Merge branch 'release_candidate'

This commit is contained in:
AUTOMATIC1111 2023-07-27 09:02:22 +03:00
commit 68f336bd99
16 changed files with 140 additions and 164 deletions

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@ -1,3 +1,28 @@
## 1.5.1
### Minor:
* support parsing text encoder blocks in some new LoRAs
* delete scale checker script due to user demand
### Extensions and API:
* add postprocess_batch_list script callback
### Bug Fixes:
* fix TI training for SD1
* fix reload altclip model error
* prepend the pythonpath instead of overriding it
* fix typo in SD_WEBUI_RESTARTING
* if txt2img/img2img raises an exception, finally call state.end()
* fix composable diffusion weight parsing
* restyle Startup profile for black users
* fix webui not launching with --nowebui
* catch exception for non git extensions
* fix some options missing from /sdapi/v1/options
* fix for extension update status always saying "unknown"
* fix display of extra network cards that have `<>` in the name
* update lora extension to work with python 3.8
## 1.5.0
### Features:

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@ -1,3 +1,4 @@
from __future__ import annotations
import os
from collections import namedtuple
import enum

View File

@ -163,6 +163,11 @@ def load_network(name, network_on_disk):
key = key_network_without_network_parts.replace("lora_te1_text_model", "0_transformer_text_model")
sd_module = shared.sd_model.network_layer_mapping.get(key, None)
# some SD1 Loras also have correct compvis keys
if sd_module is None:
key = key_network_without_network_parts.replace("lora_te1_text_model", "transformer_text_model")
sd_module = shared.sd_model.network_layer_mapping.get(key, None)
if sd_module is None:
keys_failed_to_match[key_network] = key
continue

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@ -1,108 +0,0 @@
(function() {
var ignore = localStorage.getItem("bad-scale-ignore-it") == "ignore-it";
function getScale() {
var ratio = 0,
screen = window.screen,
ua = navigator.userAgent.toLowerCase();
if (window.devicePixelRatio !== undefined) {
ratio = window.devicePixelRatio;
} else if (~ua.indexOf('msie')) {
if (screen.deviceXDPI && screen.logicalXDPI) {
ratio = screen.deviceXDPI / screen.logicalXDPI;
}
} else if (window.outerWidth !== undefined && window.innerWidth !== undefined) {
ratio = window.outerWidth / window.innerWidth;
}
return ratio == 0 ? 0 : Math.round(ratio * 100);
}
var showing = false;
var div = document.createElement("div");
div.style.position = "fixed";
div.style.top = "0px";
div.style.left = "0px";
div.style.width = "100vw";
div.style.backgroundColor = "firebrick";
div.style.textAlign = "center";
div.style.zIndex = 99;
var b = document.createElement("b");
b.innerHTML = 'Bad Scale: ??% ';
div.appendChild(b);
var note1 = document.createElement("p");
note1.innerHTML = "Change your browser or your computer settings!";
note1.title = 'Just make sure "computer-scale" * "browser-scale" = 100% ,\n' +
"you can keep your computer-scale and only change this page's scale,\n" +
"for example: your computer-scale is 125%, just use [\"CTRL\"+\"-\"] to make your browser-scale of this page to 80%.";
div.appendChild(note1);
var note2 = document.createElement("p");
note2.innerHTML = " Otherwise, it will cause this page to not function properly!";
note2.title = "When you click \"Copy image to: [inpaint sketch]\" in some img2img's tab,\n" +
"if scale<100% the canvas will be invisible,\n" +
"else if scale>100% this page will take large amount of memory and CPU performance.";
div.appendChild(note2);
var btn = document.createElement("button");
btn.innerHTML = "Click here to ignore";
div.appendChild(btn);
function tryShowTopBar(scale) {
if (showing) return;
b.innerHTML = 'Bad Scale: ' + scale + '% ';
var updateScaleTimer = setInterval(function() {
var newScale = getScale();
b.innerHTML = 'Bad Scale: ' + newScale + '% ';
if (newScale == 100) {
var p = div.parentNode;
if (p != null) p.removeChild(div);
showing = false;
clearInterval(updateScaleTimer);
check();
}
}, 999);
btn.onclick = function() {
clearInterval(updateScaleTimer);
var p = div.parentNode;
if (p != null) p.removeChild(div);
ignore = true;
showing = false;
localStorage.setItem("bad-scale-ignore-it", "ignore-it");
};
document.body.appendChild(div);
}
function check() {
if (!ignore) {
var timer = setInterval(function() {
var scale = getScale();
if (scale != 100 && !ignore) {
tryShowTopBar(scale);
clearInterval(timer);
}
if (ignore) {
clearInterval(timer);
}
}, 999);
}
}
if (document.readyState != "complete") {
document.onreadystatechange = function() {
if (document.readyState != "complete") check();
};
} else {
check();
}
})();

