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)