diff --git a/modules/extras.py b/modules/extras.py index d8ece955..77d88592 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -1,6 +1,7 @@ import os import re import shutil +import json import torch @@ -71,7 +72,7 @@ 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): +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.job = 'model-merge' @@ -241,13 +242,52 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_ shared.state.textinfo = "Saving" print(f"Saving to {output_modelname}...") + metadata = {"format": "pt", "models": {}, "merge_recipe": None} + + if save_metadata: + merge_recipe = { + "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["merge_recipe"] = json.dumps(merge_recipe) + + def add_model_metadata(checkpoint_info): + metadata["models"][checkpoint_info.sha256] = { + "name": checkpoint_info.name, + "legacy_hash": checkpoint_info.hash, + "merge_recipe": checkpoint_info.metadata.get("merge_recipe", None) + } + + metadata["models"].update(checkpoint_info.metadata.get("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["models"] = json.dumps(metadata["models"]) + _, extension = os.path.splitext(output_modelname) 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: torch.save(theta_0, output_modelname) 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) diff --git a/modules/sd_models.py b/modules/sd_models.py index 6ea874df..4f7613a1 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -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.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: @@ -544,4 +553,4 @@ def unload_model_weights(sd_model=None, info=None): print(f"Unloaded weights {timer.summary()}.") - return sd_model \ No newline at end of file + return sd_model diff --git a/modules/ui.py b/modules/ui.py index 627fbe0b..64fb93c3 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1019,8 +1019,9 @@ def create_ui(): interp_method.change(fn=update_interp_description, inputs=[interp_method], outputs=[interp_description]) 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_metadata = gr.Checkbox(value=True, label="Save metadata (.safetensors only)", elem_id="modelmerger_save_metadata") with FormRow(): with gr.Column(): @@ -1658,6 +1659,7 @@ def create_ui(): config_source, bake_in_vae, discard_weights, + save_metadata, ], outputs=[ primary_model_name,