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@ -333,14 +333,16 @@ class Api:
p.outpath_grids = opts.outdir_txt2img_grids
p.outpath_samples = opts.outdir_txt2img_samples
shared.state.begin(job="scripts_txt2img")
if selectable_scripts is not None:
p.script_args = script_args
processed = scripts.scripts_txt2img.run(p, *p.script_args) # Need to pass args as list here
else:
p.script_args = tuple(script_args) # Need to pass args as tuple here
processed = process_images(p)
shared.state.end()
try:
shared.state.begin(job="scripts_txt2img")
if selectable_scripts is not None:
p.script_args = script_args
processed = scripts.scripts_txt2img.run(p, *p.script_args) # Need to pass args as list here
else:
p.script_args = tuple(script_args) # Need to pass args as tuple here
processed = process_images(p)
finally:
shared.state.end()
b64images = list(map(encode_pil_to_base64, processed.images)) if send_images else []
@ -390,14 +392,16 @@ class Api:
p.outpath_grids = opts.outdir_img2img_grids
p.outpath_samples = opts.outdir_img2img_samples
shared.state.begin(job="scripts_img2img")
if selectable_scripts is not None:
p.script_args = script_args
processed = scripts.scripts_img2img.run(p, *p.script_args) # Need to pass args as list here
else:
p.script_args = tuple(script_args) # Need to pass args as tuple here
processed = process_images(p)
shared.state.end()
try:
shared.state.begin(job="scripts_img2img")
if selectable_scripts is not None:
p.script_args = script_args
processed = scripts.scripts_img2img.run(p, *p.script_args) # Need to pass args as list here
else:
p.script_args = tuple(script_args) # Need to pass args as tuple here
processed = process_images(p)
finally:
shared.state.end()
b64images = list(map(encode_pil_to_base64, processed.images)) if send_images else []
@ -720,9 +724,9 @@ class Api:
cuda = {'error': f'{err}'}
return models.MemoryResponse(ram=ram, cuda=cuda)
def launch(self, server_name, port):
def launch(self, server_name, port, root_path):
self.app.include_router(self.router)
uvicorn.run(self.app, host=server_name, port=port, timeout_keep_alive=shared.cmd_opts.timeout_keep_alive)
uvicorn.run(self.app, host=server_name, port=port, timeout_keep_alive=shared.cmd_opts.timeout_keep_alive, root_path=root_path)
def kill_webui(self):
restart.stop_program()

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@ -208,11 +208,9 @@ class PreprocessResponse(BaseModel):
fields = {}
for key, metadata in opts.data_labels.items():
value = opts.data.get(key)
optType = opts.typemap.get(type(metadata.default), type(metadata.default))
optType = opts.typemap.get(type(metadata.default), type(metadata.default)) if metadata.default else Any
if metadata.default is None:
pass
elif metadata is not None:
if metadata is not None:
fields.update({key: (Optional[optType], Field(default=metadata.default, description=metadata.label))})
else:
fields.update({key: (Optional[optType], Field())})

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@ -56,10 +56,12 @@ class Extension:
self.do_read_info_from_repo()
return self.to_dict()
d = cache.cached_data_for_file('extensions-git', self.name, os.path.join(self.path, ".git"), read_from_repo)
self.from_dict(d)
self.status = 'unknown'
try:
d = cache.cached_data_for_file('extensions-git', self.name, os.path.join(self.path, ".git"), read_from_repo)
self.from_dict(d)
except FileNotFoundError:
pass
self.status = 'unknown' if self.status == '' else self.status
def do_read_info_from_repo(self):
repo = None

