mobilenet-v2dpwise-bn_deploy.prototxt

name: "MOBILENET_V2"
#  transform_param {
#    scale: 0.017
#    mirror: false
#    crop_size: 224
#    mean_value: [103.94,116.78,123.68]
#  }
input: "data"
input_dim: 1
input_dim: 3
input_dim: 224
input_dim: 224
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data"
  top: "conv1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv1/bn"
  type: "BatchNorm"
  bottom: "conv1"
  top: "conv1/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv1/scale"
  type: "Scale"
  bottom: "conv1/bn"
  top: "conv1/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu1"
  type: "ReLU"
  bottom: "conv1/bn"
  top: "conv1/bn"
}
layer {
  name: "conv2_1/expand"
  type: "Convolution"
  bottom: "conv1/bn"
  top: "conv2_1/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 32
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv2_1/expand/bn"
  type: "BatchNorm"
  bottom: "conv2_1/expand"
  top: "conv2_1/expand/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv2_1/expand/scale"
  type: "Scale"
  bottom: "conv2_1/expand/bn"
  top: "conv2_1/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu2_1/expand"
  type: "ReLU"
  bottom: "conv2_1/expand/bn"
  top: "conv2_1/expand/bn"
}
layer {
  name: "conv2_1/dwise"
  type: "DepthwiseConvolution"
  bottom: "conv2_1/expand/bn"
  top: "conv2_1/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 32
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv2_1/dwise/bn"
  type: "BatchNorm"
  bottom: "conv2_1/dwise"
  top: "conv2_1/dwise/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv2_1/dwise/scale"
  type: "Scale"
  bottom: "conv2_1/dwise/bn"
  top: "conv2_1/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu2_1/dwise"
  type: "ReLU"
  bottom: "conv2_1/dwise/bn"
  top: "conv2_1/dwise/bn"
}
layer {
  name: "conv2_1/linear"
  type: "Convolution"
  bottom: "conv2_1/dwise/bn"
  top: "conv2_1/linear"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 16
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv2_1/linear/bn"
  type: "BatchNorm"
  bottom: "conv2_1/linear"
  top: "conv2_1/linear/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv2_1/linear/scale"
  type: "Scale"
  bottom: "conv2_1/linear/bn"
  top: "conv2_1/linear/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv2_2/expand"
  type: "Convolution"
  bottom: "conv2_1/linear/bn"
  top: "conv2_2/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 96
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv2_2/expand/bn"
  type: "BatchNorm"
  bottom: "conv2_2/expand"
  top: "conv2_2/expand/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv2_2/expand/scale"
  type: "Scale"
  bottom: "conv2_2/expand/bn"
  top: "conv2_2/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu2_2/expand"
  type: "ReLU"
  bottom: "conv2_2/expand/bn"
  top: "conv2_2/expand/bn"
}
layer {
  name: "conv2_2/dwise"
  type: "DepthwiseConvolution"
  bottom: "conv2_2/expand/bn"
  top: "conv2_2/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 96
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 96
    stride: 2
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv2_2/dwise/bn"
  type: "BatchNorm"
  bottom: "conv2_2/dwise"
  top: "conv2_2/dwise/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv2_2/dwise/scale"
  type: "Scale"
  bottom: "conv2_2/dwise/bn"
  top: "conv2_2/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu2_2/dwise"
  type: "ReLU"
  bottom: "conv2_2/dwise/bn"
  top: "conv2_2/dwise/bn"
}
layer {
  name: "conv2_2/linear"
  type: "Convolution"
  bottom: "conv2_2/dwise/bn"
  top: "conv2_2/linear"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 24
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv2_2/linear/bn"
  type: "BatchNorm"
  bottom: "conv2_2/linear"
  top: "conv2_2/linear/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv2_2/linear/scale"
  type: "Scale"
  bottom: "conv2_2/linear/bn"
  top: "conv2_2/linear/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv3_1/expand"
  type: "Convolution"
  bottom: "conv2_2/linear/bn"
  top: "conv3_1/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 144
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv3_1/expand/bn"
  type: "BatchNorm"
  bottom: "conv3_1/expand"
  top: "conv3_1/expand/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv3_1/expand/scale"
  type: "Scale"
  bottom: "conv3_1/expand/bn"
  top: "conv3_1/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu3_1/expand"
  type: "ReLU"
