diff --git a/javascript/hints.js b/javascript/hints.js
index 4167cb28b..6de9372e8 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -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;
+ }
+ }
+ }
+});
diff --git a/javascript/ui.js b/javascript/ui.js
index d70a681bf..abf23a78c 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -152,7 +152,11 @@ function submit() {
showSubmitButtons('txt2img', false);
var id = randomId();
- localStorage.setItem("txt2img_task_id", id);
+ 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();
- localStorage.setItem("img2img_task_id", id);
+ 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);
diff --git a/modules/call_queue.py b/modules/call_queue.py
index 61aa240fb..f2eb17d61 100644
--- a/modules/call_queue.py
+++ b/modules/call_queue.py
@@ -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"{html.escape(error_message)}
"]
+ devices.torch_gc()
+
shared.state.skipped = False
shared.state.interrupted = False
shared.state.job_count = 0
diff --git a/modules/errors.py b/modules/errors.py
index 5271a9fe1..dffabe45c 100644
--- a/modules/errors.py
+++ b/modules/errors.py
@@ -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)
diff --git a/modules/extras.py b/modules/extras.py
index e9c0263ec..2a310ae3f 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -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)
diff --git a/modules/img2img.py b/modules/img2img.py
index 132cd100e..68e415ef5 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -10,7 +10,6 @@ from modules import sd_samplers, images as imgutil
from modules.generation_parameters_copypaste import create_override_settings_dict, parse_generation_parameters
from modules.processing import Processed, StableDiffusionProcessingImg2Img, process_images
from modules.shared import opts, state
-from modules.images import save_image
import modules.shared as shared
import modules.processing as processing
from modules.ui import plaintext_to_html
@@ -18,6 +17,7 @@ import modules.scripts
def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=False, scale_by=1.0, use_png_info=False, png_info_props=None, png_info_dir=None):
+ output_dir = output_dir.strip()
processing.fix_seed(p)
images = list(shared.walk_files(input_dir, allowed_extensions=(".png", ".jpg", ".jpeg", ".webp", ".tif", ".tiff")))
@@ -32,11 +32,6 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal
print(f"Will process {len(images)} images, creating {p.n_iter * p.batch_size} new images for each.")
- save_normally = output_dir == ''
-
- p.do_not_save_grid = True
- p.do_not_save_samples = not save_normally
-
state.job_count = len(images) * p.n_iter
# extract "default" params to use in case getting png info fails
@@ -111,21 +106,14 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal
proc = modules.scripts.scripts_img2img.run(p, *args)
if proc is None:
- proc = process_images(p)
-
- for n, processed_image in enumerate(proc.images):
- filename = image_path.stem
- infotext = proc.infotext(p, n)
- relpath = os.path.dirname(os.path.relpath(image, input_dir))
-
- if n > 0:
- filename += f"-{n}"
-
- if not save_normally:
- os.makedirs(os.path.join(output_dir, relpath), exist_ok=True)
- if processed_image.mode == 'RGBA':
- processed_image = processed_image.convert("RGB")
- save_image(processed_image, os.path.join(output_dir, relpath), None, extension=opts.samples_format, info=infotext, forced_filename=filename, save_to_dirs=False)
+ if output_dir:
+ p.outpath_samples = output_dir
+ p.override_settings['save_to_dirs'] = False
+ if p.n_iter > 1 or p.batch_size > 1:
+ p.override_settings['samples_filename_pattern'] = f'{image_path.stem}-[generation_number]'
+ else:
+ p.override_settings['samples_filename_pattern'] = f'{image_path.stem}'
