File size: 1,590 Bytes
0fbabef |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 |
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)
|