  bottom: "conv3_1/expand/bn"
  top: "conv3_1/expand/bn"
}
layer {
  name: "conv3_1/dwise"
  type: "DepthwiseConvolution"
  bottom: "conv3_1/expand/bn"
  top: "conv3_1/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 144
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 144
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv3_1/dwise/bn"
  type: "BatchNorm"
  bottom: "conv3_1/dwise"
  top: "conv3_1/dwise/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv3_1/dwise/scale"
  type: "Scale"
  bottom: "conv3_1/dwise/bn"
  top: "conv3_1/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu3_1/dwise"
  type: "ReLU"
  bottom: "conv3_1/dwise/bn"
  top: "conv3_1/dwise/bn"
}
layer {
  name: "conv3_1/linear"
  type: "Convolution"
  bottom: "conv3_1/dwise/bn"
  top: "conv3_1/linear"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 24
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv3_1/linear/bn"
  type: "BatchNorm"
  bottom: "conv3_1/linear"
  top: "conv3_1/linear/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv3_1/linear/scale"
  type: "Scale"
  bottom: "conv3_1/linear/bn"
  top: "conv3_1/linear/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "block_3_1"
  type: "Eltwise"
  bottom: "conv2_2/linear/bn"
  bottom: "conv3_1/linear/bn"
  top: "block_3_1"
}
layer {
  name: "conv3_2/expand"
  type: "Convolution"
  bottom: "block_3_1"
  top: "conv3_2/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 144
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv3_2/expand/bn"
  type: "BatchNorm"
  bottom: "conv3_2/expand"
  top: "conv3_2/expand/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv3_2/expand/scale"
  type: "Scale"
  bottom: "conv3_2/expand/bn"
  top: "conv3_2/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu3_2/expand"
  type: "ReLU"
  bottom: "conv3_2/expand/bn"
  top: "conv3_2/expand/bn"
}
layer {
  name: "conv3_2/dwise"
  type: "DepthwiseConvolution"
  bottom: "conv3_2/expand/bn"
  top: "conv3_2/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 144
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 144
    stride: 2
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv3_2/dwise/bn"
  type: "BatchNorm"
  bottom: "conv3_2/dwise"
  top: "conv3_2/dwise/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv3_2/dwise/scale"
  type: "Scale"
  bottom: "conv3_2/dwise/bn"
  top: "conv3_2/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu3_2/dwise"
  type: "ReLU"
  bottom: "conv3_2/dwise/bn"
  top: "conv3_2/dwise/bn"
}
layer {
  name: "conv3_2/linear"
  type: "Convolution"
  bottom: "conv3_2/dwise/bn"
  top: "conv3_2/linear"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 32
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv3_2/linear/bn"
  type: "BatchNorm"
  bottom: "conv3_2/linear"
  top: "conv3_2/linear/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv3_2/linear/scale"
  type: "Scale"
  bottom: "conv3_2/linear/bn"
  top: "conv3_2/linear/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv4_1/expand"
  type: "Convolution"
  bottom: "conv3_2/linear/bn"
  top: "conv4_1/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 192
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4_1/expand/bn"
  type: "BatchNorm"
  bottom: "conv4_1/expand"
  top: "conv4_1/expand/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv4_1/expand/scale"
  type: "Scale"
  bottom: "conv4_1/expand/bn"
  top: "conv4_1/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu4_1/expand"
  type: "ReLU"
  bottom: "conv4_1/expand/bn"
  top: "conv4_1/expand/bn"
}
layer {
  name: "conv4_1/dwise"
  type: "DepthwiseConvolution"
  bottom: "conv4_1/expand/bn"
  top: "conv4_1/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 192
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv4_1/dwise/bn"
  type: "BatchNorm"
  bottom: "conv4_1/dwise"
  top: "conv4_1/dwise/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv4_1/dwise/scale"
  type: "Scale"
  bottom: "conv4_1/dwise/bn"
  top: "conv4_1/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu4_1/dwise"
  type: "ReLU"
  bottom: "conv4_1/dwise/bn"
  top: "conv4_1/dwise/bn"
}
layer {
  name: "conv4_1/linear"
  type: "Convolution"
  bottom: "conv4_1/dwise/bn"
  top: "conv4_1/linear"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 32
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4_1/linear/bn"
  type: "BatchNorm"
  bottom: "conv4_1/linear"
  top: "conv4_1/linear/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv4_1/linear/scale"
