mirror of
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90 lines
2.7 KiB
Python
90 lines
2.7 KiB
Python
import argparse
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from pathlib import Path
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from convert_diffusers_unet import Args as UNetArgs, setup_converter as setup_unet_converter
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from huggingface_hub import hf_hub_download # type: ignore
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from refiners.fluxion.utils import load_from_safetensors, save_to_safetensors
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class Args(argparse.Namespace):
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source_path: str
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output_path: str | None
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subfolder: str
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half: bool
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verbose: bool
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reference_unet_path: str
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def main() -> None:
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parser = argparse.ArgumentParser(description="Converts IC-Light patch weights to work with Refiners")
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parser.add_argument(
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"--from",
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type=str,
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dest="source_path",
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default="lllyasviel/ic-light",
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help=(
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"Can be a path to a .bin file, a .safetensors file or a model name from the Hugging Face Hub. Default:"
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" lllyasviel/ic-light"
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),
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)
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parser.add_argument("--filename", type=str, default="iclight_sd15_fc.safetensors", help="Filename inside the hub.")
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parser.add_argument(
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"--to",
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type=str,
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dest="output_path",
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default=None,
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help=(
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"Output path (.safetensors) for converted model. If not provided, the output path will be the same as the"
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" source path."
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),
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)
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parser.add_argument(
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"--verbose",
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action="store_true",
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default=False,
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help="Prints additional information during conversion. Default: False",
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)
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parser.add_argument(
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"--reference-unet-path",
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type=str,
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dest="reference_unet_path",
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default="runwayml/stable-diffusion-v1-5",
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help="Path to the reference UNet weights.",
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)
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args = parser.parse_args(namespace=Args())
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if args.output_path is None:
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args.output_path = f"{Path(args.filename).stem}-refiners.safetensors"
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patch_file = (
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Path(args.source_path)
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if args.source_path.endswith(".safetensors")
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else Path(
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hf_hub_download(
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repo_id=args.source_path,
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filename=args.filename,
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)
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)
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)
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patch_weights = load_from_safetensors(patch_file)
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unet_args = UNetArgs(
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source_path=args.reference_unet_path,
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subfolder="unet",
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half=False,
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verbose=False,
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skip_init_check=True,
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override_weights=None,
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)
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converter = setup_unet_converter(args=unet_args)
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result = converter._convert_state_dict( # pyright: ignore[reportPrivateUsage]
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source_state_dict=patch_weights,
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target_state_dict=converter.target_model.state_dict(),
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state_dict_mapping=converter.get_mapping(),
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)
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save_to_safetensors(path=args.output_path, tensors=result)
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if __name__ == "__main__":
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main()
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