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ly0/gist:c4c8455800ddec0caadd8ac3cbb2773f

Created December 27, 2019 10:38
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  1. ly0 created this gist Dec 27, 2019.
    2,316 changes: 2,316 additions & 0 deletions gistfile1.txt
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    Original file line number Diff line number Diff line change
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    name: "ResNet-50"
    input: "data"
    input_dim: 1
    input_dim: 3
    input_dim: 224
    input_dim: 224
    layer {
    bottom: "data"
    top: "conv1"
    name: "conv1"
    type: "Convolution"
    convolution_param {
    num_output: 64
    kernel_size: 7
    pad: 3
    stride: 2
    }
    }

    layer {
    bottom: "conv1"
    top: "conv1"
    name: "bn_conv1"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "conv1"
    top: "conv1"
    name: "scale_conv1"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "conv1"
    top: "conv1"
    name: "conv1_relu"
    type: "ReLU"
    }

    layer {
    bottom: "conv1"
    top: "pool1"
    name: "pool1"
    type: "Pooling"
    pooling_param {
    kernel_size: 3
    stride: 2
    pool: MAX
    }
    }

    layer {
    bottom: "pool1"
    top: "res2a_branch1"
    name: "res2a_branch1"
    type: "Convolution"
    convolution_param {
    num_output: 256
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res2a_branch1"
    top: "res2a_branch1"
    name: "bn2a_branch1"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res2a_branch1"
    top: "res2a_branch1"
    name: "scale2a_branch1"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "pool1"
    top: "res2a_branch2a"
    name: "res2a_branch2a"
    type: "Convolution"
    convolution_param {
    num_output: 64
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res2a_branch2a"
    top: "res2a_branch2a"
    name: "bn2a_branch2a"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res2a_branch2a"
    top: "res2a_branch2a"
    name: "scale2a_branch2a"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res2a_branch2a"
    top: "res2a_branch2a"
    name: "res2a_branch2a_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res2a_branch2a"
    top: "res2a_branch2b"
    name: "res2a_branch2b"
    type: "Convolution"
    convolution_param {
    num_output: 64
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res2a_branch2b"
    top: "res2a_branch2b"
    name: "bn2a_branch2b"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res2a_branch2b"
    top: "res2a_branch2b"
    name: "scale2a_branch2b"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res2a_branch2b"
    top: "res2a_branch2b"
    name: "res2a_branch2b_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res2a_branch2b"
    top: "res2a_branch2c"
    name: "res2a_branch2c"
    type: "Convolution"
    convolution_param {
    num_output: 256
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res2a_branch2c"
    top: "res2a_branch2c"
    name: "bn2a_branch2c"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res2a_branch2c"
    top: "res2a_branch2c"
    name: "scale2a_branch2c"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res2a_branch1"
    bottom: "res2a_branch2c"
    top: "res2a"
    name: "res2a"
    type: "Eltwise"
    }

    layer {
    bottom: "res2a"
    top: "res2a"
    name: "res2a_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res2a"
    top: "res2b_branch2a"
    name: "res2b_branch2a"
    type: "Convolution"
    convolution_param {
    num_output: 64
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res2b_branch2a"
    top: "res2b_branch2a"
    name: "bn2b_branch2a"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res2b_branch2a"
    top: "res2b_branch2a"
    name: "scale2b_branch2a"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res2b_branch2a"
    top: "res2b_branch2a"
    name: "res2b_branch2a_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res2b_branch2a"
    top: "res2b_branch2b"
    name: "res2b_branch2b"
    type: "Convolution"
    convolution_param {
    num_output: 64
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res2b_branch2b"
    top: "res2b_branch2b"
    name: "bn2b_branch2b"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res2b_branch2b"
    top: "res2b_branch2b"
    name: "scale2b_branch2b"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res2b_branch2b"
    top: "res2b_branch2b"
    name: "res2b_branch2b_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res2b_branch2b"
    top: "res2b_branch2c"
    name: "res2b_branch2c"
    type: "Convolution"
    convolution_param {
    num_output: 256
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res2b_branch2c"
    top: "res2b_branch2c"
    name: "bn2b_branch2c"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res2b_branch2c"
    top: "res2b_branch2c"
    name: "scale2b_branch2c"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res2a"
    bottom: "res2b_branch2c"
    top: "res2b"
    name: "res2b"
    type: "Eltwise"
    }

