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ncnn/benchmark/alexnet.param

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  1. 7767517

  2. 24 24

  3. Input            data             0 1 data 0=227 1=227 2=3

  4. Convolution      conv1            1 1 data conv1 0=96 1=11 2=1 3=4 4=0 5=1 6=34848

  5. ReLU             relu1            1 1 conv1 conv1_relu1

  6. LRN              norm1            1 1 conv1_relu1 norm1 0=0 1=5 2=0.000100 3=0.750000

  7. Pooling          pool1            1 1 norm1 pool1 0=0 1=3 2=2 3=0 4=0

  8. ConvolutionDepthWise conv2            1 1 pool1 conv2 0=256 1=5 2=1 3=1 4=2 5=1 6=307200 7=2

  9. ReLU             relu2            1 1 conv2 conv2_relu2

  10. LRN              norm2            1 1 conv2_relu2 norm2 0=0 1=5 2=0.000100 3=0.750000

  11. Pooling          pool2            1 1 norm2 pool2 0=0 1=3 2=2 3=0 4=0

  12. Convolution      conv3            1 1 pool2 conv3 0=384 1=3 2=1 3=1 4=1 5=1 6=884736

  13. ReLU             relu3            1 1 conv3 conv3_relu3

  14. ConvolutionDepthWise conv4            1 1 conv3_relu3 conv4 0=384 1=3 2=1 3=1 4=1 5=1 6=663552 7=2

  15. ReLU             relu4            1 1 conv4 conv4_relu4

  16. ConvolutionDepthWise conv5            1 1 conv4_relu4 conv5 0=256 1=3 2=1 3=1 4=1 5=1 6=442368 7=2

  17. ReLU             relu5            1 1 conv5 conv5_relu5

  18. Pooling          pool5            1 1 conv5_relu5 pool5 0=0 1=3 2=2 3=0 4=0

  19. InnerProduct     fc6              1 1 pool5 fc6 0=4096 1=1 2=37748736

  20. ReLU             relu6            1 1 fc6 fc6_relu6

  21. Dropout          drop6            1 1 fc6_relu6 fc6_drop6

  22. InnerProduct     fc7              1 1 fc6_drop6 fc7 0=4096 1=1 2=16777216

  23. ReLU             relu7            1 1 fc7 fc7_relu7

  24. Dropout          drop7            1 1 fc7_relu7 fc7_drop7

  25. InnerProduct     fc8              1 1 fc7_drop7 fc8 0=1000 1=1 2=4096000

  26. Softmax          prob             1 1 fc8 prob 0=0