name: "mobilenet_v2"
layer {
  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TRAIN
  }
  transform_param {
    mirror: true
    mean_file: "mean.binaryproto"
  }
  data_param {
    source: "train.lmdb"
    batch_size: 32
    backend: LMDB
  }
}
layer {
  name: "mobilenet_v2"
  type: "MemoryData"
  top: "data"
  top: "label"
  memory_data_param {
    batch_size: 32
    channels: 3
    height: 224
    width: 224
  }
 include {
    phase: TEST
  }
}
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"
}
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"
}
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: "ConvolutionDepthwise"
  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"
}
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"
}
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"
}
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: "ConvolutionDepthwise"
  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"
}
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"
}
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"
}
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: "ConvolutionDepthwise"
  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"
 }
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"
}
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"
}
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: "ConvolutionDepthwise"
  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"

}
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"

}
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"

}
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: "ConvolutionDepthwise"
  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"

}
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"

}
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"

}
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: "ConvolutionDepthwise"
  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"

}
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"

}
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"

}
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: "ConvolutionDepthwise"
  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"

}
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"

}
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"

}
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: "ConvolutionDepthwise"
  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"

}
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"

}
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"

}
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: "ConvolutionDepthwise"
  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"

}
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"

}
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"

}
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: "ConvolutionDepthwise"
  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"

}
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"

}
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"

}
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: "ConvolutionDepthwise"
  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"

}
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"

}
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"

}
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: "ConvolutionDepthwise"
  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"

}
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"

}
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"

}
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: "ConvolutionDepthwise"
  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"

}
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"

}
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"

}
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: "ConvolutionDepthwise"
  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"

}
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"

}
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"

}
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: "ConvolutionDepthwise"
  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"

}
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"

}
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"

}
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: "ConvolutionDepthwise"
  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"

}
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"

}
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"
}
########### below modification for ssd: stride 2 in 6_3

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"

}
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: "ConvolutionDepthwise"
  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
    stride: 2
    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"

}
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"

}
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
  }
}
##### below change all the end for ssd: add 6_4 and 6_5 on the model of bottleneck
layer {
  name: "conv6_4/expand"
  type: "Convolution"
  bottom: "conv6_3/linear/bn"
  top: "conv6_4/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 1920
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv6_4/expand/bn"
  type: "BatchNorm"
  bottom: "conv6_4/expand"
  top: "conv6_4/expand/bn"

}
layer {
  name: "conv6_4/expand/scale"
  type: "Scale"
  bottom: "conv6_4/expand/bn"
  top: "conv6_4/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu6_4/expand"
  type: "ReLU"
  bottom: "conv6_4/expand/bn"
  top: "conv6_4/expand/bn"
}
layer {
  name: "conv6_4/dwise"
  type: "ConvolutionDepthwise"
  bottom: "conv6_4/expand/bn"
  top: "conv6_4/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 1920
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1920
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv6_4/dwise/bn"
  type: "BatchNorm"
  bottom: "conv6_4/dwise"
  top: "conv6_4/dwise/bn"

}
layer {
  name: "conv6_4/dwise/scale"
  type: "Scale"
  bottom: "conv6_4/dwise/bn"
  top: "conv6_4/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu6_4/dwise"
  type: "ReLU"
  bottom: "conv6_4/dwise/bn"
  top: "conv6_4/dwise/bn"
}
layer {
  name: "conv6_4/linear"
  type: "Convolution"
  bottom: "conv6_4/dwise/bn"
  top: "conv6_4/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_4/linear/bn"
  type: "BatchNorm"
  bottom: "conv6_4/linear"
  top: "conv6_4/linear/bn"

}
layer {
  name: "conv6_4/linear/scale"
  type: "Scale"
  bottom: "conv6_4/linear/bn"
  top: "conv6_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_6_4"
  type: "Eltwise"
  bottom: "conv6_3/linear/bn"
  bottom: "conv6_4/linear/bn"
  top: "block_6_4"
}
layer {
  name: "conv6_5/expand"
  type: "Convolution"
  bottom: "block_6_4"
  top: "conv6_5/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 1920
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv6_5/expand/bn"
  type: "BatchNorm"
  bottom: "conv6_5/expand"
  top: "conv6_5/expand/bn"

}
layer {
  name: "conv6_5/expand/scale"
  type: "Scale"
  bottom: "conv6_5/expand/bn"
  top: "conv6_5/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu6_5/expand"
  type: "ReLU"
  bottom: "conv6_5/expand/bn"
  top: "conv6_5/expand/bn"
}
layer {
  name: "conv6_5/dwise"
  type: "ConvolutionDepthwise"
  bottom: "conv6_5/expand/bn"
  top: "conv6_5/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 1920
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1920
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv6_5/dwise/bn"
  type: "BatchNorm"
  bottom: "conv6_5/dwise"
  top: "conv6_5/dwise/bn"

}
layer {
  name: "conv6_5/dwise/scale"
  type: "Scale"
  bottom: "conv6_5/dwise/bn"
  top: "conv6_5/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu6_5/dwise"
  type: "ReLU"
  bottom: "conv6_5/dwise/bn"
  top: "conv6_5/dwise/bn"
}
layer {
  name: "conv6_5/linear"
  type: "Convolution"
  bottom: "conv6_5/dwise/bn"
  top: "conv6_5/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_5/linear/bn"
  type: "BatchNorm"
  bottom: "conv6_5/linear"
  top: "conv6_5/linear/bn"

