mirror of
https://github.com/invoke-ai/InvokeAI
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32 lines
1.2 KiB
Python
32 lines
1.2 KiB
Python
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# Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
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"""Class for VAE model loading in InvokeAI."""
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from pathlib import Path
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from typing import Dict, Optional
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import torch
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from invokeai.backend.model_manager import BaseModelType, ModelFormat, ModelRepoVariant, ModelType, SubModelType
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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.Vae, format=ModelFormat.Diffusers)
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class VaeDiffusersModel(ModelLoader):
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"""Class to load VAE 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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) -> Dict[str, torch.Tensor]:
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if submodel_type is not None:
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raise Exception("There are no submodels in VAEs")
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vae_class = self._get_hf_load_class(model_path)
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variant = model_variant.value if model_variant else ""
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result: Dict[str, torch.Tensor] = vae_class.from_pretrained(
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model_path, torch_dtype=self._torch_dtype, variant=variant
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) # type: ignore
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return result
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