+ process_images(p)
def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, selected_scale_tab: int, height: int, width: int, scale_by: float, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, img2img_batch_use_png_info: bool, img2img_batch_png_info_props: list, img2img_batch_png_info_dir: str, request: gr.Request, *args):
diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py
index 203ae1acc..8169a4596 100644
--- a/modules/prompt_parser.py
+++ b/modules/prompt_parser.py
@@ -19,7 +19,7 @@ prompt: (emphasized | scheduled | alternate | plain | WHITESPACE)*
!emphasized: "(" prompt ")"
| "(" prompt ":" prompt ")"
| "[" prompt "]"
-scheduled: "[" [prompt ":"] prompt ":" [WHITESPACE] NUMBER "]"
+scheduled: "[" [prompt ":"] prompt ":" [WHITESPACE] NUMBER [WHITESPACE] "]"
alternate: "[" prompt ("|" prompt)+ "]"
WHITESPACE: /\s+/
plain: /([^\\\[\]():|]|\\.)+/
@@ -60,11 +60,11 @@ def get_learned_conditioning_prompt_schedules(prompts, steps):
class CollectSteps(lark.Visitor):
def scheduled(self, tree):
- tree.children[-1] = float(tree.children[-1])
- if tree.children[-1] < 1:
- tree.children[-1] *= steps
- tree.children[-1] = min(steps, int(tree.children[-1]))
- res.append(tree.children[-1])
+ tree.children[-2] = float(tree.children[-2])
+ if tree.children[-2] < 1:
+ tree.children[-2] *= steps
+ tree.children[-2] = min(steps, int(tree.children[-2]))
+ res.append(tree.children[-2])
def alternate(self, tree):
res.extend(range(1, steps+1))
@@ -75,7 +75,7 @@ def get_learned_conditioning_prompt_schedules(prompts, steps):
def at_step(step, tree):
class AtStep(lark.Transformer):
def scheduled(self, args):
- before, after, _, when = args
+ before, after, _, when, _ = args
yield before or () if step <= when else after
def alternate(self, args):
yield next(args[(step - 1)%len(args)])
@@ -333,7 +333,7 @@ re_attention = re.compile(r"""
\\|
\(|
\[|
-:([+-]?[.\d]+)\)|
+:\s*([+-]?[.\d]+)\s*\)|
\)|
]|
[^\\()\[\]:]+|
diff --git a/modules/scripts.py b/modules/scripts.py
index 5b4edcac3..edf7347ea 100644
--- a/modules/scripts.py
+++ b/modules/scripts.py
@@ -646,6 +646,8 @@ def add_classes_to_gradio_component(comp):
def IOComponent_init(self, *args, **kwargs):
+ self.webui_tooltip = kwargs.pop('tooltip', None)
+
if scripts_current is not None:
scripts_current.before_component(self, **kwargs)
@@ -663,8 +665,20 @@ def IOComponent_init(self, *args, **kwargs):
return res
+def Block_get_config(self):
+ config = original_Block_get_config(self)
+
+ webui_tooltip = getattr(self, 'webui_tooltip', None)
+ if webui_tooltip:
+ config["webui_tooltip"] = webui_tooltip
+
+ return config
+
+
original_IOComponent_init = gr.components.IOComponent.__init__
+original_Block_get_config = gr.components.Block.get_config
gr.components.IOComponent.__init__ = IOComponent_init
+gr.components.Block.get_config = Block_get_config
def BlockContext_init(self, *args, **kwargs):
diff --git a/modules/sd_models.py b/modules/sd_models.py
index 77195f2f3..40a450df7 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -14,7 +14,8 @@ import ldm.modules.midas as midas
from ldm.util import instantiate_from_config
-from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config, sd_unet, sd_models_xl
+from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config, sd_unet, sd_models_xl, cache
+from modules.sd_hijack_inpainting import do_inpainting_hijack
from modules.timer import Timer
import tomesd
@@ -32,6 +33,8 @@ class CheckpointInfo:
self.filename = filename
abspath = os.path.abspath(filename)
+ self.is_safetensors = os.path.splitext(filename)[1].lower() == ".safetensors"
+
if shared.cmd_opts.ckpt_dir is not None and abspath.startswith(shared.cmd_opts.ckpt_dir):
name = abspath.replace(shared.cmd_opts.ckpt_dir, '')