    layer {
    bottom: "res2b"
    top: "res2b"
    name: "res2b_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res2b"
    top: "res2c_branch2a"
    name: "res2c_branch2a"
    type: "Convolution"
    convolution_param {
    num_output: 64
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res2c_branch2a"
    top: "res2c_branch2a"
    name: "bn2c_branch2a"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res2c_branch2a"
    top: "res2c_branch2a"
    name: "scale2c_branch2a"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res2c_branch2a"
    top: "res2c_branch2a"
    name: "res2c_branch2a_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res2c_branch2a"
    top: "res2c_branch2b"
    name: "res2c_branch2b"
    type: "Convolution"
    convolution_param {
    num_output: 64
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res2c_branch2b"
    top: "res2c_branch2b"
    name: "bn2c_branch2b"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res2c_branch2b"
    top: "res2c_branch2b"
    name: "scale2c_branch2b"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res2c_branch2b"
    top: "res2c_branch2b"
    name: "res2c_branch2b_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res2c_branch2b"
    top: "res2c_branch2c"
    name: "res2c_branch2c"
    type: "Convolution"
    convolution_param {
    num_output: 256
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res2c_branch2c"
    top: "res2c_branch2c"
    name: "bn2c_branch2c"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res2c_branch2c"
    top: "res2c_branch2c"
    name: "scale2c_branch2c"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res2b"
    bottom: "res2c_branch2c"
    top: "res2c"
    name: "res2c"
    type: "Eltwise"
    }

    layer {
    bottom: "res2c"
    top: "res2c"
    name: "res2c_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res2c"
    top: "res3a_branch1"
    name: "res3a_branch1"
    type: "Convolution"
    convolution_param {
    num_output: 512
    kernel_size: 1
    pad: 0
    stride: 2
    bias_term: false
    }
    }

    layer {
    bottom: "res3a_branch1"
    top: "res3a_branch1"
    name: "bn3a_branch1"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res3a_branch1"
    top: "res3a_branch1"
    name: "scale3a_branch1"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res2c"
    top: "res3a_branch2a"
    name: "res3a_branch2a"
    type: "Convolution"
    convolution_param {
    num_output: 128
    kernel_size: 1
    pad: 0
    stride: 2
    bias_term: false
    }
    }

    layer {
    bottom: "res3a_branch2a"
    top: "res3a_branch2a"
    name: "bn3a_branch2a"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res3a_branch2a"
    top: "res3a_branch2a"
    name: "scale3a_branch2a"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res3a_branch2a"
    top: "res3a_branch2a"
    name: "res3a_branch2a_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res3a_branch2a"
    top: "res3a_branch2b"
    name: "res3a_branch2b"
    type: "Convolution"
    convolution_param {
    num_output: 128
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res3a_branch2b"
    top: "res3a_branch2b"
    name: "bn3a_branch2b"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res3a_branch2b"
    top: "res3a_branch2b"
    name: "scale3a_branch2b"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res3a_branch2b"
    top: "res3a_branch2b"
    name: "res3a_branch2b_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res3a_branch2b"
    top: "res3a_branch2c"
    name: "res3a_branch2c"
    type: "Convolution"
    convolution_param {
    num_output: 512
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res3a_branch2c"
    top: "res3a_branch2c"
    name: "bn3a_branch2c"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res3a_branch2c"
    top: "res3a_branch2c"
    name: "scale3a_branch2c"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res3a_branch1"
    bottom: "res3a_branch2c"
    top: "res3a"
    name: "res3a"
    type: "Eltwise"
    }

