shufflenet-1x-p1-g3-d200_deploy.prototxt

name: "shufflenet"
input: "data"
input_dim: 1
input_dim: 3
input_dim: 224
input_dim: 224
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data"
  top: "conv1"
  convolution_param {
    num_output: 24
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv1_bn"
  type: "BatchNorm"
  bottom: "conv1"
  top: "conv1"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "conv1_scale"
  type: "Scale"
  bottom: "conv1"
  top: "conv1"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "conv1_relu"
  type: "ReLU"
  bottom: "conv1"
  top: "conv1"
}
layer {
  name: "pool1"
  type: "Pooling"
  bottom: "conv1"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "resx1_match_conv"
  type: "Pooling"
  bottom: "pool1"
  top: "resx1_match_conv"
  pooling_param {
    pool: AVE
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "resx1_conv1"
  type: "Convolution"
  bottom: "pool1"
  top: "resx1_conv1"
  convolution_param {
    num_output: 54
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx1_conv1_bn"
  type: "BatchNorm"
  bottom: "resx1_conv1"
  top: "resx1_conv1"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx1_conv1_scale"
  type: "Scale"
  bottom: "resx1_conv1"
  top: "resx1_conv1"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx1_conv1_relu"
  type: "ReLU"
  bottom: "resx1_conv1"
  top: "resx1_conv1"
}
layer {
  name: "resx1_conv2"
  type: "DepthwiseConvolution"
  bottom: "resx1_conv1"
  top: "resx1_conv2"
  convolution_param {
    num_output: 54
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 54
    stride: 2
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx1_conv2_bn"
  type: "BatchNorm"
  bottom: "resx1_conv2"
  top: "resx1_conv2"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx1_conv2_scale"
  type: "Scale"
  bottom: "resx1_conv2"
  top: "resx1_conv2"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx1_conv3"
  type: "Convolution"
  bottom: "resx1_conv2"
  top: "resx1_conv3"
  convolution_param {
    num_output: 216
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx1_conv3_bn"
  type: "BatchNorm"
  bottom: "resx1_conv3"
  top: "resx1_conv3"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx1_conv3_scale"
  type: "Scale"
  bottom: "resx1_conv3"
  top: "resx1_conv3"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx1_concat"
  type: "Concat"
  bottom: "resx1_match_conv"
  bottom: "resx1_conv3"
  top: "resx1_concat"
}
layer {
  name: "resx1_concat_relu"
  type: "ReLU"
  bottom: "resx1_concat"
  top: "resx1_concat"
}
layer {
  name: "resx2_conv1"
  type: "Convolution"
  bottom: "resx1_concat"
  top: "resx2_conv1"
  convolution_param {
    num_output: 60
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx2_conv1_bn"
  type: "BatchNorm"
  bottom: "resx2_conv1"
  top: "resx2_conv1"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx2_conv1_scale"
  type: "Scale"
  bottom: "resx2_conv1"
  top: "resx2_conv1"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx2_conv1_relu"
  type: "ReLU"
  bottom: "resx2_conv1"
  top: "resx2_conv1"
}
layer {
  name: "shuffle2"
  type: "ShuffleChannel"
  bottom: "resx2_conv1"
  top: "shuffle2"
  shuffle_channel_param {
    group: 3
  }
}
layer {
  name: "resx2_conv2"
  type: "DepthwiseConvolution"
  bottom: "shuffle2"
  top: "resx2_conv2"
  convolution_param {
    num_output: 60
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 60
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx2_conv2_bn"
  type: "BatchNorm"
  bottom: "resx2_conv2"
  top: "resx2_conv2"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx2_conv2_scale"
  type: "Scale"
  bottom: "resx2_conv2"
  top: "resx2_conv2"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx2_conv3"
  type: "Convolution"
  bottom: "resx2_conv2"
  top: "resx2_conv3"
  convolution_param {
    num_output: 240
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx2_conv3_bn"
  type: "BatchNorm"
  bottom: "resx2_conv3"