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@ -196,7 +196,7 @@ def run_extension_installer(extension_dir):
try:
env = os.environ.copy()
env['PYTHONPATH'] = os.path.abspath(".")
env['PYTHONPATH'] = f"{os.path.abspath('.')}{os.pathsep}{env.get('PYTHONPATH', '')}"
print(run(f'"{python}" "{path_installer}"', errdesc=f"Error running install.py for extension {extension_dir}", custom_env=env))
except Exception as e:
@ -233,7 +233,7 @@ def run_extensions_installers(settings_file):
re_requirement = re.compile(r"\s*([-_a-zA-Z0-9]+)\s*(?:==\s*([-+_.a-zA-Z0-9]+))?\s*")
def requrements_met(requirements_file):
def requirements_met(requirements_file):
"""
Does a simple parse of a requirements.txt file to determine if all rerqirements in it
are already installed. Returns True if so, False if not installed or parsing fails.
@ -293,7 +293,7 @@ def prepare_environment():
try:
# the existance of this file is a signal to webui.sh/bat that webui needs to be restarted when it stops execution
os.remove(os.path.join(script_path, "tmp", "restart"))
os.environ.setdefault('SD_WEBUI_RESTARTING ', '1')
os.environ.setdefault('SD_WEBUI_RESTARTING', '1')
except OSError:
pass
@ -354,7 +354,7 @@ def prepare_environment():
if not os.path.isfile(requirements_file):
requirements_file = os.path.join(script_path, requirements_file)
if not requrements_met(requirements_file):
if not requirements_met(requirements_file):
run_pip(f"install -r \"{requirements_file}\"", "requirements")
run_extensions_installers(settings_file=args.ui_settings_file)

