cifar.cfg 1.2 KB

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  1. [net]
  2. batch=128
  3. subdivisions=1
  4. height=32
  5. width=32
  6. channels=3
  7. momentum=0.9
  8. decay=0.0005
  9. learning_rate=0.4
  10. policy=poly
  11. power=4
  12. max_batches = 50000
  13. [crop]
  14. crop_width=28
  15. crop_height=28
  16. flip=1
  17. angle=0
  18. saturation = 1
  19. exposure = 1
  20. noadjust=1
  21. [convolutional]
  22. batch_normalize=1
  23. filters=128
  24. size=3
  25. stride=1
  26. pad=1
  27. activation=leaky
  28. [convolutional]
  29. batch_normalize=1
  30. filters=128
  31. size=3
  32. stride=1
  33. pad=1
  34. activation=leaky
  35. [convolutional]
  36. batch_normalize=1
  37. filters=128
  38. size=3
  39. stride=1
  40. pad=1
  41. activation=leaky
  42. [maxpool]
  43. size=2
  44. stride=2
  45. [dropout]
  46. probability=.5
  47. [convolutional]
  48. batch_normalize=1
  49. filters=256
  50. size=3
  51. stride=1
  52. pad=1
  53. activation=leaky
  54. [convolutional]
  55. batch_normalize=1
  56. filters=256
  57. size=3
  58. stride=1
  59. pad=1
  60. activation=leaky
  61. [convolutional]
  62. batch_normalize=1
  63. filters=256
  64. size=3
  65. stride=1
  66. pad=1
  67. activation=leaky
  68. [maxpool]
  69. size=2
  70. stride=2
  71. [dropout]
  72. probability=.5
  73. [convolutional]
  74. batch_normalize=1
  75. filters=512
  76. size=3
  77. stride=1
  78. pad=1
  79. activation=leaky
  80. [convolutional]
  81. batch_normalize=1
  82. filters=512
  83. size=3
  84. stride=1
  85. pad=1
  86. activation=leaky
  87. [convolutional]
  88. batch_normalize=1
  89. filters=512
  90. size=3
  91. stride=1
  92. pad=1
  93. activation=leaky
  94. [dropout]
  95. probability=.5
  96. [convolutional]
  97. filters=10
  98. size=1
  99. stride=1
  100. pad=1
  101. activation=leaky
  102. [avgpool]
  103. [softmax]
  104. groups=1
  105. [cost]