  top: "resx2_conv3"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx2_conv3_scale"
  type: "Scale"
  bottom: "resx2_conv3"
  top: "resx2_conv3"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx2_elewise"
  type: "Eltwise"
  bottom: "resx1_concat"
  bottom: "resx2_conv3"
  top: "resx2_elewise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "resx2_elewise_relu"
  type: "ReLU"
  bottom: "resx2_elewise"
  top: "resx2_elewise"
}
layer {
  name: "resx3_conv1"
  type: "Convolution"
  bottom: "resx2_elewise"
  top: "resx3_conv1"
  convolution_param {
    num_output: 60
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx3_conv1_bn"
  type: "BatchNorm"
  bottom: "resx3_conv1"
  top: "resx3_conv1"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx3_conv1_scale"
  type: "Scale"
  bottom: "resx3_conv1"
  top: "resx3_conv1"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx3_conv1_relu"
  type: "ReLU"
  bottom: "resx3_conv1"
  top: "resx3_conv1"
}
layer {
  name: "shuffle3"
  type: "ShuffleChannel"
  bottom: "resx3_conv1"
  top: "shuffle3"
  shuffle_channel_param {
    group: 3
  }
}
layer {
  name: "resx3_conv2"
  type: "DepthwiseConvolution"
  bottom: "shuffle3"
  top: "resx3_conv2"
  convolution_param {
    num_output: 60
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 60
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx3_conv2_bn"
  type: "BatchNorm"
  bottom: "resx3_conv2"
  top: "resx3_conv2"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx3_conv2_scale"
  type: "Scale"
  bottom: "resx3_conv2"
  top: "resx3_conv2"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx3_conv3"
  type: "Convolution"
  bottom: "resx3_conv2"
  top: "resx3_conv3"
  convolution_param {
    num_output: 240
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx3_conv3_bn"
  type: "BatchNorm"
  bottom: "resx3_conv3"
  top: "resx3_conv3"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx3_conv3_scale"
  type: "Scale"
  bottom: "resx3_conv3"
  top: "resx3_conv3"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx3_elewise"
  type: "Eltwise"
  bottom: "resx2_elewise"
  bottom: "resx3_conv3"
  top: "resx3_elewise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "resx3_elewise_relu"
  type: "ReLU"
  bottom: "resx3_elewise"
  top: "resx3_elewise"
}
layer {
  name: "resx4_conv1"
  type: "Convolution"
  bottom: "resx3_elewise"
  top: "resx4_conv1"
  convolution_param {
    num_output: 60
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx4_conv1_bn"
  type: "BatchNorm"
  bottom: "resx4_conv1"
  top: "resx4_conv1"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx4_conv1_scale"
  type: "Scale"
  bottom: "resx4_conv1"
  top: "resx4_conv1"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx4_conv1_relu"
  type: "ReLU"
  bottom: "resx4_conv1"
  top: "resx4_conv1"
}
layer {
  name: "shuffle4"
  type: "ShuffleChannel"
  bottom: "resx4_conv1"
  top: "shuffle4"
  shuffle_channel_param {
    group: 3
  }
}
layer {
  name: "resx4_conv2"
  type: "DepthwiseConvolution"
  bottom: "shuffle4"
  top: "resx4_conv2"
  convolution_param {
    num_output: 60
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 60
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx4_conv2_bn"
  type: "BatchNorm"
  bottom: "resx4_conv2"
  top: "resx4_conv2"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx4_conv2_scale"
  type: "Scale"
  bottom: "resx4_conv2"
  top: "resx4_conv2"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx4_conv3"
  type: "Convolution"
  bottom: "resx4_conv2"
  top: "resx4_conv3"
  convolution_param {
    num_output: 240
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx4_conv3_bn"
  type: "BatchNorm"
  bottom: "resx4_conv3"
  top: "resx4_conv3"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx4_conv3_scale"
  type: "Scale"
  bottom: "resx4_conv3"
  top: "resx4_conv3"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx4_elewise"
