Mirrors
/
stable-diffusion-webui
mirror of https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Merge branch 'master' into test_resolve_conflicts

This commit is contained in:
MalumaDev 2022-10-16 00:06:36 +02:00 committed by GitHub
parent 3d21684ee3 be1596ce30
commit 97ceaa23d0
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
6 changed files with 30 additions and 26 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

5
launch.py
View File

@ -104,6 +104,7 @@ def prepare_enviroment():
args = shlex.split(commandline_args)
args, skip_torch_cuda_test = extract_arg(args, '--skip-torch-cuda-test')
args, reinstall_xformers = extract_arg(args, '--reinstall-xformers')
xformers = '--xformers' in args
deepdanbooru = '--deepdanbooru' in args
ngrok = '--ngrok' in args
@ -128,9 +129,9 @@ def prepare_enviroment():
if not is_installed("clip"):
run_pip(f"install {clip_package}", "clip")
if not is_installed("xformers") and xformers and platform.python_version().startswith("3.10"):
if (not is_installed("xformers") or reinstall_xformers) and xformers and platform.python_version().startswith("3.10"):
if platform.system() == "Windows":
run_pip("install https://github.com/C43H66N12O12S2/stable-diffusion-webui/releases/download/c/xformers-0.0.14.dev0-cp310-cp310-win_amd64.whl", "xformers")
run_pip("install -U -I --no-deps https://github.com/C43H66N12O12S2/stable-diffusion-webui/releases/download/f/xformers-0.0.14.dev0-cp310-cp310-win_amd64.whl", "xformers")
elif platform.system() == "Linux":
run_pip("install xformers", "xformers")

10
modules/hypernetworks/hypernetwork.py
View File

@ -272,15 +272,17 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
optimizer.zero_grad()
loss.backward()
optimizer.step()
pbar.set_description(f"loss: {losses.mean():.7f}")
mean_loss = losses.mean()
if torch.isnan(mean_loss):
raise RuntimeError("Loss diverged.")
pbar.set_description(f"loss: {mean_loss:.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)
textual_inversion.write_loss(log_directory, "hypernetwork_loss.csv", hypernetwork.step, len(ds), {
"loss": f"{losses.mean():.7f}",
"loss": f"{mean_loss:.7f}",
"learn_rate": scheduler.learn_rate
})
@ -328,7 +330,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
shared.state.textinfo = f"""
<p>
Loss: {losses.mean():.7f}<br/>
Loss: {mean_loss:.7f}<br/>
Step: {hypernetwork.step}<br/>
Last prompt: {html.escape(entries[0].cond_text)}<br/>
Last saved embedding: {html.escape(last_saved_file)}<br/>

4
modules/sd_hijack.py
View File

@ -29,8 +29,8 @@ def apply_optimizations():
ldm.modules.diffusionmodules.model.nonlinearity = silu
if cmd_opts.force_enable_xformers or (cmd_opts.xformers and shared.xformers_available and torch.version.cuda and (
6, 0) <= torch.cuda.get_device_capability(shared.device) <= (8, 6)):
if cmd_opts.force_enable_xformers or (cmd_opts.xformers and shared.xformers_available and torch.version.cuda and (6, 0) <= torch.cuda.get_device_capability(shared.device) <= (9, 0)):
print("Applying xformers cross attention optimization.")
ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward
ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.xformers_attnblock_forward

