classification.py 1.2 KB

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  1. # copytrue (c) 2020 PaddlePaddle Authors. All Rights Reserve.
  2. #
  3. # Licensed under the Apache License, Version 2.0 (the "License");
  4. # you may not use this file except in compliance with the License.
  5. # You may obtain a copy of the License at
  6. #
  7. # http://www.apache.org/licenses/LICENSE-2.0
  8. #
  9. # Unless required by applicable law or agreed to in writing, software
  10. # distributed under the License is distributed on an "AS IS" BASIS,
  11. # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  12. # See the License for the specific language governing permissions and
  13. # limitations under the License.
  14. import os.path as osp
  15. def prune(best_model_path, dataset_path, sensitivities_path, batch_size):
  16. import paddlex as pdx
  17. print(best_model_path)
  18. model = pdx.load_model(best_model_path)
  19. eval_dataset = pdx.datasets.ImageNet(
  20. data_dir=dataset_path,
  21. file_list=osp.join(dataset_path, 'val_list.txt'),
  22. label_list=osp.join(dataset_path, 'labels.txt'),
  23. transforms=model.test_transforms)
  24. model.analyze_sensitivity(
  25. dataset=eval_dataset,
  26. batch_size=batch_size,
  27. criterion='l1_norm',
  28. save_dir=sensitivities_path)