MobileNet-v2-deploy.prototxt

name: "MobileNet-v2"
input: "data"
input_dim: 1
input_dim: 3
input_dim: 224
input_dim: 224
layer {
  name: "conv_1_1"
  type: "Convolution"
  bottom: "data"
  top: "conv_1_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_1_1"
  type: "BatchNorm"
  bottom: "conv_1_1"
  top: "conv_1_1"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_1_1"
  type: "Scale"
  bottom: "conv_1_1"
  top: "conv_1_1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_1_1"
  type: "ReLU"
  bottom: "conv_1_1"
  top: "conv_1_1"
}
layer {
  name: "conv_2_1_pw"
  type: "Convolution"
  bottom: "conv_1_1"
  top: "conv_2_1_pw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_2_1_pw"
  type: "BatchNorm"
  bottom: "conv_2_1_pw"
  top: "conv_2_1_pw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_2_1_pw"
  type: "Scale"
  bottom: "conv_2_1_pw"
  top: "conv_2_1_pw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_2_1_pw"
  type: "ReLU"
  bottom: "conv_2_1_pw"
  top: "conv_2_1_pw"
}
layer {
  name: "conv_2_1_dw"
  type: "Convolution"
  bottom: "conv_2_1_pw"
  top: "conv_2_1_dw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 32
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CAFFE
  }
}
layer {
  name: "bn_2_1_dw"
  type: "BatchNorm"
  bottom: "conv_2_1_dw"
  top: "conv_2_1_dw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_2_1_dw"
  type: "Scale"
  bottom: "conv_2_1_dw"
  top: "conv_2_1_dw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_2_1_dw"
  type: "ReLU"
  bottom: "conv_2_1_dw"
  top: "conv_2_1_dw"
}
layer {
  name: "conv_2_1_linear"
  type: "Convolution"
  bottom: "conv_2_1_dw"
  top: "conv_2_1_linear"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_2_1_linear"
  type: "BatchNorm"
  bottom: "conv_2_1_linear"
  top: "conv_2_1_linear"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_2_1_linear"
  type: "Scale"
  bottom: "conv_2_1_linear"
  top: "conv_2_1_linear"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv_3_1_pw"
  type: "Convolution"
  bottom: "conv_2_1_linear"
  top: "conv_3_1_pw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 96
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_3_1_pw"
  type: "BatchNorm"
  bottom: "conv_3_1_pw"
  top: "conv_3_1_pw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_3_1_pw"
  type: "Scale"
  bottom: "conv_3_1_pw"
  top: "conv_3_1_pw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_3_1_pw"
  type: "ReLU"
  bottom: "conv_3_1_pw"
  top: "conv_3_1_pw"
}
layer {
  name: "conv_3_1_dw"
  type: "Convolution"
  bottom: "conv_3_1_pw"
  top: "conv_3_1_dw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 96
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 96
    stride: 2
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CAFFE
  }
}
layer {
  name: "bn_3_1_dw"
  type: "BatchNorm"
  bottom: "conv_3_1_dw"
  top: "conv_3_1_dw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_3_1_dw"
  type: "Scale"
  bottom: "conv_3_1_dw"
  top: "conv_3_1_dw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_3_1_dw"
  type: "ReLU"
  bottom: "conv_3_1_dw"
  top: "conv_3_1_dw"
}
layer {
  name: "conv_3_1_linear"
  type: "Convolution"
  bottom: "conv_3_1_dw"
  top: "conv_3_1_linear"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 24
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_3_1_linear"
  type: "BatchNorm"
  bottom: "conv_3_1_linear"
  top: "conv_3_1_linear"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_3_1_linear"
  type: "Scale"
  bottom: "conv_3_1_linear"
  top: "conv_3_1_linear"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv_3_2_pw"
  type: "Convolution"
  bottom: "conv_3_1_linear"
  top: "conv_3_2_pw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 144
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_3_2_pw"
  type: "BatchNorm"
  bottom: "conv_3_2_pw"
  top: "conv_3_2_pw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_3_2_pw"
  type: "Scale"
  bottom: "conv_3_2_pw"
  top: "conv_3_2_pw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_3_2_pw"