  type: "Eltwise"
  bottom: "resx3_elewise"
  bottom: "resx4_conv3"
  top: "resx4_elewise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "resx4_elewise_relu"
  type: "ReLU"
  bottom: "resx4_elewise"
  top: "resx4_elewise"
}
layer {
  name: "resx5_match_conv"
  type: "Pooling"
  bottom: "resx4_elewise"
  top: "resx5_match_conv"
  pooling_param {
    pool: AVE
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "resx5_conv1"
  type: "Convolution"
  bottom: "resx4_elewise"
  top: "resx5_conv1"
  convolution_param {
    num_output: 60
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx5_conv1_bn"
  type: "BatchNorm"
  bottom: "resx5_conv1"
  top: "resx5_conv1"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx5_conv1_scale"
  type: "Scale"
  bottom: "resx5_conv1"
  top: "resx5_conv1"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx5_conv1_relu"
  type: "ReLU"
  bottom: "resx5_conv1"
  top: "resx5_conv1"
}
layer {
  name: "shuffle5"
  type: "ShuffleChannel"
  bottom: "resx5_conv1"
  top: "shuffle5"
  shuffle_channel_param {
    group: 3
  }
}
layer {
  name: "resx5_conv2"
  type: "DepthwiseConvolution"
  bottom: "shuffle5"
  top: "resx5_conv2"
  convolution_param {
    num_output: 60
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 60
    stride: 2
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx5_conv2_bn"
  type: "BatchNorm"
  bottom: "resx5_conv2"
  top: "resx5_conv2"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx5_conv2_scale"
  type: "Scale"
  bottom: "resx5_conv2"
  top: "resx5_conv2"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx5_conv3"
  type: "Convolution"
  bottom: "resx5_conv2"
  top: "resx5_conv3"
  convolution_param {
    num_output: 240
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx5_conv3_bn"
  type: "BatchNorm"
  bottom: "resx5_conv3"
  top: "resx5_conv3"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx5_conv3_scale"
  type: "Scale"
  bottom: "resx5_conv3"
  top: "resx5_conv3"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx5_concat"
  type: "Concat"
  bottom: "resx5_match_conv"
  bottom: "resx5_conv3"
  top: "resx5_concat"
}
layer {
  name: "resx5_concat_relu"
  type: "ReLU"
  bottom: "resx5_concat"
  top: "resx5_concat"
}
layer {
  name: "resx6_conv1"
  type: "Convolution"
  bottom: "resx5_concat"
  top: "resx6_conv1"
  convolution_param {
    num_output: 120
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx6_conv1_bn"
  type: "BatchNorm"
  bottom: "resx6_conv1"
  top: "resx6_conv1"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx6_conv1_scale"
  type: "Scale"
  bottom: "resx6_conv1"
  top: "resx6_conv1"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx6_conv1_relu"
  type: "ReLU"
  bottom: "resx6_conv1"
  top: "resx6_conv1"
}
layer {
  name: "shuffle6"
  type: "ShuffleChannel"
  bottom: "resx6_conv1"
  top: "shuffle6"
  shuffle_channel_param {
    group: 3
  }
}
layer {
  name: "resx6_conv2"
  type: "DepthwiseConvolution"
  bottom: "shuffle6"
  top: "resx6_conv2"
  convolution_param {
    num_output: 120
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 120
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx6_conv2_bn"
  type: "BatchNorm"
  bottom: "resx6_conv2"
  top: "resx6_conv2"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx6_conv2_scale"
  type: "Scale"
  bottom: "resx6_conv2"
  top: "resx6_conv2"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx6_conv3"
  type: "Convolution"
  bottom: "resx6_conv2"
  top: "resx6_conv3"
  convolution_param {
    num_output: 480
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx6_conv3_bn"
  type: "BatchNorm"
  bottom: "resx6_conv3"
  top: "resx6_conv3"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx6_conv3_scale"
  type: "Scale"
  bottom: "resx6_conv3"
  top: "resx6_conv3"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx6_elewise"
  type: "Eltwise"
  bottom: "resx5_concat"
  bottom: "resx6_conv3"
