode_img2img')
 
     return res
 }
diff --git a/modules/call_queue.py b/modules/call_queue.py
index 4cd49533..92097c15 100644
--- a/modules/call_queue.py
+++ b/modules/call_queue.py
@@ -4,7 +4,7 @@ import threading
 import traceback
 import time
 
-from modules import shared
+from modules import shared, progress
 
 queue_lock = threading.Lock()
 
@@ -22,12 +22,23 @@ def wrap_queued_call(func):
 def wrap_gradio_gpu_call(func, extra_outputs=None):
     def f(*args, **kwargs):
 
-        shared.state.begin()
+        # if the first argument is a string that says "task(...)", it is treated as a job id
+        if len(args) > 0 and type(args[0]) == str and args[0][0:5] == "task(" and args[0][-1] == ")":
+            id_task = args[0]
+            progress.add_task_to_queue(id_task)
+        else:
+            id_task = None
 
         with queue_lock:
-            res = func(*args, **kwargs)
+            shared.state.begin()
+            progress.start_task(id_task)
+
+            try:
+                res = func(*args, **kwargs)
+            finally:
+                progress.finish_task(id_task)
 
-        shared.state.end()
+            shared.state.end()
 
         return res
 
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 3aebefa8..ae6af516 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -453,7 +453,7 @@ def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None,
     shared.reload_hypernetworks()
 
 
-def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_hypernetwork_every, template_filename, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
+def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_hypernetwork_every, template_filename, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
     # images allows training previews to have infotext. Importing it at the top causes a circular import problem.
     from modules import images
 
@@ -629,7 +629,6 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step,
 
                 description = f"Training hypernetwork [Epoch {epoch_num}: {epoch_step+1}/{steps_per_epoch}]loss: {loss_step:.7f}"
                 pbar.set_description(description)
-                shared.state.textinfo = description
                 if hypernetwork_dir is not None and steps_done % save_hypernetwork_every == 0:
                     # Before saving, change name to match current checkpoint.
                     hypernetwork_name_every = f'{hypernetwork_name}-{steps_done}'
@@ -701,7 +700,8 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step,
                         torch.cuda.set_rng_state_all(cuda_rng_state)
                     hypernetwork.train()
                     if image is not None:
-                        shared.state.current_image = image
+                        shared.state.assign_current_image(image)
+
                         last_saved_image, last_text_info = images.save_image(image, images_dir, "", p.seed, p.prompt, shared.opts.samples_format, processed.infotexts[0], p=p, forced_filename=forced_filename, save_to_dirs=False)
                         last_saved_image += f", prompt: {preview_text}"
 
diff --git a/modules/img2img.py b/modules/img2img.py
index f62783c6..f4a03c57 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -59,7 +59,7 @@ def process_batch(p, input_dir, output_dir, args):
                 processed_image.save(os.path.join(output_dir, filename))
 
 
-def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, *args):
+def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, *args):
     is_batch = mode == 5
 
     if mode == 0:  # img2img
diff --git a/modules/progress.py b/modules/progress.py
new file mode 100644
index 00000000..3327b883
--- /dev/null
+++ b/modules/progress.py
@@ -0,0 +1,96 @@
+import base64
+import io
+import time
+
+import gradio as gr
+from pydantic import BaseModel, Field
+
+from modules.shared import opts
+
+import modules.shared as shared
+
+
+current_task = None
+pending_tasks = {}
+finished_tasks = []
+
+
+def start_task(id_task):
+    global current_task
+
+    current_task = id_task
+    pending_tasks.pop(id_task, None)
+
+
+def finish_task(id_task):
+    global current_task
+
+    if current_task == id_task:
+        current_task = None
+
+    finished_tasks.append(id_task)
+    if len(finished_tasks) > 16:
+        finished_tasks.pop(0)
+
+
+def add_task_to_queue(id_job):
+    pending_tasks[id_job] = time.time()
+
+
+class ProgressRequest(BaseModel):
+    id_task: str = Field(default=None, title="Task ID", description="id of the task to get progress for")
+    id_live_preview: int = Field(default=-1, title="Live preview image ID", description="id of last received last preview image")
+
+
+class ProgressResponse(BaseModel):
+    active: bool = Field(title="Whether the task is being worked on right now")
+    queued: bool = Field(title="Whether the task is in queue")
+    completed: bool = Field(title="Whether the task has already finished")
+    progress: float = Field(default=None, title="Progress", description="The progress with a range of 0 to 1")
+    eta: float = Field(default=None, title="ETA in secs")
+    live_preview: str = Field(default=None, title="Live preview image", description="Current live preview; a data: uri")
+    id_live_preview: int = Field(default=None, title="Live preview image ID", description="Send this together with next request to prevent receiving same image")
+    textinfo: str = Field(default=None, title="Info text", description="Info text used by WebUI.")
+
+
+def setup_progress_api(app):
+    return app.add_api_route("/internal/progress", progressapi, methods=["POST"], response_model=ProgressResponse)
+
+
+def progressapi(req: ProgressRequest):
+    active = req.id_task == current_task
+    queued = req.id_task in pending_tasks
+    completed = req.id_task in finished_tasks
+
+    if not active:
+        return ProgressResponse(active=active, queued=queued, completed=completed, id_live_preview=-1, textinfo="In queue..." if queued else "Waiting...")
+
+    progress = 0
+
+    if shared.state.job_count > 0:
+        progress += shared.state.job_no / shared.state.job_count
+    if shared.state.sampling_steps > 0:
+        progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps
+
+    progress = min(progress, 1)
+
+    elapsed_since_start = time.time() - shared.state.time_start
+    predicted_duration = elapsed_since_start / progress if progress > 0 else None
+    eta = predicted_duration - elapsed_since_start if predicted_duration is not None else None
+
+    id_live_preview = req.id_live_preview
+    shared.state.set_current_image()
+    if opts.live_previews_enable and shared.state.id_live_preview != req.id_live_preview:
+        image = shared.state.current_image
+        if image is not None:
+            buffered = io.BytesIO()
+            image.save(buffered, format="png")
+            live_preview = 'data:image/png;base64,' + base64.b64encode(buffered.getvalue()).decode("ascii")
+            id_live_preview = shared.state.id_live_preview
+        else:
+            live_preview = None
+    else:
+        live_preview = None
+
+    return ProgressResponse(active=active, queued=queued, completed=completed, progress=progress, eta=eta, live_preview=live_preview, id_live_preview=id_live_preview, textinfo=shared.state.textinfo)
+
diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index 7616fded..76e0e0d5 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -140,7 +140,7 @@ def store_latent(decoded):
 
     if opts.live_previews_enable and opts.show_progress_every_n_steps > 0 and shared.state.sampling_step % opts.show_progress_every_n_steps == 0:
         if not shared.parallel_processing_allowed:
-            shared.state.current_image = sample_to_image(decoded)
+            shared.state.assign_current_image(sample_to_image(decoded))
 
 
 class InterruptedException(BaseException):
diff --git a/modules/shared.py b/modules/shared.py
index 51df056c..de99aca9 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -152,6 +152,7 @@ def reload_hypernetworks():
     hypernetwork.load_hypernetwork(opts.sd_hypernetwork)
 
 
+
 class State:
     skipped = False
     interrupted = False
@@ -165,6 +166,7 @@ class State:
     current_latent = None
     current_image = None
     current_image_sampling_step = 0
+    id_live_preview = 0
     textinfo = None
     time_start = None
     need_restart = False
@@ -207,6 +209,7 @@ class State:
         self.current_latent = None
         self.current_image = None
         self.current_image_sampling_step = 0
+        self.id_live_preview = 0
         self.skipped = False
         self.interrupted = False
         self.textinfo = None
@@ -220,8 +223,8 @@ class State:
 
         devices.torch_gc()
 
-    """sets self.current_image from self.current_latent if enough sampling steps have been made after the last call to this"""
     def set_current_image(self):
+        """sets self.current_image from self.current_latent if enough sampling steps have been made after the last call to this"""
         if not parallel_processing_allowed:
             return
 
@@ -234,12 +237,16 @@ class State:
 
         import modules.sd_samplers
         if opts.show_progress_grid:
-            self.current_image = modules.sd_samplers.samples_to_image_grid(self.current_latent)
+            self.assign_current_image(modules.sd_samplers.samples_to_image_grid(self.current_latent))
         else:
-            self.current_image = modules.sd_samplers.sample_to_image(self.current_latent)
+            self.assign_current_image(modules.sd_samplers.sample_to_image(self.current_latent))
 
         self.current_image_sampling_step = self.sampling_step
 
+    def assign_current_image(self, image):
+        self.current_image = image
+        self.id_live_preview += 1
+
 
 state = State()
 state.server_start = time.time()
@@ -424,8 +431,6 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"),
 }))
 
 options_templates.update(options_section(('ui', "User interface"), {
-    "show_progressbar": OptionInfo(True, "Show progressbar"),
-    "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"),
     "return_grid": OptionInfo(True, "Show grid in results for web"),
     "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"),
     "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"),
@@ -446,6 +451,7 @@ options_templates.update(options_section(('ui', "User interface"), {
 
 options_templates.update(options_section(('ui', "Live previews"), {
     "live_previews_enable": OptionInfo(True, "Show live previews of the created image"),
+    "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"),
     "show_progress_every_n_steps": OptionInfo(10, "Show new live preview image every N sampling steps. Set to -1 to show after completion of batch.", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}),
     "show_progress_type": OptionInfo("Approx NN", "Image creation progress preview mode", gr.Radio, {"choices": ["Full", "Approx NN", "Approx cheap"]}),
     "live_preview_content": OptionInfo("Prompt", "Live preview subject", gr.Radio, {"choices": ["Combined", "Prompt", "Negative prompt"]}),
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index 3c1042ad..64abff4d 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -12,7 +12,7 @@ from modules.shared import opts, cmd_opts
 from modules.textual_inversion import autocrop
 
 
-def preprocess(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False):
+def preprocess(id_task, process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False):
     try:
         if process_caption:
             shared.interrogator.load()
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 63935878..7e4a6d24 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -345,7 +345,7 @@ def validate_train_inputs(model_name, learn_rate, batch_size, gradient_step, dat
         assert log_directory, "Log directory is empty"
 
 
-def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_embedding_every, template_filename, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
+def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_embedding_every, template_filename, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
     save_embedding_every = save_embedding_every or 0
     create_image_every = create_image_every or 0
     template_file = textual_inversion_templates.get(template_filename, None)
@@ -510,7 +510,6 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_
 
                 description = f"Training textual inversion [Epoch {epoch_num}: {epoch_step+1}/{steps_per_epoch}] loss: {loss_step:.7f}"
                 pbar.set_description(description)
-                shared.state.textinfo = description
                 if embedding_dir is not None and steps_done % save_embedding_every == 0:
                     # Before saving, change name to match current checkpoint.
                     embedding_name_every = f'{embedding_name}-{steps_done}'
@@ -560,7 +559,8 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_
                         shared.sd_model.first_stage_model.to(devices.cpu)
 
                     if image is not None:
-                        shared.state.current_image = image
+                        shared.state.assign_current_image(image)
+
                         last_saved_image, last_text_info = images.save_image(image, images_dir, "", p.seed, p.prompt, shared.opts.samples_format, processed.infotexts[0], p=p, forced_filename=forced_filename, save_to_dirs=False)
                         last_saved_image += f", prompt: {preview_text}"
 
diff --git a/modules/txt2img.py b/modules/txt2img.py
index 38b5f591..ca5d4550 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -8,7 +8,7 @@ import modules.processing as processing
 from modules.ui import plaintext_to_html
 
 
-def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, *args):
+def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_style: str, prompt_style2: str, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, *args):
     p = StableDiffusionProcessingTxt2Img(
         sd_model=shared.sd_model,
         outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples,
diff --git a/modules/ui.py b/modules/ui.py
index 2425c66f..ff33236b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -356,7 +356,7 @@ def create_toprow(is_img2img):
                 button_deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru")
 
         with gr.Column(scale=1):
-            with gr.Row():
+            with gr.Row(elem_id=f"{id_part}_generate_box"):
                 skip = gr.Button('Skip', elem_id=f"{id_part}_skip")
                 interrupt = gr.Button('Interrupt', elem_id=f"{id_part}_interrupt")
                 submit = gr.Button('Generate', elem_id=f"{id_part}_generate", variant='primary')
@@ -384,9 +384,7 @@ def create_toprow(is_img2img):
 
 
 def setup_progressbar(*args, **kwargs):
-    import modules.ui_progress
-
-    modules.ui_progress.setup_progressbar(*args, **kwargs)
+    pass
 
 
 def apply_setting(key, value):
@@ -479,8 +477,8 @@ Requested path was: {f}
             else:
                 sp.Popen(["xdg-open", path])
 
-    with gr.Column(variant='panel'):
-            with gr.Group():
+    with gr.Column(variant='panel', elem_id=f"{tabname}_results"):
+            with gr.Group(elem_id=f"{tabname}_gallery_container"):
                 result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery").style(grid=4)
 
             generation_info = None
@@ -595,15 +593,6 @@ def create_ui():
         dummy_component = gr.Label(visible=False)
         txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False)
 
-        with gr.Row(elem_id='txt2img_progress_row'):
-            with gr.Column(scale=1):
-                pass
-
-            with gr.Column(scale=1):
-                progressbar = gr.HTML(elem_id="txt2img_progressbar")
-                txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False)
-                setup_progressbar(progressbar, txt2img_preview, 'txt2img')
-
         with gr.Row().style(equal_height=False):
             with gr.Column(variant='panel', elem_id="txt2img_settings"):
                 for category in ordered_ui_categories():
@@ -682,6 +671,7 @@ def create_ui():
                 fn=wrap_gradio_gpu_call(modules.txt2img.txt2img, extra_outputs=[None, '', '']),
                 _js="submit",
                 inputs=[
+                    dummy_component,
                     txt2img_prompt,
                     txt2img_negative_prompt,
                     txt2img_prompt_style,
@@ -782,16 +772,7 @@ def create_ui():
     with gr.Blocks(analytics_enabled=False) as img2img_interface:
         img2img_prompt, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,token_counter, token_button = create_toprow(is_img2img=True)
 
-        with gr.Row(elem_id='img2img_progress_row'):
-            img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False)
-
-            with gr.Column(scale=1):
-                pass
-
-            with gr.Column(scale=1):
-                progressbar = gr.HTML(elem_id="img2img_progressbar")
-                img2img_preview = gr.Image(elem_id='img2img_preview', visible=False)
-                setup_progressbar(progressbar, img2img_preview, 'img2img')
+        img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False)
 
         with FormRow().style(equal_height=False):
             with gr.Column(variant='panel', elem_id="img2img_settings"):
@@ -958,6 +939,7 @@ def create_ui():
                 fn=wrap_gradio_gpu_call(modules.img2img.img2img, extra_outputs=[None, '', '']),
                 _js="submit_img2img",
                 inputs=[
+                    dummy_component,
                     dummy_component,
                     img2img_prompt,
                     img2img_negative_prompt,
@@ -1335,15 +1317,11 @@ def create_ui():
 
                 script_callbacks.ui_train_tabs_callback(params)
 
-            with gr.Column():
-                progressbar = gr.HTML(elem_id="ti_progressbar")
+            with gr.Column(elem_id='ti_gallery_container'):
                 ti_output = gr.Text(elem_id="ti_output", value="", show_label=False)
-
                 ti_gallery = gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(grid=4)
-                ti_preview = gr.Image(elem_id='ti_preview', visible=False)
                 ti_progress = gr.HTML(elem_id="ti_progress", value="")
                 ti_outcome = gr.HTML(elem_id="ti_error", value="")
-                setup_progressbar(progressbar, ti_preview, 'ti', textinfo=ti_progress)
 
         create_embedding.click(
             fn=modules.textual_inversion.ui.create_embedding,
@@ -1384,6 +1362,7 @@ def create_ui():
             fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]),
             _js="start_training_textual_inversion",
             inputs=[
+                dummy_component,
                 process_src,
                 process_dst,
                 process_width,
@@ -1411,6 +1390,7 @@ def create_ui():
             fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.train_embedding, extra_outputs=[gr.update()]),
             _js="start_training_textual_inversion",
             inputs=[
+                dummy_component,
                 train_embedding_name,
                 embedding_learn_rate,
                 batch_size,
@@ -1443,6 +1423,7 @@ def create_ui():
             fn=wrap_gradio_gpu_call(modules.hypernetworks.ui.train_hypernetwork, extra_outputs=[gr.update()]),
             _js="start_training_textual_inversion",
             inputs=[
+                dummy_component,
                 train_hypernetwork_name,
                 hypernetwork_learn_rate,
                 batch_size,
diff --git a/modules/ui_progress.py b/modules/ui_progress.py
deleted file mode 100644
index 7cd312e4..00000000
--- a/modules/ui_progress.py
+++ /dev/null
@@ -1,101 +0,0 @@
-import time
-
-import gradio as gr
-
-from modules.shared import opts
-
-import modules.shared as shared
-
-
-def calc_time_left(progress, threshold, label, force_display, show_eta):
-    if progress == 0:
-        return ""
-    else:
-        time_since_start = time.time() - shared.state.time_start
-        eta = (time_since_start/progress)
-        eta_relative = eta-time_since_start
-        if (eta_relative > threshold and show_eta) or force_display:
-            if eta_relative > 3600:
-                return label + time.strftime('%H:%M:%S', time.gmtime(eta_relative))
-            elif eta_relative > 60:
-                return label + time.strftime('%M:%S',  time.gmtime(eta_relative))
-            else:
-                return label + time.strftime('%Ss',  time.gmtime(eta_relative))
-        else:
-            return ""
-
-
-def check_progress_call(id_part):
-    if shared.state.job_count == 0:
-        return "", gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
-
-    progress = 0
-
-    if shared.state.job_count > 0:
-        progress += shared.state.job_no / shared.state.job_count
-    if shared.state.sampling_steps > 0:
-        progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps
-
-    # Show progress percentage and time left at the same moment, and base it also on steps done
-    show_eta = progress >= 0.01 or shared.state.sampling_step >= 10
-
-    time_left = calc_time_left(progress, 1, " ETA: ", shared.state.time_left_force_display, show_eta)
-    if time_left != "":
-        shared.state.time_left_force_display = True
-
-    progress = min(progress, 1)
-
-    progressbar = ""
-    if opts.show_progressbar:
-        progressbar = f"""<div class='progressDiv'><div class='progress' style="overflow:visible;width:{progress * 100}%;white-space:nowrap;">{"&nbsp;" * 2 + str(int(progress*100))+"%" + time_left if show_eta else ""}</div></div>"""
-
-    image = gr.update(visible=False)
-    preview_visibility = gr.update(visible=False)
-
-    if opts.live_previews_enable:
-        shared.state.set_current_image()
-        image = shared.state.current_image
-
-        if image is None:
-            image = gr.update(value=None)
-        else:
-            preview_visibility = gr.update(visible=True)
-
-    if shared.state.textinfo is not None:
-        textinfo_result = gr.HTML.update(value=shared.state.textinfo, visible=True)
-    else:
-        textinfo_result = gr.update(visible=False)
-
-    return f"<span id='{id_part}_progress_span' style='display: none'>{time.time()}</span><p>{progressbar}</p>", preview_visibility, image, textinfo_result
-
-
-def check_progress_call_initial(id_part):
-    shared.state.job_count = -1
-    shared.state.current_latent = None
-    shared.state.current_image = None
-    shared.state.textinfo = None
-    shared.state.time_start = time.time()
-    shared.state.time_left_force_display = False
-
-    return check_progress_call(id_part)
-
-
-def setup_progressbar(progressbar, preview, id_part, textinfo=None):
-    if textinfo is None:
-        textinfo = gr.HTML(visible=False)
-
-    check_progress = gr.Button('Check progress', elem_id=f"{id_part}_check_progress", visible=False)
-    check_progress.click(
-        fn=lambda: check_progress_call(id_part),
-        show_progress=False,
-        inputs=[],
-        outputs=[progressbar, preview, preview, textinfo],
-    )
-
-    check_progress_initial = gr.Button('Check progress (first)', elem_id=f"{id_part}_check_progress_initial", visible=False)
-    check_progress_initial.click(
-        fn=lambda: check_progress_call_initial(id_part),
-        show_progress=False,
-        inputs=[],
-        outputs=[progressbar, preview, preview, textinfo],
-    )
diff --git a/style.css b/style.css
index 2d484e06..786b71d1 100644
--- a/style.css
+++ b/style.css
@@ -305,26 +305,42 @@ input[type="range"]{
 }
 
 .progressDiv{
-  width: 100%;
-  height: 20px;
-  background: #b4c0cc;
-  border-radius: 8px;
+    position: absolute;
+    height: 20px;
+    top: -20px;
+    background: #b4c0cc;
+    border-radius: 8px !important;
 }
 
 .dark .progressDiv{
-  background: #424c5b;
+    background: #424c5b;
 }
 
 .progressDiv .progress{
-  width: 0%;
-  height: 20px;
-  background: #0060df;
-  color: white;
-  font-weight: bold;
-  line-height: 20px;
-  padding: 0 8px 0 0;
-  text-align: right;
-  border-radius: 8px;
+    width: 0%;
+    height: 20px;
+    background: #0060df;
+    color: white;
+    font-weight: bold;
+    line-height: 20px;
+    padding: 0 8px 0 0;
+    text-align: right;
+    border-radius: 8px;
+    overflow: visible;
+    white-space: nowrap;
+}
+
+.livePreview{
+    position: absolute;
+    z-index: 300;
+    background-color: white;
+    margin: -4px;
+}
+
+.livePreview img{
+    object-fit: contain;
+    width: 100%;
+    height: 100%;
 }
 
 #lightboxModal{
@@ -450,23 +466,25 @@ input[type="range"]{
     display:none
 }
 
-#txt2img_interrupt, #img2img_interrupt{
-  position: absolute;
-  width: 50%;
-  height: 72px;
-  background: #b4c0cc;
-  border-radius: 0px;
-  display: none;
+#txt2img_generate_box, #img2img_generate_box{
+    position: relative;
+}
+
+#txt2img_interrupt, #img2img_interrupt, #txt2img_skip, #img2img_skip{
+    position: absolute;
+    width: 50%;
+    height: 100%;
+    background: #b4c0cc;
+    display: none;
 }
 
+#txt2img_interrupt, #img2img_interrupt{
+    right: 0;
+    border-radius: 0 0.5rem 0.5rem 0;
+}
 #txt2img_skip, #img2img_skip{
-  position: absolute;
-  width: 50%;
-  right: 0px;
-  height: 72px;
-  background: #b4c0cc;
-  border-radius: 0px;
-  display: none;
+    left: 0;
+    border-radius: 0.5rem 0 0 0.5rem;
 }
 
 .red {
diff --git a/webui.py b/webui.py
index 1fff80da..4624fe18 100644
--- a/webui.py
+++ b/webui.py
@@ -34,6 +34,7 @@ import modules.sd_vae
 import modules.txt2img
 import modules.script_callbacks
 import modules.textual_inversion.textual_inversion
+import modules.progress
 
 import modules.ui
 from modules import modelloader
@@ -181,6 +182,8 @@ def webui():
 
         app.add_middleware(GZipMiddleware, minimum_size=1000)
 
+        modules.progress.setup_progress_api(app)
+
         if launch_api:
             create_api(app)
 
-- 
cgit v1.2.3


From b6ce041cdf722b400df9b5eac306d0cb049923d7 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 15 Jan 2023 20:29:48 +0300
Subject: put interrupt and skip buttons back where they were

---
 modules/ui.py | 2 +-
 style.css     | 8 ++++----
 2 files changed, 5 insertions(+), 5 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index ff33236b..7a357f9a 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -357,8 +357,8 @@ def create_toprow(is_img2img):
 
         with gr.Column(scale=1):
             with gr.Row(elem_id=f"{id_part}_generate_box"):
-                skip = gr.Button('Skip', elem_id=f"{id_part}_skip")
                 interrupt = gr.Button('Interrupt', elem_id=f"{id_part}_interrupt")
+                skip = gr.Button('Skip', elem_id=f"{id_part}_skip")
                 submit = gr.Button('Generate', elem_id=f"{id_part}_generate", variant='primary')
 
                 skip.click(
diff --git a/style.css b/style.css
index 5bf1c6f9..750fe315 100644
--- a/style.css
+++ b/style.css
@@ -480,13 +480,13 @@ input[type="range"]{
 }
 
 #txt2img_interrupt, #img2img_interrupt{
-    right: 0;
-    border-radius: 0 0.5rem 0.5rem 0;
-}
-#txt2img_skip, #img2img_skip{
     left: 0;
     border-radius: 0.5rem 0 0 0.5rem;
 }
+#txt2img_skip, #img2img_skip{
+    right: 0;
+    border-radius: 0 0.5rem 0.5rem 0;
+}
 
 .red {
 	color: red;
-- 
cgit v1.2.3


From 3db22e6ee45193559a2c3ba44ab672b067245f99 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 15 Jan 2023 23:32:38 +0300
Subject: rename masking to inpaint in UI make inpaint go to the right place
 for users who don't have it in config string

---
 modules/shared.py | 2 +-
 modules/ui.py     | 6 +++---
 2 files changed, 4 insertions(+), 4 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/shared.py b/modules/shared.py
index 3bdc375b..f06ae610 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -116,7 +116,7 @@ restricted_opts = {
 }
 
 ui_reorder_categories = [
-    "masking",
+    "inpaint",
     "sampler",
     "dimensions",
     "cfg",
diff --git a/modules/ui.py b/modules/ui.py
index b3d4af3e..20b66165 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -570,9 +570,9 @@ def create_sampler_and_steps_selection(choices, tabname):
 
 
 def ordered_ui_categories():
-    user_order = {x.strip(): i for i, x in enumerate(shared.opts.ui_reorder.split(","))}
+    user_order = {x.strip(): i * 2 + 1 for i, x in enumerate(shared.opts.ui_reorder.split(","))}
 
-    for i, category in sorted(enumerate(shared.ui_reorder_categories), key=lambda x: user_order.get(x[1], x[0] + 1000)):
+    for i, category in sorted(enumerate(shared.ui_reorder_categories), key=lambda x: user_order.get(x[1], x[0] * 2 + 0)):
         yield category
 
 
@@ -889,7 +889,7 @@ def create_ui():
                         with FormGroup(elem_id="img2img_script_container"):
                             custom_inputs = modules.scripts.scripts_img2img.setup_ui()
 
-                    elif category == "masking":
+                    elif category == "inpaint":
                         with FormGroup(elem_id="inpaint_controls", visible=False) as inpaint_controls:
                             with FormRow():
                                 mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id="img2img_mask_blur")
-- 
cgit v1.2.3


From 4688bfff55dd6607e6608524fb219f97dc6fe8bb Mon Sep 17 00:00:00 2001
From: dan <guaneec@gmail.com>
Date: Tue, 17 Jan 2023 17:16:43 +0800
Subject: Add auto-sized cropping UI

---
 modules/textual_inversion/preprocess.py | 38 ++++++++++++++++++++++++++++++---
 modules/ui.py                           | 28 +++++++++++++++++++++++-
 2 files changed, 62 insertions(+), 4 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index 64abff4d..86c1cd33 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -12,7 +12,7 @@ from modules.shared import opts, cmd_opts
 from modules.textual_inversion import autocrop
 
 
-def preprocess(id_task, process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False):
+def preprocess(id_task, process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False, process_multicrop=None, process_multicrop_mindim=None, process_multicrop_maxdim=None, process_multicrop_minarea=None, process_multicrop_maxarea=None, process_multicrop_objective=None, process_multicrop_threshold=None):
     try:
         if process_caption:
             shared.interrogator.load()
@@ -20,7 +20,7 @@ def preprocess(id_task, process_src, process_dst, process_width, process_height,
         if process_caption_deepbooru:
             deepbooru.model.start()
 
-        preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru, split_threshold, overlap_ratio, process_focal_crop, process_focal_crop_face_weight, process_focal_crop_entropy_weight, process_focal_crop_edges_weight, process_focal_crop_debug)
+        preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru, split_threshold, overlap_ratio, process_focal_crop, process_focal_crop_face_weight, process_focal_crop_entropy_weight, process_focal_crop_edges_weight, process_focal_crop_debug, process_multicrop, process_multicrop_mindim, process_multicrop_maxdim, process_multicrop_minarea, process_multicrop_maxarea, process_multicrop_objective, process_multicrop_threshold)
 
     finally:
 
@@ -109,8 +109,32 @@ def split_pic(image, inverse_xy, width, height, overlap_ratio):
             splitted = image.crop((0, y, to_w, y + to_h))
         yield splitted
 
+# not using torchvision.transforms.CenterCrop because it doesn't allow float regions
+def center_crop(image: Image, w: int, h: int):
+    iw, ih = image.size
+    if ih / h < iw / w:
+        sw = w * ih / h
+        box = (iw - sw) / 2, 0, iw - (iw - sw) / 2, ih
+    else:
+        sh = h * iw / w
+        box = 0, (ih - sh) / 2, iw, ih - (ih - sh) / 2
+    return image.resize((w, h), Image.Resampling.LANCZOS, box)
+
 
-def preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False):
+def multicrop_pic(image: Image, mindim, maxdim, minarea, maxarea, objective, threshold):
+    iw, ih = image.size
+    err = lambda w, h: 1-(lambda x: x if x < 1 else 1/x)(iw/ih/(w/h))
+    try:
+        w, h = max(((w, h) for w in range(mindim, maxdim+1, 64) for h in range(mindim, maxdim+1, 64)
+            if minarea <= w * h <= maxarea and err(w, h) <= threshold),
+            key= lambda wh: ((objective=='Maximize area')*wh[0]*wh[1], -err(*wh))
+        )
+    except ValueError:
+        return
+    return center_crop(image, w, h)
+    
+
+def preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False, process_multicrop=None, process_multicrop_mindim=None, process_multicrop_maxdim=None, process_multicrop_minarea=None, process_multicrop_maxarea=None, process_multicrop_objective=None, process_multicrop_threshold=None):
     width = process_width
     height = process_height
     src = os.path.abspath(process_src)
@@ -194,6 +218,14 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre
                 save_pic(focal, index, params, existing_caption=existing_caption)
             process_default_resize = False
 
+        if process_multicrop:
+            cropped = multicrop_pic(img, process_multicrop_mindim, process_multicrop_maxdim, process_multicrop_minarea, process_multicrop_maxarea, process_multicrop_objective, process_multicrop_threshold)
+            if cropped is not None:
+                save_pic(cropped, index, params, existing_caption=existing_caption)
+            else:
+                print(f"skipped {img.width}x{img.height} image {filename} (can't find suitable size within error threshold)")
+            process_default_resize = False
+
         if process_default_resize:
             img = images.resize_image(1, img, width, height)
             save_pic(img, index, params, existing_caption=existing_caption)
diff --git a/modules/ui.py b/modules/ui.py
index 20b66165..bbce9acd 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1226,6 +1226,7 @@ def create_ui():
                         process_flip = gr.Checkbox(label='Create flipped copies', elem_id="train_process_flip")
                         process_split = gr.Checkbox(label='Split oversized images', elem_id="train_process_split")
                         process_focal_crop = gr.Checkbox(label='Auto focal point crop', elem_id="train_process_focal_crop")
+                        process_multicrop = gr.Checkbox(label='Auto-sized crop', elem_id="train_process_multicrop")
                         process_caption = gr.Checkbox(label='Use BLIP for caption', elem_id="train_process_caption")
                         process_caption_deepbooru = gr.Checkbox(label='Use deepbooru for caption', visible=True, elem_id="train_process_caption_deepbooru")
 
@@ -1238,7 +1239,19 @@ def create_ui():
                         process_focal_crop_entropy_weight = gr.Slider(label='Focal point entropy weight', value=0.15, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_entropy_weight")
                         process_focal_crop_edges_weight = gr.Slider(label='Focal point edges weight', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_edges_weight")
                         process_focal_crop_debug = gr.Checkbox(label='Create debug image', elem_id="train_process_focal_crop_debug")
-
+                    
+                    with gr.Column(visible=False) as process_multicrop_col:
+                        gr.Markdown('Each image is center-cropped with an automatically chosen width and height.')
+                        with gr.Row():
+                            process_multicrop_mindim = gr.Slider(minimum=64, maximum=2048, step=8, label="Dimension lower bound", value=384, elem_id="train_process_multicrop_mindim")
+                            process_multicrop_maxdim = gr.Slider(minimum=64, maximum=2048, step=8, label="Dimension upper bound", value=768, elem_id="train_process_multicrop_maxdim")
+                        with gr.Row():
+                            process_multicrop_minarea = gr.Slider(minimum=64*64, maximum=2048*2048, step=1, label="Area lower bound", value=64*64, elem_id="train_process_multicrop_minarea")
+                            process_multicrop_maxarea = gr.Slider(minimum=64*64, maximum=2048*2048, step=1, label="Area upper bound", value=640*640, elem_id="train_process_multicrop_maxarea")
+                        with gr.Row():
+                            process_multicrop_objective = gr.Radio(["Maximize area", "Minimize error"], value="Maximize area", label="Resizing objective", elem_id="train_process_multicrop_objective")
+                            process_multicrop_threshold = gr.Slider(minimum=0, maximum=1, step=0.01, label="Error threshold", value=0.1, elem_id="train_process_multicrop_threshold")
+   
                     with gr.Row():
                         with gr.Column(scale=3):
                             gr.HTML(value="")
@@ -1260,6 +1273,12 @@ def create_ui():
                         outputs=[process_focal_crop_row],
                     )
 
+                    process_multicrop.change(
+                        fn=lambda show: gr_show(show),
+                        inputs=[process_multicrop],
+                        outputs=[process_multicrop_col],
+                    )
+
                 def get_textual_inversion_template_names():
                     return sorted([x for x in textual_inversion.textual_inversion_templates])
 
@@ -1379,6 +1398,13 @@ def create_ui():
                 process_focal_crop_entropy_weight,
                 process_focal_crop_edges_weight,
                 process_focal_crop_debug,
+                process_multicrop,
+                process_multicrop_mindim,
+                process_multicrop_maxdim,
+                process_multicrop_minarea,
+                process_multicrop_maxarea,
+                process_multicrop_objective,
+                process_multicrop_threshold,
             ],
             outputs=[
                 ti_output,
-- 
cgit v1.2.3


From 6faae2323963f9b0e0086a85b9d0472a24fbaa73 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 18 Jan 2023 14:33:09 +0300
Subject: repair broken quicksettings when some form-requiring options are
 added to it

---
 modules/ui.py | 2 +-
 style.css     | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index e1f98d23..6d70a795 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1659,7 +1659,7 @@ def create_ui():
     interfaces += [(extensions_interface, "Extensions", "extensions")]
 
     with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion") as demo:
-        with gr.Row(elem_id="quicksettings"):
+        with gr.Row(elem_id="quicksettings", variant="compact"):
             for i, k, item in sorted(quicksettings_list, key=lambda x: quicksettings_names.get(x[1], x[0])):
                 component = create_setting_component(k, is_quicksettings=True)
                 component_dict[k] = component
diff --git a/style.css b/style.css
index b6239142..fb58b6c3 100644
--- a/style.css
+++ b/style.css
@@ -530,7 +530,7 @@ input[type="range"]{
     gap: 0.4em;
 }
 
-#quicksettings > div{
+#quicksettings > div, #quicksettings > fieldset{
     max-width: 24em;
     min-width: 24em;
     padding: 0;
-- 
cgit v1.2.3


From 8683427bd9315d2fda0d2f9644c8b1f6a182da55 Mon Sep 17 00:00:00 2001
From: Vladimir Repin <32306715+mezotaken@users.noreply.github.com>
Date: Wed, 18 Jan 2023 20:16:52 +0300
Subject: Process interrogation on all img2img subtabs

---
 javascript/ui.js |  7 +++++++
 modules/ui.py    | 50 +++++++++++++++++++++++++++++++++++++++++++-------
 2 files changed, 50 insertions(+), 7 deletions(-)

(limited to 'modules/ui.py')

diff --git a/javascript/ui.js b/javascript/ui.js
index 954beadd..7d3d57a3 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -109,6 +109,13 @@ function get_extras_tab_index(){
     return [get_tab_index('mode_extras'), get_tab_index('extras_resize_mode'), ...args]
 }
 
+function get_img2img_tab_index() {
+    let res = args_to_array(arguments)
+    res.splice(-2)
+    res[0] = get_tab_index('mode_img2img')
+    return res
+}
+
 function create_submit_args(args){
     res = []
     for(var i=0;i<args.length;i++){
diff --git a/modules/ui.py b/modules/ui.py
index 20b66165..78c0c92a 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -204,9 +204,31 @@ def apply_styles(prompt, prompt_neg, style1_name, style2_name):
     return [gr.Textbox.update(value=prompt), gr.Textbox.update(value=prompt_neg), gr.Dropdown.update(value="None"), gr.Dropdown.update(value="None")]
 
 
+def process_interrogate(interrogation_function, mode, ii_input_dir, ii_output_dir, *ii_singles):
+    if mode in {0, 1, 3, 4}:
+        return [interrogation_function(ii_singles[mode]), None]
+    elif mode == 2:
+        return [interrogation_function(ii_singles[mode]["image"]), None]
+    elif mode == 5:
+        assert not shared.cmd_opts.hide_ui_dir_config, "Launched with --hide-ui-dir-config, batch img2img disabled"
+        images = shared.listfiles(ii_input_dir)
+        print(f"Will process {len(images)} images.")
+        if ii_output_dir != "":
+            os.makedirs(ii_output_dir, exist_ok=True)
+        else:
+            ii_output_dir = ii_input_dir
+
+        for image in images:
+            img = Image.open(image)
+            filename = os.path.basename(image)
+            left, _ = os.path.splitext(filename)
+            print(interrogation_function(img), file=open(os.path.join(ii_output_dir, left + ".txt"), 'a'))
+
+        return [gr_show(True), None]
+
+
 def interrogate(image):
     prompt = shared.interrogator.interrogate(image.convert("RGB"))
-
     return gr_show(True) if prompt is None else prompt
 
 
@@ -983,19 +1005,33 @@ def create_ui():
                 show_progress=False,
             )
 