  type: "ReLU"
  bottom: "conv_3_2_pw"
  top: "conv_3_2_pw"
}
layer {
  name: "conv_3_2_dw"
  type: "Convolution"
  bottom: "conv_3_2_pw"
  top: "conv_3_2_dw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 144
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 144
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CAFFE
  }
}
layer {
  name: "bn_3_2_dw"
  type: "BatchNorm"
  bottom: "conv_3_2_dw"
  top: "conv_3_2_dw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_3_2_dw"
  type: "Scale"
  bottom: "conv_3_2_dw"
  top: "conv_3_2_dw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_3_2_dw"
  type: "ReLU"
  bottom: "conv_3_2_dw"
  top: "conv_3_2_dw"
}
layer {
  name: "conv_3_2_linear"
  type: "Convolution"
  bottom: "conv_3_2_dw"
  top: "conv_3_2_linear"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 24
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_3_2_linear"
  type: "BatchNorm"
  bottom: "conv_3_2_linear"
  top: "conv_3_2_linear"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_3_2_linear"
  type: "Scale"
  bottom: "conv_3_2_linear"
  top: "conv_3_2_linear"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "add_3_2"
  type: "Eltwise"
  bottom: "conv_3_1_linear"
  bottom: "conv_3_2_linear"
  top: "add_3_2"
}
layer {
  name: "conv_4_1_pw"
  type: "Convolution"
  bottom: "add_3_2"
  top: "conv_4_1_pw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 144
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_4_1_pw"
  type: "BatchNorm"
  bottom: "conv_4_1_pw"
  top: "conv_4_1_pw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_4_1_pw"
  type: "Scale"
  bottom: "conv_4_1_pw"
  top: "conv_4_1_pw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_4_1_pw"
  type: "ReLU"
  bottom: "conv_4_1_pw"
  top: "conv_4_1_pw"
}
layer {
  name: "conv_4_1_dw"
  type: "Convolution"
  bottom: "conv_4_1_pw"
  top: "conv_4_1_dw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 144
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 144
    stride: 2
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CAFFE
  }
}
layer {
  name: "bn_4_1_dw"
  type: "BatchNorm"
  bottom: "conv_4_1_dw"
  top: "conv_4_1_dw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_4_1_dw"
  type: "Scale"
  bottom: "conv_4_1_dw"
  top: "conv_4_1_dw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_4_1_dw"
  type: "ReLU"
  bottom: "conv_4_1_dw"
  top: "conv_4_1_dw"
}
layer {
  name: "conv_4_1_linear"
  type: "Convolution"
  bottom: "conv_4_1_dw"
  top: "conv_4_1_linear"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_4_1_linear"
  type: "BatchNorm"
  bottom: "conv_4_1_linear"
  top: "conv_4_1_linear"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_4_1_linear"
  type: "Scale"
  bottom: "conv_4_1_linear"
  top: "conv_4_1_linear"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv_4_2_pw"
  type: "Convolution"
  bottom: "conv_4_1_linear"
  top: "conv_4_2_pw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_4_2_pw"
  type: "BatchNorm"
  bottom: "conv_4_2_pw"
  top: "conv_4_2_pw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_4_2_pw"
  type: "Scale"
  bottom: "conv_4_2_pw"
  top: "conv_4_2_pw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_4_2_pw"
  type: "ReLU"
  bottom: "conv_4_2_pw"
  top: "conv_4_2_pw"
}
layer {
  name: "conv_4_2_dw"
  type: "Convolution"
  bottom: "conv_4_2_pw"
  top: "conv_4_2_dw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 192
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CAFFE
  }
}
layer {
  name: "bn_4_2_dw"
  type: "BatchNorm"
  bottom: "conv_4_2_dw"
  top: "conv_4_2_dw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_4_2_dw"
  type: "Scale"
  bottom: "conv_4_2_dw"
  top: "conv_4_2_dw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_4_2_dw"
  type: "ReLU"
  bottom: "conv_4_2_dw"
  top: "conv_4_2_dw"
}
layer {
  name: "conv_4_2_linear"
  type: "Convolution"
  bottom: "conv_4_2_dw"
  top: "conv_4_2_linear"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_4_2_linear"
  type: "BatchNorm"
  bottom: "conv_4_2_linear"