    layer {
    bottom: "res3a"
    top: "res3a"
    name: "res3a_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res3a"
    top: "res3b_branch2a"
    name: "res3b_branch2a"
    type: "Convolution"
    convolution_param {
    num_output: 128
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res3b_branch2a"
    top: "res3b_branch2a"
    name: "bn3b_branch2a"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res3b_branch2a"
    top: "res3b_branch2a"
    name: "scale3b_branch2a"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res3b_branch2a"
    top: "res3b_branch2a"
    name: "res3b_branch2a_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res3b_branch2a"
    top: "res3b_branch2b"
    name: "res3b_branch2b"
    type: "Convolution"
    convolution_param {
    num_output: 128
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res3b_branch2b"
    top: "res3b_branch2b"
    name: "bn3b_branch2b"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res3b_branch2b"
    top: "res3b_branch2b"
    name: "scale3b_branch2b"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res3b_branch2b"
    top: "res3b_branch2b"
    name: "res3b_branch2b_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res3b_branch2b"
    top: "res3b_branch2c"
    name: "res3b_branch2c"
    type: "Convolution"
    convolution_param {
    num_output: 512
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res3b_branch2c"
    top: "res3b_branch2c"
    name: "bn3b_branch2c"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res3b_branch2c"
    top: "res3b_branch2c"
    name: "scale3b_branch2c"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res3a"
    bottom: "res3b_branch2c"
    top: "res3b"
    name: "res3b"
    type: "Eltwise"
    }

    layer {
    bottom: "res3b"
    top: "res3b"
    name: "res3b_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res3b"
    top: "res3c_branch2a"
    name: "res3c_branch2a"
    type: "Convolution"
    convolution_param {
    num_output: 128
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res3c_branch2a"
    top: "res3c_branch2a"
    name: "bn3c_branch2a"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res3c_branch2a"
    top: "res3c_branch2a"
    name: "scale3c_branch2a"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res3c_branch2a"
    top: "res3c_branch2a"
    name: "res3c_branch2a_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res3c_branch2a"
    top: "res3c_branch2b"
    name: "res3c_branch2b"
    type: "Convolution"
    convolution_param {
    num_output: 128
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res3c_branch2b"
    top: "res3c_branch2b"
    name: "bn3c_branch2b"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res3c_branch2b"
    top: "res3c_branch2b"
    name: "scale3c_branch2b"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res3c_branch2b"
    top: "res3c_branch2b"
    name: "res3c_branch2b_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res3c_branch2b"
    top: "res3c_branch2c"
    name: "res3c_branch2c"
    type: "Convolution"
    convolution_param {
    num_output: 512
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res3c_branch2c"
    top: "res3c_branch2c"
    name: "bn3c_branch2c"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res3c_branch2c"
    top: "res3c_branch2c"
    name: "scale3c_branch2c"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res3b"
    bottom: "res3c_branch2c"
    top: "res3c"
    name: "res3c"
    type: "Eltwise"
    }

    layer {
    bottom: "res3c"
    top: "res3c"
    name: "res3c_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res3c"
    top: "res3d_branch2a"
    name: "res3d_branch2a"
    type: "Convolution"
    convolution_param {
    num_output: 128
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res3d_branch2a"
    top: "res3d_branch2a"
    name: "bn3d_branch2a"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res3d_branch2a"
    top: "res3d_branch2a"
    name: "scale3d_branch2a"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res3d_branch2a"
    top: "res3d_branch2a"
    name: "res3d_branch2a_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res3d_branch2a"
    top: "res3d_branch2b"
    name: "res3d_branch2b"
    type: "Convolution"
    convolution_param {
    num_output: 128
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res3d_branch2b"
    top: "res3d_branch2b"
    name: "bn3d_branch2b"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res3d_branch2b"
    top: "res3d_branch2b"
    name: "scale3d_branch2b"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res3d_branch2b"
    top: "res3d_branch2b"
    name: "res3d_branch2b_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res3d_branch2b"
    top: "res3d_branch2c"
    name: "res3d_branch2c"
    type: "Convolution"
    convolution_param {
    num_output: 512
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res3d_branch2c"
    top: "res3d_branch2c"
    name: "bn3d_branch2c"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res3d_branch2c"
    top: "res3d_branch2c"
    name: "scale3d_branch2c"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res3c"
    bottom: "res3d_branch2c"
    top: "res3d"
    name: "res3d"
    type: "Eltwise"
    }