+            interrogate_args = dict(
+                _js="get_img2img_tab_index",
+                inputs=[
+                    dummy_component,
+                    img2img_batch_input_dir,
+                    img2img_batch_output_dir,
+                    init_img,
+                    sketch,
+                    init_img_with_mask,
+                    inpaint_color_sketch,
+                    init_img_inpaint,
+                ],
+                outputs=[img2img_prompt, dummy_component],
+                show_progress=False,
+            )
+
             img2img_prompt.submit(**img2img_args)
             submit.click(**img2img_args)
 
             img2img_interrogate.click(
-                fn=interrogate,
-                inputs=[init_img],
-                outputs=[img2img_prompt],
+                fn=lambda *args : process_interrogate(interrogate, *args),
+                **interrogate_args,
             )
 
             img2img_deepbooru.click(
-                fn=interrogate_deepbooru,
-                inputs=[init_img],
-                outputs=[img2img_prompt],
+                fn=lambda *args : process_interrogate(interrogate_deepbooru, *args),
+                **interrogate_args,
             )
 
             prompts = [(txt2img_prompt, txt2img_negative_prompt), (img2img_prompt, img2img_negative_prompt)]
-- 
cgit v1.2.3


From 924e222004ab54273806c5f2ca7a0e7cfa76ad83 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 18 Jan 2023 23:04:24 +0300
Subject: add option to show/hide warnings removed hiding warnings from LDSR
 fixed/reworked few places that produced warnings

---
 extensions-builtin/LDSR/ldsr_model_arch.py     |  3 --
 javascript/localization.js                     |  2 +-
 modules/hypernetworks/hypernetwork.py          |  7 ++++-
 modules/sd_hijack.py                           |  8 ------
 modules/sd_hijack_checkpoint.py                | 38 +++++++++++++++++++++++++-
 modules/shared.py                              |  1 +
 modules/textual_inversion/textual_inversion.py |  6 +++-
 modules/ui.py                                  | 31 ++++++++++++---------
 scripts/prompts_from_file.py                   |  2 +-
 style.css                                      |  5 ++--
 10 files changed, 71 insertions(+), 32 deletions(-)

(limited to 'modules/ui.py')

diff --git a/extensions-builtin/LDSR/ldsr_model_arch.py b/extensions-builtin/LDSR/ldsr_model_arch.py
index 0ad49f4e..bc11cc6e 100644
--- a/extensions-builtin/LDSR/ldsr_model_arch.py
+++ b/extensions-builtin/LDSR/ldsr_model_arch.py
@@ -1,7 +1,6 @@
 import os
 import gc
 import time
-import warnings
 
 import numpy as np
 import torch
@@ -15,8 +14,6 @@ from ldm.models.diffusion.ddim import DDIMSampler
 from ldm.util import instantiate_from_config, ismap
 from modules import shared, sd_hijack
 
-warnings.filterwarnings("ignore", category=UserWarning)
-
 cached_ldsr_model: torch.nn.Module = None
 
 
diff --git a/javascript/localization.js b/javascript/localization.js
index bf9e1506..1a5a1dbb 100644
--- a/javascript/localization.js
+++ b/javascript/localization.js
@@ -11,7 +11,7 @@ ignore_ids_for_localization={
     train_embedding: 'OPTION',
     train_hypernetwork: 'OPTION',
     txt2img_styles: 'OPTION',
-    img2img_styles 'OPTION',
+    img2img_styles: 'OPTION',
     setting_random_artist_categories: 'SPAN',
     setting_face_restoration_model: 'SPAN',
     setting_realesrgan_enabled_models: 'SPAN',
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index c963fc40..74e78582 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -12,7 +12,7 @@ import torch
 import tqdm
 from einops import rearrange, repeat
 from ldm.util import default
-from modules import devices, processing, sd_models, shared, sd_samplers, hashes
+from modules import devices, processing, sd_models, shared, sd_samplers, hashes, sd_hijack_checkpoint
 from modules.textual_inversion import textual_inversion, logging
 from modules.textual_inversion.learn_schedule import LearnRateScheduler
 from torch import einsum
@@ -575,6 +575,8 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
 
     pbar = tqdm.tqdm(total=steps - initial_step)
     try:
+        sd_hijack_checkpoint.add()
+
         for i in range((steps-initial_step) * gradient_step):
             if scheduler.finished:
                 break
@@ -724,6 +726,9 @@ Last saved image: {html.escape(last_saved_image)}<br/>
         pbar.close()
         hypernetwork.eval()
         #report_statistics(loss_dict)
+        sd_hijack_checkpoint.remove()
+
+
 
     filename = os.path.join(shared.cmd_opts.hypernetwork_dir, f'{hypernetwork_name}.pt')
     hypernetwork.optimizer_name = optimizer_name
diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 6b0d95af..870eba88 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -69,12 +69,6 @@ def undo_optimizations():
     ldm.modules.diffusionmodules.model.AttnBlock.forward = diffusionmodules_model_AttnBlock_forward
 
 
-def fix_checkpoint():
-    ldm.modules.attention.BasicTransformerBlock.forward = sd_hijack_checkpoint.BasicTransformerBlock_forward
-    ldm.modules.diffusionmodules.openaimodel.ResBlock.forward = sd_hijack_checkpoint.ResBlock_forward
-    ldm.modules.diffusionmodules.openaimodel.AttentionBlock.forward = sd_hijack_checkpoint.AttentionBlock_forward
-
-
 class StableDiffusionModelHijack:
     fixes = None
     comments = []
@@ -106,8 +100,6 @@ class StableDiffusionModelHijack:
         self.optimization_method = apply_optimizations()
 
         self.clip = m.cond_stage_model
-        
-        fix_checkpoint()
 
         def flatten(el):
             flattened = [flatten(children) for children in el.children()]
diff --git a/modules/sd_hijack_checkpoint.py b/modules/sd_hijack_checkpoint.py
index 5712972f..2604d969 100644
--- a/modules/sd_hijack_checkpoint.py
+++ b/modules/sd_hijack_checkpoint.py
@@ -1,10 +1,46 @@
 from torch.utils.checkpoint import checkpoint
 
+import ldm.modules.attention
+import ldm.modules.diffusionmodules.openaimodel
+
+
 def BasicTransformerBlock_forward(self, x, context=None):
     return checkpoint(self._forward, x, context)
 
+
 def AttentionBlock_forward(self, x):
     return checkpoint(self._forward, x)
 
+
 def ResBlock_forward(self, x, emb):
-    return checkpoint(self._forward, x, emb)
\ No newline at end of file
+    return checkpoint(self._forward, x, emb)
+
+
+stored = []
+
+
+def add():
+    if len(stored) != 0:
+        return
+
+    stored.extend([
+        ldm.modules.attention.BasicTransformerBlock.forward,
+        ldm.modules.diffusionmodules.openaimodel.ResBlock.forward,
+        ldm.modules.diffusionmodules.openaimodel.AttentionBlock.forward
+    ])
+
+    ldm.modules.attention.BasicTransformerBlock.forward = BasicTransformerBlock_forward
+    ldm.modules.diffusionmodules.openaimodel.ResBlock.forward = ResBlock_forward
+    ldm.modules.diffusionmodules.openaimodel.AttentionBlock.forward = AttentionBlock_forward
+
+
+def remove():
+    if len(stored) == 0:
+        return
+
+    ldm.modules.attention.BasicTransformerBlock.forward = stored[0]
+    ldm.modules.diffusionmodules.openaimodel.ResBlock.forward = stored[1]
+    ldm.modules.diffusionmodules.openaimodel.AttentionBlock.forward = stored[2]
+
+    stored.clear()
+
diff --git a/modules/shared.py b/modules/shared.py
index a708f23c..ddb97f99 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -369,6 +369,7 @@ options_templates.update(options_section(('face-restoration', "Face restoration"
 }))
 
 options_templates.update(options_section(('system', "System"), {
+    "show_warnings": OptionInfo(False, "Show warnings in console."),
     "memmon_poll_rate": OptionInfo(8, "VRAM usage polls per second during generation. Set to 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}),
     "samples_log_stdout": OptionInfo(False, "Always print all generation info to standard output"),
     "multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job."),
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 7e4a6d24..5a7be422 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -15,7 +15,7 @@ import numpy as np
 from PIL import Image, PngImagePlugin
 from torch.utils.tensorboard import SummaryWriter
 
-from modules import shared, devices, sd_hijack, processing, sd_models, images, sd_samplers
+from modules import shared, devices, sd_hijack, processing, sd_models, images, sd_samplers, sd_hijack_checkpoint
 import modules.textual_inversion.dataset
 from modules.textual_inversion.learn_schedule import LearnRateScheduler
 
@@ -452,6 +452,8 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
 
     pbar = tqdm.tqdm(total=steps - initial_step)
     try:
+        sd_hijack_checkpoint.add()
+
         for i in range((steps-initial_step) * gradient_step):
             if scheduler.finished:
                 break
@@ -617,9 +619,11 @@ Last saved image: {html.escape(last_saved_image)}<br/>
         pbar.close()
         shared.sd_model.first_stage_model.to(devices.device)
         shared.parallel_processing_allowed = old_parallel_processing_allowed
+        sd_hijack_checkpoint.remove()
 
     return embedding, filename
 
+
 def save_embedding(embedding, optimizer, checkpoint, embedding_name, filename, remove_cached_checksum=True):
     old_embedding_name = embedding.name
     old_sd_checkpoint = embedding.sd_checkpoint if hasattr(embedding, "sd_checkpoint") else None
diff --git a/modules/ui.py b/modules/ui.py
index 6d70a795..25818fb0 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -11,6 +11,7 @@ import tempfile
 import time
 import traceback
 from functools import partial, reduce
+import warnings
 
 import gradio as gr
 import gradio.routes
@@ -41,6 +42,8 @@ from modules.textual_inversion import textual_inversion
 import modules.hypernetworks.ui
 from modules.generation_parameters_copypaste import image_from_url_text
 
+warnings.filterwarnings("default" if opts.show_warnings else "ignore", category=UserWarning)
+
 # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI
 mimetypes.init()
 mimetypes.add_type('application/javascript', '.js')
@@ -417,17 +420,16 @@ def apply_setting(key, value):
     return value
 
 
-def update_generation_info(args):
-    generation_info, html_info, img_index = args
+def update_generation_info(generation_info, html_info, img_index):
     try:
         generation_info = json.loads(generation_info)
         if img_index < 0 or img_index >= len(generation_info["infotexts"]):
-            return html_info
-        return plaintext_to_html(generation_info["infotexts"][img_index])
+            return html_info, gr.update()
+        return plaintext_to_html(generation_info["infotexts"][img_index]), gr.update()
     except Exception:
         pass
     # if the json parse or anything else fails, just return the old html_info
-    return html_info
+    return html_info, gr.update()
 
 
 def create_refresh_button(refresh_component, refresh_method, refreshed_args, elem_id):
@@ -508,10 +510,9 @@ Requested path was: {f}
                             generation_info_button = gr.Button(visible=False, elem_id=f"{tabname}_generation_info_button")
                             generation_info_button.click(
                                 fn=update_generation_info,
-                                _js="(x, y) => [x, y, selected_gallery_index()]",
-                                inputs=[generation_info, html_info],
-                                outputs=[html_info],
-                                preprocess=False
+                                _js="function(x, y, z){ console.log(x, y, z); return [x, y, selected_gallery_index()] }",
+                                inputs=[generation_info, html_info, html_info],
+                                outputs=[html_info, html_info],
                             )
 
                         save.click(
@@ -526,7 +527,8 @@ Requested path was: {f}
                             outputs=[
                                 download_files,
                                 html_log,
-                            ]
+                            ],
+                            show_progress=False,
                         )
 
                         save_zip.click(
@@ -588,7 +590,7 @@ def create_ui():
         txt2img_prompt, txt2img_prompt_styles, txt2img_negative_prompt, submit, _, _,txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False)
 
         dummy_component = gr.Label(visible=False)
-        txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False)
+        txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="binary", visible=False)
 
         with gr.Row().style(equal_height=False):
             with gr.Column(variant='compact', elem_id="txt2img_settings"):
@@ -768,7 +770,7 @@ def create_ui():
     with gr.Blocks(analytics_enabled=False) as img2img_interface:
         img2img_prompt, img2img_prompt_styles, img2img_negative_prompt, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,token_counter, token_button = create_toprow(is_img2img=True)
 
-        img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False)
+        img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="binary", visible=False)
 
         with FormRow().style(equal_height=False):
             with gr.Column(variant='compact', elem_id="img2img_settings"):
@@ -1768,7 +1770,10 @@ def create_ui():
             if saved_value is None:
                 ui_settings[key] = getattr(obj, field)
             elif condition and not condition(saved_value):
-                print(f'Warning: Bad ui setting value: {key}: {saved_value}; Default value "{getattr(obj, field)}" will be used instead.')
+                pass
+
+                # this warning is generally not useful;
+                # print(f'Warning: Bad ui setting value: {key}: {saved_value}; Default value "{getattr(obj, field)}" will be used instead.')
             else:
                 setattr(obj, field, saved_value)
                 if init_field is not None:
diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py
index f3e711d7..76dc5778 100644
--- a/scripts/prompts_from_file.py
+++ b/scripts/prompts_from_file.py
@@ -116,7 +116,7 @@ class Script(scripts.Script):
         checkbox_iterate_batch = gr.Checkbox(label="Use same random seed for all lines", value=False, elem_id=self.elem_id("checkbox_iterate_batch"))
 
         prompt_txt = gr.Textbox(label="List of prompt inputs", lines=1, elem_id=self.elem_id("prompt_txt"))
-        file = gr.File(label="Upload prompt inputs", type='bytes', elem_id=self.elem_id("file"))
+        file = gr.File(label="Upload prompt inputs", type='binary', elem_id=self.elem_id("file"))
 
         file.change(fn=load_prompt_file, inputs=[file], outputs=[file, prompt_txt, prompt_txt])
 
diff --git a/style.css b/style.css
index 61279a19..0845519a 100644
--- a/style.css
+++ b/style.css
@@ -299,9 +299,8 @@ input[type="range"]{
 }
 
 /* more gradio's garbage cleanup */
-.min-h-\[4rem\] {
-  min-height: unset !important;
-}
+.min-h-\[4rem\] { min-height: unset !important; }
+.min-h-\[6rem\] { min-height: unset !important; }
 
 .progressDiv{
     position: absolute;
-- 
cgit v1.2.3


From bb0978ecfd3177d0bfd7cacd1ac8796d7eec2d79 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 19 Jan 2023 00:44:51 +0300
Subject: fix hires fix ui weirdness caused by gradio update

---
 modules/ui.py | 6 +++---
 style.css     | 2 +-
 2 files changed, 4 insertions(+), 4 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index 8b7f1dfb..09a3c92e 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -638,7 +638,7 @@ def create_ui():
                         seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('txt2img')
 
                     elif category == "checkboxes":
-                        with FormRow(elem_id="txt2img_checkboxes"):
+                        with FormRow(elem_id="txt2img_checkboxes", variant="compact"):
                             restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="txt2img_restore_faces")
                             tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling")
                             enable_hr = gr.Checkbox(label='Hires. fix', value=False, elem_id="txt2img_enable_hr")
@@ -646,12 +646,12 @@ def create_ui():
 
                     elif category == "hires_fix":
                         with FormGroup(visible=False, elem_id="txt2img_hires_fix") as hr_options:
-                            with FormRow(elem_id="txt2img_hires_fix_row1"):
+                            with FormRow(elem_id="txt2img_hires_fix_row1", variant="compact"):
                                 hr_upscaler = gr.Dropdown(label="Upscaler", elem_id="txt2img_hr_upscaler", choices=[*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]], value=shared.latent_upscale_default_mode)
                                 hr_second_pass_steps = gr.Slider(minimum=0, maximum=150, step=1, label='Hires steps', value=0, elem_id="txt2img_hires_steps")
                                 denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7, elem_id="txt2img_denoising_strength")
 
-                            with FormRow(elem_id="txt2img_hires_fix_row2"):
+                            with FormRow(elem_id="txt2img_hires_fix_row2", variant="compact"):
                                 hr_scale = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Upscale by", value=2.0, elem_id="txt2img_hr_scale")
                                 hr_resize_x = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize width to", value=0, elem_id="txt2img_hr_resize_x")
                                 hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y")
diff --git a/style.css b/style.css
index 0845519a..a6abd93d 100644
--- a/style.css
+++ b/style.css
@@ -686,7 +686,7 @@ footer {
 #txt2img_checkboxes, #img2img_checkboxes{
     margin-bottom: 0.5em;
 }
-#txt2img_checkboxes > div > div, #img2img_checkboxes > div > div{
+#txt2img_checkboxes > div, #img2img_checkboxes > div{
     flex: 0;
     white-space: nowrap;
     min-width: auto;
-- 
cgit v1.2.3


From c7e50425f63c07242068f8dcccce70a4ef28a17f Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 19 Jan 2023 09:25:37 +0300
Subject: add progress bar to modelmerger

---
 javascript/ui.js    | 11 +++++++++++
 modules/extras.py   | 18 +++++++++++++++---
 modules/progress.py |  2 +-
 modules/ui.py       | 13 ++++++++-----
 style.css           |  5 +++++
 5 files changed, 40 insertions(+), 9 deletions(-)

(limited to 'modules/ui.py')

diff --git a/javascript/ui.js b/javascript/ui.js
index 7d3d57a3..428375d4 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -172,6 +172,17 @@ function submit_img2img(){
     return res
 }
 
+function modelmerger(){
+    var id = randomId()
+    requestProgress(id, gradioApp().getElementById('modelmerger_results_panel'), null, function(){})
+
+    gradioApp().getElementById('modelmerger_result').innerHTML = ''
+
+    var res = create_submit_args(arguments)
+    res[0] = id
+    return res
+}
+
 
 function ask_for_style_name(_, prompt_text, negative_prompt_text) {
     name_ = prompt('Style name:')
diff --git a/modules/extras.py b/modules/extras.py
index 367c15cc..034f28e4 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -274,14 +274,15 @@ def create_config(ckpt_result, config_source, a, b, c):
     shutil.copyfile(cfg, checkpoint_filename)
 
 
-def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format, config_source):
+def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format, config_source):
     shared.state.begin()
     shared.state.job = 'model-merge'
+    shared.state.job_count = 1
 
     def fail(message):
         shared.state.textinfo = message
         shared.state.end()
-        return [message, *[gr.update() for _ in range(4)]]
+        return [*[gr.update() for _ in range(4)], message]
 
     def weighted_sum(theta0, theta1, alpha):
         return ((1 - alpha) * theta0) + (alpha * theta1)
@@ -320,9 +321,12 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
     theta_1 = sd_models.read_state_dict(secondary_model_info.filename, map_location='cpu')
 
     if theta_func1:
+        shared.state.job_count += 1
+
         print(f"Loading {tertiary_model_info.filename}...")
         theta_2 = sd_models.read_state_dict(tertiary_model_info.filename, map_location='cpu')
 
+        shared.state.sampling_steps = len(theta_1.keys())
         for key in tqdm.tqdm(theta_1.keys()):
             if 'model' in key:
                 if key in theta_2:
@@ -330,8 +334,12 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
                     theta_1[key] = theta_func1(theta_1[key], t2)
                 else:
                     theta_1[key] = torch.zeros_like(theta_1[key])
+
+            shared.state.sampling_step += 1
         del theta_2
 
+        shared.state.nextjob()
+
     shared.state.textinfo = f"Loading {primary_model_info.filename}..."
     print(f"Loading {primary_model_info.filename}...")
     theta_0 = sd_models.read_state_dict(primary_model_info.filename, map_location='cpu')
@@ -340,6 +348,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
 
     chckpoint_dict_skip_on_merge = ["cond_stage_model.transformer.text_model.embeddings.position_ids"]
 
+    shared.state.sampling_steps = len(theta_0.keys())
     for key in tqdm.tqdm(theta_0.keys()):
         if 'model' in key and key in theta_1:
 
@@ -367,6 +376,8 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
             if save_as_half:
                 theta_0[key] = theta_0[key].half()
 
+        shared.state.sampling_step += 1
+
     # I believe this part should be discarded, but I'll leave it for now until I am sure
     for key in theta_1.keys():
         if 'model' in key and key not in theta_0:
@@ -393,6 +404,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
 
     output_modelname = os.path.join(ckpt_dir, filename)
 
+    shared.state.nextjob()
     shared.state.textinfo = f"Saving to {output_modelname}..."
     print(f"Saving to {output_modelname}...")
 
@@ -410,4 +422,4 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
     shared.state.textinfo = "Checkpoint saved to " + output_modelname
     shared.state.end()
 
-    return ["Checkpoint saved to " + output_modelname] + [gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)]
+    return [*[gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)], "Checkpoint saved to " + output_modelname]
diff --git a/modules/progress.py b/modules/progress.py
index f9e005d3..c69ecf3d 100644
--- a/modules/progress.py
+++ b/modules/progress.py
@@ -72,7 +72,7 @@ def progressapi(req: ProgressRequest):
 
     if job_count > 0:
         progress += job_no / job_count
-    if sampling_steps > 0:
+    if sampling_steps > 0 and job_count > 0:
         progress += 1 / job_count * sampling_step / sampling_steps
 
     progress = min(progress, 1)
diff --git a/modules/ui.py b/modules/ui.py
index 09a3c92e..aeee7853 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1208,8 +1208,9 @@ def create_ui():
                 with gr.Row():
                     modelmerger_merge = gr.Button(elem_id="modelmerger_merge", value="Merge", variant='primary')
 
-            with gr.Column(variant='panel'):
-                submit_result = gr.Textbox(elem_id="modelmerger_result", show_label=False)
+            with gr.Column(variant='compact', elem_id="modelmerger_results_container"):
+                with gr.Group(elem_id="modelmerger_results_panel"):
+                    modelmerger_result = gr.HTML(elem_id="modelmerger_result", show_label=False)
 
     with gr.Blocks(analytics_enabled=False) as train_interface:
         with gr.Row().style(equal_height=False):
@@ -1753,12 +1754,14 @@ def create_ui():
                 print("Error loading/saving model file:", file=sys.stderr)
                 print(traceback.format_exc(), file=sys.stderr)
                 modules.sd_models.list_models()  # to remove the potentially missing models from the list
-                return [f"Error merging checkpoints: {e}"] + [gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(4)]
+                return [*[gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(4)], f"Error merging checkpoints: {e}"]
             return results
 
         modelmerger_merge.click(
-            fn=modelmerger,
+            fn=wrap_gradio_gpu_call(modelmerger, extra_outputs=lambda: [gr.update() for _ in range(4)]),
+            _js='modelmerger',
             inputs=[
+                dummy_component,
                 primary_model_name,
                 secondary_model_name,
                 tertiary_model_name,
@@ -1770,11 +1773,11 @@ def create_ui():
                 config_source,
             ],
             outputs=[
-                submit_result,
                 primary_model_name,
                 secondary_model_name,
                 tertiary_model_name,
                 component_dict['sd_model_checkpoint'],
+                modelmerger_result,
             ]
         )
 
diff --git a/style.css b/style.css
index a6abd93d..32ba4753 100644
--- a/style.css
+++ b/style.css
@@ -737,6 +737,11 @@ footer {
     line-height: 2.4em;
 }
 
+#modelmerger_results_container{
+    margin-top: 1em;
+    overflow: visible;
+}
+
 /* The following handles localization for right-to-left (RTL) languages like Arabic.
 The rtl media type will only be activated by the logic in javascript/localization.js.
 If you change anything above, you need to make sure it is RTL compliant by just running
-- 
cgit v1.2.3


From 0f5dbfffd0b7202a48e404d8e74b5cc9a3e5b135 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 19 Jan 2023 10:39:51 +0300
Subject: allow baking in VAE in checkpoint merger tab do not save config if
 it's the default for checkpoint merger tab change file naming scheme for
 checkpoint merger tab allow just saving A without any merging for checkpoint
 merger tab some stylistic changes for UI in checkpoint merger tab

---
 javascript/hints.js |   1 +
 javascript/ui.js    |   2 -
 modules/extras.py   | 112 +++++++++++++++++++++++++++++++---------------------
 modules/sd_vae.py   |   9 ++++-
 modules/shared.py   |   3 +-
 modules/ui.py       |  17 ++++++--
 style.css           |  15 ++++---
 7 files changed, 101 insertions(+), 58 deletions(-)

(limited to 'modules/ui.py')

diff --git a/javascript/hints.js b/javascript/hints.js
index fa5e5ae8..e746e20d 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -92,6 +92,7 @@ titles = {
 
     "Weighted sum": "Result = A * (1 - M) + B * M",
     "Add difference": "Result = A + (B - C) * M",
+    "No interpolation": "Result = A",
 
 	"Initialization text": "If the number of tokens is more than the number of vectors, some may be skipped.\nLeave the textbox empty to start with zeroed out vectors",
     "Learning rate": "How fast should training go. Low values will take longer to train, high values may fail to converge (not generate accurate results) and/or may break the embedding (This has happened if you see Loss: nan in the training info textbox. If this happens, you need to manually restore your embedding from an older not-broken backup).\n\nYou can set a single numeric value, or multiple learning rates using the syntax:\n\n   rate_1:max_steps_1, rate_2:max_steps_2, ...\n\nEG:   0.005:100, 1e-3:1000, 1e-5\n\nWill train with rate of 0.005 for first 100 steps, then 1e-3 until 1000 steps, then 1e-5 for all remaining steps.",
diff --git a/javascript/ui.js b/javascript/ui.js
index 428375d4..37788a3e 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -176,8 +176,6 @@ function modelmerger(){
     var id = randomId()
     requestProgress(id, gradioApp().getElementById('modelmerger_results_panel'), null, function(){})
 
-    gradioApp().getElementById('modelmerger_result').innerHTML = ''
-
     var res = create_submit_args(arguments)
     res[0] = id
     return res
diff --git a/modules/extras.py b/modules/extras.py
index 034f28e4..fe701a0e 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -15,7 +15,7 @@ from typing import Callable, List, OrderedDict, Tuple
 from functools import partial
 from dataclasses import dataclass
 
-from modules import processing, shared, images, devices, sd_models, sd_samplers
+from modules import processing, shared, images, devices, sd_models, sd_samplers, sd_vae
 from modules.shared import opts
 import modules.gfpgan_model
 from modules.ui import plaintext_to_html
@@ -251,7 +251,8 @@ def run_pnginfo(image):
 
 def create_config(ckpt_result, config_source, a, b, c):
     def config(x):
-        return sd_models.find_checkpoint_config(x) if x else None
+        res = sd_models.find_checkpoint_config(x) if x else None
+        return res if res != shared.sd_default_config else None
 
     if config_source == 0:
         cfg = config(a) or config(b) or config(c)
@@ -274,10 +275,12 @@ def create_config(ckpt_result, config_source, a, b, c):
     shutil.copyfile(cfg, checkpoint_filename)
 
 
-def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format, config_source):
+chckpoint_dict_skip_on_merge = ["cond_stage_model.transformer.text_model.embeddings.position_ids"]
+
+
+def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format, config_source, bake_in_vae):
     shared.state.begin()
     shared.state.job = 'model-merge'
-    shared.state.job_count = 1
 
     def fail(message):
         shared.state.textinfo = message
@@ -293,41 +296,68 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
     def add_difference(theta0, theta1_2_diff, alpha):
         return theta0 + (alpha * theta1_2_diff)
 
+    def filename_weighed_sum():
+        a = primary_model_info.model_name
+        b = secondary_model_info.model_name
+        Ma = round(1 - multiplier, 2)
+        Mb = round(multiplier, 2)
+
+        return f"{Ma}({a}) + {Mb}({b})"
+
+    def filename_add_differnece():
+        a = primary_model_info.model_name
+        b = secondary_model_info.model_name
+        c = tertiary_model_info.model_name
+        M = round(multiplier, 2)
+
+        return f"{a} + {M}({b} - {c})"
+
+    def filename_nothing():
+        return primary_model_info.model_name
+
+    theta_funcs = {
+        "Weighted sum": (filename_weighed_sum, None, weighted_sum),
+        "Add difference": (filename_add_differnece, get_difference, add_difference),
+        "No interpolation": (filename_nothing, None, None),
+    }
+    filename_generator, theta_func1, theta_func2 = theta_funcs[interp_method]
+    shared.state.job_count = (1 if theta_func1 else 0) + (1 if theta_func2 else 0)
+
     if not primary_model_name:
         return fail("Failed: Merging requires a primary model.")
 
     primary_model_info = sd_models.checkpoints_list[primary_model_name]
 
-    if not secondary_model_name:
+    if theta_func2 and not secondary_model_name:
         return fail("Failed: Merging requires a secondary model.")
-    
-    secondary_model_info = sd_models.checkpoints_list[secondary_model_name]
 
-    theta_funcs = {
-        "Weighted sum": (None, weighted_sum),
-        "Add difference": (get_difference, add_difference),
-    }
-    theta_func1, theta_func2 = theta_funcs[interp_method]
+    secondary_model_info = sd_models.checkpoints_list[secondary_model_name] if theta_func2 else None
 
     if theta_func1 and not tertiary_model_name:
         return fail(f"Failed: Interpolation method ({interp_method}) requires a tertiary model.")
-    
+
     tertiary_model_info = sd_models.checkpoints_list[tertiary_model_name] if theta_func1 else None
 
     result_is_inpainting_model = False
 
-    shared.state.textinfo = f"Loading {secondary_model_info.filename}..."
-    print(f"Loading {secondary_model_info.filename}...")
-    theta_1 = sd_models.read_state_dict(secondary_model_info.filename, map_location='cpu')
+    if theta_func2:
+        shared.state.textinfo = f"Loading B"
+        print(f"Loading {secondary_model_info.filename}...")
+        theta_1 = sd_models.read_state_dict(secondary_model_info.filename, map_location='cpu')
+    else:
+        theta_1 = None
 
     if theta_func1:
-        shared.state.job_count += 1
-
+        shared.state.textinfo = f"Loading C"
         print(f"Loading {tertiary_model_info.filename}...")
         theta_2 = sd_models.read_state_dict(tertiary_model_info.filename, map_location='cpu')
 
+        shared.state.textinfo = 'Merging B and C'
         shared.state.sampling_steps = len(theta_1.keys())
         for key in tqdm.tqdm(theta_1.keys()):
+            if key in chckpoint_dict_skip_on_merge:
+                continue
+
             if 'model' in key:
                 if key in theta_2:
                     t2 = theta_2.get(key, torch.zeros_like(theta_1[key]))
@@ -345,12 +375,10 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
     theta_0 = sd_models.read_state_dict(primary_model_info.filename, map_location='cpu')
 
     print("Merging...")
-
-    chckpoint_dict_skip_on_merge = ["cond_stage_model.transformer.text_model.embeddings.position_ids"]
-
+    shared.state.textinfo = 'Merging A and B'
     shared.state.sampling_steps = len(theta_0.keys())
     for key in tqdm.tqdm(theta_0.keys()):
-        if 'model' in key and key in theta_1:
+        if theta_1 and 'model' in key and key in theta_1:
 
             if key in chckpoint_dict_skip_on_merge:
                 continue
@@ -358,7 +386,6 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
             a = theta_0[key]
             b = theta_1[key]
 
-            shared.state.textinfo = f'Merging layer {key}'
             # this enables merging an inpainting model (A) with another one (B);
             # where normal model would have 4 channels, for latenst space, inpainting model would
             # have another 4 channels for unmasked picture's latent space, plus one channel for mask, for a total of 9
@@ -378,34 +405,31 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
 
         shared.state.sampling_step += 1
 
-    # I believe this part should be discarded, but I'll leave it for now until I am sure
-    for key in theta_1.keys():
-        if 'model' in key and key not in theta_0:
+    del theta_1
+
+    bake_in_vae_filename = sd_vae.vae_dict.get(bake_in_vae, None)
+    if bake_in_vae_filename is not None:
+        print(f"Baking in VAE from {bake_in_vae_filename}")
+        shared.state.textinfo = 'Baking in VAE'
+        vae_dict = sd_vae.load_vae_dict(bake_in_vae_filename, map_location='cpu')
 
-            if key in chckpoint_dict_skip_on_merge:
-                continue
+        for key in vae_dict.keys():
+            theta_0_key = 'first_stage_model.' + key
+            if theta_0_key in theta_0:
+                theta_0[theta_0_key] = vae_dict[key].half() if save_as_half else vae_dict[key]
 
-            theta_0[key] = theta_1[key]
-            if save_as_half:
-                theta_0[key] = theta_0[key].half()
-    del theta_1
+        del vae_dict
 
     ckpt_dir = shared.cmd_opts.ckpt_dir or sd_models.model_path
 
-    filename = \
-        primary_model_info.model_name + '_' + str(round(1-multiplier, 2)) + '-' + \
-        secondary_model_info.model_name + '_' + str(round(multiplier, 2)) + '-' + \
-        interp_method.replace(" ", "_") + \
-        '-merged.' +  \
-        ("inpainting." if result_is_inpainting_model else "") + \
-        checkpoint_format
-
-    filename = filename if custom_name == '' else (custom_name + '.' + checkpoint_format)
+    filename = filename_generator() if custom_name == '' else custom_name
+    filename += ".inpainting" if result_is_inpainting_model else ""
+    filename += "." + checkpoint_format
 
     output_modelname = os.path.join(ckpt_dir, filename)
 
     shared.state.nextjob()
-    shared.state.textinfo = f"Saving to {output_modelname}..."
+    shared.state.textinfo = "Saving"
     print(f"Saving to {output_modelname}...")
 