  type: "Scale"
  bottom: "conv4_1/linear/bn"
  top: "conv4_1/linear/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "block_4_1"
  type: "Eltwise"
  bottom: "conv3_2/linear/bn"
  bottom: "conv4_1/linear/bn"
  top: "block_4_1"
}
layer {
  name: "conv4_2/expand"
  type: "Convolution"
  bottom: "block_4_1"
  top: "conv4_2/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 192
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4_2/expand/bn"
  type: "BatchNorm"
  bottom: "conv4_2/expand"
  top: "conv4_2/expand/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv4_2/expand/scale"
  type: "Scale"
  bottom: "conv4_2/expand/bn"
  top: "conv4_2/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu4_2/expand"
  type: "ReLU"
  bottom: "conv4_2/expand/bn"
  top: "conv4_2/expand/bn"
}
layer {
  name: "conv4_2/dwise"
  type: "DepthwiseConvolution"
  bottom: "conv4_2/expand/bn"
  top: "conv4_2/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 192
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv4_2/dwise/bn"
  type: "BatchNorm"
  bottom: "conv4_2/dwise"
  top: "conv4_2/dwise/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv4_2/dwise/scale"
  type: "Scale"
  bottom: "conv4_2/dwise/bn"
  top: "conv4_2/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu4_2/dwise"
  type: "ReLU"
  bottom: "conv4_2/dwise/bn"
  top: "conv4_2/dwise/bn"
}
layer {
  name: "conv4_2/linear"
  type: "Convolution"
  bottom: "conv4_2/dwise/bn"
  top: "conv4_2/linear"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 32
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4_2/linear/bn"
  type: "BatchNorm"
  bottom: "conv4_2/linear"
  top: "conv4_2/linear/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv4_2/linear/scale"
  type: "Scale"
  bottom: "conv4_2/linear/bn"
  top: "conv4_2/linear/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "block_4_2"
  type: "Eltwise"
  bottom: "block_4_1"
  bottom: "conv4_2/linear/bn"
  top: "block_4_2"
}
layer {
  name: "conv4_3/expand"
  type: "Convolution"
  bottom: "block_4_2"
  top: "conv4_3/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 192
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4_3/expand/bn"
  type: "BatchNorm"
  bottom: "conv4_3/expand"
  top: "conv4_3/expand/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv4_3/expand/scale"
  type: "Scale"
  bottom: "conv4_3/expand/bn"
  top: "conv4_3/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu4_3/expand"
  type: "ReLU"
  bottom: "conv4_3/expand/bn"
  top: "conv4_3/expand/bn"
}
layer {
  name: "conv4_3/dwise"
  type: "DepthwiseConvolution"
  bottom: "conv4_3/expand/bn"
  top: "conv4_3/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 192
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv4_3/dwise/bn"
  type: "BatchNorm"
  bottom: "conv4_3/dwise"
  top: "conv4_3/dwise/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv4_3/dwise/scale"
  type: "Scale"
  bottom: "conv4_3/dwise/bn"
  top: "conv4_3/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu4_3/dwise"
  type: "ReLU"
  bottom: "conv4_3/dwise/bn"
  top: "conv4_3/dwise/bn"
}
layer {
  name: "conv4_3/linear"
  type: "Convolution"
  bottom: "conv4_3/dwise/bn"
  top: "conv4_3/linear"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 64
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4_3/linear/bn"
  type: "BatchNorm"
  bottom: "conv4_3/linear"
  top: "conv4_3/linear/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv4_3/linear/scale"
  type: "Scale"
  bottom: "conv4_3/linear/bn"
  top: "conv4_3/linear/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv4_4/expand"
  type: "Convolution"
  bottom: "conv4_3/linear/bn"
  top: "conv4_4/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 384
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4_4/expand/bn"
  type: "BatchNorm"
  bottom: "conv4_4/expand"
  top: "conv4_4/expand/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv4_4/expand/scale"
  type: "Scale"
  bottom: "conv4_4/expand/bn"
  top: "conv4_4/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu4_4/expand"
  type: "ReLU"
  bottom: "conv4_4/expand/bn"
  top: "conv4_4/expand/bn"
}
layer {
  name: "conv4_4/dwise"
  type: "DepthwiseConvolution"
  bottom: "conv4_4/expand/bn"
  top: "conv4_4/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 384
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 384
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv4_4/dwise/bn"
  type: "BatchNorm"