elif abspath.startswith(model_path):
@@ -42,6 +45,19 @@ class CheckpointInfo:
if name.startswith("\\") or name.startswith("/"):
name = name[1:]
+ def read_metadata():
+ metadata = read_metadata_from_safetensors(filename)
+ self.modelspec_thumbnail = metadata.pop('modelspec.thumbnail', None)
+
+ return metadata
+
+ self.metadata = {}
+ if self.is_safetensors:
+ try:
+ self.metadata = cache.cached_data_for_file('safetensors-metadata', "checkpoint/" + name, filename, read_metadata)
+ except Exception as e:
+ errors.display(e, f"reading metadata for {filename}")
+
self.name = name
self.name_for_extra = os.path.splitext(os.path.basename(filename))[0]
self.model_name = os.path.splitext(name.replace("/", "_").replace("\\", "_"))[0]
@@ -54,15 +70,6 @@ class CheckpointInfo:
self.ids = [self.hash, self.model_name, self.title, name, f'{name} [{self.hash}]'] + ([self.shorthash, self.sha256, f'{self.name} [{self.shorthash}]'] if self.shorthash else [])
- self.metadata = {}
-
- _, ext = os.path.splitext(self.filename)
- if ext.lower() == ".safetensors":
- try:
- self.metadata = read_metadata_from_safetensors(filename)
- except Exception as e:
- errors.display(e, f"reading checkpoint metadata: {filename}")
-
def register(self):
checkpoints_list[self.title] = self
for id in self.ids:
@@ -78,7 +85,7 @@ class CheckpointInfo:
if self.shorthash not in self.ids:
self.ids += [self.shorthash, self.sha256, f'{self.name} [{self.shorthash}]']
- checkpoints_list.pop(self.title)
+ checkpoints_list.pop(self.title, None)
self.title = f'{self.name} [{self.shorthash}]'
self.register()
diff --git a/modules/sysinfo.py b/modules/sysinfo.py
index 5f15ac4fa..cf24c6dd4 100644
--- a/modules/sysinfo.py
+++ b/modules/sysinfo.py
@@ -109,11 +109,15 @@ def format_traceback(tb):
return [[f"{x.filename}, line {x.lineno}, {x.name}", x.line] for x in traceback.extract_tb(tb)]
+def format_exception(e, tb):
+ return {"exception": str(e), "traceback": format_traceback(tb)}
+
+
def get_exceptions():
try:
from modules import errors
- return [{"exception": str(e), "traceback": format_traceback(tb)} for e, tb in reversed(errors.exception_records)]
+ return list(reversed(errors.exception_records))
except Exception as e:
return str(e)
diff --git a/modules/ui.py b/modules/ui.py
index 07ecee7b6..ac2787eb4 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -12,7 +12,7 @@ import numpy as np
from PIL import Image, PngImagePlugin # noqa: F401
from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
-from modules import sd_hijack, sd_models, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, ui_common, ui_postprocessing, progress, ui_loadsave, errors, shared_items, ui_settings, timer, sysinfo
+from modules import sd_hijack, sd_models, script_callbacks, ui_extensions, deepbooru, extra_networks, ui_common, ui_postprocessing, progress, ui_loadsave, errors, shared_items, ui_settings, timer, sysinfo, ui_checkpoint_merger
from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
from modules.paths import script_path
from modules.ui_common import create_refresh_button
@@ -1083,58 +1083,7 @@ def create_ui():
outputs=[html, generation_info, html2],
)
- def update_interp_description(value):
- interp_description_css = "{}
"
- interp_descriptions = {
- "No interpolation": interp_description_css.format("No interpolation will be used. Requires one model; A. Allows for format conversion and VAE baking."),
- "Weighted sum": interp_description_css.format("A weighted sum will be used for interpolation. Requires two models; A and B. The result is calculated as A * (1 - M) + B * M"),
- "Add difference": interp_description_css.format("The difference between the last two models will be added to the first. Requires three models; A, B and C. The result is calculated as A + (B - C) * M")
