From 12c4d5c6b5bf9dd50d0601c36af4f99b65316d58 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 7 Oct 2022 23:22:22 +0300
Subject: [PATCH 01/53] hypernetwork training mk1

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

diff --git a/modules/hypernetwork.py b/modules/hypernetwork.py
deleted file mode 100644
index c7b866829..000000000
--- a/modules/hypernetwork.py
+++ /dev/null
@@ -1,88 +0,0 @@
-import glob
-import os
-import sys
-import traceback
-
-import torch
-
-from ldm.util import default
-from modules import devices, shared
-import torch
-from torch import einsum
-from einops import rearrange, repeat
-
-
-class HypernetworkModule(torch.nn.Module):
-    def __init__(self, dim, state_dict):
-        super().__init__()
-
-        self.linear1 = torch.nn.Linear(dim, dim * 2)
-        self.linear2 = torch.nn.Linear(dim * 2, dim)
-
-        self.load_state_dict(state_dict, strict=True)
-        self.to(devices.device)
-
-    def forward(self, x):
-        return x + (self.linear2(self.linear1(x)))
-
-
-class Hypernetwork:
-    filename = None
-    name = None
-
-    def __init__(self, filename):
-        self.filename = filename
-        self.name = os.path.splitext(os.path.basename(filename))[0]
-        self.layers = {}
-
-        state_dict = torch.load(filename, map_location='cpu')
-        for size, sd in state_dict.items():
-            self.layers[size] = (HypernetworkModule(size, sd[0]), HypernetworkModule(size, sd[1]))
-
-
-def load_hypernetworks(path):
-    res = {}
-
-    for filename in glob.iglob(path + '**/*.pt', recursive=True):
-        try:
-            hn = Hypernetwork(filename)
-            res[hn.name] = hn
-        except Exception:
-            print(f"Error loading hypernetwork {filename}", file=sys.stderr)
-            print(traceback.format_exc(), file=sys.stderr)
-
-    return res
-
-
-def attention_CrossAttention_forward(self, x, context=None, mask=None):
-    h = self.heads
-
-    q = self.to_q(x)
-    context = default(context, x)
-
-    hypernetwork = shared.selected_hypernetwork()
-    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
-
-    if hypernetwork_layers is not None:
-        k = self.to_k(hypernetwork_layers[0](context))
-        v = self.to_v(hypernetwork_layers[1](context))
-    else:
-        k = self.to_k(context)
-        v = self.to_v(context)
-
-    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
-
-    sim = einsum('b i d, b j d -> b i j', q, k) * self.scale
-
-    if mask is not None:
-        mask = rearrange(mask, 'b ... -> b (...)')
-        max_neg_value = -torch.finfo(sim.dtype).max
-        mask = repeat(mask, 'b j -> (b h) () j', h=h)
-        sim.masked_fill_(~mask, max_neg_value)
-
-    # attention, what we cannot get enough of
-    attn = sim.softmax(dim=-1)
-
-    out = einsum('b i j, b j d -> b i d', attn, v)
-    out = rearrange(out, '(b h) n d -> b n (h d)', h=h)
-    return self.to_out(out)
diff --git a/modules/hypernetwork/hypernetwork.py b/modules/hypernetwork/hypernetwork.py
new file mode 100644
index 000000000..a3d6a47ef
--- /dev/null
+++ b/modules/hypernetwork/hypernetwork.py
@@ -0,0 +1,267 @@
+import datetime
+import glob
+import html
+import os
+import sys
+import traceback
+import tqdm
+
+import torch
+
+from ldm.util import default
+from modules import devices, shared, processing, sd_models
+import torch
+from torch import einsum
+from einops import rearrange, repeat
+import modules.textual_inversion.dataset
+
+
+class HypernetworkModule(torch.nn.Module):
+    def __init__(self, dim, state_dict=None):
+        super().__init__()
+
+        self.linear1 = torch.nn.Linear(dim, dim * 2)
+        self.linear2 = torch.nn.Linear(dim * 2, dim)
+
+        if state_dict is not None:
+            self.load_state_dict(state_dict, strict=True)
+        else:
+            self.linear1.weight.data.fill_(0.0001)
+            self.linear1.bias.data.fill_(0.0001)
+            self.linear2.weight.data.fill_(0.0001)
+            self.linear2.bias.data.fill_(0.0001)
+
+        self.to(devices.device)
+
+    def forward(self, x):
+        return x + (self.linear2(self.linear1(x)))
+
+
+class Hypernetwork:
+    filename = None
+    name = None
+
+    def __init__(self, name=None):
+        self.filename = None
+        self.name = name
+        self.layers = {}
+        self.step = 0
+        self.sd_checkpoint = None
+        self.sd_checkpoint_name = None
+
+        for size in [320, 640, 768, 1280]:
+            self.layers[size] = (HypernetworkModule(size), HypernetworkModule(size))
+
+    def weights(self):
+        res = []
+
+        for k, layers in self.layers.items():
+            for layer in layers:
+                layer.train()
+                res += [layer.linear1.weight, layer.linear1.bias, layer.linear2.weight, layer.linear2.bias]
+
+        return res
+
+    def save(self, filename):
+        state_dict = {}
+
+        for k, v in self.layers.items():
+            state_dict[k] = (v[0].state_dict(), v[1].state_dict())
+
+        state_dict['step'] = self.step
+        state_dict['name'] = self.name
+        state_dict['sd_checkpoint'] = self.sd_checkpoint
+        state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name
+
+        torch.save(state_dict, filename)
+
+    def load(self, filename):
+        self.filename = filename
+        if self.name is None:
+            self.name = os.path.splitext(os.path.basename(filename))[0]
+
+        state_dict = torch.load(filename, map_location='cpu')
+
+        for size, sd in state_dict.items():
+            if type(size) == int:
+                self.layers[size] = (HypernetworkModule(size, sd[0]), HypernetworkModule(size, sd[1]))
+
+        self.name = state_dict.get('name', self.name)
+        self.step = state_dict.get('step', 0)
+        self.sd_checkpoint = state_dict.get('sd_checkpoint', None)
+        self.sd_checkpoint_name = state_dict.get('sd_checkpoint_name', None)
+
+
+def load_hypernetworks(path):
+    res = {}
+
+    for filename in glob.iglob(path + '**/*.pt', recursive=True):
+        try:
+            hn = Hypernetwork()
+            hn.load(filename)
+            res[hn.name] = hn
+        except Exception:
+            print(f"Error loading hypernetwork {filename}", file=sys.stderr)
+            print(traceback.format_exc(), file=sys.stderr)
+
+    return res
+
+
+def attention_CrossAttention_forward(self, x, context=None, mask=None):
+    h = self.heads
+
+    q = self.to_q(x)
+    context = default(context, x)
+
+    hypernetwork_layers = (shared.hypernetwork.layers if shared.hypernetwork is not None else {}).get(context.shape[2], None)
+
+    if hypernetwork_layers is not None:
+        hypernetwork_k, hypernetwork_v = hypernetwork_layers
+
+        self.hypernetwork_k = hypernetwork_k
+        self.hypernetwork_v = hypernetwork_v
+
+        context_k = hypernetwork_k(context)
+        context_v = hypernetwork_v(context)
+    else:
+        context_k = context
+        context_v = context
+
+    k = self.to_k(context_k)
+    v = self.to_v(context_v)
+
+    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
+
+    sim = einsum('b i d, b j d -> b i j', q, k) * self.scale
+
+    if mask is not None:
+        mask = rearrange(mask, 'b ... -> b (...)')
+        max_neg_value = -torch.finfo(sim.dtype).max
+        mask = repeat(mask, 'b j -> (b h) () j', h=h)
+        sim.masked_fill_(~mask, max_neg_value)
+
+    # attention, what we cannot get enough of
+    attn = sim.softmax(dim=-1)
+
+    out = einsum('b i j, b j d -> b i d', attn, v)
+    out = rearrange(out, '(b h) n d -> b n (h d)', h=h)
+    return self.to_out(out)
+
+
+def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_image_prompt):
+    assert hypernetwork_name, 'embedding not selected'
+
+    shared.hypernetwork = shared.hypernetworks[hypernetwork_name]
+
+    shared.state.textinfo = "Initializing hypernetwork training..."
+    shared.state.job_count = steps
+
+    filename = os.path.join(shared.cmd_opts.hypernetwork_dir, f'{hypernetwork_name}.pt')
+
+    log_directory = os.path.join(log_directory, datetime.datetime.now().strftime("%Y-%m-%d"), hypernetwork_name)
+
+    if save_hypernetwork_every > 0:
+        hypernetwork_dir = os.path.join(log_directory, "hypernetworks")
+        os.makedirs(hypernetwork_dir, exist_ok=True)
+    else:
+        hypernetwork_dir = None
+
+    if create_image_every > 0:
+        images_dir = os.path.join(log_directory, "images")
+        os.makedirs(images_dir, exist_ok=True)
+    else:
+        images_dir = None
+
+    cond_model = shared.sd_model.cond_stage_model
+
+    shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
+    with torch.autocast("cuda"):
+        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, size=512, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file)
+
+    hypernetwork = shared.hypernetworks[hypernetwork_name]
+    weights = hypernetwork.weights()
+    for weight in weights:
+        weight.requires_grad = True
+
+    optimizer = torch.optim.AdamW(weights, lr=learn_rate)
+
+    losses = torch.zeros((32,))
+
+    last_saved_file = "<none>"
+    last_saved_image = "<none>"
+
+    ititial_step = hypernetwork.step or 0
+    if ititial_step > steps:
+        return hypernetwork, filename
+
+    pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step)
+    for i, (x, text) in pbar:
+        hypernetwork.step = i + ititial_step
+
+        if hypernetwork.step > steps:
+            break
+
+        if shared.state.interrupted:
+            break
+
+        with torch.autocast("cuda"):
+            c = cond_model([text])
+
+            x = x.to(devices.device)
+            loss = shared.sd_model(x.unsqueeze(0), c)[0]
+            del x
+
+            losses[hypernetwork.step % losses.shape[0]] = loss.item()
+
+            optimizer.zero_grad()
+            loss.backward()
+            optimizer.step()
+
+        pbar.set_description(f"loss: {losses.mean():.7f}")
+
+        if hypernetwork.step > 0 and hypernetwork_dir is not None and hypernetwork.step % save_hypernetwork_every == 0:
+            last_saved_file = os.path.join(hypernetwork_dir, f'{hypernetwork_name}-{hypernetwork.step}.pt')
+            hypernetwork.save(last_saved_file)
+
+        if hypernetwork.step > 0 and images_dir is not None and hypernetwork.step % create_image_every == 0:
+            last_saved_image = os.path.join(images_dir, f'{hypernetwork_name}-{hypernetwork.step}.png')
+
+            preview_text = text if preview_image_prompt == "" else preview_image_prompt
+
+            p = processing.StableDiffusionProcessingTxt2Img(
+                sd_model=shared.sd_model,
+                prompt=preview_text,
+                steps=20,
+                do_not_save_grid=True,
+                do_not_save_samples=True,
+            )
+
+            processed = processing.process_images(p)
+            image = processed.images[0]
+
+            shared.state.current_image = image
+            image.save(last_saved_image)
+
+            last_saved_image += f", prompt: {preview_text}"
+
+        shared.state.job_no = hypernetwork.step
+
+        shared.state.textinfo = f"""
+<p>
+Loss: {losses.mean():.7f}<br/>
+Step: {hypernetwork.step}<br/>
+Last prompt: {html.escape(text)}<br/>
+Last saved embedding: {html.escape(last_saved_file)}<br/>
+Last saved image: {html.escape(last_saved_image)}<br/>
+</p>
+"""
+
+    checkpoint = sd_models.select_checkpoint()
+
+    hypernetwork.sd_checkpoint = checkpoint.hash
+    hypernetwork.sd_checkpoint_name = checkpoint.model_name
+    hypernetwork.save(filename)
+
+    return hypernetwork, filename
+
+
diff --git a/modules/hypernetwork/ui.py b/modules/hypernetwork/ui.py
new file mode 100644
index 000000000..525f978c5
--- /dev/null
+++ b/modules/hypernetwork/ui.py
@@ -0,0 +1,43 @@
+import html
+import os
+
+import gradio as gr
+
+import modules.textual_inversion.textual_inversion
+import modules.textual_inversion.preprocess
+from modules import sd_hijack, shared
+
+
+def create_hypernetwork(name):
+    fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt")
+    assert not os.path.exists(fn), f"file {fn} already exists"
+
+    hypernetwork = modules.hypernetwork.hypernetwork.Hypernetwork(name=name)
+    hypernetwork.save(fn)
+
+    shared.reload_hypernetworks()
+    shared.hypernetwork = shared.hypernetworks.get(shared.opts.sd_hypernetwork, None)
+
+    return gr.Dropdown.update(choices=sorted([x for x in shared.hypernetworks.keys()])), f"Created: {fn}", ""
+
+
+def train_hypernetwork(*args):
+
+    initial_hypernetwork = shared.hypernetwork
+
+    try:
+        sd_hijack.undo_optimizations()
+
+        hypernetwork, filename = modules.hypernetwork.hypernetwork.train_hypernetwork(*args)
+
+        res = f"""
+Training {'interrupted' if shared.state.interrupted else 'finished'} at {hypernetwork.step} steps.
+Hypernetwork saved to {html.escape(filename)}
+"""
+        return res, ""
+    except Exception:
+        raise
+    finally:
+        shared.hypernetwork = initial_hypernetwork
+        sd_hijack.apply_optimizations()
+
diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index d68f89cc2..ec8c9d4b2 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -8,7 +8,7 @@ from torch import einsum
 from torch.nn.functional import silu
 
 import modules.textual_inversion.textual_inversion
-from modules import prompt_parser, devices, sd_hijack_optimizations, shared, hypernetwork
+from modules import prompt_parser, devices, sd_hijack_optimizations, shared
 from modules.shared import opts, device, cmd_opts
 
 import ldm.modules.attention
@@ -32,6 +32,8 @@ def apply_optimizations():
 
 
 def undo_optimizations():
+    from modules.hypernetwork import hypernetwork
+
     ldm.modules.attention.CrossAttention.forward = hypernetwork.attention_CrossAttention_forward
     ldm.modules.diffusionmodules.model.nonlinearity = diffusionmodules_model_nonlinearity
     ldm.modules.diffusionmodules.model.AttnBlock.forward = diffusionmodules_model_AttnBlock_forward
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index d9cca4851..3f32e0209 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -45,8 +45,7 @@ def split_cross_attention_forward(self, x, context=None, mask=None):
     q_in = self.to_q(x)
     context = default(context, x)
 
-    hypernetwork = shared.selected_hypernetwork()
-    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
+    hypernetwork_layers = (shared.hypernetwork.layers if shared.hypernetwork is not None else {}).get(context.shape[2], None)
 
     if hypernetwork_layers is not None:
         k_in = self.to_k(hypernetwork_layers[0](context))
diff --git a/modules/shared.py b/modules/shared.py
index 879d8424a..c5a893e8d 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -13,7 +13,7 @@ import modules.memmon
 import modules.sd_models
 import modules.styles
 import modules.devices as devices
-from modules import sd_samplers, hypernetwork
+from modules import sd_samplers
 from modules.paths import models_path, script_path, sd_path
 
 sd_model_file = os.path.join(script_path, 'model.ckpt')
@@ -28,6 +28,7 @@ parser.add_argument("--no-half", action='store_true', help="do not switch the mo
 parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware acceleration in browser)")
 parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI")
 parser.add_argument("--embeddings-dir", type=str, default=os.path.join(script_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)")
+parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_path, 'hypernetworks'), help="hypernetwork directory")
 parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui")
 parser.add_argument("--medvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a little speed for low VRM usage")
 parser.add_argument("--lowvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a lot of speed for very low VRM usage")
@@ -76,11 +77,15 @@ parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram
 
 config_filename = cmd_opts.ui_settings_file
 
-hypernetworks = hypernetwork.load_hypernetworks(os.path.join(models_path, 'hypernetworks'))
+
+def reload_hypernetworks():
+    from modules.hypernetwork import hypernetwork
+    hypernetworks.clear()
+    hypernetworks.update(hypernetwork.load_hypernetworks(cmd_opts.hypernetwork_dir))
 
 
-def selected_hypernetwork():
-    return hypernetworks.get(opts.sd_hypernetwork, None)
+hypernetworks = {}
+hypernetwork = None
 
 
 class State:
diff --git a/modules/textual_inversion/ui.py b/modules/textual_inversion/ui.py
index f19ac5e02..c57de1f94 100644
--- a/modules/textual_inversion/ui.py
+++ b/modules/textual_inversion/ui.py
@@ -22,7 +22,6 @@ def preprocess(*args):
 
 
 def train_embedding(*args):
-
     try:
         sd_hijack.undo_optimizations()
 
diff --git a/modules/ui.py b/modules/ui.py
index 4f18126fb..051908c1c 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -37,6 +37,7 @@ import modules.generation_parameters_copypaste
 from modules import prompt_parser
 from modules.images import save_image
 import modules.textual_inversion.ui
+import modules.hypernetwork.ui
 
 # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the bowser will not show any UI
 mimetypes.init()
@@ -965,6 +966,18 @@ def create_ui(wrap_gradio_gpu_call):
                         with gr.Column():
                             create_embedding = gr.Button(value="Create", variant='primary')
 
+                with gr.Group():
+                    gr.HTML(value="<p style='margin-bottom: 0.7em'>Create a new hypernetwork</p>")
+
+                    new_hypernetwork_name = gr.Textbox(label="Name")
+
+                    with gr.Row():
+                        with gr.Column(scale=3):
+                            gr.HTML(value="")
+
+                        with gr.Column():
+                            create_hypernetwork = gr.Button(value="Create", variant='primary')
+
                 with gr.Group():
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Preprocess images</p>")
 
@@ -986,6 +999,7 @@ def create_ui(wrap_gradio_gpu_call):
                 with gr.Group():
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding; must specify a directory with a set of 512x512 images</p>")
                     train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
+                    train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', choices=[x for x in shared.hypernetworks.keys()])
                     learn_rate = gr.Number(label='Learning rate', value=5.0e-03)
                     dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images")
                     log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")
@@ -993,15 +1007,12 @@ def create_ui(wrap_gradio_gpu_call):
                     steps = gr.Number(label='Max steps', value=100000, precision=0)
                     create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0)
                     save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0)
+                    preview_image_prompt = gr.Textbox(label='Preview prompt', value="")
 
                     with gr.Row():
-                        with gr.Column(scale=2):
-                            gr.HTML(value="")
-
-                        with gr.Column():
-                            with gr.Row():
-                                interrupt_training = gr.Button(value="Interrupt")
-                                train_embedding = gr.Button(value="Train", variant='primary')
+                        interrupt_training = gr.Button(value="Interrupt")
+                        train_hypernetwork = gr.Button(value="Train Hypernetwork", variant='primary')
+                        train_embedding = gr.Button(value="Train Embedding", variant='primary')
 
             with gr.Column():
                 progressbar = gr.HTML(elem_id="ti_progressbar")
@@ -1027,6 +1038,18 @@ def create_ui(wrap_gradio_gpu_call):
             ]
         )
 
+        create_hypernetwork.click(
+            fn=modules.hypernetwork.ui.create_hypernetwork,
+            inputs=[
+                new_hypernetwork_name,
+            ],
+            outputs=[
+                train_hypernetwork_name,
+                ti_output,
+                ti_outcome,
+            ]
+        )
+
         run_preprocess.click(
             fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]),
             _js="start_training_textual_inversion",
@@ -1062,12 +1085,33 @@ def create_ui(wrap_gradio_gpu_call):
             ]
         )
 