    layer {
    bottom: "res3d"
    top: "res3d"
    name: "res3d_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res3d"
    top: "res4a_branch1"
    name: "res4a_branch1"
    type: "Convolution"
    convolution_param {
    num_output: 1024
    kernel_size: 1
    pad: 0
    stride: 2
    bias_term: false
    }
    }

    layer {
    bottom: "res4a_branch1"
    top: "res4a_branch1"
    name: "bn4a_branch1"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res4a_branch1"
    top: "res4a_branch1"
    name: "scale4a_branch1"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res3d"
    top: "res4a_branch2a"
    name: "res4a_branch2a"
    type: "Convolution"
    convolution_param {
    num_output: 256
    kernel_size: 1
    pad: 0
    stride: 2
    bias_term: false
    }
    }

    layer {
    bottom: "res4a_branch2a"
    top: "res4a_branch2a"
    name: "bn4a_branch2a"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res4a_branch2a"
    top: "res4a_branch2a"
    name: "scale4a_branch2a"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res4a_branch2a"
    top: "res4a_branch2a"
    name: "res4a_branch2a_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res4a_branch2a"
    top: "res4a_branch2b"
    name: "res4a_branch2b"
    type: "Convolution"
    convolution_param {
    num_output: 256
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res4a_branch2b"
    top: "res4a_branch2b"
    name: "bn4a_branch2b"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res4a_branch2b"
    top: "res4a_branch2b"
    name: "scale4a_branch2b"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res4a_branch2b"
    top: "res4a_branch2b"
    name: "res4a_branch2b_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res4a_branch2b"
    top: "res4a_branch2c"
    name: "res4a_branch2c"
    type: "Convolution"
    convolution_param {
    num_output: 1024
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res4a_branch2c"
    top: "res4a_branch2c"
    name: "bn4a_branch2c"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res4a_branch2c"
    top: "res4a_branch2c"
    name: "scale4a_branch2c"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res4a_branch1"
    bottom: "res4a_branch2c"
    top: "res4a"
    name: "res4a"
    type: "Eltwise"
    }

    layer {
    bottom: "res4a"
    top: "res4a"
    name: "res4a_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res4a"
    top: "res4b_branch2a"
    name: "res4b_branch2a"
    type: "Convolution"
    convolution_param {
    num_output: 256
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res4b_branch2a"
    top: "res4b_branch2a"
    name: "bn4b_branch2a"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res4b_branch2a"
    top: "res4b_branch2a"
    name: "scale4b_branch2a"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res4b_branch2a"
    top: "res4b_branch2a"
    name: "res4b_branch2a_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res4b_branch2a"
    top: "res4b_branch2b"
    name: "res4b_branch2b"
    type: "Convolution"
    convolution_param {
    num_output: 256
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res4b_branch2b"
    top: "res4b_branch2b"
    name: "bn4b_branch2b"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res4b_branch2b"
    top: "res4b_branch2b"
    name: "scale4b_branch2b"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res4b_branch2b"
    top: "res4b_branch2b"
    name: "res4b_branch2b_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res4b_branch2b"
    top: "res4b_branch2c"
    name: "res4b_branch2c"
    type: "Convolution"
    convolution_param {
    num_output: 1024
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res4b_branch2c"
    top: "res4b_branch2c"
    name: "bn4b_branch2c"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res4b_branch2c"
    top: "res4b_branch2c"
    name: "scale4b_branch2c"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res4a"
    bottom: "res4b_branch2c"
    top: "res4b"
    name: "res4b"
    type: "Eltwise"
    }