  top: "conv_4_2_linear"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_4_2_linear"
  type: "Scale"
  bottom: "conv_4_2_linear"
  top: "conv_4_2_linear"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "add_4_2"
  type: "Eltwise"
  bottom: "conv_4_1_linear"
  bottom: "conv_4_2_linear"
  top: "add_4_2"
}
layer {
  name: "conv_4_3_pw"
  type: "Convolution"
  bottom: "add_4_2"
  top: "conv_4_3_pw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_4_3_pw"
  type: "BatchNorm"
  bottom: "conv_4_3_pw"
  top: "conv_4_3_pw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_4_3_pw"
  type: "Scale"
  bottom: "conv_4_3_pw"
  top: "conv_4_3_pw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_4_3_pw"
  type: "ReLU"
  bottom: "conv_4_3_pw"
  top: "conv_4_3_pw"
}
layer {
  name: "conv_4_3_dw"
  type: "Convolution"
  bottom: "conv_4_3_pw"
  top: "conv_4_3_dw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 192
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CAFFE
  }
}
layer {
  name: "bn_4_3_dw"
  type: "BatchNorm"
  bottom: "conv_4_3_dw"
  top: "conv_4_3_dw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_4_3_dw"
  type: "Scale"
  bottom: "conv_4_3_dw"
  top: "conv_4_3_dw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_4_3_dw"
  type: "ReLU"
  bottom: "conv_4_3_dw"
  top: "conv_4_3_dw"
}
layer {
  name: "conv_4_3_linear"
  type: "Convolution"
  bottom: "conv_4_3_dw"
  top: "conv_4_3_linear"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_4_3_linear"
  type: "BatchNorm"
  bottom: "conv_4_3_linear"
  top: "conv_4_3_linear"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_4_3_linear"
  type: "Scale"
  bottom: "conv_4_3_linear"
  top: "conv_4_3_linear"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "add_4_3"
  type: "Eltwise"
  bottom: "add_4_2"
  bottom: "conv_4_3_linear"
  top: "add_4_3"
}
layer {
  name: "conv_5_1_pw"
  type: "Convolution"
  bottom: "add_4_3"
  top: "conv_5_1_pw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_5_1_pw"
  type: "BatchNorm"
  bottom: "conv_5_1_pw"
  top: "conv_5_1_pw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_5_1_pw"
  type: "Scale"
  bottom: "conv_5_1_pw"
  top: "conv_5_1_pw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_5_1_pw"
  type: "ReLU"
  bottom: "conv_5_1_pw"
  top: "conv_5_1_pw"
}
layer {
  name: "conv_5_1_dw"
  type: "Convolution"
  bottom: "conv_5_1_pw"
  top: "conv_5_1_dw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 192
    stride: 2
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CAFFE
  }
}
layer {
  name: "bn_5_1_dw"
  type: "BatchNorm"
  bottom: "conv_5_1_dw"
  top: "conv_5_1_dw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_5_1_dw"
  type: "Scale"
  bottom: "conv_5_1_dw"
  top: "conv_5_1_dw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_5_1_dw"
  type: "ReLU"
  bottom: "conv_5_1_dw"
  top: "conv_5_1_dw"
}
layer {
  name: "conv_5_1_linear"
  type: "Convolution"
  bottom: "conv_5_1_dw"
  top: "conv_5_1_linear"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_5_1_linear"
  type: "BatchNorm"
  bottom: "conv_5_1_linear"
  top: "conv_5_1_linear"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_5_1_linear"
  type: "Scale"
  bottom: "conv_5_1_linear"
  top: "conv_5_1_linear"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv_5_2_pw"
  type: "Convolution"
  bottom: "conv_5_1_linear"
  top: "conv_5_2_pw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_5_2_pw"
  type: "BatchNorm"
  bottom: "conv_5_2_pw"
  top: "conv_5_2_pw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_5_2_pw"
  type: "Scale"
  bottom: "conv_5_2_pw"
  top: "conv_5_2_pw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_5_2_pw"
  type: "ReLU"
  bottom: "conv_5_2_pw"
  top: "conv_5_2_pw"
}
layer {
  name: "conv_5_2_dw"
  type: "Convolution"
  bottom: "conv_5_2_pw"
  top: "conv_5_2_dw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 384
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CAFFE
  }
}
layer {
  name: "bn_5_2_dw"
  type: "BatchNorm"
  bottom: "conv_5_2_dw"
