| import argparse | |
| import torch | |
| from safetensors.torch import load_file, save_file | |
| if __name__ == "__main__": | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("--src", default=None, type=str, required=True, help="Path to the model to convert.") | |
| parser.add_argument("--dst", default=None, type=str, required=True, help="Path to the output model.") | |
| parser.add_argument("--half", action="store_true", help="Cast to FP16.") | |
| args = parser.parse_args() | |
| assert args.src is not None, "Must provide a model path!" | |
| assert args.dst is not None, "Must provide a checkpoint path!" | |
| if args.src.endswith(".safetensors"): | |
| state_dict = load_file(args.src) | |
| else: | |
| state_dict = torch.load(args.src) | |
| if any([k.startswith("control_model.") for k, v in state_dict.items()]): | |
| dtype = torch.float16 if args.half else torch.float32 | |
| state_dict = {k.replace("control_model.", ""): v.to(dtype) for k, v in state_dict.items() if k.startswith("control_model.")} | |
| if args.dst.endswith(".safetensors"): | |
| save_file(state_dict, args.dst) | |
| else: | |
| torch.save({"state_dict": state_dict}, args.dst) | |