     _, extension = os.path.splitext(output_modelname)
@@ -418,8 +442,8 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
 
     create_config(output_modelname, config_source, primary_model_info, secondary_model_info, tertiary_model_info)
 
-    print("Checkpoint saved.")
-    shared.state.textinfo = "Checkpoint saved to " + output_modelname
+    print(f"Checkpoint saved to {output_modelname}.")
+    shared.state.textinfo = "Checkpoint saved"
     shared.state.end()
 
     return [*[gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)], "Checkpoint saved to " + output_modelname]
diff --git a/modules/sd_vae.py b/modules/sd_vae.py
index da1bf15c..4ce238b8 100644
--- a/modules/sd_vae.py
+++ b/modules/sd_vae.py
@@ -120,6 +120,12 @@ def resolve_vae(checkpoint_file):
     return None, None
 
 
+def load_vae_dict(filename, map_location):
+    vae_ckpt = sd_models.read_state_dict(filename, map_location=map_location)
+    vae_dict_1 = {k: v for k, v in vae_ckpt.items() if k[0:4] != "loss" and k not in vae_ignore_keys}
+    return vae_dict_1
+
+
 def load_vae(model, vae_file=None, vae_source="from unknown source"):
     global vae_dict, loaded_vae_file
     # save_settings = False
@@ -137,8 +143,7 @@ def load_vae(model, vae_file=None, vae_source="from unknown source"):
             print(f"Loading VAE weights {vae_source}: {vae_file}")
             store_base_vae(model)
 
-            vae_ckpt = sd_models.read_state_dict(vae_file, map_location=shared.weight_load_location)
-            vae_dict_1 = {k: v for k, v in vae_ckpt.items() if k[0:4] != "loss" and k not in vae_ignore_keys}
+            vae_dict_1 = load_vae_dict(vae_file, map_location=shared.weight_load_location)
             _load_vae_dict(model, vae_dict_1)
 
             if cache_enabled:
diff --git a/modules/shared.py b/modules/shared.py
index 77e5e91c..29b28bff 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -20,10 +20,11 @@ from modules.paths import models_path, script_path, sd_path
 
 demo = None
 
+sd_default_config = os.path.join(script_path, "configs/v1-inference.yaml")
 sd_model_file = os.path.join(script_path, 'model.ckpt')
 default_sd_model_file = sd_model_file
 parser = argparse.ArgumentParser()
-parser.add_argument("--config", type=str, default=os.path.join(script_path, "configs/v1-inference.yaml"), help="path to config which constructs model",)
+parser.add_argument("--config", type=str, default=sd_default_config, help="path to config which constructs model",)
 parser.add_argument("--ckpt", type=str, default=sd_model_file, help="path to checkpoint of stable diffusion model; if specified, this checkpoint will be added to the list of checkpoints and loaded",)
 parser.add_argument("--ckpt-dir", type=str, default=None, help="Path to directory with stable diffusion checkpoints")
 parser.add_argument("--vae-dir", type=str, default=None, help="Path to directory with VAE files")
diff --git a/modules/ui.py b/modules/ui.py
index aeee7853..4e381a49 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -20,7 +20,7 @@ import numpy as np
 from PIL import Image, PngImagePlugin
 from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
 
-from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru
+from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae
 from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
 from modules.paths import script_path
 
@@ -1185,7 +1185,7 @@ def create_ui():
             with gr.Column(variant='compact'):
                 gr.HTML(value="<p style='margin-bottom: 2.5em'>A merger of the two checkpoints will be generated in your <b>checkpoint</b> directory.</p>")
 
-                with FormRow():
+                with FormRow(elem_id="modelmerger_models"):
                     primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)")
                     create_refresh_button(primary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_A")
 
@@ -1197,13 +1197,20 @@ def create_ui():
 
                 custom_name = gr.Textbox(label="Custom Name (Optional)", elem_id="modelmerger_custom_name")
                 interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3, elem_id="modelmerger_interp_amount")
-                interp_method = gr.Radio(choices=["Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method", elem_id="modelmerger_interp_method")
+                interp_method = gr.Radio(choices=["No interpolation", "Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method", elem_id="modelmerger_interp_method")
 
                 with FormRow():
                     checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format", elem_id="modelmerger_checkpoint_format")
                     save_as_half = gr.Checkbox(value=False, label="Save as float16", elem_id="modelmerger_save_as_half")
 
-                config_source = gr.Radio(choices=["A, B or C", "B", "C", "Don't"], value="A, B or C", label="Copy config from", type="index", elem_id="modelmerger_config_method")
+                with FormRow():
+                    with gr.Column():
+                        config_source = gr.Radio(choices=["A, B or C", "B", "C", "Don't"], value="A, B or C", label="Copy config from", type="index", elem_id="modelmerger_config_method")
+
+                    with gr.Column():
+                        with FormRow():
+                            bake_in_vae = gr.Dropdown(choices=["None"] + list(sd_vae.vae_dict), value="None", label="Bake in VAE", elem_id="modelmerger_bake_in_vae")
+                            create_refresh_button(bake_in_vae, sd_vae.refresh_vae_list, lambda: {"choices": ["None"] + list(sd_vae.vae_dict)}, "modelmerger_refresh_bake_in_vae")
 
                 with gr.Row():
                     modelmerger_merge = gr.Button(elem_id="modelmerger_merge", value="Merge", variant='primary')
@@ -1757,6 +1764,7 @@ def create_ui():
                 return [*[gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(4)], f"Error merging checkpoints: {e}"]
             return results
 
+        modelmerger_merge.click(fn=lambda: '', inputs=[], outputs=[modelmerger_result])
         modelmerger_merge.click(
             fn=wrap_gradio_gpu_call(modelmerger, extra_outputs=lambda: [gr.update() for _ in range(4)]),
             _js='modelmerger',
@@ -1771,6 +1779,7 @@ def create_ui():
                 custom_name,
                 checkpoint_format,
                 config_source,
+                bake_in_vae,
             ],
             outputs=[
                 primary_model_name,
diff --git a/style.css b/style.css
index 32ba4753..c10e32a1 100644
--- a/style.css
+++ b/style.css
@@ -641,6 +641,16 @@ canvas[key="mask"] {
     margin: 0.6em 0em 0.55em 0;
 }
 
+#modelmerger_results_container{
+    margin-top: 1em;
+    overflow: visible;
+}
+
+#modelmerger_models{
+    gap: 0;
+}
+
+
 #quicksettings .gr-button-tool{
     margin: 0;
 }
@@ -737,11 +747,6 @@ footer {
     line-height: 2.4em;
 }
 
-#modelmerger_results_container{
-    margin-top: 1em;
-    overflow: visible;
-}
-
 /* The following handles localization for right-to-left (RTL) languages like Arabic.
 The rtl media type will only be activated by the logic in javascript/localization.js.
 If you change anything above, you need to make sure it is RTL compliant by just running
-- 
cgit v1.2.3


From d1ea518dea3d7584be2927cc486d15ec3e18ddb0 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 19 Jan 2023 18:07:37 +0300
Subject: remember the list of checkpoints after you press refresh button and
 reload the page

---
 modules/ui.py | 11 ++++++++++-
 1 file changed, 10 insertions(+), 1 deletion(-)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index af416d5f..0c5ba358 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1771,8 +1771,17 @@ def create_ui():
 
         component_keys = [k for k in opts.data_labels.keys() if k in component_dict]
 
+        def get_value_for_setting(key):
+            value = getattr(opts, key)
+
+            info = opts.data_labels[key]
+            args = info.component_args() if callable(info.component_args) else info.component_args or {}
+            args = {k: v for k, v in args.items() if k not in {'precision'}}
+
+            return gr.update(value=value, **args)
+
         def get_settings_values():
-            return [getattr(opts, key) for key in component_keys]
+            return [get_value_for_setting(key) for key in component_keys]
 
         demo.load(
             fn=get_settings_values,
-- 
cgit v1.2.3


From c1928cdd6194928af0f53f70c51d59479b7025e2 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 19 Jan 2023 18:58:08 +0300
Subject: bring back short hashes to sd checkpoint selection

---
 modules/sd_models.py | 15 +++++++++++----
 modules/ui.py        | 23 ++++++++++++-----------
 2 files changed, 23 insertions(+), 15 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/sd_models.py b/modules/sd_models.py
index 6a681cef..12083848 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -41,14 +41,16 @@ class CheckpointInfo:
         if name.startswith("\\") or name.startswith("/"):
             name = name[1:]
 
-        self.title = name
+        self.name = name
         self.model_name = os.path.splitext(name.replace("/", "_").replace("\\", "_"))[0]
         self.hash = model_hash(filename)
 
-        self.sha256 = hashes.sha256_from_cache(self.filename, "checkpoint/" + self.title)
+        self.sha256 = hashes.sha256_from_cache(self.filename, "checkpoint/" + name)
         self.shorthash = self.sha256[0:10] if self.sha256 else None
 
-        self.ids = [self.hash, self.model_name, self.title, f'{name} [{self.hash}]'] + ([self.shorthash, self.sha256] if self.shorthash else [])
+        self.title = name if self.shorthash is None else f'{name} [{self.shorthash}]'
+
+        self.ids = [self.hash, self.model_name, self.title, name, f'{name} [{self.hash}]'] + ([self.shorthash, self.sha256, f'{self.name} [{self.shorthash}]'] if self.shorthash else [])
 
     def register(self):
         checkpoints_list[self.title] = self
@@ -56,13 +58,15 @@ class CheckpointInfo:
             checkpoint_alisases[id] = self
 
     def calculate_shorthash(self):
-        self.sha256 = hashes.sha256(self.filename, "checkpoint/" + self.title)
+        self.sha256 = hashes.sha256(self.filename, "checkpoint/" + self.name)
         self.shorthash = self.sha256[0:10]
 
         if self.shorthash not in self.ids:
             self.ids += [self.shorthash, self.sha256]
             self.register()
 
+        self.title = f'{self.name} [{self.shorthash}]'
+
         return self.shorthash
 
 
@@ -225,7 +229,10 @@ def read_state_dict(checkpoint_file, print_global_state=False, map_location=None
 
 
 def load_model_weights(model, checkpoint_info: CheckpointInfo):
+    title = checkpoint_info.title
     sd_model_hash = checkpoint_info.calculate_shorthash()
+    if checkpoint_info.title != title:
+        shared.opts.data["sd_model_checkpoint"] = checkpoint_info.title
 
     cache_enabled = shared.opts.sd_checkpoint_cache > 0
 
diff --git a/modules/ui.py b/modules/ui.py
index 0c5ba358..13d80ae2 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -439,7 +439,7 @@ def apply_setting(key, value):
         opts.data_labels[key].onchange()
 
     opts.save(shared.config_filename)
-    return value
+    return getattr(opts, key)
 
 
 def update_generation_info(generation_info, html_info, img_index):
@@ -597,6 +597,16 @@ def ordered_ui_categories():
         yield category
 
 
+def get_value_for_setting(key):
+    value = getattr(opts, key)
+
+    info = opts.data_labels[key]
+    args = info.component_args() if callable(info.component_args) else info.component_args or {}
+    args = {k: v for k, v in args.items() if k not in {'precision'}}
+
+    return gr.update(value=value, **args)
+
+
 def create_ui():
     import modules.img2img
     import modules.txt2img
@@ -1600,7 +1610,7 @@ def create_ui():
 
         opts.save(shared.config_filename)
 
-        return gr.update(value=value), opts.dumpjson()
+        return get_value_for_setting(key), opts.dumpjson()
 
     with gr.Blocks(analytics_enabled=False) as settings_interface:
         with gr.Row():
@@ -1771,15 +1781,6 @@ def create_ui():
 
         component_keys = [k for k in opts.data_labels.keys() if k in component_dict]
 
-        def get_value_for_setting(key):
-            value = getattr(opts, key)
-
-            info = opts.data_labels[key]
-            args = info.component_args() if callable(info.component_args) else info.component_args or {}
-            args = {k: v for k, v in args.items() if k not in {'precision'}}
-
-            return gr.update(value=value, **args)
-
         def get_settings_values():
             return [get_value_for_setting(key) for key in component_keys]
 
-- 
cgit v1.2.3


From 6c7a50d783c4e406d8597f9cf354bb8128026f6c Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 20 Jan 2023 08:36:30 +0300
Subject: remove some unnecessary logging to javascript console

---
 javascript/hires_fix.js | 3 ---
 modules/ui.py           | 2 +-
 2 files changed, 1 insertion(+), 4 deletions(-)

(limited to 'modules/ui.py')

diff --git a/javascript/hires_fix.js b/javascript/hires_fix.js
index 07fba549..0629475f 100644
--- a/javascript/hires_fix.js
+++ b/javascript/hires_fix.js
@@ -1,6 +1,5 @@
 
 function setInactive(elem, inactive){
-    console.log(elem)
     if(inactive){
         elem.classList.add('inactive')
     } else{
@@ -9,8 +8,6 @@ function setInactive(elem, inactive){
 }
 
 function onCalcResolutionHires(enable, width, height, hr_scale, hr_resize_x, hr_resize_y){
-    console.log(enable, width, height, hr_scale, hr_resize_x, hr_resize_y)
-
     hrUpscaleBy = gradioApp().getElementById('txt2img_hr_scale')
     hrResizeX = gradioApp().getElementById('txt2img_hr_resize_x')
     hrResizeY = gradioApp().getElementById('txt2img_hr_resize_y')
diff --git a/modules/ui.py b/modules/ui.py
index 13d80ae2..eb45a128 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -532,7 +532,7 @@ Requested path was: {f}
                             generation_info_button = gr.Button(visible=False, elem_id=f"{tabname}_generation_info_button")
                             generation_info_button.click(
                                 fn=update_generation_info,
-                                _js="function(x, y, z){ console.log(x, y, z); return [x, y, selected_gallery_index()] }",
+                                _js="function(x, y, z){ return [x, y, selected_gallery_index()] }",
                                 inputs=[generation_info, html_info, html_info],
                                 outputs=[html_info, html_info],
                             )
-- 
cgit v1.2.3


From 98466da4bc312c0fa9c8cea4c825afc64194cb58 Mon Sep 17 00:00:00 2001
From: EllangoK <karun.ellango7@gmail.com>
Date: Fri, 20 Jan 2023 00:48:15 -0500
Subject: adds descriptions for merging methods in ui

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

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index eb45a128..ee434bde 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1190,10 +1190,19 @@ def create_ui():
             outputs=[html, generation_info, html2],
         )
 
+    def update_interp_description(value):
+        interp_description_css = "<p style='margin-bottom: 2.5em'>{}</p>"
+        interp_descriptions = {
+            "No interpolation": interp_description_css.format("No interpolation will be used. Requires one model; A. Allows for format conversion and VAE baking."),
+            "Weighted sum": interp_description_css.format("A weighted sum will be used for interpolation. Requires two models; A and B. The result is calculated as A * (1 - M) + B * M"),
+            "Add difference": interp_description_css.format("The difference between the last two models will be added to the first. Requires three models; A, B and C. The result is calculated as A + (B - C) * M")
+        }
+        return interp_descriptions[value]
+
     with gr.Blocks(analytics_enabled=False) as modelmerger_interface:
         with gr.Row().style(equal_height=False):
             with gr.Column(variant='compact'):
-                gr.HTML(value="<p style='margin-bottom: 2.5em'>A merger of the two checkpoints will be generated in your <b>checkpoint</b> directory.</p>")
+                interp_description = gr.HTML(value=update_interp_description("Weighted sum"), elem_id="modelmerger_interp_description")
 
                 with FormRow(elem_id="modelmerger_models"):
                     primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)")
@@ -1208,6 +1217,7 @@ def create_ui():
                 custom_name = gr.Textbox(label="Custom Name (Optional)", elem_id="modelmerger_custom_name")
                 interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3, elem_id="modelmerger_interp_amount")
                 interp_method = gr.Radio(choices=["No interpolation", "Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method", elem_id="modelmerger_interp_method")
+                interp_method.change(fn=update_interp_description, inputs=[interp_method], outputs=[interp_description])
 
                 with FormRow():
                     checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format", elem_id="modelmerger_checkpoint_format")
@@ -1903,6 +1913,9 @@ def create_ui():
         with open(ui_config_file, "w", encoding="utf8") as file:
             json.dump(ui_settings, file, indent=4)
 
+    # Required as a workaround for change() event not triggering when loading values from ui-config.json
+    interp_description.value = update_interp_description(interp_method.value)
+
     return demo
 
 
-- 
cgit v1.2.3


From 20a59ab3b171f398abd09087108c1ed087dbea9b Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 20 Jan 2023 10:18:41 +0300
Subject: move token counter to the location of the prompt, add token counting
 for the negative prompt

---
 .../javascript/prompt-bracket-checker.js           | 45 +++++++++++----------
 javascript/ui.js                                   | 29 +++++++++----
 modules/ui.py                                      | 25 ++++++------
 style.css                                          | 47 ++++++++++++++--------
 4 files changed, 87 insertions(+), 59 deletions(-)

(limited to 'modules/ui.py')

diff --git a/extensions-builtin/prompt-bracket-checker/javascript/prompt-bracket-checker.js b/extensions-builtin/prompt-bracket-checker/javascript/prompt-bracket-checker.js
index 251a1f57..4a85c8eb 100644
--- a/extensions-builtin/prompt-bracket-checker/javascript/prompt-bracket-checker.js
+++ b/extensions-builtin/prompt-bracket-checker/javascript/prompt-bracket-checker.js
@@ -4,16 +4,10 @@
 // Counts open and closed brackets (round, square, curly) in the prompt and negative prompt text boxes in the txt2img and img2img tabs.
 // If there's a mismatch, the keyword counter turns red and if you hover on it, a tooltip tells you what's wrong.
 
-function checkBrackets(evt) {
-  textArea = evt.target;
-  tabName = evt.target.parentElement.parentElement.id.split("_")[0];
-  counterElt = document.querySelector('gradio-app').shadowRoot.querySelector('#' + tabName + '_token_counter');
-
-  promptName = evt.target.parentElement.parentElement.id.includes('neg') ? ' negative' : '';
-
-  errorStringParen  = '(' + tabName + promptName + ' prompt) - Different number of opening and closing parentheses detected.\n';
-  errorStringSquare = '[' + tabName + promptName + ' prompt] - Different number of opening and closing square brackets detected.\n';
-  errorStringCurly  = '{' + tabName + promptName + ' prompt} - Different number of opening and closing curly brackets detected.\n';
+function checkBrackets(evt, textArea, counterElt) {
+  errorStringParen  = '(...) - Different number of opening and closing parentheses detected.\n';
+  errorStringSquare = '[...] - Different number of opening and closing square brackets detected.\n';
+  errorStringCurly  = '{...} - Different number of opening and closing curly brackets detected.\n';
 
   openBracketRegExp = /\(/g;
   closeBracketRegExp = /\)/g;
@@ -86,24 +80,31 @@ function checkBrackets(evt) {
   }
 
   if(counterElt.title != '') {
-    counterElt.style = 'color: #FF5555;';
+    counterElt.classList.add('error');
   } else {
-    counterElt.style = '';
+    counterElt.classList.remove('error');
   }
 }
 
-var shadowRootLoaded = setInterval(function() {
-  var sahdowRoot = document.querySelector('gradio-app').shadowRoot;
-  if(! sahdowRoot)  return false;
+function setupBracketChecking(id_prompt, id_counter){
+    var textarea = gradioApp().querySelector("#" + id_prompt + " > label > textarea");
+    var counter = gradioApp().getElementById(id_counter)
+    textarea.addEventListener("input", function(evt){
+        checkBrackets(evt, textarea, counter)
+    });
+}
 
-  var shadowTextArea = sahdowRoot.querySelectorAll('#txt2img_prompt > label > textarea');
-  if(shadowTextArea.length < 1)  return false;
+var shadowRootLoaded = setInterval(function() {
+    var shadowRoot = document.querySelector('gradio-app').shadowRoot;
+    if(! shadowRoot)  return false;
 
+    var shadowTextArea = shadowRoot.querySelectorAll('#txt2img_prompt > label > textarea');
+    if(shadowTextArea.length < 1)  return false;
 
-  clearInterval(shadowRootLoaded);
+    clearInterval(shadowRootLoaded);
 
-  document.querySelector('gradio-app').shadowRoot.querySelector('#txt2img_prompt').onkeyup = checkBrackets;
-  document.querySelector('gradio-app').shadowRoot.querySelector('#txt2img_neg_prompt').onkeyup = checkBrackets;
-  document.querySelector('gradio-app').shadowRoot.querySelector('#img2img_prompt').onkeyup = checkBrackets;
-  document.querySelector('gradio-app').shadowRoot.querySelector('#img2img_neg_prompt').onkeyup = checkBrackets;
+    setupBracketChecking('txt2img_prompt', 'txt2img_token_counter')
+    setupBracketChecking('txt2img_neg_prompt', 'txt2img_negative_token_counter')
+    setupBracketChecking('img2img_prompt', 'imgimg_token_counter')
+    setupBracketChecking('img2img_neg_prompt', 'img2img_negative_token_counter')
 }, 1000);
diff --git a/javascript/ui.js b/javascript/ui.js
index 37788a3e..3ba90ca8 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -230,14 +230,26 @@ onUiUpdate(function(){
 
     json_elem.parentElement.style.display="none"
 
-	if (!txt2img_textarea) {
-		txt2img_textarea = gradioApp().querySelector("#txt2img_prompt > label > textarea");
-		txt2img_textarea?.addEventListener("input", () => update_token_counter("txt2img_token_button"));
-	}
-	if (!img2img_textarea) {
-		img2img_textarea = gradioApp().querySelector("#img2img_prompt > label > textarea");
-		img2img_textarea?.addEventListener("input", () => update_token_counter("img2img_token_button"));
-	}
+    function registerTextarea(id, id_counter, id_button){
+        var prompt = gradioApp().getElementById(id)
+        var counter = gradioApp().getElementById(id_counter)
+        var textarea = gradioApp().querySelector("#" + id + " > label > textarea");
+
+        if(counter.parentElement == prompt.parentElement){
+            return
+        }
+
+        prompt.parentElement.insertBefore(counter, prompt)
+        counter.classList.add("token-counter")
+        prompt.parentElement.style.position = "relative"
+
+		textarea.addEventListener("input", () => update_token_counter(id_button));
+    }
+
+    registerTextarea('txt2img_prompt', 'txt2img_token_counter', 'txt2img_token_button')
+    registerTextarea('txt2img_neg_prompt', 'txt2img_negative_token_counter', 'txt2img_negative_token_button')
+    registerTextarea('img2img_prompt', 'img2img_token_counter', 'img2img_token_button')
+    registerTextarea('img2img_neg_prompt', 'img2img_negative_token_counter', 'img2img_negative_token_button')
 
     show_all_pages = gradioApp().getElementById('settings_show_all_pages')
     settings_tabs = gradioApp().querySelector('#settings div')
@@ -249,6 +261,7 @@ onUiUpdate(function(){
             })
         }
     }
+
 })
 
 
diff --git a/modules/ui.py b/modules/ui.py
index eb45a128..06c11848 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -335,28 +335,23 @@ def update_token_counter(text, steps):
     flat_prompts = reduce(lambda list1, list2: list1+list2, prompt_schedules)
     prompts = [prompt_text for step, prompt_text in flat_prompts]
     token_count, max_length = max([model_hijack.get_prompt_lengths(prompt) for prompt in prompts], key=lambda args: args[0])
-    style_class = ' class="red"' if (token_count > max_length) else ""
-    return f"<span {style_class}>{token_count}/{max_length}</span>"
+    return f"<span class='gr-box gr-text-input'>{token_count}/{max_length}</span>"
 
 
 def create_toprow(is_img2img):
     id_part = "img2img" if is_img2img else "txt2img"
 
-    with gr.Row(elem_id="toprow"):
-        with gr.Column(scale=6):
+    with gr.Row(elem_id=f"{id_part}_toprow", variant="compact"):
+        with gr.Column(elem_id=f"{id_part}_prompt_container", scale=6):
             with gr.Row():
                 with gr.Column(scale=80):
                     with gr.Row():
-                        prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=2,
-                            placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)"
-                        )
+                        prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=2, placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)")
 
             with gr.Row():
                 with gr.Column(scale=80):
                     with gr.Row():
-                        negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2,
-                            placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)"
-                        )
+                        negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2, placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)")
 
         with gr.Column(scale=1, elem_id="roll_col"):
             paste = gr.Button(value=paste_symbol, elem_id="paste")
@@ -365,6 +360,8 @@ def create_toprow(is_img2img):
             clear_prompt_button = gr.Button(value=clear_prompt_symbol, elem_id=f"{id_part}_clear_prompt")
             token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_token_counter")
             token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button")
+            negative_token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_negative_token_counter")
+            negative_token_button = gr.Button(visible=False, elem_id=f"{id_part}_negative_token_button")
 
             clear_prompt_button.click(
                 fn=lambda *x: x,
@@ -402,7 +399,7 @@ def create_toprow(is_img2img):
                 prompt_styles = gr.Dropdown(label="Styles", elem_id=f"{id_part}_styles", choices=[k for k, v in shared.prompt_styles.styles.items()], value=[], multiselect=True)
                 create_refresh_button(prompt_styles, shared.prompt_styles.reload, lambda: {"choices": [k for k, v in shared.prompt_styles.styles.items()]}, f"refresh_{id_part}_styles")
 
-    return prompt, prompt_styles, negative_prompt, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button
+    return prompt, prompt_styles, negative_prompt, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button, negative_token_counter, negative_token_button
 
 
 def setup_progressbar(*args, **kwargs):
@@ -619,7 +616,7 @@ def create_ui():
     modules.scripts.scripts_txt2img.initialize_scripts(is_img2img=False)
 
     with gr.Blocks(analytics_enabled=False) as txt2img_interface:
-        txt2img_prompt, txt2img_prompt_styles, txt2img_negative_prompt, submit, _, _,txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False)
+        txt2img_prompt, txt2img_prompt_styles, txt2img_negative_prompt, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button, negative_token_counter, negative_token_button = create_toprow(is_img2img=False)
 
         dummy_component = gr.Label(visible=False)
         txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="binary", visible=False)
@@ -795,12 +792,13 @@ def create_ui():
             ]
 
             token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[txt2img_prompt, steps], outputs=[token_counter])
+            negative_token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[txt2img_negative_prompt, steps], outputs=[negative_token_counter])
 
     modules.scripts.scripts_current = modules.scripts.scripts_img2img
     modules.scripts.scripts_img2img.initialize_scripts(is_img2img=True)
 
     with gr.Blocks(analytics_enabled=False) as img2img_interface:
-        img2img_prompt, img2img_prompt_styles, img2img_negative_prompt, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,token_counter, token_button = create_toprow(is_img2img=True)
+        img2img_prompt, img2img_prompt_styles, img2img_negative_prompt, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste, token_counter, token_button, negative_token_counter, negative_token_button = create_toprow(is_img2img=True)
 
         img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="binary", visible=False)
 
@@ -1064,6 +1062,7 @@ def create_ui():
                 )
 
             token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter])
+            negative_token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[txt2img_negative_prompt, steps], outputs=[negative_token_counter])
 
             img2img_paste_fields = [
                 (img2img_prompt, "Prompt"),
diff --git a/style.css b/style.css
index c10e32a1..994932de 100644
--- a/style.css
+++ b/style.css
@@ -2,12 +2,26 @@
     max-width: 100%;
 }
 
-#txt2img_token_counter {
-    height: 0px;
+.token-counter{
+    position: absolute;
+    display: inline-block;
+    right: 2em;
+    min-width: 0 !important;
+    width: auto;
+    z-index: 100;
+}
+
+.token-counter.error span{
+    box-shadow: 0 0 0.0 0.3em rgba(255,0,0,0.15), inset 0 0 0.6em rgba(255,0,0,0.075);
+    border: 2px solid rgba(255,0,0,0.4) !important;
 }
 
-#img2img_token_counter {
-    height: 0px;
+.token-counter div{
+    display: inline;
+}
+
+.token-counter span{
+    padding: 0.1em 0.75em;
 }
 
 #sh{
@@ -113,7 +127,7 @@
 #roll_col{
     min-width: unset !important;
     flex-grow: 0 !important;
-    padding: 0.4em 0;
+    padding: 0 1em 0 0;
     gap: 0;
 }
 
@@ -160,16 +174,6 @@
     margin-bottom: 0;
 }
 
-#toprow div.gr-box, #toprow div.gr-form{
-    border: none;
-    gap: 0;
-    background: transparent;
-    box-shadow: none;
-}
-#toprow div{
-    gap: 0;
-}
-
 #resize_mode{
     flex: 1.5;
 }
@@ -706,6 +710,14 @@ footer {
     opacity: 0.5;
 }
 
+[id*='_prompt_container']{
+    gap: 0;
+}
+
+[id*='_prompt_container'] > div{
+    margin: -0.4em 0 0 0;
+}
+
 .gr-compact {
     border: none;
 }
@@ -715,8 +727,11 @@ footer {
     margin-left: 0.8em;
 }
 
+.gr-compact{
+    overflow: visible;
+}
+
 .gr-compact > *{
-    margin-top: 0.5em !important;
 }
 
 .gr-compact .gr-block, .gr-compact .gr-form{
-- 
cgit v1.2.3


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

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

(limited to 'modules/ui.py')

diff --git a/html/card-no-preview.png b/html/card-no-preview.png
new file mode 100644
index 00000000..e2beb269
Binary files /dev/null and b/html/card-no-preview.png differ
diff --git a/html/extra-networks-card.html b/html/extra-networks-card.html
new file mode 100644
index 00000000..7314b063
--- /dev/null
+++ b/html/extra-networks-card.html
@@ -0,0 +1,11 @@
+<div class='card' {preview_html} onclick='return cardClicked({prompt}, {allow_negative_prompt})'>
+	<div class='actions'>
+		<div class='additional'>
+			<ul>
+				<a href="#" title="replace preview image with currently selected in gallery" onclick='return saveCardPreview(event, {tabname}, {local_preview})'>replace preview</a>
+			</ul>
+		</div>
+		<span class='name'>{name}</span>
+	</div>
+</div>
+
diff --git a/html/extra-networks-no-cards.html b/html/extra-networks-no-cards.html
new file mode 100644
index 00000000..389358d6
--- /dev/null
+++ b/html/extra-networks-no-cards.html
@@ -0,0 +1,8 @@
+<div class='nocards'>
+<h1>Nothing here. Add some content to the following directories:</h1>
+
+<ul>
+{dirs}
+</ul>
+</div>
+
diff --git a/javascript/extraNetworks.js b/javascript/extraNetworks.js
new file mode 100644
index 00000000..71e522d1
--- /dev/null
+++ b/javascript/extraNetworks.js
@@ -0,0 +1,60 @@
+
+function setupExtraNetworksForTab(tabname){
+    gradioApp().querySelector('#'+tabname+'_extra_tabs').classList.add('extra-networks')
+
+    gradioApp().querySelector('#'+tabname+'_extra_tabs > div').appendChild(gradioApp().getElementById(tabname+'_extra_refresh'))
+    gradioApp().querySelector('#'+tabname+'_extra_tabs > div').appendChild(gradioApp().getElementById(tabname+'_extra_close'))
+}
+
+var activePromptTextarea = null;
+var activePositivePromptTextarea = null;
+
+function setupExtraNetworks(){
+    setupExtraNetworksForTab('txt2img')
+    setupExtraNetworksForTab('img2img')
+
+    function registerPrompt(id, isNegative){
+        var textarea = gradioApp().querySelector("#" + id + " > label > textarea");
+
+        if (activePromptTextarea == null){
+            activePromptTextarea = textarea
+        }
+        if (activePositivePromptTextarea == null && ! isNegative){
+            activePositivePromptTextarea = textarea
+        }
+
+		textarea.addEventListener("focus", function(){
+            activePromptTextarea = textarea;
+            if(! isNegative)  activePositivePromptTextarea = textarea;
+		});
+    }
+
+    registerPrompt('txt2img_prompt')
+    registerPrompt('txt2img_neg_prompt', true)
+    registerPrompt('img2img_prompt')
+    registerPrompt('img2img_neg_prompt', true)
+}
+
+onUiLoaded(setupExtraNetworks)
+
+function cardClicked(textToAdd, allowNegativePrompt){
+    textarea = allowNegativePrompt ? activePromptTextarea : activePositivePromptTextarea
+
+    textarea.value = textarea.value + " " + textToAdd
+    updateInput(textarea)
+
+    return false
+}
+
+function saveCardPreview(event, tabname, filename){
+    textarea = gradioApp().querySelector("#" + tabname + '_preview_filename  > label > textarea')
+    button = gradioApp().getElementById(tabname + '_save_preview')
+
+    textarea.value = filename
+    updateInput(textarea)
+
+    button.click()
+
+    event.stopPropagation()
+    event.preventDefault()
+}
diff --git a/javascript/hints.js b/javascript/hints.js
index e746e20d..f4079f96 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -21,6 +21,8 @@ titles = {
     "\U0001F5D1": "Clear prompt",
     "\u{1f4cb}": "Apply selected styles to current prompt",
     "\u{1f4d2}": "Paste available values into the field",
+    "\u{1f3b4}": "Show extra networks",
+
 
     "Inpaint a part of image": "Draw a mask over an image, and the script will regenerate the masked area with content according to prompt",
     "SD upscale": "Upscale image normally, split result into tiles, improve each tile using img2img, merge whole image back",
diff --git a/javascript/ui.js b/javascript/ui.js
index 3ba90ca8..a7e75439 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -196,8 +196,6 @@ function confirm_clear_prompt(prompt, negative_prompt) {
     return [prompt, negative_prompt]
 }
 
-
-
 opts = {}
 onUiUpdate(function(){
 	if(Object.keys(opts).length != 0) return;
@@ -239,11 +237,14 @@ onUiUpdate(function(){
             return
         }
 
+
         prompt.parentElement.insertBefore(counter, prompt)
         counter.classList.add("token-counter")
         prompt.parentElement.style.position = "relative"
 
-		textarea.addEventListener("input", () => update_token_counter(id_button));
+		textarea.addEventListener("input", function(){
+		    update_token_counter(id_button);
+		});
     }
 
     registerTextarea('txt2img_prompt', 'txt2img_token_counter', 'txt2img_token_button')
@@ -261,10 +262,8 @@ onUiUpdate(function(){
             })
         }
     }
-
 })
 
-
 onOptionsChanged(function(){
     elem = gradioApp().getElementById('sd_checkpoint_hash')
     sd_checkpoint_hash = opts.sd_checkpoint_hash || ""
diff --git a/modules/api/api.py b/modules/api/api.py
index 9814bbc2..2c371e6e 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -480,7 +480,7 @@ class Api:
     def train_hypernetwork(self, args: dict):
         try:
             shared.state.begin()
-            initial_hypernetwork = shared.loaded_hypernetwork
+            shared.loaded_hypernetworks = []
             apply_optimizations = shared.opts.training_xattention_optimizations
             error = None
             filename = ''
@@ -491,16 +491,15 @@ class Api:
             except Exception as e:
                 error = e
             finally:
-                shared.loaded_hypernetwork = initial_hypernetwork
                 shared.sd_model.cond_stage_model.to(devices.device)
                 shared.sd_model.first_stage_model.to(devices.device)
                 if not apply_optimizations:
                     sd_hijack.apply_optimizations()
                 shared.state.end()
-            return TrainResponse(info = "train embedding complete: filename: {filename} error: {error}".format(filename = filename, error = error))
+            return TrainResponse(info="train embedding complete: filename: {filename} error: {error}".format(filename=filename, error=error))
         except AssertionError as msg:
             shared.state.end()
-            return TrainResponse(info = "train embedding error: {error}".format(error = error))
+            return TrainResponse(info="train embedding error: {error}".format(error=error))
 
     def get_memory(self):
         try:
diff --git a/modules/extra_networks.py b/modules/extra_networks.py
new file mode 100644
index 00000000..1978673d
--- /dev/null
+++ b/modules/extra_networks.py
@@ -0,0 +1,147 @@
+import re
+from collections import defaultdict
+
+from modules import errors
+
+extra_network_registry = {}
+
+
+def initialize():
+    extra_network_registry.clear()
+
+
+def register_extra_network(extra_network):
+    extra_network_registry[extra_network.name] = extra_network
+
+
+class ExtraNetworkParams:
+    def __init__(self, items=None):
+        self.items = items or []
+
+
+class ExtraNetwork:
+    def __init__(self, name):
+        self.name = name
+
+    def activate(self, p, params_list):
+        """
+        Called by processing on every run. Whatever the extra network is meant to do should be activated here.
+        Passes arguments related to this extra network in params_list.
+        User passes arguments by specifying this in his prompt:
+
+        <name:arg1:arg2:arg3>
+
+        Where name matches the name of this ExtraNetwork object, and arg1:arg2:arg3 are any natural number of text arguments
+        separated by colon.
+
+        Even if the user does not mention this ExtraNetwork in his prompt, the call will stil be made, with empty params_list -
+        in this case, all effects of this extra networks should be disabled.
+
+        Can be called multiple times before deactivate() - each new call should override the previous call completely.
+
+        For example, if this ExtraNetwork's name is 'hypernet' and user's prompt is:
+
+        > "1girl, <hypernet:agm:1.1> <extrasupernet:master:12:13:14> <hypernet:ray>"
+
+        params_list will be:
+
+        [
+            ExtraNetworkParams(items=["agm", "1.1"]),
+            ExtraNetworkParams(items=["ray"])
+        ]
+
+        """
+        raise NotImplementedError
+
+    def deactivate(self, p):
+        """
+        Called at the end of processing for housekeeping. No need to do anything here.
+        """
+
+        raise NotImplementedError
+
+
+def activate(p, extra_network_data):
+    """call activate for extra networks in extra_network_data in specified order, then call
+    activate for all remaining registered networks with an empty argument list"""
+
+    for extra_network_name, extra_network_args in extra_network_data.items():
+        extra_network = extra_network_registry.get(extra_network_name, None)
+        if extra_network is None:
+            print(f"Skipping unknown extra network: {extra_network_name}")
+            continue
+
+        try:
+            extra_network.activate(p, extra_network_args)
+        except Exception as e:
+            errors.display(e, f"activating extra network {extra_network_name} with arguments {extra_network_args}")
+
+    for extra_network_name, extra_network in extra_network_registry.items():
+        args = extra_network_data.get(extra_network_name, None)
+        if args is not None:
+            continue
+
+        try:
+            extra_network.activate(p, [])
+        except Exception as e:
+            errors.display(e, f"activating extra network {extra_network_name}")
+
+
+def deactivate(p, extra_network_data):
+    """call deactivate for extra networks in extra_network_data in specified order, then call
+    deactivate for all remaining registered networks"""
+
+    for extra_network_name, extra_network_args in extra_network_data.items():
+        extra_network = extra_network_registry.get(extra_network_name, None)
+        if extra_network is None:
+            continue
+
+        try:
+            extra_network.deactivate(p)
+        except Exception as e:
+            errors.display(e, f"deactivating extra network {extra_network_name}")
+
+    for extra_network_name, extra_network in extra_network_registry.items():
+        args = extra_network_data.get(extra_network_name, None)
+        if args is not None:
+            continue
+
+        try:
+            extra_network.deactivate(p)
+        except Exception as e:
+            errors.display(e, f"deactivating unmentioned extra network {extra_network_name}")
+
+
+re_extra_net = re.compile(r"<(\w+):([^>]+)>")
+
+
+def parse_prompt(prompt):
+    res = defaultdict(list)
+
+    def found(m):
+        name = m.group(1)
+        args = m.group(2)
+
+        res[name].append(ExtraNetworkParams(items=args.split(":")))
+
+        return ""
+
+    prompt = re.sub(re_extra_net, found, prompt)
+
+    return prompt, res
+
+
+def parse_prompts(prompts):
+    res = []
+    extra_data = None
+
+    for prompt in prompts:
+        updated_prompt, parsed_extra_data = parse_prompt(prompt)
+
+        if extra_data is None:
+            extra_data = parsed_extra_data
+
+        res.append(updated_prompt)
+
+    return res, extra_data
+
diff --git a/modules/extra_networks_hypernet.py b/modules/extra_networks_hypernet.py
new file mode 100644
index 00000000..6a0c4ba8
--- /dev/null
+++ b/modules/extra_networks_hypernet.py
@@ -0,0 +1,21 @@
+from modules import extra_networks
+from modules.hypernetworks import hypernetwork
+
+
+class ExtraNetworkHypernet(extra_networks.ExtraNetwork):
+    def __init__(self):
+        super().__init__('hypernet')
+
+    def activate(self, p, params_list):
+        names = []
+        multipliers = []
+        for params in params_list:
+            assert len(params.items) > 0
+
+            names.append(params.items[0])
+            multipliers.append(float(params.items[1]) if len(params.items) > 1 else 1.0)
+
+        hypernetwork.load_hypernetworks(names, multipliers)
+
+    def deactivate(p, self):
+        pass
diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py
index a381ff59..46e12dc6 100644
--- a/modules/generation_parameters_copypaste.py
+++ b/modules/generation_parameters_copypaste.py
@@ -79,8 +79,6 @@ def integrate_settings_paste_fields(component_dict):
     from modules import ui
 
     settings_map = {
-        'sd_hypernetwork': 'Hypernet',
-        'sd_hypernetwork_strength': 'Hypernet strength',
         'CLIP_stop_at_last_layers': 'Clip skip',
         'inpainting_mask_weight': 'Conditional mask weight',
         'sd_model_checkpoint': 'Model hash',
@@ -275,13 +273,9 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
     if "Clip skip" not in res:
         res["Clip skip"] = "1"
 
-    if "Hypernet strength" not in res:
-        res["Hypernet strength"] = "1"
-
-    if "Hypernet" in res:
-        hypernet_name = res["Hypernet"]
-        hypernet_hash = res.get("Hypernet hash", None)
-        res["Hypernet"] = find_hypernetwork_key(hypernet_name, hypernet_hash)
+    hypernet = res.get("Hypernet", None)
+    if hypernet is not None:
+        res["Prompt"] += f"""<hypernet:{hypernet}:{res.get("Hypernet strength", "1.0")}>"""
 
     if "Hires resize-1" not in res:
         res["Hires resize-1"] = 0
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 74e78582..80a47c79 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -25,7 +25,6 @@ from statistics import stdev, mean
 optimizer_dict = {optim_name : cls_obj for optim_name, cls_obj in inspect.getmembers(torch.optim, inspect.isclass) if optim_name != "Optimizer"}
 
 class HypernetworkModule(torch.nn.Module):
-    multiplier = 1.0
     activation_dict = {
         "linear": torch.nn.Identity,
         "relu": torch.nn.ReLU,
@@ -41,6 +40,8 @@ class HypernetworkModule(torch.nn.Module):
                  add_layer_norm=False, activate_output=False, dropout_structure=None):
         super().__init__()
 
+        self.multiplier = 1.0
+
         assert layer_structure is not None, "layer_structure must not be None"
         assert layer_structure[0] == 1, "Multiplier Sequence should start with size 1!"
         assert layer_structure[-1] == 1, "Multiplier Sequence should end with size 1!"
@@ -115,7 +116,7 @@ class HypernetworkModule(torch.nn.Module):
             state_dict[to] = x
 
     def forward(self, x):
-        return x + self.linear(x) * (HypernetworkModule.multiplier if not self.training else 1)
+        return x + self.linear(x) * (self.multiplier if not self.training else 1)
 
     def trainables(self):
         layer_structure = []
@@ -125,9 +126,6 @@ class HypernetworkModule(torch.nn.Module):
         return layer_structure
 