  top: "conv_5_2_dw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_5_2_dw"
  type: "Scale"
  bottom: "conv_5_2_dw"
  top: "conv_5_2_dw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_5_2_dw"
  type: "ReLU"
  bottom: "conv_5_2_dw"
  top: "conv_5_2_dw"
}
layer {
  name: "conv_5_2_linear"
  type: "Convolution"
  bottom: "conv_5_2_dw"
  top: "conv_5_2_linear"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_5_2_linear"
  type: "BatchNorm"
  bottom: "conv_5_2_linear"
  top: "conv_5_2_linear"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_5_2_linear"
  type: "Scale"
  bottom: "conv_5_2_linear"
  top: "conv_5_2_linear"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "add_5_2"
  type: "Eltwise"
  bottom: "conv_5_1_linear"
  bottom: "conv_5_2_linear"
  top: "add_5_2"
}
layer {
  name: "conv_5_3_pw"
  type: "Convolution"
  bottom: "add_5_2"
  top: "conv_5_3_pw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_5_3_pw"
  type: "BatchNorm"
  bottom: "conv_5_3_pw"
  top: "conv_5_3_pw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_5_3_pw"
  type: "Scale"
  bottom: "conv_5_3_pw"
  top: "conv_5_3_pw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_5_3_pw"
  type: "ReLU"
  bottom: "conv_5_3_pw"
  top: "conv_5_3_pw"
}
layer {
  name: "conv_5_3_dw"
  type: "Convolution"
  bottom: "conv_5_3_pw"
  top: "conv_5_3_dw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 384
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CAFFE
  }
}
layer {
  name: "bn_5_3_dw"
  type: "BatchNorm"
  bottom: "conv_5_3_dw"
  top: "conv_5_3_dw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_5_3_dw"
  type: "Scale"
  bottom: "conv_5_3_dw"
  top: "conv_5_3_dw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_5_3_dw"
  type: "ReLU"
  bottom: "conv_5_3_dw"
  top: "conv_5_3_dw"
}
layer {
  name: "conv_5_3_linear"
  type: "Convolution"
  bottom: "conv_5_3_dw"
  top: "conv_5_3_linear"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_5_3_linear"
  type: "BatchNorm"
  bottom: "conv_5_3_linear"
  top: "conv_5_3_linear"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_5_3_linear"
  type: "Scale"
  bottom: "conv_5_3_linear"
  top: "conv_5_3_linear"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "add_5_3"
  type: "Eltwise"
  bottom: "add_5_2"
  bottom: "conv_5_3_linear"
  top: "add_5_3"
}
layer {
  name: "conv_5_4_pw"
  type: "Convolution"
  bottom: "add_5_3"
  top: "conv_5_4_pw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_5_4_pw"
  type: "BatchNorm"
  bottom: "conv_5_4_pw"
  top: "conv_5_4_pw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_5_4_pw"
  type: "Scale"
  bottom: "conv_5_4_pw"
  top: "conv_5_4_pw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_5_4_pw"
  type: "ReLU"
  bottom: "conv_5_4_pw"
  top: "conv_5_4_pw"
}
layer {
  name: "conv_5_4_dw"
  type: "Convolution"
  bottom: "conv_5_4_pw"
  top: "conv_5_4_dw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 384
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CAFFE
  }
}
layer {
  name: "bn_5_4_dw"
  type: "BatchNorm"
  bottom: "conv_5_4_dw"
  top: "conv_5_4_dw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_5_4_dw"
  type: "Scale"
  bottom: "conv_5_4_dw"
  top: "conv_5_4_dw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_5_4_dw"
  type: "ReLU"
  bottom: "conv_5_4_dw"
  top: "conv_5_4_dw"
}
layer {
  name: "conv_5_4_linear"
  type: "Convolution"
  bottom: "conv_5_4_dw"
  top: "conv_5_4_linear"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_5_4_linear"
  type: "BatchNorm"
  bottom: "conv_5_4_linear"
  top: "conv_5_4_linear"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_5_4_linear"
  type: "Scale"
  bottom: "conv_5_4_linear"
  top: "conv_5_4_linear"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "add_5_4"
  type: "Eltwise"
  bottom: "add_5_3"
  bottom: "conv_5_4_linear"
  top: "add_5_4"
}
layer {
  name: "conv_6_1_pw"
  type: "Convolution"
  bottom: "add_5_4"
  top: "conv_6_1_pw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_6_1_pw"
  type: "BatchNorm"
