| # Copyright (c) 2020 Mobvoi Inc. (authors: Binbin Zhang) | |
| # | |
| # 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. | |
| import logging | |
| import os | |
| import re | |
| import yaml | |
| import torch | |
| from collections import OrderedDict | |
| import datetime | |
| def load_checkpoint(model: torch.nn.Module, model_pth: str) -> dict: | |
| checkpoint = torch.load(model_pth, map_location='cpu') | |
| checkpoint = checkpoint['model'] if 'model' in checkpoint else checkpoint | |
| model.load_state_dict(checkpoint, strict=True) | |
| info_path = re.sub('.pth$', '.yaml', model_pth) | |
| configs = {} | |
| if os.path.exists(info_path): | |
| with open(info_path, 'r') as fin: | |
| configs = yaml.load(fin, Loader=yaml.FullLoader) | |
| return configs | |