 
-def apply_strength(value=None):
-    HypernetworkModule.multiplier = value if value is not None else shared.opts.sd_hypernetwork_strength
-
 #param layer_structure : sequence used for length, use_dropout : controlling boolean, last_layer_dropout : for compatibility check.
 def parse_dropout_structure(layer_structure, use_dropout, last_layer_dropout):
     if layer_structure is None:
@@ -192,6 +190,20 @@ class Hypernetwork:
                 for param in layer.parameters():
                     param.requires_grad = mode
 
+    def to(self, device):
+        for k, layers in self.layers.items():
+            for layer in layers:
+                layer.to(device)
+
+        return self
+
+    def set_multiplier(self, multiplier):
+        for k, layers in self.layers.items():
+            for layer in layers:
+                layer.multiplier = multiplier
+
+        return self
+
     def eval(self):
         for k, layers in self.layers.items():
             for layer in layers:
@@ -269,11 +281,13 @@ class Hypernetwork:
             self.optimizer_state_dict = None
         if self.optimizer_state_dict:
             self.optimizer_name = optimizer_saved_dict.get('optimizer_name', 'AdamW')
-            print("Loaded existing optimizer from checkpoint")
-            print(f"Optimizer name is {self.optimizer_name}")
+            if shared.opts.print_hypernet_extra:
+                print("Loaded existing optimizer from checkpoint")
+                print(f"Optimizer name is {self.optimizer_name}")
         else:
             self.optimizer_name = "AdamW"
-            print("No saved optimizer exists in checkpoint")
+            if shared.opts.print_hypernet_extra:
+                print("No saved optimizer exists in checkpoint")
 
         for size, sd in state_dict.items():
             if type(size) == int:
@@ -306,23 +320,43 @@ def list_hypernetworks(path):
     return res
 
 
-def load_hypernetwork(filename):
-    path = shared.hypernetworks.get(filename, None)
-    # Prevent any file named "None.pt" from being loaded.
-    if path is not None and filename != "None":
-        print(f"Loading hypernetwork {filename}")
-        try:
-            shared.loaded_hypernetwork = Hypernetwork()
-            shared.loaded_hypernetwork.load(path)
+def load_hypernetwork(name):
+    path = shared.hypernetworks.get(name, None)
 
-        except Exception:
-            print(f"Error loading hypernetwork {path}", file=sys.stderr)
-            print(traceback.format_exc(), file=sys.stderr)
-    else:
-        if shared.loaded_hypernetwork is not None:
-            print("Unloading hypernetwork")
+    if path is None:
+        return None
+
+    hypernetwork = Hypernetwork()
+
+    try:
+        hypernetwork.load(path)
+    except Exception:
+        print(f"Error loading hypernetwork {path}", file=sys.stderr)
+        print(traceback.format_exc(), file=sys.stderr)
+        return None
+
+    return hypernetwork
+
+
+def load_hypernetworks(names, multipliers=None):
+    already_loaded = {}
+
+    for hypernetwork in shared.loaded_hypernetworks:
+        if hypernetwork.name in names:
+            already_loaded[hypernetwork.name] = hypernetwork
 
-        shared.loaded_hypernetwork = None
+    shared.loaded_hypernetworks.clear()
+
+    for i, name in enumerate(names):
+        hypernetwork = already_loaded.get(name, None)
+        if hypernetwork is None:
+            hypernetwork = load_hypernetwork(name)
+
+        if hypernetwork is None:
+            continue
+
+        hypernetwork.set_multiplier(multipliers[i] if multipliers else 1.0)
+        shared.loaded_hypernetworks.append(hypernetwork)
 
 
 def find_closest_hypernetwork_name(search: str):
@@ -336,18 +370,27 @@ def find_closest_hypernetwork_name(search: str):
     return applicable[0]
 
 
-def apply_hypernetwork(hypernetwork, context, layer=None):
-    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
+def apply_single_hypernetwork(hypernetwork, context_k, context_v, layer=None):
+    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context_k.shape[2], None)
 
     if hypernetwork_layers is None:
-        return context, context
+        return context_k, context_v
 
     if layer is not None:
         layer.hyper_k = hypernetwork_layers[0]
         layer.hyper_v = hypernetwork_layers[1]
 
-    context_k = hypernetwork_layers[0](context)
-    context_v = hypernetwork_layers[1](context)
+    context_k = hypernetwork_layers[0](context_k)
+    context_v = hypernetwork_layers[1](context_v)
+    return context_k, context_v
+
+
+def apply_hypernetworks(hypernetworks, context, layer=None):
+    context_k = context
+    context_v = context
+    for hypernetwork in hypernetworks:
+        context_k, context_v = apply_single_hypernetwork(hypernetwork, context_k, context_v, layer)
+
     return context_k, context_v
 
 
@@ -357,7 +400,7 @@ def attention_CrossAttention_forward(self, x, context=None, mask=None):
     q = self.to_q(x)
     context = default(context, x)
 
-    context_k, context_v = apply_hypernetwork(shared.loaded_hypernetwork, context, self)
+    context_k, context_v = apply_hypernetworks(shared.loaded_hypernetworks, context, self)
     k = self.to_k(context_k)
     v = self.to_v(context_v)
 
@@ -464,8 +507,9 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
     template_file = template_file.path
 
     path = shared.hypernetworks.get(hypernetwork_name, None)
-    shared.loaded_hypernetwork = Hypernetwork()
-    shared.loaded_hypernetwork.load(path)
+    hypernetwork = Hypernetwork()
+    hypernetwork.load(path)
+    shared.loaded_hypernetworks = [hypernetwork]
 
     shared.state.job = "train-hypernetwork"
     shared.state.textinfo = "Initializing hypernetwork training..."
@@ -489,7 +533,6 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
     else:
         images_dir = None
 
-    hypernetwork = shared.loaded_hypernetwork
     checkpoint = sd_models.select_checkpoint()
 
     initial_step = hypernetwork.step or 0
diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py
index 81e3f519..76599f5a 100644
--- a/modules/hypernetworks/ui.py
+++ b/modules/hypernetworks/ui.py
@@ -9,6 +9,7 @@ from modules import devices, sd_hijack, shared
 not_available = ["hardswish", "multiheadattention"]
 keys = list(x for x in modules.hypernetworks.hypernetwork.HypernetworkModule.activation_dict.keys() if x not in not_available)
 
+
 def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False, dropout_structure=None):
     filename = modules.hypernetworks.hypernetwork.create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure, activation_func, weight_init, add_layer_norm, use_dropout, dropout_structure)
 
@@ -16,8 +17,7 @@ def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None,
 
 
 def train_hypernetwork(*args):
-
-    initial_hypernetwork = shared.loaded_hypernetwork
+    shared.loaded_hypernetworks = []
 
     assert not shared.cmd_opts.lowvram, 'Training models with lowvram is not possible'
 
@@ -34,7 +34,6 @@ Hypernetwork saved to {html.escape(filename)}
     except Exception:
         raise
     finally:
-        shared.loaded_hypernetwork = initial_hypernetwork
         shared.sd_model.cond_stage_model.to(devices.device)
         shared.sd_model.first_stage_model.to(devices.device)
         sd_hijack.apply_optimizations()
diff --git a/modules/processing.py b/modules/processing.py
index a3e9f709..b5deeacf 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -13,7 +13,7 @@ from skimage import exposure
 from typing import Any, Dict, List, Optional
 
 import modules.sd_hijack
-from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, script_callbacks
+from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, script_callbacks, extra_networks
 from modules.sd_hijack import model_hijack
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
@@ -438,9 +438,6 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
         "Size": f"{p.width}x{p.height}",
         "Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash),
         "Model": (None if not opts.add_model_name_to_info or not shared.sd_model.sd_checkpoint_info.model_name else shared.sd_model.sd_checkpoint_info.model_name.replace(',', '').replace(':', '')),
-        "Hypernet": (None if shared.loaded_hypernetwork is None else shared.loaded_hypernetwork.name),
-        "Hypernet hash": (None if shared.loaded_hypernetwork is None else shared.loaded_hypernetwork.shorthash()),
-        "Hypernet strength": (None if shared.loaded_hypernetwork is None or shared.opts.sd_hypernetwork_strength >= 1 else shared.opts.sd_hypernetwork_strength),
         "Batch size": (None if p.batch_size < 2 else p.batch_size),
         "Batch pos": (None if p.batch_size < 2 else position_in_batch),
         "Variation seed": (None if p.subseed_strength == 0 else all_subseeds[index]),
@@ -468,14 +465,12 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
     try:
         for k, v in p.override_settings.items():
             setattr(opts, k, v)
-            if k == 'sd_hypernetwork':
-                shared.reload_hypernetworks()  # make onchange call for changing hypernet
 
             if k == 'sd_model_checkpoint':
-                sd_models.reload_model_weights()  # make onchange call for changing SD model
+                sd_models.reload_model_weights()
 
             if k == 'sd_vae':
-                sd_vae.reload_vae_weights()  # make onchange call for changing VAE
+                sd_vae.reload_vae_weights()
 
         res = process_images_inner(p)
 
@@ -484,9 +479,11 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
         if p.override_settings_restore_afterwards:
             for k, v in stored_opts.items():
                 setattr(opts, k, v)
-                if k == 'sd_hypernetwork': shared.reload_hypernetworks()
-                if k == 'sd_model_checkpoint': sd_models.reload_model_weights()
-                if k == 'sd_vae': sd_vae.reload_vae_weights()
+                if k == 'sd_model_checkpoint':
+                    sd_models.reload_model_weights()
+
+                if k == 'sd_vae':
+                    sd_vae.reload_vae_weights()
 
     return res
 
@@ -564,10 +561,14 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
         cache[0] = (required_prompts, steps)
         return cache[1]
 
+    p.all_prompts, extra_network_data = extra_networks.parse_prompts(p.all_prompts)
+
     with torch.no_grad(), p.sd_model.ema_scope():
         with devices.autocast():
             p.init(p.all_prompts, p.all_seeds, p.all_subseeds)
 
+            extra_networks.activate(p, extra_network_data)
+
         with open(os.path.join(shared.script_path, "params.txt"), "w", encoding="utf8") as file:
             processed = Processed(p, [], p.seed, "")
             file.write(processed.infotext(p, 0))
@@ -681,6 +682,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
             if opts.grid_save:
                 images.save_image(grid, p.outpath_grids, "grid", p.all_seeds[0], p.all_prompts[0], opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename, p=p, grid=True)
 
+    extra_networks.deactivate(p, extra_network_data)
     devices.torch_gc()
 
     res = Processed(p, output_images, p.all_seeds[0], infotext(), comments="".join(["\n\n" + x for x in comments]), subseed=p.all_subseeds[0], index_of_first_image=index_of_first_image, infotexts=infotexts)
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index cdc63ed7..4fa54329 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -44,7 +44,7 @@ def split_cross_attention_forward_v1(self, x, context=None, mask=None):
     q_in = self.to_q(x)
     context = default(context, x)
 
-    context_k, context_v = hypernetwork.apply_hypernetwork(shared.loaded_hypernetwork, context)
+    context_k, context_v = hypernetwork.apply_hypernetworks(shared.loaded_hypernetworks, context)
     k_in = self.to_k(context_k)
     v_in = self.to_v(context_v)
     del context, context_k, context_v, x
@@ -78,7 +78,7 @@ def split_cross_attention_forward(self, x, context=None, mask=None):
     q_in = self.to_q(x)
     context = default(context, x)
 
-    context_k, context_v = hypernetwork.apply_hypernetwork(shared.loaded_hypernetwork, context)
+    context_k, context_v = hypernetwork.apply_hypernetworks(shared.loaded_hypernetworks, context)
     k_in = self.to_k(context_k)
     v_in = self.to_v(context_v)
 
@@ -203,7 +203,7 @@ def split_cross_attention_forward_invokeAI(self, x, context=None, mask=None):
     q = self.to_q(x)
     context = default(context, x)
 
-    context_k, context_v = hypernetwork.apply_hypernetwork(shared.loaded_hypernetwork, context)
+    context_k, context_v = hypernetwork.apply_hypernetworks(shared.loaded_hypernetworks, context)
     k = self.to_k(context_k) * self.scale
     v = self.to_v(context_v)
     del context, context_k, context_v, x
@@ -225,7 +225,7 @@ def sub_quad_attention_forward(self, x, context=None, mask=None):
     q = self.to_q(x)
     context = default(context, x)
 
-    context_k, context_v = hypernetwork.apply_hypernetwork(shared.loaded_hypernetwork, context)
+    context_k, context_v = hypernetwork.apply_hypernetworks(shared.loaded_hypernetworks, context)
     k = self.to_k(context_k)
     v = self.to_v(context_v)
     del context, context_k, context_v, x
@@ -284,7 +284,7 @@ def xformers_attention_forward(self, x, context=None, mask=None):
     q_in = self.to_q(x)
     context = default(context, x)
 
-    context_k, context_v = hypernetwork.apply_hypernetwork(shared.loaded_hypernetwork, context)
+    context_k, context_v = hypernetwork.apply_hypernetworks(shared.loaded_hypernetworks, context)
     k_in = self.to_k(context_k)
     v_in = self.to_v(context_v)
 
diff --git a/modules/shared.py b/modules/shared.py
index 2f366454..c0e11f18 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -23,6 +23,7 @@ demo = None
 sd_default_config = os.path.join(script_path, "configs/v1-inference.yaml")
 sd_model_file = os.path.join(script_path, 'model.ckpt')
 default_sd_model_file = sd_model_file
+
 parser = argparse.ArgumentParser()
 parser.add_argument("--config", type=str, default=sd_default_config, help="path to config which constructs model",)
 parser.add_argument("--ckpt", type=str, default=sd_model_file, help="path to checkpoint of stable diffusion model; if specified, this checkpoint will be added to the list of checkpoints and loaded",)
@@ -145,7 +146,7 @@ config_filename = cmd_opts.ui_settings_file
 
 os.makedirs(cmd_opts.hypernetwork_dir, exist_ok=True)
 hypernetworks = {}
-loaded_hypernetwork = None
+loaded_hypernetworks = []
 
 
 def reload_hypernetworks():
@@ -153,8 +154,6 @@ def reload_hypernetworks():
     global hypernetworks
 
     hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir)
-    hypernetwork.load_hypernetwork(opts.sd_hypernetwork)
-
 
 
 class State:
@@ -399,8 +398,6 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "sd_vae_checkpoint_cache": OptionInfo(0, "VAE Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
     "sd_vae": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": ["Automatic", "None"] + list(sd_vae.vae_dict)}, refresh=sd_vae.refresh_vae_list),
     "sd_vae_as_default": OptionInfo(True, "Ignore selected VAE for stable diffusion checkpoints that have their own .vae.pt next to them"),
-    "sd_hypernetwork": OptionInfo("None", "Hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks),
-    "sd_hypernetwork_strength": OptionInfo(1.0, "Hypernetwork strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.001}),
     "inpainting_mask_weight": OptionInfo(1.0, "Inpainting conditioning mask strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
     "initial_noise_multiplier": OptionInfo(1.0, "Noise multiplier for img2img", gr.Slider, {"minimum": 0.5, "maximum": 1.5, "step": 0.01 }),
     "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."),
@@ -661,3 +658,17 @@ mem_mon.start()
 def listfiles(dirname):
     filenames = [os.path.join(dirname, x) for x in sorted(os.listdir(dirname)) if not x.startswith(".")]
     return [file for file in filenames if os.path.isfile(file)]
+
+
+def html_path(filename):
+    return os.path.join(script_path, "html", filename)
+
+
+def html(filename):
+    path = html_path(filename)
+
+    if os.path.exists(path):
+        with open(path, encoding="utf8") as file:
+            return file.read()
+
+    return ""
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 5a7be422..4e90f690 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -50,6 +50,7 @@ class Embedding:
         self.sd_checkpoint = None
         self.sd_checkpoint_name = None
         self.optimizer_state_dict = None
+        self.filename = None
 
     def save(self, filename):
         embedding_data = {
@@ -182,6 +183,7 @@ class EmbeddingDatabase:
         embedding.sd_checkpoint_name = data.get('sd_checkpoint_name', None)
         embedding.vectors = vec.shape[0]
         embedding.shape = vec.shape[-1]
+        embedding.filename = path
 
         if self.expected_shape == -1 or self.expected_shape == embedding.shape:
             self.register_embedding(embedding, shared.sd_model)
diff --git a/modules/ui.py b/modules/ui.py
index 06c11848..d23b2b8e 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -20,7 +20,7 @@ import numpy as np
 from PIL import Image, PngImagePlugin
 from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
 
-from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae
+from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks
 from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
 from modules.paths import script_path
 
@@ -90,6 +90,7 @@ refresh_symbol = '\U0001f504'  # 🔄
 save_style_symbol = '\U0001f4be'  # 💾
 apply_style_symbol = '\U0001f4cb'  # 📋
 clear_prompt_symbol = '\U0001F5D1'  # 🗑️
+extra_networks_symbol = '\U0001F3B4'  # 🎴
 
 
 def plaintext_to_html(text):
@@ -324,6 +325,8 @@ def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info:
 
 def update_token_counter(text, steps):
     try:
+        text, _ = extra_networks.parse_prompt(text)
+
         _, prompt_flat_list, _ = prompt_parser.get_multicond_prompt_list([text])
         prompt_schedules = prompt_parser.get_learned_conditioning_prompt_schedules(prompt_flat_list, steps)
 
@@ -354,10 +357,10 @@ def create_toprow(is_img2img):
                         negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2, placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)")
 
         with gr.Column(scale=1, elem_id="roll_col"):
-            paste = gr.Button(value=paste_symbol, elem_id="paste")
-            save_style = gr.Button(value=save_style_symbol, elem_id="style_create")
-            prompt_style_apply = gr.Button(value=apply_style_symbol, elem_id="style_apply")
-            clear_prompt_button = gr.Button(value=clear_prompt_symbol, elem_id=f"{id_part}_clear_prompt")
+            paste = ToolButton(value=paste_symbol, elem_id="paste")
+            clear_prompt_button = ToolButton(value=clear_prompt_symbol, elem_id=f"{id_part}_clear_prompt")
+            extra_networks_button = ToolButton(value=extra_networks_symbol, elem_id=f"{id_part}_extra_networks")
+
             token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_token_counter")
             token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button")
             negative_token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_negative_token_counter")
@@ -395,11 +398,14 @@ def create_toprow(is_img2img):
                     outputs=[],
                 )
 
-            with gr.Row():
+            with gr.Row(elem_id=f"{id_part}_styles_row"):
                 prompt_styles = gr.Dropdown(label="Styles", elem_id=f"{id_part}_styles", choices=[k for k, v in shared.prompt_styles.styles.items()], value=[], multiselect=True)
                 create_refresh_button(prompt_styles, shared.prompt_styles.reload, lambda: {"choices": [k for k, v in shared.prompt_styles.styles.items()]}, f"refresh_{id_part}_styles")
 
-    return prompt, prompt_styles, negative_prompt, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button, negative_token_counter, negative_token_button
+                prompt_style_apply = ToolButton(value=apply_style_symbol, elem_id="style_apply")
+                save_style = ToolButton(value=save_style_symbol, elem_id="style_create")
+
+    return prompt, prompt_styles, negative_prompt, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, extra_networks_button, token_counter, token_button, negative_token_counter, negative_token_button
 
 
 def setup_progressbar(*args, **kwargs):
@@ -616,11 +622,15 @@ def create_ui():
     modules.scripts.scripts_txt2img.initialize_scripts(is_img2img=False)
 
     with gr.Blocks(analytics_enabled=False) as txt2img_interface:
-        txt2img_prompt, txt2img_prompt_styles, txt2img_negative_prompt, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button, negative_token_counter, negative_token_button = create_toprow(is_img2img=False)
+        txt2img_prompt, txt2img_prompt_styles, txt2img_negative_prompt, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, extra_networks_button, token_counter, token_button, negative_token_counter, negative_token_button = create_toprow(is_img2img=False)
 
         dummy_component = gr.Label(visible=False)
         txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="binary", visible=False)
 
+        with FormRow(variant='compact', elem_id="txt2img_extra_networks", visible=False) as extra_networks:
+            from modules import ui_extra_networks
+            extra_networks_ui = ui_extra_networks.create_ui(extra_networks, extra_networks_button, 'txt2img')
+
         with gr.Row().style(equal_height=False):
             with gr.Column(variant='compact', elem_id="txt2img_settings"):
                 for category in ordered_ui_categories():
@@ -794,14 +804,20 @@ def create_ui():
             token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[txt2img_prompt, steps], outputs=[token_counter])
             negative_token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[txt2img_negative_prompt, steps], outputs=[negative_token_counter])
 
+            ui_extra_networks.setup_ui(extra_networks_ui, txt2img_gallery)
+
     modules.scripts.scripts_current = modules.scripts.scripts_img2img
     modules.scripts.scripts_img2img.initialize_scripts(is_img2img=True)
 
     with gr.Blocks(analytics_enabled=False) as img2img_interface:
-        img2img_prompt, img2img_prompt_styles, img2img_negative_prompt, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste, token_counter, token_button, negative_token_counter, negative_token_button = create_toprow(is_img2img=True)
+        img2img_prompt, img2img_prompt_styles, img2img_negative_prompt, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste, extra_networks_button, token_counter, token_button, negative_token_counter, negative_token_button = create_toprow(is_img2img=True)
 
         img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="binary", visible=False)
 
+        with FormRow(variant='compact', elem_id="img2img_extra_networks", visible=False) as extra_networks:
+            from modules import ui_extra_networks
+            extra_networks_ui_img2img = ui_extra_networks.create_ui(extra_networks, extra_networks_button, 'img2img')
+
         with FormRow().style(equal_height=False):
             with gr.Column(variant='compact', elem_id="img2img_settings"):
                 copy_image_buttons = []
@@ -1064,6 +1080,8 @@ def create_ui():
             token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter])
             negative_token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[txt2img_negative_prompt, steps], outputs=[negative_token_counter])
 
+            ui_extra_networks.setup_ui(extra_networks_ui_img2img, img2img_gallery)
+
             img2img_paste_fields = [
                 (img2img_prompt, "Prompt"),
                 (img2img_negative_prompt, "Negative prompt"),
@@ -1666,10 +1684,8 @@ def create_ui():
                 download_localization = gr.Button(value='Download localization template', elem_id="download_localization")
                 reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary', elem_id="settings_reload_script_bodies")
 
-            if os.path.exists("html/licenses.html"):
-                with open("html/licenses.html", encoding="utf8") as file:
-                    with gr.TabItem("Licenses"):
-                        gr.HTML(file.read(), elem_id="licenses")
+            with gr.TabItem("Licenses"):
+                gr.HTML(shared.html("licenses.html"), elem_id="licenses")
 
             gr.Button(value="Show all pages", elem_id="settings_show_all_pages")
 
@@ -1756,11 +1772,9 @@ def create_ui():
         if os.path.exists(os.path.join(script_path, "notification.mp3")):
             audio_notification = gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False)
 
-        if os.path.exists("html/footer.html"):
-            with open("html/footer.html", encoding="utf8") as file:
-                footer = file.read()
-                footer = footer.format(versions=versions_html())
-                gr.HTML(footer, elem_id="footer")
+        footer = shared.html("footer.html")
+        footer = footer.format(versions=versions_html())
+        gr.HTML(footer, elem_id="footer")
 
         text_settings = gr.Textbox(elem_id="settings_json", value=lambda: opts.dumpjson(), visible=False)
         settings_submit.click(
diff --git a/modules/ui_components.py b/modules/ui_components.py
index 97acff06..46324425 100644
--- a/modules/ui_components.py
+++ b/modules/ui_components.py
@@ -11,6 +11,16 @@ class ToolButton(gr.Button, gr.components.FormComponent):
         return "button"
 
 
+class ToolButtonTop(gr.Button, gr.components.FormComponent):
+    """Small button with single emoji as text, with extra margin at top, fits inside gradio forms"""
+
+    def __init__(self, **kwargs):
+        super().__init__(variant="tool-top", **kwargs)
+
+    def get_block_name(self):
+        return "button"
+
+
 class FormRow(gr.Row, gr.components.FormComponent):
     """Same as gr.Row but fits inside gradio forms"""
 
diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py
new file mode 100644
index 00000000..253e90f7
--- /dev/null
+++ b/modules/ui_extra_networks.py
@@ -0,0 +1,149 @@
+import os.path
+
+from modules import shared
+import gradio as gr
+import json
+
+from modules.generation_parameters_copypaste import image_from_url_text
+
+extra_pages = []
+
+
+def register_page(page):
+    """registers extra networks page for the UI; recommend doing it in on_app_started() callback for extensions"""
+
+    extra_pages.append(page)
+
+
+class ExtraNetworksPage:
+    def __init__(self, title):
+        self.title = title
+        self.card_page = shared.html("extra-networks-card.html")
+        self.allow_negative_prompt = False
+
+    def refresh(self):
+        pass
+
+    def create_html(self, tabname):
+        items_html = ''
+
+        for item in self.list_items():
+            items_html += self.create_html_for_item(item, tabname)
+
+        if items_html == '':
+            dirs = "".join([f"<li>{x}</li>" for x in self.allowed_directories_for_previews()])
+            items_html = shared.html("extra-networks-no-cards.html").format(dirs=dirs)
+
+        res = "<div class='extra-network-cards'>" + items_html + "</div>"
+
+        return res
+
+    def list_items(self):
+        raise NotImplementedError()
+
+    def allowed_directories_for_previews(self):
+        return []
+
+    def create_html_for_item(self, item, tabname):
+        preview = item.get("preview", None)
+
+        args = {
+            "preview_html": "style='background-image: url(" + json.dumps(preview) + ")'" if preview else '',
+            "prompt": json.dumps(item["prompt"]),
+            "tabname": json.dumps(tabname),
+            "local_preview": json.dumps(item["local_preview"]),
+            "name": item["name"],
+            "allow_negative_prompt": "true" if self.allow_negative_prompt else "false",
+        }
+
+        return self.card_page.format(**args)
+
+
+def intialize():
+    extra_pages.clear()
+
+
+class ExtraNetworksUi:
+    def __init__(self):
+        self.pages = None
+        self.stored_extra_pages = None
+
+        self.button_save_preview = None
+        self.preview_target_filename = None
+
+        self.tabname = None
+
+
+def create_ui(container, button, tabname):
+    ui = ExtraNetworksUi()
+    ui.pages = []
+    ui.stored_extra_pages = extra_pages.copy()
+    ui.tabname = tabname
+
+    with gr.Tabs(elem_id=tabname+"_extra_tabs") as tabs:
+        button_refresh = gr.Button('Refresh', elem_id=tabname+"_extra_refresh")
+        button_close = gr.Button('Close', elem_id=tabname+"_extra_close")
+
+        for page in ui.stored_extra_pages:
+            with gr.Tab(page.title):
+                page_elem = gr.HTML(page.create_html(ui.tabname))
+                ui.pages.append(page_elem)
+
+    ui.button_save_preview = gr.Button('Save preview', elem_id=tabname+"_save_preview", visible=False)
+    ui.preview_target_filename = gr.Textbox('Preview save filename', elem_id=tabname+"_preview_filename", visible=False)
+
+    button.click(fn=lambda: gr.update(visible=True), inputs=[], outputs=[container])
+    button_close.click(fn=lambda: gr.update(visible=False), inputs=[], outputs=[container])
+
+    def refresh():
+        res = []
+
+        for pg in ui.stored_extra_pages:
+            pg.refresh()
+            res.append(pg.create_html(ui.tabname))
+
+        return res
+
+    button_refresh.click(fn=refresh, inputs=[], outputs=ui.pages)
+
+    return ui
+
+
+def path_is_parent(parent_path, child_path):
+    parent_path = os.path.abspath(parent_path)
+    child_path = os.path.abspath(child_path)
+
+    return os.path.commonpath([parent_path]) == os.path.commonpath([parent_path, child_path])
+
+
+def setup_ui(ui, gallery):
+    def save_preview(index, images, filename):
+        if len(images) == 0:
+            print("There is no image in gallery to save as a preview.")
+            return [page.create_html(ui.tabname) for page in ui.stored_extra_pages]
+
+        index = int(index)
+        index = 0 if index < 0 else index
+        index = len(images) - 1 if index >= len(images) else index
+
+        img_info = images[index if index >= 0 else 0]
+        image = image_from_url_text(img_info)
+
+        is_allowed = False
+        for extra_page in ui.stored_extra_pages:
+            if any([path_is_parent(x, filename) for x in extra_page.allowed_directories_for_previews()]):
+                is_allowed = True
+                break
+
+        assert is_allowed, f'writing to {filename} is not allowed'
+
+        image.save(filename)
+
+        return [page.create_html(ui.tabname) for page in ui.stored_extra_pages]
+
+    ui.button_save_preview.click(
+        fn=save_preview,
+        _js="function(x, y, z){console.log(x, y, z); return [selected_gallery_index(), y, z]}",
+        inputs=[ui.preview_target_filename, gallery, ui.preview_target_filename],
+        outputs=[*ui.pages]
+    )
diff --git a/modules/ui_extra_networks_hypernets.py b/modules/ui_extra_networks_hypernets.py
new file mode 100644
index 00000000..312dbaf0
--- /dev/null
+++ b/modules/ui_extra_networks_hypernets.py
@@ -0,0 +1,34 @@
+import os
+
+from modules import shared, ui_extra_networks
+
+
+class ExtraNetworksPageHypernetworks(ui_extra_networks.ExtraNetworksPage):
+    def __init__(self):
+        super().__init__('Hypernetworks')
+
+    def refresh(self):
+        shared.reload_hypernetworks()
+
+    def list_items(self):
+        for name, path in shared.hypernetworks.items():
+            path, ext = os.path.splitext(path)
+            previews = [path + ".png", path + ".preview.png"]
+
+            preview = None
+            for file in previews:
+                if os.path.isfile(file):
+                    preview = "./file=" + file.replace('\\', '/') + "?mtime=" + str(os.path.getmtime(file))
+                    break
+
+            yield {
+                "name": name,
+                "filename": path,
+                "preview": preview,
+                "prompt": f"<hypernet:{name}:1.0>",
+                "local_preview": path + ".png",
+            }
+
+    def allowed_directories_for_previews(self):
+        return [shared.cmd_opts.hypernetwork_dir]
+
diff --git a/modules/ui_extra_networks_textual_inversion.py b/modules/ui_extra_networks_textual_inversion.py
new file mode 100644
index 00000000..e4a6e3bf
--- /dev/null
+++ b/modules/ui_extra_networks_textual_inversion.py
@@ -0,0 +1,32 @@
+import os
+
+from modules import ui_extra_networks, sd_hijack
+
+
+class ExtraNetworksPageTextualInversion(ui_extra_networks.ExtraNetworksPage):
+    def __init__(self):
+        super().__init__('Textual Inversion')
+        self.allow_negative_prompt = True
+
+    def refresh(self):
+        sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings(force_reload=True)
+
+    def list_items(self):
+        for embedding in sd_hijack.model_hijack.embedding_db.word_embeddings.values():
+            path, ext = os.path.splitext(embedding.filename)
+            preview_file = path + ".preview.png"
+
+            preview = None
+            if os.path.isfile(preview_file):
+                preview = "./file=" + preview_file.replace('\\', '/') + "?mtime=" + str(os.path.getmtime(preview_file))
+
+            yield {
+                "name": embedding.name,
+                "filename": embedding.filename,
+                "preview": preview,
+                "prompt": embedding.name,
+                "local_preview": path + ".preview.png",
+            }
+
+    def allowed_directories_for_previews(self):
+        return list(sd_hijack.model_hijack.embedding_db.embedding_dirs)
diff --git a/script.js b/script.js
index 3345e32b..97e0bfcf 100644
--- a/script.js
+++ b/script.js
@@ -13,6 +13,7 @@ function get_uiCurrentTabContent() {
 }
 
 uiUpdateCallbacks = []
+uiLoadedCallbacks = []
 uiTabChangeCallbacks = []
 optionsChangedCallbacks = []
 let uiCurrentTab = null
@@ -20,6 +21,9 @@ let uiCurrentTab = null
 function onUiUpdate(callback){
     uiUpdateCallbacks.push(callback)
 }
+function onUiLoaded(callback){
+    uiLoadedCallbacks.push(callback)
+}
 function onUiTabChange(callback){
     uiTabChangeCallbacks.push(callback)
 }
@@ -38,8 +42,15 @@ function executeCallbacks(queue, m) {
     queue.forEach(function(x){runCallback(x, m)})
 }
 
+var executedOnLoaded = false;
+
 document.addEventListener("DOMContentLoaded", function() {
     var mutationObserver = new MutationObserver(function(m){
+        if(!executedOnLoaded && gradioApp().querySelector('#txt2img_prompt')){
+            executedOnLoaded = true;
+            executeCallbacks(uiLoadedCallbacks);
+        }
+
         executeCallbacks(uiUpdateCallbacks, m);
         const newTab = get_uiCurrentTab();
         if ( newTab && ( newTab !== uiCurrentTab ) ) {
@@ -53,7 +64,7 @@ document.addEventListener("DOMContentLoaded", function() {
 /**
  * Add a ctrl+enter as a shortcut to start a generation
  */
- document.addEventListener('keydown', function(e) {
+document.addEventListener('keydown', function(e) {
     var handled = false;
     if (e.key !== undefined) {
         if((e.key == "Enter" && (e.metaKey || e.ctrlKey || e.altKey))) handled = true;
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 6629f5d5..b1badec9 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -11,7 +11,6 @@ import modules.scripts as scripts
 import gradio as gr
 
 from modules import images, paths, sd_samplers, processing, sd_models, sd_vae
-from modules.hypernetworks import hypernetwork
 from modules.processing import process_images, Processed, StableDiffusionProcessingTxt2Img
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
@@ -94,28 +93,6 @@ def confirm_checkpoints(p, xs):
             raise RuntimeError(f"Unknown checkpoint: {x}")
 
 
-def apply_hypernetwork(p, x, xs):
-    if x.lower() in ["", "none"]:
-        name = None
-    else:
-        name = hypernetwork.find_closest_hypernetwork_name(x)
-        if not name:
-            raise RuntimeError(f"Unknown hypernetwork: {x}")
-    hypernetwork.load_hypernetwork(name)
-
-
-def apply_hypernetwork_strength(p, x, xs):
-    hypernetwork.apply_strength(x)
-
-
-def confirm_hypernetworks(p, xs):
-    for x in xs:
-        if x.lower() in ["", "none"]:
-            continue
-        if not hypernetwork.find_closest_hypernetwork_name(x):
-            raise RuntimeError(f"Unknown hypernetwork: {x}")
-
-
 def apply_clip_skip(p, x, xs):
     opts.data["CLIP_stop_at_last_layers"] = x
 
@@ -208,8 +185,6 @@ axis_options = [
     AxisOption("Prompt order", str_permutations, apply_order, format_value=format_value_join_list),
     AxisOption("Sampler", str, apply_sampler, format_value=format_value, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.samplers]),
     AxisOption("Checkpoint name", str, apply_checkpoint, format_value=format_value, confirm=confirm_checkpoints, cost=1.0, choices=lambda: list(sd_models.checkpoints_list)),
-    AxisOption("Hypernetwork", str, apply_hypernetwork, format_value=format_value, confirm=confirm_hypernetworks, cost=0.2, choices=lambda: list(shared.hypernetworks)),
-    AxisOption("Hypernet str.", float, apply_hypernetwork_strength),
     AxisOption("Sigma Churn", float, apply_field("s_churn")),
     AxisOption("Sigma min", float, apply_field("s_tmin")),
     AxisOption("Sigma max", float, apply_field("s_tmax")),
@@ -291,7 +266,6 @@ def draw_xy_grid(p, xs, ys, x_labels, y_labels, cell, draw_legend, include_lone_
 class SharedSettingsStackHelper(object):
     def __enter__(self):
         self.CLIP_stop_at_last_layers = opts.CLIP_stop_at_last_layers
-        self.hypernetwork = opts.sd_hypernetwork
         self.vae = opts.sd_vae
   
     def __exit__(self, exc_type, exc_value, tb):
@@ -299,9 +273,6 @@ class SharedSettingsStackHelper(object):
         modules.sd_models.reload_model_weights()
         modules.sd_vae.reload_vae_weights()
 
-        hypernetwork.load_hypernetwork(self.hypernetwork)
-        hypernetwork.apply_strength()
-
         opts.data["CLIP_stop_at_last_layers"] = self.CLIP_stop_at_last_layers
 
 
diff --git a/style.css b/style.css
index 3a515ebd..5e8bc2ca 100644
--- a/style.css
+++ b/style.css
@@ -132,13 +132,6 @@
 }
 
 #roll_col > button {
-    min-width: 2em;
-    min-height: 2em;
-    max-width: 2em;
-    max-height: 2em;
-    flex-grow: 0;
-    padding-left: 0.25em;
-    padding-right: 0.25em;
     margin: 0.1em 0;
 }
 
@@ -146,9 +139,10 @@
     min-width: 0 !important;
     max-width: 8em !important;
     margin-right: 1em;
+    gap: 0;
 }
 #interrogate, #deepbooru{
-    margin: 0em 0.25em 0.9em 0.25em;
+    margin: 0em 0.25em 0.5em 0.25em;
     min-width: 8em;
     max-width: 8em;
 }
@@ -157,8 +151,17 @@
     min-width: 8em !important;
 }
 
+#txt2img_styles_row, #img2img_styles_row{
+    gap: 0.25em;
+    margin-top: 0.5em;
+}
+
+#txt2img_styles_row > button, #img2img_styles_row > button{
+    margin: 0;
+}
+
 #txt2img_styles, #img2img_styles{
-    margin-top: 1em;
+    padding: 0;
 }
 
 #txt2img_styles ul, #img2img_styles ul{
@@ -635,17 +638,21 @@ canvas[key="mask"] {
     background-color: rgb(31 41 55 / var(--tw-bg-opacity));
 }
 
-.gr-button-tool{
+.gr-button-tool, .gr-button-tool-top{
     max-width: 2.5em;
     min-width: 2.5em !important;
     height: 2.4em;
-    margin: 1.6em 0.7em 0.55em 0;
 }
 
-#tab_modelmerger .gr-button-tool{
+.gr-button-tool{
     margin: 0.6em 0em 0.55em 0;
 }
 