  bottom: "conv_6_1_pw"
  top: "conv_6_1_pw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_6_1_pw"
  type: "Scale"
  bottom: "conv_6_1_pw"
  top: "conv_6_1_pw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_6_1_pw"
  type: "ReLU"
  bottom: "conv_6_1_pw"
  top: "conv_6_1_pw"
}
layer {
  name: "conv_6_1_dw"
  type: "Convolution"
  bottom: "conv_6_1_pw"
  top: "conv_6_1_dw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 384
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CAFFE
  }
}
layer {
  name: "bn_6_1_dw"
  type: "BatchNorm"
  bottom: "conv_6_1_dw"
  top: "conv_6_1_dw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_6_1_dw"
  type: "Scale"
  bottom: "conv_6_1_dw"
  top: "conv_6_1_dw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_6_1_dw"
  type: "ReLU"
  bottom: "conv_6_1_dw"
  top: "conv_6_1_dw"
}
layer {
  name: "conv_6_1_linear"
  type: "Convolution"
  bottom: "conv_6_1_dw"
  top: "conv_6_1_linear"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 96
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_6_1_linear"
  type: "BatchNorm"
  bottom: "conv_6_1_linear"
  top: "conv_6_1_linear"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_6_1_linear"
  type: "Scale"
  bottom: "conv_6_1_linear"
  top: "conv_6_1_linear"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv_6_2_pw"
  type: "Convolution"
  bottom: "conv_6_1_linear"
  top: "conv_6_2_pw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 576
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_6_2_pw"
  type: "BatchNorm"
  bottom: "conv_6_2_pw"
  top: "conv_6_2_pw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_6_2_pw"
  type: "Scale"
  bottom: "conv_6_2_pw"
  top: "conv_6_2_pw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_6_2_pw"
  type: "ReLU"
  bottom: "conv_6_2_pw"
  top: "conv_6_2_pw"
}
layer {
  name: "conv_6_2_dw"
  type: "Convolution"
  bottom: "conv_6_2_pw"
  top: "conv_6_2_dw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 576
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 576
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CAFFE
  }
}
layer {
  name: "bn_6_2_dw"
  type: "BatchNorm"
  bottom: "conv_6_2_dw"
  top: "conv_6_2_dw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_6_2_dw"
  type: "Scale"
  bottom: "conv_6_2_dw"
  top: "conv_6_2_dw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_6_2_dw"
  type: "ReLU"
  bottom: "conv_6_2_dw"
  top: "conv_6_2_dw"
}
layer {
  name: "conv_6_2_linear"
  type: "Convolution"
  bottom: "conv_6_2_dw"
  top: "conv_6_2_linear"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 96
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_6_2_linear"
  type: "BatchNorm"
  bottom: "conv_6_2_linear"
  top: "conv_6_2_linear"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_6_2_linear"
  type: "Scale"
  bottom: "conv_6_2_linear"
  top: "conv_6_2_linear"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "add_6_2"
  type: "Eltwise"
  bottom: "conv_6_1_linear"
  bottom: "conv_6_2_linear"
  top: "add_6_2"
}
layer {
  name: "conv_6_3_pw"
  type: "Convolution"
  bottom: "add_6_2"
  top: "conv_6_3_pw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 576
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_6_3_pw"
  type: "BatchNorm"
  bottom: "conv_6_3_pw"
  top: "conv_6_3_pw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_6_3_pw"
  type: "Scale"
  bottom: "conv_6_3_pw"
  top: "conv_6_3_pw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_6_3_pw"
  type: "ReLU"
  bottom: "conv_6_3_pw"
  top: "conv_6_3_pw"
}
layer {
  name: "conv_6_3_dw"
  type: "Convolution"
  bottom: "conv_6_3_pw"
  top: "conv_6_3_dw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 576
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 576
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CAFFE
  }
}
layer {
  name: "bn_6_3_dw"
  type: "BatchNorm"
  bottom: "conv_6_3_dw"
  top: "conv_6_3_dw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_6_3_dw"
  type: "Scale"
  bottom: "conv_6_3_dw"
  top: "conv_6_3_dw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_6_3_dw"