+        train_hypernetwork.click(
+            fn=wrap_gradio_gpu_call(modules.hypernetwork.ui.train_hypernetwork, extra_outputs=[gr.update()]),
+            _js="start_training_textual_inversion",
+            inputs=[
+                train_hypernetwork_name,
+                learn_rate,
+                dataset_directory,
+                log_directory,
+                steps,
+                create_image_every,
+                save_embedding_every,
+                template_file,
+                preview_image_prompt,
+            ],
+            outputs=[
+                ti_output,
+                ti_outcome,
+            ]
+        )
+
         interrupt_training.click(
             fn=lambda: shared.state.interrupt(),
             inputs=[],
             outputs=[],
         )
 
+
     def create_setting_component(key):
         def fun():
             return opts.data[key] if key in opts.data else opts.data_labels[key].default
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index c0c364df8..5b504de6b 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -78,8 +78,7 @@ def apply_checkpoint(p, x, xs):
 
 
 def apply_hypernetwork(p, x, xs):
-    hn = shared.hypernetworks.get(x, None)
-    opts.data["sd_hypernetwork"] = hn.name if hn is not None else 'None'
+    shared.hypernetwork = shared.hypernetworks.get(x, None)
 
 
 def format_value_add_label(p, opt, x):
@@ -199,7 +198,7 @@ class Script(scripts.Script):
         modules.processing.fix_seed(p)
         p.batch_size = 1
 
-        initial_hn = opts.sd_hypernetwork
+        initial_hn = shared.hypernetwork
 
         def process_axis(opt, vals):
             if opt.label == 'Nothing':
@@ -308,6 +307,6 @@ class Script(scripts.Script):
         # restore checkpoint in case it was changed by axes
         modules.sd_models.reload_model_weights(shared.sd_model)
 
-        opts.data["sd_hypernetwork"] = initial_hn
+        shared.hypernetwork = initial_hn
 
         return processed
diff --git a/textual_inversion_templates/hypernetwork.txt b/textual_inversion_templates/hypernetwork.txt
new file mode 100644
index 000000000..91e068905
--- /dev/null
+++ b/textual_inversion_templates/hypernetwork.txt
@@ -0,0 +1,27 @@
+a photo of a [filewords]
+a rendering of a [filewords]
+a cropped photo of the [filewords]
+the photo of a [filewords]
+a photo of a clean [filewords]
+a photo of a dirty [filewords]
+a dark photo of the [filewords]
+a photo of my [filewords]
+a photo of the cool [filewords]
+a close-up photo of a [filewords]
+a bright photo of the [filewords]
+a cropped photo of a [filewords]
+a photo of the [filewords]
+a good photo of the [filewords]
+a photo of one [filewords]
+a close-up photo of the [filewords]
+a rendition of the [filewords]
+a photo of the clean [filewords]
+a rendition of a [filewords]
+a photo of a nice [filewords]
+a good photo of a [filewords]
+a photo of the nice [filewords]
+a photo of the small [filewords]
+a photo of the weird [filewords]
+a photo of the large [filewords]
+a photo of a cool [filewords]
+a photo of a small [filewords]
diff --git a/textual_inversion_templates/none.txt b/textual_inversion_templates/none.txt
new file mode 100644
index 000000000..f77af4612
--- /dev/null
+++ b/textual_inversion_templates/none.txt
@@ -0,0 +1 @@
+picture
diff --git a/webui.py b/webui.py
index 480360fe0..60f9061f9 100644
--- a/webui.py
+++ b/webui.py
@@ -74,6 +74,15 @@ def wrap_gradio_gpu_call(func, extra_outputs=None):
     return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs)
 
 
+def set_hypernetwork():
+    shared.hypernetwork = shared.hypernetworks.get(shared.opts.sd_hypernetwork, None)
+
+
+shared.reload_hypernetworks()
+shared.opts.onchange("sd_hypernetwork", set_hypernetwork)
+set_hypernetwork()
+
+
 modules.scripts.load_scripts(os.path.join(script_path, "scripts"))
 
 shared.sd_model = modules.sd_models.load_model()

From 3110f895b2718a3a25aae419fdf5c87c177ec9f4 Mon Sep 17 00:00:00 2001
From: alg-wiki <alg.4chan@gmail.com>
Date: Mon, 10 Oct 2022 17:07:46 +0900
Subject: [PATCH 02/53] Textual Inversion: Added custom training image size and
 number of repeats per input image in a single epoch

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

diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index 7c44ea5be..acc4ce597 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -15,13 +15,13 @@ re_tag = re.compile(r"[a-zA-Z][_\w\d()]+")
 
 
 class PersonalizedBase(Dataset):
-    def __init__(self, data_root, size=None, repeats=100, flip_p=0.5, placeholder_token="*", width=512, height=512, model=None, device=None, template_file=None):
+    def __init__(self, data_root, size, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None):
 
         self.placeholder_token = placeholder_token
 
         self.size = size
-        self.width = width
-        self.height = height
+        self.width = size
+        self.height = size
         self.flip = transforms.RandomHorizontalFlip(p=flip_p)
 
         self.dataset = []
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index f1c002a2b..b3de6fd7e 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -7,8 +7,8 @@ import tqdm
 from modules import shared, images
 
 
-def preprocess(process_src, process_dst, process_flip, process_split, process_caption):
-    size = 512
+def preprocess(process_src, process_dst, process_size, process_flip, process_split, process_caption):
+    size = process_size
     src = os.path.abspath(process_src)
     dst = os.path.abspath(process_dst)
 
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index cd9f34984..e34dc2e81 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -6,6 +6,7 @@ import torch
 import tqdm
 import html
 import datetime
+import math
 
 
 from modules import shared, devices, sd_hijack, processing, sd_models
@@ -156,7 +157,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'):
     return fn
 
 
-def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps, create_image_every, save_embedding_every, template_file):
+def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_size, steps, num_repeats, create_image_every, save_embedding_every, template_file):
     assert embedding_name, 'embedding not selected'
 
     shared.state.textinfo = "Initializing textual inversion training..."
@@ -182,7 +183,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
 
     shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
     with torch.autocast("cuda"):
-        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, size=512, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file)
+        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, size=training_size, repeats=num_repeats, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file)
 
     hijack = sd_hijack.model_hijack
 
@@ -200,6 +201,9 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
     if ititial_step > steps:
         return embedding, filename
 
+    tr_img_len = len([os.path.join(data_root, file_path) for file_path in os.listdir(data_root)])
+    epoch_len = (tr_img_len * num_repeats) + tr_img_len
+
     pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step)
     for i, (x, text) in pbar:
         embedding.step = i + ititial_step
@@ -223,7 +227,10 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
             loss.backward()
             optimizer.step()
 
-        pbar.set_description(f"loss: {losses.mean():.7f}")
+        epoch_num = math.floor(embedding.step / epoch_len)
+        epoch_step = embedding.step - (epoch_num * epoch_len)
+
+        pbar.set_description(f"[Epoch {epoch_num}: {epoch_step}/{epoch_len}]loss: {losses.mean():.7f}")
 
         if embedding.step > 0 and embedding_dir is not None and embedding.step % save_embedding_every == 0:
             last_saved_file = os.path.join(embedding_dir, f'{embedding_name}-{embedding.step}.pt')
@@ -236,6 +243,8 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
                 sd_model=shared.sd_model,
                 prompt=text,
                 steps=20,
+                height=training_size,
+                width=training_size,
                 do_not_save_grid=True,
                 do_not_save_samples=True,
             )
diff --git a/modules/ui.py b/modules/ui.py
index 2231a8ed8..f821fd8db 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1029,6 +1029,7 @@ def create_ui(wrap_gradio_gpu_call):
 
                     process_src = gr.Textbox(label='Source directory')
                     process_dst = gr.Textbox(label='Destination directory')
+                    process_size = gr.Slider(minimum=64, maximum=2048, step=64, label="Size (width and height)", value=512)
 
                     with gr.Row():
                         process_flip = gr.Checkbox(label='Create flipped copies')
@@ -1043,13 +1044,15 @@ def create_ui(wrap_gradio_gpu_call):
                             run_preprocess = gr.Button(value="Preprocess", variant='primary')
 
                 with gr.Group():
-                    gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding; must specify a directory with a set of 512x512 images</p>")
+                    gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding; must specify a directory with a set of 1:1 ratio images</p>")
                     train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
                     learn_rate = gr.Number(label='Learning rate', value=5.0e-03)
                     dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images")
                     log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")
                     template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"))
+                    training_size = gr.Slider(minimum=64, maximum=2048, step=64, label="Size (width and height)", value=512)
                     steps = gr.Number(label='Max steps', value=100000, precision=0)
+                    num_repeats = gr.Number(label='Number of repeats for a single input image per epoch', value=100, precision=0)
                     create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0)
                     save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0)
 
@@ -1092,6 +1095,7 @@ def create_ui(wrap_gradio_gpu_call):
             inputs=[
                 process_src,
                 process_dst,
+                process_size,
                 process_flip,
                 process_split,
                 process_caption,
@@ -1110,7 +1114,9 @@ def create_ui(wrap_gradio_gpu_call):
                 learn_rate,
                 dataset_directory,
                 log_directory,
+                training_size,
                 steps,
+                num_repeats,
                 create_image_every,
                 save_embedding_every,
                 template_file,

From 4ee7519fc2e459ce8eff1f61f1655afba393357c Mon Sep 17 00:00:00 2001
From: alg-wiki <alg.4chan@gmail.com>
Date: Mon, 10 Oct 2022 17:31:33 +0900
Subject: [PATCH 03/53] Fixed progress bar output for epoch

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

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index e34dc2e81..769682ea5 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -228,7 +228,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
             optimizer.step()
 
         epoch_num = math.floor(embedding.step / epoch_len)
-        epoch_step = embedding.step - (epoch_num * epoch_len)
+        epoch_step = embedding.step - (epoch_num * epoch_len) + 1
 
         pbar.set_description(f"[Epoch {epoch_num}: {epoch_step}/{epoch_len}]loss: {losses.mean():.7f}")
 

From 04c745ea4f81518999927fee5f78500560c25e29 Mon Sep 17 00:00:00 2001
From: alg-wiki <alg.4chan@gmail.com>
Date: Mon, 10 Oct 2022 22:35:35 +0900
Subject: [PATCH 04/53] Custom Width and Height

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

diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index acc4ce597..bcf772d2f 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -15,13 +15,12 @@ re_tag = re.compile(r"[a-zA-Z][_\w\d()]+")
 
 
 class PersonalizedBase(Dataset):
-    def __init__(self, data_root, size, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None):
+    def __init__(self, data_root, width, height, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None):
 
         self.placeholder_token = placeholder_token
 
-        self.size = size
-        self.width = size
-        self.height = size
+        self.width = width
+        self.height = height
         self.flip = transforms.RandomHorizontalFlip(p=flip_p)
 
         self.dataset = []
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index b3de6fd7e..d7efdef29 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -7,8 +7,9 @@ import tqdm
 from modules import shared, images
 
 
-def preprocess(process_src, process_dst, process_size, process_flip, process_split, process_caption):
-    size = process_size
+def preprocess(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption):
+    width = process_width
+    height = process_height
     src = os.path.abspath(process_src)
     dst = os.path.abspath(process_dst)
 
@@ -55,23 +56,23 @@ def preprocess(process_src, process_dst, process_size, process_flip, process_spl
         is_wide = ratio < 1 / 1.35
 
         if process_split and is_tall:
-            img = img.resize((size, size * img.height // img.width))
+            img = img.resize((width, height * img.height // img.width))
 
-            top = img.crop((0, 0, size, size))
+            top = img.crop((0, 0, width, height))
             save_pic(top, index)
 
-            bot = img.crop((0, img.height - size, size, img.height))
+            bot = img.crop((0, img.height - height, width, img.height))
             save_pic(bot, index)
         elif process_split and is_wide:
-            img = img.resize((size * img.width // img.height, size))
+            img = img.resize((width * img.width // img.height, height))
 
-            left = img.crop((0, 0, size, size))
+            left = img.crop((0, 0, width, height))
             save_pic(left, index)
 
-            right = img.crop((img.width - size, 0, img.width, size))
+            right = img.crop((img.width - width, 0, img.width, height))
             save_pic(right, index)
         else:
-            img = images.resize_image(1, img, size, size)
+            img = images.resize_image(1, img, width, height)
             save_pic(img, index)
 
         shared.state.nextjob()
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 769682ea5..5965c5a06 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -6,7 +6,6 @@ import torch
 import tqdm
 import html
 import datetime
-import math
 
 
 from modules import shared, devices, sd_hijack, processing, sd_models
@@ -157,7 +156,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'):
     return fn
 
 
-def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_size, steps, num_repeats, create_image_every, save_embedding_every, template_file):
+def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, num_repeats, create_image_every, save_embedding_every, template_file):
     assert embedding_name, 'embedding not selected'
 
     shared.state.textinfo = "Initializing textual inversion training..."
@@ -183,7 +182,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
 
     shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
     with torch.autocast("cuda"):
-        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, size=training_size, repeats=num_repeats, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file)
+        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, height=training_height, repeats=num_repeats, placeholder_token=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file)
 
     hijack = sd_hijack.model_hijack
 
@@ -227,7 +226,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
             loss.backward()
             optimizer.step()
 
-        epoch_num = math.floor(embedding.step / epoch_len)
+        epoch_num = embedding.step // epoch_len
         epoch_step = embedding.step - (epoch_num * epoch_len) + 1
 
         pbar.set_description(f"[Epoch {epoch_num}: {epoch_step}/{epoch_len}]loss: {losses.mean():.7f}")
@@ -243,8 +242,8 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
                 sd_model=shared.sd_model,
                 prompt=text,
                 steps=20,
-                height=training_size,
-                width=training_size,
+				height=training_height,
+				width=training_width,
                 do_not_save_grid=True,
                 do_not_save_samples=True,
             )
diff --git a/modules/ui.py b/modules/ui.py
index f821fd8db..8c06ad7cc 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1029,7 +1029,8 @@ def create_ui(wrap_gradio_gpu_call):
 
                     process_src = gr.Textbox(label='Source directory')
                     process_dst = gr.Textbox(label='Destination directory')
-                    process_size = gr.Slider(minimum=64, maximum=2048, step=64, label="Size (width and height)", value=512)
+                    process_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
+                    process_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
 
                     with gr.Row():
                         process_flip = gr.Checkbox(label='Create flipped copies')
@@ -1050,7 +1051,8 @@ def create_ui(wrap_gradio_gpu_call):
                     dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images")
                     log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")
                     template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"))
-                    training_size = gr.Slider(minimum=64, maximum=2048, step=64, label="Size (width and height)", value=512)
+                    training_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
+                    training_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
                     steps = gr.Number(label='Max steps', value=100000, precision=0)
                     num_repeats = gr.Number(label='Number of repeats for a single input image per epoch', value=100, precision=0)
                     create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0)
@@ -1095,7 +1097,8 @@ def create_ui(wrap_gradio_gpu_call):
             inputs=[
                 process_src,
                 process_dst,
-                process_size,
+                process_width,
+                process_height,
                 process_flip,
                 process_split,
                 process_caption,
@@ -1114,7 +1117,8 @@ def create_ui(wrap_gradio_gpu_call):
                 learn_rate,
                 dataset_directory,
                 log_directory,
-                training_size,
+                training_width,
+                training_height,
                 steps,
                 num_repeats,
                 create_image_every,

From bc3e183b739913e7be91213a256f038b10eb71e9 Mon Sep 17 00:00:00 2001
From: alg-wiki <alg.4chan@gmail.com>
Date: Tue, 11 Oct 2022 04:30:13 +0900
Subject: [PATCH 05/53] Textual Inversion: Preprocess and Training will only
 pick-up image files

---
 modules/textual_inversion/dataset.py           | 3 ++-
 modules/textual_inversion/preprocess.py        | 3 ++-
 modules/textual_inversion/textual_inversion.py | 3 ++-
 3 files changed, 6 insertions(+), 3 deletions(-)

diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index bcf772d2f..d4baf0660 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -22,6 +22,7 @@ class PersonalizedBase(Dataset):
         self.width = width
         self.height = height
         self.flip = transforms.RandomHorizontalFlip(p=flip_p)
+        self.extns = [".jpg",".jpeg",".png"]
 
         self.dataset = []
 
@@ -32,7 +33,7 @@ class PersonalizedBase(Dataset):
 
         assert data_root, 'dataset directory not specified'
 
-        self.image_paths = [os.path.join(data_root, file_path) for file_path in os.listdir(data_root)]
+        self.image_paths = [os.path.join(data_root, file_path) for file_path in os.listdir(data_root) if os.path.splitext(file_path.casefold())[1] in self.extns]
         print("Preparing dataset...")
         for path in tqdm.tqdm(self.image_paths):
             image = Image.open(path)
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index d7efdef29..b6c78cf85 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -12,12 +12,13 @@ def preprocess(process_src, process_dst, process_width, process_height, process_
     height = process_height
     src = os.path.abspath(process_src)
     dst = os.path.abspath(process_dst)
+    extns = [".jpg",".jpeg",".png"]
 
     assert src != dst, 'same directory specified as source and destination'
 
     os.makedirs(dst, exist_ok=True)
 
-    files = os.listdir(src)
+    files = [i for i in os.listdir(src) if os.path.splitext(i.casefold())[1] in extns]
 
     shared.state.textinfo = "Preprocessing..."
     shared.state.job_count = len(files)
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 5965c5a06..45397be92 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -161,6 +161,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
 
     shared.state.textinfo = "Initializing textual inversion training..."
     shared.state.job_count = steps
+    extns = [".jpg",".jpeg",".png"]
 
     filename = os.path.join(shared.cmd_opts.embeddings_dir, f'{embedding_name}.pt')
 
@@ -200,7 +201,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
     if ititial_step > steps:
         return embedding, filename
 
-    tr_img_len = len([os.path.join(data_root, file_path) for file_path in os.listdir(data_root)])
+    tr_img_len = len([os.path.join(data_root, file_path) for file_path in os.listdir(data_root) if os.path.splitext(file_path.casefold())[1] in extns])
     epoch_len = (tr_img_len * num_repeats) + tr_img_len
 
     pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step)

From 2536ecbb1790da2af0d61b6a26f38732cba665cd Mon Sep 17 00:00:00 2001
From: Fampai <>
Date: Mon, 10 Oct 2022 17:10:29 -0400
Subject: [PATCH 06/53] Refactored learning rate code

---
 .../textual_inversion/textual_inversion.py    | 51 +++++++++++++++++--
 modules/ui.py                                 |  2 +-
 2 files changed, 48 insertions(+), 5 deletions(-)

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 5965c5a06..c64a45987 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -189,8 +189,6 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
     embedding = hijack.embedding_db.word_embeddings[embedding_name]
     embedding.vec.requires_grad = True
 
-    optimizer = torch.optim.AdamW([embedding.vec], lr=learn_rate)
-
     losses = torch.zeros((32,))
 
     last_saved_file = "<none>"
@@ -203,12 +201,24 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
     tr_img_len = len([os.path.join(data_root, file_path) for file_path in os.listdir(data_root)])
     epoch_len = (tr_img_len * num_repeats) + tr_img_len
 