- }
- return interp_descriptions[value]
-
- with gr.Blocks(analytics_enabled=False) as modelmerger_interface:
- with gr.Row().style(equal_height=False):
- with gr.Column(variant='compact'):
- interp_description = gr.HTML(value=update_interp_description("Weighted sum"), elem_id="modelmerger_interp_description")
-
- with FormRow(elem_id="modelmerger_models"):
- primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)")
- create_refresh_button(primary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_A")
-
- secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary model (B)")
- create_refresh_button(secondary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_B")
-
- tertiary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_tertiary_model_name", label="Tertiary model (C)")
- create_refresh_button(tertiary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_C")
-
- custom_name = gr.Textbox(label="Custom Name (Optional)", elem_id="modelmerger_custom_name")
- interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3, elem_id="modelmerger_interp_amount")
- interp_method = gr.Radio(choices=["No interpolation", "Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method", elem_id="modelmerger_interp_method")
- interp_method.change(fn=update_interp_description, inputs=[interp_method], outputs=[interp_description])
-
- with FormRow():
- checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="safetensors", label="Checkpoint format", elem_id="modelmerger_checkpoint_format")
- save_as_half = gr.Checkbox(value=False, label="Save as float16", elem_id="modelmerger_save_as_half")
- save_metadata = gr.Checkbox(value=True, label="Save metadata (.safetensors only)", elem_id="modelmerger_save_metadata")
-
- with FormRow():
- with gr.Column():
- config_source = gr.Radio(choices=["A, B or C", "B", "C", "Don't"], value="A, B or C", label="Copy config from", type="index", elem_id="modelmerger_config_method")
-
- with gr.Column():
- with FormRow():
- bake_in_vae = gr.Dropdown(choices=["None"] + list(sd_vae.vae_dict), value="None", label="Bake in VAE", elem_id="modelmerger_bake_in_vae")
- create_refresh_button(bake_in_vae, sd_vae.refresh_vae_list, lambda: {"choices": ["None"] + list(sd_vae.vae_dict)}, "modelmerger_refresh_bake_in_vae")
-
- with FormRow():
- discard_weights = gr.Textbox(value="", label="Discard weights with matching name", elem_id="modelmerger_discard_weights")
-
- with gr.Row():
- modelmerger_merge = gr.Button(elem_id="modelmerger_merge", value="Merge", variant='primary')
-
- with gr.Column(variant='compact', elem_id="modelmerger_results_container"):
- with gr.Group(elem_id="modelmerger_results_panel"):
- modelmerger_result = gr.HTML(elem_id="modelmerger_result", show_label=False)
+ modelmerger_ui = ui_checkpoint_merger.UiCheckpointMerger()
with gr.Blocks(analytics_enabled=False) as train_interface:
with gr.Row().style(equal_height=False):
@@ -1464,7 +1413,7 @@ def create_ui():
(img2img_interface, "img2img", "img2img"),
(extras_interface, "Extras", "extras"),
(pnginfo_interface, "PNG Info", "pnginfo"),
- (modelmerger_interface, "Checkpoint Merger", "modelmerger"),
+ (modelmerger_ui.blocks, "Checkpoint Merger", "modelmerger"),
(train_interface, "Train", "train"),
]
@@ -1516,49 +1465,11 @@ def create_ui():
settings.text_settings.change(fn=update_image_cfg_scale_visibility, inputs=[], outputs=[image_cfg_scale])
demo.load(fn=update_image_cfg_scale_visibility, inputs=[], outputs=[image_cfg_scale])
- def modelmerger(*args):
- try:
- results = modules.extras.run_modelmerger(*args)
- except Exception as e:
- errors.report("Error loading/saving model file", exc_info=True)
- modules.sd_models.list_models() # to remove the potentially missing models from the list