  bottom: "conv4_4/dwise"
  top: "conv4_4/dwise/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv4_4/dwise/scale"
  type: "Scale"
  bottom: "conv4_4/dwise/bn"
  top: "conv4_4/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu4_4/dwise"
  type: "ReLU"
  bottom: "conv4_4/dwise/bn"
  top: "conv4_4/dwise/bn"
}
layer {
  name: "conv4_4/linear"
  type: "Convolution"
  bottom: "conv4_4/dwise/bn"
  top: "conv4_4/linear"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 64
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4_4/linear/bn"
  type: "BatchNorm"
  bottom: "conv4_4/linear"
  top: "conv4_4/linear/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv4_4/linear/scale"
  type: "Scale"
  bottom: "conv4_4/linear/bn"
  top: "conv4_4/linear/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "block_4_4"
  type: "Eltwise"
  bottom: "conv4_3/linear/bn"
  bottom: "conv4_4/linear/bn"
  top: "block_4_4"
}
layer {
  name: "conv4_5/expand"
  type: "Convolution"
  bottom: "block_4_4"
  top: "conv4_5/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 384
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4_5/expand/bn"
  type: "BatchNorm"
  bottom: "conv4_5/expand"
  top: "conv4_5/expand/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv4_5/expand/scale"
  type: "Scale"
  bottom: "conv4_5/expand/bn"
  top: "conv4_5/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu4_5/expand"
  type: "ReLU"
  bottom: "conv4_5/expand/bn"
  top: "conv4_5/expand/bn"
}
layer {
  name: "conv4_5/dwise"
  type: "DepthwiseConvolution"
  bottom: "conv4_5/expand/bn"
  top: "conv4_5/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 384
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 384
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv4_5/dwise/bn"
  type: "BatchNorm"
  bottom: "conv4_5/dwise"
  top: "conv4_5/dwise/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv4_5/dwise/scale"
  type: "Scale"
  bottom: "conv4_5/dwise/bn"
  top: "conv4_5/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu4_5/dwise"
  type: "ReLU"
  bottom: "conv4_5/dwise/bn"
  top: "conv4_5/dwise/bn"
}
layer {
  name: "conv4_5/linear"
  type: "Convolution"
  bottom: "conv4_5/dwise/bn"
  top: "conv4_5/linear"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 64
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4_5/linear/bn"
  type: "BatchNorm"
  bottom: "conv4_5/linear"
  top: "conv4_5/linear/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv4_5/linear/scale"
  type: "Scale"
  bottom: "conv4_5/linear/bn"
  top: "conv4_5/linear/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "block_4_5"
  type: "Eltwise"
  bottom: "block_4_4"
  bottom: "conv4_5/linear/bn"
  top: "block_4_5"
}
layer {
  name: "conv4_6/expand"
  type: "Convolution"
  bottom: "block_4_5"
  top: "conv4_6/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 384
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4_6/expand/bn"
  type: "BatchNorm"
  bottom: "conv4_6/expand"
  top: "conv4_6/expand/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv4_6/expand/scale"
  type: "Scale"
  bottom: "conv4_6/expand/bn"
  top: "conv4_6/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu4_6/expand"
  type: "ReLU"
  bottom: "conv4_6/expand/bn"
  top: "conv4_6/expand/bn"
}
layer {
  name: "conv4_6/dwise"
  type: "DepthwiseConvolution"
  bottom: "conv4_6/expand/bn"
  top: "conv4_6/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 384
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 384
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv4_6/dwise/bn"
  type: "BatchNorm"
  bottom: "conv4_6/dwise"
  top: "conv4_6/dwise/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv4_6/dwise/scale"
  type: "Scale"
  bottom: "conv4_6/dwise/bn"
  top: "conv4_6/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu4_6/dwise"
  type: "ReLU"
  bottom: "conv4_6/dwise/bn"
  top: "conv4_6/dwise/bn"
}
layer {
  name: "conv4_6/linear"
  type: "Convolution"
  bottom: "conv4_6/dwise/bn"
  top: "conv4_6/linear"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 64
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4_6/linear/bn"
  type: "BatchNorm"
  bottom: "conv4_6/linear"
  top: "conv4_6/linear/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv4_6/linear/scale"
  type: "Scale"
  bottom: "conv4_6/linear/bn"
  top: "conv4_6/linear/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "block_4_6"
  type: "Eltwise"
  bottom: "block_4_5"