+    scheduleIter = iter(LearnSchedule(learn_rate, steps, ititial_step))
+    (learn_rate, end_step) = next(scheduleIter)
+    print(f'Training at rate of {learn_rate} until step {end_step}')
+
+    optimizer = torch.optim.AdamW([embedding.vec], lr=learn_rate)
+
     pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step)
     for i, (x, text) in pbar:
         embedding.step = i + ititial_step
 
-        if embedding.step > steps:
-            break
+        if embedding.step > end_step:
+            try:
+                (learn_rate, end_step) = next(scheduleIter)
+            except:
+                break
+            tqdm.tqdm.write(f'Training at rate of {learn_rate} until step {end_step}')
+            for pg in optimizer.param_groups:
+                pg['lr'] = learn_rate
 
         if shared.state.interrupted:
             break
@@ -277,3 +287,36 @@ Last saved image: {html.escape(last_saved_image)}<br/>
 
     return embedding, filename
 
+class LearnSchedule:
+    def __init__(self, learn_rate, max_steps, cur_step=0):
+        pairs = learn_rate.split(',')
+        self.rates = []
+        self.it = 0
+        self.maxit = 0
+        for i, pair in enumerate(pairs):
+            tmp = pair.split(':')
+            if len(tmp) == 2:
+                step = int(tmp[1])
+                if step > cur_step:
+                    self.rates.append((float(tmp[0]), min(step, max_steps)))
+                    self.maxit += 1
+                    if step > max_steps:
+                        return
+                elif step == -1:
+                    self.rates.append((float(tmp[0]), max_steps))
+                    self.maxit += 1
+                    return
+            else:
+                self.rates.append((float(tmp[0]), max_steps))
+                self.maxit += 1
+                return
+
+    def __iter__(self):
+        return self
+
+    def __next__(self):
+        if self.it < self.maxit:
+            self.it += 1
+            return self.rates[self.it - 1]
+        else:
+            raise StopIteration
diff --git a/modules/ui.py b/modules/ui.py
index 8c06ad7cc..c9e8355bf 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1047,7 +1047,7 @@ def create_ui(wrap_gradio_gpu_call):
                 with gr.Group():
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding; must specify a directory with a set of 1:1 ratio images</p>")
                     train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
-                    learn_rate = gr.Number(label='Learning rate', value=5.0e-03)
+                    learn_rate = gr.Textbox(label='Learning rate', placeholder="Learning rate", value = "5.0e-03")
                     dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images")
                     log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")
                     template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"))

From 907a88b2d0be320575c2129d8d6a1d4f3a68f9eb Mon Sep 17 00:00:00 2001
From: alg-wiki <alg.4chan@gmail.com>
Date: Tue, 11 Oct 2022 06:33:08 +0900
Subject: [PATCH 07/53] Added .webp .bmp

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

diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index d4baf0660..0dc54fb70 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -22,7 +22,7 @@ class PersonalizedBase(Dataset):
         self.width = width
         self.height = height
         self.flip = transforms.RandomHorizontalFlip(p=flip_p)
-        self.extns = [".jpg",".jpeg",".png"]
+        self.extns = [".jpg",".jpeg",".png",".webp",".bmp"]
 
         self.dataset = []
 
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index b6c78cf85..8290abe88 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -12,7 +12,7 @@ def preprocess(process_src, process_dst, process_width, process_height, process_
     height = process_height
     src = os.path.abspath(process_src)
     dst = os.path.abspath(process_dst)
-    extns = [".jpg",".jpeg",".png"]
+    extns = [".jpg",".jpeg",".png",".webp",".bmp"]
 
     assert src != dst, 'same directory specified as source and destination'
 
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index a03b299c4..33c923d16 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -161,7 +161,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
 
     shared.state.textinfo = "Initializing textual inversion training..."
     shared.state.job_count = steps
-    extns = [".jpg",".jpeg",".png"]
+    extns = [".jpg",".jpeg",".png",".webp",".bmp"]
 
     filename = os.path.join(shared.cmd_opts.embeddings_dir, f'{embedding_name}.pt')
 

From 70b50b1dfcb0ce0f87998c994f4855014bc7e26b Mon Sep 17 00:00:00 2001
From: ClashSAN <98228077+ClashSAN@users.noreply.github.com>
Date: Mon, 10 Oct 2022 23:23:12 +0000
Subject: [PATCH 08/53] add features, credit for Composable Diffusion

to readme

https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/2171
---
 README.md | 10 ++++++++--
 1 file changed, 8 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index 561eb03d1..0e9387686 100644
--- a/README.md
+++ b/README.md
@@ -28,10 +28,12 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
     - CodeFormer, face restoration tool as an alternative to GFPGAN
     - RealESRGAN, neural network upscaler
     - ESRGAN, neural network upscaler with a lot of third party models
-    - SwinIR, neural network upscaler
+    - SwinIR and Swin2SR([see here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/2092)), neural network upscalers
     - LDSR, Latent diffusion super resolution upscaling
 - Resizing aspect ratio options
 - Sampling method selection
+    - Adjust sampler eta values (noise multiplier)
+    - More advanced noise setting options
 - Interrupt processing at any time
 - 4GB video card support (also reports of 2GB working)
 - Correct seeds for batches
@@ -67,6 +69,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
      - also supports weights for prompts: `a cat :1.2 AND a dog AND a penguin :2.2`
 - No token limit for prompts (original stable diffusion lets you use up to 75 tokens)
 - DeepDanbooru integration, creates danbooru style tags for anime prompts (add --deepdanbooru to commandline args)
+- [xformers](https://github.com/mv-lab/swin2sr), major speed increase for select cards: (add --xformers to commandline args)
 
 ## Installation and Running
 Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for both [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended) and [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs.
@@ -116,6 +119,7 @@ The documentation was moved from this README over to the project's [wiki](https:
 - CodeFormer - https://github.com/sczhou/CodeFormer
 - ESRGAN - https://github.com/xinntao/ESRGAN
 - SwinIR - https://github.com/JingyunLiang/SwinIR
+- Swin2SR - https://github.com/mv-lab/swin2sr
 - LDSR - https://github.com/Hafiidz/latent-diffusion
 - Ideas for optimizations - https://github.com/basujindal/stable-diffusion
 - Doggettx - Cross Attention layer optimization - https://github.com/Doggettx/stable-diffusion, original idea for prompt editing.
@@ -123,6 +127,8 @@ The documentation was moved from this README over to the project's [wiki](https:
 - Idea for SD upscale - https://github.com/jquesnelle/txt2imghd
 - Noise generation for outpainting mk2 - https://github.com/parlance-zz/g-diffuser-bot
 - CLIP interrogator idea and borrowing some code - https://github.com/pharmapsychotic/clip-interrogator
+- Idea for Composable Diffusion - https://github.com/energy-based-model/Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch
+- xformers - https://github.com/facebookresearch/xformers
+- DeepDanbooru - interrogator for anime diffusers https://github.com/KichangKim/DeepDanbooru
 - Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user.
-- DeepDanbooru - interrogator for anime diffusors https://github.com/KichangKim/DeepDanbooru
 - (You)

From 1add3cff84b7e2436d69b1e97ae689281e4a7c33 Mon Sep 17 00:00:00 2001
From: papuSpartan <mcgpapu@gmail.com>
Date: Mon, 10 Oct 2022 19:57:43 -0500
Subject: [PATCH 09/53] Refresh list of models/ckpts upon hitting restart
 gradio in the settings pane

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

diff --git a/modules/ui.py b/modules/ui.py
index e8039d76c..06ff118f8 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -39,6 +39,7 @@ import modules.generation_parameters_copypaste
 from modules import prompt_parser
 from modules.images import save_image
 import modules.textual_inversion.ui
+from modules.sd_models import list_models
 
 # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI
 mimetypes.init()
@@ -1290,6 +1291,9 @@ Requested path was: {f}
             shared.state.interrupt()
             settings_interface.gradio_ref.do_restart = True
 
+            # refresh models so that new models/.ckpt's show up on reload
+            list_models()
+
         restart_gradio.click(
             fn=request_restart,
             inputs=[],

From 8b7d3f1bef47bbe048f644ed0d8dd3ad46554045 Mon Sep 17 00:00:00 2001
From: Jairo Correa <jn.j41r0@gmail.com>
Date: Tue, 11 Oct 2022 02:22:46 -0300
Subject: [PATCH 10/53] Make the ctrl+enter shortcut use the generate button on
 the current tab

---
 modules/ui.py |  2 +-
 script.js     | 11 +++++++++--
 2 files changed, 10 insertions(+), 3 deletions(-)

diff --git a/modules/ui.py b/modules/ui.py
index e8039d76c..cafda8845 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1331,7 +1331,7 @@ Requested path was: {f}
         
         with gr.Tabs() as tabs:
             for interface, label, ifid in interfaces:
-                with gr.TabItem(label, id=ifid):
+                with gr.TabItem(label, id=ifid, elem_id='tab_' + ifid):
                     interface.render()
         
         if os.path.exists(os.path.join(script_path, "notification.mp3")):
diff --git a/script.js b/script.js
index a92c0f77d..9543cbe68 100644
--- a/script.js
+++ b/script.js
@@ -6,6 +6,10 @@ function get_uiCurrentTab() {
     return gradioApp().querySelector('.tabs button:not(.border-transparent)')
 }
 
+function get_uiCurrentTabContent() {
+    return gradioApp().querySelector('.tabitem[id^=tab_]:not([style*="display: none"])')
+}
+
 uiUpdateCallbacks = []
 uiTabChangeCallbacks = []
 let uiCurrentTab = null
@@ -50,8 +54,11 @@ document.addEventListener("DOMContentLoaded", function() {
     } else if (e.keyCode !== undefined) {
         if((e.keyCode == 13 && (e.metaKey || e.ctrlKey))) handled = true;
     }
-    if (handled) { 
-        gradioApp().querySelector("#txt2img_generate").click(); 
+    if (handled) {
+        button = get_uiCurrentTabContent().querySelector('button[id$=_generate]');
+        if (button) {
+            button.click();
+        }
         e.preventDefault();
     }
 })

From 8617396c6df71074c7fd3d39419802026874712a Mon Sep 17 00:00:00 2001
From: Kenneth <kenneth.mccarthy24@yahoo.com>
Date: Mon, 10 Oct 2022 17:23:07 -0600
Subject: [PATCH 11/53] Added slider for deepbooru score threshold in settings

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

diff --git a/modules/shared.py b/modules/shared.py
index ecd15ef5d..e0830e281 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -239,6 +239,7 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"),
     "interrogate_clip_min_length": OptionInfo(24, "Interrogate: minimum description length (excluding artists, etc..)", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}),
     "interrogate_clip_max_length": OptionInfo(48, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}),
     "interrogate_clip_dict_limit": OptionInfo(1500, "Interrogate: maximum number of lines in text file (0 = No limit)"),
+    "interrogate_deepbooru_score_threshold": OptionInfo(0.5, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
 }))
 
 options_templates.update(options_section(('ui', "User interface"), {
diff --git a/modules/ui.py b/modules/ui.py
index cafda8845..ca3151c47 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -311,7 +311,7 @@ def interrogate(image):
 
 
 def interrogate_deepbooru(image):
-    prompt = get_deepbooru_tags(image)
+    prompt = get_deepbooru_tags(image, opts.interrogate_deepbooru_score_threshold)
     return gr_show(True) if prompt is None else prompt
 
 

From 5e2627a1a63e4c9f87e6e604ecc24e9936f149de Mon Sep 17 00:00:00 2001
From: hentailord85ez <112723046+hentailord85ez@users.noreply.github.com>
Date: Tue, 11 Oct 2022 07:55:28 +0100
Subject: [PATCH 12/53] Comma backtrack padding (#2192)

Comma backtrack padding
---
 modules/sd_hijack.py | 19 ++++++++++++++++++-
 modules/shared.py    |  1 +
 2 files changed, 19 insertions(+), 1 deletion(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 827bf3045..aa4d2cbc0 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -107,6 +107,8 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
         self.tokenizer = wrapped.tokenizer
         self.token_mults = {}
 
+        self.comma_token = [v for k, v in self.tokenizer.get_vocab().items() if k == ',</w>'][0]
+
         tokens_with_parens = [(k, v) for k, v in self.tokenizer.get_vocab().items() if '(' in k or ')' in k or '[' in k or ']' in k]
         for text, ident in tokens_with_parens:
             mult = 1.0
@@ -136,6 +138,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
         fixes = []
         remade_tokens = []
         multipliers = []
+        last_comma = -1
 
         for tokens, (text, weight) in zip(tokenized, parsed):
             i = 0
@@ -144,6 +147,20 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
 
                 embedding, embedding_length_in_tokens = self.hijack.embedding_db.find_embedding_at_position(tokens, i)
 
+                if token == self.comma_token:
+                    last_comma = len(remade_tokens)
+                elif opts.comma_padding_backtrack != 0 and max(len(remade_tokens), 1) % 75 == 0 and last_comma != -1 and len(remade_tokens) - last_comma <= opts.comma_padding_backtrack:
+                    last_comma += 1
+                    reloc_tokens = remade_tokens[last_comma:]
+                    reloc_mults = multipliers[last_comma:]
+
+                    remade_tokens = remade_tokens[:last_comma]
+                    length = len(remade_tokens)
+                    
+                    rem = int(math.ceil(length / 75)) * 75 - length
+                    remade_tokens += [id_end] * rem + reloc_tokens
+                    multipliers = multipliers[:last_comma] + [1.0] * rem + reloc_mults
+                
                 if embedding is None:
                     remade_tokens.append(token)
                     multipliers.append(weight)
@@ -284,7 +301,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
         while max(map(len, remade_batch_tokens)) != 0:
             rem_tokens = [x[75:] for x in remade_batch_tokens]
             rem_multipliers = [x[75:] for x in batch_multipliers]
-            
+
             self.hijack.fixes = []
             for unfiltered in hijack_fixes:
                 fixes = []
diff --git a/modules/shared.py b/modules/shared.py
index e0830e281..14b40d70d 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -227,6 +227,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "enable_emphasis": OptionInfo(True, "Emphasis: use (text) to make model pay more attention to text and [text] to make it pay less attention"),
     "use_old_emphasis_implementation": OptionInfo(False, "Use old emphasis implementation. Can be useful to reproduce old seeds."),
     "enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"),
+    "comma_padding_backtrack": OptionInfo(20, "Increase coherency by padding from the last comma within n tokens when using more than 75 tokens", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1 }),
     "filter_nsfw": OptionInfo(False, "Filter NSFW content"),
     'CLIP_stop_at_last_layers': OptionInfo(1, "Stop At last layers of CLIP model", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}),
     "random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}),

From 948533950c9db5069a874d925fadd50bac00fdb5 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 11:09:51 +0300
Subject: [PATCH 13/53] replace duplicate code with a function

---
 modules/hypernetwork.py            | 23 ++++++++++------
 modules/sd_hijack_optimizations.py | 44 ++++++++++--------------------
 2 files changed, 29 insertions(+), 38 deletions(-)

diff --git a/modules/hypernetwork.py b/modules/hypernetwork.py
index 498bc9d8f..7bbc443e5 100644
--- a/modules/hypernetwork.py
+++ b/modules/hypernetwork.py
@@ -64,21 +64,26 @@ def load_hypernetwork(filename):
         shared.loaded_hypernetwork = None
 
 
+def apply_hypernetwork(hypernetwork, context):
+    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
+
+    if hypernetwork_layers is None:
+        return context, context
+
+    context_k = hypernetwork_layers[0](context)
+    context_v = hypernetwork_layers[1](context)
+    return context_k, context_v
+
+
 def attention_CrossAttention_forward(self, x, context=None, mask=None):
     h = self.heads
 
     q = self.to_q(x)
     context = default(context, x)
 
-    hypernetwork = shared.loaded_hypernetwork
-    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
-
-    if hypernetwork_layers is not None:
-        k = self.to_k(hypernetwork_layers[0](context))
-        v = self.to_v(hypernetwork_layers[1](context))
-    else:
-        k = self.to_k(context)
-        v = self.to_v(context)
+    context_k, context_v = apply_hypernetwork(shared.loaded_hypernetwork, context)
+    k = self.to_k(context_k)
+    v = self.to_v(context_v)
 
     q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
 
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index 18408e629..25cb67a4e 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -8,7 +8,8 @@ from torch import einsum
 from ldm.util import default
 from einops import rearrange
 
-from modules import shared
+from modules import shared, hypernetwork
+
 
 if shared.cmd_opts.xformers or shared.cmd_opts.force_enable_xformers:
     try:
@@ -26,16 +27,10 @@ def split_cross_attention_forward_v1(self, x, context=None, mask=None):
     q_in = self.to_q(x)
     context = default(context, x)
 
-    hypernetwork = shared.loaded_hypernetwork
-    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
-
-    if hypernetwork_layers is not None:
-        k_in = self.to_k(hypernetwork_layers[0](context))
-        v_in = self.to_v(hypernetwork_layers[1](context))
-    else:
-        k_in = self.to_k(context)
-        v_in = self.to_v(context)
-    del context, x
+    context_k, context_v = hypernetwork.apply_hypernetwork(shared.loaded_hypernetwork, context)
+    k_in = self.to_k(context_k)
+    v_in = self.to_v(context_v)
+    del context, context_k, context_v, x
 
     q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q_in, k_in, v_in))
     del q_in, k_in, v_in
@@ -59,22 +54,16 @@ def split_cross_attention_forward_v1(self, x, context=None, mask=None):
     return self.to_out(r2)
 
 
-# taken from https://github.com/Doggettx/stable-diffusion
+# taken from https://github.com/Doggettx/stable-diffusion and modified
 def split_cross_attention_forward(self, x, context=None, mask=None):
     h = self.heads
 
     q_in = self.to_q(x)
     context = default(context, x)
 
-    hypernetwork = shared.loaded_hypernetwork
-    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
-
-    if hypernetwork_layers is not None:
-        k_in = self.to_k(hypernetwork_layers[0](context))
-        v_in = self.to_v(hypernetwork_layers[1](context))
-    else:
-        k_in = self.to_k(context)
-        v_in = self.to_v(context)
+    context_k, context_v = hypernetwork.apply_hypernetwork(shared.loaded_hypernetwork, context)
+    k_in = self.to_k(context_k)
+    v_in = self.to_v(context_v)
 
     k_in *= self.scale
 
@@ -130,14 +119,11 @@ def xformers_attention_forward(self, x, context=None, mask=None):
     h = self.heads
     q_in = self.to_q(x)
     context = default(context, x)
-    hypernetwork = shared.loaded_hypernetwork
-    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
-    if hypernetwork_layers is not None:
-        k_in = self.to_k(hypernetwork_layers[0](context))
-        v_in = self.to_v(hypernetwork_layers[1](context))
-    else:
-        k_in = self.to_k(context)
-        v_in = self.to_v(context)
+
+    context_k, context_v = hypernetwork.apply_hypernetwork(shared.loaded_hypernetwork, context)
+    k_in = self.to_k(context_k)
+    v_in = self.to_v(context_v)
+
     q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> b n h d', h=h), (q_in, k_in, v_in))
     del q_in, k_in, v_in
     out = xformers.ops.memory_efficient_attention(q, k, v, attn_bias=None)

From b2368a3bce663f19a7209d9cb38617e635ca6e3c Mon Sep 17 00:00:00 2001
From: alg-wiki <alg.4chan@gmail.com>
Date: Tue, 11 Oct 2022 17:32:46 +0900
Subject: [PATCH 14/53] Switched to exception handling

