| 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("--fp16", action="store_true", help="Whether to convert the model 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, map_location="cpu") |
| else: |
| state_dict = torch.load(args.src, map_location="cpu") |
| |
| try: |
| state_dict = state_dict['state_dict']["state_dict"] |
| except: |
| try: |
| state_dict = state_dict['state_dict'] |
| except: |
| pass |
|
|
| if args.fp16: |
| if any([k.startswith("control_model.") for k, v in state_dict.items()]): |
| state_dict = {k.replace("control_model.", ""): v.half() for k, v in state_dict.items() if k.startswith("control_model.")} |
| else: |
| if any([k.startswith("control_model.") for k, v in state_dict.items()]): |
| state_dict = {k.replace("control_model.", ""): v 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) |
|
|