  type: "ReLU"
  bottom: "conv_6_3_dw"
  top: "conv_6_3_dw"
}
layer {
  name: "conv_6_3_linear"
  type: "Convolution"
  bottom: "conv_6_3_dw"
  top: "conv_6_3_linear"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 96
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_6_3_linear"
  type: "BatchNorm"
  bottom: "conv_6_3_linear"
  top: "conv_6_3_linear"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_6_3_linear"
  type: "Scale"
  bottom: "conv_6_3_linear"
  top: "conv_6_3_linear"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "add_6_3"
  type: "Eltwise"
  bottom: "add_6_2"
  bottom: "conv_6_3_linear"
  top: "add_6_3"
}
layer {
  name: "conv_7_1_pw"
  type: "Convolution"
  bottom: "add_6_3"
  top: "conv_7_1_pw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 576
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_7_1_pw"
  type: "BatchNorm"
  bottom: "conv_7_1_pw"
  top: "conv_7_1_pw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_7_1_pw"
  type: "Scale"
  bottom: "conv_7_1_pw"
  top: "conv_7_1_pw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_7_1_pw"
  type: "ReLU"
  bottom: "conv_7_1_pw"
  top: "conv_7_1_pw"
}
layer {
  name: "conv_7_1_dw"
  type: "Convolution"
  bottom: "conv_7_1_pw"
  top: "conv_7_1_dw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 576
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 576
    stride: 2
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CAFFE
  }
}
layer {
  name: "bn_7_1_dw"
  type: "BatchNorm"
  bottom: "conv_7_1_dw"
  top: "conv_7_1_dw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_7_1_dw"
  type: "Scale"
  bottom: "conv_7_1_dw"
  top: "conv_7_1_dw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_7_1_dw"
  type: "ReLU"
  bottom: "conv_7_1_dw"
  top: "conv_7_1_dw"
}
layer {
  name: "conv_7_1_linear"
  type: "Convolution"
  bottom: "conv_7_1_dw"
  top: "conv_7_1_linear"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 160
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_7_1_linear"
  type: "BatchNorm"
  bottom: "conv_7_1_linear"
  top: "conv_7_1_linear"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_7_1_linear"
  type: "Scale"
  bottom: "conv_7_1_linear"
  top: "conv_7_1_linear"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv_7_2_pw"
  type: "Convolution"
  bottom: "conv_7_1_linear"
  top: "conv_7_2_pw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 960
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_7_2_pw"
  type: "BatchNorm"
  bottom: "conv_7_2_pw"
  top: "conv_7_2_pw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_7_2_pw"
  type: "Scale"
  bottom: "conv_7_2_pw"
  top: "conv_7_2_pw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_7_2_pw"
  type: "ReLU"
  bottom: "conv_7_2_pw"
  top: "conv_7_2_pw"
}
layer {
  name: "conv_7_2_dw"
  type: "Convolution"
  bottom: "conv_7_2_pw"
  top: "conv_7_2_dw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 960
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 960
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CAFFE
  }
}
layer {
  name: "bn_7_2_dw"
  type: "BatchNorm"
  bottom: "conv_7_2_dw"
  top: "conv_7_2_dw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_7_2_dw"
  type: "Scale"
  bottom: "conv_7_2_dw"
  top: "conv_7_2_dw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_7_2_dw"
  type: "ReLU"
  bottom: "conv_7_2_dw"
  top: "conv_7_2_dw"
}
layer {
  name: "conv_7_2_linear"
  type: "Convolution"
  bottom: "conv_7_2_dw"
  top: "conv_7_2_linear"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 160
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_7_2_linear"
  type: "BatchNorm"
  bottom: "conv_7_2_linear"
  top: "conv_7_2_linear"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_7_2_linear"
  type: "Scale"
  bottom: "conv_7_2_linear"
  top: "conv_7_2_linear"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "add_7_2"
  type: "Eltwise"
  bottom: "conv_7_1_linear"
  bottom: "conv_7_2_linear"
  top: "add_7_2"
}
layer {
  name: "conv_7_3_pw"