---
 modules/textual_inversion/dataset.py           | 10 +++++-----
 modules/textual_inversion/preprocess.py        |  8 +++++---
 modules/textual_inversion/textual_inversion.py | 18 ++++++++----------
 3 files changed, 18 insertions(+), 18 deletions(-)

diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index 0dc54fb70..4d0063669 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -22,7 +22,6 @@ class PersonalizedBase(Dataset):
         self.width = width
         self.height = height
         self.flip = transforms.RandomHorizontalFlip(p=flip_p)
-        self.extns = [".jpg",".jpeg",".png",".webp",".bmp"]
 
         self.dataset = []
 
@@ -33,12 +32,13 @@ class PersonalizedBase(Dataset):
 
         assert data_root, 'dataset directory not specified'
 
-        self.image_paths = [os.path.join(data_root, file_path) for file_path in os.listdir(data_root) if os.path.splitext(file_path.casefold())[1] in self.extns]
+        self.image_paths = [os.path.join(data_root, file_path) for file_path in os.listdir(data_root)]
         print("Preparing dataset...")
         for path in tqdm.tqdm(self.image_paths):
-            image = Image.open(path)
-            image = image.convert('RGB')
-            image = image.resize((self.width, self.height), PIL.Image.BICUBIC)
+            try:
+                image = Image.open(path).convert('RGB').resize((self.width, self.height), PIL.Image.BICUBIC)
+            except Exception:
+                continue
 
             filename = os.path.basename(path)
             filename_tokens = os.path.splitext(filename)[0]
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index 8290abe88..1a6727255 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -12,13 +12,12 @@ def preprocess(process_src, process_dst, process_width, process_height, process_
     height = process_height
     src = os.path.abspath(process_src)
     dst = os.path.abspath(process_dst)
-    extns = [".jpg",".jpeg",".png",".webp",".bmp"]
 
     assert src != dst, 'same directory specified as source and destination'
 
     os.makedirs(dst, exist_ok=True)
 
-    files = [i for i in os.listdir(src) if os.path.splitext(i.casefold())[1] in extns]
+    files = os.listdir(src)
 
     shared.state.textinfo = "Preprocessing..."
     shared.state.job_count = len(files)
@@ -47,7 +46,10 @@ def preprocess(process_src, process_dst, process_width, process_height, process_
     for index, imagefile in enumerate(tqdm.tqdm(files)):
         subindex = [0]
         filename = os.path.join(src, imagefile)
-        img = Image.open(filename).convert("RGB")
+        try:
+            img = Image.open(filename).convert("RGB")
+        except Exception:
+            continue
 
         if shared.state.interrupted:
             break
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 33c923d16..91cde04b5 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -161,7 +161,6 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
 
     shared.state.textinfo = "Initializing textual inversion training..."
     shared.state.job_count = steps
-    extns = [".jpg",".jpeg",".png",".webp",".bmp"]
 
     filename = os.path.join(shared.cmd_opts.embeddings_dir, f'{embedding_name}.pt')
 
@@ -201,10 +200,6 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
     if ititial_step > steps:
         return embedding, filename
 
-    tr_img_len = len([os.path.join(data_root, file_path) for file_path in os.listdir(data_root) if os.path.splitext(file_path.casefold())[1] in extns])
-
-    epoch_len = (tr_img_len * num_repeats) + tr_img_len
-
     pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step)
     for i, (x, text) in pbar:
         embedding.step = i + ititial_step
@@ -228,10 +223,10 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
             loss.backward()
             optimizer.step()
 
-        epoch_num = embedding.step // epoch_len
-        epoch_step = embedding.step - (epoch_num * epoch_len) + 1
+        epoch_num = embedding.step // len(ds)
+        epoch_step = embedding.step - (epoch_num * len(ds)) + 1
 
-        pbar.set_description(f"[Epoch {epoch_num}: {epoch_step}/{epoch_len}]loss: {losses.mean():.7f}")
+        pbar.set_description(f"[Epoch {epoch_num}: {epoch_step}/{len(ds)}]loss: {losses.mean():.7f}")
 
         if embedding.step > 0 and embedding_dir is not None and embedding.step % save_embedding_every == 0:
             last_saved_file = os.path.join(embedding_dir, f'{embedding_name}-{embedding.step}.pt')
@@ -243,9 +238,12 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
             p = processing.StableDiffusionProcessingTxt2Img(
                 sd_model=shared.sd_model,
                 prompt=text,
-                steps=20,
-				height=training_height,
+                steps=28,
+				height=768,
 				width=training_width,
+                negative_prompt="lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts,signature, watermark, username, blurry, artist name",
+                cfg_scale=7.0,
+                sampler_index=0,
                 do_not_save_grid=True,
                 do_not_save_samples=True,
             )

From 8bacbca0a1ab9aabcb0ad0cbf070e0006991e98a Mon Sep 17 00:00:00 2001
From: alg-wiki <alg.4chan@gmail.com>
Date: Tue, 11 Oct 2022 17:35:09 +0900
Subject: [PATCH 15/53] Removed my local edits to checkpoint image generation

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

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 91cde04b5..e9ff80c24 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -238,12 +238,9 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
             p = processing.StableDiffusionProcessingTxt2Img(
                 sd_model=shared.sd_model,
                 prompt=text,
-                steps=28,
-				height=768,
+                steps=20,
+				height=training_height,
 				width=training_width,
-                negative_prompt="lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts,signature, watermark, username, blurry, artist name",
-                cfg_scale=7.0,
-                sampler_index=0,
                 do_not_save_grid=True,
                 do_not_save_samples=True,
             )

From 255be75d30f41e089e499ec1c8462d6bf64dec24 Mon Sep 17 00:00:00 2001
From: aperullo <18688190+aperullo@users.noreply.github.com>
Date: Tue, 11 Oct 2022 06:16:57 -0400
Subject: [PATCH 16/53] Error if prompt missing SR token to prevent mis-gens
 (#2209)

---
 scripts/xy_grid.py | 7 +++++++
 1 file changed, 7 insertions(+)

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 42e1489c4..10a82dc9f 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -27,9 +27,16 @@ def apply_field(field):
 
 
 def apply_prompt(p, x, xs):
+
+    orig_prompt = p.prompt
+    orig_negative_prompt = p.negative_prompt
+
     p.prompt = p.prompt.replace(xs[0], x)
     p.negative_prompt = p.negative_prompt.replace(xs[0], x)
 
+    if p.prompt == orig_prompt and p.negative_prompt == orig_negative_prompt:
+        raise RuntimeError(f"Prompt S/R did not find {xs[0]} in prompt or negative prompt. Did you forget to add the token?")
+
 
 def apply_order(p, x, xs):
     token_order = []

From 4b460fcb1a0224772949556fe0469da93245c532 Mon Sep 17 00:00:00 2001
From: Rory Grieve <rhrg500@gmail.com>
Date: Tue, 11 Oct 2022 11:23:47 +0100
Subject: [PATCH 17/53] Reset init img in loopback at start of each batch
 (#2214)

Before a new batch would use the last image from the previous batch. Now
each batch will use the original image for the init image at the start of the
batch.
---
 scripts/loopback.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/scripts/loopback.py b/scripts/loopback.py
index e90b58d46..d8c68af89 100644
--- a/scripts/loopback.py
+++ b/scripts/loopback.py
@@ -38,6 +38,7 @@ class Script(scripts.Script):
 
         grids = []
         all_images = []
+        original_init_image = p.init_images
         state.job_count = loops * batch_count
 
         initial_color_corrections = [processing.setup_color_correction(p.init_images[0])]
@@ -45,6 +46,9 @@ class Script(scripts.Script):
         for n in range(batch_count):
             history = []
 
+            # Reset to original init image at the start of each batch
+            p.init_images = original_init_image
+
             for i in range(loops):
                 p.n_iter = 1
                 p.batch_size = 1

From a8490e4019c359ff24824e004059744d7164361b Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Tue, 11 Oct 2022 11:42:41 +0100
Subject: [PATCH 18/53] revert sr warning

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

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 10a82dc9f..99b3c4f64 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -35,7 +35,8 @@ def apply_prompt(p, x, xs):
     p.negative_prompt = p.negative_prompt.replace(xs[0], x)
 
     if p.prompt == orig_prompt and p.negative_prompt == orig_negative_prompt:
-        raise RuntimeError(f"Prompt S/R did not find {xs[0]} in prompt or negative prompt. Did you forget to add the token?")
+        pass
+        #raise RuntimeError(f"Prompt S/R did not find {xs[0]} in prompt or negative prompt. Did you forget to add the token?")
 
 
 def apply_order(p, x, xs):

From 1a0a6a84c3149e236211d547471f5416cd1129f3 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Tue, 11 Oct 2022 11:59:56 +0100
Subject: [PATCH 19/53] add incorrect start word guard to xy_grid (#2259)

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

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 99b3c4f64..9d4d6187e 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -27,17 +27,12 @@ def apply_field(field):
 
 
 def apply_prompt(p, x, xs):
-
-    orig_prompt = p.prompt
-    orig_negative_prompt = p.negative_prompt
+    if xs[0] not in p.prompt and xs[0] not in p.negative_prompt:
+        raise RuntimeError(f"Prompt S/R did not find {xs[0]} in prompt or negative prompt.")
 
     p.prompt = p.prompt.replace(xs[0], x)
     p.negative_prompt = p.negative_prompt.replace(xs[0], x)
 
-    if p.prompt == orig_prompt and p.negative_prompt == orig_negative_prompt:
-        pass
-        #raise RuntimeError(f"Prompt S/R did not find {xs[0]} in prompt or negative prompt. Did you forget to add the token?")
-
 
 def apply_order(p, x, xs):
     token_order = []

From 530103b586109c11fd068eb70ef09503ec6a4caf Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 14:53:02 +0300
Subject: [PATCH 20/53] fixes related to merge

---
 modules/hypernetwork.py                       | 103 ------------------
 modules/hypernetwork/hypernetwork.py          |  82 ++++++++------
 modules/hypernetwork/ui.py                    |  10 +-
 modules/sd_hijack_optimizations.py            |   3 +-
 modules/shared.py                             |  13 ++-
 .../textual_inversion/textual_inversion.py    |  12 +-
 modules/ui.py                                 |   5 +-
 scripts/xy_grid.py                            |   3 +-
 webui.py                                      |  15 +--
 9 files changed, 82 insertions(+), 164 deletions(-)
 delete mode 100644 modules/hypernetwork.py

diff --git a/modules/hypernetwork.py b/modules/hypernetwork.py
deleted file mode 100644
index 7bbc443e5..000000000
--- a/modules/hypernetwork.py
+++ /dev/null
@@ -1,103 +0,0 @@
-import glob
-import os
-import sys
-import traceback
-
-import torch
-
-from ldm.util import default
-from modules import devices, shared
-import torch
-from torch import einsum
-from einops import rearrange, repeat
-
-
-class HypernetworkModule(torch.nn.Module):
-    def __init__(self, dim, state_dict):
-        super().__init__()
-
-        self.linear1 = torch.nn.Linear(dim, dim * 2)
-        self.linear2 = torch.nn.Linear(dim * 2, dim)
-
-        self.load_state_dict(state_dict, strict=True)
-        self.to(devices.device)
-
-    def forward(self, x):
-        return x + (self.linear2(self.linear1(x)))
-
-
-class Hypernetwork:
-    filename = None
-    name = None
-
-    def __init__(self, filename):
-        self.filename = filename
-        self.name = os.path.splitext(os.path.basename(filename))[0]
-        self.layers = {}
-
-        state_dict = torch.load(filename, map_location='cpu')
-        for size, sd in state_dict.items():
-            self.layers[size] = (HypernetworkModule(size, sd[0]), HypernetworkModule(size, sd[1]))
-
-
-def list_hypernetworks(path):
-    res = {}
-    for filename in glob.iglob(os.path.join(path, '**/*.pt'), recursive=True):
-        name = os.path.splitext(os.path.basename(filename))[0]
-        res[name] = filename
-    return res
-
-
-def load_hypernetwork(filename):
-    path = shared.hypernetworks.get(filename, None)
-    if path is not None:
-        print(f"Loading hypernetwork {filename}")
-        try:
-            shared.loaded_hypernetwork = Hypernetwork(path)
-        except Exception:
-            print(f"Error loading hypernetwork {path}", file=sys.stderr)
-            print(traceback.format_exc(), file=sys.stderr)
-    else:
-        if shared.loaded_hypernetwork is not None:
-            print(f"Unloading hypernetwork")
-
-        shared.loaded_hypernetwork = None
-
-
-def apply_hypernetwork(hypernetwork, context):
-    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
-
-    if hypernetwork_layers is None:
-        return context, context
-
-    context_k = hypernetwork_layers[0](context)
-    context_v = hypernetwork_layers[1](context)
-    return context_k, context_v
-
-
-def attention_CrossAttention_forward(self, x, context=None, mask=None):
-    h = self.heads
-
-    q = self.to_q(x)
-    context = default(context, x)
-
-    context_k, context_v = apply_hypernetwork(shared.loaded_hypernetwork, context)
-    k = self.to_k(context_k)
-    v = self.to_v(context_v)
-
-    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
-
-    sim = einsum('b i d, b j d -> b i j', q, k) * self.scale
-
-    if mask is not None:
-        mask = rearrange(mask, 'b ... -> b (...)')
-        max_neg_value = -torch.finfo(sim.dtype).max
-        mask = repeat(mask, 'b j -> (b h) () j', h=h)
-        sim.masked_fill_(~mask, max_neg_value)
-
-    # attention, what we cannot get enough of
-    attn = sim.softmax(dim=-1)
-
-    out = einsum('b i j, b j d -> b i d', attn, v)
-    out = rearrange(out, '(b h) n d -> b n (h d)', h=h)
-    return self.to_out(out)
diff --git a/modules/hypernetwork/hypernetwork.py b/modules/hypernetwork/hypernetwork.py
index a3d6a47ef..aa701bda5 100644
--- a/modules/hypernetwork/hypernetwork.py
+++ b/modules/hypernetwork/hypernetwork.py
@@ -26,10 +26,11 @@ class HypernetworkModule(torch.nn.Module):
         if state_dict is not None:
             self.load_state_dict(state_dict, strict=True)
         else:
-            self.linear1.weight.data.fill_(0.0001)
-            self.linear1.bias.data.fill_(0.0001)
-            self.linear2.weight.data.fill_(0.0001)
-            self.linear2.bias.data.fill_(0.0001)
+
+            self.linear1.weight.data.normal_(mean=0.0, std=0.01)
+            self.linear1.bias.data.zero_()
+            self.linear2.weight.data.normal_(mean=0.0, std=0.01)
+            self.linear2.bias.data.zero_()
 
         self.to(devices.device)
 
@@ -92,41 +93,54 @@ class Hypernetwork:
         self.sd_checkpoint_name = state_dict.get('sd_checkpoint_name', None)
 
 
-def load_hypernetworks(path):
+def list_hypernetworks(path):
     res = {}
-
-    for filename in glob.iglob(path + '**/*.pt', recursive=True):
-        try:
-            hn = Hypernetwork()
-            hn.load(filename)
-            res[hn.name] = hn
-        except Exception:
-            print(f"Error loading hypernetwork {filename}", file=sys.stderr)
-            print(traceback.format_exc(), file=sys.stderr)
-
+    for filename in glob.iglob(os.path.join(path, '**/*.pt'), recursive=True):
+        name = os.path.splitext(os.path.basename(filename))[0]
+        res[name] = filename
     return res
 
 
+def load_hypernetwork(filename):
+    path = shared.hypernetworks.get(filename, None)
+    if path is not None:
+        print(f"Loading hypernetwork {filename}")
+        try:
+            shared.loaded_hypernetwork = Hypernetwork()
+            shared.loaded_hypernetwork.load(path)
+
+        except Exception:
+            print(f"Error loading hypernetwork {path}", file=sys.stderr)
+            print(traceback.format_exc(), file=sys.stderr)
+    else:
+        if shared.loaded_hypernetwork is not None:
+            print(f"Unloading hypernetwork")
+
+        shared.loaded_hypernetwork = None
+
+
+def apply_hypernetwork(hypernetwork, context, layer=None):
+    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
+
+    if hypernetwork_layers is None:
+        return context, context
+
+    if layer is not None:
+        layer.hyper_k = hypernetwork_layers[0]
+        layer.hyper_v = hypernetwork_layers[1]
+
+    context_k = hypernetwork_layers[0](context)
+    context_v = hypernetwork_layers[1](context)
+    return context_k, context_v
+
+
 def attention_CrossAttention_forward(self, x, context=None, mask=None):
     h = self.heads
 
     q = self.to_q(x)
     context = default(context, x)
 
-    hypernetwork_layers = (shared.hypernetwork.layers if shared.hypernetwork is not None else {}).get(context.shape[2], None)
-
-    if hypernetwork_layers is not None:
-        hypernetwork_k, hypernetwork_v = hypernetwork_layers
-
-        self.hypernetwork_k = hypernetwork_k
-        self.hypernetwork_v = hypernetwork_v
-
-        context_k = hypernetwork_k(context)
-        context_v = hypernetwork_v(context)
-    else:
-        context_k = context
-        context_v = context
-
+    context_k, context_v = apply_hypernetwork(shared.loaded_hypernetwork, context, self)
     k = self.to_k(context_k)
     v = self.to_v(context_v)
 
@@ -151,7 +165,9 @@ def attention_CrossAttention_forward(self, x, context=None, mask=None):
 def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_image_prompt):
     assert hypernetwork_name, 'embedding not selected'
 
-    shared.hypernetwork = shared.hypernetworks[hypernetwork_name]
+    path = shared.hypernetworks.get(hypernetwork_name, None)
+    shared.loaded_hypernetwork = Hypernetwork()
+    shared.loaded_hypernetwork.load(path)
 
     shared.state.textinfo = "Initializing hypernetwork training..."
     shared.state.job_count = steps
@@ -176,9 +192,9 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
 
     shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
     with torch.autocast("cuda"):
-        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, size=512, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file)
+        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=512, height=512, repeats=1, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file)
 
-    hypernetwork = shared.hypernetworks[hypernetwork_name]
+    hypernetwork = shared.loaded_hypernetwork
     weights = hypernetwork.weights()
     for weight in weights:
         weight.requires_grad = True
@@ -194,7 +210,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
     if ititial_step > steps:
         return hypernetwork, filename
 
-    pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step)
+    pbar = tqdm.tqdm(enumerate(ds), total=steps - ititial_step)
     for i, (x, text) in pbar:
         hypernetwork.step = i + ititial_step
 
diff --git a/modules/hypernetwork/ui.py b/modules/hypernetwork/ui.py
index 525f978c5..f6d1d0a35 100644
--- a/modules/hypernetwork/ui.py
+++ b/modules/hypernetwork/ui.py
@@ -6,24 +6,24 @@ import gradio as gr
 import modules.textual_inversion.textual_inversion
 import modules.textual_inversion.preprocess
 from modules import sd_hijack, shared
+from modules.hypernetwork import hypernetwork
 
 
 def create_hypernetwork(name):
     fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt")
     assert not os.path.exists(fn), f"file {fn} already exists"
 
-    hypernetwork = modules.hypernetwork.hypernetwork.Hypernetwork(name=name)
-    hypernetwork.save(fn)
+    hypernet = modules.hypernetwork.hypernetwork.Hypernetwork(name=name)
+    hypernet.save(fn)
 
     shared.reload_hypernetworks()
-    shared.hypernetwork = shared.hypernetworks.get(shared.opts.sd_hypernetwork, None)
 
     return gr.Dropdown.update(choices=sorted([x for x in shared.hypernetworks.keys()])), f"Created: {fn}", ""
 
 
 def train_hypernetwork(*args):
 
