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https://github.com/invoke-ai/InvokeAI
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add API for model convert
This commit is contained in:
Lincoln Stein
parent
5027d0a603
commit
5b6dd47b9f
@ -9,9 +9,11 @@ from starlette.exceptions import HTTPException
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from invokeai.backend import BaseModelType, ModelType
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from invokeai.backend.model_management import AddModelResult
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from invokeai.backend.model_management.models import (MODEL_CONFIGS,
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OPENAPI_MODEL_CONFIGS,
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SchedulerPredictionType)
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from invokeai.backend.model_management.models import (
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MODEL_CONFIGS,
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OPENAPI_MODEL_CONFIGS,
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SchedulerPredictionType
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)
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from ..dependencies import ApiDependencies
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@ -25,11 +27,6 @@ class ImportModelResponse(BaseModel):
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location: str = Field(description="The path, repo_id or URL of the imported model")
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info: AddModelResult = Field(description="The model info")
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class ConvertModelResponse(BaseModel):
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name: str = Field(description="The name of the imported model")
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info: AddModelResult = Field(description="The model info")
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status: str = Field(description="The status of the API response")
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class ModelsList(BaseModel):
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models: list[Union[tuple(OPENAPI_MODEL_CONFIGS)]]
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@ -168,75 +165,36 @@ async def delete_model(
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logger.error(f"Model not found: {model_name}")
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raise HTTPException(status_code=404, detail=f"Model '{model_name}' not found")
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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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@models_router.patch(
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"/convert/{base_model}/{model_type}/{model_name}",
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operation_id="convert_model",
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responses={
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200: { "description": "Model converted successfully" },
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400: {"description" : "Bad request" },
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404: { "description": "Model not found" },
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},
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status_code = 200,
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response_model = Union[tuple(MODEL_CONFIGS)],
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)
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async def convert_model(
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base_model: BaseModelType = Path(description="Base model"),
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model_type: ModelType = Path(description="The type of model"),
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model_name: str = Path(description="model name"),
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) -> Union[tuple(MODEL_CONFIGS)]:
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"""Convert a checkpoint model into a diffusers model"""
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logger = ApiDependencies.invoker.services.logger
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try:
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logger.info(f"Converting model: {model_name}")
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result = ApiDependencies.invoker.services.model_manager.convert_model(model_name,
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base_model = base_model,
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model_type = model_type
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)
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except KeyError:
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raise HTTPException(status_code=404, detail=f"Model '{model_name}' not found")
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except ValueError as e:
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raise HTTPException(status_code=400, detail=str(e))
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return result.config
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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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@ -651,7 +651,7 @@ class ModelManager(object):
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)
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checkpoint_path = self.app_config.root_path / info["path"]
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old_diffusers_path = self.app_config.models_path / model.location
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new_diffusers_path = self.app_config.models_path / base_model / model_type / model_name
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new_diffusers_path = self.app_config.models_path / base_model.value / model_type.value / model_name
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if new_diffusers_path.exists():
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raise ValueError(f"A diffusers model already exists at {new_path}")
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