+.gr-button-tool-top, #settings .gr-button-tool{
+    margin: 1.6em 0.7em 0.55em 0;
+}
+
+
 #modelmerger_results_container{
     margin-top: 1em;
     overflow: visible;
@@ -763,81 +770,88 @@ footer {
     line-height: 2.4em;
 }
 
-/* The following handles localization for right-to-left (RTL) languages like Arabic.
-The rtl media type will only be activated by the logic in javascript/localization.js.
-If you change anything above, you need to make sure it is RTL compliant by just running
-your changes through converters like https://cssjanus.github.io/ or https://rtlcss.com/.
-Then, you will need to add the RTL counterpart only if needed in the rtl section below.*/
-@media rtl {
-    /* this part was added manually */
-    :host {
-        direction: rtl;
-    }
-    select, .file-preview, .gr-text-input, .output-html:has(.performance), #ti_progress {
-        direction: ltr;
-    }
-    #script_list > label > select,
-    #x_type > label > select,
-    #y_type > label > select {
-        direction: rtl;
-    }
-    .gr-radio, .gr-checkbox{
-        margin-left: 0.25em;
-    }
+#txt2img_extra_networks, #img2img_extra_networks{
+    margin-top: -1em;
+}
 
-    /* automatically generated with few manual modifications */
-    .performance .time {
-        margin-right: unset;
-        margin-left: 0;
-    }
-    .justify-center.overflow-x-scroll {
-        justify-content: right;
-    }
-    .justify-center.overflow-x-scroll button:first-of-type {
-        margin-left: unset;
-        margin-right: auto;
-    }
-    .justify-center.overflow-x-scroll button:last-of-type {
-        margin-right: unset;
-        margin-left: auto;
-    }
-    #settings fieldset span.text-gray-500, #settings .gr-block.gr-box span.text-gray-500, #settings label.block span{
-        margin-right: unset;
-        margin-left: 8em;
-    }
-    #txt2img_progressbar, #img2img_progressbar, #ti_progressbar{
-        right: unset;
-        left: 0;
-    }
-    .progressDiv .progress{
-        padding: 0 0 0 8px;
-        text-align: left;
-    }
-    #lightboxModal{
-        left: unset;
-        right: 0;
-    }
-    .modalPrev, .modalNext{
-        border-radius: 3px 0 0 3px;
-    }
-    .modalNext {
-        right: unset;
-        left: 0;
-        border-radius: 0 3px 3px 0;
-    }
-    #imageARPreview{
-        left:unset;
-        right:0px;
-    }
-    #txt2img_skip, #img2img_skip{
-        right: unset;
-        left: 0px;
-    }
-    #context-menu{
-        box-shadow:-1px 1px 2px #CE6400;
-    }
-    .gr-box > div > div > input.gr-text-input{
-        right: unset;
-        left: 0.5em;
-    }
+.extra-networks > div > [id *= '_extra_']{
+    margin: 0.3em;
 }
+
+.extra-network-cards .nocards{
+    margin: 1.25em 0.5em 0.5em 0.5em;
+}
+
+.extra-network-cards .nocards h1{
+    font-size: 1.5em;
+    margin-bottom: 1em;
+}
+
+.extra-network-cards .nocards li{
+    margin-left: 0.5em;
+}
+
+.extra-network-cards .card{
+    display: inline-block;
+    margin: 0.5em;
+    width: 16em;
+    height: 24em;
+    box-shadow: 0 0 5px rgba(128, 128, 128, 0.5);
+    border-radius: 0.2em;
+    position: relative;
+
+    background-size: auto 100%;
+    background-position: center;
+    overflow: hidden;
+    cursor: pointer;
+
+    background-image: url('./file=html/card-no-preview.png')
+}
+
+.extra-network-cards .card:hover{
+    box-shadow: 0 0 2px 0.3em rgba(0, 128, 255, 0.35);
+}
+
+.extra-network-cards .card .actions .additional{
+    display: none;
+}
+
+.extra-network-cards .card .actions{
+    position: absolute;
+    bottom: 0;
+    left: 0;
+    right: 0;
+    padding: 0.5em;
+    color: white;
+    background: rgba(0,0,0,0.5);
+    box-shadow: 0 0 0.25em 0.25em rgba(0,0,0,0.5);
+    text-shadow: 0 0 0.2em black;
+}
+
+.extra-network-cards .card .actions:hover{
+    box-shadow: 0 0 0.75em 0.75em rgba(0,0,0,0.5) !important;
+}
+
+.extra-network-cards .card .actions .name{
+    font-size: 1.7em;
+    font-weight: bold;
+    line-break: anywhere;
+}
+
+.extra-network-cards .card .actions:hover .additional{
+    display: block;
+}
+
+.extra-network-cards .card ul{
+    margin: 0.25em 0 0.75em 0.25em;
+    cursor: unset;
+}
+
+.extra-network-cards .card ul a{
+    cursor: pointer;
+}
+
+.extra-network-cards .card ul a:hover{
+    color: red;
+}
+
diff --git a/webui.py b/webui.py
index 865a7300..e8dd822a 100644
--- a/webui.py
+++ b/webui.py
@@ -9,16 +9,18 @@ from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.middleware.gzip import GZipMiddleware
 
-from modules import import_hook, errors
+from modules import import_hook, errors, extra_networks
+from modules import extra_networks_hypernet, ui_extra_networks_hypernets, ui_extra_networks_textual_inversion
 from modules.call_queue import wrap_queued_call, queue_lock, wrap_gradio_gpu_call
 from modules.paths import script_path
 
 import torch
+
 # Truncate version number of nightly/local build of PyTorch to not cause exceptions with CodeFormer or Safetensors
 if ".dev" in torch.__version__ or "+git" in torch.__version__:
     torch.__version__ = re.search(r'[\d.]+[\d]', torch.__version__).group(0)
 
-from modules import shared, devices, sd_samplers, upscaler, extensions, localization, ui_tempdir
+from modules import shared, devices, sd_samplers, upscaler, extensions, localization, ui_tempdir, ui_extra_networks
 import modules.codeformer_model as codeformer
 import modules.extras
 import modules.face_restoration
@@ -84,10 +86,17 @@ def initialize():
     shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights()))
     shared.opts.onchange("sd_vae", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)
     shared.opts.onchange("sd_vae_as_default", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)
-    shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: shared.reload_hypernetworks()))
-    shared.opts.onchange("sd_hypernetwork_strength", modules.hypernetworks.hypernetwork.apply_strength)
     shared.opts.onchange("temp_dir", ui_tempdir.on_tmpdir_changed)
 
+    shared.reload_hypernetworks()
+
+    ui_extra_networks.intialize()
+    ui_extra_networks.register_page(ui_extra_networks_textual_inversion.ExtraNetworksPageTextualInversion())
+    ui_extra_networks.register_page(ui_extra_networks_hypernets.ExtraNetworksPageHypernetworks())
+
+    extra_networks.initialize()
+    extra_networks.register_extra_network(extra_networks_hypernet.ExtraNetworkHypernet())
+
     if cmd_opts.tls_keyfile is not None and cmd_opts.tls_keyfile is not None:
 
         try:
@@ -209,6 +218,15 @@ def webui():
 
         modules.sd_models.list_models()
 
+        shared.reload_hypernetworks()
+
+        ui_extra_networks.intialize()
+        ui_extra_networks.register_page(ui_extra_networks_textual_inversion.ExtraNetworksPageTextualInversion())
+        ui_extra_networks.register_page(ui_extra_networks_hypernets.ExtraNetworksPageHypernetworks())
+
+        extra_networks.initialize()
+        extra_networks.register_extra_network(extra_networks_hypernet.ExtraNetworkHypernet())
+
 
 if __name__ == "__main__":
     if cmd_opts.nowebui:
-- 
cgit v1.2.3


From 6d805b669e86233432f56ee1892d062103abe501 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 21 Jan 2023 09:14:27 +0300
Subject: make CLIP interrogator download original text files if the directory
 does not exist remove random artist built-in extension (to re-added as a
 normal extension on demand) remove artists.csv (but what does it
 mean????????????????????) make interrogate buttons show Loading... when you
 click them

---
 README.md                                          |    1 -
 artists.csv                                        | 3041 --------------------
 .../roll-artist/scripts/roll-artist.py             |   50 -
 javascript/hints.js                                |    1 -
 modules/api/api.py                                 |    8 -
 modules/artists.py                                 |   25 -
 modules/interrogate.py                             |   55 +-
 modules/shared.py                                  |    5 -
 modules/ui.py                                      |   11 +-
 9 files changed, 46 insertions(+), 3151 deletions(-)
 delete mode 100644 artists.csv
 delete mode 100644 extensions-builtin/roll-artist/scripts/roll-artist.py
 delete mode 100644 modules/artists.py

(limited to 'modules/ui.py')

diff --git a/README.md b/README.md
index d783fdf0..1ac794e8 100644
--- a/README.md
+++ b/README.md
@@ -49,7 +49,6 @@ A browser interface based on Gradio library for Stable Diffusion.
 - Running arbitrary python code from UI (must run with --allow-code to enable)
 - Mouseover hints for most UI elements
 - Possible to change defaults/mix/max/step values for UI elements via text config
-- Random artist button
 - Tiling support, a checkbox to create images that can be tiled like textures
 - Progress bar and live image generation preview
 - Negative prompt, an extra text field that allows you to list what you don't want to see in generated image
diff --git a/artists.csv b/artists.csv
deleted file mode 100644
index 1a61ed88..00000000
--- a/artists.csv
+++ /dev/null
@@ -1,3041 +0,0 @@
-artist,score,category
-Peter Max,0.99715996,weird
-Roy Lichtenstein,0.98272276,cartoon
-Romero Britto,0.9498342,scribbles
-Keith Haring,0.9431302,weird
-Hiroshige,0.93995106,ukioe
-Joan Miró,0.9169429,scribbles
-Jean-Michel Basquiat,0.90080947,scribbles
-Katsushika Hokusai,0.8887236,ukioe
-Paul Klee,0.8868682,scribbles
-Marc Chagall,0.8868168,scribbles
-Karl Schmidt-Rottluff,0.88444495,scribbles
-Howard Hodgkin,0.8808578,scribbles
-Jean Metzinger,0.88056004,scribbles
-Alma Thomas,0.87658304,weird
-Rufino Tamayo,0.8749848,scribbles
-Utagawa Hiroshige,0.8728796,ukioe
-Chagall,0.8718535,scribbles
-Harumi Hironaka,0.86914605,scribbles
-Hans Hofmann,0.8686159,scribbles
-Kawanabe Kyōsai,0.86612236,ukioe
-Andy Warhol,0.8654825,scribbles
-Barbara Takenaga,0.86223894,scribbles
-Tatsuro Kiuchi,0.8597267,cartoon
-Vincent Van Gogh,0.85538065,scribbles
-Wassily Kandinsky,0.85490596,scribbles
-Georges Seurat,0.8534801,scribbles
-Karel Appel,0.8529153,scribbles
-Sonia Delaunay,0.8506156,scribbles
-Hokusai,0.85046995,ukioe
-Eduardo Kobra,0.85036755,weird
-Fra Angelico,0.84984255,fineart
-Milton Avery,0.849746,scribbles
-David Hockney,0.8496144,scribbles
-Hiroshi Nagai,0.847129,cartoon
-Aristarkh Lentulov,0.846537,scribbles
-Lyonel Feininger,0.84573764,scribbles
-Mary Blair,0.845709,scribbles
-Ellsworth Kelly,0.8455428,scribbles
-Jun Kaneko,0.8448367,scribbles
-Roz Chast,0.8432013,weird
-Ida Rentoul Outhwaite,0.84275174,scribbles
-Robert Motherwell,0.8409468,scribbles
-Garry Winogrand,0.83994275,black-white
-Andrei Rublev,0.83950496,fineart
-Alexander Calder,0.83832693,scribbles
-Tomokazu Matsuyama,0.8376121,scribbles
-August Macke,0.8362022,scribbles
-Kazimir Malevich,0.8356527,scribbles
-Richard Scarry,0.83554685,scribbles
-Victor Vasarely,0.8335438,scribbles
-Kitagawa Utamaro,0.83333457,ukioe
-Matt Bors,0.83252287,scribbles
-Emil Nolde,0.8323225,scribbles
-Patrick Caulfield,0.8322225,scribbles
-Charles Blackman,0.83200824,scribbles
-Peter Doig,0.83111644,scribbles
-Alexej von Jawlensky,0.8308932,scribbles
-Rumiko Takahashi,0.8301817,anime
-Eileen Agar,0.82945526,scribbles
-Ernst Ludwig Kirchner,0.82756275,scribbles
-Nicolas Delort,0.8261329,scribbles
-Marsden Hartley,0.8250993,scribbles
-Keith Negley,0.8212553,scribbles
-Jamini Roy,0.8212199,scribbles
-Quentin Blake,0.82115215,scribbles
-Andy Kehoe,0.82063186,cartoon
-George barbier,0.82046914,fineart
-Frans Masereel,0.81997275,scribbles
-Umberto Boccioni,0.81921184,scribbles
-Conrad Roset,0.8190752,cartoon
-Paul Ranson,0.81903255,scribbles
-Yayoi Kusama,0.81886625,weird
-Tomi Ungerer,0.81848705,scribbles
-Saul Steinberg,0.81778854,scribbles
-Jon Klassen,0.81773067,scribbles
-W.W. Denslow,0.81708044,fineart
-Helen Frankenthaler,0.81704986,scribbles
-Jean Jullien,0.816437,scribbles
-Brett Whiteley,0.81601924,scribbles
-Giotto Di Bondone,0.81427747,fineart
-Takashi Murakami,0.81338763,weird
-Howard Finster,0.81333554,scribbles
-Eduardo Paolozzi,0.81312317,scribbles
-Charles Rennie Mackintosh,0.81297064,scribbles
-Brandon Mably,0.8128239,weird
-Rebecca Louise Law,0.81214285,weird
-Victo Ngai,0.81195843,cartoon
-Hanabusa Itchō II,0.81187993,ukioe
-Edmund Dulac,0.81104875,scribbles
-Ben Shahn,0.8104582,scribbles
-Howard Arkley,0.8103746,scribbles
-Wilfredo Lam,0.8096211,scribbles
-Michael Deforge,0.8095954,scribbles
-John Hoyland,0.8094592,fineart
-Francesco Clemente,0.8090387,scribbles
-Leonetto Cappiello,0.8087691,scribbles
-Norman Ackroyd,0.80788493,scribbles
-Bhupen Khakhar,0.8077607,scribbles
-Jeremiah Ketner,0.8075384,cartoon
-Chris Ofili,0.8073793,scribbles
-Banksy,0.80695426,scribbles
-Tom Whalen,0.805867,scribbles
-Ernst Wilhelm Nay,0.805295,scribbles
-Henri Rousseau,0.8049866,scribbles
-Kunisada,0.80493814,ukioe
-Naoko Takeuchi,0.80482674,anime
-Kaethe Butcher,0.80406916,scribbles
-Hasui Kawase,0.8040483,ukioe
-Alvin Langdon Coburn,0.8035004,black-white
-Stanley Donwood,0.8033054,scribbles
-Agnes Martin,0.8028028,scribbles
-Osamu Tezuka,0.8005524,cartoon
-Frank Stella,0.80049455,scribbles
-Dale Chihuly,0.79982775,digipa-high-impact
-Evgeni Gordiets,0.79967916,scribbles
-Janek Sedlar,0.7993992,fineart
-Alasdair Gray,0.7992301,scribbles
-Yasuo Kuniyoshi,0.79870003,ukioe
-Edward Gorey,0.7984938,scribbles
-Johannes Itten,0.798481,scribbles
-Cuno Amiet,0.7979497,scribbles
-M.C. Escher,0.7976657,scribbles
-Albert Irvin,0.79688835,scribbles
-Jack Gaughan,0.79443675,scribbles
-Ravi Zupa,0.7939542,scribbles
-Kay Nielsen,0.79385525,scribbles
-Agnolo Gaddi,0.79369193,fineart
-Alessandro Gottardo,0.79321593,scribbles
-Paul Laffoley,0.79196846,scribbles
-Giovanni Battista Piranesi,0.79111177,fineart
-Adrian Tomine,0.79109013,scribbles
-Adolph Gottlieb,0.79061794,scribbles
-Milton Caniff,0.7905358,cartoon
-Philip Guston,0.78994095,scribbles
-Debbie Criswell,0.7895031,cartoon
-Alice Pasquini,0.78949904,cartoon
-Johannes Vermeer,0.78931487,fineart
-Lisa Frank,0.7892591,cartoon
-Patrick Heron,0.78889126,scribbles
-Mikhail Nesterov,0.78814346,fineart
-Cézanne,0.7879481,scribbles
-Tristan Eaton,0.787513,scribbles
-Jillian Tamaki,0.7868066,scribbles
-Takato Yamamoto,0.78460765,ukioe
-Martiros Saryan,0.7844924,scribbles
-Emil Orlik,0.7842625,scribbles
-Armand Guillaumin,0.7840431,scribbles
-Jane Newland,0.7837676,scribbles
-Paul Cézanne,0.78368753,scribbles
-Tove Jansson,0.78356475,scribbles
-Guido Crepax,0.7835321,cartoon
-OSGEMEOS,0.7829088,weird
-Albert Watson,0.48901254,digipa-med-impact
-Emory Douglas,0.78179604,scribbles
-Chris Van Allsburg,0.66413003,fineart
-Ohara Koson,0.78132576,ukioe
-Nicolas de Stael,0.7802779,scribbles
-Aubrey Beardsley,0.77970016,scribbles
-Hishikawa Moronobu,0.7794119,ukioe
-Alfred Wallis,0.77926695,scribbles
-Friedensreich Hundertwasser,0.7791805,scribbles
-Eyvind Earle,0.7788089,scribbles
-Giotto,0.7785216,fineart
-Simone Martini,0.77843,fineart
-Ivan Bilibin,0.77720606,fineart
-Karl Blossfeldt,0.77652574,black-white
-Duy Huynh,0.77634746,scribbles
-Giovanni da Udina,0.7763063,fineart
-Henri-Edmond Cross,0.7762994,fineart
-Barry McGee,0.77618384,scribbles
-William Kentridge,0.77615225,scribbles
-Alexander Archipenko,0.7759824,scribbles
-Jaume Plensa,0.7756799,weird
-Bill Jacklin,0.77504414,fineart
-Alberto Vargas,0.7747376,cartoon
-Jean Dubuffet,0.7744374,scribbles
-Eugène Grasset,0.7741958,fineart
-Arthur Rackham,0.77418125,fineart
-Yves Tanguy,0.77380997,scribbles
-Elsa Beskow,0.7736908,fineart
-Georgia O’Keeffe,0.77368987,scribbles
-Georgia O'Keeffe,0.77368987,scribbles
-Henri Cartier-Bresson,0.7735415,black-white
-Andrea del Verrocchio,0.77307427,fineart
-Mark Rothko,0.77294236,scribbles
-Bruce Gilden,0.7256681,black-white
-Gino Severini,0.77247965,scribbles
-Delphin Enjolras,0.5594248,fineart
-Alena Aenami,0.77210015,cartoon
-Ed Freeman,0.42526615,digipa-low-impact
-Apollonia Saintclair,0.7718383,anime
-László Moholy-Nagy,0.771497,scribbles
-Louis Glackens,0.7713224,fineart
-Fang Lijun,0.77097225,fineart
-Alfred Kubin,0.74409986,fineart
-David Wojnarowicz,0.7705802,scribbles
-Tara McPherson,0.77023256,scribbles
-Gustav Doré,0.7367536,fineart
-Patricia Polacco,0.7696109,scribbles
-Norman Bluhm,0.7692634,fineart
-Elizabeth Gadd,0.7691194,digipa-high-impact
-Gabriele Münter,0.7690926,scribbles
-David Inshaw,0.76905304,scribbles
-Maurice Sendak,0.7690118,cartoon
-Harry Clarke,0.7688428,cartoon
-Howardena Pindell,0.7686921,n
-Jamie Hewlett,0.7680373,scribbles
-Steve Ditko,0.76725733,scribbles
-Annie Soudain,0.7671485,scribbles
-Albert Gleizes,0.76658314,scribbles
-Henry Fuseli,0.69147265,fineart
-Alain Laboile,0.67634284,c
-Albrecht Altdorfer,0.7663378,fineart
-Jack Butler Yeats,0.7661406,fineart
-Yue Minjun,0.76583517,scribbles
-Art Spiegelman,0.7656343,scribbles
-Grete Stern,0.7656276,fineart
-Mordecai Ardon,0.7648692,scribbles
-Joel Sternfeld,0.76456416,digipa-high-impact
-Milton Glaser,0.7641823,scribbles
-Eishōsai Chōki,0.7639659,scribbles
-Domenico Ghirlandaio,0.76372653,fineart
-Alex Timmermans,0.64443207,digipa-high-impact
-Andreas Vesalius,0.763446,fineart
-Bruce McLean,0.76335883,scribbles
-Jacob Lawrence,0.76330304,scribbles
-Alex Katz,0.76317835,scribbles
-Henri de Toulouse-Lautrec,0.76268333,scribbles
-Franz Sedlacek,0.762062,scribbles
-Paul Lehr,0.70854837,cartoon
-Nicholas Roerich,0.76117516,scribbles
-Henri Matisse,0.76110923,scribbles
-Colin McCahon,0.76086944,scribbles
-Max Dupain,0.6661642,black-white
-Stephen Gammell,0.74001735,weird
-Alberto Giacometti,0.7596302,scribbles
-Goyō Hashiguchi,0.7595048,ukioe
-Gustave Doré,0.7018832,fineart
-Butcher Billy,0.7593378,cartoon
-Pieter de Hooch,0.75916564,fineart
-Gaetano Pesce,0.75906265,scribbles
-Winsor McCay,0.7589382,scribbles
-Claude Cahun,0.7588153,weird
-Roger Ballen,0.64683115,black-white
-Ellen Gallagher,0.758621,scribbles
-Anton Corbijn,0.5550669,digipa-high-impact
-Margaret Macdonald Mackintosh,0.75781375,fineart
-Franz Kline,0.7576461,scribbles
-Cimabue,0.75720495,fineart
-André Kertész,0.7319392,black-white
-Hans Hartung,0.75718236,scribbles
-J. J. Grandville,0.7321584,fineart
-David Octavius Hill,0.6333561,digipa-high-impact
-teamLab,0.7566472,digipa-high-impact
-Paul Gauguin,0.75635266,scribbles
-Etel Adnan,0.75631833,scribbles
-Barbara Kruger,0.7562784,scribbles
-Franz Marc,0.75538874,scribbles
-Saul Bass,0.75496316,scribbles
-El Lissitzky,0.7549487,scribbles
-Thomas Moran,0.6507399,fineart
-Claude Monet,0.7541377,fineart
-David Young Cameron,0.7541016,scribbles
-W. Heath Robinson,0.75374347,cartoon
-Yves Klein,0.7536262,fineart
-Albert Pinkham Ryder,0.7338848,fineart
-Elizabeth Shippen Green,0.7533686,fineart
-Robert Stivers,0.5516287,fineart
-Emily Kame Kngwarreye,0.7532016,weird
-Charline von Heyl,0.753142,scribbles
-Frida Kahlo,0.75303876,scribbles
-Amy Sillman,0.752921,scribbles
-Emperor Huizong of Song,0.7525214,ukioe
-Edward Burne-Jones,0.75220466,fineart
-Brett Weston,0.6891357,black-white
-Charles E. Burchfield,0.75174403,scribbles
-Hishida Shunsō,0.751617,fareast
-Elaine de Kooning,0.7514996,scribbles
-Gary Panter,0.7514598,scribbles
-Frederick Hammersley,0.7514268,scribbles
-Gustave Dore,0.6735896,fineart
-Ephraim Moses Lilien,0.7510494,fineart
-Hannah Hoch,0.7509496,scribbles
-Shepard Fairey,0.7508583,scribbles
-Richard Burlet,0.7506659,scribbles
-Bill Brandt,0.6833408,black-white
-Herbert List,0.68455493,black-white
-Joseph Cornell,0.75023884,nudity
-Nathan Wirth,0.6436741,black-white
-John Kenn Mortensen,0.74758303,anime
-Andre De Dienes,0.5683014,digipa-high-impact
-Albert Robida,0.7485741,cartoon
-Shintaro Kago,0.7484431,anime
-Sidney Nolan,0.74809414,scribbles
-Patrice Murciano,0.61973965,fineart
-Brian Stelfreeze,0.7478351,scribbles
-Francisco De Goya,0.6954584,fineart
-William Morris,0.7478111,fineart
-Honoré Daumier,0.74767774,scribbles
-Hubert Robert,0.6863421,fineart
-Marianne von Werefkin,0.7475825,fineart
-Edvard Munch,0.74719715,scribbles
-Victor Brauner,0.74719006,scribbles
-George Inness,0.7470588,fineart
-Naoki Urasawa,0.7469665,anime
-Kilian Eng,0.7468486,scribbles
-Bordalo II,0.7467364,digipa-high-impact
-Katsuhiro Otomo,0.746364,anime
-Maximilien Luce,0.74609685,fineart
-Amy Earles,0.74603415,fineart
-Jeanloup Sieff,0.7196009,black-white
-William Zorach,0.74574494,scribbles
-Pascale Campion,0.74516207,fineart
-Dorothy Lathrop,0.74418795,fineart
-Sofonisba Anguissola,0.74418664,fineart
-Natalia Goncharova,0.74414873,scribbles
-August Sander,0.6644566,black-white
-Jasper Johns,0.74395454,scribbles
-Arthur Dove,0.74383533,scribbles
-Darwyn Cooke,0.7435789,scribbles
-Leonardo Da Vinci,0.6825216,fineart
-Fra Filippo Lippi,0.7433891,fineart
-Pierre-Auguste Renoir,0.742464,fineart
-Jeff Lemire,0.7422893,scribbles
-Al Williamson,0.742113,cartoon
-Childe Hassam,0.7418015,fineart
-Francisco Goya,0.69522625,fineart
-Alphonse Mucha,0.74171394,special
-Cleon Peterson,0.74163914,scribbles
-J.M.W. Turner,0.65582645,fineart
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-Sarah Lucas,0.4420507,digipa-low-impact
-Sydney Edmunds,0.44198513,digipa-low-impact
-Amos Ferguson,0.4418735,digipa-low-impact
-Alton Tobey,0.4416385,digipa-low-impact
-Clifford Ross,0.44139367,digipa-low-impact
-Henric Trenk,0.4412782,digipa-low-impact
-Claire Hummel,0.44119984,digipa-low-impact
-Norman Foster,0.4411899,digipa-low-impact
-Carmen Saldana,0.44076762,digipa-low-impact
-Michael Whelan,0.4372847,digipa-low-impact
-Carlos Berlanga,0.440354,digipa-low-impact
-Gilles Beloeil,0.43997732,digipa-low-impact
-Ashley Wood,0.4398396,digipa-low-impact
-David Allan,0.43969798,digipa-low-impact
-Mark Lovett,0.43922082,digipa-low-impact
-Jed Henry,0.43882954,digipa-low-impact
-Adam Bruce Thomson,0.43847767,digipa-low-impact
-Horst Antes,0.4384303,digipa-low-impact
-Fritz Glarner,0.43787453,digipa-low-impact
-Harold McCauley,0.43760818,digipa-low-impact
-Estuardo Maldonado,0.437594,digipa-low-impact
-Dai Jin,0.4375449,fareast
-Fabien Charuau,0.43688047,digipa-low-impact
-Chica Macnab,0.4365166,digipa-low-impact
-Jim Burns,0.3975072,digipa-low-impact
-Santiago Calatrava,0.43651623,digipa-low-impact
-Robert Maguire,0.40926617,digipa-low-impact
-Cliff Childs,0.43611953,digipa-low-impact
-Charles Martin,0.43582463,fareast
-Elbridge Ayer Burbank,0.43572164,digipa-low-impact
-Anita Kunz,0.4356005,digipa-low-impact
-Colin Geller,0.43559563,digipa-low-impact
-Allen Tupper True,0.43556124,digipa-low-impact
-Jef Wu,0.43555313,digipa-low-impact
-Jon McCoy,0.4147122,digipa-low-impact
-Cedric Seaut,0.43521535,digipa-low-impact
-Emily Shanks,0.43519047,digipa-low-impact
-Andrew Whem,0.43512022,digipa-low-impact
-Ibrahim Kodra,0.43471518,digipa-low-impact
-Harrington Mann,0.4345901,digipa-low-impact
-Jerry Siegel,0.43458986,digipa-low-impact
-Howard Kanovitz,0.4345178,digipa-low-impact
-Cicely Hey,0.43449926,digipa-low-impact
-Ben Thompson,0.43436068,digipa-low-impact
-Joe Bowler,0.43413073,digipa-low-impact
-Lori Earley,0.43389612,digipa-low-impact
-Arent Arentsz,0.43373522,digipa-low-impact
-David Bailly,0.43371305,digipa-low-impact
-Hans Arnold,0.4335214,digipa-low-impact
-Constance Copeman,0.4334836,digipa-low-impact
-Brent Heighton,0.4333118,fineart
-Eric Taylor,0.43312082,digipa-low-impact
-Aleksander Gine,0.4326849,digipa-low-impact
-Alexander Johnston,0.4326589,digipa-low-impact
-David Park,0.43235332,digipa-low-impact
-Balázs Diószegi,0.432244,digipa-low-impact
-Ed Binkley,0.43222216,digipa-low-impact
-Eric Dinyer,0.4321258,digipa-low-impact
-Susan Luo,0.43198025,fareast
-Cedric Seaut (Keos Masons),0.4317356,digipa-low-impact
-Lorena Alvarez Gómez,0.431683,digipa-low-impact
-Fred Ludekens,0.431662,digipa-low-impact
-David Begbie,0.4316218,digipa-low-impact
-Ai Xuan,0.43150818,fareast
-Felix-Kelly,0.43132153,digipa-low-impact
-Antonín Chittussi,0.431248,digipa-low-impact
-Ammi Phillips,0.43095884,digipa-low-impact
-Elke Vogelsang,0.43092483,digipa-low-impact
-Fathi Hassan,0.43090487,digipa-low-impact
-Angela Sung,0.391746,fareast
-Clément Serveau,0.43050706,digipa-low-impact
-Dong Yuan,0.4303865,fareast
-Hew Lorimer,0.43035403,digipa-low-impact
-David Finch,0.29487437,digipa-low-impact
-Bill Durgin,0.4300932,digipa-low-impact
-Alexander Robertson,0.4300743,digipa-low-impact
diff --git a/extensions-builtin/roll-artist/scripts/roll-artist.py b/extensions-builtin/roll-artist/scripts/roll-artist.py
deleted file mode 100644
index c3bc1fd0..00000000
--- a/extensions-builtin/roll-artist/scripts/roll-artist.py
+++ /dev/null
@@ -1,50 +0,0 @@
-import random
-
-from modules import script_callbacks, shared
-import gradio as gr
-
-art_symbol = '\U0001f3a8'  # 🎨
-global_prompt = None
-related_ids = {"txt2img_prompt", "txt2img_clear_prompt", "img2img_prompt", "img2img_clear_prompt" }
-
-
-def roll_artist(prompt):
-    allowed_cats = set([x for x in shared.artist_db.categories() if len(shared.opts.random_artist_categories)==0 or x in shared.opts.random_artist_categories])
-    artist = random.choice([x for x in shared.artist_db.artists if x.category in allowed_cats])
-
-    return prompt + ", " + artist.name if prompt != '' else artist.name
-
-
-def add_roll_button(prompt):
-    roll = gr.Button(value=art_symbol, elem_id="roll", visible=len(shared.artist_db.artists) > 0)
-
-    roll.click(
-        fn=roll_artist,
-        _js="update_txt2img_tokens",
-        inputs=[
-            prompt,
-        ],
-        outputs=[
-            prompt,
-        ]
-    )
-
-
-def after_component(component, **kwargs):
-    global global_prompt
-
-    elem_id = kwargs.get('elem_id', None)
-    if elem_id not in related_ids:
-        return
-
-    if elem_id == "txt2img_prompt":
-        global_prompt = component
-    elif elem_id == "txt2img_clear_prompt":
-        add_roll_button(global_prompt)
-    elif elem_id == "img2img_prompt":
-        global_prompt = component
-    elif elem_id == "img2img_clear_prompt":
-        add_roll_button(global_prompt)
-
-
-script_callbacks.on_after_component(after_component)
diff --git a/javascript/hints.js b/javascript/hints.js
index f4079f96..ef410fba 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -14,7 +14,6 @@ titles = {
     "Seed": "A value that determines the output of random number generator - if you create an image with same parameters and seed as another image, you'll get the same result",
     "\u{1f3b2}\ufe0f": "Set seed to -1, which will cause a new random number to be used every time",
     "\u267b\ufe0f": "Reuse seed from last generation, mostly useful if it was randomed",
-    "\u{1f3a8}": "Add a random artist to the prompt.",
     "\u2199\ufe0f": "Read generation parameters from prompt or last generation if prompt is empty into user interface.",
     "\u{1f4c2}": "Open images output directory",
     "\u{1f4be}": "Save style",
diff --git a/modules/api/api.py b/modules/api/api.py
index 2c371e6e..f2e9e884 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -126,8 +126,6 @@ class Api:
         self.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=List[FaceRestorerItem])
         self.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=List[RealesrganItem])
         self.add_api_route("/sdapi/v1/prompt-styles", self.get_prompt_styles, methods=["GET"], response_model=List[PromptStyleItem])
-        self.add_api_route("/sdapi/v1/artist-categories", self.get_artists_categories, methods=["GET"], response_model=List[str])
-        self.add_api_route("/sdapi/v1/artists", self.get_artists, methods=["GET"], response_model=List[ArtistItem])
         self.add_api_route("/sdapi/v1/embeddings", self.get_embeddings, methods=["GET"], response_model=EmbeddingsResponse)
         self.add_api_route("/sdapi/v1/refresh-checkpoints", self.refresh_checkpoints, methods=["POST"])
         self.add_api_route("/sdapi/v1/create/embedding", self.create_embedding, methods=["POST"], response_model=CreateResponse)
@@ -390,12 +388,6 @@ class Api:
 
         return styleList
 
-    def get_artists_categories(self):
-        return shared.artist_db.cats
-
-    def get_artists(self):
-        return [{"name":x[0], "score":x[1], "category":x[2]} for x in shared.artist_db.artists]
-
     def get_embeddings(self):
         db = sd_hijack.model_hijack.embedding_db
 
diff --git a/modules/artists.py b/modules/artists.py
deleted file mode 100644
index 3612758b..00000000
--- a/modules/artists.py
+++ /dev/null
@@ -1,25 +0,0 @@
-import os.path
-import csv
-from collections import namedtuple
-
-Artist = namedtuple("Artist", ['name', 'weight', 'category'])
-
-
-class ArtistsDatabase:
-    def __init__(self, filename):
-        self.cats = set()
-        self.artists = []
-
-        if not os.path.exists(filename):
-            return
-
-        with open(filename, "r", newline='', encoding="utf8") as file:
-            reader = csv.DictReader(file)
-
-            for row in reader:
-                artist = Artist(row["artist"], float(row["score"]), row["category"])
-                self.artists.append(artist)
-                self.cats.add(artist.category)
-
-    def categories(self):
-        return sorted(self.cats)
diff --git a/modules/interrogate.py b/modules/interrogate.py
index 738d8ff7..19938cbb 100644
--- a/modules/interrogate.py
+++ b/modules/interrogate.py
@@ -5,12 +5,13 @@ from collections import namedtuple
 import re
 
 import torch
+import torch.hub
 
 from torchvision import transforms
 from torchvision.transforms.functional import InterpolationMode
 
 import modules.shared as shared
-from modules import devices, paths, lowvram, modelloader
+from modules import devices, paths, lowvram, modelloader, errors
 
 blip_image_eval_size = 384
 clip_model_name = 'ViT-L/14'
@@ -20,27 +21,59 @@ Category = namedtuple("Category", ["name", "topn", "items"])
 re_topn = re.compile(r"\.top(\d+)\.")
 