  bottom: "conv4_6/linear/bn"
  top: "block_4_6"
}
layer {
  name: "conv4_7/expand"
  type: "Convolution"
  bottom: "block_4_6"
  top: "conv4_7/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 384
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4_7/expand/bn"
  type: "BatchNorm"
  bottom: "conv4_7/expand"
  top: "conv4_7/expand/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv4_7/expand/scale"
  type: "Scale"
  bottom: "conv4_7/expand/bn"
  top: "conv4_7/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu4_7/expand"
  type: "ReLU"
  bottom: "conv4_7/expand/bn"
  top: "conv4_7/expand/bn"
}
layer {
  name: "conv4_7/dwise"
  type: "DepthwiseConvolution"
  bottom: "conv4_7/expand/bn"
  top: "conv4_7/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 384
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 384
    stride: 2
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv4_7/dwise/bn"
  type: "BatchNorm"
  bottom: "conv4_7/dwise"
  top: "conv4_7/dwise/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv4_7/dwise/scale"
  type: "Scale"
  bottom: "conv4_7/dwise/bn"
  top: "conv4_7/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu4_7/dwise"
  type: "ReLU"
  bottom: "conv4_7/dwise/bn"
  top: "conv4_7/dwise/bn"
}
layer {
  name: "conv4_7/linear"
  type: "Convolution"
  bottom: "conv4_7/dwise/bn"
  top: "conv4_7/linear"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 96
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4_7/linear/bn"
  type: "BatchNorm"
  bottom: "conv4_7/linear"
  top: "conv4_7/linear/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv4_7/linear/scale"
  type: "Scale"
  bottom: "conv4_7/linear/bn"
  top: "conv4_7/linear/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv5_1/expand"
  type: "Convolution"
  bottom: "conv4_7/linear/bn"
  top: "conv5_1/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 576
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5_1/expand/bn"
  type: "BatchNorm"
  bottom: "conv5_1/expand"
  top: "conv5_1/expand/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv5_1/expand/scale"
  type: "Scale"
  bottom: "conv5_1/expand/bn"
  top: "conv5_1/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu5_1/expand"
  type: "ReLU"
  bottom: "conv5_1/expand/bn"
  top: "conv5_1/expand/bn"
}
layer {
  name: "conv5_1/dwise"
  type: "DepthwiseConvolution"
  bottom: "conv5_1/expand/bn"
  top: "conv5_1/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 576
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 576
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv5_1/dwise/bn"
  type: "BatchNorm"
  bottom: "conv5_1/dwise"
  top: "conv5_1/dwise/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv5_1/dwise/scale"
  type: "Scale"
  bottom: "conv5_1/dwise/bn"
  top: "conv5_1/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu5_1/dwise"
  type: "ReLU"
  bottom: "conv5_1/dwise/bn"
  top: "conv5_1/dwise/bn"
}
layer {
  name: "conv5_1/linear"
  type: "Convolution"
  bottom: "conv5_1/dwise/bn"
  top: "conv5_1/linear"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 96
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5_1/linear/bn"
  type: "BatchNorm"
  bottom: "conv5_1/linear"
  top: "conv5_1/linear/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv5_1/linear/scale"
  type: "Scale"
  bottom: "conv5_1/linear/bn"
  top: "conv5_1/linear/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "block_5_1"
  type: "Eltwise"
  bottom: "conv4_7/linear/bn"
  bottom: "conv5_1/linear/bn"
  top: "block_5_1"
}
layer {
  name: "conv5_2/expand"
  type: "Convolution"
  bottom: "block_5_1"
  top: "conv5_2/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 576
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5_2/expand/bn"
  type: "BatchNorm"
  bottom: "conv5_2/expand"
  top: "conv5_2/expand/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv5_2/expand/scale"
  type: "Scale"
  bottom: "conv5_2/expand/bn"
  top: "conv5_2/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu5_2/expand"
  type: "ReLU"
  bottom: "conv5_2/expand/bn"
  top: "conv5_2/expand/bn"
}
layer {
  name: "conv5_2/dwise"
  type: "DepthwiseConvolution"
  bottom: "conv5_2/expand/bn"
  top: "conv5_2/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 576
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 576
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv5_2/dwise/bn"
  type: "BatchNorm"
  bottom: "conv5_2/dwise"
