diff --git a/modules/extras.py b/modules/extras.py index e9c0263ec7d83d112c42645c18a3cbda64ed911e..2a310ae3f25304f6d3cf6c1c071c77ca4a5e5e4c 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/sd_models.py b/modules/sd_models.py index 1af7fd786cb77e642ec4833bed804676e3f75335..8f72f21d122aaf618752c43b1f40cd6018596b59 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -85,7 +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/ui_checkpoint_merger.py b/modules/ui_checkpoint_merger.py index 8e72258a3406217d9af57a852e636933a4c80c23..4863d861092fdcbb6f3056e7b7107533bf7d25f4 100644 --- a/modules/ui_checkpoint_merger.py +++ b/modules/ui_checkpoint_merger.py @@ -51,7 +51,6 @@ class UiCheckpointMerger: 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") - self.save_metadata = gr.Checkbox(value=True, label="Save metadata (.safetensors only)", elem_id="modelmerger_save_metadata") with FormRow(): with gr.Column(): @@ -65,16 +64,30 @@ class UiCheckpointMerger: with FormRow(): self.discard_weights = gr.Textbox(value="", label="Discard weights with matching name", elem_id="modelmerger_discard_weights") - with gr.Row(): + 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)]), @@ -93,6 +106,9 @@ class UiCheckpointMerger: 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,