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@ -600,8 +600,12 @@ def program_version():
return res
def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iteration=0, position_in_batch=0, use_main_prompt=False):
index = position_in_batch + iteration * p.batch_size
def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iteration=0, position_in_batch=0, use_main_prompt=False, index=None, all_negative_prompts=None):
if index is None:
index = position_in_batch + iteration * p.batch_size
if all_negative_prompts is None:
all_negative_prompts = p.all_negative_prompts
clip_skip = getattr(p, 'clip_skip', opts.CLIP_stop_at_last_layers)
enable_hr = getattr(p, 'enable_hr', False)
@ -617,12 +621,12 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
"Sampler": p.sampler_name,
"CFG scale": p.cfg_scale,
"Image CFG scale": getattr(p, 'image_cfg_scale', None),
"Seed": all_seeds[index],
"Seed": p.all_seeds[0] if use_main_prompt else all_seeds[index],
"Face restoration": (opts.face_restoration_model if p.restore_faces else None),
"Size": f"{p.width}x{p.height}",
"Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash),
"Model": (None if not opts.add_model_name_to_info else shared.sd_model.sd_checkpoint_info.name_for_extra),
"Variation seed": (None if p.subseed_strength == 0 else all_subseeds[index]),
"Variation seed": (None if p.subseed_strength == 0 else (p.all_subseeds[0] if use_main_prompt else all_subseeds[index])),
"Variation seed strength": (None if p.subseed_strength == 0 else p.subseed_strength),
"Seed resize from": (None if p.seed_resize_from_w <= 0 or p.seed_resize_from_h <= 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"),
"Denoising strength": getattr(p, 'denoising_strength', None),
@ -642,7 +646,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
generation_params_text = ", ".join([k if k == v else f'{k}: {generation_parameters_copypaste.quote(v)}' for k, v in generation_params.items() if v is not None])
prompt_text = p.prompt if use_main_prompt else all_prompts[index]
negative_prompt_text = f"\nNegative prompt: {p.all_negative_prompts[index]}" if p.all_negative_prompts[index] else ""
negative_prompt_text = f"\nNegative prompt: {all_negative_prompts[index]}" if all_negative_prompts[index] else ""
return f"{prompt_text}{negative_prompt_text}\n{generation_params_text}".strip()
@ -716,9 +720,6 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
else:
p.all_subseeds = [int(subseed) + x for x in range(len(p.all_prompts))]
def infotext(iteration=0, position_in_batch=0, use_main_prompt=False):
return create_infotext(p, p.all_prompts, p.all_seeds, p.all_subseeds, comments, iteration, position_in_batch, use_main_prompt)
if os.path.exists(cmd_opts.embeddings_dir) and not p.do_not_reload_embeddings:
model_hijack.embedding_db.load_textual_inversion_embeddings()
@ -806,6 +807,16 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if p.scripts is not None:
p.scripts.postprocess_batch(p, x_samples_ddim, batch_number=n)
p.prompts = p.all_prompts[n * p.batch_size:(n + 1) * p.batch_size]
p.negative_prompts = p.all_negative_prompts[n * p.batch_size:(n + 1) * p.batch_size]
batch_params = scripts.PostprocessBatchListArgs(list(x_samples_ddim))
p.scripts.postprocess_batch_list(p, batch_params, batch_number=n)
x_samples_ddim = batch_params.images
def infotext(index=0, use_main_prompt=False):
return create_infotext(p, p.prompts, p.seeds, p.subseeds, use_main_prompt=use_main_prompt, index=index, all_negative_prompts=p.negative_prompts)
for i, x_sample in enumerate(x_samples_ddim):
p.batch_index = i
@ -814,7 +825,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if p.restore_faces:
if opts.save and not p.do_not_save_samples and opts.save_images_before_face_restoration:
images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-face-restoration")
images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p, suffix="-before-face-restoration")
devices.torch_gc()
@ -831,15 +842,15 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if p.color_corrections is not None and i < len(p.color_corrections):
if opts.save and not p.do_not_save_samples and opts.save_images_before_color_correction:
image_without_cc = apply_overlay(image, p.paste_to, i, p.overlay_images)
images.save_image(image_without_cc, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-color-correction")
images.save_image(image_without_cc, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p, suffix="-before-color-correction")
image = apply_color_correction(p.color_corrections[i], image)
image = apply_overlay(image, p.paste_to, i, p.overlay_images)
if opts.samples_save and not p.do_not_save_samples:
images.save_image(image, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p)
images.save_image(image, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p)
text = infotext(n, i)
text = infotext(i)
infotexts.append(text)
if opts.enable_pnginfo:
image.info["parameters"] = text
@ -850,10 +861,10 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
image_mask_composite = Image.composite(image.convert('RGBA').convert('RGBa'), Image.new('RGBa', image.size), images.resize_image(2, p.mask_for_overlay, image.width, image.height).convert('L')).convert('RGBA')
if opts.save_mask:
images.save_image(image_mask, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-mask")
images.save_image(image_mask, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p, suffix="-mask")
if opts.save_mask_composite:
images.save_image(image_mask_composite, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-mask-composite")
images.save_image(image_mask_composite, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p, suffix="-mask-composite")
if opts.return_mask:
output_images.append(image_mask)
@ -894,7 +905,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
p,
images_list=output_images,
seed=p.all_seeds[0],
info=infotext(),
info=infotexts[0],
comments="".join(f"{comment}\n" for comment in comments),
subseed=p.all_subseeds[0],
index_of_first_image=index_of_first_image,

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@ -178,7 +178,7 @@ def get_learned_conditioning(model, prompts: SdConditioning | list[str], steps):
re_AND = re.compile(r"\bAND\b")
re_weight = re.compile(r"^(.*?)(?:\s*:\s*([-+]?(?:\d+\.?|\d*\.\d+)))?\s*$")
re_weight = re.compile(r"^((?:\s|.)*?)(?:\s*:\s*([-+]?(?:\d+\.?|\d*\.\d+)))?\s*$")
def get_multicond_prompt_list(prompts: SdConditioning | list[str]):

