Merge pull request #9312 from space-nuko/save-merge-recipe

Embed model merge metadata in .safetensors file
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AUTOMATIC1111 2023-04-29 17:15:01 +03:00 committed by GitHub
commit 8987764395
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3 changed files with 57 additions and 4 deletions

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@ -1,6 +1,7 @@
import os import os
import re import re
import shutil import shutil
import json
import torch import torch
@ -71,7 +72,7 @@ def to_half(tensor, enable):
return tensor 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): 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):
shared.state.begin() shared.state.begin()
shared.state.job = 'model-merge' shared.state.job = 'model-merge'
@ -241,13 +242,54 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
shared.state.textinfo = "Saving" shared.state.textinfo = "Saving"
print(f"Saving to {output_modelname}...") print(f"Saving to {output_modelname}...")
metadata = {"format": "pt", "sd_merge_models": {}, "sd_merge_recipe": None}
if save_metadata:
merge_recipe = {
"type": "webui", # indicate this model was merged with webui's built-in merger
"primary_model_hash": primary_model_info.sha256,
"secondary_model_hash": secondary_model_info.sha256 if secondary_model_info else None,
"tertiary_model_hash": tertiary_model_info.sha256 if tertiary_model_info else None,
"interp_method": interp_method,
"multiplier": multiplier,
"save_as_half": save_as_half,
"custom_name": custom_name,
"config_source": config_source,
"bake_in_vae": bake_in_vae,
"discard_weights": discard_weights,
"is_inpainting": result_is_inpainting_model,
"is_instruct_pix2pix": result_is_instruct_pix2pix_model
}
metadata["sd_merge_recipe"] = json.dumps(merge_recipe)
def add_model_metadata(checkpoint_info):
checkpoint_info.calculate_shorthash()
metadata["sd_merge_models"][checkpoint_info.sha256] = {
"name": checkpoint_info.name,
"legacy_hash": checkpoint_info.hash,
"sd_merge_recipe": checkpoint_info.metadata.get("sd_merge_recipe", None)
}
metadata["sd_merge_models"].update(checkpoint_info.metadata.get("sd_merge_models", {}))
add_model_metadata(primary_model_info)
if secondary_model_info:
add_model_metadata(secondary_model_info)
if tertiary_model_info:
add_model_metadata(tertiary_model_info)
metadata["sd_merge_models"] = json.dumps(metadata["sd_merge_models"])
_, extension = os.path.splitext(output_modelname) _, extension = os.path.splitext(output_modelname)
if extension.lower() == ".safetensors": if extension.lower() == ".safetensors":
safetensors.torch.save_file(theta_0, output_modelname, metadata={"format": "pt"}) safetensors.torch.save_file(theta_0, output_modelname, metadata=metadata)
else: else:
torch.save(theta_0, output_modelname) torch.save(theta_0, output_modelname)
sd_models.list_models() sd_models.list_models()
created_model = next((ckpt for ckpt in sd_models.checkpoints_list.values() if ckpt.name == filename), None)
if created_model:
created_model.calculate_shorthash()
create_config(output_modelname, config_source, primary_model_info, secondary_model_info, tertiary_model_info) 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:
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.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): def register(self):
checkpoints_list[self.title] = self checkpoints_list[self.title] = self
for id in self.ids: for id in self.ids:

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@ -1019,8 +1019,9 @@ def create_ui():
interp_method.change(fn=update_interp_description, inputs=[interp_method], outputs=[interp_description]) interp_method.change(fn=update_interp_description, inputs=[interp_method], outputs=[interp_description])
with FormRow(): with FormRow():
checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format", elem_id="modelmerger_checkpoint_format") 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_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 FormRow():
with gr.Column(): with gr.Column():
@ -1658,6 +1659,7 @@ def create_ui():
config_source, config_source,
bake_in_vae, bake_in_vae,
discard_weights, discard_weights,
save_metadata,
], ],
outputs=[ outputs=[
primary_model_name, primary_model_name,