-    initial_hypernetwork = shared.hypernetwork
+    initial_hypernetwork = shared.loaded_hypernetwork
 
     try:
         sd_hijack.undo_optimizations()
@@ -38,6 +38,6 @@ Hypernetwork saved to {html.escape(filename)}
     except Exception:
         raise
     finally:
-        shared.hypernetwork = initial_hypernetwork
+        shared.loaded_hypernetwork = initial_hypernetwork
         sd_hijack.apply_optimizations()
 
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index 25cb67a4e..27e571fcd 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -8,7 +8,8 @@ from torch import einsum
 from ldm.util import default
 from einops import rearrange
 
-from modules import shared, hypernetwork
+from modules import shared
+from modules.hypernetwork import hypernetwork
 
 
 if shared.cmd_opts.xformers or shared.cmd_opts.force_enable_xformers:
diff --git a/modules/shared.py b/modules/shared.py
index 14b40d70d..8753015e5 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -13,7 +13,8 @@ import modules.memmon
 import modules.sd_models
 import modules.styles
 import modules.devices as devices
-from modules import sd_samplers, hypernetwork
+from modules import sd_samplers
+from modules.hypernetwork import hypernetwork
 from modules.paths import models_path, script_path, sd_path
 
 sd_model_file = os.path.join(script_path, 'model.ckpt')
@@ -29,6 +30,7 @@ parser.add_argument("--no-half-vae", action='store_true', help="do not switch th
 parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware acceleration in browser)")
 parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI")
 parser.add_argument("--embeddings-dir", type=str, default=os.path.join(script_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)")
+parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_path, 'hypernetworks'), help="hypernetwork directory")
 parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui")
 parser.add_argument("--medvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a little speed for low VRM usage")
 parser.add_argument("--lowvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a lot of speed for very low VRM usage")
@@ -82,10 +84,17 @@ parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram
 xformers_available = False
 config_filename = cmd_opts.ui_settings_file
 
-hypernetworks = hypernetwork.list_hypernetworks(os.path.join(models_path, 'hypernetworks'))
+hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir)
 loaded_hypernetwork = None
 
 
+def reload_hypernetworks():
+    global hypernetworks
+
+    hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir)
+    hypernetwork.load_hypernetwork(opts.sd_hypernetwork)
+
+
 class State:
     skipped = False
     interrupted = False
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 5965c5a06..d69779504 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -156,7 +156,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'):
     return fn
 
 
-def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, num_repeats, create_image_every, save_embedding_every, template_file):
+def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, num_repeats, create_image_every, save_embedding_every, template_file, preview_image_prompt):
     assert embedding_name, 'embedding not selected'
 
     shared.state.textinfo = "Initializing textual inversion training..."
@@ -238,12 +238,14 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
         if embedding.step > 0 and images_dir is not None and embedding.step % create_image_every == 0:
             last_saved_image = os.path.join(images_dir, f'{embedding_name}-{embedding.step}.png')
 
+            preview_text = text if preview_image_prompt == "" else preview_image_prompt
+
             p = processing.StableDiffusionProcessingTxt2Img(
                 sd_model=shared.sd_model,
-                prompt=text,
+                prompt=preview_text,
                 steps=20,
-				height=training_height,
-				width=training_width,
+                height=training_height,
+                width=training_width,
                 do_not_save_grid=True,
                 do_not_save_samples=True,
             )
@@ -254,7 +256,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
             shared.state.current_image = image
             image.save(last_saved_image)
 
-            last_saved_image += f", prompt: {text}"
+            last_saved_image += f", prompt: {preview_text}"
 
         shared.state.job_no = embedding.step
 
diff --git a/modules/ui.py b/modules/ui.py
index 10b1ee3a9..df6530590 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1023,7 +1023,7 @@ def create_ui(wrap_gradio_gpu_call):
                             gr.HTML(value="")
 
                         with gr.Column():
-                            create_embedding = gr.Button(value="Create", variant='primary')
+                            create_embedding = gr.Button(value="Create embedding", variant='primary')
 
                 with gr.Group():
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Create a new hypernetwork</p>")
@@ -1035,7 +1035,7 @@ def create_ui(wrap_gradio_gpu_call):
                             gr.HTML(value="")
 
                         with gr.Column():
-                            create_hypernetwork = gr.Button(value="Create", variant='primary')
+                            create_hypernetwork = gr.Button(value="Create hypernetwork", variant='primary')
 
                 with gr.Group():
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Preprocess images</p>")
@@ -1147,6 +1147,7 @@ def create_ui(wrap_gradio_gpu_call):
                 create_image_every,
                 save_embedding_every,
                 template_file,
+                preview_image_prompt,
             ],
             outputs=[
                 ti_output,
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 42e1489c4..0af5993ce 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -10,7 +10,8 @@ import numpy as np
 import modules.scripts as scripts
 import gradio as gr
 
-from modules import images, hypernetwork
+from modules import images
+from modules.hypernetwork import hypernetwork
 from modules.processing import process_images, Processed, get_correct_sampler
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
diff --git a/webui.py b/webui.py
index 7c2005519..ba2156c84 100644
--- a/webui.py
+++ b/webui.py
@@ -29,6 +29,7 @@ from modules import devices
 from modules import modelloader
 from modules.paths import script_path
 from modules.shared import cmd_opts
+import modules.hypernetwork.hypernetwork
 
 modelloader.cleanup_models()
 modules.sd_models.setup_model()
@@ -77,22 +78,12 @@ def wrap_gradio_gpu_call(func, extra_outputs=None):
     return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs)
 
 
-def set_hypernetwork():
-    shared.hypernetwork = shared.hypernetworks.get(shared.opts.sd_hypernetwork, None)
-
-
-shared.reload_hypernetworks()
-shared.opts.onchange("sd_hypernetwork", set_hypernetwork)
-set_hypernetwork()
-
-
 modules.scripts.load_scripts(os.path.join(script_path, "scripts"))
 
 shared.sd_model = modules.sd_models.load_model()
 shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model)))
 
-loaded_hypernetwork = modules.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)
-shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)))
+shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetwork.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)))
 
 
 def webui():
@@ -117,7 +108,7 @@ def webui():
             prevent_thread_lock=True
         )
         
-        app.add_middleware(GZipMiddleware,minimum_size=1000)
+        app.add_middleware(GZipMiddleware, minimum_size=1000)
 
         while 1:
             time.sleep(0.5)

From 45ada1c91025e221df04f911de6377e419f19e3f Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Tue, 11 Oct 2022 13:10:11 +0100
Subject: [PATCH 21/53] Correct list style, apply gen forever to both tabs,
 roll3 on both tabs

---
 javascript/contextMenus.js | 24 ++++++++++++++++--------
 1 file changed, 16 insertions(+), 8 deletions(-)

diff --git a/javascript/contextMenus.js b/javascript/contextMenus.js
index 7852793c1..4e7720658 100644
--- a/javascript/contextMenus.js
+++ b/javascript/contextMenus.js
@@ -16,7 +16,7 @@ contextMenuInit = function(){
       oldMenu.remove()
     }
 
-    let tabButton = gradioApp().querySelector('button')
+    let tabButton = uiCurrentTab
     let baseStyle = window.getComputedStyle(tabButton)
 
     const contextMenu = document.createElement('nav')
@@ -130,9 +130,9 @@ addContextMenuEventListener = initResponse[2]
 
 
 //Start example Context Menu Items
-generateOnRepeatId = appendContextMenuOption('#txt2img_generate','Generate forever',function(){
-  let genbutton = gradioApp().querySelector('#txt2img_generate');
-  let interruptbutton = gradioApp().querySelector('#txt2img_interrupt');
+generateOnRepeat = function(genbuttonid,interruptbuttonid){
+  let genbutton = gradioApp().querySelector(genbuttonid);
+  let interruptbutton = gradioApp().querySelector(interruptbuttonid);
   if(!interruptbutton.offsetParent){
     genbutton.click();
   }
@@ -142,8 +142,15 @@ generateOnRepeatId = appendContextMenuOption('#txt2img_generate','Generate forev
       genbutton.click();
     }
   },
-  500)}
-)
+  500)
+}
+
+generateOnRepeatId = appendContextMenuOption('#txt2img_generate','Generate forever',function(){
+  generateOnRepeat('#txt2img_generate','#txt2img_interrupt');
+})
+generateOnRepeatId = appendContextMenuOption('#img2img_generate','Generate forever',function(){
+  generateOnRepeat('#img2img_generate','#img2img_interrupt');
+})
 
 cancelGenerateForever = function(){ 
   clearInterval(window.generateOnRepeatInterval) 
@@ -151,11 +158,12 @@ cancelGenerateForever = function(){
 
 appendContextMenuOption('#txt2img_interrupt','Cancel generate forever',cancelGenerateForever)
 appendContextMenuOption('#txt2img_generate', 'Cancel generate forever',cancelGenerateForever)
-
+appendContextMenuOption('#img2img_interrupt','Cancel generate forever',cancelGenerateForever)
+appendContextMenuOption('#img2img_generate', 'Cancel generate forever',cancelGenerateForever)
 
 appendContextMenuOption('#roll','Roll three',
   function(){ 
-    let rollbutton = gradioApp().querySelector('#roll');
+    let rollbutton = get_uiCurrentTabContent().querySelector('#roll');
     setTimeout(function(){rollbutton.click()},100)
     setTimeout(function(){rollbutton.click()},200)
     setTimeout(function(){rollbutton.click()},300)

From 9b8faefde05464fe6ba51668fe1d361e4fe22339 Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Tue, 11 Oct 2022 13:19:16 +0100
Subject: [PATCH 22/53] context menus closure

---
 javascript/contextMenus.js | 83 +++++++++++++++++++-------------------
 1 file changed, 42 insertions(+), 41 deletions(-)

diff --git a/javascript/contextMenus.js b/javascript/contextMenus.js
index 4e7720658..7636c4b33 100644
--- a/javascript/contextMenus.js
+++ b/javascript/contextMenus.js
@@ -123,52 +123,53 @@ contextMenuInit = function(){
   return [appendContextMenuOption, removeContextMenuOption, addContextMenuEventListener]
 }
 
-initResponse = contextMenuInit()
-appendContextMenuOption     = initResponse[0]
-removeContextMenuOption     = initResponse[1]
-addContextMenuEventListener = initResponse[2]
+initResponse = contextMenuInit();
+appendContextMenuOption     = initResponse[0];
+removeContextMenuOption     = initResponse[1];
+addContextMenuEventListener = initResponse[2];
 
-
-//Start example Context Menu Items
-generateOnRepeat = function(genbuttonid,interruptbuttonid){
-  let genbutton = gradioApp().querySelector(genbuttonid);
-  let interruptbutton = gradioApp().querySelector(interruptbuttonid);
-  if(!interruptbutton.offsetParent){
-    genbutton.click();
-  }
-  clearInterval(window.generateOnRepeatInterval)
-  window.generateOnRepeatInterval = setInterval(function(){
+(function(){
+  //Start example Context Menu Items
+  let generateOnRepeat = function(genbuttonid,interruptbuttonid){
+    let genbutton = gradioApp().querySelector(genbuttonid);
+    let interruptbutton = gradioApp().querySelector(interruptbuttonid);
     if(!interruptbutton.offsetParent){
       genbutton.click();
     }
-  },
-  500)
-}
-
-generateOnRepeatId = appendContextMenuOption('#txt2img_generate','Generate forever',function(){
-  generateOnRepeat('#txt2img_generate','#txt2img_interrupt');
-})
-generateOnRepeatId = appendContextMenuOption('#img2img_generate','Generate forever',function(){
-  generateOnRepeat('#img2img_generate','#img2img_interrupt');
-})
-
-cancelGenerateForever = function(){ 
-  clearInterval(window.generateOnRepeatInterval) 
-}
-
-appendContextMenuOption('#txt2img_interrupt','Cancel generate forever',cancelGenerateForever)
-appendContextMenuOption('#txt2img_generate', 'Cancel generate forever',cancelGenerateForever)
-appendContextMenuOption('#img2img_interrupt','Cancel generate forever',cancelGenerateForever)
-appendContextMenuOption('#img2img_generate', 'Cancel generate forever',cancelGenerateForever)
-
-appendContextMenuOption('#roll','Roll three',
-  function(){ 
-    let rollbutton = get_uiCurrentTabContent().querySelector('#roll');
-    setTimeout(function(){rollbutton.click()},100)
-    setTimeout(function(){rollbutton.click()},200)
-    setTimeout(function(){rollbutton.click()},300)
+    clearInterval(window.generateOnRepeatInterval)
+    window.generateOnRepeatInterval = setInterval(function(){
+      if(!interruptbutton.offsetParent){
+        genbutton.click();
+      }
+    },
+    500)
   }
-)
+
+  appendContextMenuOption('#txt2img_generate','Generate forever',function(){
+    generateOnRepeat('#txt2img_generate','#txt2img_interrupt');
+  })
+  appendContextMenuOption('#img2img_generate','Generate forever',function(){
+    generateOnRepeat('#img2img_generate','#img2img_interrupt');
+  })
+
+  let cancelGenerateForever = function(){ 
+    clearInterval(window.generateOnRepeatInterval) 
+  }
+
+  appendContextMenuOption('#txt2img_interrupt','Cancel generate forever',cancelGenerateForever)
+  appendContextMenuOption('#txt2img_generate', 'Cancel generate forever',cancelGenerateForever)
+  appendContextMenuOption('#img2img_interrupt','Cancel generate forever',cancelGenerateForever)
+  appendContextMenuOption('#img2img_generate', 'Cancel generate forever',cancelGenerateForever)
+
+  appendContextMenuOption('#roll','Roll three',
+    function(){ 
+      let rollbutton = get_uiCurrentTabContent().querySelector('#roll');
+      setTimeout(function(){rollbutton.click()},100)
+      setTimeout(function(){rollbutton.click()},200)
+      setTimeout(function(){rollbutton.click()},300)
+    }
+  )
+})();
 //End example Context Menu Items
 
 onUiUpdate(function(){

From 92d7a138857b308c97a8d009848f642aeb93d6c8 Mon Sep 17 00:00:00 2001
From: Martin Cairns <Martin.Cairns+github@gmail.com>
Date: Tue, 11 Oct 2022 00:02:44 +0100
Subject: [PATCH 23/53] Handle different parameters for DPM fast & adaptive

---
 modules/sd_samplers.py | 25 ++++++++++++++++++-------
 1 file changed, 18 insertions(+), 7 deletions(-)

diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index d168b938f..eee52e7d7 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -57,7 +57,7 @@ def set_samplers():
     global samplers, samplers_for_img2img
 
     hidden = set(opts.hide_samplers)
-    hidden_img2img = set(opts.hide_samplers + ['PLMS', 'DPM fast', 'DPM adaptive'])
+    hidden_img2img = set(opts.hide_samplers + ['PLMS'])
 
     samplers = [x for x in all_samplers if x.name not in hidden]
     samplers_for_img2img = [x for x in all_samplers if x.name not in hidden_img2img]
@@ -365,16 +365,27 @@ class KDiffusionSampler:
         else:
             sigmas = self.model_wrap.get_sigmas(steps)
 
-        noise = noise * sigmas[steps - t_enc - 1]
-        xi = x + noise
-
-        extra_params_kwargs = self.initialize(p)
-
         sigma_sched = sigmas[steps - t_enc - 1:]
+        print('check values same', sigmas[steps - t_enc - 1] , sigma_sched[0], sigmas[steps - t_enc - 1] - sigma_sched[0])
+        xi = x + noise * sigma_sched[0]
+        
+        extra_params_kwargs = self.initialize(p)
+        if 'sigma_min' in inspect.signature(self.func).parameters:
+            ## last sigma is zero which is allowed by DPM Fast & Adaptive so taking value before last
+            extra_params_kwargs['sigma_min'] = sigma_sched[-2]
+        if 'sigma_max' in inspect.signature(self.func).parameters:
+            extra_params_kwargs['sigma_max'] = sigma_sched[0]
+        if 'n' in inspect.signature(self.func).parameters:
+            extra_params_kwargs['n'] = len(sigma_sched) - 1
+        if 'sigma_sched' in inspect.signature(self.func).parameters:
+            extra_params_kwargs['sigma_sched'] = sigma_sched
+        if 'sigmas' in inspect.signature(self.func).parameters:
+            extra_params_kwargs['sigmas'] = sigma_sched
 
         self.model_wrap_cfg.init_latent = x
 
-        return self.func(self.model_wrap_cfg, xi, sigma_sched, extra_args={'cond': conditioning, 'uncond': unconditional_conditioning, 'cond_scale': p.cfg_scale}, disable=False, callback=self.callback_state, **extra_params_kwargs)
+        return self.func(self.model_wrap_cfg, xi, extra_args={'cond': conditioning, 'uncond': unconditional_conditioning, 'cond_scale': p.cfg_scale}, disable=False, callback=self.callback_state, **extra_params_kwargs)
+
 
     def sample(self, p, x, conditioning, unconditional_conditioning, steps=None):
         steps = steps or p.steps

From 1eae3076078f00ecc5d0fac3c77fffb85cd2eb77 Mon Sep 17 00:00:00 2001
From: Martin Cairns <Martin.Cairns+github@gmail.com>
Date: Tue, 11 Oct 2022 00:04:06 +0100
Subject: [PATCH 24/53] Remove debug code for checking that first sigma value
 is same after code cleanup

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

diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index eee52e7d7..32272916f 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -366,7 +366,6 @@ class KDiffusionSampler:
             sigmas = self.model_wrap.get_sigmas(steps)
 
         sigma_sched = sigmas[steps - t_enc - 1:]
-        print('check values same', sigmas[steps - t_enc - 1] , sigma_sched[0], sigmas[steps - t_enc - 1] - sigma_sched[0])
         xi = x + noise * sigma_sched[0]
         
         extra_params_kwargs = self.initialize(p)

From eacc03b16730bcc5be95cda2d7c966ff1b4a8263 Mon Sep 17 00:00:00 2001
From: Martin Cairns <Martin.Cairns+github@gmail.com>
Date: Tue, 11 Oct 2022 00:36:00 +0100
Subject: [PATCH 25/53] Fix typo in comments

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

diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index 32272916f..20309e06b 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -370,7 +370,7 @@ class KDiffusionSampler:
         
         extra_params_kwargs = self.initialize(p)
         if 'sigma_min' in inspect.signature(self.func).parameters:
-            ## last sigma is zero which is allowed by DPM Fast & Adaptive so taking value before last
+            ## last sigma is zero which isn't allowed by DPM Fast & Adaptive so taking value before last
             extra_params_kwargs['sigma_min'] = sigma_sched[-2]
         if 'sigma_max' in inspect.signature(self.func).parameters:
             extra_params_kwargs['sigma_max'] = sigma_sched[0]

From b372f5538bee4feba87080af4f3acf1e437accc6 Mon Sep 17 00:00:00 2001
From: Ben <110583491+TheLastBen@users.noreply.github.com>
Date: Mon, 10 Oct 2022 19:34:07 +0100
Subject: [PATCH 26/53] Save some space

---
 style.css | 12 ++++++++++++
 1 file changed, 12 insertions(+)

diff --git a/style.css b/style.css
index 00a3d07fe..38410ca44 100644
--- a/style.css
+++ b/style.css
@@ -2,6 +2,18 @@
     max-width: 100%;
 }
 
+#txt2img_token_counter {
+    height: 0px;
+}
+
+#img2img_token_counter {
+    height: 0px;
+}
+
+#negative_prompt {
+    width: 97.9%;
+}
+
 .output-html p {margin: 0 0.5em;}
 