  top: "resx6_elewise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "resx6_elewise_relu"
  type: "ReLU"
  bottom: "resx6_elewise"
  top: "resx6_elewise"
}
layer {
  name: "resx7_conv1"
  type: "Convolution"
  bottom: "resx6_elewise"
  top: "resx7_conv1"
  convolution_param {
    num_output: 120
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx7_conv1_bn"
  type: "BatchNorm"
  bottom: "resx7_conv1"
  top: "resx7_conv1"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx7_conv1_scale"
  type: "Scale"
  bottom: "resx7_conv1"
  top: "resx7_conv1"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx7_conv1_relu"
  type: "ReLU"
  bottom: "resx7_conv1"
  top: "resx7_conv1"
}
layer {
  name: "shuffle7"
  type: "ShuffleChannel"
  bottom: "resx7_conv1"
  top: "shuffle7"
  shuffle_channel_param {
    group: 3
  }
}
layer {
  name: "resx7_conv2"
  type: "DepthwiseConvolution"
  bottom: "shuffle7"
  top: "resx7_conv2"
  convolution_param {
    num_output: 120
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 120
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx7_conv2_bn"
  type: "BatchNorm"
  bottom: "resx7_conv2"
  top: "resx7_conv2"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx7_conv2_scale"
  type: "Scale"
  bottom: "resx7_conv2"
  top: "resx7_conv2"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx7_conv3"
  type: "Convolution"
  bottom: "resx7_conv2"
  top: "resx7_conv3"
  convolution_param {
    num_output: 480
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx7_conv3_bn"
  type: "BatchNorm"
  bottom: "resx7_conv3"
  top: "resx7_conv3"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx7_conv3_scale"
  type: "Scale"
  bottom: "resx7_conv3"
  top: "resx7_conv3"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx7_elewise"
  type: "Eltwise"
  bottom: "resx6_elewise"
  bottom: "resx7_conv3"
  top: "resx7_elewise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "resx7_elewise_relu"
  type: "ReLU"
  bottom: "resx7_elewise"
  top: "resx7_elewise"
}
layer {
  name: "resx8_conv1"
  type: "Convolution"
  bottom: "resx7_elewise"
  top: "resx8_conv1"
  convolution_param {
    num_output: 120
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx8_conv1_bn"
  type: "BatchNorm"
  bottom: "resx8_conv1"
  top: "resx8_conv1"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx8_conv1_scale"
  type: "Scale"
  bottom: "resx8_conv1"
  top: "resx8_conv1"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx8_conv1_relu"
  type: "ReLU"
  bottom: "resx8_conv1"
  top: "resx8_conv1"
}
layer {
  name: "shuffle8"
  type: "ShuffleChannel"
  bottom: "resx8_conv1"
  top: "shuffle8"
  shuffle_channel_param {
    group: 3
  }
}
layer {
  name: "resx8_conv2"
  type: "DepthwiseConvolution"
  bottom: "shuffle8"
  top: "resx8_conv2"
  convolution_param {
    num_output: 120
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 120
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx8_conv2_bn"
  type: "BatchNorm"
  bottom: "resx8_conv2"
  top: "resx8_conv2"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx8_conv2_scale"
  type: "Scale"
  bottom: "resx8_conv2"
  top: "resx8_conv2"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx8_conv3"
  type: "Convolution"
  bottom: "resx8_conv2"
  top: "resx8_conv3"
  convolution_param {
    num_output: 480
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx8_conv3_bn"
  type: "BatchNorm"
  bottom: "resx8_conv3"
  top: "resx8_conv3"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx8_conv3_scale"
  type: "Scale"
  bottom: "resx8_conv3"
  top: "resx8_conv3"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx8_elewise"
  type: "Eltwise"
  bottom: "resx7_elewise"
  bottom: "resx8_conv3"
  top: "resx8_elewise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "resx8_elewise_relu"
  type: "ReLU"
  bottom: "resx8_elewise"
  top: "resx8_elewise"
}
layer {
  name: "resx9_conv1"
  type: "Convolution"
  bottom: "resx8_elewise"