17
modules/textual_inversion/textual_inversion.py
View File

@ -88,9 +88,9 @@ class EmbeddingDatabase:
data = []
if filename.upper().endswith('.PNG'):
if os.path.splitext(filename.upper())[-1] in ['.PNG', '.WEBP', '.JXL', '.AVIF']:
embed_image = Image.open(path)
if 'sd-ti-embedding' in embed_image.text:
if hasattr(embed_image, 'text') and 'sd-ti-embedding' in embed_image.text:
data = embedding_from_b64(embed_image.text['sd-ti-embedding'])
name = data.get('name', name)
else:
@ -242,6 +242,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
last_saved_file = "<none>"
last_saved_image = "<none>"
embedding_yet_to_be_embedded = False
ititial_step = embedding.step or 0
if ititial_step > steps:
@ -283,6 +284,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
if embedding.step > 0 and embedding_dir is not None and embedding.step % save_embedding_every == 0:
last_saved_file = os.path.join(embedding_dir, f'{embedding_name}-{embedding.step}.pt')
embedding.save(last_saved_file)
embedding_yet_to_be_embedded = True
write_loss(log_directory, "textual_inversion_loss.csv", embedding.step, len(ds), {
"loss": f"{losses.mean():.7f}",
@ -320,7 +322,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
shared.state.current_image = image
if save_image_with_stored_embedding and os.path.exists(last_saved_file):
if save_image_with_stored_embedding and os.path.exists(last_saved_file) and embedding_yet_to_be_embedded:
last_saved_image_chunks = os.path.join(images_embeds_dir, f'{embedding_name}-{embedding.step}.png')
@ -329,15 +331,22 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
info.add_text("sd-ti-embedding", embedding_to_b64(data))
title = "<{}>".format(data.get('name', '???'))
try:
vectorSize = list(data['string_to_param'].values())[0].shape[0]
except Exception as e:
vectorSize = '?'
checkpoint = sd_models.select_checkpoint()
footer_left = checkpoint.model_name
footer_mid = '[{}]'.format(checkpoint.hash)
footer_right = '{}'.format(embedding.step)
footer_right = '{}v {}s'.format(vectorSize, embedding.step)
captioned_image = caption_image_overlay(image, title, footer_left, footer_mid, footer_right)
captioned_image = insert_image_data_embed(captioned_image, data)
captioned_image.save(last_saved_image_chunks, "PNG", pnginfo=info)
embedding_yet_to_be_embedded = False
image.save(last_saved_image)

9
modules/ui.py
View File

@ -158,10 +158,7 @@ def save_files(js_data, images, do_make_zip, index):
writer.writerow(["prompt", "seed", "width", "height", "sampler", "cfgs", "steps", "filename", "negative_prompt"])
for image_index, filedata in enumerate(images, start_index):
if filedata.startswith("data:image/png;base64,"):
filedata = filedata[len("data:image/png;base64,"):]
image = Image.open(io.BytesIO(base64.decodebytes(filedata.encode('utf-8'))))
image = image_from_url_text(filedata)
is_grid = image_index < p.index_of_first_image
i = 0 if is_grid else (image_index - p.index_of_first_image)
@ -638,7 +635,7 @@ def create_ui(wrap_gradio_gpu_call):
txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False)
txt2img_gallery = gr.Gallery(label='Output', show_label=False, elem_id='txt2img_gallery').style(grid=4)
with gr.Group():
with gr.Column():
with gr.Row():
save = gr.Button('Save')
send_to_img2img = gr.Button('Send to img2img')
@ -862,7 +859,7 @@ def create_ui(wrap_gradio_gpu_call):
img2img_preview = gr.Image(elem_id='img2img_preview', visible=False)
img2img_gallery = gr.Gallery(label='Output', show_label=False, elem_id='img2img_gallery').style(grid=4)
with gr.Group():
with gr.Column():
with gr.Row():
save = gr.Button('Save')
img2img_send_to_img2img = gr.Button('Send to img2img')

11
style.css
View File

@ -237,13 +237,6 @@ fieldset span.text-gray-500, .gr-block.gr-box span.text-gray-500, label.block s
margin: 0;
}
.gr-panel div.flex-col div.justify-between div{
position: absolute;
top: -0.1em;
right: 1em;
padding: 0 0.5em;
}
#settings .gr-panel div.flex-col div.justify-between div{
position: relative;
z-index: 200;
@ -316,6 +309,8 @@ input[type="range"]{
height: 100%;
overflow: auto;
background-color: rgba(20, 20, 20, 0.95);
user-select: none;
-webkit-user-select: none;
}
.modalControls {
@ -520,4 +515,4 @@ img2maskimg, #img2maskimg > .h-60, #img2maskimg > .h-60 > div, #img2maskimg > .h
height: 480px !important;
max-height: 480px !important;
min-height: 480px !important;
}
}