 
+def download_default_clip_interrogate_categories(content_dir):
+    print("Downloading CLIP categories...")
+
+    tmpdir = content_dir + "_tmp"
+    try:
+        os.makedirs(tmpdir)
+
+        torch.hub.download_url_to_file("https://raw.githubusercontent.com/pharmapsychotic/clip-interrogator/main/clip_interrogator/data/artists.txt", os.path.join(tmpdir, "artists.txt"))
+        torch.hub.download_url_to_file("https://raw.githubusercontent.com/pharmapsychotic/clip-interrogator/main/clip_interrogator/data/flavors.txt", os.path.join(tmpdir, "flavors.top3.txt"))
+        torch.hub.download_url_to_file("https://raw.githubusercontent.com/pharmapsychotic/clip-interrogator/main/clip_interrogator/data/mediums.txt", os.path.join(tmpdir, "mediums.txt"))
+        torch.hub.download_url_to_file("https://raw.githubusercontent.com/pharmapsychotic/clip-interrogator/main/clip_interrogator/data/movements.txt", os.path.join(tmpdir, "movements.txt"))
+
+        os.rename(tmpdir, content_dir)
+
+    except Exception as e:
+        errors.display(e, "downloading default CLIP interrogate categories")
+    finally:
+        if os.path.exists(tmpdir):
+            os.remove(tmpdir)
+
+
 class InterrogateModels:
     blip_model = None
     clip_model = None
     clip_preprocess = None
-    categories = None
     dtype = None
     running_on_cpu = None
 
     def __init__(self, content_dir):
-        self.categories = []
+        self.loaded_categories = None
+        self.content_dir = content_dir
         self.running_on_cpu = devices.device_interrogate == torch.device("cpu")
 
-        if os.path.exists(content_dir):
-            for filename in os.listdir(content_dir):
+    def categories(self):
+        if self.loaded_categories is not None:
+            return self.loaded_categories
+
+        self.loaded_categories = []
+
+        if not os.path.exists(self.content_dir):
+            download_default_clip_interrogate_categories(self.content_dir)
+
+        if os.path.exists(self.content_dir):
+            for filename in os.listdir(self.content_dir):
                 m = re_topn.search(filename)
                 topn = 1 if m is None else int(m.group(1))
 
-                with open(os.path.join(content_dir, filename), "r", encoding="utf8") as file:
+                with open(os.path.join(self.content_dir, filename), "r", encoding="utf8") as file:
                     lines = [x.strip() for x in file.readlines()]
 
-                self.categories.append(Category(name=filename, topn=topn, items=lines))
+                self.loaded_categories.append(Category(name=filename, topn=topn, items=lines))
+
+        return self.loaded_categories
 
     def load_blip_model(self):
         import models.blip
@@ -139,7 +172,6 @@ class InterrogateModels:
         shared.state.begin()
         shared.state.job = 'interrogate'
         try:
-
             if shared.cmd_opts.lowvram or shared.cmd_opts.medvram:
                 lowvram.send_everything_to_cpu()
                 devices.torch_gc()
@@ -159,12 +191,7 @@ class InterrogateModels:
 
                 image_features /= image_features.norm(dim=-1, keepdim=True)
 
-                if shared.opts.interrogate_use_builtin_artists:
-                    artist = self.rank(image_features, ["by " + artist.name for artist in shared.artist_db.artists])[0]
-
-                    res += ", " + artist[0]
-
-                for name, topn, items in self.categories:
+                for name, topn, items in self.categories():
                     matches = self.rank(image_features, items, top_count=topn)
                     for match, score in matches:
                         if shared.opts.interrogate_return_ranks:
diff --git a/modules/shared.py b/modules/shared.py
index c0e11f18..72fb1934 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -9,7 +9,6 @@ from PIL import Image
 import gradio as gr
 import tqdm
 
-import modules.artists
 import modules.interrogate
 import modules.memmon
 import modules.styles
@@ -254,8 +253,6 @@ class State:
 state = State()
 state.server_start = time.time()
 
-artist_db = modules.artists.ArtistsDatabase(os.path.join(script_path, 'artists.csv'))
-
 styles_filename = cmd_opts.styles_file
 prompt_styles = modules.styles.StyleDatabase(styles_filename)
 
@@ -408,7 +405,6 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"),
     "comma_padding_backtrack": OptionInfo(20, "Increase coherency by padding from the last comma within n tokens when using more than 75 tokens", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1 }),
     'CLIP_stop_at_last_layers': OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}),
-    "random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}),
 }))
 
 options_templates.update(options_section(('compatibility', "Compatibility"), {
@@ -419,7 +415,6 @@ options_templates.update(options_section(('compatibility', "Compatibility"), {
 
 options_templates.update(options_section(('interrogate', "Interrogate Options"), {
     "interrogate_keep_models_in_memory": OptionInfo(False, "Interrogate: keep models in VRAM"),
-    "interrogate_use_builtin_artists": OptionInfo(True, "Interrogate: use artists from artists.csv"),
     "interrogate_return_ranks": OptionInfo(False, "Interrogate: include ranks of model tags matches in results (Has no effect on caption-based interrogators)."),
     "interrogate_clip_num_beams": OptionInfo(1, "Interrogate: num_beams for BLIP", gr.Slider, {"minimum": 1, "maximum": 16, "step": 1}),
     "interrogate_clip_min_length": OptionInfo(24, "Interrogate: minimum description length (excluding artists, etc..)", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}),
diff --git a/modules/ui.py b/modules/ui.py
index d23b2b8e..164e0e93 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -228,17 +228,17 @@ def process_interrogate(interrogation_function, mode, ii_input_dir, ii_output_di
             left, _ = os.path.splitext(filename)
             print(interrogation_function(img), file=open(os.path.join(ii_output_dir, left + ".txt"), 'a'))
 
-        return [gr_show(True), None]
+        return [gr.update(), None]
 
 
 def interrogate(image):
     prompt = shared.interrogator.interrogate(image.convert("RGB"))
-    return gr_show(True) if prompt is None else prompt
+    return gr.update() if prompt is None else prompt
 
 
 def interrogate_deepbooru(image):
     prompt = deepbooru.model.tag(image)
-    return gr_show(True) if prompt is None else prompt
+    return gr.update() if prompt is None else prompt
 
 
 def create_seed_inputs(target_interface):
@@ -1039,19 +1039,18 @@ def create_ui():
                     init_img_inpaint,
                 ],
                 outputs=[img2img_prompt, dummy_component],
-                show_progress=False,
             )
 
             img2img_prompt.submit(**img2img_args)
             submit.click(**img2img_args)
 
             img2img_interrogate.click(
-                fn=lambda *args : process_interrogate(interrogate, *args),
+                fn=lambda *args: process_interrogate(interrogate, *args),
                 **interrogate_args,
             )
 
             img2img_deepbooru.click(
-                fn=lambda *args : process_interrogate(interrogate_deepbooru, *args),
+                fn=lambda *args: process_interrogate(interrogate_deepbooru, *args),
                 **interrogate_args,
             )
 
-- 
cgit v1.2.3


From 184e23eb89c198b42f351a4d5ff862ee64917619 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 21 Jan 2023 09:48:38 +0300
Subject: relocate tool buttons next to generate button prevent extra network
 tabs from putting images into wrong prompts prevent settings leaking into
 prompt

---
 html/extra-networks-card.html |  2 +-
 javascript/extraNetworks.js   | 33 +++++++++++++--------------------
 javascript/ui.js              |  4 ++--
 modules/ui.py                 | 43 +++++++++++++++++++++----------------------
 style.css                     | 18 +++++++-----------
 5 files changed, 44 insertions(+), 56 deletions(-)

(limited to 'modules/ui.py')

diff --git a/html/extra-networks-card.html b/html/extra-networks-card.html
index 7314b063..1bdf1d27 100644
--- a/html/extra-networks-card.html
+++ b/html/extra-networks-card.html
@@ -1,4 +1,4 @@
-<div class='card' {preview_html} onclick='return cardClicked({prompt}, {allow_negative_prompt})'>
+<div class='card' {preview_html} onclick='return cardClicked({tabname}, {prompt}, {allow_negative_prompt})'>
 	<div class='actions'>
 		<div class='additional'>
 			<ul>
diff --git a/javascript/extraNetworks.js b/javascript/extraNetworks.js
index 71e522d1..5e0d9714 100644
--- a/javascript/extraNetworks.js
+++ b/javascript/extraNetworks.js
@@ -6,49 +6,42 @@ function setupExtraNetworksForTab(tabname){
     gradioApp().querySelector('#'+tabname+'_extra_tabs > div').appendChild(gradioApp().getElementById(tabname+'_extra_close'))
 }
 
-var activePromptTextarea = null;
-var activePositivePromptTextarea = null;
+var activePromptTextarea = {};
 
 function setupExtraNetworks(){
     setupExtraNetworksForTab('txt2img')
     setupExtraNetworksForTab('img2img')
 
-    function registerPrompt(id, isNegative){
+    function registerPrompt(tabname, id){
         var textarea = gradioApp().querySelector("#" + id + " > label > textarea");
 
-        if (activePromptTextarea == null){
-            activePromptTextarea = textarea
-        }
-        if (activePositivePromptTextarea == null && ! isNegative){
-            activePositivePromptTextarea = textarea
+        if (! activePromptTextarea[tabname]){
+            activePromptTextarea[tabname] = textarea
         }
 
 		textarea.addEventListener("focus", function(){
-            activePromptTextarea = textarea;
-            if(! isNegative)  activePositivePromptTextarea = textarea;
+            activePromptTextarea[tabname] = textarea;
 		});
     }
 
-    registerPrompt('txt2img_prompt')
-    registerPrompt('txt2img_neg_prompt', true)
-    registerPrompt('img2img_prompt')
-    registerPrompt('img2img_neg_prompt', true)
+    registerPrompt('txt2img', 'txt2img_prompt')
+    registerPrompt('txt2img', 'txt2img_neg_prompt')
+    registerPrompt('img2img', 'img2img_prompt')
+    registerPrompt('img2img', 'img2img_neg_prompt')
 }
 
 onUiLoaded(setupExtraNetworks)
 
-function cardClicked(textToAdd, allowNegativePrompt){
-    textarea = allowNegativePrompt ? activePromptTextarea : activePositivePromptTextarea
+function cardClicked(tabname, textToAdd, allowNegativePrompt){
+    var textarea = allowNegativePrompt ? activePromptTextarea[tabname] : gradioApp().querySelector("#" + tabname + "_prompt > label > textarea")
 
     textarea.value = textarea.value + " " + textToAdd
     updateInput(textarea)
-
-    return false
 }
 
 function saveCardPreview(event, tabname, filename){
-    textarea = gradioApp().querySelector("#" + tabname + '_preview_filename  > label > textarea')
-    button = gradioApp().getElementById(tabname + '_save_preview')
+    var textarea = gradioApp().querySelector("#" + tabname + '_preview_filename  > label > textarea')
+    var button = gradioApp().getElementById(tabname + '_save_preview')
 
     textarea.value = filename
     updateInput(textarea)
diff --git a/javascript/ui.js b/javascript/ui.js
index a7e75439..77256e15 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -203,8 +203,8 @@ onUiUpdate(function(){
 	json_elem = gradioApp().getElementById('settings_json')
 	if(json_elem == null) return;
 
-    textarea = json_elem.querySelector('textarea')
-    jsdata = textarea.value
+    var textarea = json_elem.querySelector('textarea')
+    var jsdata = textarea.value
     opts = JSON.parse(jsdata)
     executeCallbacks(optionsChangedCallbacks);
 
diff --git a/modules/ui.py b/modules/ui.py
index 164e0e93..fbc3efa0 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -349,30 +349,13 @@ def create_toprow(is_img2img):
             with gr.Row():
                 with gr.Column(scale=80):
                     with gr.Row():
-                        prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=2, placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)")
+                        prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=3, placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)")
 
             with gr.Row():
                 with gr.Column(scale=80):
                     with gr.Row():
                         negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2, placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)")
 
-        with gr.Column(scale=1, elem_id="roll_col"):
-            paste = ToolButton(value=paste_symbol, elem_id="paste")
-            clear_prompt_button = ToolButton(value=clear_prompt_symbol, elem_id=f"{id_part}_clear_prompt")
-            extra_networks_button = ToolButton(value=extra_networks_symbol, elem_id=f"{id_part}_extra_networks")
-
-            token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_token_counter")
-            token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button")
-            negative_token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_negative_token_counter")
-            negative_token_button = gr.Button(visible=False, elem_id=f"{id_part}_negative_token_button")
-
-            clear_prompt_button.click(
-                fn=lambda *x: x,
-                _js="confirm_clear_prompt",
-                inputs=[prompt, negative_prompt],
-                outputs=[prompt, negative_prompt],
-            )
-
         button_interrogate = None
         button_deepbooru = None
         if is_img2img:
@@ -380,7 +363,7 @@ def create_toprow(is_img2img):
                 button_interrogate = gr.Button('Interrogate\nCLIP', elem_id="interrogate")
                 button_deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru")
 
-        with gr.Column(scale=1):
+        with gr.Column(scale=1, elem_id=f"{id_part}_actions_column"):
             with gr.Row(elem_id=f"{id_part}_generate_box"):
                 interrupt = gr.Button('Interrupt', elem_id=f"{id_part}_interrupt")
                 skip = gr.Button('Skip', elem_id=f"{id_part}_skip")
@@ -398,13 +381,29 @@ def create_toprow(is_img2img):
                     outputs=[],
                 )
 
+            with gr.Row(elem_id=f"{id_part}_tools"):
+                paste = ToolButton(value=paste_symbol, elem_id="paste")
+                clear_prompt_button = ToolButton(value=clear_prompt_symbol, elem_id=f"{id_part}_clear_prompt")
+                extra_networks_button = ToolButton(value=extra_networks_symbol, elem_id=f"{id_part}_extra_networks")
+                prompt_style_apply = ToolButton(value=apply_style_symbol, elem_id=f"{id_part}_style_apply")
+                save_style = ToolButton(value=save_style_symbol, elem_id=f"{id_part}_style_create")
+
+                token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_token_counter")
+                token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button")
+                negative_token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_negative_token_counter")
+                negative_token_button = gr.Button(visible=False, elem_id=f"{id_part}_negative_token_button")
+
+                clear_prompt_button.click(
+                    fn=lambda *x: x,
+                    _js="confirm_clear_prompt",
+                    inputs=[prompt, negative_prompt],
+                    outputs=[prompt, negative_prompt],
+                )
+
             with gr.Row(elem_id=f"{id_part}_styles_row"):
                 prompt_styles = gr.Dropdown(label="Styles", elem_id=f"{id_part}_styles", choices=[k for k, v in shared.prompt_styles.styles.items()], value=[], multiselect=True)
                 create_refresh_button(prompt_styles, shared.prompt_styles.reload, lambda: {"choices": [k for k, v in shared.prompt_styles.styles.items()]}, f"refresh_{id_part}_styles")
 
-                prompt_style_apply = ToolButton(value=apply_style_symbol, elem_id="style_apply")
-                save_style = ToolButton(value=save_style_symbol, elem_id="style_create")
-
     return prompt, prompt_styles, negative_prompt, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, extra_networks_button, token_counter, token_button, negative_token_counter, negative_token_button
 
 
diff --git a/style.css b/style.css
index 5e8bc2ca..04bf2982 100644
--- a/style.css
+++ b/style.css
@@ -124,15 +124,12 @@
     height: 100%;
 }
 
-#roll_col{
-    min-width: unset !important;
-    flex-grow: 0 !important;
-    padding: 0 1em 0 0;
+#txt2img_actions_column, #img2img_actions_column{
     gap: 0;
 }
 
-#roll_col > button {
-    margin: 0.1em 0;
+#txt2img_tools, #img2img_tools{
+    gap: 0.4em;
 }
 
 #interrogate_col{
@@ -153,7 +150,6 @@
 
 #txt2img_styles_row, #img2img_styles_row{
     gap: 0.25em;
-    margin-top: 0.5em;
 }
 
 #txt2img_styles_row > button, #img2img_styles_row > button{
@@ -164,6 +160,10 @@
     padding: 0;
 }
 
+#txt2img_styles > label > div, #img2img_styles > label > div{
+    min-height: 3.2em;
+}
+
 #txt2img_styles ul, #img2img_styles ul{
     max-height: 35em;
     z-index: 2000;
@@ -770,10 +770,6 @@ footer {
     line-height: 2.4em;
 }
 
-#txt2img_extra_networks, #img2img_extra_networks{
-    margin-top: -1em;
-}
-
 .extra-networks > div > [id *= '_extra_']{
     margin: 0.3em;
 }
-- 
cgit v1.2.3


From f53527f7786575fe60da0223bd63ea3f0a06a754 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 21 Jan 2023 20:07:14 +0300
Subject: make it run on gradio < 3.16.2

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

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index fbc3efa0..b3105901 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1897,7 +1897,7 @@ def create_ui():
 
         if type(x) == gr.Dropdown:
             def check_dropdown(val):
-                if x.multiselect:
+                if getattr(x, 'multiselect', False):
                     return all([value in x.choices for value in val])
                 else:
                     return val in x.choices
-- 
cgit v1.2.3


From f726df8a2fd2620ba245de5702e2afe620f79b91 Mon Sep 17 00:00:00 2001
From: James Tolton <jjtolton@gmail.com>
Date: Sat, 21 Jan 2023 12:59:05 -0500
Subject: Compile and serve js from /statica instead of inline in html

---
 modules/ui.py                     | 35 ++++++++++++++++++++++++++++++-----
 statica/put-static-files-here.txt |  1 +
 webui.py                          |  2 ++
 3 files changed, 33 insertions(+), 5 deletions(-)
 create mode 100644 statica/put-static-files-here.txt

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index fbc3efa0..d19eaf25 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -10,6 +10,7 @@ import sys
 import tempfile
 import time
 import traceback
+from collections import OrderedDict
 from functools import partial, reduce
 import warnings
 
@@ -1918,27 +1919,51 @@ def create_ui():
 
 
 def reload_javascript():
+    javascript_files = OrderedDict()
     with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile:
-        javascript = f'<script>{jsfile.read()}</script>'
+        contents = jsfile.read()
+        javascript_files["script.js"] = [contents]
+        # javascript = f'<script>{contents}</script>'
 
     scripts_list = modules.scripts.list_scripts("javascript", ".js")
 
     for basedir, filename, path in scripts_list:
         with open(path, "r", encoding="utf8") as jsfile:
-            javascript += f"\n<!-- {filename} --><script>{jsfile.read()}</script>"
+            contents = jsfile.read()
+            javascript_files[filename] = [contents]
+            # javascript += f"\n<!-- {filename} --><script>{contents}</script>"
 
     if cmd_opts.theme is not None:
-        javascript += f"\n<script>set_theme('{cmd_opts.theme}');</script>\n"
+        javascript_files["theme.js"] = [f"set_theme('{cmd_opts.theme}');"]
+        # javascript += f"\n<script>set_theme('{cmd_opts.theme}');</script>\n"
 
-    javascript += f"\n<script>{localization.localization_js(shared.opts.localization)}</script>"
+    # javascript += f"\n<script>{localization.localization_js(shared.opts.localization)}</script>"
+    javascript_files["localization.js"] = [f"{localization.localization_js(shared.opts.localization)}"]
+
+    compiled_name = "webui-compiled.js"
+    head = f"""
+    <script src=/statica/{compiled_name}?{int(time.time())} type="text/javascript"></script>
+    """
 
     def template_response(*args, **kwargs):
         res = shared.GradioTemplateResponseOriginal(*args, **kwargs)
         res.body = res.body.replace(
-            b'</head>', f'{javascript}</head>'.encode("utf8"))
+            b'</head>', f'{head}</head>'.encode("utf8"))
         res.init_headers()
         return res
 
+    for k in javascript_files:
+        javascript_files[k] = "\n".join(javascript_files[k])
+
+    # make static_path if not exists
+    statica_path = os.path.join(script_path, 'statica')
+    if not os.path.exists(statica_path):
+        os.mkdir(statica_path)
+
+    javascript_out = "\n\n\n".join([f"// <!-- {k} -->\n\n{v}" for k, v in javascript_files.items()])
+    with open(os.path.join(script_path, "statica", compiled_name), "w", encoding="utf8") as jsfile:
+        jsfile.write(javascript_out)
+
     gradio.routes.templates.TemplateResponse = template_response
 
 
diff --git a/statica/put-static-files-here.txt b/statica/put-static-files-here.txt
new file mode 100644
index 00000000..7cfaaa86
--- /dev/null
+++ b/statica/put-static-files-here.txt
@@ -0,0 +1 @@
+ayo
\ No newline at end of file
diff --git a/webui.py b/webui.py
index d235da74..50dee700 100644
--- a/webui.py
+++ b/webui.py
@@ -8,6 +8,7 @@ import re
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.middleware.gzip import GZipMiddleware
+from starlette.staticfiles import StaticFiles
 
 from modules import import_hook, errors, extra_networks
 from modules import extra_networks_hypernet, ui_extra_networks_hypernets, ui_extra_networks_textual_inversion
@@ -195,6 +196,7 @@ def webui():
         setup_cors(app)
 
         app.add_middleware(GZipMiddleware, minimum_size=1000)
+        app.mount("/statica", StaticFiles(directory=os.path.join(script_path, 'statica')), name="statica")
 
         modules.progress.setup_progress_api(app)
 
-- 
cgit v1.2.3


From 17af0fb95574068a1d5032ae96879dab145e173a Mon Sep 17 00:00:00 2001
From: James Tolton <jjtolton@gmail.com>
Date: Sat, 21 Jan 2023 13:27:05 -0500
Subject: remove commented out lines

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

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index d19eaf25..ef85d43c 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1923,7 +1923,6 @@ def reload_javascript():
     with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile:
         contents = jsfile.read()
         javascript_files["script.js"] = [contents]
-        # javascript = f'<script>{contents}</script>'
 
     scripts_list = modules.scripts.list_scripts("javascript", ".js")
 
@@ -1931,13 +1930,10 @@ def reload_javascript():
         with open(path, "r", encoding="utf8") as jsfile:
             contents = jsfile.read()
             javascript_files[filename] = [contents]
-            # javascript += f"\n<!-- {filename} --><script>{contents}</script>"
 
     if cmd_opts.theme is not None:
         javascript_files["theme.js"] = [f"set_theme('{cmd_opts.theme}');"]
-        # javascript += f"\n<script>set_theme('{cmd_opts.theme}');</script>\n"
 
-    # javascript += f"\n<script>{localization.localization_js(shared.opts.localization)}</script>"
     javascript_files["localization.js"] = [f"{localization.localization_js(shared.opts.localization)}"]
 
     compiled_name = "webui-compiled.js"
-- 
cgit v1.2.3


From 50059ea661b63967b217e687819cf7a9081e4a0c Mon Sep 17 00:00:00 2001
From: James Tolton <jjtolton@gmail.com>
Date: Sat, 21 Jan 2023 14:07:48 -0500
Subject: server individually listed javascript files vs single compiled file

---
 modules/ui.py                     | 52 +++++++++++++++++----------------------
 statica/put-static-files-here.txt |  1 -
 webui.py                          |  2 --
 3 files changed, 23 insertions(+), 32 deletions(-)
 delete mode 100644 statica/put-static-files-here.txt

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index ef85d43c..b372d29c 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1919,47 +1919,41 @@ def create_ui():
 
 
 def reload_javascript():
-    javascript_files = OrderedDict()
-    with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile:
-        contents = jsfile.read()
-        javascript_files["script.js"] = [contents]
-
     scripts_list = modules.scripts.list_scripts("javascript", ".js")
-
+    js_files = []
     for basedir, filename, path in scripts_list:
-        with open(path, "r", encoding="utf8") as jsfile:
-            contents = jsfile.read()
-            javascript_files[filename] = [contents]
+        path = path[len(script_path) + 1:]
+        js_files.append(path)
 
+    inline = [f"{localization.localization_js(shared.opts.localization)};"]
     if cmd_opts.theme is not None:
-        javascript_files["theme.js"] = [f"set_theme('{cmd_opts.theme}');"]
+        inline.append(f"set_theme('{cmd_opts.theme}');", )
 
-    javascript_files["localization.js"] = [f"{localization.localization_js(shared.opts.localization)}"]
-
-    compiled_name = "webui-compiled.js"
-    head = f"""
-    <script src=/statica/{compiled_name}?{int(time.time())} type="text/javascript"></script>
-    """
+    t = int(time.time())
+    head = [
+        f"""
+            <script type="text/javascript" src="file=./script.js?{t}"></script>
+    """.strip()
+    ]
+    inline_code = "\n".join(inline)
+    head.append(f"""
+        <script type="text/javascript">
+        {inline_code}
+        </script>
+        """.strip())
+    for file in js_files:
+        head.append(f"""
+        <script type="text/javascript" src="file={file}?{t}"></script>
+        """.strip())
 
     def template_response(*args, **kwargs):
         res = shared.GradioTemplateResponseOriginal(*args, **kwargs)
+        head_inject = "\n".join(head)
         res.body = res.body.replace(
-            b'</head>', f'{head}</head>'.encode("utf8"))
+            b'</head>', f'{head_inject}</head>'.encode("utf8"))
         res.init_headers()
         return res
 
-    for k in javascript_files:
-        javascript_files[k] = "\n".join(javascript_files[k])
-
-    # make static_path if not exists
-    statica_path = os.path.join(script_path, 'statica')
-    if not os.path.exists(statica_path):
-        os.mkdir(statica_path)
-
-    javascript_out = "\n\n\n".join([f"// <!-- {k} -->\n\n{v}" for k, v in javascript_files.items()])
-    with open(os.path.join(script_path, "statica", compiled_name), "w", encoding="utf8") as jsfile:
-        jsfile.write(javascript_out)
-
     gradio.routes.templates.TemplateResponse = template_response
 
 
diff --git a/statica/put-static-files-here.txt b/statica/put-static-files-here.txt
deleted file mode 100644
index 7cfaaa86..00000000
--- a/statica/put-static-files-here.txt
+++ /dev/null
@@ -1 +0,0 @@
-ayo
\ No newline at end of file
diff --git a/webui.py b/webui.py
index 50dee700..d235da74 100644
--- a/webui.py
+++ b/webui.py
@@ -8,7 +8,6 @@ import re
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.middleware.gzip import GZipMiddleware
-from starlette.staticfiles import StaticFiles
 
 from modules import import_hook, errors, extra_networks
 from modules import extra_networks_hypernet, ui_extra_networks_hypernets, ui_extra_networks_textual_inversion
@@ -196,7 +195,6 @@ def webui():
         setup_cors(app)
 
         app.add_middleware(GZipMiddleware, minimum_size=1000)
-        app.mount("/statica", StaticFiles(directory=os.path.join(script_path, 'statica')), name="statica")
 
         modules.progress.setup_progress_api(app)
 
-- 
cgit v1.2.3


From 035459c9a22bebcf68ac454a1f178fefe8c82054 Mon Sep 17 00:00:00 2001
From: James Tolton <jjtolton@gmail.com>
Date: Sat, 21 Jan 2023 14:11:13 -0500
Subject: remove dead import

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

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index b372d29c..5fde7fc5 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -10,7 +10,6 @@ import sys
 import tempfile
 import time
 import traceback
-from collections import OrderedDict
 from functools import partial, reduce
 import warnings
 
-- 
cgit v1.2.3


From e4e0918f58d382b5da400e680d743dcf0e66fd7f Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 21 Jan 2023 22:57:19 +0300
Subject: remove timestamp for js files, reformat code

---
 modules/ui.py | 34 ++++++++--------------------------
 1 file changed, 8 insertions(+), 26 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index b5581a06..ef7becc6 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1918,38 +1918,20 @@ def create_ui():
 
 
 def reload_javascript():
-    scripts_list = modules.scripts.list_scripts("javascript", ".js")
-    js_files = []
-    for basedir, filename, path in scripts_list:
-        path = path[len(script_path) + 1:]
-        js_files.append(path)
+    head = f'<script type="text/javascript" src="file={os.path.abspath("script.js")}"></script>\n'
 
-    inline = [f"{localization.localization_js(shared.opts.localization)};"]
+    inline = f"{localization.localization_js(shared.opts.localization)};"
     if cmd_opts.theme is not None:
-        inline.append(f"set_theme('{cmd_opts.theme}');", )
+        inline += f"set_theme('{cmd_opts.theme}');"
 
-    t = int(time.time())
-    head = [
-        f"""
-            <script type="text/javascript" src="file=./script.js?{t}"></script>
-    """.strip()
-    ]
-    inline_code = "\n".join(inline)
-    head.append(f"""
-        <script type="text/javascript">
-        {inline_code}
-        </script>
-        """.strip())
-    for file in js_files:
-        head.append(f"""
-        <script type="text/javascript" src="file={file}?{t}"></script>
-        """.strip())
+    head += f'<script type="text/javascript">{inline}</script>\n'
+
+    for script in modules.scripts.list_scripts("javascript", ".js"):
+        head += f'<script type="text/javascript" src="file={script.path}"></script>\n'
 
     def template_response(*args, **kwargs):
         res = shared.GradioTemplateResponseOriginal(*args, **kwargs)
-        head_inject = "\n".join(head)
-        res.body = res.body.replace(
-            b'</head>', f'{head_inject}</head>'.encode("utf8"))
+        res.body = res.body.replace(b'</head>', f'{head}</head>'.encode("utf8"))
         res.init_headers()
         return res
 
-- 
cgit v1.2.3


From 4a8fe09652b304034708d967c47901312940e852 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 21 Jan 2023 23:06:18 +0300
Subject: remove the double loading text

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

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index ef7becc6..aa39a713 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -75,6 +75,7 @@ css_hide_progressbar = """
 .wrap .m-12::before { content:"Loading..." }
 .wrap .z-20 svg { display:none!important; }
 .wrap .z-20::before { content:"Loading..." }
+.wrap.cover-bg .z-20::before { content:"" }
 .progress-bar { display:none!important; }
 .meta-text { display:none!important; }
 .meta-text-center { display:none!important; }
-- 
cgit v1.2.3


From 78f59a4e014d090bce7df3b218bfbcd7f11e0894 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 21 Jan 2023 23:40:13 +0300
Subject: enable compact view for train tab prevent  previews from ruining
 hypernetwork training

---
 modules/hypernetworks/hypernetwork.py | 2 ++
 modules/processing.py                 | 8 ++++++--
 modules/ui.py                         | 2 +-
 3 files changed, 9 insertions(+), 3 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 80a47c79..503534e2 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -715,6 +715,8 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
                         do_not_save_samples=True,
                     )
 
+                    p.disable_extra_networks = True
+
                     if preview_from_txt2img:
                         p.prompt = preview_prompt
                         p.negative_prompt = preview_negative_prompt
diff --git a/modules/processing.py b/modules/processing.py
index 6e6371a1..bc541e2f 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -140,6 +140,7 @@ class StableDiffusionProcessing:
         self.override_settings = {k: v for k, v in (override_settings or {}).items() if k not in shared.restricted_opts}
         self.override_settings_restore_afterwards = override_settings_restore_afterwards
         self.is_using_inpainting_conditioning = False
+        self.disable_extra_networks = False
 
         if not seed_enable_extras:
             self.subseed = -1
@@ -567,7 +568,8 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
         with devices.autocast():
             p.init(p.all_prompts, p.all_seeds, p.all_subseeds)
 
-            extra_networks.activate(p, extra_network_data)
+            if not p.disable_extra_networks:
+                extra_networks.activate(p, extra_network_data)
 
         with open(os.path.join(shared.script_path, "params.txt"), "w", encoding="utf8") as file:
             processed = Processed(p, [], p.seed, "")
@@ -684,7 +686,9 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
             if opts.grid_save:
                 images.save_image(grid, p.outpath_grids, "grid", p.all_seeds[0], p.all_prompts[0], opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename, p=p, grid=True)
 
-    extra_networks.deactivate(p, extra_network_data)
+    if not p.disable_extra_networks:
+        extra_networks.deactivate(p, extra_network_data)
+
     devices.torch_gc()
 
     res = Processed(p, output_images, p.all_seeds[0], infotext(), comments="".join(["\n\n" + x for x in comments]), subseed=p.all_subseeds[0], index_of_first_image=index_of_first_image, infotexts=infotexts)
diff --git a/modules/ui.py b/modules/ui.py
index daebbc9f..af6dfb21 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1259,7 +1259,7 @@ def create_ui():
         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>")
 
-        with gr.Row().style(equal_height=False):
+        with gr.Row(variant="compact").style(equal_height=False):
             with gr.Tabs(elem_id="train_tabs"):
 
                 with gr.Tab(label="Create embedding"):
-- 
cgit v1.2.3


From bf457b30fbfedb4b6eb2a198cbaa9f2ba071d31f Mon Sep 17 00:00:00 2001
From: EllangoK <karun.ellango7@gmail.com>
Date: Sat, 21 Jan 2023 16:21:33 -0500
Subject: compact checkbox and fix copy image btn overflow also fixes type for
 #tab_extensions in style.css

---
 modules/ui.py | 2 +-
 style.css     | 6 +++++-
 2 files changed, 6 insertions(+), 2 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index af6dfb21..12fc9e6a 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -919,7 +919,7 @@ def create_ui():
                         seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('img2img')
 
                     elif category == "checkboxes":
-                        with FormRow(elem_id="img2img_checkboxes"):
+                        with FormRow(elem_id="img2img_checkboxes", variant="compact"):
                             restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="img2img_restore_faces")
                             tiling = gr.Checkbox(label='Tiling', value=False, elem_id="img2img_tiling")
 
diff --git a/style.css b/style.css
index 507acec1..b215405d 100644
--- a/style.css
+++ b/style.css
@@ -589,7 +589,7 @@ canvas[key="mask"] {
 
 /* Extensions */
 
-#tab_extensions table``{
+#tab_extensions table{
     border-collapse: collapse;
 }
 
@@ -718,6 +718,10 @@ footer {
     margin-left: -0.8em;
 }
 
+#img2img_copy_to_img2img, #img2img_copy_to_sketch, #img2img_copy_to_inpaint, #img2img_copy_to_inpaint_sketch{
+    margin-left: 0em;
+}
+
 .inactive{
     opacity: 0.5;
 }
-- 
cgit v1.2.3


From 112416d04171e4bee673f0adc9bd3aeba87ec71a Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 22 Jan 2023 10:17:12 +0300
Subject: add option to discard weights in checkpoint merger UI

---
 modules/extras.py | 9 ++++++++-
 modules/ui.py     | 4 ++++
 2 files changed, 12 insertions(+), 1 deletion(-)

(limited to 'modules/ui.py')

diff --git a/modules/extras.py b/modules/extras.py
index 1218f88f..385430dc 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -1,6 +1,7 @@
 from __future__ import annotations
 import math
 import os
+import re
 import sys
 import traceback
 import shutil
@@ -285,7 +286,7 @@ def to_half(tensor, enable):
     return tensor
 
 
-def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format, config_source, bake_in_vae):
+def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format, config_source, bake_in_vae, discard_weights):
     shared.state.begin()
     shared.state.job = 'model-merge'
 
@@ -430,6 +431,12 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
         for key in theta_0.keys():
             theta_0[key] = to_half(theta_0[key], save_as_half)
 
+    if discard_weights:
+        regex = re.compile(discard_weights)
+        for key in list(theta_0):
+            if re.search(regex, key):
+                theta_0.pop(key, None)
+
     ckpt_dir = shared.cmd_opts.ckpt_dir or sd_models.model_path
 
     filename = filename_generator() if custom_name == '' else custom_name
diff --git a/modules/ui.py b/modules/ui.py
index af6dfb21..eb4b7e6b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1248,6 +1248,9 @@ def create_ui():
                             bake_in_vae = gr.Dropdown(choices=["None"] + list(sd_vae.vae_dict), value="None", label="Bake in VAE", elem_id="modelmerger_bake_in_vae")
                             create_refresh_button(bake_in_vae, sd_vae.refresh_vae_list, lambda: {"choices": ["None"] + list(sd_vae.vae_dict)}, "modelmerger_refresh_bake_in_vae")
 
+                with FormRow():
+                    discard_weights = gr.Textbox(value="", label="Discard weights with matching name", elem_id="modelmerger_discard_weights")
+
                 with gr.Row():
                     modelmerger_merge = gr.Button(elem_id="modelmerger_merge", value="Merge", variant='primary')
 
@@ -1838,6 +1841,7 @@ def create_ui():
                 checkpoint_format,
                 config_source,
                 bake_in_vae,
+                discard_weights,
             ],
             outputs=[
                 primary_model_name,
-- 
cgit v1.2.3


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

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

(limited to 'modules/ui.py')

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


From b5230197a69d36a79fdc4919c59a03e00e872dd3 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 23 Jan 2023 09:24:43 +0300
Subject: rework extras tab to use script system

---
 javascript/ui.js                     |   5 -
 modules/api/api.py                   |  13 +-
 modules/postprocessing.py            | 236 ++++++++-----------------------
 modules/scripts.py                   |  28 ++--
 modules/scripts_postprocessing.py    | 147 +++++++++++++++++++
 modules/shared.py                    |   5 +
 modules/ui.py                        | 265 +----------------------------------
 modules/ui_common.py                 | 202 ++++++++++++++++++++++++++
 modules/ui_components.py             |   6 -
 modules/ui_postprocessing.py         |  57 ++++++++
 scripts/postprocessing_codeformer.py |  36 +++++
 scripts/postprocessing_gfpgan.py     |  33 +++++
 scripts/postprocessing_upscale.py    | 106 ++++++++++++++
 13 files changed, 675 insertions(+), 464 deletions(-)
 create mode 100644 modules/scripts_postprocessing.py
 create mode 100644 modules/ui_common.py
 create mode 100644 modules/ui_postprocessing.py
 create mode 100644 scripts/postprocessing_codeformer.py
 create mode 100644 scripts/postprocessing_gfpgan.py
 create mode 100644 scripts/postprocessing_upscale.py

(limited to 'modules/ui.py')

diff --git a/javascript/ui.js b/javascript/ui.js
index 77256e15..ba72623c 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -104,11 +104,6 @@ function create_tab_index_args(tabId, args){
     return res
 }
 
-function get_extras_tab_index(){
-    const [,,...args] = [...arguments]
-    return [get_tab_index('mode_extras'), get_tab_index('extras_resize_mode'), ...args]
-}
-
 function get_img2img_tab_index() {
     let res = args_to_array(arguments)
     res.splice(-2)
diff --git a/modules/api/api.py b/modules/api/api.py
index f2e9e884..5d60fc0a 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -11,10 +11,9 @@ from fastapi.security import HTTPBasic, HTTPBasicCredentials
 from secrets import compare_digest
 
 import modules.shared as shared
-from modules import sd_samplers, deepbooru, sd_hijack, images, scripts, ui
+from modules import sd_samplers, deepbooru, sd_hijack, images, scripts, ui, postprocessing
 from modules.api.models import *
 from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images
-from modules.extras import run_extras
 from modules.textual_inversion.textual_inversion import create_embedding, train_embedding
 from modules.textual_inversion.preprocess import preprocess
 from modules.hypernetworks.hypernetwork import create_hypernetwork, train_hypernetwork
@@ -45,10 +44,8 @@ def validate_sampler_name(name):
 
 def setUpscalers(req: dict):
     reqDict = vars(req)
-    reqDict['extras_upscaler_1'] = upscaler_to_index(req.upscaler_1)
-    reqDict['extras_upscaler_2'] = upscaler_to_index(req.upscaler_2)
-    reqDict.pop('upscaler_1')
-    reqDict.pop('upscaler_2')
+    reqDict['extras_upscaler_1'] = reqDict.pop('upscaler_1', None)
+    reqDict['extras_upscaler_2'] = reqDict.pop('upscaler_2', None)
     return reqDict
 
 def decode_base64_to_image(encoding):
@@ -244,7 +241,7 @@ class Api:
         reqDict['image'] = decode_base64_to_image(reqDict['image'])
 
         with self.queue_lock:
-            result = run_extras(extras_mode=0, image_folder="", input_dir="", output_dir="", save_output=False, **reqDict)
+            result = postprocessing.run_extras(extras_mode=0, image_folder="", input_dir="", output_dir="", save_output=False, **reqDict)
 
         return ExtrasSingleImageResponse(image=encode_pil_to_base64(result[0][0]), html_info=result[1])
 
@@ -260,7 +257,7 @@ class Api:
         reqDict.pop('imageList')
 
         with self.queue_lock:
-            result = run_extras(extras_mode=1, image="", input_dir="", output_dir="", save_output=False, **reqDict)
+            result = postprocessing.run_extras(extras_mode=1, image="", input_dir="", output_dir="", save_output=False, **reqDict)
 
         return ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1])
 
diff --git a/modules/postprocessing.py b/modules/postprocessing.py
index cb85720b..8514fea7 100644
--- a/modules/postprocessing.py
+++ b/modules/postprocessing.py
@@ -1,219 +1,103 @@
-from __future__ import annotations
 import os
 