  top: "resx9_conv1"
  convolution_param {
    num_output: 120
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx9_conv1_bn"
  type: "BatchNorm"
  bottom: "resx9_conv1"
  top: "resx9_conv1"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx9_conv1_scale"
  type: "Scale"
  bottom: "resx9_conv1"
  top: "resx9_conv1"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx9_conv1_relu"
  type: "ReLU"
  bottom: "resx9_conv1"
  top: "resx9_conv1"
}
layer {
  name: "shuffle9"
  type: "ShuffleChannel"
  bottom: "resx9_conv1"
  top: "shuffle9"
  shuffle_channel_param {
    group: 3
  }
}
layer {
  name: "resx9_conv2"
  type: "DepthwiseConvolution"
  bottom: "shuffle9"
  top: "resx9_conv2"
  convolution_param {
    num_output: 120
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 120
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx9_conv2_bn"
  type: "BatchNorm"
  bottom: "resx9_conv2"
  top: "resx9_conv2"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx9_conv2_scale"
  type: "Scale"
  bottom: "resx9_conv2"
  top: "resx9_conv2"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx9_conv3"
  type: "Convolution"
  bottom: "resx9_conv2"
  top: "resx9_conv3"
  convolution_param {
    num_output: 480
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx9_conv3_bn"
  type: "BatchNorm"
  bottom: "resx9_conv3"
  top: "resx9_conv3"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx9_conv3_scale"
  type: "Scale"
  bottom: "resx9_conv3"
  top: "resx9_conv3"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx9_elewise"
  type: "Eltwise"
  bottom: "resx8_elewise"
  bottom: "resx9_conv3"
  top: "resx9_elewise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "resx9_elewise_relu"
  type: "ReLU"
  bottom: "resx9_elewise"
  top: "resx9_elewise"
}
layer {
  name: "resx10_conv1"
  type: "Convolution"
  bottom: "resx9_elewise"
  top: "resx10_conv1"
  convolution_param {
    num_output: 120
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx10_conv1_bn"
  type: "BatchNorm"
  bottom: "resx10_conv1"
  top: "resx10_conv1"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx10_conv1_scale"
  type: "Scale"
  bottom: "resx10_conv1"
  top: "resx10_conv1"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx10_conv1_relu"
  type: "ReLU"
  bottom: "resx10_conv1"
  top: "resx10_conv1"
}
layer {
  name: "shuffle10"
  type: "ShuffleChannel"
  bottom: "resx10_conv1"
  top: "shuffle10"
  shuffle_channel_param {
    group: 3
  }
}
layer {
  name: "resx10_conv2"
  type: "DepthwiseConvolution"
  bottom: "shuffle10"
  top: "resx10_conv2"
  convolution_param {
    num_output: 120
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 120
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx10_conv2_bn"
  type: "BatchNorm"
  bottom: "resx10_conv2"
  top: "resx10_conv2"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx10_conv2_scale"
  type: "Scale"
  bottom: "resx10_conv2"
  top: "resx10_conv2"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx10_conv3"
  type: "Convolution"
  bottom: "resx10_conv2"
  top: "resx10_conv3"
  convolution_param {
    num_output: 480
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx10_conv3_bn"
  type: "BatchNorm"
  bottom: "resx10_conv3"
  top: "resx10_conv3"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx10_conv3_scale"
  type: "Scale"
  bottom: "resx10_conv3"
  top: "resx10_conv3"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx10_elewise"
  type: "Eltwise"
  bottom: "resx9_elewise"
  bottom: "resx10_conv3"
  top: "resx10_elewise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "resx10_elewise_relu"
  type: "ReLU"
  bottom: "resx10_elewise"
  top: "resx10_elewise"
}
layer {
  name: "resx11_conv1"
  type: "Convolution"
  bottom: "resx10_elewise"
  top: "resx11_conv1"
  convolution_param {
    num_output: 120
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx11_conv1_bn"
  type: "BatchNorm"
  bottom: "resx11_conv1"