 .row > *,

From 87b77cad5f3017c952a7dfec0e7904a9df5b72fd Mon Sep 17 00:00:00 2001
From: Ben <110583491+TheLastBen@users.noreply.github.com>
Date: Mon, 10 Oct 2022 19:37:16 +0100
Subject: [PATCH 27/53] Layout fix

---
 modules/ui.py | 28 ++++++++++++++--------------
 1 file changed, 14 insertions(+), 14 deletions(-)

diff --git a/modules/ui.py b/modules/ui.py
index df6530590..de4cd7f23 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -550,15 +550,15 @@ def create_ui(wrap_gradio_gpu_call):
                         button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder'
                         open_txt2img_folder = gr.Button(folder_symbol, elem_id=button_id)
 
-                    with gr.Row():
-                        do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
+                with gr.Row():
+                    do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
                     
-                    with gr.Row():
-                        download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
+                with gr.Row():
+                    download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
 
-                with gr.Group():
-                    html_info = gr.HTML()
-                    generation_info = gr.Textbox(visible=False)
+                    with gr.Group():
+                        html_info = gr.HTML()
+                        generation_info = gr.Textbox(visible=False)
 
             connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
             connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
@@ -738,15 +738,15 @@ def create_ui(wrap_gradio_gpu_call):
                         button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder'
                         open_img2img_folder = gr.Button(folder_symbol, elem_id=button_id)
 
-                    with gr.Row():
-                        do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
+                with gr.Row():
+                    do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
                     
-                    with gr.Row():
-                        download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
+                with gr.Row():
+                    download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
 
-                with gr.Group():
-                    html_info = gr.HTML()
-                    generation_info = gr.Textbox(visible=False)
+                    with gr.Group():
+                        html_info = gr.HTML()
+                        generation_info = gr.Textbox(visible=False)
 
             connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
             connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)

From 861297cefe2bb663f4e09dd4778a4cb93ebe8ff1 Mon Sep 17 00:00:00 2001
From: Ben <110583491+TheLastBen@users.noreply.github.com>
Date: Tue, 11 Oct 2022 08:08:45 +0100
Subject: [PATCH 28/53] add a space holder

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

diff --git a/modules/ui.py b/modules/ui.py
index de4cd7f23..fc0f3d3cb 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -429,7 +429,10 @@ def create_toprow(is_img2img):
 
             with gr.Row():
                 with gr.Column(scale=8):
-                    negative_prompt = gr.Textbox(label="Negative prompt", elem_id="negative_prompt", show_label=False, placeholder="Negative prompt", lines=2)
+                    with gr.Row():
+                        negative_prompt = gr.Textbox(label="Negative prompt", elem_id="negative_prompt", show_label=False, placeholder="Negative prompt", lines=2)
+                with gr.Column(scale=1, elem_id="roll_col"):
+                    sh = gr.Button(elem_id="sh", visible=True)                           
 
                 with gr.Column(scale=1, elem_id="style_neg_col"):
                     prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())), visible=len(shared.prompt_styles.styles) > 1)

From 031dc8cd7fa6bc74b44114715b28e0737342de37 Mon Sep 17 00:00:00 2001
From: Ben <110583491+TheLastBen@users.noreply.github.com>
Date: Tue, 11 Oct 2022 08:08:47 +0100
Subject: [PATCH 29/53] space holder

---
 style.css | 12 ++++++++++--
 1 file changed, 10 insertions(+), 2 deletions(-)

diff --git a/style.css b/style.css
index 38410ca44..d1c866fcb 100644
--- a/style.css
+++ b/style.css
@@ -10,8 +10,16 @@
     height: 0px;
 }
 
-#negative_prompt {
-    width: 97.9%;
+#sh{
+    min-width: 2em;
+    min-height: 2em;
+    max-width: 2em;
+    max-height: 2em;
+    flex-grow: 0;
+    padding-left: 0.25em;
+    padding-right: 0.25em;
+    margin: 0.1em 0;
+    opacity: 0%;
 }
 
 .output-html p {margin: 0 0.5em;}

From 54c519943a24881ea61af5a73dedbab92f9431ce Mon Sep 17 00:00:00 2001
From: Ben <110583491+TheLastBen@users.noreply.github.com>
Date: Tue, 11 Oct 2022 10:16:53 +0100
Subject: [PATCH 30/53] Update style.css

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

diff --git a/style.css b/style.css
index d1c866fcb..ecb51bb02 100644
--- a/style.css
+++ b/style.css
@@ -20,6 +20,7 @@
     padding-right: 0.25em;
     margin: 0.1em 0;
     opacity: 0%;
+    cursor: default;	
 }
 
 .output-html p {margin: 0 0.5em;}

From 210fd72babb8314b280a7b5ef8603c62024a22db Mon Sep 17 00:00:00 2001
From: parsec501 <105080989+parsec501@users.noreply.github.com>
Date: Tue, 11 Oct 2022 14:37:01 +0200
Subject: [PATCH 31/53] Added 'suggestion' flair to suggestion template

---
 .github/ISSUE_TEMPLATE/feature_request.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/ISSUE_TEMPLATE/feature_request.md b/.github/ISSUE_TEMPLATE/feature_request.md
index bbcbbe7d6..eda42fa7d 100644
--- a/.github/ISSUE_TEMPLATE/feature_request.md
+++ b/.github/ISSUE_TEMPLATE/feature_request.md
@@ -2,7 +2,7 @@
 name: Feature request
 about: Suggest an idea for this project
 title: ''
-labels: ''
+labels: 'suggestion'
 assignees: ''
 
 ---

From 4e485b79238666ace2b270045f73a12e5ccc7af9 Mon Sep 17 00:00:00 2001
From: JamnedZ <zaguzinegor@gmail.com>
Date: Tue, 11 Oct 2022 16:38:03 +0700
Subject: [PATCH 32/53] Added installation of pyngrok if needed

---
 launch.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/launch.py b/launch.py
index e1000f559..16627a032 100644
--- a/launch.py
+++ b/launch.py
@@ -104,6 +104,7 @@ def prepare_enviroment():
     args, skip_torch_cuda_test = extract_arg(args, '--skip-torch-cuda-test')
     xformers = '--xformers' in args
     deepdanbooru = '--deepdanbooru' in args
+    ngrok = '--ngrok' in args
 
     try:
         commit = run(f"{git} rev-parse HEAD").strip()
@@ -134,6 +135,9 @@ def prepare_enviroment():
     if not is_installed("deepdanbooru") and deepdanbooru:
         run_pip("install git+https://github.com/KichangKim/DeepDanbooru.git@edf73df4cdaeea2cf00e9ac08bd8a9026b7a7b26#egg=deepdanbooru[tensorflow] tensorflow==2.10.0 tensorflow-io==0.27.0", "deepdanbooru")
 
+    if not is_installed("pyngrok") and ngrok:
+        run_pip("install pyngrok", "ngrok")
+
     os.makedirs(dir_repos, exist_ok=True)
 
     git_clone("https://github.com/CompVis/stable-diffusion.git", repo_dir('stable-diffusion'), "Stable Diffusion", stable_diffusion_commit_hash)

From 59925644480b6fd84f6bb84b4df7d4fbc6a0cce8 Mon Sep 17 00:00:00 2001
From: JamnedZ <zaguzinegor@gmail.com>
Date: Tue, 11 Oct 2022 16:40:27 +0700
Subject: [PATCH 33/53] Cleaned ngrok integration

---
 modules/ngrok.py  | 15 +++++++++++++++
 modules/shared.py |  1 +
 modules/ui.py     |  5 +++++
 3 files changed, 21 insertions(+)
 create mode 100644 modules/ngrok.py

diff --git a/modules/ngrok.py b/modules/ngrok.py
new file mode 100644
index 000000000..17e6976f7
--- /dev/null
+++ b/modules/ngrok.py
@@ -0,0 +1,15 @@
+from pyngrok import ngrok, conf, exception
+
+
+def connect(token, port):
+    if token == None:
+        token = 'None'
+    conf.get_default().auth_token = token
+    try:
+        public_url = ngrok.connect(port).public_url
+    except exception.PyngrokNgrokError:
+        print(f'Invalid ngrok authtoken, ngrok connection aborted.\n'
+              f'Your token: {token}, get the right one on https://dashboard.ngrok.com/get-started/your-authtoken')
+    else:
+        print(f'ngrok connected to localhost:{port}! URL: {public_url}\n'
+               'You can use this link after the launch is complete.')
\ No newline at end of file
diff --git a/modules/shared.py b/modules/shared.py
index 8753015e5..375e3afb6 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -38,6 +38,7 @@ parser.add_argument("--always-batch-cond-uncond", action='store_true', help="dis
 parser.add_argument("--unload-gfpgan", action='store_true', help="does not do anything.")
 parser.add_argument("--precision", type=str, help="evaluate at this precision", choices=["full", "autocast"], default="autocast")
 parser.add_argument("--share", action='store_true', help="use share=True for gradio and make the UI accessible through their site (doesn't work for me but you might have better luck)")
+parser.add_argument("--ngrok", type=str, help="ngrok authtoken, alternative to gradio --share", default=None)
 parser.add_argument("--codeformer-models-path", type=str, help="Path to directory with codeformer model file(s).", default=os.path.join(models_path, 'Codeformer'))
 parser.add_argument("--gfpgan-models-path", type=str, help="Path to directory with GFPGAN model file(s).", default=os.path.join(models_path, 'GFPGAN'))
 parser.add_argument("--esrgan-models-path", type=str, help="Path to directory with ESRGAN model file(s).", default=os.path.join(models_path, 'ESRGAN'))
diff --git a/modules/ui.py b/modules/ui.py
index fc0f3d3cb..f57f32db7 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -51,6 +51,11 @@ if not cmd_opts.share and not cmd_opts.listen:
     gradio.utils.version_check = lambda: None
     gradio.utils.get_local_ip_address = lambda: '127.0.0.1'
 
+if cmd_opts.ngrok != None:
+    import modules.ngrok as ngrok
+    print('ngrok authtoken detected, trying to connect...')
+    ngrok.connect(cmd_opts.ngrok, cmd_opts.port if cmd_opts.port != None else 7860)
+
 
 def gr_show(visible=True):
     return {"visible": visible, "__type__": "update"}

From a004d1a855311b0d7ff2976a4e31b0247ad9d1f6 Mon Sep 17 00:00:00 2001
From: JamnedZ <zaguzinegor@gmail.com>
Date: Tue, 11 Oct 2022 16:48:27 +0700
Subject: [PATCH 34/53] Added new line at the end of ngrok.py

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

diff --git a/modules/ngrok.py b/modules/ngrok.py
index 17e6976f7..7d03a6df5 100644
--- a/modules/ngrok.py
+++ b/modules/ngrok.py
@@ -12,4 +12,4 @@ def connect(token, port):
               f'Your token: {token}, get the right one on https://dashboard.ngrok.com/get-started/your-authtoken')
     else:
         print(f'ngrok connected to localhost:{port}! URL: {public_url}\n'
-               'You can use this link after the launch is complete.')
\ No newline at end of file
+               'You can use this link after the launch is complete.')

From 873efeed49bb5197a42da18272115b326c5d68f3 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 15:51:22 +0300
Subject: [PATCH 35/53] rename hypernetwork dir to hypernetworks to prevent
 clash with an old filename that people who use zip instead of git clone will
 have

---
 modules/{hypernetwork => hypernetworks}/hypernetwork.py | 0
 modules/{hypernetwork => hypernetworks}/ui.py           | 2 +-
 modules/sd_hijack.py                                    | 2 +-
 modules/sd_hijack_optimizations.py                      | 2 +-
 modules/shared.py                                       | 2 +-
 modules/ui.py                                           | 2 +-
 scripts/xy_grid.py                                      | 2 +-
 webui.py                                                | 2 +-
 8 files changed, 7 insertions(+), 7 deletions(-)
 rename modules/{hypernetwork => hypernetworks}/hypernetwork.py (100%)
 rename modules/{hypernetwork => hypernetworks}/ui.py (92%)

diff --git a/modules/hypernetwork/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
similarity index 100%
rename from modules/hypernetwork/hypernetwork.py
rename to modules/hypernetworks/hypernetwork.py
diff --git a/modules/hypernetwork/ui.py b/modules/hypernetworks/ui.py
similarity index 92%
rename from modules/hypernetwork/ui.py
rename to modules/hypernetworks/ui.py
index f6d1d0a35..811bc31eb 100644
--- a/modules/hypernetwork/ui.py
+++ b/modules/hypernetworks/ui.py
@@ -6,7 +6,7 @@ import gradio as gr
 import modules.textual_inversion.textual_inversion
 import modules.textual_inversion.preprocess
 from modules import sd_hijack, shared
-from modules.hypernetwork import hypernetwork
+from modules.hypernetworks import hypernetwork
 
 
 def create_hypernetwork(name):
diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index f873049a9..f07ec0416 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -37,7 +37,7 @@ def apply_optimizations():
 
 
 def undo_optimizations():
-    from modules.hypernetwork import hypernetwork
+    from modules.hypernetworks import hypernetwork
 
     ldm.modules.attention.CrossAttention.forward = hypernetwork.attention_CrossAttention_forward
     ldm.modules.diffusionmodules.model.nonlinearity = diffusionmodules_model_nonlinearity
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index 27e571fcd..3349b9c3c 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -9,7 +9,7 @@ from ldm.util import default
 from einops import rearrange
 
 from modules import shared
-from modules.hypernetwork import hypernetwork
+from modules.hypernetworks import hypernetwork
 
 
 if shared.cmd_opts.xformers or shared.cmd_opts.force_enable_xformers:
diff --git a/modules/shared.py b/modules/shared.py
index 375e3afb6..1dc2ccf20 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -14,7 +14,7 @@ import modules.sd_models
 import modules.styles
 import modules.devices as devices
 from modules import sd_samplers
-from modules.hypernetwork import hypernetwork
+from modules.hypernetworks import hypernetwork
 from modules.paths import models_path, script_path, sd_path
 
 sd_model_file = os.path.join(script_path, 'model.ckpt')
diff --git a/modules/ui.py b/modules/ui.py
index f57f32db7..42e5d8663 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -39,7 +39,7 @@ import modules.generation_parameters_copypaste
 from modules import prompt_parser
 from modules.images import save_image
 import modules.textual_inversion.ui
-import modules.hypernetwork.ui
+import modules.hypernetworks.ui
 
 # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI
 mimetypes.init()
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 16918c99c..cddb192a7 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -11,7 +11,7 @@ import modules.scripts as scripts
 import gradio as gr
 
 from modules import images
-from modules.hypernetwork import hypernetwork
+from modules.hypernetworks import hypernetwork
 from modules.processing import process_images, Processed, get_correct_sampler
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
diff --git a/webui.py b/webui.py
index ba2156c84..faa38a0df 100644
--- a/webui.py
+++ b/webui.py
@@ -29,7 +29,7 @@ from modules import devices
 from modules import modelloader
 from modules.paths import script_path
 from modules.shared import cmd_opts
-import modules.hypernetwork.hypernetwork
+import modules.hypernetworks.hypernetwork
 
 modelloader.cleanup_models()
 modules.sd_models.setup_model()

From b0583be0884cd17dafb408fd79b52b2a0a972563 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 15:54:34 +0300
Subject: [PATCH 36/53] more renames

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

diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py
index 811bc31eb..e7540f41e 100644
--- a/modules/hypernetworks/ui.py
+++ b/modules/hypernetworks/ui.py
@@ -13,7 +13,7 @@ def create_hypernetwork(name):
     fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt")
     assert not os.path.exists(fn), f"file {fn} already exists"
 
-    hypernet = modules.hypernetwork.hypernetwork.Hypernetwork(name=name)
+    hypernet = modules.hypernetworks.hypernetwork.Hypernetwork(name=name)
     hypernet.save(fn)
 
     shared.reload_hypernetworks()
@@ -28,7 +28,7 @@ def train_hypernetwork(*args):
     try:
         sd_hijack.undo_optimizations()
 
-        hypernetwork, filename = modules.hypernetwork.hypernetwork.train_hypernetwork(*args)
+        hypernetwork, filename = modules.hypernetworks.hypernetwork.train_hypernetwork(*args)
 
         res = f"""
 Training {'interrupted' if shared.state.interrupted else 'finished'} at {hypernetwork.step} steps.
diff --git a/modules/ui.py b/modules/ui.py
index 42e5d8663..ee333c3b4 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1111,7 +1111,7 @@ def create_ui(wrap_gradio_gpu_call):
         )
 
         create_hypernetwork.click(
-            fn=modules.hypernetwork.ui.create_hypernetwork,
+            fn=modules.hypernetworks.ui.create_hypernetwork,
             inputs=[
                 new_hypernetwork_name,
             ],
@@ -1164,7 +1164,7 @@ def create_ui(wrap_gradio_gpu_call):
         )
 
         train_hypernetwork.click(
-            fn=wrap_gradio_gpu_call(modules.hypernetwork.ui.train_hypernetwork, extra_outputs=[gr.update()]),
+            fn=wrap_gradio_gpu_call(modules.hypernetworks.ui.train_hypernetwork, extra_outputs=[gr.update()]),
             _js="start_training_textual_inversion",
             inputs=[
                 train_hypernetwork_name,
diff --git a/webui.py b/webui.py
index faa38a0df..338f58e13 100644
--- a/webui.py
+++ b/webui.py
@@ -83,7 +83,7 @@ modules.scripts.load_scripts(os.path.join(script_path, "scripts"))
 shared.sd_model = modules.sd_models.load_model()
 shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model)))
 
-shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetwork.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)))
+shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetworks.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)))
 
 
 def webui():

From 5766ce21abc1986c94d8bd3279b6f4d5205ba984 Mon Sep 17 00:00:00 2001
From: ClashSAN <98228077+ClashSAN@users.noreply.github.com>
Date: Tue, 11 Oct 2022 13:20:03 +0000
Subject: [PATCH 37/53] Update README.md

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

diff --git a/README.md b/README.md
index 0e9387686..a10faa01a 100644
--- a/README.md
+++ b/README.md
@@ -69,7 +69,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
      - also supports weights for prompts: `a cat :1.2 AND a dog AND a penguin :2.2`
 - No token limit for prompts (original stable diffusion lets you use up to 75 tokens)
 - DeepDanbooru integration, creates danbooru style tags for anime prompts (add --deepdanbooru to commandline args)
-- [xformers](https://github.com/mv-lab/swin2sr), major speed increase for select cards: (add --xformers to commandline args)
+- [xformers](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers), major speed increase for select cards: (add --xformers to commandline args)
 
 ## Installation and Running
 Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for both [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended) and [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs.