    layer {
    bottom: "res4b"
    top: "res4b"
    name: "res4b_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res4b"
    top: "res4c_branch2a"
    name: "res4c_branch2a"
    type: "Convolution"
    convolution_param {
    num_output: 256
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res4c_branch2a"
    top: "res4c_branch2a"
    name: "bn4c_branch2a"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res4c_branch2a"
    top: "res4c_branch2a"
    name: "scale4c_branch2a"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res4c_branch2a"
    top: "res4c_branch2a"
    name: "res4c_branch2a_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res4c_branch2a"
    top: "res4c_branch2b"
    name: "res4c_branch2b"
    type: "Convolution"
    convolution_param {
    num_output: 256
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res4c_branch2b"
    top: "res4c_branch2b"
    name: "bn4c_branch2b"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res4c_branch2b"
    top: "res4c_branch2b"
    name: "scale4c_branch2b"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res4c_branch2b"
    top: "res4c_branch2b"
    name: "res4c_branch2b_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res4c_branch2b"
    top: "res4c_branch2c"
    name: "res4c_branch2c"
    type: "Convolution"
    convolution_param {
    num_output: 1024
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res4c_branch2c"
    top: "res4c_branch2c"
    name: "bn4c_branch2c"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res4c_branch2c"
    top: "res4c_branch2c"
    name: "scale4c_branch2c"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res4b"
    bottom: "res4c_branch2c"
    top: "res4c"
    name: "res4c"
    type: "Eltwise"
    }

    layer {
    bottom: "res4c"
    top: "res4c"
    name: "res4c_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res4c"
    top: "res4d_branch2a"
    name: "res4d_branch2a"
    type: "Convolution"
    convolution_param {
    num_output: 256
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res4d_branch2a"
    top: "res4d_branch2a"
    name: "bn4d_branch2a"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res4d_branch2a"
    top: "res4d_branch2a"
    name: "scale4d_branch2a"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res4d_branch2a"
    top: "res4d_branch2a"
    name: "res4d_branch2a_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res4d_branch2a"
    top: "res4d_branch2b"
    name: "res4d_branch2b"
    type: "Convolution"
    convolution_param {
    num_output: 256
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res4d_branch2b"
    top: "res4d_branch2b"
    name: "bn4d_branch2b"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res4d_branch2b"
    top: "res4d_branch2b"
    name: "scale4d_branch2b"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res4d_branch2b"
    top: "res4d_branch2b"
    name: "res4d_branch2b_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res4d_branch2b"
    top: "res4d_branch2c"
    name: "res4d_branch2c"
    type: "Convolution"
    convolution_param {
    num_output: 1024
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res4d_branch2c"
    top: "res4d_branch2c"
    name: "bn4d_branch2c"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res4d_branch2c"
    top: "res4d_branch2c"
    name: "scale4d_branch2c"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res4c"
    bottom: "res4d_branch2c"
    top: "res4d"
    name: "res4d"
    type: "Eltwise"
    }

    layer {
    bottom: "res4d"
    top: "res4d"
    name: "res4d_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res4d"
    top: "res4e_branch2a"
    name: "res4e_branch2a"
    type: "Convolution"
    convolution_param {
    num_output: 256
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res4e_branch2a"
    top: "res4e_branch2a"
    name: "bn4e_branch2a"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res4e_branch2a"
    top: "res4e_branch2a"
    name: "scale4e_branch2a"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res4e_branch2a"
    top: "res4e_branch2a"
    name: "res4e_branch2a_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res4e_branch2a"
    top: "res4e_branch2b"
    name: "res4e_branch2b"
    type: "Convolution"
    convolution_param {
    num_output: 256
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res4e_branch2b"
    top: "res4e_branch2b"
    name: "bn4e_branch2b"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res4e_branch2b"
    top: "res4e_branch2b"
    name: "scale4e_branch2b"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res4e_branch2b"
    top: "res4e_branch2b"
    name: "res4e_branch2b_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res4e_branch2b"
    top: "res4e_branch2c"
    name: "res4e_branch2c"
    type: "Convolution"
    convolution_param {
    num_output: 1024
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res4e_branch2c"
    top: "res4e_branch2c"
    name: "bn4e_branch2c"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res4e_branch2c"
    top: "res4e_branch2c"
    name: "scale4e_branch2c"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res4d"
    bottom: "res4e_branch2c"
    top: "res4e"
    name: "res4e"
    type: "Eltwise"
    }

