mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
279 lines
11 KiB
Python
279 lines
11 KiB
Python
# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
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from typing import Annotated, Any, List, Literal, Optional, Union
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from fastapi.routing import APIRouter
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from pydantic import BaseModel, Field, parse_obj_as
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from ..dependencies import ApiDependencies
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models_router = APIRouter(prefix="/v1/models", tags=["models"])
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class VaeRepo(BaseModel):
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repo_id: str = Field(description="The repo ID to use for this VAE")
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path: Optional[str] = Field(description="The path to the VAE")
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subfolder: Optional[str] = Field(description="The subfolder to use for this VAE")
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class ModelInfo(BaseModel):
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description: Optional[str] = Field(description="A description of the model")
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class CkptModelInfo(ModelInfo):
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format: Literal['ckpt'] = 'ckpt'
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config: str = Field(description="The path to the model config")
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weights: str = Field(description="The path to the model weights")
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vae: str = Field(description="The path to the model VAE")
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width: Optional[int] = Field(description="The width of the model")
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height: Optional[int] = Field(description="The height of the model")
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class DiffusersModelInfo(ModelInfo):
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format: Literal['diffusers'] = 'diffusers'
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vae: Optional[VaeRepo] = Field(description="The VAE repo to use for this model")
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repo_id: Optional[str] = Field(description="The repo ID to use for this model")
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path: Optional[str] = Field(description="The path to the model")
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class ModelsList(BaseModel):
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models: dict[str, Annotated[Union[(CkptModelInfo,DiffusersModelInfo)], Field(discriminator="format")]]
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@models_router.get(
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"/",
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operation_id="list_models",
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responses={200: {"model": ModelsList }},
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)
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async def list_models() -> ModelsList:
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"""Gets a list of models"""
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models_raw = ApiDependencies.invoker.services.model_manager.list_models()
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models = parse_obj_as(ModelsList, { "models": models_raw })
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return models
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# @socketio.on("requestSystemConfig")
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# def handle_request_capabilities():
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# print(">> System config requested")
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# config = self.get_system_config()
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# config["model_list"] = self.generate.model_manager.list_models()
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# config["infill_methods"] = infill_methods()
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# socketio.emit("systemConfig", config)
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# @socketio.on("searchForModels")
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# def handle_search_models(search_folder: str):
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# try:
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# if not search_folder:
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# socketio.emit(
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# "foundModels",
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# {"search_folder": None, "found_models": None},
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# )
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# else:
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# (
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# search_folder,
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# found_models,
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# ) = self.generate.model_manager.search_models(search_folder)
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# socketio.emit(
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# "foundModels",
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# {"search_folder": search_folder, "found_models": found_models},
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# )
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# except Exception as e:
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# self.handle_exceptions(e)
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# print("\n")
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# @socketio.on("addNewModel")
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# def handle_add_model(new_model_config: dict):
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# try:
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# model_name = new_model_config["name"]
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# del new_model_config["name"]
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# model_attributes = new_model_config
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# if len(model_attributes["vae"]) == 0:
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# del model_attributes["vae"]
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# update = False
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# current_model_list = self.generate.model_manager.list_models()
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# if model_name in current_model_list:
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# update = True
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# print(f">> Adding New Model: {model_name}")
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# self.generate.model_manager.add_model(
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# model_name=model_name,
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# model_attributes=model_attributes,
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# clobber=True,
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# )
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# self.generate.model_manager.commit(opt.conf)
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# new_model_list = self.generate.model_manager.list_models()
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# socketio.emit(
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# "newModelAdded",
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# {
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# "new_model_name": model_name,
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# "model_list": new_model_list,
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# "update": update,
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# },
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# )
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# print(f">> New Model Added: {model_name}")
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# except Exception as e:
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# self.handle_exceptions(e)
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# @socketio.on("deleteModel")
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# def handle_delete_model(model_name: str):
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# try:
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# print(f">> Deleting Model: {model_name}")
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# self.generate.model_manager.del_model(model_name)
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# self.generate.model_manager.commit(opt.conf)
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# updated_model_list = self.generate.model_manager.list_models()
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# socketio.emit(
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# "modelDeleted",
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# {
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# "deleted_model_name": model_name,
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# "model_list": updated_model_list,
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# },
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# )
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# print(f">> Model Deleted: {model_name}")
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# except Exception as e:
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# self.handle_exceptions(e)
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# @socketio.on("requestModelChange")
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# def handle_set_model(model_name: str):
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# try:
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# print(f">> Model change requested: {model_name}")