- return [*[gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(4)], f"Error merging checkpoints: {e}"]
- return results
-
- modelmerger_merge.click(fn=lambda: '', inputs=[], outputs=[modelmerger_result])
- modelmerger_merge.click(
- fn=wrap_gradio_gpu_call(modelmerger, extra_outputs=lambda: [gr.update() for _ in range(4)]),
- _js='modelmerger',
- inputs=[
- dummy_component,
- primary_model_name,
- secondary_model_name,
- tertiary_model_name,
- interp_method,
- interp_amount,
- save_as_half,
- custom_name,
- checkpoint_format,
- config_source,
- bake_in_vae,
- discard_weights,
- save_metadata,
- ],
- outputs=[
- primary_model_name,
- secondary_model_name,
- tertiary_model_name,
- settings.component_dict['sd_model_checkpoint'],
- modelmerger_result,
- ]
- )
+ modelmerger_ui.setup_ui(dummy_component=dummy_component, sd_model_checkpoint_component=settings.component_dict['sd_model_checkpoint'])
loadsave.dump_defaults()
demo.ui_loadsave = loadsave
- # Required as a workaround for change() event not triggering when loading values from ui-config.json
- interp_description.value = update_interp_description(interp_method.value)
-
return demo
diff --git a/modules/ui_checkpoint_merger.py b/modules/ui_checkpoint_merger.py
new file mode 100644
index 000000000..4863d8610
--- /dev/null
+++ b/modules/ui_checkpoint_merger.py
@@ -0,0 +1,124 @@
+
+import gradio as gr
+
+from modules import sd_models, sd_vae, errors, extras, call_queue
+from modules.ui_components import FormRow
+from modules.ui_common import create_refresh_button
+
+
+def update_interp_description(value):
+ interp_description_css = "{}
"
+ interp_descriptions = {
+ "No interpolation": interp_description_css.format("No interpolation will be used. Requires one model; A. Allows for format conversion and VAE baking."),
+ "Weighted sum": interp_description_css.format("A weighted sum will be used for interpolation. Requires two models; A and B. The result is calculated as A * (1 - M) + B * M"),
+ "Add difference": interp_description_css.format("The difference between the last two models will be added to the first. Requires three models; A, B and C. The result is calculated as A + (B - C) * M")
+ }
+ return interp_descriptions[value]
+
+
+def modelmerger(*args):
+ try:
+ results = extras.run_modelmerger(*args)
+ except Exception as e:
+ errors.report("Error loading/saving model file", exc_info=True)
+ sd_models.list_models() # to remove the potentially missing models from the list
+ return [*[gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)], f"Error merging checkpoints: {e}"]
+ return results
+
+
+class UiCheckpointMerger:
+ def __init__(self):
+ with gr.Blocks(analytics_enabled=False) as modelmerger_interface:
+ with gr.Row().style(equal_height=False):
+ with gr.Column(variant='compact'):
+ self.interp_description = gr.HTML(value=update_interp_description("Weighted sum"), elem_id="modelmerger_interp_description")
+
+ with FormRow(elem_id="modelmerger_models"):
+ self.primary_model_name = gr.Dropdown(sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)")
+ create_refresh_button(self.primary_model_name, sd_models.list_models, lambda: {"choices": sd_models.checkpoint_tiles()}, "refresh_checkpoint_A")
+
+ self.secondary_model_name = gr.Dropdown(sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary model (B)")
+ create_refresh_button(self.secondary_model_name, sd_models.list_models, lambda: {"choices": sd_models.checkpoint_tiles()}, "refresh_checkpoint_B")
+
+ self.tertiary_model_name = gr.Dropdown(sd_models.checkpoint_tiles(), elem_id="modelmerger_tertiary_model_name", label="Tertiary model (C)")
+ create_refresh_button(self.tertiary_model_name, sd_models.list_models, lambda: {"choices": sd_models.checkpoint_tiles()}, "refresh_checkpoint_C")