  type: "Convolution"
  bottom: "add_7_2"
  top: "conv_7_3_pw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 960
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_7_3_pw"
  type: "BatchNorm"
  bottom: "conv_7_3_pw"
  top: "conv_7_3_pw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_7_3_pw"
  type: "Scale"
  bottom: "conv_7_3_pw"
  top: "conv_7_3_pw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_7_3_pw"
  type: "ReLU"
  bottom: "conv_7_3_pw"
  top: "conv_7_3_pw"
}
layer {
  name: "conv_7_3_dw"
  type: "Convolution"
  bottom: "conv_7_3_pw"
  top: "conv_7_3_dw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 960
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 960
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CAFFE
  }
}
layer {
  name: "bn_7_3_dw"
  type: "BatchNorm"
  bottom: "conv_7_3_dw"
  top: "conv_7_3_dw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_7_3_dw"
  type: "Scale"
  bottom: "conv_7_3_dw"
  top: "conv_7_3_dw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_7_3_dw"
  type: "ReLU"
  bottom: "conv_7_3_dw"
  top: "conv_7_3_dw"
}
layer {
  name: "conv_7_3_linear"
  type: "Convolution"
  bottom: "conv_7_3_dw"
  top: "conv_7_3_linear"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 160
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_7_3_linear"
  type: "BatchNorm"
  bottom: "conv_7_3_linear"
  top: "conv_7_3_linear"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_7_3_linear"
  type: "Scale"
  bottom: "conv_7_3_linear"
  top: "conv_7_3_linear"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "add_7_3"
  type: "Eltwise"
  bottom: "add_7_2"
  bottom: "conv_7_3_linear"
  top: "add_7_3"
}
layer {
  name: "conv_8_1_pw"
  type: "Convolution"
  bottom: "add_7_3"
  top: "conv_8_1_pw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 960
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_8_1_pw"
  type: "BatchNorm"
  bottom: "conv_8_1_pw"
  top: "conv_8_1_pw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_8_1_pw"
  type: "Scale"
  bottom: "conv_8_1_pw"
  top: "conv_8_1_pw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_8_1_pw"
  type: "ReLU"
  bottom: "conv_8_1_pw"
  top: "conv_8_1_pw"
}
layer {
  name: "conv_8_1_dw"
  type: "Convolution"
  bottom: "conv_8_1_pw"
  top: "conv_8_1_dw"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 960
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 960
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CAFFE
  }
}
layer {
  name: "bn_8_1_dw"
  type: "BatchNorm"
  bottom: "conv_8_1_dw"
  top: "conv_8_1_dw"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_8_1_dw"
  type: "Scale"
  bottom: "conv_8_1_dw"
  top: "conv_8_1_dw"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_8_1_dw"
  type: "ReLU"
  bottom: "conv_8_1_dw"
  top: "conv_8_1_dw"
}
layer {
  name: "conv_8_1_linear"
  type: "Convolution"
  bottom: "conv_8_1_dw"
  top: "conv_8_1_linear"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 320
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn_8_1_linear"
  type: "BatchNorm"
  bottom: "conv_8_1_linear"
  top: "conv_8_1_linear"
  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
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_8_1_linear"
  type: "Scale"
  bottom: "conv_8_1_linear"
  top: "conv_8_1_linear"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv9"
  type: "Convolution"
  bottom: "conv_8_1_linear"
  top: "conv9"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 1280
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "pool9"
  type: "Pooling"
  bottom: "conv9"
  top: "pool9"
  pooling_param {
    pool: AVE
    stride: 1
    global_pooling: true
  }
}
layer {
  name: "dropout"
  type: "Dropout"
  bottom: "pool9"
  top: "pool9"
  dropout_param {
    dropout_ratio : 0.2
  }
}
layer {
  name: "conv10"
  type: "Convolution"
  bottom: "pool9"
  top: "conv10"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 1000
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "loss"
  type: "Softmax"
  bottom: "conv10"
  top: "loss"
}