Merge branch 'dev' into multiple_loaded_models (0c9b1e79) · Commits · github_fork / Stable Diffusion Webui

javascript/hints.js

+11 −0

Original line number	Diff line number	Diff line
		@@ -190,3 +190,14 @@ onUiUpdate(function(mutationRecords) {
		tooltipCheckTimer = setTimeout(processTooltipCheckNodes, 1000);
		}
		});

		onUiLoaded(function() {
		for (var comp of window.gradio_config.components) {
		if (comp.props.webui_tooltip && comp.props.elem_id) {
		var elem = gradioApp().getElementById(comp.props.elem_id);
		if (elem) {
		elem.title = comp.props.webui_tooltip;
		}
		}
		}
		});

javascript/ui.js

+10 −4

Original line number	Diff line number	Diff line
		@@ -152,7 +152,11 @@ function submit() {
		showSubmitButtons('txt2img', false);

		var id = randomId();
		try {
		localStorage.setItem("txt2img_task_id", id);
		} catch (e) {
		console.warn(`Failed to save txt2img task id to localStorage: ${e}`);
		}

		requestProgress(id, gradioApp().getElementById('txt2img_gallery_container'), gradioApp().getElementById('txt2img_gallery'), function() {
		showSubmitButtons('txt2img', true);
		@@ -171,7 +175,11 @@ function submit_img2img() {
		showSubmitButtons('img2img', false);

		var id = randomId();
		try {
		localStorage.setItem("img2img_task_id", id);
		} catch (e) {
		console.warn(`Failed to save img2img task id to localStorage: ${e}`);
		}

		requestProgress(id, gradioApp().getElementById('img2img_gallery_container'), gradioApp().getElementById('img2img_gallery'), function() {
		showSubmitButtons('img2img', true);
		@@ -191,8 +199,6 @@ function restoreProgressTxt2img() {
		showRestoreProgressButton("txt2img", false);
		var id = localStorage.getItem("txt2img_task_id");

		id = localStorage.getItem("txt2img_task_id");

		if (id) {
		requestProgress(id, gradioApp().getElementById('txt2img_gallery_container'), gradioApp().getElementById('txt2img_gallery'), function() {
		showSubmitButtons('txt2img', true);

modules/call_queue.py

+3 −1

Original line number	Diff line number	Diff line
		@@ -3,7 +3,7 @@ import html
		import threading
		import time

		from modules import shared, progress, errors
		from modules import shared, progress, errors, devices

		queue_lock = threading.Lock()

		@@ -75,6 +75,8 @@ def wrap_gradio_call(func, extra_outputs=None, add_stats=False):
		error_message = f'{type(e).__name__}: {e}'
		res = extra_outputs_array + [f"<div class='error'>{html.escape(error_message)}</div>"]

		devices.torch_gc()

		shared.state.skipped = False
		shared.state.interrupted = False
		shared.state.job_count = 0

modules/errors.py

+2 −1

Original line number	Diff line number	Diff line
		@@ -14,7 +14,8 @@ def record_exception():
		if exception_records and exception_records[-1] == e:
		return

		exception_records.append((e, tb))
		from modules import sysinfo
		exception_records.append(sysinfo.format_exception(e, tb))

		if len(exception_records) > 5:
		exception_records.pop(0)

modules/extras.py

+33 −6

Original line number	Diff line number	Diff line
		@@ -7,7 +7,7 @@ import json
		import torch
		import tqdm

		from modules import shared, images, sd_models, sd_vae, sd_models_config
		from modules import shared, images, sd_models, sd_vae, sd_models_config, errors
		from modules.ui_common import plaintext_to_html
		import gradio as gr
		import safetensors.torch
		@@ -72,7 +72,20 @@ def to_half(tensor, enable):
		return tensor


		def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format, config_source, bake_in_vae, discard_weights, save_metadata):
		def read_metadata(primary_model_name, secondary_model_name, tertiary_model_name):
		metadata = {}

		for checkpoint_name in [primary_model_name, secondary_model_name, tertiary_model_name]:
		checkpoint_info = sd_models.checkpoints_list.get(checkpoint_name, None)
		if checkpoint_info is None:
		continue

		metadata.update(checkpoint_info.metadata)

		return json.dumps(metadata, indent=4, ensure_ascii=False)


		def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format, config_source, bake_in_vae, discard_weights, save_metadata, add_merge_recipe, copy_metadata_fields, metadata_json):
		shared.state.begin(job="model-merge")

		def fail(message):
		@@ -241,11 +254,25 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
		shared.state.textinfo = "Saving"
		print(f"Saving to {output_modelname}...")

		metadata = None
		metadata = {}

		if save_metadata and copy_metadata_fields:
		if primary_model_info:
		metadata.update(primary_model_info.metadata)
		if secondary_model_info:
		metadata.update(secondary_model_info.metadata)
		if tertiary_model_info:
		metadata.update(tertiary_model_info.metadata)

		if save_metadata:
		metadata = {"format": "pt"}
		try:
		metadata.update(json.loads(metadata_json))
		except Exception as e:
		errors.display(e, "readin metadata from json")

		metadata["format"] = "pt"

		if save_metadata and add_merge_recipe:
		merge_recipe = {
		"type": "webui", # indicate this model was merged with webui's built-in merger
		"primary_model_hash": primary_model_info.sha256,
		@@ -261,7 +288,6 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
		"is_inpainting": result_is_inpainting_model,
		"is_instruct_pix2pix": result_is_instruct_pix2pix_model
		}
		metadata["sd_merge_recipe"] = json.dumps(merge_recipe)

		sd_merge_models = {}

		@@ -281,11 +307,12 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
		if tertiary_model_info:
		add_model_metadata(tertiary_model_info)

		metadata["sd_merge_recipe"] = json.dumps(merge_recipe)
		metadata["sd_merge_models"] = json.dumps(sd_merge_models)

		_, extension = os.path.splitext(output_modelname)
		if extension.lower() == ".safetensors":
		safetensors.torch.save_file(theta_0, output_modelname, metadata=metadata)
		safetensors.torch.save_file(theta_0, output_modelname, metadata=metadata if len(metadata)>0 else None)
		else:
		torch.save(theta_0, output_modelname)

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