+
+ self.custom_name = gr.Textbox(label="Custom Name (Optional)", elem_id="modelmerger_custom_name")
+ self.interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3, elem_id="modelmerger_interp_amount")
+ self.interp_method = gr.Radio(choices=["No interpolation", "Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method", elem_id="modelmerger_interp_method")
+ self.interp_method.change(fn=update_interp_description, inputs=[self.interp_method], outputs=[self.interp_description])
+
+ with FormRow():
+ self.checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="safetensors", label="Checkpoint format", elem_id="modelmerger_checkpoint_format")
+ self.save_as_half = gr.Checkbox(value=False, label="Save as float16", elem_id="modelmerger_save_as_half")
+
+ with FormRow():
+ with gr.Column():
+ self.config_source = gr.Radio(choices=["A, B or C", "B", "C", "Don't"], value="A, B or C", label="Copy config from", type="index", elem_id="modelmerger_config_method")
+
+ with gr.Column():
+ with FormRow():
+ self.bake_in_vae = gr.Dropdown(choices=["None"] + list(sd_vae.vae_dict), value="None", label="Bake in VAE", elem_id="modelmerger_bake_in_vae")
+ create_refresh_button(self.bake_in_vae, sd_vae.refresh_vae_list, lambda: {"choices": ["None"] + list(sd_vae.vae_dict)}, "modelmerger_refresh_bake_in_vae")
+
+ with FormRow():
+ self.discard_weights = gr.Textbox(value="", label="Discard weights with matching name", elem_id="modelmerger_discard_weights")
+
+ with gr.Accordion("Metadata", open=False) as metadata_editor:
+ with FormRow():
+ self.save_metadata = gr.Checkbox(value=True, label="Save metadata", elem_id="modelmerger_save_metadata")
+ self.add_merge_recipe = gr.Checkbox(value=True, label="Add merge recipe metadata", elem_id="modelmerger_add_recipe")
+ self.copy_metadata_fields = gr.Checkbox(value=True, label="Copy metadata from merged models", elem_id="modelmerger_copy_metadata")
+
+ self.metadata_json = gr.TextArea('{}', label="Metadata in JSON format")
+ self.read_metadata = gr.Button("Read metadata from selected checkpoints")
+
+ with FormRow():
+ self.modelmerger_merge = gr.Button(elem_id="modelmerger_merge", value="Merge", variant='primary')
+
+ with gr.Column(variant='compact', elem_id="modelmerger_results_container"):
+ with gr.Group(elem_id="modelmerger_results_panel"):
+ self.modelmerger_result = gr.HTML(elem_id="modelmerger_result", show_label=False)
+
+ self.metadata_editor = metadata_editor
+ self.blocks = modelmerger_interface
+
+ def setup_ui(self, dummy_component, sd_model_checkpoint_component):
+ self.checkpoint_format.change(lambda fmt: gr.update(visible=fmt == 'safetensors'), inputs=[self.checkpoint_format], outputs=[self.metadata_editor], show_progress=False)
+
+ self.read_metadata.click(extras.read_metadata, inputs=[self.primary_model_name, self.secondary_model_name, self.tertiary_model_name], outputs=[self.metadata_json])
+
+ self.modelmerger_merge.click(fn=lambda: '', inputs=[], outputs=[self.modelmerger_result])
+ self.modelmerger_merge.click(
+ fn=call_queue.wrap_gradio_gpu_call(modelmerger, extra_outputs=lambda: [gr.update() for _ in range(4)]),
+ _js='modelmerger',
+ inputs=[
+ dummy_component,
+ self.primary_model_name,
+ self.secondary_model_name,
+ self.tertiary_model_name,
+ self.interp_method,
+ self.interp_amount,
+ self.save_as_half,
+ self.custom_name,
+ self.checkpoint_format,
+ self.config_source,
+ self.bake_in_vae,
+ self.discard_weights,
+ self.save_metadata,
+ self.add_merge_recipe,
+ self.copy_metadata_fields,
+ self.metadata_json,
+ ],
+ outputs=[
+ self.primary_model_name,
+ self.secondary_model_name,
+ self.tertiary_model_name,
+ sd_model_checkpoint_component,
+ self.modelmerger_result,
+ ]
+ )
+