    layer {
    bottom: "res4e"
    top: "res4e"
    name: "res4e_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res4e"
    top: "res4f_branch2a"
    name: "res4f_branch2a"
    type: "Convolution"
    convolution_param {
    num_output: 256
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res4f_branch2a"
    top: "res4f_branch2a"
    name: "bn4f_branch2a"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res4f_branch2a"
    top: "res4f_branch2a"
    name: "scale4f_branch2a"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res4f_branch2a"
    top: "res4f_branch2a"
    name: "res4f_branch2a_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res4f_branch2a"
    top: "res4f_branch2b"
    name: "res4f_branch2b"
    type: "Convolution"
    convolution_param {
    num_output: 256
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res4f_branch2b"
    top: "res4f_branch2b"
    name: "bn4f_branch2b"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res4f_branch2b"
    top: "res4f_branch2b"
    name: "scale4f_branch2b"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res4f_branch2b"
    top: "res4f_branch2b"
    name: "res4f_branch2b_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res4f_branch2b"
    top: "res4f_branch2c"
    name: "res4f_branch2c"
    type: "Convolution"
    convolution_param {
    num_output: 1024
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res4f_branch2c"
    top: "res4f_branch2c"
    name: "bn4f_branch2c"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res4f_branch2c"
    top: "res4f_branch2c"
    name: "scale4f_branch2c"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res4e"
    bottom: "res4f_branch2c"
    top: "res4f"
    name: "res4f"
    type: "Eltwise"
    }

    layer {
    bottom: "res4f"
    top: "res4f"
    name: "res4f_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res4f"
    top: "res5a_branch1"
    name: "res5a_branch1"
    type: "Convolution"
    convolution_param {
    num_output: 2048
    kernel_size: 1
    pad: 0
    stride: 2
    bias_term: false
    }
    }

    layer {
    bottom: "res5a_branch1"
    top: "res5a_branch1"
    name: "bn5a_branch1"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res5a_branch1"
    top: "res5a_branch1"
    name: "scale5a_branch1"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res4f"
    top: "res5a_branch2a"
    name: "res5a_branch2a"
    type: "Convolution"
    convolution_param {
    num_output: 512
    kernel_size: 1
    pad: 0
    stride: 2
    bias_term: false
    }
    }

    layer {
    bottom: "res5a_branch2a"
    top: "res5a_branch2a"
    name: "bn5a_branch2a"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res5a_branch2a"
    top: "res5a_branch2a"
    name: "scale5a_branch2a"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res5a_branch2a"
    top: "res5a_branch2a"
    name: "res5a_branch2a_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res5a_branch2a"
    top: "res5a_branch2b"
    name: "res5a_branch2b"
    type: "Convolution"
    convolution_param {
    num_output: 512
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res5a_branch2b"
    top: "res5a_branch2b"
    name: "bn5a_branch2b"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res5a_branch2b"
    top: "res5a_branch2b"
    name: "scale5a_branch2b"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res5a_branch2b"
    top: "res5a_branch2b"
    name: "res5a_branch2b_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res5a_branch2b"
    top: "res5a_branch2c"
    name: "res5a_branch2c"
    type: "Convolution"
    convolution_param {
    num_output: 2048
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res5a_branch2c"
    top: "res5a_branch2c"
    name: "bn5a_branch2c"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res5a_branch2c"
    top: "res5a_branch2c"
    name: "scale5a_branch2c"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res5a_branch1"
    bottom: "res5a_branch2c"
    top: "res5a"
    name: "res5a"
    type: "Eltwise"
    }