  top: "conv5_2/dwise/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv5_2/dwise/scale"
  type: "Scale"
  bottom: "conv5_2/dwise/bn"
  top: "conv5_2/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu5_2/dwise"
  type: "ReLU"
  bottom: "conv5_2/dwise/bn"
  top: "conv5_2/dwise/bn"
}
layer {
  name: "conv5_2/linear"
  type: "Convolution"
  bottom: "conv5_2/dwise/bn"
  top: "conv5_2/linear"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 96
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5_2/linear/bn"
  type: "BatchNorm"
  bottom: "conv5_2/linear"
  top: "conv5_2/linear/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv5_2/linear/scale"
  type: "Scale"
  bottom: "conv5_2/linear/bn"
  top: "conv5_2/linear/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "block_5_2"
  type: "Eltwise"
  bottom: "block_5_1"
  bottom: "conv5_2/linear/bn"
  top: "block_5_2"
}
layer {
  name: "conv5_3/expand"
  type: "Convolution"
  bottom: "block_5_2"
  top: "conv5_3/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 576
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5_3/expand/bn"
  type: "BatchNorm"
  bottom: "conv5_3/expand"
  top: "conv5_3/expand/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv5_3/expand/scale"
  type: "Scale"
  bottom: "conv5_3/expand/bn"
  top: "conv5_3/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu5_3/expand"
  type: "ReLU"
  bottom: "conv5_3/expand/bn"
  top: "conv5_3/expand/bn"
}
layer {
  name: "conv5_3/dwise"
  type: "DepthwiseConvolution"
  bottom: "conv5_3/expand/bn"
  top: "conv5_3/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 576
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 576
    stride: 2
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv5_3/dwise/bn"
  type: "BatchNorm"
  bottom: "conv5_3/dwise"
  top: "conv5_3/dwise/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv5_3/dwise/scale"
  type: "Scale"
  bottom: "conv5_3/dwise/bn"
  top: "conv5_3/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu5_3/dwise"
  type: "ReLU"
  bottom: "conv5_3/dwise/bn"
  top: "conv5_3/dwise/bn"
}
layer {
  name: "conv5_3/linear"
  type: "Convolution"
  bottom: "conv5_3/dwise/bn"
  top: "conv5_3/linear"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 160
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5_3/linear/bn"
  type: "BatchNorm"
  bottom: "conv5_3/linear"
  top: "conv5_3/linear/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv5_3/linear/scale"
  type: "Scale"
  bottom: "conv5_3/linear/bn"
  top: "conv5_3/linear/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv6_1/expand"
  type: "Convolution"
  bottom: "conv5_3/linear/bn"
  top: "conv6_1/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 960
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv6_1/expand/bn"
  type: "BatchNorm"
  bottom: "conv6_1/expand"
  top: "conv6_1/expand/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv6_1/expand/scale"
  type: "Scale"
  bottom: "conv6_1/expand/bn"
  top: "conv6_1/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu6_1/expand"
  type: "ReLU"
  bottom: "conv6_1/expand/bn"
  top: "conv6_1/expand/bn"
}
layer {
  name: "conv6_1/dwise"
  type: "DepthwiseConvolution"
  bottom: "conv6_1/expand/bn"
  top: "conv6_1/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 960
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 960
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv6_1/dwise/bn"
  type: "BatchNorm"
  bottom: "conv6_1/dwise"
  top: "conv6_1/dwise/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv6_1/dwise/scale"
  type: "Scale"
  bottom: "conv6_1/dwise/bn"
  top: "conv6_1/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu6_1/dwise"
  type: "ReLU"
  bottom: "conv6_1/dwise/bn"
  top: "conv6_1/dwise/bn"
}
layer {
  name: "conv6_1/linear"
  type: "Convolution"
  bottom: "conv6_1/dwise/bn"
  top: "conv6_1/linear"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 160
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv6_1/linear/bn"
  type: "BatchNorm"
  bottom: "conv6_1/linear"
  top: "conv6_1/linear/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv6_1/linear/scale"
  type: "Scale"
  bottom: "conv6_1/linear/bn"
  top: "conv6_1/linear/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "block_6_1"
  type: "Eltwise"
  bottom: "conv5_3/linear/bn"
  bottom: "conv6_1/linear/bn"
  top: "block_6_1"
}
layer {
  name: "conv6_2/expand"
  type: "Convolution"
  bottom: "block_6_1"
  top: "conv6_2/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 960
