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Merge pull request #9312 from space-nuko/save-merge-recipe
Embed model merge metadata in .safetensors file
This commit is contained in:
commit
8987764395
@ -1,6 +1,7 @@
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import os
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import os
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import re
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import re
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import shutil
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import shutil
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import json
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import torch
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import torch
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@ -71,7 +72,7 @@ def to_half(tensor, enable):
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return tensor
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return tensor
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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):
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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):
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shared.state.begin()
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shared.state.begin()
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shared.state.job = 'model-merge'
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shared.state.job = 'model-merge'
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@ -241,13 +242,54 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
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shared.state.textinfo = "Saving"
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shared.state.textinfo = "Saving"
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print(f"Saving to {output_modelname}...")
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print(f"Saving to {output_modelname}...")
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metadata = {"format": "pt", "sd_merge_models": {}, "sd_merge_recipe": None}
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if save_metadata:
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merge_recipe = {
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"type": "webui", # indicate this model was merged with webui's built-in merger
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"primary_model_hash": primary_model_info.sha256,
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"secondary_model_hash": secondary_model_info.sha256 if secondary_model_info else None,
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"tertiary_model_hash": tertiary_model_info.sha256 if tertiary_model_info else None,
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"interp_method": interp_method,
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"multiplier": multiplier,
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"save_as_half": save_as_half,
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"custom_name": custom_name,
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"config_source": config_source,
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"bake_in_vae": bake_in_vae,
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"discard_weights": discard_weights,
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"is_inpainting": result_is_inpainting_model,
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"is_instruct_pix2pix": result_is_instruct_pix2pix_model
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}
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metadata["sd_merge_recipe"] = json.dumps(merge_recipe)
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def add_model_metadata(checkpoint_info):
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checkpoint_info.calculate_shorthash()
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metadata["sd_merge_models"][checkpoint_info.sha256] = {
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"name": checkpoint_info.name,
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"legacy_hash": checkpoint_info.hash,
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"sd_merge_recipe": checkpoint_info.metadata.get("sd_merge_recipe", None)
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}
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metadata["sd_merge_models"].update(checkpoint_info.metadata.get("sd_merge_models", {}))
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add_model_metadata(primary_model_info)
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if secondary_model_info:
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add_model_metadata(secondary_model_info)
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if tertiary_model_info:
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add_model_metadata(tertiary_model_info)
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metadata["sd_merge_models"] = json.dumps(metadata["sd_merge_models"])
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_, extension = os.path.splitext(output_modelname)
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_, extension = os.path.splitext(output_modelname)
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if extension.lower() == ".safetensors":
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if extension.lower() == ".safetensors":
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safetensors.torch.save_file(theta_0, output_modelname, metadata={"format": "pt"})
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safetensors.torch.save_file(theta_0, output_modelname, metadata=metadata)
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else:
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else:
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torch.save(theta_0, output_modelname)
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torch.save(theta_0, output_modelname)
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sd_models.list_models()
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sd_models.list_models()
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created_model = next((ckpt for ckpt in sd_models.checkpoints_list.values() if ckpt.name == filename), None)
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if created_model:
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created_model.calculate_shorthash()
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create_config(output_modelname, config_source, primary_model_info, secondary_model_info, tertiary_model_info)
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create_config(output_modelname, config_source, primary_model_info, secondary_model_info, tertiary_model_info)
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@ -52,6 +52,15 @@ class CheckpointInfo:
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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 [])
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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 [])
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self.metadata = {}
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_, ext = os.path.splitext(self.filename)
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if ext.lower() == ".safetensors":
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try:
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self.metadata = read_metadata_from_safetensors(filename)
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except Exception as e:
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errors.display(e, f"reading checkpoint metadata: {filename}")
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def register(self):
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def register(self):
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checkpoints_list[self.title] = self
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checkpoints_list[self.title] = self
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for id in self.ids:
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for id in self.ids:
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@ -544,4 +553,4 @@ def unload_model_weights(sd_model=None, info=None):
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print(f"Unloaded weights {timer.summary()}.")
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print(f"Unloaded weights {timer.summary()}.")
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return sd_model
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return sd_model
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@ -1019,8 +1019,9 @@ def create_ui():
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interp_method.change(fn=update_interp_description, inputs=[interp_method], outputs=[interp_description])
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interp_method.change(fn=update_interp_description, inputs=[interp_method], outputs=[interp_description])
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with FormRow():
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with FormRow():
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checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format", elem_id="modelmerger_checkpoint_format")
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checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="safetensors", label="Checkpoint format", elem_id="modelmerger_checkpoint_format")
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save_as_half = gr.Checkbox(value=False, label="Save as float16", elem_id="modelmerger_save_as_half")
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save_as_half = gr.Checkbox(value=False, label="Save as float16", elem_id="modelmerger_save_as_half")
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save_metadata = gr.Checkbox(value=True, label="Save metadata (.safetensors only)", elem_id="modelmerger_save_metadata")
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with FormRow():
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with FormRow():
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with gr.Column():
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with gr.Column():
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@ -1658,6 +1659,7 @@ def create_ui():
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config_source,
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config_source,
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bake_in_vae,
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bake_in_vae,
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discard_weights,
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discard_weights,
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save_metadata,
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],
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],
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outputs=[
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outputs=[
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primary_model_name,
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primary_model_name,
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