  top: "resx11_conv1"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx11_conv1_scale"
  type: "Scale"
  bottom: "resx11_conv1"
  top: "resx11_conv1"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx11_conv1_relu"
  type: "ReLU"
  bottom: "resx11_conv1"
  top: "resx11_conv1"
}
layer {
  name: "shuffle11"
  type: "ShuffleChannel"
  bottom: "resx11_conv1"
  top: "shuffle11"
  shuffle_channel_param {
    group: 3
  }
}
layer {
  name: "resx11_conv2"
  type: "DepthwiseConvolution"
  bottom: "shuffle11"
  top: "resx11_conv2"
  convolution_param {
    num_output: 120
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 120
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx11_conv2_bn"
  type: "BatchNorm"
  bottom: "resx11_conv2"
  top: "resx11_conv2"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx11_conv2_scale"
  type: "Scale"
  bottom: "resx11_conv2"
  top: "resx11_conv2"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx11_conv3"
  type: "Convolution"
  bottom: "resx11_conv2"
  top: "resx11_conv3"
  convolution_param {
    num_output: 480
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx11_conv3_bn"
  type: "BatchNorm"
  bottom: "resx11_conv3"
  top: "resx11_conv3"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx11_conv3_scale"
  type: "Scale"
  bottom: "resx11_conv3"
  top: "resx11_conv3"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx11_elewise"
  type: "Eltwise"
  bottom: "resx10_elewise"
  bottom: "resx11_conv3"
  top: "resx11_elewise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "resx11_elewise_relu"
  type: "ReLU"
  bottom: "resx11_elewise"
  top: "resx11_elewise"
}
layer {
  name: "resx12_conv1"
  type: "Convolution"
  bottom: "resx11_elewise"
  top: "resx12_conv1"
  convolution_param {
    num_output: 120
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx12_conv1_bn"
  type: "BatchNorm"
  bottom: "resx12_conv1"
  top: "resx12_conv1"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx12_conv1_scale"
  type: "Scale"
  bottom: "resx12_conv1"
  top: "resx12_conv1"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx12_conv1_relu"
  type: "ReLU"
  bottom: "resx12_conv1"
  top: "resx12_conv1"
}
layer {
  name: "shuffle12"
  type: "ShuffleChannel"
  bottom: "resx12_conv1"
  top: "shuffle12"
  shuffle_channel_param {
    group: 3
  }
}
layer {
  name: "resx12_conv2"
  type: "DepthwiseConvolution"
  bottom: "shuffle12"
  top: "resx12_conv2"
  convolution_param {
    num_output: 120
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 120
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx12_conv2_bn"
  type: "BatchNorm"
  bottom: "resx12_conv2"
  top: "resx12_conv2"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx12_conv2_scale"
  type: "Scale"
  bottom: "resx12_conv2"
  top: "resx12_conv2"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx12_conv3"
  type: "Convolution"
  bottom: "resx12_conv2"
  top: "resx12_conv3"
  convolution_param {
    num_output: 480
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx12_conv3_bn"
  type: "BatchNorm"
  bottom: "resx12_conv3"
  top: "resx12_conv3"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx12_conv3_scale"
  type: "Scale"
  bottom: "resx12_conv3"
  top: "resx12_conv3"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx12_elewise"
  type: "Eltwise"
  bottom: "resx11_elewise"
  bottom: "resx12_conv3"
  top: "resx12_elewise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "resx12_elewise_relu"
  type: "ReLU"
  bottom: "resx12_elewise"
  top: "resx12_elewise"
}
layer {
  name: "resx13_match_conv"
  type: "Pooling"
  bottom: "resx12_elewise"
  top: "resx13_match_conv"
  pooling_param {
    pool: AVE
    kernel_size: 3
    stride: 2
    pad_w:1
    pad_h:0
  }
}
layer {
  name: "resx13_conv1"
  type: "Convolution"
  bottom: "resx12_elewise"
  top: "resx13_conv1"
  convolution_param {
    num_output: 120
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx13_conv1_bn"