+ # Required as a workaround for change() event not triggering when loading values from ui-config.json
+ self.interp_description.value = update_interp_description(self.interp_method.value)
+
diff --git a/modules/ui_extra_networks_checkpoints.py b/modules/ui_extra_networks_checkpoints.py
index 76780cfd0..2bb0a222e 100644
--- a/modules/ui_extra_networks_checkpoints.py
+++ b/modules/ui_extra_networks_checkpoints.py
@@ -23,6 +23,7 @@ class ExtraNetworksPageCheckpoints(ui_extra_networks.ExtraNetworksPage):
"search_term": self.search_terms_from_path(checkpoint.filename) + " " + (checkpoint.sha256 or ""),
"onclick": '"' + html.escape(f"""return selectCheckpoint({quote_js(name)})""") + '"',
"local_preview": f"{path}.{shared.opts.samples_format}",
+ "metadata": checkpoint.metadata,
"sort_keys": {'default': index, **self.get_sort_keys(checkpoint.filename)},
}
diff --git a/modules/ui_extra_networks_user_metadata.py b/modules/ui_extra_networks_user_metadata.py
index 63d4b5031..1cb9eb6fe 100644
--- a/modules/ui_extra_networks_user_metadata.py
+++ b/modules/ui_extra_networks_user_metadata.py
@@ -96,6 +96,7 @@ class UserMetadataEditor:
stats = os.stat(filename)
params = [
+ ('Filename: ', os.path.basename(filename)),
('File size: ', sysinfo.pretty_bytes(stats.st_size)),
('Modified: ', datetime.datetime.fromtimestamp(stats.st_mtime).strftime('%Y-%m-%d %H:%M')),
]
diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py
index 1010845e5..103bf1048 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -3,6 +3,7 @@ from copy import copy
from itertools import permutations, chain
import random
import csv
+import os.path
from io import StringIO
from PIL import Image
import numpy as np
@@ -10,7 +11,7 @@ import numpy as np
import modules.scripts as scripts
import gradio as gr
-from modules import images, sd_samplers, processing, sd_models, sd_vae, sd_samplers_kdiffusion
+from modules import images, sd_samplers, processing, sd_models, sd_vae, sd_samplers_kdiffusion, errors
from modules.processing import process_images, Processed, StableDiffusionProcessingTxt2Img
from modules.shared import opts, state
import modules.shared as shared
@@ -182,6 +183,8 @@ def do_nothing(p, x, xs):
def format_nothing(p, opt, x):
return ""
+def format_remove_path(p, opt, x):
+ return os.path.basename(x)
def str_permutations(x):
"""dummy function for specifying it in AxisOption's type when you want to get a list of permutations"""
@@ -223,7 +226,7 @@ axis_options = [
AxisOption("Prompt order", str_permutations, apply_order, format_value=format_value_join_list),
AxisOptionTxt2Img("Sampler", str, apply_sampler, format_value=format_value, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.samplers]),
AxisOptionImg2Img("Sampler", str, apply_sampler, format_value=format_value, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.samplers_for_img2img]),
- AxisOption("Checkpoint name", str, apply_checkpoint, format_value=format_value, confirm=confirm_checkpoints, cost=1.0, choices=lambda: sorted(sd_models.checkpoints_list, key=str.casefold)),
+ AxisOption("Checkpoint name", str, apply_checkpoint, format_value=format_remove_path, confirm=confirm_checkpoints, cost=1.0, choices=lambda: sorted(sd_models.checkpoints_list, key=str.casefold)),
AxisOption("Negative Guidance minimum sigma", float, apply_field("s_min_uncond")),
AxisOption("Sigma Churn", float, apply_field("s_churn")),
AxisOption("Sigma min", float, apply_field("s_tmin")),
@@ -648,7 +651,12 @@ class Script(scripts.Script):
y_opt.apply(pc, y, ys)
z_opt.apply(pc, z, zs)
- res = process_images(pc)
+ try:
+ res = process_images(pc)
+ except Exception as e:
+ errors.display(e, "generating image for xyz plot")
+
+ res = Processed(p, [], p.seed, "")
# Sets subgrid infotexts
subgrid_index = 1 + iz