From d01a2d01560b31937df1f3433d210c18f97d32fa Mon Sep 17 00:00:00 2001
From: papuSpartan <mcgpapu@gmail.com>
Date: Tue, 11 Oct 2022 08:03:31 -0500
Subject: [PATCH 38/53] move list refresh to webui.py and add stdout indicating
 it's doing so

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

diff --git a/modules/ui.py b/modules/ui.py
index 06ff118f8..ae9317a36 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -39,7 +39,6 @@ import modules.generation_parameters_copypaste
 from modules import prompt_parser
 from modules.images import save_image
 import modules.textual_inversion.ui
-from modules.sd_models import list_models
 
 # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI
 mimetypes.init()
@@ -1291,8 +1290,6 @@ Requested path was: {f}
             shared.state.interrupt()
             settings_interface.gradio_ref.do_restart = True
 
-            # refresh models so that new models/.ckpt's show up on reload
-            list_models()
 
         restart_gradio.click(
             fn=request_restart,
diff --git a/webui.py b/webui.py
index 270584f77..94098c4cd 100644
--- a/webui.py
+++ b/webui.py
@@ -124,6 +124,8 @@ def webui():
         modules.scripts.reload_scripts(os.path.join(script_path, "scripts"))
         print('Reloading modules: modules.ui')
         importlib.reload(modules.ui)
+        print('Refreshing Model List')
+        modules.sd_models.list_models()
         print('Restarting Gradio')
 
 

From 66b7d7584f0b44ce1316425808c27ca7df38293c Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 17:03:00 +0300
Subject: [PATCH 39/53] become even stricter with pickles no pickle shall pass
 thank you again, RyotaK

---
 modules/safe.py | 17 +++++++++++++++++
 1 file changed, 17 insertions(+)

diff --git a/modules/safe.py b/modules/safe.py
index 059174632..20be16a50 100644
--- a/modules/safe.py
+++ b/modules/safe.py
@@ -10,6 +10,7 @@ import torch
 import numpy
 import _codecs
 import zipfile
+import re
 
 
 # PyTorch 1.13 and later have _TypedStorage renamed to TypedStorage
@@ -54,11 +55,27 @@ class RestrictedUnpickler(pickle.Unpickler):
         raise pickle.UnpicklingError(f"global '{module}/{name}' is forbidden")
 
 
+allowed_zip_names = ["archive/data.pkl", "archive/version"]
+allowed_zip_names_re = re.compile(r"^archive/data/\d+$")
+
+
+def check_zip_filenames(filename, names):
+    for name in names:
+        if name in allowed_zip_names:
+            continue
+        if allowed_zip_names_re.match(name):
+            continue
+
+        raise Exception(f"bad file inside {filename}: {name}")
+
+
 def check_pt(filename):
     try:
 
         # new pytorch format is a zip file
         with zipfile.ZipFile(filename) as z:
+            check_zip_filenames(filename, z.namelist())
+
             with z.open('archive/data.pkl') as file:
                 unpickler = RestrictedUnpickler(file)
                 unpickler.load()

From e0ee5bf703996b33e6d97aa36e0973ceedc88503 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 17:08:03 +0300
Subject: [PATCH 40/53] add codeowners file so stop the great guys who are
 collaborating on the project from merging in PRs.

---
 CODEOWNERS | 1 +
 1 file changed, 1 insertion(+)
 create mode 100644 CODEOWNERS

diff --git a/CODEOWNERS b/CODEOWNERS
new file mode 100644
index 000000000..935fedcf2
--- /dev/null
+++ b/CODEOWNERS
@@ -0,0 +1 @@
+*       @AUTOMATIC1111

From c0484f1b986ce7acb0e3596f6089a191279f5442 Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Mon, 10 Oct 2022 22:48:54 -0400
Subject: [PATCH 41/53] Add cross-attention optimization from InvokeAI

* Add cross-attention optimization from InvokeAI (~30% speed improvement on MPS)
* Add command line option for it
* Make it default when CUDA is unavailable
---
 modules/sd_hijack.py               |  5 +-
 modules/sd_hijack_optimizations.py | 79 ++++++++++++++++++++++++++++++
 modules/shared.py                  |  5 +-
 3 files changed, 86 insertions(+), 3 deletions(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index f07ec0416..5a1b167fa 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -30,8 +30,11 @@ def apply_optimizations():
     elif cmd_opts.opt_split_attention_v1:
         print("Applying v1 cross attention optimization.")
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1
+    elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention_invokeai or not torch.cuda.is_available()):
+        print("Applying cross attention optimization (InvokeAI).")
+        ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_invokeAI
     elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention or torch.cuda.is_available()):
-        print("Applying cross attention optimization.")
+        print("Applying cross attention optimization (Doggettx).")
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward
         ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.cross_attention_attnblock_forward
 
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index 3349b9c3c..870226c50 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -1,6 +1,7 @@
 import math
 import sys
 import traceback
+import psutil
 
 import torch
 from torch import einsum
@@ -116,6 +117,84 @@ def split_cross_attention_forward(self, x, context=None, mask=None):
 
     return self.to_out(r2)
 
+# -- From https://github.com/invoke-ai/InvokeAI/blob/main/ldm/modules/attention.py (with hypernetworks support added) --
+
+mem_total_gb = psutil.virtual_memory().total // (1 << 30)
+
+def einsum_op_compvis(q, k, v):
+    s = einsum('b i d, b j d -> b i j', q, k)
+    s = s.softmax(dim=-1, dtype=s.dtype)
+    return einsum('b i j, b j d -> b i d', s, v)
+
+def einsum_op_slice_0(q, k, v, slice_size):
+    r = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device, dtype=q.dtype)
+    for i in range(0, q.shape[0], slice_size):
+        end = i + slice_size
+        r[i:end] = einsum_op_compvis(q[i:end], k[i:end], v[i:end])
+    return r
+
+def einsum_op_slice_1(q, k, v, slice_size):
+    r = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device, dtype=q.dtype)
+    for i in range(0, q.shape[1], slice_size):
+        end = i + slice_size
+        r[:, i:end] = einsum_op_compvis(q[:, i:end], k, v)
+    return r
+
+def einsum_op_mps_v1(q, k, v):
+    if q.shape[1] <= 4096: # (512x512) max q.shape[1]: 4096
+        return einsum_op_compvis(q, k, v)
+    else:
+        slice_size = math.floor(2**30 / (q.shape[0] * q.shape[1]))
+        return einsum_op_slice_1(q, k, v, slice_size)
+
+def einsum_op_mps_v2(q, k, v):
+    if mem_total_gb > 8 and q.shape[1] <= 4096:
+        return einsum_op_compvis(q, k, v)
+    else:
+        return einsum_op_slice_0(q, k, v, 1)
+
+def einsum_op_tensor_mem(q, k, v, max_tensor_mb):
+    size_mb = q.shape[0] * q.shape[1] * k.shape[1] * q.element_size() // (1 << 20)
+    if size_mb <= max_tensor_mb:
+        return einsum_op_compvis(q, k, v)
+    div = 1 << int((size_mb - 1) / max_tensor_mb).bit_length()
+    if div <= q.shape[0]:
+        return einsum_op_slice_0(q, k, v, q.shape[0] // div)
+    return einsum_op_slice_1(q, k, v, max(q.shape[1] // div, 1))
+
+def einsum_op(q, k, v):
+    if q.device.type == 'mps':
+        if mem_total_gb >= 32:
+            return einsum_op_mps_v1(q, k, v)
+        return einsum_op_mps_v2(q, k, v)
+
+    # Smaller slices are faster due to L2/L3/SLC caches.
+    # Tested on i7 with 8MB L3 cache.
+    return einsum_op_tensor_mem(q, k, v, 32)
+
+def split_cross_attention_forward_invokeAI(self, x, context=None, mask=None):
+    h = self.heads
+
+    q = self.to_q(x)
+    context = default(context, x)
+
+    hypernetwork = shared.loaded_hypernetwork
+    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
+
+    if hypernetwork_layers is not None:
+        k = self.to_k(hypernetwork_layers[0](context)) * self.scale
+        v = self.to_v(hypernetwork_layers[1](context))
+    else:
+        k = self.to_k(context) * self.scale
+        v = self.to_v(context)
+    del context, x
+
+    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
+    r = einsum_op(q, k, v)
+    return self.to_out(rearrange(r, '(b h) n d -> b n (h d)', h=h))
+
+# -- End of code from https://github.com/invoke-ai/InvokeAI/blob/main/ldm/modules/attention.py --
+
 def xformers_attention_forward(self, x, context=None, mask=None):
     h = self.heads
     q_in = self.to_q(x)
diff --git a/modules/shared.py b/modules/shared.py
index 1dc2ccf20..20b45f231 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -50,9 +50,10 @@ parser.add_argument("--ldsr-models-path", type=str, help="Path to directory with
 parser.add_argument("--xformers", action='store_true', help="enable xformers for cross attention layers")
 parser.add_argument("--force-enable-xformers", action='store_true', help="enable xformers for cross attention layers regardless of whether the checking code thinks you can run it; do not make bug reports if this fails to work")
 parser.add_argument("--deepdanbooru", action='store_true', help="enable deepdanbooru interrogator")
-parser.add_argument("--opt-split-attention", action='store_true', help="force-enables cross-attention layer optimization. By default, it's on for torch.cuda and off for other torch devices.")
-parser.add_argument("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization")
+parser.add_argument("--opt-split-attention", action='store_true', help="force-enables Doggettx's cross-attention layer optimization. By default, it's on for torch cuda.")
+parser.add_argument("--opt-split-attention-invokeai", action='store_true', help="force-enables InvokeAI's cross-attention layer optimization. By default, it's on when cuda is unavailable.")
 parser.add_argument("--opt-split-attention-v1", action='store_true', help="enable older version of split attention optimization that does not consume all the VRAM it can find")
+parser.add_argument("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization")
 parser.add_argument("--use-cpu", nargs='+',choices=['SD', 'GFPGAN', 'BSRGAN', 'ESRGAN', 'SCUNet', 'CodeFormer'], help="use CPU as torch device for specified modules", default=[])
 parser.add_argument("--listen", action='store_true', help="launch gradio with 0.0.0.0 as server name, allowing to respond to network requests")
 parser.add_argument("--port", type=int, help="launch gradio with given server port, you need root/admin rights for ports < 1024, defaults to 7860 if available", default=None)

From 98fd5cde72d5bda1620ab78416c7828fdc3dc10b Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Mon, 10 Oct 2022 23:55:48 -0400
Subject: [PATCH 42/53] Add check for psutil

---
 modules/sd_hijack.py               | 10 ++++++++--
 modules/sd_hijack_optimizations.py | 19 +++++++++++++++----
 2 files changed, 23 insertions(+), 6 deletions(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 5a1b167fa..ac70f8767 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -10,6 +10,7 @@ from torch.nn.functional import silu
 import modules.textual_inversion.textual_inversion
 from modules import prompt_parser, devices, sd_hijack_optimizations, shared
 from modules.shared import opts, device, cmd_opts
+from modules.sd_hijack_optimizations import invokeAI_mps_available
 
 import ldm.modules.attention
 import ldm.modules.diffusionmodules.model
@@ -31,8 +32,13 @@ def apply_optimizations():
         print("Applying v1 cross attention optimization.")
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1
     elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention_invokeai or not torch.cuda.is_available()):
-        print("Applying cross attention optimization (InvokeAI).")
-        ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_invokeAI
+        if not invokeAI_mps_available and shared.device.type == 'mps':
+            print("The InvokeAI cross attention optimization for MPS requires the psutil package which is not installed.")
+            print("Applying v1 cross attention optimization.")
+            ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1
+        else:
+            print("Applying cross attention optimization (InvokeAI).")
+            ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_invokeAI
     elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention or torch.cuda.is_available()):
         print("Applying cross attention optimization (Doggettx).")
         ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index 870226c50..2a4ac7e00 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -1,7 +1,7 @@
 import math
 import sys
 import traceback
-import psutil
+import importlib
 
 import torch
 from torch import einsum
@@ -117,9 +117,20 @@ def split_cross_attention_forward(self, x, context=None, mask=None):
 
     return self.to_out(r2)
 
-# -- From https://github.com/invoke-ai/InvokeAI/blob/main/ldm/modules/attention.py (with hypernetworks support added) --
 
-mem_total_gb = psutil.virtual_memory().total // (1 << 30)
+def check_for_psutil():
+    try:
+        spec = importlib.util.find_spec('psutil')
+        return spec is not None
+    except ModuleNotFoundError:
+        return False
+
+invokeAI_mps_available = check_for_psutil()
+
+# -- Taken from https://github.com/invoke-ai/InvokeAI --
+if invokeAI_mps_available:
+    import psutil
+    mem_total_gb = psutil.virtual_memory().total // (1 << 30)
 
 def einsum_op_compvis(q, k, v):
     s = einsum('b i d, b j d -> b i j', q, k)
@@ -193,7 +204,7 @@ def split_cross_attention_forward_invokeAI(self, x, context=None, mask=None):
     r = einsum_op(q, k, v)
     return self.to_out(rearrange(r, '(b h) n d -> b n (h d)', h=h))
 
-# -- End of code from https://github.com/invoke-ai/InvokeAI/blob/main/ldm/modules/attention.py --
+# -- End of code from https://github.com/invoke-ai/InvokeAI --
 
 def xformers_attention_forward(self, x, context=None, mask=None):
     h = self.heads

From 574c8e554a5371eca2cbf344764cb241c6ec4efc Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Tue, 11 Oct 2022 03:32:11 -0400
Subject: [PATCH 43/53] Add InvokeAI and lstein to credits, add back CUDA
 support

---
 README.md                          |  1 +
 modules/sd_hijack_optimizations.py | 13 +++++++++++++
 2 files changed, 14 insertions(+)

diff --git a/README.md b/README.md
index a10faa01a..859a91b6f 100644
--- a/README.md
+++ b/README.md
@@ -123,6 +123,7 @@ The documentation was moved from this README over to the project's [wiki](https:
 - LDSR - https://github.com/Hafiidz/latent-diffusion
 - Ideas for optimizations - https://github.com/basujindal/stable-diffusion
 - Doggettx - Cross Attention layer optimization - https://github.com/Doggettx/stable-diffusion, original idea for prompt editing.
+- InvokeAI, lstein - Cross Attention layer optimization - https://github.com/invoke-ai/InvokeAI (originally http://github.com/lstein/stable-diffusion)
 - Rinon Gal - Textual Inversion - https://github.com/rinongal/textual_inversion (we're not using his code, but we are using his ideas).
 - Idea for SD upscale - https://github.com/jquesnelle/txt2imghd
 - Noise generation for outpainting mk2 - https://github.com/parlance-zz/g-diffuser-bot
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index 2a4ac7e00..f006427f8 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -173,7 +173,20 @@ def einsum_op_tensor_mem(q, k, v, max_tensor_mb):
         return einsum_op_slice_0(q, k, v, q.shape[0] // div)
     return einsum_op_slice_1(q, k, v, max(q.shape[1] // div, 1))
 
+def einsum_op_cuda(q, k, v):
+    stats = torch.cuda.memory_stats(q.device)
+    mem_active = stats['active_bytes.all.current']
+    mem_reserved = stats['reserved_bytes.all.current']
+    mem_free_cuda, _ = torch.cuda.mem_get_info(q.device)
+    mem_free_torch = mem_reserved - mem_active
+    mem_free_total = mem_free_cuda + mem_free_torch
+    # Divide factor of safety as there's copying and fragmentation
+    return self.einsum_op_tensor_mem(q, k, v, mem_free_total / 3.3 / (1 << 20))
+
 def einsum_op(q, k, v):
+    if q.device.type == 'cuda':
+        return einsum_op_cuda(q, k, v)
+
     if q.device.type == 'mps':
         if mem_total_gb >= 32:
             return einsum_op_mps_v1(q, k, v)

From 861db783c7acfcb93cf0b5191db3d50f9a9bc531 Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Tue, 11 Oct 2022 05:13:17 -0400
Subject: [PATCH 44/53] Use apply_hypernetwork function

---
 modules/sd_hijack_optimizations.py | 14 ++++----------
 1 file changed, 4 insertions(+), 10 deletions(-)

diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index f006427f8..79405525e 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -202,16 +202,10 @@ def split_cross_attention_forward_invokeAI(self, x, context=None, mask=None):
     q = self.to_q(x)
     context = default(context, x)
 
-    hypernetwork = shared.loaded_hypernetwork
-    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)
-
-    if hypernetwork_layers is not None:
-        k = self.to_k(hypernetwork_layers[0](context)) * self.scale
-        v = self.to_v(hypernetwork_layers[1](context))
-    else:
-        k = self.to_k(context) * self.scale
-        v = self.to_v(context)
-    del context, x
+    context_k, context_v = hypernetwork.apply_hypernetwork(shared.loaded_hypernetwork, context)
+    k = self.to_k(context_k) * self.scale
+    v = self.to_v(context_v)
+    del context, context_k, context_v, x
 
     q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
     r = einsum_op(q, k, v)

From 5ba23cb41f28f5856a7f64cb0d95e1e94dce90af Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 17:28:17 +0300
Subject: [PATCH 45/53] change default for XY plot's Y to Nothing.

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

diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index cddb192a7..ef4311054 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -197,7 +197,7 @@ class Script(scripts.Script):
             x_values = gr.Textbox(label="X values", visible=False, lines=1)
 
         with gr.Row():
-            y_type = gr.Dropdown(label="Y type", choices=[x.label for x in current_axis_options], value=current_axis_options[4].label, visible=False, type="index", elem_id="y_type")
+            y_type = gr.Dropdown(label="Y type", choices=[x.label for x in current_axis_options], value=current_axis_options[0].label, visible=False, type="index", elem_id="y_type")
             y_values = gr.Textbox(label="Y values", visible=False, lines=1)
         
         draw_legend = gr.Checkbox(label='Draw legend', value=True)

From d682444ecc99319fbd2b142a12727501e2884ba7 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 18:04:47 +0300
Subject: [PATCH 46/53] add option to select hypernetwork modules when creating

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

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index aa701bda5..b081f14e9 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -42,7 +42,7 @@ class Hypernetwork:
     filename = None
     name = None
 
-    def __init__(self, name=None):
+    def __init__(self, name=None, enable_sizes=None):
         self.filename = None
         self.name = name
         self.layers = {}
@@ -50,7 +50,7 @@ class Hypernetwork:
         self.sd_checkpoint = None
         self.sd_checkpoint_name = None
 
-        for size in [320, 640, 768, 1280]:
+        for size in enable_sizes or [320, 640, 768, 1280]:
             self.layers[size] = (HypernetworkModule(size), HypernetworkModule(size))
 
     def weights(self):
diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py
index e7540f41e..cdddcce1a 100644
--- a/modules/hypernetworks/ui.py
+++ b/modules/hypernetworks/ui.py
@@ -9,11 +9,11 @@ from modules import sd_hijack, shared
 from modules.hypernetworks import hypernetwork
 
 
-def create_hypernetwork(name):
+def create_hypernetwork(name, enable_sizes):
     fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt")
     assert not os.path.exists(fn), f"file {fn} already exists"
 
-    hypernet = modules.hypernetworks.hypernetwork.Hypernetwork(name=name)
+    hypernet = modules.hypernetworks.hypernetwork.Hypernetwork(name=name, enable_sizes=[int(x) for x in enable_sizes])
     hypernet.save(fn)
 
     shared.reload_hypernetworks()
diff --git a/modules/ui.py b/modules/ui.py
index f2d16b120..14b87b927 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1037,6 +1037,7 @@ def create_ui(wrap_gradio_gpu_call):
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Create a new hypernetwork</p>")
 
                     new_hypernetwork_name = gr.Textbox(label="Name")
+                    new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"])
 
                     with gr.Row():
                         with gr.Column(scale=3):
@@ -1114,6 +1115,7 @@ def create_ui(wrap_gradio_gpu_call):
             fn=modules.hypernetworks.ui.create_hypernetwork,
             inputs=[
                 new_hypernetwork_name,
+                new_hypernetwork_sizes,
             ],
             outputs=[
                 train_hypernetwork_name,

From 6d09b8d1df3a96e1380bb1650f5961781630af96 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 18:33:57 +0300
Subject: [PATCH 47/53] produce error when training with medvram/lowvram
 enabled