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv6_2/expand/bn"
  type: "BatchNorm"
  bottom: "conv6_2/expand"
  top: "conv6_2/expand/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv6_2/expand/scale"
  type: "Scale"
  bottom: "conv6_2/expand/bn"
  top: "conv6_2/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu6_2/expand"
  type: "ReLU"
  bottom: "conv6_2/expand/bn"
  top: "conv6_2/expand/bn"
}
layer {
  name: "conv6_2/dwise"
  type: "DepthwiseConvolution"
  bottom: "conv6_2/expand/bn"
  top: "conv6_2/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 960
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 960
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv6_2/dwise/bn"
  type: "BatchNorm"
  bottom: "conv6_2/dwise"
  top: "conv6_2/dwise/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv6_2/dwise/scale"
  type: "Scale"
  bottom: "conv6_2/dwise/bn"
  top: "conv6_2/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu6_2/dwise"
  type: "ReLU"
  bottom: "conv6_2/dwise/bn"
  top: "conv6_2/dwise/bn"
}
layer {
  name: "conv6_2/linear"
  type: "Convolution"
  bottom: "conv6_2/dwise/bn"
  top: "conv6_2/linear"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 160
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv6_2/linear/bn"
  type: "BatchNorm"
  bottom: "conv6_2/linear"
  top: "conv6_2/linear/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv6_2/linear/scale"
  type: "Scale"
  bottom: "conv6_2/linear/bn"
  top: "conv6_2/linear/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "block_6_2"
  type: "Eltwise"
  bottom: "block_6_1"
  bottom: "conv6_2/linear/bn"
  top: "block_6_2"
}
layer {
  name: "conv6_3/expand"
  type: "Convolution"
  bottom: "block_6_2"
  top: "conv6_3/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 960
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv6_3/expand/bn"
  type: "BatchNorm"
  bottom: "conv6_3/expand"
  top: "conv6_3/expand/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv6_3/expand/scale"
  type: "Scale"
  bottom: "conv6_3/expand/bn"
  top: "conv6_3/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu6_3/expand"
  type: "ReLU"
  bottom: "conv6_3/expand/bn"
  top: "conv6_3/expand/bn"
}
layer {
  name: "conv6_3/dwise"
  type: "DepthwiseConvolution"
  bottom: "conv6_3/expand/bn"
  top: "conv6_3/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 960
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 960
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv6_3/dwise/bn"
  type: "BatchNorm"
  bottom: "conv6_3/dwise"
  top: "conv6_3/dwise/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv6_3/dwise/scale"
  type: "Scale"
  bottom: "conv6_3/dwise/bn"
  top: "conv6_3/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu6_3/dwise"
  type: "ReLU"
  bottom: "conv6_3/dwise/bn"
  top: "conv6_3/dwise/bn"
}
layer {
  name: "conv6_3/linear"
  type: "Convolution"
  bottom: "conv6_3/dwise/bn"
  top: "conv6_3/linear"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 320
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv6_3/linear/bn"
  type: "BatchNorm"
  bottom: "conv6_3/linear"
  top: "conv6_3/linear/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv6_3/linear/scale"
  type: "Scale"
  bottom: "conv6_3/linear/bn"
  top: "conv6_3/linear/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv6_4"
  type: "Convolution"
  bottom: "conv6_3/linear/bn"
  top: "conv6_4"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 1280
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv6_4/bn"
  type: "BatchNorm"
  bottom: "conv6_4"
  top: "conv6_4/bn"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
    eps: 1e-5
  }
}
layer {
  name: "conv6_4/scale"
  type: "Scale"
  bottom: "conv6_4/bn"
  top: "conv6_4/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu6_4"
  type: "ReLU"
  bottom: "conv6_4/bn"
  top: "conv6_4/bn"
}
layer {
  name: "pool6"
  type: "Pooling"
  bottom: "conv6_4/bn"
  top: "pool6"
  pooling_param {
    pool: AVE
    global_pooling: true
  }
}
layer {
  name: "fc7"
  type: "Convolution"
  bottom: "pool6"
  top: "fc7"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 1000
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer{
   name: "fc7_bn"
   type: "BatchNorm"
   bottom: "fc7"
   top: "fc7"
   batch_norm_param{
    use_global_stats: true
    }
  
}

layer {
  name: "l2"
  type: "L2Norm"
  bottom: "fc7"
  top: "l2"
}

layer {
  name: "silence"
  type: "Silence"
  bottom: "l2"
}