params.py 998 B

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  1. import numpy as np
  2. seed = 0
  3. n_jobs = 1
  4. data_path_base = 'vtest_new2'
  5. mean = np.array([0.485, 0.456, 0.406])
  6. std = np.array([0.229, 0.224, 0.225])
  7. # test end-to-end
  8. experiment_test = {
  9. 'data_path_base': {data_path_base},
  10. 'conv_model_name': {'resnet'},
  11. 'num_epochs': {10},
  12. 'feature_extract': {True},
  13. 'batch_size': {64},
  14. 'lr': {0.001},
  15. 'use_vggish': {True},
  16. 'momentum': {0.9}
  17. }
  18. experiment_test_3d = {
  19. 'data_path_base': {data_path_base},
  20. 'conv_model_name': {'resnet'},
  21. 'num_epochs': {15},
  22. 'feature_extract': {True, False},
  23. 'batch_size': {64},
  24. 'lr': {0.001},
  25. 'use_vggish': {True, False},
  26. 'momentum': {0.9},
  27. 'use_3d': {True}
  28. }
  29. experiments = {
  30. 'data_path_base': {data_path_base},
  31. 'conv_model_name': {'resnet', None, 'vgg', 'densenet', 'squeezenet'},
  32. 'num_epochs': {10},
  33. 'feature_extract': {True, False},
  34. 'batch_size': {64},
  35. 'lr': {1e-3, 1e-2},
  36. 'use_vggish': {False, True},
  37. 'momentum': {0.9, 0.95}
  38. }