---
 modules/hypernetworks/ui.py     | 2 ++
 modules/textual_inversion/ui.py | 3 +++
 2 files changed, 5 insertions(+)

diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py
index cdddcce1a..3541a388b 100644
--- a/modules/hypernetworks/ui.py
+++ b/modules/hypernetworks/ui.py
@@ -25,6 +25,8 @@ def train_hypernetwork(*args):
 
     initial_hypernetwork = shared.loaded_hypernetwork
 
+    assert not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram, 'Training models with lowvram or medvram is not possible'
+
     try:
         sd_hijack.undo_optimizations()
 
diff --git a/modules/textual_inversion/ui.py b/modules/textual_inversion/ui.py
index c57de1f94..70f47343e 100644
--- a/modules/textual_inversion/ui.py
+++ b/modules/textual_inversion/ui.py
@@ -22,6 +22,9 @@ def preprocess(*args):
 
 
 def train_embedding(*args):
+
+    assert not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram, 'Training models with lowvram or medvram is not possible'
+
     try:
         sd_hijack.undo_optimizations()
 

From d4ea5f4d8631f778d11efcde397e4a5b8801d43b Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 19:03:08 +0300
Subject: [PATCH 48/53] add an option to unload models during hypernetwork
 training to save VRAM

---
 modules/hypernetworks/hypernetwork.py         | 25 +++++++++++-----
 modules/hypernetworks/ui.py                   |  4 ++-
 modules/shared.py                             |  4 +++
 modules/textual_inversion/dataset.py          | 29 +++++++++++++------
 .../textual_inversion/textual_inversion.py    |  2 +-
 5 files changed, 46 insertions(+), 18 deletions(-)

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index b081f14e9..4700e1ec1 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -175,6 +175,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
     filename = os.path.join(shared.cmd_opts.hypernetwork_dir, f'{hypernetwork_name}.pt')
 
     log_directory = os.path.join(log_directory, datetime.datetime.now().strftime("%Y-%m-%d"), hypernetwork_name)
+    unload = shared.opts.unload_models_when_training
 
     if save_hypernetwork_every > 0:
         hypernetwork_dir = os.path.join(log_directory, "hypernetworks")
@@ -188,11 +189,13 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
     else:
         images_dir = None
 
-    cond_model = shared.sd_model.cond_stage_model
-
     shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
     with torch.autocast("cuda"):
-        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=512, height=512, repeats=1, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file)
+        ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=512, height=512, repeats=1, placeholder_token=hypernetwork_name, model=shared.sd_model, device=devices.device, template_file=template_file, include_cond=True)
+
+    if unload:
+        shared.sd_model.cond_stage_model.to(devices.cpu)
+        shared.sd_model.first_stage_model.to(devices.cpu)
 
     hypernetwork = shared.loaded_hypernetwork
     weights = hypernetwork.weights()
@@ -211,7 +214,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
         return hypernetwork, filename
 
     pbar = tqdm.tqdm(enumerate(ds), total=steps - ititial_step)
-    for i, (x, text) in pbar:
+    for i, (x, text, cond) in pbar:
         hypernetwork.step = i + ititial_step
 
         if hypernetwork.step > steps:
@@ -221,11 +224,11 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
             break
 
         with torch.autocast("cuda"):
-            c = cond_model([text])
-
+            cond = cond.to(devices.device)
             x = x.to(devices.device)
-            loss = shared.sd_model(x.unsqueeze(0), c)[0]
+            loss = shared.sd_model(x.unsqueeze(0), cond)[0]
             del x
+            del cond
 
             losses[hypernetwork.step % losses.shape[0]] = loss.item()
 
@@ -244,6 +247,10 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
 
             preview_text = text if preview_image_prompt == "" else preview_image_prompt
 
+            optimizer.zero_grad()
+            shared.sd_model.cond_stage_model.to(devices.device)
+            shared.sd_model.first_stage_model.to(devices.device)
+
             p = processing.StableDiffusionProcessingTxt2Img(
                 sd_model=shared.sd_model,
                 prompt=preview_text,
@@ -255,6 +262,10 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
             processed = processing.process_images(p)
             image = processed.images[0]
 
+            if unload:
+                shared.sd_model.cond_stage_model.to(devices.cpu)
+                shared.sd_model.first_stage_model.to(devices.cpu)
+
             shared.state.current_image = image
             image.save(last_saved_image)
 
diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py
index 3541a388b..c67facbb7 100644
--- a/modules/hypernetworks/ui.py
+++ b/modules/hypernetworks/ui.py
@@ -5,7 +5,7 @@ import gradio as gr
 
 import modules.textual_inversion.textual_inversion
 import modules.textual_inversion.preprocess
-from modules import sd_hijack, shared
+from modules import sd_hijack, shared, devices
 from modules.hypernetworks import hypernetwork
 
 
@@ -41,5 +41,7 @@ Hypernetwork saved to {html.escape(filename)}
         raise
     finally:
         shared.loaded_hypernetwork = initial_hypernetwork
+        shared.sd_model.cond_stage_model.to(devices.device)
+        shared.sd_model.first_stage_model.to(devices.device)
         sd_hijack.apply_optimizations()
 
diff --git a/modules/shared.py b/modules/shared.py
index 20b45f231..c1092ff79 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -228,6 +228,10 @@ options_templates.update(options_section(('system', "System"), {
     "multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job."),
 }))
 
+options_templates.update(options_section(('training', "Training"), {
+    "unload_models_when_training": OptionInfo(False, "Unload VAE and CLIP form VRAM when training"),
+}))
+
 options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, show_on_main_page=True),
     "sd_hypernetwork": OptionInfo("None", "Stable Diffusion finetune hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}),
diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index 4d0063669..f61f40d30 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -8,14 +8,14 @@ from torchvision import transforms
 
 import random
 import tqdm
-from modules import devices
+from modules import devices, shared
 import re
 
 re_tag = re.compile(r"[a-zA-Z][_\w\d()]+")
 
 
 class PersonalizedBase(Dataset):
-    def __init__(self, data_root, width, height, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None):
+    def __init__(self, data_root, width, height, repeats, flip_p=0.5, placeholder_token="*", model=None, device=None, template_file=None, include_cond=False):
 
         self.placeholder_token = placeholder_token
 
@@ -32,6 +32,8 @@ class PersonalizedBase(Dataset):
 
         assert data_root, 'dataset directory not specified'
 
+        cond_model = shared.sd_model.cond_stage_model
+
         self.image_paths = [os.path.join(data_root, file_path) for file_path in os.listdir(data_root)]
         print("Preparing dataset...")
         for path in tqdm.tqdm(self.image_paths):
@@ -53,7 +55,13 @@ class PersonalizedBase(Dataset):
             init_latent = model.get_first_stage_encoding(model.encode_first_stage(torchdata.unsqueeze(dim=0))).squeeze()
             init_latent = init_latent.to(devices.cpu)
 
-            self.dataset.append((init_latent, filename_tokens))
+            if include_cond:
+                text = self.create_text(filename_tokens)
+                cond = cond_model([text]).to(devices.cpu)
+            else:
+                cond = None
+
+            self.dataset.append((init_latent, filename_tokens, cond))
 
         self.length = len(self.dataset) * repeats
 
@@ -64,6 +72,12 @@ class PersonalizedBase(Dataset):
     def shuffle(self):
         self.indexes = self.initial_indexes[torch.randperm(self.initial_indexes.shape[0])]
 
+    def create_text(self, filename_tokens):
+        text = random.choice(self.lines)
+        text = text.replace("[name]", self.placeholder_token)
+        text = text.replace("[filewords]", ' '.join(filename_tokens))
+        return text
+
     def __len__(self):
         return self.length
 
@@ -72,10 +86,7 @@ class PersonalizedBase(Dataset):
             self.shuffle()
 
         index = self.indexes[i % len(self.indexes)]
-        x, filename_tokens = self.dataset[index]
+        x, filename_tokens, cond = self.dataset[index]
 
-        text = random.choice(self.lines)
-        text = text.replace("[name]", self.placeholder_token)
-        text = text.replace("[filewords]", ' '.join(filename_tokens))
-
-        return x, text
+        text = self.create_text(filename_tokens)
+        return x, text, cond
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index bb05cdc65..35f4bd9e0 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -201,7 +201,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
         return embedding, filename
 
     pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step)
-    for i, (x, text) in pbar:
+    for i, (x, text, _) in pbar:
         embedding.step = i + ititial_step
 
         if embedding.step > steps:

From 6a9ea5b41cf92cd9e980349bb5034439f4e7a58b Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 19:22:30 +0300
Subject: [PATCH 49/53] prevent extra modules from being saved/loaded with
 hypernet

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

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 4700e1ec1..5608e7995 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -50,7 +50,7 @@ class Hypernetwork:
         self.sd_checkpoint = None
         self.sd_checkpoint_name = None
 
-        for size in enable_sizes or [320, 640, 768, 1280]:
+        for size in enable_sizes or []:
             self.layers[size] = (HypernetworkModule(size), HypernetworkModule(size))
 
     def weights(self):

From d7474a5185df2af84a93a12bc7e140d24e0fc516 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 21:10:55 +0300
Subject: [PATCH 50/53] bump gradio to 3.4.1

---
 requirements.txt          |  2 +-
 requirements_versions.txt |  2 +-
 style.css                 | 11 +++++++++++
 3 files changed, 13 insertions(+), 2 deletions(-)

diff --git a/requirements.txt b/requirements.txt
index 631fe616a..a0d985ce7 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -4,7 +4,7 @@ fairscale==0.4.4
 fonts
 font-roboto
 gfpgan
-gradio==3.4b3
+gradio==3.4.1
 invisible-watermark
 numpy
 omegaconf
diff --git a/requirements_versions.txt b/requirements_versions.txt
index fdff26878..2bbea40b4 100644
--- a/requirements_versions.txt
+++ b/requirements_versions.txt
@@ -2,7 +2,7 @@ transformers==4.19.2
 diffusers==0.3.0
 basicsr==1.4.2
 gfpgan==1.3.8
-gradio==3.4b3
+gradio==3.4.1
 numpy==1.23.3
 Pillow==9.2.0
 realesrgan==0.3.0
diff --git a/style.css b/style.css
index ecb51bb02..e6fa10b4f 100644
--- a/style.css
+++ b/style.css
@@ -240,6 +240,7 @@ fieldset span.text-gray-500, .gr-block.gr-box span.text-gray-500,  label.block s
 #settings fieldset span.text-gray-500, #settings .gr-block.gr-box span.text-gray-500, #settings label.block span{
     position: relative;
     border: none;
+    margin-right: 8em;
 }
 
 .gr-panel div.flex-col div.justify-between label span{
@@ -495,3 +496,13 @@ canvas[key="mask"] {
     mix-blend-mode: multiply;
     pointer-events: none;
 }
+
+
+/* gradio 3.4.1 stuff for editable scrollbar values */
+.gr-box > div > div > input.gr-text-input{
+    position: absolute;
+    right: 0.5em;
+    top: -0.6em;
+    z-index: 200;
+    width: 8em;
+}

From 9e5f6b558072f6cdfa0f7010fa819662952fcaf1 Mon Sep 17 00:00:00 2001
From: nai-degen <92774204+nai-degen@users.noreply.github.com>
Date: Sun, 9 Oct 2022 19:37:35 -0500
Subject: [PATCH 51/53] triggers 'input' event when using arrow keys to edit
 attention

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

diff --git a/javascript/edit-attention.js b/javascript/edit-attention.js
index 0280c603f..79566a2e2 100644
--- a/javascript/edit-attention.js
+++ b/javascript/edit-attention.js
@@ -38,4 +38,7 @@ addEventListener('keydown', (event) => {
 		target.selectionStart = selectionStart;
 		target.selectionEnd = selectionEnd;
 	}
+	// Since we've modified a Gradio Textbox component manually, we need to simulate an `input` DOM event to ensure its
+	// internal Svelte data binding remains in sync.
+	target.dispatchEvent(new Event("input", { bubbles: true }));
 });

From d6fcc6b87bc00fcdecea276fe5b7c7945f7a8b14 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 22:03:05 +0300
Subject: [PATCH 52/53] apply lr schedule to hypernets

---
 modules/hypernetworks/hypernetwork.py         | 19 ++++++--
 modules/textual_inversion/learn_schedule.py   | 34 ++++++++++++++
 .../textual_inversion/textual_inversion.py    | 44 ++-----------------
 modules/ui.py                                 |  2 +-
 4 files changed, 54 insertions(+), 45 deletions(-)
 create mode 100644 modules/textual_inversion/learn_schedule.py

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 5608e7995..470659dfe 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -14,6 +14,7 @@ import torch
 from torch import einsum
 from einops import rearrange, repeat
 import modules.textual_inversion.dataset
+from modules.textual_inversion.learn_schedule import LearnSchedule
 
 
 class HypernetworkModule(torch.nn.Module):
@@ -202,8 +203,6 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
     for weight in weights:
         weight.requires_grad = True
 
-    optimizer = torch.optim.AdamW(weights, lr=learn_rate)
-
     losses = torch.zeros((32,))
 
     last_saved_file = "<none>"
@@ -213,12 +212,24 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
     if ititial_step > steps:
         return hypernetwork, filename
 
+    schedules = iter(LearnSchedule(learn_rate, steps, ititial_step))
+    (learn_rate, end_step) = next(schedules)
+    print(f'Training at rate of {learn_rate} until step {end_step}')
+
+    optimizer = torch.optim.AdamW(weights, lr=learn_rate)
+
     pbar = tqdm.tqdm(enumerate(ds), total=steps - ititial_step)
     for i, (x, text, cond) in pbar:
         hypernetwork.step = i + ititial_step
 
-        if hypernetwork.step > steps:
-            break
+        if hypernetwork.step > end_step:
+            try:
+                (learn_rate, end_step) = next(schedules)
+            except Exception:
+                break
+            tqdm.tqdm.write(f'Training at rate of {learn_rate} until step {end_step}')
+            for pg in optimizer.param_groups:
+                pg['lr'] = learn_rate
 
         if shared.state.interrupted:
             break
diff --git a/modules/textual_inversion/learn_schedule.py b/modules/textual_inversion/learn_schedule.py
new file mode 100644
index 000000000..db7202712
--- /dev/null
+++ b/modules/textual_inversion/learn_schedule.py
@@ -0,0 +1,34 @@
+
+class LearnSchedule:
+    def __init__(self, learn_rate, max_steps, cur_step=0):
+        pairs = learn_rate.split(',')
+        self.rates = []
+        self.it = 0
+        self.maxit = 0
+        for i, pair in enumerate(pairs):
+            tmp = pair.split(':')
+            if len(tmp) == 2:
+                step = int(tmp[1])
+                if step > cur_step:
+                    self.rates.append((float(tmp[0]), min(step, max_steps)))
+                    self.maxit += 1
+                    if step > max_steps:
+                        return
+                elif step == -1:
+                    self.rates.append((float(tmp[0]), max_steps))
+                    self.maxit += 1
+                    return
+            else:
+                self.rates.append((float(tmp[0]), max_steps))
+                self.maxit += 1
+                return
+
+    def __iter__(self):
+        return self
+
+    def __next__(self):
+        if self.it < self.maxit:
+            self.it += 1
+            return self.rates[self.it - 1]
+        else:
+            raise StopIteration
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 47a27faf2..7717837da 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -10,6 +10,7 @@ import datetime
 
 from modules import shared, devices, sd_hijack, processing, sd_models
 import modules.textual_inversion.dataset
+from modules.textual_inversion.learn_schedule import LearnSchedule
 
 
 class Embedding:
@@ -198,11 +199,8 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
     if ititial_step > steps:
         return embedding, filename
 
-    tr_img_len = len([os.path.join(data_root, file_path) for file_path in os.listdir(data_root)])
-    epoch_len = (tr_img_len * num_repeats) + tr_img_len
-
-    scheduleIter = iter(LearnSchedule(learn_rate, steps, ititial_step))
-    (learn_rate, end_step) = next(scheduleIter)
+    schedules = iter(LearnSchedule(learn_rate, steps, ititial_step))
+    (learn_rate, end_step) = next(schedules)
     print(f'Training at rate of {learn_rate} until step {end_step}')
 
     optimizer = torch.optim.AdamW([embedding.vec], lr=learn_rate)
@@ -213,7 +211,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
 
         if embedding.step > end_step:
             try:
-                (learn_rate, end_step) = next(scheduleIter)
+                (learn_rate, end_step) = next(schedules)
             except:
                 break
             tqdm.tqdm.write(f'Training at rate of {learn_rate} until step {end_step}')
@@ -288,37 +286,3 @@ Last saved image: {html.escape(last_saved_image)}<br/>
     embedding.save(filename)
 
     return embedding, filename
-
-class LearnSchedule:
-    def __init__(self, learn_rate, max_steps, cur_step=0):
-        pairs = learn_rate.split(',')
-        self.rates = []
-        self.it = 0
-        self.maxit = 0
-        for i, pair in enumerate(pairs):
-            tmp = pair.split(':')
-            if len(tmp) == 2:
-                step = int(tmp[1])
-                if step > cur_step:
-                    self.rates.append((float(tmp[0]), min(step, max_steps)))
-                    self.maxit += 1
-                    if step > max_steps:
-                        return
-                elif step == -1:
-                    self.rates.append((float(tmp[0]), max_steps))
-                    self.maxit += 1
-                    return
-            else:
-                self.rates.append((float(tmp[0]), max_steps))
-                self.maxit += 1
-                return
-
-    def __iter__(self):
-        return self
-
-    def __next__(self):
-        if self.it < self.maxit:
-            self.it += 1
-            return self.rates[self.it - 1]
-        else:
-            raise StopIteration
diff --git a/modules/ui.py b/modules/ui.py
index 2b688e325..1204eef7b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1070,7 +1070,7 @@ def create_ui(wrap_gradio_gpu_call):
                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding; must specify a directory with a set of 1:1 ratio images</p>")
                     train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
                     train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', choices=[x for x in shared.hypernetworks.keys()])
-                    learn_rate = gr.Textbox(label='Learning rate', placeholder="Learning rate", value = "5.0e-03")
+                    learn_rate = gr.Textbox(label='Learning rate', placeholder="Learning rate", value="0.005")
                     dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images")
                     log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")
                     template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"))

From 6be32b31d181e42c639dad3451229aa7b9cfd1cf Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 11 Oct 2022 23:07:09 +0300
Subject: [PATCH 53/53] reports that training with medvram is possible.

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

diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py
index c67facbb7..dfa599afa 100644
--- a/modules/hypernetworks/ui.py
+++ b/modules/hypernetworks/ui.py
@@ -25,7 +25,7 @@ def train_hypernetwork(*args):
 
     initial_hypernetwork = shared.loaded_hypernetwork
 
-    assert not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram, 'Training models with lowvram or medvram is not possible'
+    assert not shared.cmd_opts.lowvram, 'Training models with lowvram is not possible'
 
     try:
         sd_hijack.undo_optimizations()
diff --git a/modules/textual_inversion/ui.py b/modules/textual_inversion/ui.py
index 70f47343e..36881e7ad 100644
--- a/modules/textual_inversion/ui.py
+++ b/modules/textual_inversion/ui.py
@@ -23,7 +23,7 @@ def preprocess(*args):
 
 def train_embedding(*args):
 
-    assert not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram, 'Training models with lowvram or medvram is not possible'
+    assert not shared.cmd_opts.lowvram, 'Training models with lowvram not possible'
 
     try:
         sd_hijack.undo_optimizations()