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@ -16,6 +16,11 @@ class PostprocessImageArgs:
self.image = image
class PostprocessBatchListArgs:
def __init__(self, images):
self.images = images
class Script:
name = None
"""script's internal name derived from title"""
@ -119,7 +124,7 @@ class Script:
def after_extra_networks_activate(self, p, *args, **kwargs):
"""
Calledafter extra networks activation, before conds calculation
Called after extra networks activation, before conds calculation
allow modification of the network after extra networks activation been applied
won't be call if p.disable_extra_networks
@ -156,6 +161,25 @@ class Script:
pass
def postprocess_batch_list(self, p, pp: PostprocessBatchListArgs, *args, **kwargs):
"""
Same as postprocess_batch(), but receives batch images as a list of 3D tensors instead of a 4D tensor.
This is useful when you want to update the entire batch instead of individual images.
You can modify the postprocessing object (pp) to update the images in the batch, remove images, add images, etc.
If the number of images is different from the batch size when returning,
then the script has the responsibility to also update the following attributes in the processing object (p):
- p.prompts
- p.negative_prompts
- p.seeds
- p.subseeds
**kwargs will have same items as process_batch, and also:
- batch_number - index of current batch, from 0 to number of batches-1
"""
pass
def postprocess_image(self, p, pp: PostprocessImageArgs, *args):
"""
Called for every image after it has been generated.
@ -536,6 +560,14 @@ class ScriptRunner:
except Exception:
errors.report(f"Error running postprocess_batch: {script.filename}", exc_info=True)
def postprocess_batch_list(self, p, pp: PostprocessBatchListArgs, **kwargs):
for script in self.alwayson_scripts:
try:
script_args = p.script_args[script.args_from:script.args_to]
script.postprocess_batch_list(p, pp, *script_args, **kwargs)
except Exception:
errors.report(f"Error running postprocess_batch_list: {script.filename}", exc_info=True)
def postprocess_image(self, p, pp: PostprocessImageArgs):
for script in self.alwayson_scripts:
try:

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@ -243,7 +243,7 @@ class StableDiffusionModelHijack:
ldm.modules.diffusionmodules.openaimodel.UNetModel.forward = sd_unet.UNetModel_forward
def undo_hijack(self, m):
if type(m.cond_stage_model) == xlmr.BertSeriesModelWithTransformation:
if type(m.cond_stage_model) == sd_hijack_xlmr.FrozenXLMREmbedderWithCustomWords:
m.cond_stage_model = m.cond_stage_model.wrapped
elif type(m.cond_stage_model) == sd_hijack_clip.FrozenCLIPEmbedderWithCustomWords:

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@ -270,12 +270,17 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
z = self.encode_with_transformers(tokens)
pooled = getattr(z, 'pooled', None)
# restoring original mean is likely not correct, but it seems to work well to prevent artifacts that happen otherwise
batch_multipliers = torch.asarray(batch_multipliers).to(devices.device)
original_mean = z.mean()
z *= batch_multipliers.reshape(batch_multipliers.shape + (1,)).expand(z.shape)
z = z * batch_multipliers.reshape(batch_multipliers.shape + (1,)).expand(z.shape)
new_mean = z.mean()
z *= (original_mean / new_mean)
z = z * (original_mean / new_mean)
if pooled is not None:
z.pooled = pooled
return z

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@ -253,7 +253,7 @@ class ExtraNetworksPage:
"prompt": item.get("prompt", None),
"tabname": quote_js(tabname),
"local_preview": quote_js(item["local_preview"]),
"name": item["name"],
"name": html.escape(item["name"]),
"description": (item.get("description") or "" if shared.opts.extra_networks_card_show_desc else ""),
"card_clicked": onclick,
"save_card_preview": '"' + html.escape(f"""return saveCardPreview(event, {quote_js(tabname)}, {quote_js(item["local_preview"])})""") + '"',

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@ -423,15 +423,16 @@ div#extras_scale_to_tab div.form{
}
table.popup-table{
background: white;
background: var(--body-background-fill);
color: var(--body-text-color);
border-collapse: collapse;
margin: 1em;
border: 4px solid white;
border: 4px solid var(--body-background-fill);
}
table.popup-table td{
padding: 0.4em;
border: 1px solid #ccc;
border: 1px solid rgba(128, 128, 128, 0.5);
max-width: 36em;
}

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@ -374,7 +374,7 @@ def api_only():
api.launch(
server_name="0.0.0.0" if cmd_opts.listen else "127.0.0.1",
port=cmd_opts.port if cmd_opts.port else 7861,
root_path = f"/{cmd_opts.subpath}"
root_path=f"/{cmd_opts.subpath}" if cmd_opts.subpath else ""
)
@ -407,7 +407,7 @@ def webui():
ssl_verify=cmd_opts.disable_tls_verify,
debug=cmd_opts.gradio_debug,
auth=gradio_auth_creds,
inbrowser=cmd_opts.autolaunch and os.getenv('SD_WEBUI_RESTARTING ') != '1',
inbrowser=cmd_opts.autolaunch and os.getenv('SD_WEBUI_RESTARTING') != '1',
prevent_thread_lock=True,
allowed_paths=cmd_opts.gradio_allowed_path,
app_kwargs={