params.py 1.0 KB

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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. vggish_frame_rate = 0.96
  8. # test end-to-end
  9. experiment_test = {
  10. 'data_path_base': {data_path_base},
  11. 'conv_model_name': {'resnet'},
  12. 'num_epochs': {10},
  13. 'feature_extract': {False},
  14. 'batch_size': {64},
  15. 'lr': {0.001},
  16. 'use_vggish': {True},
  17. 'momentum': {0.9}
  18. }
  19. experiment_test_3d = {
  20. 'data_path_base': {data_path_base},
  21. 'conv_model_name': {'resnet'},
  22. 'num_epochs': {15},
  23. 'feature_extract': {True, False},
  24. 'batch_size': {64},
  25. 'lr': {0.001},
  26. 'use_vggish': {True, False},
  27. 'momentum': {0.9},
  28. 'use_3d': {True}
  29. }
  30. experiments = {
  31. 'data_path_base': {data_path_base},
  32. 'conv_model_name': {'resnet', None, 'vgg', 'densenet', 'squeezenet'},
  33. 'num_epochs': {10},
  34. 'feature_extract': {True, False},
  35. 'batch_size': {64},
  36. 'lr': {1e-3, 1e-2},
  37. 'use_vggish': {False, True},
  38. 'momentum': {0.9, 0.95}
  39. }