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# model = self.generate.set_model(model_name)
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# model_list = self.generate.model_manager.list_models()
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# if model is None:
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# socketio.emit(
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# "modelChangeFailed",
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# {"model_name": model_name, "model_list": model_list},
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# )
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# else:
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# socketio.emit(
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# "modelChanged",
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# {"model_name": model_name, "model_list": model_list},
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# )
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# except Exception as e:
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# self.handle_exceptions(e)
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# @socketio.on("convertToDiffusers")
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# def convert_to_diffusers(model_to_convert: dict):
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# try:
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# if model_info := self.generate.model_manager.model_info(
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# model_name=model_to_convert["model_name"]
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# ):
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# if "weights" in model_info:
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# ckpt_path = Path(model_info["weights"])
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# original_config_file = Path(model_info["config"])
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# model_name = model_to_convert["model_name"]
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# model_description = model_info["description"]
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# else:
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# self.socketio.emit(
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# "error", {"message": "Model is not a valid checkpoint file"}
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# )
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# else:
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# self.socketio.emit(
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# "error", {"message": "Could not retrieve model info."}
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# )
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# if not ckpt_path.is_absolute():
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# ckpt_path = Path(Globals.root, ckpt_path)
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# if original_config_file and not original_config_file.is_absolute():
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# original_config_file = Path(Globals.root, original_config_file)
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# diffusers_path = Path(
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# ckpt_path.parent.absolute(), f"{model_name}_diffusers"
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# )
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# if model_to_convert["save_location"] == "root":
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# diffusers_path = Path(
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# global_converted_ckpts_dir(), f"{model_name}_diffusers"
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# )
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# if (
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# model_to_convert["save_location"] == "custom"
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# and model_to_convert["custom_location"] is not None
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# ):
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# diffusers_path = Path(
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# model_to_convert["custom_location"], f"{model_name}_diffusers"
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# )
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# if diffusers_path.exists():
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# shutil.rmtree(diffusers_path)
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# self.generate.model_manager.convert_and_import(
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# ckpt_path,
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# diffusers_path,
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# model_name=model_name,
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# model_description=model_description,
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# vae=None,
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# original_config_file=original_config_file,
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# commit_to_conf=opt.conf,
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# )
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# new_model_list = self.generate.model_manager.list_models()
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# socketio.emit(
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# "modelConverted",
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# {
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# "new_model_name": model_name,
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# "model_list": new_model_list,
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# "update": True,
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# },
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# )
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# print(f">> Model Converted: {model_name}")
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# except Exception as e:
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# self.handle_exceptions(e)
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# @socketio.on("mergeDiffusersModels")
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# def merge_diffusers_models(model_merge_info: dict):
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# try:
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# models_to_merge = model_merge_info["models_to_merge"]
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# model_ids_or_paths = [
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# self.generate.model_manager.model_name_or_path(x)
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# for x in models_to_merge
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# ]
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# merged_pipe = merge_diffusion_models(
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# model_ids_or_paths,
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# model_merge_info["alpha"],
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# model_merge_info["interp"],
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# model_merge_info["force"],
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# )
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# dump_path = global_models_dir() / "merged_models"
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# if model_merge_info["model_merge_save_path"] is not None:
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# dump_path = Path(model_merge_info["model_merge_save_path"])
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# os.makedirs(dump_path, exist_ok=True)
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# dump_path = dump_path / model_merge_info["merged_model_name"]
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# merged_pipe.save_pretrained(dump_path, safe_serialization=1)
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# merged_model_config = dict(
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# model_name=model_merge_info["merged_model_name"],
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# description=f'Merge of models {", ".join(models_to_merge)}',
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# commit_to_conf=opt.conf,
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# )
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# if vae := self.generate.model_manager.config[models_to_merge[0]].get(
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# "vae", None
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# ):
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# print(f">> Using configured VAE assigned to {models_to_merge[0]}")
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# merged_model_config.update(vae=vae)
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# self.generate.model_manager.import_diffuser_model(
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# dump_path, **merged_model_config
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# )
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# new_model_list = self.generate.model_manager.list_models()
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# socketio.emit(
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# "modelsMerged",
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# {
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# "merged_models": models_to_merge,
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# "merged_model_name": model_merge_info["merged_model_name"],
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# "model_list": new_model_list,
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# "update": True,
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# },
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# )
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# print(f">> Models Merged: {models_to_merge}")
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# print(f">> New Model Added: {model_merge_info['merged_model_name']}")
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# except Exception as e:
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# self.handle_exceptions(e) |