  type: "BatchNorm"
  bottom: "resx13_conv1"
  top: "resx13_conv1"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx13_conv1_scale"
  type: "Scale"
  bottom: "resx13_conv1"
  top: "resx13_conv1"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx13_conv1_relu"
  type: "ReLU"
  bottom: "resx13_conv1"
  top: "resx13_conv1"
}
layer {
  name: "shuffle13"
  type: "ShuffleChannel"
  bottom: "resx13_conv1"
  top: "shuffle13"
  shuffle_channel_param {
    group: 3
  }
}
layer {
  name: "resx13_conv2"
  type: "DepthwiseConvolution"
  bottom: "shuffle13"
  top: "resx13_conv2"
  convolution_param {
    num_output: 120
    bias_term: false
    #pad: 1
    pad_w:2
    pad_h:0
    kernel_size: 3
    group: 120
    stride: 2
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx13_conv2_bn"
  type: "BatchNorm"
  bottom: "resx13_conv2"
  top: "resx13_conv2"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx13_conv2_scale"
  type: "Scale"
  bottom: "resx13_conv2"
  top: "resx13_conv2"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx13_conv3"
  type: "Convolution"
  bottom: "resx13_conv2"
  top: "resx13_conv3"
  convolution_param {
    num_output: 480
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx13_conv3_bn"
  type: "BatchNorm"
  bottom: "resx13_conv3"
  top: "resx13_conv3"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx13_conv3_scale"
  type: "Scale"
  bottom: "resx13_conv3"
  top: "resx13_conv3"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx13_concat"
  type: "Concat"
  bottom: "resx13_match_conv"
  bottom: "resx13_conv3"
  top: "resx13_concat"
}
layer {
  name: "resx13_concat_relu"
  type: "ReLU"
  bottom: "resx13_concat"
  top: "resx13_concat"
}
layer {
  name: "resx14_conv1"
  type: "Convolution"
  bottom: "resx13_concat"
  top: "resx14_conv1"
  convolution_param {
    num_output: 240
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx14_conv1_bn"
  type: "BatchNorm"
  bottom: "resx14_conv1"
  top: "resx14_conv1"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx14_conv1_scale"
  type: "Scale"
  bottom: "resx14_conv1"
  top: "resx14_conv1"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx14_conv1_relu"
  type: "ReLU"
  bottom: "resx14_conv1"
  top: "resx14_conv1"
}
layer {
  name: "shuffle14"
  type: "ShuffleChannel"
  bottom: "resx14_conv1"
  top: "shuffle14"
  shuffle_channel_param {
    group: 3
  }
}
layer {
  name: "resx14_conv2"
  type: "DepthwiseConvolution"
  bottom: "shuffle14"
  top: "resx14_conv2"
  convolution_param {
    num_output: 240
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 240
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx14_conv2_bn"
  type: "BatchNorm"
  bottom: "resx14_conv2"
  top: "resx14_conv2"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx14_conv2_scale"
  type: "Scale"
  bottom: "resx14_conv2"
  top: "resx14_conv2"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx14_conv3"
  type: "Convolution"
  bottom: "resx14_conv2"
  top: "resx14_conv3"
  convolution_param {
    num_output: 960
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx14_conv3_bn"
  type: "BatchNorm"
  bottom: "resx14_conv3"
  top: "resx14_conv3"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx14_conv3_scale"
  type: "Scale"
  bottom: "resx14_conv3"
  top: "resx14_conv3"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx14_elewise"
  type: "Eltwise"
  bottom: "resx13_concat"
  bottom: "resx14_conv3"
  top: "resx14_elewise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "resx14_elewise_relu"
  type: "ReLU"
  bottom: "resx14_elewise"
  top: "resx14_elewise"
}
layer {
  name: "resx15_conv1"
  type: "Convolution"
  bottom: "resx14_elewise"
  top: "resx15_conv1"
  convolution_param {
    num_output: 240
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx15_conv1_bn"
  type: "BatchNorm"
  bottom: "resx15_conv1"
  top: "resx15_conv1"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx15_conv1_scale"