-import numpy as np
 from PIL import Image
 
-from typing import Callable, List, OrderedDict, Tuple
-from functools import partial
-from dataclasses import dataclass
-
-from modules import shared, images, devices, ui_components
+from modules import shared, images, devices, scripts, scripts_postprocessing, ui_common, generation_parameters_copypaste
 from modules.shared import opts
-import modules.gfpgan_model
-import modules.codeformer_model
-
-
-class LruCache(OrderedDict):
-    @dataclass(frozen=True)
-    class Key:
-        image_hash: int
-        info_hash: int
-        args_hash: int
-
-    @dataclass
-    class Value:
-        image: Image.Image
-        info: str
-
-    def __init__(self, max_size: int = 5, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-        self._max_size = max_size
-
-    def get(self, key: LruCache.Key) -> LruCache.Value:
-        ret = super().get(key)
-        if ret is not None:
-            self.move_to_end(key)  # Move to end of eviction list
-        return ret
-
-    def put(self, key: LruCache.Key, value: LruCache.Value) -> None:
-        self[key] = value
-        while len(self) > self._max_size:
-            self.popitem(last=False)
-
-
-cached_images: LruCache = LruCache(max_size=5)
 
 
-def run_postprocessing(extras_mode, resize_mode, image, image_folder, input_dir, output_dir, show_extras_results, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, upscale_first: bool, save_output: bool = True):
+def run_postprocessing(extras_mode, image, image_folder, input_dir, output_dir, show_extras_results, *args, save_output: bool = True):
     devices.torch_gc()
 
     shared.state.begin()
     shared.state.job = 'extras'
 
-    imageArr = []
-    # Also keep track of original file names
-    imageNameArr = []
+    image_data = []
+    image_names = []
     outputs = []
 
     if extras_mode == 1:
-        #convert file to pillow image
         for img in image_folder:
             image = Image.open(img)
-            imageArr.append(image)
-            imageNameArr.append(os.path.splitext(img.orig_name)[0])
+            image_data.append(image)
+            image_names.append(os.path.splitext(img.orig_name)[0])
     elif extras_mode == 2:
         assert not shared.cmd_opts.hide_ui_dir_config, '--hide-ui-dir-config option must be disabled'
+        assert input_dir, 'input directory not selected'
 
-        if input_dir == '':
-            return outputs, "Please select an input directory.", ''
         image_list = shared.listfiles(input_dir)
-        for img in image_list:
+        for filename in image_list:
             try:
-                image = Image.open(img)
+                image = Image.open(filename)
             except Exception:
                 continue
-            imageArr.append(image)
-            imageNameArr.append(img)
+            image_data.append(image)
+            image_names.append(filename)
     else:
-        imageArr.append(image)
-        imageNameArr.append(None)
+        assert image, 'image not selected'
+
+        image_data.append(image)
+        image_names.append(None)
 
     if extras_mode == 2 and output_dir != '':
         outpath = output_dir
     else:
         outpath = opts.outdir_samples or opts.outdir_extras_samples
 
-    # Extra operation definitions
-
-    def run_gfpgan(image: Image.Image, info: str) -> Tuple[Image.Image, str]:
-        shared.state.job = 'extras-gfpgan'
-        restored_img = modules.gfpgan_model.gfpgan_fix_faces(np.array(image, dtype=np.uint8))
-        res = Image.fromarray(restored_img)
-
-        if gfpgan_visibility < 1.0:
-            res = Image.blend(image, res, gfpgan_visibility)
-
-        info += f"GFPGAN visibility:{round(gfpgan_visibility, 2)}\n"
-        return (res, info)
-
-    def run_codeformer(image: Image.Image, info: str) -> Tuple[Image.Image, str]:
-        shared.state.job = 'extras-codeformer'
-        restored_img = modules.codeformer_model.codeformer.restore(np.array(image, dtype=np.uint8), w=codeformer_weight)
-        res = Image.fromarray(restored_img)
-
-        if codeformer_visibility < 1.0:
-            res = Image.blend(image, res, codeformer_visibility)
-
-        info += f"CodeFormer w: {round(codeformer_weight, 2)}, CodeFormer visibility:{round(codeformer_visibility, 2)}\n"
-        return (res, info)
-
-    def upscale(image, scaler_index, resize, mode, resize_w, resize_h, crop):
-        shared.state.job = 'extras-upscale'
-        upscaler = shared.sd_upscalers[scaler_index]
-        res = upscaler.scaler.upscale(image, resize, upscaler.data_path)
-        if mode == 1 and crop:
-            cropped = Image.new("RGB", (resize_w, resize_h))
-            cropped.paste(res, box=(resize_w // 2 - res.width // 2, resize_h // 2 - res.height // 2))
-            res = cropped
-        return res
-
-    def run_prepare_crop(image: Image.Image, info: str) -> Tuple[Image.Image, str]:
-        # Actual crop happens in run_upscalers_blend, this just sets upscaling_resize and adds info text
-        nonlocal upscaling_resize
-        if resize_mode == 1:
-            upscaling_resize = max(upscaling_resize_w/image.width, upscaling_resize_h/image.height)
-            crop_info = " (crop)" if upscaling_crop else ""
-            info += f"Resize to: {upscaling_resize_w:g}x{upscaling_resize_h:g}{crop_info}\n"
-        return (image, info)
-
-    @dataclass
-    class UpscaleParams:
-        upscaler_idx: int
-        blend_alpha: float
-
-    def run_upscalers_blend(params: List[UpscaleParams], image: Image.Image, info: str) -> Tuple[Image.Image, str]:
-        blended_result: Image.Image = None
-        image_hash: str = hash(np.array(image.getdata()).tobytes())
-        for upscaler in params:
-            upscale_args = (upscaler.upscaler_idx, upscaling_resize, resize_mode,
-                            upscaling_resize_w, upscaling_resize_h, upscaling_crop)
-            cache_key = LruCache.Key(image_hash=image_hash,
-                                     info_hash=hash(info),
-                                     args_hash=hash(upscale_args))
-            cached_entry = cached_images.get(cache_key)
-            if cached_entry is None:
-                res = upscale(image, *upscale_args)
-                info += f"Upscale: {round(upscaling_resize, 3)}, visibility: {upscaler.blend_alpha}, model:{shared.sd_upscalers[upscaler.upscaler_idx].name}\n"
-                cached_images.put(cache_key, LruCache.Value(image=res, info=info))
-            else:
-                res, info = cached_entry.image, cached_entry.info
-
-            if blended_result is None:
-                blended_result = res
-            else:
-                blended_result = Image.blend(blended_result, res, upscaler.blend_alpha)
-        return (blended_result, info)
-
-    # Build a list of operations to run
-    facefix_ops: List[Callable] = []
-    facefix_ops += [run_gfpgan] if gfpgan_visibility > 0 else []
-    facefix_ops += [run_codeformer] if codeformer_visibility > 0 else []
-
-    upscale_ops: List[Callable] = []
-    upscale_ops += [run_prepare_crop] if resize_mode == 1 else []
-
-    if upscaling_resize != 0:
-        step_params: List[UpscaleParams] = []
-        step_params.append(UpscaleParams(upscaler_idx=extras_upscaler_1, blend_alpha=1.0))
-        if extras_upscaler_2 != 0 and extras_upscaler_2_visibility > 0:
-            step_params.append(UpscaleParams(upscaler_idx=extras_upscaler_2, blend_alpha=extras_upscaler_2_visibility))
-
-        upscale_ops.append(partial(run_upscalers_blend, step_params))
-
-    extras_ops: List[Callable] = (upscale_ops + facefix_ops) if upscale_first else (facefix_ops + upscale_ops)
-
-    for image, image_name in zip(imageArr, imageNameArr):
-        if image is None:
-            return outputs, "Please select an input image.", ''
-
-        shared.state.textinfo = f'Processing image {image_name}'
-        
+    infotext = ''
+
+    for image, name in zip(image_data, image_names):
+        shared.state.textinfo = name
+
         existing_pnginfo = image.info or {}
 
-        image = image.convert("RGB")
-        info = ""
-        # Run each operation on each image
-        for op in extras_ops:
-            image, info = op(image, info)
+        pp = scripts_postprocessing.PostprocessedImage(image.convert("RGB"))
 
-        if opts.use_original_name_batch and image_name is not None:
-            basename = os.path.splitext(os.path.basename(image_name))[0]
+        scripts.scripts_postproc.run(pp, args)
+
+        if opts.use_original_name_batch and name is not None:
+            basename = os.path.splitext(os.path.basename(name))[0]
         else:
             basename = ''
 
-        if opts.enable_pnginfo: # append info before save
-            image.info = existing_pnginfo
-            image.info["extras"] = info
+        infotext = ", ".join([k if k == v else f'{k}: {generation_parameters_copypaste.quote(v)}' for k, v in pp.info.items() if v is not None])
 
-        if save_output:
-            # Add upscaler name as a suffix.
-            suffix = f"-{shared.sd_upscalers[extras_upscaler_1].name}" if shared.opts.use_upscaler_name_as_suffix else ""
-            # Add second upscaler if applicable.
-            if suffix and extras_upscaler_2 and extras_upscaler_2_visibility:
-                suffix += f"-{shared.sd_upscalers[extras_upscaler_2].name}"
+        if opts.enable_pnginfo:
+            pp.image.info = existing_pnginfo
+            pp.image.info["postprocessing"] = infotext
 
-            images.save_image(image, path=outpath, basename=basename, seed=None, prompt=None, extension=opts.samples_format, info=info, short_filename=True,
-                            no_prompt=True, grid=False, pnginfo_section_name="extras", existing_info=existing_pnginfo, forced_filename=None, suffix=suffix)
+        if save_output:
+            images.save_image(pp.image, path=outpath, basename=basename, seed=None, prompt=None, extension=opts.samples_format, info=pp.info, short_filename=True, no_prompt=True, grid=False, pnginfo_section_name="extras", existing_info=existing_pnginfo, forced_filename=None)
 
-        if extras_mode != 2 or show_extras_results :
-            outputs.append(image)
+        if extras_mode != 2 or show_extras_results:
+            outputs.append(pp.image)
 
     devices.torch_gc()
 
-    return outputs, ui_components.plaintext_to_html(info), ''
-
-
-def clear_cache():
-    cached_images.clear()
-
+    return outputs, ui_common.plaintext_to_html(infotext), ''
+
+
+def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_dir, show_extras_results, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, upscale_first: bool, save_output: bool = True):
+    """old handler for API"""
+
+    args = scripts.scripts_postproc.create_args_for_run({
+        "Upscale": {
+            "upscale_mode": resize_mode,
+            "upscale_by": upscaling_resize,
+            "upscale_to_width": upscaling_resize_w,
+            "upscale_to_height": upscaling_resize_h,
+            "upscale_crop": upscaling_crop,
+            "upscaler_1_name": extras_upscaler_1,
+            "upscaler_2_name": extras_upscaler_2,
+            "upscaler_2_visibility": extras_upscaler_2_visibility,
+        },
+        "GFPGAN": {
+            "gfpgan_visibility": gfpgan_visibility,
+        },
+        "CodeFormer": {
+            "codeformer_visibility": codeformer_visibility,
+            "codeformer_weight": codeformer_weight,
+        },
+    })
+
+    return run_postprocessing(extras_mode, image, image_folder, input_dir, output_dir, show_extras_results, *args, save_output=save_output)
diff --git a/modules/scripts.py b/modules/scripts.py
index 4ffc369b..03907a63 100644
--- a/modules/scripts.py
+++ b/modules/scripts.py
@@ -7,7 +7,7 @@ from collections import namedtuple
 import gradio as gr
 
 from modules.processing import StableDiffusionProcessing
-from modules import shared, paths, script_callbacks, extensions, script_loading
+from modules import shared, paths, script_callbacks, extensions, script_loading, scripts_postprocessing
 
 AlwaysVisible = object()
 
@@ -150,8 +150,10 @@ def basedir():
     return current_basedir
 
 
-scripts_data = []
 ScriptFile = namedtuple("ScriptFile", ["basedir", "filename", "path"])
+
+scripts_data = []
+postprocessing_scripts_data = []
 ScriptClassData = namedtuple("ScriptClassData", ["script_class", "path", "basedir", "module"])
 
 
@@ -190,23 +192,31 @@ def list_files_with_name(filename):
 def load_scripts():
     global current_basedir
     scripts_data.clear()
+    postprocessing_scripts_data.clear()
     script_callbacks.clear_callbacks()
 
     scripts_list = list_scripts("scripts", ".py")
 
     syspath = sys.path
 
+    def register_scripts_from_module(module):
+        for key, script_class in module.__dict__.items():
+            if type(script_class) != type:
+                continue
+
+            if issubclass(script_class, Script):
+                scripts_data.append(ScriptClassData(script_class, scriptfile.path, scriptfile.basedir, module))
+            elif issubclass(script_class, scripts_postprocessing.ScriptPostprocessing):
+                postprocessing_scripts_data.append(ScriptClassData(script_class, scriptfile.path, scriptfile.basedir, module))
+
     for scriptfile in sorted(scripts_list):
         try:
             if scriptfile.basedir != paths.script_path:
                 sys.path = [scriptfile.basedir] + sys.path
             current_basedir = scriptfile.basedir
 
-            module = script_loading.load_module(scriptfile.path)
-
-            for key, script_class in module.__dict__.items():
-                if type(script_class) == type and issubclass(script_class, Script):
-                    scripts_data.append(ScriptClassData(script_class, scriptfile.path, scriptfile.basedir, module))
+            script_module = script_loading.load_module(scriptfile.path)
+            register_scripts_from_module(script_module)
 
         except Exception:
             print(f"Error loading script: {scriptfile.filename}", file=sys.stderr)
@@ -413,6 +423,7 @@ class ScriptRunner:
 
 scripts_txt2img = ScriptRunner()
 scripts_img2img = ScriptRunner()
+scripts_postproc = scripts_postprocessing.ScriptPostprocessingRunner()
 scripts_current: ScriptRunner = None
 
 
@@ -423,12 +434,13 @@ def reload_script_body_only():
 
 
 def reload_scripts():
-    global scripts_txt2img, scripts_img2img
+    global scripts_txt2img, scripts_img2img, scripts_postproc
 
     load_scripts()
 
     scripts_txt2img = ScriptRunner()
     scripts_img2img = ScriptRunner()
+    scripts_postproc = scripts_postprocessing.ScriptPostprocessingRunner()
 
 
 def IOComponent_init(self, *args, **kwargs):
diff --git a/modules/scripts_postprocessing.py b/modules/scripts_postprocessing.py
new file mode 100644
index 00000000..25de02d0
--- /dev/null
+++ b/modules/scripts_postprocessing.py
@@ -0,0 +1,147 @@
+import os
+import gradio as gr
+
+from modules import errors, shared
+
+
+class PostprocessedImage:
+    def __init__(self, image):
+        self.image = image
+        self.info = {}
+
+
+class ScriptPostprocessing:
+    filename = None
+    controls = None
+    args_from = None
+    args_to = None
+
+    order = 1000
+    """scripts will be ordred by this value in postprocessing UI"""
+
+    name = None
+    """this function should return the title of the script."""
+
+    group = None
+    """A gr.Group component that has all script's UI inside it"""
+
+    def ui(self):
+        """
+        This function should create gradio UI elements. See https://gradio.app/docs/#components
+        The return value should be a dictionary that maps parameter names to components used in processing.
+        Values of those components will be passed to process() function.
+        """
+
+        pass
+
+    def process(self, pp: PostprocessedImage, **args):
+        """
+        This function is called to postprocess the image.
+        args contains a dictionary with all values returned by components from ui()
+        """
+
+        pass
+
+    def image_changed(self):
+        pass
+
+
+def wrap_call(func, filename, funcname, *args, default=None, **kwargs):
+    try:
+        res = func(*args, **kwargs)
+        return res
+    except Exception as e:
+        errors.display(e, f"calling {filename}/{funcname}")
+
+    return default
+
+
+class ScriptPostprocessingRunner:
+    def __init__(self):
+        self.scripts = None
+        self.ui_created = False
+
+    def initialize_scripts(self, scripts_data):
+        self.scripts = []
+
+        for script_class, path, basedir, script_module in scripts_data:
+            script: ScriptPostprocessing = script_class()
+            script.filename = path
+
+            self.scripts.append(script)
+
+    def create_script_ui(self, script, inputs):
+        script.args_from = len(inputs)
+        script.args_to = len(inputs)
+
+        script.controls = wrap_call(script.ui, script.filename, "ui")
+
+        for control in script.controls.values():
+            control.custom_script_source = os.path.basename(script.filename)
+
+        inputs += list(script.controls.values())
+        script.args_to = len(inputs)
+
+    def scripts_in_preferred_order(self):
+        if self.scripts is None:
+            import modules.scripts
+            self.initialize_scripts(modules.scripts.postprocessing_scripts_data)
+
+        scripts_order = [x.lower().strip() for x in shared.opts.postprocessing_scipts_order.split(",")]
+
+        def script_score(name):
+            name = name.lower()
+            for i, possible_match in enumerate(scripts_order):
+                if possible_match in name:
+                    return i
+
+            return len(self.scripts)
+
+        script_scores = {script.name: (script_score(script.name), script.order, script.name, original_index) for original_index, script in enumerate(self.scripts)}
+
+        return sorted(self.scripts, key=lambda x: script_scores[x.name])
+
+    def setup_ui(self):
+        inputs = []
+
+        for script in self.scripts_in_preferred_order():
+            with gr.Box() as group:
+                self.create_script_ui(script, inputs)
+
+            script.group = group
+
+        self.ui_created = True
+        return inputs
+
+    def run(self, pp: PostprocessedImage, args):
+        for script in self.scripts_in_preferred_order():
+            shared.state.job = script.name
+
+            script_args = args[script.args_from:script.args_to]
+
+            process_args = {}
+            for (name, component), value in zip(script.controls.items(), script_args):
+                process_args[name] = value
+
+            script.process(pp, **process_args)
+
+    def create_args_for_run(self, scripts_args):
+        if not self.ui_created:
+            with gr.Blocks(analytics_enabled=False):
+                self.setup_ui()
+
+        scripts = self.scripts_in_preferred_order()
+        args = [None] * max([x.args_to for x in scripts])
+
+        for script in scripts:
+            script_args_dict = scripts_args.get(script.name, None)
+            if script_args_dict is not None:
+
+                for i, name in enumerate(script.controls):
+                    args[script.args_from + i] = script_args_dict.get(name, None)
+
+        return args
+
+    def image_changed(self):
+        for script in self.scripts_in_preferred_order():
+            script.image_changed()
diff --git a/modules/shared.py b/modules/shared.py
index cd78e50a..cb73bf31 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -474,6 +474,11 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters"
     'always_discard_next_to_last_sigma': OptionInfo(False, "Always discard next-to-last sigma"),
 }))
 
+options_templates.update(options_section(('postprocessing', "Postprocessing"), {
+    'postprocessing_scipts_order': OptionInfo("upscale, gfpgan, codeformer", "Postprocessing operation order"),
+    'upscaling_max_images_in_cache': OptionInfo(5, "Maximum number of images in upscaling cache", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
+}))
+
 options_templates.update(options_section((None, "Hidden options"), {
     "disabled_extensions": OptionInfo([], "Disable those extensions"),
     "sd_checkpoint_hash": OptionInfo("", "SHA256 hash of the current checkpoint"),
diff --git a/modules/ui.py b/modules/ui.py
index 4116e167..8cb8e613 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -20,7 +20,7 @@ import numpy as np
 from PIL import Image, PngImagePlugin
 from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
 
-from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, postprocessing, ui_components
+from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, postprocessing, ui_components, ui_common, ui_postprocessing
 from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
 from modules.paths import script_path
 
@@ -86,7 +86,6 @@ css_hide_progressbar = """
 random_symbol = '\U0001f3b2\ufe0f'  # 🎲️
 reuse_symbol = '\u267b\ufe0f'  # ♻️
 paste_symbol = '\u2199\ufe0f'  # ↙
-folder_symbol = '\U0001f4c2'  # 📂
 refresh_symbol = '\U0001f504'  # 🔄
 save_style_symbol = '\U0001f4be'  # 💾
 apply_style_symbol = '\U0001f4cb'  # 📋
@@ -95,7 +94,7 @@ extra_networks_symbol = '\U0001F3B4'  # 🎴
 
 
 def plaintext_to_html(text):
-    return ui_components.plaintext_to_html(text)
+    return ui_common.plaintext_to_html(text)
 
 
 def send_gradio_gallery_to_image(x):
@@ -103,70 +102,6 @@ def send_gradio_gallery_to_image(x):
         return None
     return image_from_url_text(x[0])
 
-def save_files(js_data, images, do_make_zip, index):
-    import csv
-    filenames = []
-    fullfns = []
-
-    #quick dictionary to class object conversion. Its necessary due apply_filename_pattern requiring it
-    class MyObject:
-        def __init__(self, d=None):
-            if d is not None:
-                for key, value in d.items():
-                    setattr(self, key, value)
-
-    data = json.loads(js_data)
-
-    p = MyObject(data)
-    path = opts.outdir_save
-    save_to_dirs = opts.use_save_to_dirs_for_ui
-    extension: str = opts.samples_format
-    start_index = 0
-
-    if index > -1 and opts.save_selected_only and (index >= data["index_of_first_image"]):  # ensures we are looking at a specific non-grid picture, and we have save_selected_only
-
-        images = [images[index]]
-        start_index = index
-
-    os.makedirs(opts.outdir_save, exist_ok=True)
-
-    with open(os.path.join(opts.outdir_save, "log.csv"), "a", encoding="utf8", newline='') as file:
-        at_start = file.tell() == 0
-        writer = csv.writer(file)
-        if at_start:
-            writer.writerow(["prompt", "seed", "width", "height", "sampler", "cfgs", "steps", "filename", "negative_prompt"])
-
-        for image_index, filedata in enumerate(images, start_index):
-            image = image_from_url_text(filedata)
-
-            is_grid = image_index < p.index_of_first_image
-            i = 0 if is_grid else (image_index - p.index_of_first_image)
-
-            fullfn, txt_fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
-
-            filename = os.path.relpath(fullfn, path)
-            filenames.append(filename)
-            fullfns.append(fullfn)
-            if txt_fullfn:
-                filenames.append(os.path.basename(txt_fullfn))
-                fullfns.append(txt_fullfn)
-
-        writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler_name"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]])
-
-    # Make Zip
-    if do_make_zip:
-        zip_filepath = os.path.join(path, "images.zip")
-
-        from zipfile import ZipFile
-        with ZipFile(zip_filepath, "w") as zip_file:
-            for i in range(len(fullfns)):
-                with open(fullfns[i], mode="rb") as f:
-                    zip_file.writestr(filenames[i], f.read())
-        fullfns.insert(0, zip_filepath)
-
-    return gr.File.update(value=fullfns, visible=True), plaintext_to_html(f"Saved: {filenames[0]}")
-
-
 def visit(x, func, path=""):
     if hasattr(x, 'children'):
         for c in x.children:
@@ -444,19 +379,6 @@ def apply_setting(key, value):
     opts.save(shared.config_filename)
     return getattr(opts, key)
 
-
-def update_generation_info(generation_info, html_info, img_index):
-    try:
-        generation_info = json.loads(generation_info)
-        if img_index < 0 or img_index >= len(generation_info["infotexts"]):
-            return html_info, gr.update()
-        return plaintext_to_html(generation_info["infotexts"][img_index]), gr.update()
-    except Exception:
-        pass
-    # if the json parse or anything else fails, just return the old html_info
-    return html_info, gr.update()
-
-
 def create_refresh_button(refresh_component, refresh_method, refreshed_args, elem_id):
     def refresh():
         refresh_method()
@@ -477,107 +399,7 @@ def create_refresh_button(refresh_component, refresh_method, refreshed_args, ele
 
 
 def create_output_panel(tabname, outdir):
-    def open_folder(f):
-        if not os.path.exists(f):
-            print(f'Folder "{f}" does not exist. After you create an image, the folder will be created.')
-            return
-        elif not os.path.isdir(f):
-            print(f"""
-WARNING
-An open_folder request was made with an argument that is not a folder.
-This could be an error or a malicious attempt to run code on your computer.
-Requested path was: {f}
-""", file=sys.stderr)
-            return
-
-        if not shared.cmd_opts.hide_ui_dir_config:
-            path = os.path.normpath(f)
-            if platform.system() == "Windows":
-                os.startfile(path)
-            elif platform.system() == "Darwin":
-                sp.Popen(["open", path])
-            elif "microsoft-standard-WSL2" in platform.uname().release:
-                sp.Popen(["wsl-open", path])
-            else:
-                sp.Popen(["xdg-open", path])
-
-    with gr.Column(variant='panel', elem_id=f"{tabname}_results"):
-            with gr.Group(elem_id=f"{tabname}_gallery_container"):
-                result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery").style(grid=4)
-
-            generation_info = None
-            with gr.Column():
-                with gr.Row(elem_id=f"image_buttons_{tabname}"):
-                    open_folder_button = gr.Button(folder_symbol, elem_id="hidden_element" if shared.cmd_opts.hide_ui_dir_config else f'open_folder_{tabname}')
-
-                    if tabname != "extras":
-                        save = gr.Button('Save', elem_id=f'save_{tabname}')
-                        save_zip = gr.Button('Zip', elem_id=f'save_zip_{tabname}')
-
-                    buttons = parameters_copypaste.create_buttons(["img2img", "inpaint", "extras"])
-
-                open_folder_button.click(
-                    fn=lambda: open_folder(opts.outdir_samples or outdir),
-                    inputs=[],
-                    outputs=[],
-                )
-
-                if tabname != "extras":
-                    with gr.Row():
-                        download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False, elem_id=f'download_files_{tabname}')
-
-                    with gr.Group():
-                        html_info = gr.HTML(elem_id=f'html_info_{tabname}')
-                        html_log = gr.HTML(elem_id=f'html_log_{tabname}')
-
-                        generation_info = gr.Textbox(visible=False, elem_id=f'generation_info_{tabname}')
-                        if tabname == 'txt2img' or tabname == 'img2img':
-                            generation_info_button = gr.Button(visible=False, elem_id=f"{tabname}_generation_info_button")
-                            generation_info_button.click(
-                                fn=update_generation_info,
-                                _js="function(x, y, z){ return [x, y, selected_gallery_index()] }",
-                                inputs=[generation_info, html_info, html_info],
-                                outputs=[html_info, html_info],
-                            )
-
-                        save.click(
-                            fn=wrap_gradio_call(save_files),
-                            _js="(x, y, z, w) => [x, y, false, selected_gallery_index()]",
-                            inputs=[
-                                generation_info,
-                                result_gallery,
-                                html_info,
-                                html_info,
-                            ],
-                            outputs=[
-                                download_files,
-                                html_log,
-                            ],
-                            show_progress=False,
-                        )
-
-                        save_zip.click(
-                            fn=wrap_gradio_call(save_files),
-                            _js="(x, y, z, w) => [x, y, true, selected_gallery_index()]",
-                            inputs=[
-                                generation_info,
-                                result_gallery,
-                                html_info,
-                                html_info,
-                            ],
-                            outputs=[
-                                download_files,
-                                html_log,
-                            ]
-                        )
-
-                else:
-                    html_info_x = gr.HTML(elem_id=f'html_info_x_{tabname}')
-                    html_info = gr.HTML(elem_id=f'html_info_{tabname}')
-                    html_log = gr.HTML(elem_id=f'html_log_{tabname}')
-
-                parameters_copypaste.bind_buttons(buttons, result_gallery, "txt2img" if tabname == "txt2img" else None)
-                return result_gallery, generation_info if tabname != "extras" else html_info_x, html_info, html_log
+    return ui_common.create_output_panel(tabname, outdir)
 
 
 def create_sampler_and_steps_selection(choices, tabname):
@@ -1106,86 +928,7 @@ def create_ui():
     modules.scripts.scripts_current = None
 
     with gr.Blocks(analytics_enabled=False) as extras_interface:
-        with gr.Row().style(equal_height=False):
-            with gr.Column(variant='compact'):
-                with gr.Tabs(elem_id="mode_extras"):
-                    with gr.TabItem('Single Image', elem_id="extras_single_tab"):
-                        extras_image = gr.Image(label="Source", source="upload", interactive=True, type="pil", elem_id="extras_image")
-
-                    with gr.TabItem('Batch Process', elem_id="extras_batch_process_tab"):
-                        image_batch = gr.File(label="Batch Process", file_count="multiple", interactive=True, type="file", elem_id="extras_image_batch")
-
-                    with gr.TabItem('Batch from Directory', elem_id="extras_batch_directory_tab"):
-                        extras_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, placeholder="A directory on the same machine where the server is running.", elem_id="extras_batch_input_dir")
-                        extras_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, placeholder="Leave blank to save images to the default path.", elem_id="extras_batch_output_dir")
-                        show_extras_results = gr.Checkbox(label='Show result images', value=True, elem_id="extras_show_extras_results")
-
-                submit = gr.Button('Generate', elem_id="extras_generate", variant='primary')
-
-                with gr.Tabs(elem_id="extras_resize_mode"):
-                    with gr.TabItem('Scale by', elem_id="extras_scale_by_tab"):
-                        upscaling_resize = gr.Slider(minimum=1.0, maximum=8.0, step=0.05, label="Resize", value=4, elem_id="extras_upscaling_resize")
-                    with gr.TabItem('Scale to', elem_id="extras_scale_to_tab"):
-                        with gr.Group():
-                            with gr.Row():
-                                upscaling_resize_w = gr.Number(label="Width", value=512, precision=0, elem_id="extras_upscaling_resize_w")
-                                upscaling_resize_h = gr.Number(label="Height", value=512, precision=0, elem_id="extras_upscaling_resize_h")
-                            upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop")
-
-                with gr.Group():
-                    extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
-
-                with gr.Group():
-                    extras_upscaler_2 = gr.Radio(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
-                    extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=1, elem_id="extras_upscaler_2_visibility")
-
-                with gr.Group():
-                    gfpgan_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="GFPGAN visibility", value=0, interactive=modules.gfpgan_model.have_gfpgan, elem_id="extras_gfpgan_visibility")
-
-                with gr.Group():
-                    codeformer_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer visibility", value=0, interactive=modules.codeformer_model.have_codeformer, elem_id="extras_codeformer_visibility")
-                    codeformer_weight = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer weight (0 = maximum effect, 1 = minimum effect)", value=0, interactive=modules.codeformer_model.have_codeformer, elem_id="extras_codeformer_weight")
-
-                with gr.Group():
-                    upscale_before_face_fix = gr.Checkbox(label='Upscale Before Restoring Faces', value=False, elem_id="extras_upscale_before_face_fix")
-
-            result_images, html_info_x, html_info, html_log = create_output_panel("extras", opts.outdir_extras_samples)
-
-        submit.click(
-            fn=wrap_gradio_gpu_call(postprocessing.run_postprocessing, extra_outputs=[None, '']),
-            _js="get_extras_tab_index",
-            inputs=[
-                dummy_component,
-                dummy_component,
-                extras_image,
-                image_batch,
-                extras_batch_input_dir,
-                extras_batch_output_dir,
-                show_extras_results,
-                gfpgan_visibility,
-                codeformer_visibility,
-                codeformer_weight,
-                upscaling_resize,
-                upscaling_resize_w,
-                upscaling_resize_h,
-                upscaling_crop,
-                extras_upscaler_1,
-                extras_upscaler_2,
-                extras_upscaler_2_visibility,
-                upscale_before_face_fix,
-            ],
-            outputs=[
-                result_images,
-                html_info_x,
-                html_info,
-            ]
-        )
-        parameters_copypaste.add_paste_fields("extras", extras_image, None)
-
-        extras_image.change(
-            fn=postprocessing.clear_cache,
-            inputs=[], outputs=[]
-        )
+        ui_postprocessing.create_ui()
 
     with gr.Blocks(analytics_enabled=False) as pnginfo_interface:
         with gr.Row().style(equal_height=False):
diff --git a/modules/ui_common.py b/modules/ui_common.py
new file mode 100644
index 00000000..8ce75b8c
--- /dev/null
+++ b/modules/ui_common.py
@@ -0,0 +1,202 @@
+import json
+import html
+import os
+import platform
+import sys
+
+import gradio as gr
+import scipy as sp
+
+from modules import call_queue, shared
+from modules.generation_parameters_copypaste import image_from_url_text
+import modules.images
+
+folder_symbol = '\U0001f4c2'  # 📂
+
+
+def update_generation_info(generation_info, html_info, img_index):
+    try:
+        generation_info = json.loads(generation_info)
+        if img_index < 0 or img_index >= len(generation_info["infotexts"]):
+            return html_info, gr.update()
+        return plaintext_to_html(generation_info["infotexts"][img_index]), gr.update()
+    except Exception:
+        pass
+    # if the json parse or anything else fails, just return the old html_info
+    return html_info, gr.update()
+
+
+def plaintext_to_html(text):
+    text = "<p>" + "<br>\n".join([f"{html.escape(x)}" for x in text.split('\n')]) + "</p>"
+    return text
+
+
+def save_files(js_data, images, do_make_zip, index):
+    import csv
+    filenames = []
+    fullfns = []
+
+    #quick dictionary to class object conversion. Its necessary due apply_filename_pattern requiring it
+    class MyObject:
+        def __init__(self, d=None):
+            if d is not None:
+                for key, value in d.items():
+                    setattr(self, key, value)
+
+    data = json.loads(js_data)
+
+    p = MyObject(data)
+    path = shared.opts.outdir_save
+    save_to_dirs = shared.opts.use_save_to_dirs_for_ui
+    extension: str = shared.opts.samples_format
+    start_index = 0
+
+    if index > -1 and shared.opts.save_selected_only and (index >= data["index_of_first_image"]):  # ensures we are looking at a specific non-grid picture, and we have save_selected_only
+
+        images = [images[index]]
+        start_index = index
+
+    os.makedirs(shared.opts.outdir_save, exist_ok=True)
+
+    with open(os.path.join(shared.opts.outdir_save, "log.csv"), "a", encoding="utf8", newline='') as file:
+        at_start = file.tell() == 0
+        writer = csv.writer(file)
+        if at_start:
+            writer.writerow(["prompt", "seed", "width", "height", "sampler", "cfgs", "steps", "filename", "negative_prompt"])
+
+        for image_index, filedata in enumerate(images, start_index):
+            image = image_from_url_text(filedata)
+
+            is_grid = image_index < p.index_of_first_image
+            i = 0 if is_grid else (image_index - p.index_of_first_image)
+
+            fullfn, txt_fullfn = modules.images.save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
+
+            filename = os.path.relpath(fullfn, path)
+            filenames.append(filename)
+            fullfns.append(fullfn)
+            if txt_fullfn:
+                filenames.append(os.path.basename(txt_fullfn))
+                fullfns.append(txt_fullfn)
+
+        writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler_name"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]])
+
+    # Make Zip
+    if do_make_zip:
+        zip_filepath = os.path.join(path, "images.zip")
+
+        from zipfile import ZipFile
+        with ZipFile(zip_filepath, "w") as zip_file:
+            for i in range(len(fullfns)):
+                with open(fullfns[i], mode="rb") as f:
+                    zip_file.writestr(filenames[i], f.read())
+        fullfns.insert(0, zip_filepath)
+
+    return gr.File.update(value=fullfns, visible=True), plaintext_to_html(f"Saved: {filenames[0]}")
+
+
+def create_output_panel(tabname, outdir):
+    from modules import shared
+    import modules.generation_parameters_copypaste as parameters_copypaste
+
+    def open_folder(f):
+        if not os.path.exists(f):
+            print(f'Folder "{f}" does not exist. After you create an image, the folder will be created.')
+            return
+        elif not os.path.isdir(f):
+            print(f"""
+WARNING
+An open_folder request was made with an argument that is not a folder.
+This could be an error or a malicious attempt to run code on your computer.
+Requested path was: {f}
+""", file=sys.stderr)
+            return
+
+        if not shared.cmd_opts.hide_ui_dir_config:
+            path = os.path.normpath(f)
+            if platform.system() == "Windows":
+                os.startfile(path)
+            elif platform.system() == "Darwin":
+                sp.Popen(["open", path])
+            elif "microsoft-standard-WSL2" in platform.uname().release:
+                sp.Popen(["wsl-open", path])
+            else:
+                sp.Popen(["xdg-open", path])
+
+    with gr.Column(variant='panel', elem_id=f"{tabname}_results"):
+        with gr.Group(elem_id=f"{tabname}_gallery_container"):
+            result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery").style(grid=4)
+
+        generation_info = None
+        with gr.Column():
+            with gr.Row(elem_id=f"image_buttons_{tabname}"):
+                open_folder_button = gr.Button(folder_symbol, elem_id="hidden_element" if shared.cmd_opts.hide_ui_dir_config else f'open_folder_{tabname}')
+
+                if tabname != "extras":
+                    save = gr.Button('Save', elem_id=f'save_{tabname}')
+                    save_zip = gr.Button('Zip', elem_id=f'save_zip_{tabname}')
+
+                buttons = parameters_copypaste.create_buttons(["img2img", "inpaint", "extras"])
+
+            open_folder_button.click(
+                fn=lambda: open_folder(shared.opts.outdir_samples or outdir),
+                inputs=[],
+                outputs=[],
+            )
+
+            if tabname != "extras":
+                with gr.Row():
+                    download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False, elem_id=f'download_files_{tabname}')
+
+                with gr.Group():
+                    html_info = gr.HTML(elem_id=f'html_info_{tabname}')
+                    html_log = gr.HTML(elem_id=f'html_log_{tabname}')
+
+                    generation_info = gr.Textbox(visible=False, elem_id=f'generation_info_{tabname}')
+                    if tabname == 'txt2img' or tabname == 'img2img':
+                        generation_info_button = gr.Button(visible=False, elem_id=f"{tabname}_generation_info_button")
+                        generation_info_button.click(
+                            fn=update_generation_info,
+                            _js="function(x, y, z){ return [x, y, selected_gallery_index()] }",
+                            inputs=[generation_info, html_info, html_info],
+                            outputs=[html_info, html_info],
+                        )
+
+                    save.click(
+                        fn=call_queue.wrap_gradio_call(save_files),
+                        _js="(x, y, z, w) => [x, y, false, selected_gallery_index()]",
+                        inputs=[
+                            generation_info,
+                            result_gallery,
+                            html_info,
+                            html_info,
+                        ],
+                        outputs=[
+                            download_files,
+                            html_log,
+                        ],
+                        show_progress=False,
+                    )
+
+                    save_zip.click(
+                        fn=call_queue.wrap_gradio_call(save_files),
+                        _js="(x, y, z, w) => [x, y, true, selected_gallery_index()]",
+                        inputs=[
+                            generation_info,
+                            result_gallery,
+                            html_info,
+                            html_info,
+                        ],
+                        outputs=[
+                            download_files,
+                            html_log,
+                        ]
+                    )
+
+            else:
+                html_info_x = gr.HTML(elem_id=f'html_info_x_{tabname}')
+                html_info = gr.HTML(elem_id=f'html_info_{tabname}')
+                html_log = gr.HTML(elem_id=f'html_log_{tabname}')
+
+            parameters_copypaste.bind_buttons(buttons, result_gallery, "txt2img" if tabname == "txt2img" else None)
+            return result_gallery, generation_info if tabname != "extras" else html_info_x, html_info, html_log
diff --git a/modules/ui_components.py b/modules/ui_components.py
index 989cc87b..9aec3097 100644
--- a/modules/ui_components.py
+++ b/modules/ui_components.py
@@ -1,5 +1,3 @@
-import html
-
 import gradio as gr
 
