Upload extract_controlnet.py
Browse files- extract_controlnet.py +39 -0
extract_controlnet.py
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import argparse
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import torch
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from safetensors.torch import load_file, save_file
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument("--src", default=None, type=str, required=True, help="Path to the model to convert.")
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parser.add_argument("--dst", default=None, type=str, required=True, help="Path to the output model.")
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parser.add_argument("--fp16", action="store_true", help="Whether to convert the model to fp16.")
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args = parser.parse_args()
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assert args.src is not None, "Must provide a model path!"
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assert args.dst is not None, "Must provide a checkpoint path!"
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if args.src.endswith(".safetensors"):
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state_dict = load_file(args.src, map_location="cpu")
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else:
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state_dict = torch.load(args.src, map_location="cpu")
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try:
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state_dict = state_dict['state_dict']["state_dict"]
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except:
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try:
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state_dict = state_dict['state_dict']
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except:
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pass
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if args.fp16:
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if any([k.startswith("control_model.") for k, v in state_dict.items()]):
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state_dict = {k.replace("control_model.", ""): v.half() for k, v in state_dict.items() if k.startswith("control_model.")}
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else:
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if any([k.startswith("control_model.") for k, v in state_dict.items()]):
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state_dict = {k.replace("control_model.", ""): v for k, v in state_dict.items() if k.startswith("control_model.")}
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if args.dst.endswith(".safetensors"):
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save_file(state_dict, args.dst)
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else:
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torch.save({"state_dict": state_dict}, args.dst)
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