  type: "Scale"
  bottom: "resx15_conv1"
  top: "resx15_conv1"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx15_conv1_relu"
  type: "ReLU"
  bottom: "resx15_conv1"
  top: "resx15_conv1"
}
layer {
  name: "shuffle15"
  type: "ShuffleChannel"
  bottom: "resx15_conv1"
  top: "shuffle15"
  shuffle_channel_param {
    group: 3
  }
}
layer {
  name: "resx15_conv2"
  type: "DepthwiseConvolution"
  bottom: "shuffle15"
  top: "resx15_conv2"
  convolution_param {
    num_output: 240
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 240
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx15_conv2_bn"
  type: "BatchNorm"
  bottom: "resx15_conv2"
  top: "resx15_conv2"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx15_conv2_scale"
  type: "Scale"
  bottom: "resx15_conv2"
  top: "resx15_conv2"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx15_conv3"
  type: "Convolution"
  bottom: "resx15_conv2"
  top: "resx15_conv3"
  convolution_param {
    num_output: 960
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx15_conv3_bn"
  type: "BatchNorm"
  bottom: "resx15_conv3"
  top: "resx15_conv3"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx15_conv3_scale"
  type: "Scale"
  bottom: "resx15_conv3"
  top: "resx15_conv3"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx15_elewise"
  type: "Eltwise"
  bottom: "resx14_elewise"
  bottom: "resx15_conv3"
  top: "resx15_elewise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "resx15_elewise_relu"
  type: "ReLU"
  bottom: "resx15_elewise"
  top: "resx15_elewise"
}
layer {
  name: "resx16_conv1"
  type: "Convolution"
  bottom: "resx15_elewise"
  top: "resx16_conv1"
  convolution_param {
    num_output: 240
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx16_conv1_bn"
  type: "BatchNorm"
  bottom: "resx16_conv1"
  top: "resx16_conv1"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx16_conv1_scale"
  type: "Scale"
  bottom: "resx16_conv1"
  top: "resx16_conv1"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx16_conv1_relu"
  type: "ReLU"
  bottom: "resx16_conv1"
  top: "resx16_conv1"
}
layer {
  name: "shuffle16"
  type: "ShuffleChannel"
  bottom: "resx16_conv1"
  top: "shuffle16"
  shuffle_channel_param {
    group: 3
  }
}
layer {
  name: "resx16_conv2"
  type: "DepthwiseConvolution"
  bottom: "shuffle16"
  top: "resx16_conv2"
  convolution_param {
    num_output: 240
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 240
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx16_conv2_bn"
  type: "BatchNorm"
  bottom: "resx16_conv2"
  top: "resx16_conv2"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx16_conv2_scale"
  type: "Scale"
  bottom: "resx16_conv2"
  top: "resx16_conv2"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx16_conv3"
  type: "Convolution"
  bottom: "resx16_conv2"
  top: "resx16_conv3"
  convolution_param {
    num_output: 960
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "resx16_conv3_bn"
  type: "BatchNorm"
  bottom: "resx16_conv3"
  top: "resx16_conv3"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
}
layer {
  name: "resx16_conv3_scale"
  type: "Scale"
  bottom: "resx16_conv3"
  top: "resx16_conv3"
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "resx16_elewise"
  type: "Eltwise"
  bottom: "resx15_elewise"
  bottom: "resx16_conv3"
  top: "resx16_elewise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "resx16_elewise_relu"
  type: "ReLU"
  bottom: "resx16_elewise"
  top: "resx16_elewise"
}
layer {
  name: "pool_ave"
  type: "Pooling"
  bottom: "resx16_elewise"
  top: "pool_ave"
  pooling_param {
    pool: AVE
    global_pooling: true
  }
}
layer {
  name: "fc200"
  type: "Convolution"
  bottom: "pool_ave"
  top: "fc200"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 200
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "l2"
  type: "L2Norm"
  bottom: "fc200"
  top: "l2"
}
layer {
  name: "silence"
  type: "Silence"
  bottom: "l2"
}