| #!/usr/bin/env python | |
| # Copyright 2020 The HuggingFace Team. All rights reserved. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| from typing import Union | |
| import fire | |
| import torch | |
| from tqdm import tqdm | |
| def convert(src_path: str, map_location: str = "cpu", save_path: Union[str, None] = None) -> None: | |
| """Convert a pytorch_model.bin or model.pt file to torch.float16 for faster downloads, less disk space.""" | |
| state_dict = torch.load(src_path, map_location=map_location, weights_only=True) | |
| for k, v in tqdm(state_dict.items()): | |
| if not isinstance(v, torch.Tensor): | |
| raise TypeError("FP16 conversion only works on paths that are saved state dicts, like pytorch_model.bin") | |
| state_dict[k] = v.half() | |
| if save_path is None: # overwrite src_path | |
| save_path = src_path | |
| torch.save(state_dict, save_path) | |
| if __name__ == "__main__": | |
| fire.Fire(convert) | |