Py之fvcore：fvcore库的简介、安装、使用方法之详细攻略

1. """Configs."""
2. from fvcore.common.config import CfgNode
3. 
4. # -----------------------------------------------------------------------------
5. # Config definition
6. # -----------------------------------------------------------------------------
7. _C = CfgNode()
8. 
9. 
10. # ---------------------------------------------------------------------------- #
11. # Batch norm options
12. # ---------------------------------------------------------------------------- #
13. _C.BN = CfgNode()
14. 
15. # BN epsilon.
16. _C.BN.EPSILON = 1e-5
17. 
18. # BN momentum.
19. _C.BN.MOMENTUM = 0.1
20. 
21. # Precise BN stats.
22. _C.BN.USE_PRECISE_STATS = False
23. 
24. # Number of samples use to compute precise bn.
25. _C.BN.NUM_BATCHES_PRECISE = 200
26. 
27. # Weight decay value that applies on BN.
28. _C.BN.WEIGHT_DECAY = 0.0
29. 
30. 
31. # ---------------------------------------------------------------------------- #
32. # Training options.
33. # ---------------------------------------------------------------------------- #
34. _C.TRAIN = CfgNode()
35. 
36. # If True Train the model, else skip training.
37. _C.TRAIN.ENABLE = True
38. 
39. # Dataset.
40. _C.TRAIN.DATASET = "kinetics"
41. 
42. # Total mini-batch size.
43. _C.TRAIN.BATCH_SIZE = 64
44. 
45. # Evaluate model on test data every eval period epochs.
46. _C.TRAIN.EVAL_PERIOD = 1
47. 
48. # Save model checkpoint every checkpoint period epochs.
49. _C.TRAIN.CHECKPOINT_PERIOD = 1
50. 
51. # Resume training from the latest checkpoint in the output directory.
52. _C.TRAIN.AUTO_RESUME = True
53. 
54. # Path to the checkpoint to load the initial weight.
55. _C.TRAIN.CHECKPOINT_FILE_PATH = ""
56. 
57. # Checkpoint types include `caffe2` or `pytorch`.
58. _C.TRAIN.CHECKPOINT_TYPE = "pytorch"
59. 
60. # If True, perform inflation when loading checkpoint.
61. _C.TRAIN.CHECKPOINT_INFLATE = False