    layer {
    bottom: "res5a"
    top: "res5a"
    name: "res5a_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res5a"
    top: "res5b_branch2a"
    name: "res5b_branch2a"
    type: "Convolution"
    convolution_param {
    num_output: 512
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res5b_branch2a"
    top: "res5b_branch2a"
    name: "bn5b_branch2a"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res5b_branch2a"
    top: "res5b_branch2a"
    name: "scale5b_branch2a"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res5b_branch2a"
    top: "res5b_branch2a"
    name: "res5b_branch2a_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res5b_branch2a"
    top: "res5b_branch2b"
    name: "res5b_branch2b"
    type: "Convolution"
    convolution_param {
    num_output: 512
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res5b_branch2b"
    top: "res5b_branch2b"
    name: "bn5b_branch2b"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res5b_branch2b"
    top: "res5b_branch2b"
    name: "scale5b_branch2b"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res5b_branch2b"
    top: "res5b_branch2b"
    name: "res5b_branch2b_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res5b_branch2b"
    top: "res5b_branch2c"
    name: "res5b_branch2c"
    type: "Convolution"
    convolution_param {
    num_output: 2048
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res5b_branch2c"
    top: "res5b_branch2c"
    name: "bn5b_branch2c"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res5b_branch2c"
    top: "res5b_branch2c"
    name: "scale5b_branch2c"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res5a"
    bottom: "res5b_branch2c"
    top: "res5b"
    name: "res5b"
    type: "Eltwise"
    }

    layer {
    bottom: "res5b"
    top: "res5b"
    name: "res5b_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res5b"
    top: "res5c_branch2a"
    name: "res5c_branch2a"
    type: "Convolution"
    convolution_param {
    num_output: 512
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res5c_branch2a"
    top: "res5c_branch2a"
    name: "bn5c_branch2a"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res5c_branch2a"
    top: "res5c_branch2a"
    name: "scale5c_branch2a"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res5c_branch2a"
    top: "res5c_branch2a"
    name: "res5c_branch2a_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res5c_branch2a"
    top: "res5c_branch2b"
    name: "res5c_branch2b"
    type: "Convolution"
    convolution_param {
    num_output: 512
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res5c_branch2b"
    top: "res5c_branch2b"
    name: "bn5c_branch2b"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res5c_branch2b"
    top: "res5c_branch2b"
    name: "scale5c_branch2b"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res5c_branch2b"
    top: "res5c_branch2b"
    name: "res5c_branch2b_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res5c_branch2b"
    top: "res5c_branch2c"
    name: "res5c_branch2c"
    type: "Convolution"
    convolution_param {
    num_output: 2048
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
    }
    }

    layer {
    bottom: "res5c_branch2c"
    top: "res5c_branch2c"
    name: "bn5c_branch2c"
    type: "BatchNorm"
    batch_norm_param {
    use_global_stats: true
    }
    }

    layer {
    bottom: "res5c_branch2c"
    top: "res5c_branch2c"
    name: "scale5c_branch2c"
    type: "Scale"
    scale_param {
    bias_term: true
    }
    }

    layer {
    bottom: "res5b"
    bottom: "res5c_branch2c"
    top: "res5c"
    name: "res5c"
    type: "Eltwise"
    }

    layer {
    bottom: "res5c"
    top: "res5c"
    name: "res5c_relu"
    type: "ReLU"
    }

    layer {
    bottom: "res5c"
    top: "pool5"
    name: "pool5"
    type: "Pooling"
    pooling_param {
    kernel_size: 7
    stride: 1
    pool: AVE
    }
    }
    layer {
    bottom: "pool5"
    top: "my-classifier"
    name: "my-classifier"
    type: "InnerProduct"
    inner_product_param {
    num_output: 3
    }
    }
    layer {
    bottom: "my-classifier"
    top: "prob"
    name: "prob"
    type: "Softmax"
    }