 
@@ -50,7 +48,3 @@ class FormColorPicker(gr.ColorPicker, gr.components.FormComponent):
     def get_block_name(self):
         return "colorpicker"
 
-
-def plaintext_to_html(text):
-    text = "<p>" + "<br>\n".join([f"{html.escape(x)}" for x in text.split('\n')]) + "</p>"
-    return text
diff --git a/modules/ui_postprocessing.py b/modules/ui_postprocessing.py
new file mode 100644
index 00000000..b418d955
--- /dev/null
+++ b/modules/ui_postprocessing.py
@@ -0,0 +1,57 @@
+import gradio as gr
+from modules import scripts_postprocessing, scripts, shared, gfpgan_model, codeformer_model, ui_common, postprocessing, call_queue
+import modules.generation_parameters_copypaste as parameters_copypaste
+
+
+def create_ui():
+    tab_index = gr.State(value=0)
+
+    with gr.Row().style(equal_height=False, variant='compact'):
+        with gr.Column(variant='compact'):
+            with gr.Tabs(elem_id="mode_extras"):
+                with gr.TabItem('Single Image', elem_id="extras_single_tab") as tab_single:
+                    extras_image = gr.Image(label="Source", source="upload", interactive=True, type="pil", elem_id="extras_image")
+
+                with gr.TabItem('Batch Process', elem_id="extras_batch_process_tab") as tab_batch:
+                    image_batch = gr.File(label="Batch Process", file_count="multiple", interactive=True, type="file", elem_id="extras_image_batch")
+
+                with gr.TabItem('Batch from Directory', elem_id="extras_batch_directory_tab") as tab_batch_dir:
+                    extras_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, placeholder="A directory on the same machine where the server is running.", elem_id="extras_batch_input_dir")
+                    extras_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, placeholder="Leave blank to save images to the default path.", elem_id="extras_batch_output_dir")
+                    show_extras_results = gr.Checkbox(label='Show result images', value=True, elem_id="extras_show_extras_results")
+
+            submit = gr.Button('Generate', elem_id="extras_generate", variant='primary')
+
+            script_inputs = scripts.scripts_postproc.setup_ui()
+
+        with gr.Column():
+            result_images, html_info_x, html_info, html_log = ui_common.create_output_panel("extras", shared.opts.outdir_extras_samples)
+
+    tab_single.select(fn=lambda: 0, inputs=[], outputs=[tab_index])
+    tab_batch.select(fn=lambda: 1, inputs=[], outputs=[tab_index])
+    tab_batch_dir.select(fn=lambda: 2, inputs=[], outputs=[tab_index])
+
+    submit.click(
+        fn=call_queue.wrap_gradio_gpu_call(postprocessing.run_postprocessing, extra_outputs=[None, '']),
+        inputs=[
+            tab_index,
+            extras_image,
+            image_batch,
+            extras_batch_input_dir,
+            extras_batch_output_dir,
+            show_extras_results,
+            *script_inputs
+        ],
+        outputs=[
+            result_images,
+            html_info_x,
+            html_info,
+        ]
+    )
+
+    parameters_copypaste.add_paste_fields("extras", extras_image, None)
+
+    extras_image.change(
+        fn=scripts.scripts_postproc.image_changed,
+        inputs=[], outputs=[]
+    )
diff --git a/scripts/postprocessing_codeformer.py b/scripts/postprocessing_codeformer.py
new file mode 100644
index 00000000..a7d80d40
--- /dev/null
+++ b/scripts/postprocessing_codeformer.py
@@ -0,0 +1,36 @@
+from PIL import Image
+import numpy as np
+
+from modules import scripts_postprocessing, codeformer_model
+import gradio as gr
+
+from modules.ui_components import FormRow
+
+
+class ScriptPostprocessingCodeFormer(scripts_postprocessing.ScriptPostprocessing):
+    name = "CodeFormer"
+    order = 3000
+
+    def ui(self):
+        with FormRow():
+            codeformer_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer visibility", value=0, elem_id="extras_codeformer_visibility")
+            codeformer_weight = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer weight (0 = maximum effect, 1 = minimum effect)", value=0, elem_id="extras_codeformer_weight")
+
+        return {
+            "codeformer_visibility": codeformer_visibility,
+            "codeformer_weight": codeformer_weight,
+        }
+
+    def process(self, pp: scripts_postprocessing.PostprocessedImage, codeformer_visibility, codeformer_weight):
+        if codeformer_visibility == 0:
+            return
+
+        restored_img = codeformer_model.codeformer.restore(np.array(pp.image, dtype=np.uint8), w=codeformer_weight)
+        res = Image.fromarray(restored_img)
+
+        if codeformer_visibility < 1.0:
+            res = Image.blend(pp.image, res, codeformer_visibility)
+
+        pp.image = res
+        pp.info["CodeFormer visibility"] = round(codeformer_visibility, 3)
+        pp.info["CodeFormer weight"] = round(codeformer_weight, 3)
diff --git a/scripts/postprocessing_gfpgan.py b/scripts/postprocessing_gfpgan.py
new file mode 100644
index 00000000..d854f3f7
--- /dev/null
+++ b/scripts/postprocessing_gfpgan.py
@@ -0,0 +1,33 @@
+from PIL import Image
+import numpy as np
+
+from modules import scripts_postprocessing, gfpgan_model
+import gradio as gr
+
+from modules.ui_components import FormRow
+
+
+class ScriptPostprocessingGfpGan(scripts_postprocessing.ScriptPostprocessing):
+    name = "GFPGAN"
+    order = 2000
+
+    def ui(self):
+        with FormRow():
+            gfpgan_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="GFPGAN visibility", value=0, elem_id="extras_gfpgan_visibility")
+
+        return {
+            "gfpgan_visibility": gfpgan_visibility,
+        }
+
+    def process(self, pp: scripts_postprocessing.PostprocessedImage, gfpgan_visibility):
+        if gfpgan_visibility == 0:
+            return
+
+        restored_img = gfpgan_model.gfpgan_fix_faces(np.array(pp.image, dtype=np.uint8))
+        res = Image.fromarray(restored_img)
+
+        if gfpgan_visibility < 1.0:
+            res = Image.blend(pp.image, res, gfpgan_visibility)
+
+        pp.image = res
+        pp.info["GFPGAN visibility"] = round(gfpgan_visibility, 3)
diff --git a/scripts/postprocessing_upscale.py b/scripts/postprocessing_upscale.py
new file mode 100644
index 00000000..095d29b2
--- /dev/null
+++ b/scripts/postprocessing_upscale.py
@@ -0,0 +1,106 @@
+from PIL import Image
+import numpy as np
+
+from modules import scripts_postprocessing, shared
+import gradio as gr
+
+from modules.ui_components import FormRow
+
+
+upscale_cache = {}
+
+
+class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing):
+    name = "Upscale"
+    order = 1000
+
+    def ui(self):
+        selected_tab = gr.State(value=0)
+
+        with gr.Tabs(elem_id="extras_resize_mode"):
+            with gr.TabItem('Scale by', elem_id="extras_scale_by_tab") as tab_scale_by:
+                upscaling_resize = gr.Slider(minimum=1.0, maximum=8.0, step=0.05, label="Resize", value=4, elem_id="extras_upscaling_resize")
+
+            with gr.TabItem('Scale to', elem_id="extras_scale_to_tab") as tab_scale_to:
+                with FormRow():
+                    upscaling_resize_w = gr.Number(label="Width", value=512, precision=0, elem_id="extras_upscaling_resize_w")
+                    upscaling_resize_h = gr.Number(label="Height", value=512, precision=0, elem_id="extras_upscaling_resize_h")
+                    upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop")
+
+        with FormRow():
+            extras_upscaler_1 = gr.Dropdown(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name)
+
+        with FormRow():
+            extras_upscaler_2 = gr.Dropdown(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name)
+            extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=0.0, elem_id="extras_upscaler_2_visibility")
+
+        tab_scale_by.select(fn=lambda: 0, inputs=[], outputs=[selected_tab])
+        tab_scale_to.select(fn=lambda: 1, inputs=[], outputs=[selected_tab])
+
+        return {
+            "upscale_mode": selected_tab,
+            "upscale_by": upscaling_resize,
+            "upscale_to_width": upscaling_resize_w,
+            "upscale_to_height": upscaling_resize_h,
+            "upscale_crop": upscaling_crop,
+            "upscaler_1_name": extras_upscaler_1,
+            "upscaler_2_name": extras_upscaler_2,
+            "upscaler_2_visibility": extras_upscaler_2_visibility,
+        }
+
+    def upscale(self, image, info, upscaler, upscale_mode, upscale_by,  upscale_to_width, upscale_to_height, upscale_crop):
+        if upscale_mode == 1:
+            upscale_by = max(upscale_to_width/image.width, upscale_to_height/image.height)
+            info["Postprocess upscale to"] = f"{upscale_to_width}x{upscale_to_height}"
+        else:
+            info["Postprocess upscale by"] = upscale_by
+
+        cache_key = (hash(np.array(image.getdata()).tobytes()), upscaler.name, upscale_mode, upscale_by,  upscale_to_width, upscale_to_height, upscale_crop)
+        cached_image = upscale_cache.pop(cache_key, None)
+
+        if cached_image is not None:
+            image = cached_image
+        else:
+            image = upscaler.scaler.upscale(image, upscale_by, upscaler.data_path)
+
+        upscale_cache[cache_key] = image
+        if len(upscale_cache) > shared.opts.upscaling_max_images_in_cache:
+            upscale_cache.pop(next(iter(upscale_cache), None), None)
+
+        if upscale_mode == 1 and upscale_crop:
+            cropped = Image.new("RGB", (upscale_to_width, upscale_to_height))
+            cropped.paste(image, box=(upscale_to_width // 2 - image.width // 2, upscale_to_height // 2 - image.height // 2))
+            image = cropped
+            info["Postprocess crop to"] = f"{image.width}x{image.height}"
+
+        return image
+
+    def process(self, pp: scripts_postprocessing.PostprocessedImage, upscale_mode=1, upscale_by=2.0, upscale_to_width=None, upscale_to_height=None, upscale_crop=False, upscaler_1_name=None, upscaler_2_name=None, upscaler_2_visibility=0.0):
+        if upscaler_1_name == "None":
+            upscaler_1_name = None
+
+        upscaler1 = next(iter([x for x in shared.sd_upscalers if x.name == upscaler_1_name]), None)
+        assert upscaler1 or (upscaler_1_name is None), f'could not find upscaler named {upscaler_1_name}'
+
+        if not upscaler1:
+            return
+
+        if upscaler_2_name == "None":
+            upscaler_2_name = None
+
+        upscaler2 = next(iter([x for x in shared.sd_upscalers if x.name == upscaler_2_name and x.name != "None"]), None)
+        assert upscaler2 or (upscaler_2_name is None), f'could not find upscaler named {upscaler_2_name}'
+
+        upscaled_image = self.upscale(pp.image, pp.info, upscaler1, upscale_mode, upscale_by, upscale_to_width, upscale_to_height, upscale_crop)
+        pp.info[f"Postprocess upscaler"] = upscaler1.name
+
+        if upscaler2 and upscaler_2_visibility > 0:
+            second_upscale = self.upscale(pp.image, pp.info, upscaler2, upscale_mode, upscale_by, upscale_to_width, upscale_to_height, upscale_crop)
+            upscaled_image = Image.blend(upscaled_image, second_upscale, upscaler_2_visibility)
+
+            pp.info[f"Postprocess upscaler 2"] = upscaler2.name
+
+        pp.image = upscaled_image
+
+    def image_changed(self):
+        upscale_cache.clear()
-- 
cgit v1.2.3


From 669dbd9725b3a285503e093a75c0dfa332073d8a Mon Sep 17 00:00:00 2001
From: Shondoit <shondoit@gmail.com>
Date: Mon, 23 Jan 2023 09:54:42 +0100
Subject: Fix dark mode

Fixes #7048

Co-Authored-By: J.J. Tolton <jjtolton@gmail.com>
---
 modules/ui.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index eb4b7e6b..43bcb7e5 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1942,11 +1942,11 @@ def reload_javascript():
     if cmd_opts.theme is not None:
         inline += f"set_theme('{cmd_opts.theme}');"
 
-    head += f'<script type="text/javascript">{inline}</script>\n'
-
     for script in modules.scripts.list_scripts("javascript", ".js"):
         head += f'<script type="text/javascript" src="file={script.path}"></script>\n'
 
+    head += f'<script type="text/javascript">{inline}</script>\n'
+
     def template_response(*args, **kwargs):
         res = shared.GradioTemplateResponseOriginal(*args, **kwargs)
         res.body = res.body.replace(b'</head>', f'{head}</head>'.encode("utf8"))
-- 
cgit v1.2.3


From fabdae089e476c66eba3b0562e4e1881891804b2 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 23 Jan 2023 14:42:49 +0300
Subject: add missing import to previous commit

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

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index 8cb8e613..6b5dfd61 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -41,6 +41,7 @@ from modules.sd_samplers import samplers, samplers_for_img2img
 from modules.textual_inversion import textual_inversion
 import modules.hypernetworks.ui
 from modules.generation_parameters_copypaste import image_from_url_text
+import modules.extras
 
 warnings.filterwarnings("default" if opts.show_warnings else "ignore", category=UserWarning)
 
-- 
cgit v1.2.3


From 194cbd065e4644e986889b78a5a949e075b610e8 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Mon, 23 Jan 2023 15:50:32 +0300
Subject: fix open directory button failing

---
 modules/ui.py        | 1 -
 modules/ui_common.py | 2 +-
 2 files changed, 1 insertion(+), 2 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index 94d4a80a..85ae62c7 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -5,7 +5,6 @@ import mimetypes
 import os
 import platform
 import random
-import subprocess as sp
 import sys
 import tempfile
 import time
diff --git a/modules/ui_common.py b/modules/ui_common.py
index 8ce75b8c..9405ac1f 100644
--- a/modules/ui_common.py
+++ b/modules/ui_common.py
@@ -5,7 +5,7 @@ import platform
 import sys
 
 import gradio as gr
-import scipy as sp
+import subprocess as sp
 
 from modules import call_queue, shared
 from modules.generation_parameters_copypaste import image_from_url_text
-- 
cgit v1.2.3


From 5eee2ac39863f9e44591b50d0710dd2615416a13 Mon Sep 17 00:00:00 2001
From: Max Audron <audron@cocaine.farm>
Date: Wed, 25 Jan 2023 17:15:42 +0100
Subject: add data-dir flag and set all user data directories based on it

---
 modules/extensions.py                      |  2 +-
 modules/generation_parameters_copypaste.py |  4 ++--
 modules/gfpgan_model.py                    |  5 ++---
 modules/hashes.py                          |  4 +++-
 modules/interrogate.py                     |  2 +-
 modules/paths.py                           | 10 +++++++++-
 modules/processing.py                      |  3 ++-
 modules/sd_models.py                       |  6 +++---
 modules/sd_vae.py                          |  5 ++---
 modules/shared.py                          | 11 ++++++-----
 modules/textual_inversion/preprocess.py    |  5 ++---
 modules/ui.py                              |  6 +++---
 modules/ui_extensions.py                   |  2 +-
 modules/upscaler.py                        |  5 ++---
 14 files changed, 39 insertions(+), 31 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/extensions.py b/modules/extensions.py
index b522125c..92ee8144 100644
--- a/modules/extensions.py
+++ b/modules/extensions.py
@@ -7,7 +7,7 @@ import git
 from modules import paths, shared
 
 extensions = []
-extensions_dir = os.path.join(paths.script_path, "extensions")
+extensions_dir = os.path.join(paths.data_path, "extensions")
 extensions_builtin_dir = os.path.join(paths.script_path, "extensions-builtin")
 
 
diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py
index 46e12dc6..35f72808 100644
--- a/modules/generation_parameters_copypaste.py
+++ b/modules/generation_parameters_copypaste.py
@@ -6,7 +6,7 @@ import re
 from pathlib import Path
 
 import gradio as gr
-from modules.shared import script_path
+from modules.paths import data_path, script_path
 from modules import shared, ui_tempdir, script_callbacks
 import tempfile
 from PIL import Image
@@ -289,7 +289,7 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
 def connect_paste(button, paste_fields, input_comp, jsfunc=None):
     def paste_func(prompt):
         if not prompt and not shared.cmd_opts.hide_ui_dir_config:
-            filename = os.path.join(script_path, "params.txt")
+            filename = os.path.join(data_path, "params.txt")
             if os.path.exists(filename):
                 with open(filename, "r", encoding="utf8") as file:
                     prompt = file.read()
diff --git a/modules/gfpgan_model.py b/modules/gfpgan_model.py
index 1e2dbc32..fbe6215a 100644
--- a/modules/gfpgan_model.py
+++ b/modules/gfpgan_model.py
@@ -6,12 +6,11 @@ import facexlib
 import gfpgan
 
 import modules.face_restoration
-from modules import shared, devices, modelloader
-from modules.paths import models_path
+from modules import paths, shared, devices, modelloader
 
 model_dir = "GFPGAN"
 user_path = None
-model_path = os.path.join(models_path, model_dir)
+model_path = os.path.join(paths.models_path, model_dir)
 model_url = "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth"
 have_gfpgan = False
 loaded_gfpgan_model = None
diff --git a/modules/hashes.py b/modules/hashes.py
index b85a7580..819362a3 100644
--- a/modules/hashes.py
+++ b/modules/hashes.py
@@ -4,8 +4,10 @@ import os.path
 
 import filelock
 
+from modules.paths import data_path
 
-cache_filename = "cache.json"
+
+cache_filename = os.path.join(data_path, "cache.json")
 cache_data = None
 
 
diff --git a/modules/interrogate.py b/modules/interrogate.py
index c72ff694..cbb80683 100644
--- a/modules/interrogate.py
+++ b/modules/interrogate.py
@@ -12,7 +12,7 @@ from torchvision import transforms
 from torchvision.transforms.functional import InterpolationMode
 
 import modules.shared as shared
-from modules import devices, paths, lowvram, modelloader, errors
+from modules import devices, paths, shared, lowvram, modelloader, errors
 
 blip_image_eval_size = 384
 clip_model_name = 'ViT-L/14'
diff --git a/modules/paths.py b/modules/paths.py
index 20b3e4d8..08e6f9b9 100644
--- a/modules/paths.py
+++ b/modules/paths.py
@@ -4,7 +4,15 @@ import sys
 import modules.safe
 
 script_path = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
-models_path = os.path.join(script_path, "models")
+
+# Parse the --data-dir flag first so we can use it as a base for our other argument default values
+parser = argparse.ArgumentParser()
+parser.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.dirname(os.path.realpath(__file__))), help="base path where all user data is stored",)
+cmd_opts_pre = parser.parse_known_args()[0]
+data_path = cmd_opts_pre.data_dir
+models_path = os.path.join(data_path, "models")
+
+# data_path = cmd_opts_pre.data
 sys.path.insert(0, script_path)
 
 # search for directory of stable diffusion in following places
diff --git a/modules/processing.py b/modules/processing.py
index 262806a1..5072fc40 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -17,6 +17,7 @@ from modules import devices, prompt_parser, masking, sd_samplers, lowvram, gener
 from modules.sd_hijack import model_hijack
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
+import modules.paths as paths
 import modules.face_restoration
 import modules.images as images
 import modules.styles
@@ -584,7 +585,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
             if not p.disable_extra_networks:
                 extra_networks.activate(p, extra_network_data)
 
-        with open(os.path.join(shared.script_path, "params.txt"), "w", encoding="utf8") as file:
+        with open(os.path.join(paths.data_path, "params.txt"), "w", encoding="utf8") as file:
             processed = Processed(p, [], p.seed, "")
             file.write(processed.infotext(p, 0))
 
diff --git a/modules/sd_models.py b/modules/sd_models.py
index 37dad18d..b2d48a51 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -12,13 +12,13 @@ import ldm.modules.midas as midas
 
 from ldm.util import instantiate_from_config
 
-from modules import shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config
+from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config
 from modules.paths import models_path
 from modules.sd_hijack_inpainting import do_inpainting_hijack
 from modules.timer import Timer
 
 model_dir = "Stable-diffusion"
-model_path = os.path.abspath(os.path.join(models_path, model_dir))
+model_path = os.path.abspath(os.path.join(paths.models_path, model_dir))
 
 checkpoints_list = {}
 checkpoint_alisases = {}
@@ -307,7 +307,7 @@ def enable_midas_autodownload():
     location automatically.
     """
 
-    midas_path = os.path.join(models_path, 'midas')
+    midas_path = os.path.join(paths.models_path, 'midas')
 
     # stable-diffusion-stability-ai hard-codes the midas model path to
     # a location that differs from where other scripts using this model look.
diff --git a/modules/sd_vae.py b/modules/sd_vae.py
index 4ce238b8..9b00f76e 100644
--- a/modules/sd_vae.py
+++ b/modules/sd_vae.py
@@ -3,13 +3,12 @@ import safetensors.torch
 import os
 import collections
 from collections import namedtuple
-from modules import shared, devices, script_callbacks, sd_models
-from modules.paths import models_path
+from modules import paths, shared, devices, script_callbacks, sd_models
 import glob
 from copy import deepcopy
 
 
-vae_path = os.path.abspath(os.path.join(models_path, "VAE"))
+vae_path = os.path.abspath(os.path.join(paths.models_path, "VAE"))
 vae_ignore_keys = {"model_ema.decay", "model_ema.num_updates"}
 vae_dict = {}
 
diff --git a/modules/shared.py b/modules/shared.py
index 14be993d..474fcc42 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -14,7 +14,7 @@ import modules.memmon
 import modules.styles
 import modules.devices as devices
 from modules import localization, extensions, script_loading, errors, ui_components, shared_items
-from modules.paths import models_path, script_path
+from modules.paths import models_path, script_path, data_path
 
 
 demo = None
@@ -25,6 +25,7 @@ sd_model_file = os.path.join(script_path, 'model.ckpt')
 default_sd_model_file = sd_model_file
 
 parser = argparse.ArgumentParser()
+parser.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.dirname(os.path.realpath(__file__))), help="base path where all user data is stored",)
 parser.add_argument("--config", type=str, default=sd_default_config, help="path to config which constructs model",)
 parser.add_argument("--ckpt", type=str, default=sd_model_file, help="path to checkpoint of stable diffusion model; if specified, this checkpoint will be added to the list of checkpoints and loaded",)
 parser.add_argument("--ckpt-dir", type=str, default=None, help="Path to directory with stable diffusion checkpoints")
@@ -35,7 +36,7 @@ parser.add_argument("--no-half", action='store_true', help="do not switch the mo
 parser.add_argument("--no-half-vae", action='store_true', help="do not switch the VAE model to 16-bit floats")
 parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware acceleration in browser)")
 parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI")
-parser.add_argument("--embeddings-dir", type=str, default=os.path.join(script_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)")
+parser.add_argument("--embeddings-dir", type=str, default=os.path.join(data_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)")
 parser.add_argument("--textual-inversion-templates-dir", type=str, default=os.path.join(script_path, 'textual_inversion_templates'), help="directory with textual inversion templates")
 parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_path, 'hypernetworks'), help="hypernetwork directory")
 parser.add_argument("--localizations-dir", type=str, default=os.path.join(script_path, 'localizations'), help="localizations directory")
@@ -74,16 +75,16 @@ parser.add_argument("--use-cpu", nargs='+', help="use CPU as torch device for sp
 parser.add_argument("--listen", action='store_true', help="launch gradio with 0.0.0.0 as server name, allowing to respond to network requests")
 parser.add_argument("--port", type=int, help="launch gradio with given server port, you need root/admin rights for ports < 1024, defaults to 7860 if available", default=None)
 parser.add_argument("--show-negative-prompt", action='store_true', help="does not do anything", default=False)
-parser.add_argument("--ui-config-file", type=str, help="filename to use for ui configuration", default=os.path.join(script_path, 'ui-config.json'))
+parser.add_argument("--ui-config-file", type=str, help="filename to use for ui configuration", default=os.path.join(data_path, 'ui-config.json'))
 parser.add_argument("--hide-ui-dir-config", action='store_true', help="hide directory configuration from webui", default=False)
 parser.add_argument("--freeze-settings", action='store_true', help="disable editing settings", default=False)
-parser.add_argument("--ui-settings-file", type=str, help="filename to use for ui settings", default=os.path.join(script_path, 'config.json'))
+parser.add_argument("--ui-settings-file", type=str, help="filename to use for ui settings", default=os.path.join(data_path, 'config.json'))
 parser.add_argument("--gradio-debug",  action='store_true', help="launch gradio with --debug option")
 parser.add_argument("--gradio-auth", type=str, help='set gradio authentication like "username:password"; or comma-delimit multiple like "u1:p1,u2:p2,u3:p3"', default=None)
 parser.add_argument("--gradio-img2img-tool", type=str, help='does not do anything')
 parser.add_argument("--gradio-inpaint-tool", type=str, help="does not do anything")
 parser.add_argument("--opt-channelslast", action='store_true', help="change memory type for stable diffusion to channels last")
-parser.add_argument("--styles-file", type=str, help="filename to use for styles", default=os.path.join(script_path, 'styles.csv'))
+parser.add_argument("--styles-file", type=str, help="filename to use for styles", default=os.path.join(data_path, 'styles.csv'))
 parser.add_argument("--autolaunch", action='store_true', help="open the webui URL in the system's default browser upon launch", default=False)
 parser.add_argument("--theme", type=str, help="launches the UI with light or dark theme", default=None)
 parser.add_argument("--use-textbox-seed", action='store_true', help="use textbox for seeds in UI (no up/down, but possible to input long seeds)", default=False)
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index c0ac11d3..2239cb84 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -6,8 +6,7 @@ import sys
 import tqdm
 import time
 
-from modules import shared, images, deepbooru
-from modules.paths import models_path
+from modules import paths, shared, images, deepbooru
 from modules.shared import opts, cmd_opts
 from modules.textual_inversion import autocrop
 
@@ -199,7 +198,7 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre
 
             dnn_model_path = None
             try:
-                dnn_model_path = autocrop.download_and_cache_models(os.path.join(models_path, "opencv"))
+                dnn_model_path = autocrop.download_and_cache_models(os.path.join(paths.models_path, "opencv"))
             except Exception as e:
                 print("Unable to load face detection model for auto crop selection. Falling back to lower quality haar method.", e)
 
diff --git a/modules/ui.py b/modules/ui.py
index 85ae62c7..0117df3e 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -21,7 +21,7 @@ from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_grad
 
 from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, postprocessing, ui_components, ui_common, ui_postprocessing
 from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
-from modules.paths import script_path
+from modules.paths import script_path, data_path
 
 from modules.shared import opts, cmd_opts, restricted_opts
 
@@ -1497,8 +1497,8 @@ def create_ui():
         with open(cssfile, "r", encoding="utf8") as file:
             css += file.read() + "\n"
 
-    if os.path.exists(os.path.join(script_path, "user.css")):
-        with open(os.path.join(script_path, "user.css"), "r", encoding="utf8") as file:
+    if os.path.exists(os.path.join(data_path, "user.css")):
+        with open(os.path.join(data_path, "user.css"), "r", encoding="utf8") as file:
             css += file.read() + "\n"
 
     if not cmd_opts.no_progressbar_hiding:
diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py
index 742e745e..66a41865 100644
--- a/modules/ui_extensions.py
+++ b/modules/ui_extensions.py
@@ -132,7 +132,7 @@ def install_extension_from_url(dirname, url):
     normalized_url = normalize_git_url(url)
     assert len([x for x in extensions.extensions if normalize_git_url(x.remote) == normalized_url]) == 0, 'Extension with this URL is already installed'
 
-    tmpdir = os.path.join(paths.script_path, "tmp", dirname)
+    tmpdir = os.path.join(paths.data_path, "tmp", dirname)
 
     try:
         shutil.rmtree(tmpdir, True)
diff --git a/modules/upscaler.py b/modules/upscaler.py
index a5bf5acb..e2eaa730 100644
--- a/modules/upscaler.py
+++ b/modules/upscaler.py
@@ -11,7 +11,6 @@ from modules import modelloader, shared
 
 LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS)
 NEAREST = (Image.Resampling.NEAREST if hasattr(Image, 'Resampling') else Image.NEAREST)
-from modules.paths import models_path
 
 
 class Upscaler:
@@ -39,7 +38,7 @@ class Upscaler:
         self.mod_scale = None
 
         if self.model_path is None and self.name:
-            self.model_path = os.path.join(models_path, self.name)
+            self.model_path = os.path.join(shared.models_path, self.name)
         if self.model_path and create_dirs:
             os.makedirs(self.model_path, exist_ok=True)
 
@@ -143,4 +142,4 @@ class UpscalerNearest(Upscaler):
     def __init__(self, dirname=None):
         super().__init__(False)
         self.name = "Nearest"
-        self.scalers = [UpscalerData("Nearest", None, self)]
\ No newline at end of file
+        self.scalers = [UpscalerData("Nearest", None, self)]
-- 
cgit v1.2.3


From eafaf14167cf574ad0f918c10f60ef86aea9cd20 Mon Sep 17 00:00:00 2001
From: Gazzoo-byte <73721238+Gazzoo-byte@users.noreply.github.com>
Date: Fri, 27 Jan 2023 18:34:41 +0000
Subject: Add button to switch width and height

Adds a button to switch width and height, allowing quick and easy switching between landscape and portrait.
---
 modules/ui.py | 11 +++++++++++
 1 file changed, 11 insertions(+)

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index 85ae62c7..fb0e4d5c 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -91,6 +91,13 @@ save_style_symbol = '\U0001f4be'  # 💾
 apply_style_symbol = '\U0001f4cb'  # 📋
 clear_prompt_symbol = '\U0001F5D1'  # 🗑️
 extra_networks_symbol = '\U0001F3B4'  # 🎴
+switch_values_symbol = '\U000021C5' # ⇅
+
+def switch_width_and_height(width, height):
+    width_temp = width
+    width = height
+    height = width_temp
+    return width, height
 
 
 def plaintext_to_html(text):
@@ -466,6 +473,7 @@ def create_ui():
                                 height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="txt2img_height")
 
                             if opts.dimensions_and_batch_together:
+                                res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="txt2img_res_switch_btn")
                                 with gr.Column(elem_id="txt2img_column_batch"):
                                     batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
                                     batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
@@ -566,6 +574,7 @@ def create_ui():
 
             txt2img_prompt.submit(**txt2img_args)
             submit.click(**txt2img_args)
+            res_switch_btn.click(switch_width_and_height, inputs=[width, height], outputs=[width, height])
 
             txt_prompt_img.change(
                 fn=modules.images.image_data,
@@ -728,6 +737,7 @@ def create_ui():
                                 height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
 
                             if opts.dimensions_and_batch_together:
+                                res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="img2img_res_switch_btn")
                                 with gr.Column(elem_id="img2img_column_batch"):
                                     batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
                                     batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")
@@ -865,6 +875,7 @@ def create_ui():
 
             img2img_prompt.submit(**img2img_args)
             submit.click(**img2img_args)
+            res_switch_btn.click(switch_width_and_height, inputs=[width, height], outputs=[width, height])
 
             img2img_interrogate.click(
                 fn=lambda *args: process_interrogate(interrogate, *args),
-- 
cgit v1.2.3


From 2aac1d97782b486f3a4a5209cf399dcdcb7bbb4d Mon Sep 17 00:00:00 2001
From: Andrii Skaliuk <askaliuk@users.noreply.github.com>
Date: Fri, 27 Jan 2023 17:32:31 -0800
Subject: Basic inpainting batch support

Modifies batch UI to add optional inpainting support
---
 modules/img2img.py | 20 +++++++++++++++++---
 modules/ui.py      |  9 ++++++++-
 2 files changed, 25 insertions(+), 4 deletions(-)

(limited to 'modules/ui.py')

diff --git a/modules/img2img.py b/modules/img2img.py
index 2168c8e2..fe9447c7 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -16,11 +16,16 @@ import modules.images as images
 import modules.scripts
 
 
-def process_batch(p, input_dir, output_dir, args):
+def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args):
     processing.fix_seed(p)
 
     images = shared.listfiles(input_dir)
 
+    inpaint_masks = shared.listfiles(inpaint_mask_dir)
+    is_inpaint_batch = inpaint_mask_dir and len(inpaint_masks) > 0
+    if is_inpaint_batch:
+        print(f"\nInpaint batch is enabled. {len(inpaint_masks)} masks found.")
+
     print(f"Will process {len(images)} images, creating {p.n_iter * p.batch_size} new images for each.")
 
     save_normally = output_dir == ''
@@ -43,6 +48,15 @@ def process_batch(p, input_dir, output_dir, args):
         img = ImageOps.exif_transpose(img)
         p.init_images = [img] * p.batch_size
 
+        if is_inpaint_batch:
+            # try to find corresponding mask for an image using simple filename matching
+            mask_image_path = os.path.join(inpaint_mask_dir, os.path.basename(image))
+            # if not found use first one ("same mask for all images" use-case)
+            if not mask_image_path in inpaint_masks:
+                mask_image_path = inpaint_masks[0]
+            mask_image = Image.open(mask_image_path)
+            p.image_mask = mask_image
+
         proc = modules.scripts.scripts_img2img.run(p, *args)
         if proc is None:
             proc = process_images(p)
@@ -59,7 +73,7 @@ def process_batch(p, input_dir, output_dir, args):
                 processed_image.save(os.path.join(output_dir, filename))
 
 
-def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, *args):
+def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, *args):
     is_batch = mode == 5
 
     if mode == 0:  # img2img
@@ -139,7 +153,7 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s
     if is_batch:
         assert not shared.cmd_opts.hide_ui_dir_config, "Launched with --hide-ui-dir-config, batch img2img disabled"
 
-        process_batch(p, img2img_batch_input_dir, img2img_batch_output_dir, args)
+        process_batch(p, img2img_batch_input_dir, img2img_batch_output_dir, img2img_batch_inpaint_mask_dir, args)
 
         processed = Processed(p, [], p.seed, "")
     else:
diff --git a/modules/ui.py b/modules/ui.py
index 85ae62c7..fddb9177 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -691,9 +691,15 @@ def create_ui():
 
                     with gr.TabItem('Batch', id='batch', elem_id="img2img_batch_tab") as tab_batch:
                         hidden = '<br>Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else ''
-                        gr.HTML(f"<p style='padding-bottom: 1em;' class=\"text-gray-500\">Process images in a directory on the same machine where the server is running.<br>Use an empty output directory to save pictures normally instead of writing to the output directory.{hidden}</p>")
+                        gr.HTML(
+                            f"<p style='padding-bottom: 1em;' class=\"text-gray-500\">Process images in a directory on the same machine where the server is running." +
+                            f"<br>Use an empty output directory to save pictures normally instead of writing to the output directory." +
+                            f"<br>Add inpaint batch mask directory to enable inpaint batch processing."
+                            f"{hidden}</p>"
+                        )
                         img2img_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, elem_id="img2img_batch_input_dir")
                         img2img_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, elem_id="img2img_batch_output_dir")
+                        img2img_batch_inpaint_mask_dir = gr.Textbox(label="Inpaint batch mask directory (required for inpaint batch processing only)", **shared.hide_dirs, elem_id="img2img_batch_inpaint_mask_dir")
 
                 def copy_image(img):
                     if isinstance(img, dict) and 'image' in img:
@@ -838,6 +844,7 @@ def create_ui():
                     inpainting_mask_invert,
                     img2img_batch_input_dir,
                     img2img_batch_output_dir,
+                    img2img_batch_inpaint_mask_dir
                 ] + custom_inputs,
                 outputs=[
                     img2img_gallery,
-- 
cgit v1.2.3


From 0834d4ce374225131e025540220c727e352a3e43 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 28 Jan 2023 08:41:15 +0300
Subject: simplify #7284

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

(limited to 'modules/ui.py')

diff --git a/modules/ui.py b/modules/ui.py
index 3c0a4050..ca2c1eb6 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -93,12 +93,6 @@ clear_prompt_symbol = '\U0001F5D1'  # 🗑️
 extra_networks_symbol = '\U0001F3B4'  # 🎴
 switch_values_symbol = '\U000021C5' # ⇅
 
-def switch_width_and_height(width, height):
-    width_temp = width
-    width = height
-    height = width_temp
-    return width, height
-
 
 def plaintext_to_html(text):
     return ui_common.plaintext_to_html(text)
@@ -574,7 +568,8 @@ def create_ui():
 
             txt2img_prompt.submit(**txt2img_args)
             submit.click(**txt2img_args)
-            res_switch_btn.click(switch_width_and_height, inputs=[width, height], outputs=[width, height])
+
+            res_switch_btn.click(lambda w, h: (h, w), inputs=[width, height], outputs=[width, height])
 
             txt_prompt_img.change(
                 fn=modules.images.image_data,
@@ -882,7 +877,7 @@ def create_ui():
 
             img2img_prompt.submit(**img2img_args)
             submit.click(**img2img_args)
-            res_switch_btn.click(switch_width_and_height, inputs=[width, height], outputs=[width, height])
+            res_switch_btn.click(lambda w, h: (h, w), inputs=[width, height], outputs=[width, height])
 
             img2img_interrogate.click(
                 fn=lambda *args: process_interrogate(interrogate, *args),
-- 
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