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5745ce9c7d
- Cache stat collection enabled. - Implemented ONNX loading. - Add ability to specify the repo version variant in installer CLI. - If caller asks for a repo version that doesn't exist, will fall back to empty version rather than raising an error.
42 lines
1.5 KiB
Python
42 lines
1.5 KiB
Python
# Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
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"""Class for Onnx model loading in InvokeAI."""
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# This should work the same as Stable Diffusion pipelines
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from pathlib import Path
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from typing import Optional
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from invokeai.backend.model_manager import (
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AnyModel,
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BaseModelType,
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ModelFormat,
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ModelRepoVariant,
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ModelType,
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SubModelType,
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)
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from invokeai.backend.model_manager.load.load_base import AnyModelLoader
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from invokeai.backend.model_manager.load.load_default import ModelLoader
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@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.ONNX, format=ModelFormat.Onnx)
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@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.ONNX, format=ModelFormat.Olive)
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class OnnyxDiffusersModel(ModelLoader):
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"""Class to load onnx models."""
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def _load_model(
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self,
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model_path: Path,
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model_variant: Optional[ModelRepoVariant] = None,
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submodel_type: Optional[SubModelType] = None,
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) -> AnyModel:
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if not submodel_type is not None:
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raise Exception("A submodel type must be provided when loading onnx pipelines.")
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load_class = self._get_hf_load_class(model_path, submodel_type)
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variant = model_variant.value if model_variant else None
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model_path = model_path / submodel_type.value
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result: AnyModel = load_class.from_pretrained(
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model_path,
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torch_dtype=self._torch_dtype,
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variant=variant,
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) # type: ignore
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return result
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