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71a1740740
- No longer install core conversion models. Use the HuggingFace cache to load them if and when needed. - Call directly into the diffusers library to perform conversions with only shallow wrappers around them to massage arguments, etc. - At root configuration time, do not create all the possible model subdirectories, but let them be created and populated at model install time. - Remove checks for missing core conversion files, since they are no longer installed.
59 lines
2.2 KiB
Python
59 lines
2.2 KiB
Python
# Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
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"""Class for ControlNet model loading in InvokeAI."""
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from pathlib import Path
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from invokeai.backend.model_manager import (
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AnyModelConfig,
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BaseModelType,
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ModelFormat,
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ModelType,
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)
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from invokeai.backend.model_manager.config import CheckpointConfigBase
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from invokeai.backend.model_manager.convert_ckpt_to_diffusers import convert_controlnet_to_diffusers
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from .. import ModelLoaderRegistry
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from .generic_diffusers import GenericDiffusersLoader
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@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.ControlNet, format=ModelFormat.Diffusers)
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@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.ControlNet, format=ModelFormat.Checkpoint)
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class ControlNetLoader(GenericDiffusersLoader):
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"""Class to load ControlNet models."""
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def _needs_conversion(self, config: AnyModelConfig, model_path: Path, dest_path: Path) -> bool:
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if not isinstance(config, CheckpointConfigBase):
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return False
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elif (
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dest_path.exists()
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and (dest_path / "config.json").stat().st_mtime >= (config.converted_at or 0.0)
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and (dest_path / "config.json").stat().st_mtime >= model_path.stat().st_mtime
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):
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return False
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else:
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return True
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def _convert_model(self, config: AnyModelConfig, model_path: Path, output_path: Path) -> Path:
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assert isinstance(config, CheckpointConfigBase)
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config_file = config.config_path
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image_size = (
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512
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if config.base == BaseModelType.StableDiffusion1
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else 768
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if config.base == BaseModelType.StableDiffusion2
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else 1024
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)
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self._logger.info(f"Converting {model_path} to diffusers format")
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with open(self._app_config.root_path / config_file, "r") as config_stream:
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convert_controlnet_to_diffusers(
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model_path,
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output_path,
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original_config_file=config_stream,
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image_size=image_size,
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precision=self._torch_dtype,
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from_safetensors=model_path.suffix == ".safetensors",
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)
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return output_path
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