}
layer {
  name: "conv6_5/linear/scale"
  type: "Scale"
  bottom: "conv6_5/linear/bn"
  top: "conv6_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_6_5"
  type: "Eltwise"
  bottom: "block_6_4"
  bottom: "conv6_5/linear/bn"
  top: "block_6_5"
}


##### as well as 7_1 and 7_2 and 7_3 : bottlenecks



layer {
  name: "conv7_1/expand"
  type: "Convolution"
  bottom: "block_6_5"
  top: "conv7_1/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 1920
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}


layer {
  name: "conv7_1/expand/bn"
  type: "BatchNorm"
  bottom: "conv7_1/expand"
  top: "conv7_1/expand/bn"

}
layer {
  name: "conv7_1/expand/scale"
  type: "Scale"
  bottom: "conv7_1/expand/bn"
  top: "conv7_1/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu7_1/expand"
  type: "ReLU"
  bottom: "conv7_1/expand/bn"
  top: "conv7_1/expand/bn"
}
layer {
  name: "conv7_1/dwise"
  type: "ConvolutionDepthwise"
  bottom: "conv7_1/expand/bn"
  top: "conv7_1/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 1920
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    group: 1920
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv7_1/dwise/bn"
  type: "BatchNorm"
  bottom: "conv7_1/dwise"
  top: "conv7_1/dwise/bn"

}
layer {
  name: "conv7_1/dwise/scale"
  type: "Scale"
  bottom: "conv7_1/dwise/bn"
  top: "conv7_1/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu7_1/dwise"
  type: "ReLU"
  bottom: "conv7_1/dwise/bn"
  top: "conv7_1/dwise/bn"
}
layer {
  name: "conv7_1/linear"
  type: "Convolution"
  bottom: "conv7_1/dwise/bn"
  top: "conv7_1/linear"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 640
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv7_1/linear/bn"
  type: "BatchNorm"
  bottom: "conv7_1/linear"
  top: "conv7_1/linear/bn"

}
layer {
  name: "conv7_1/linear/scale"
  type: "Scale"
  bottom: "conv7_1/linear/bn"
  top: "conv7_1/linear/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv7_2/expand"
  type: "Convolution"
  bottom: "conv7_1/linear/bn"
  top: "conv7_2/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 3840
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv7_2/expand/bn"
  type: "BatchNorm"
  bottom: "conv7_2/expand"
  top: "conv7_2/expand/bn"

}
layer {
  name: "conv7_2/expand/scale"
  type: "Scale"
  bottom: "conv7_2/expand/bn"
  top: "conv7_2/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu7_2/expand"
  type: "ReLU"
  bottom: "conv7_2/expand/bn"
  top: "conv7_2/expand/bn"
}
layer {
  name: "conv7_2/dwise"
  type: "ConvolutionDepthwise"
  bottom: "conv7_2/expand/bn"
  top: "conv7_2/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 3840
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 3840
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv7_2/dwise/bn"
  type: "BatchNorm"
  bottom: "conv7_2/dwise"
  top: "conv7_2/dwise/bn"

}
layer {
  name: "conv7_2/dwise/scale"
  type: "Scale"
  bottom: "conv7_2/dwise/bn"
  top: "conv7_2/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu7_2/dwise"
  type: "ReLU"
  bottom: "conv7_2/dwise/bn"
  top: "conv7_2/dwise/bn"
}
layer {
  name: "conv7_2/linear"
  type: "Convolution"
  bottom: "conv7_2/dwise/bn"
  top: "conv7_2/linear"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 640
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv7_2/linear/bn"
  type: "BatchNorm"
  bottom: "conv7_2/linear"
  top: "conv7_2/linear/bn"
}
layer {
  name: "conv7_2/linear/scale"
  type: "Scale"
  bottom: "conv7_2/linear/bn"
  top: "conv7_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_7_2"
  type: "Eltwise"
  bottom: "conv7_1/linear/bn"
  bottom: "conv7_2/linear/bn"
  top: "block_7_2"
}
layer {
  name: "conv7_3/expand"
  type: "Convolution"
  bottom: "block_7_2"
  top: "conv7_3/expand"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 3840
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv7_3/expand/bn"
  type: "BatchNorm"
  bottom: "conv7_3/expand"
  top: "conv7_3/expand/bn"

}
layer {
  name: "conv7_3/expand/scale"
  type: "Scale"
  bottom: "conv7_3/expand/bn"
  top: "conv7_3/expand/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu7_3/expand"
  type: "ReLU"
  bottom: "conv7_3/expand/bn"
  top: "conv7_3/expand/bn"
}
layer {
  name: "conv7_3/dwise"
  type: "ConvolutionDepthwise"
  bottom: "conv7_3/expand/bn"
  top: "conv7_3/dwise"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 3840
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 3840
    weight_filler {
      type: "msra"
    }
    engine: CAFFE
  }
}
layer {
  name: "conv7_3/dwise/bn"
  type: "BatchNorm"
  bottom: "conv7_3/dwise"
  top: "conv7_3/dwise/bn"

}
layer {
  name: "conv7_3/dwise/scale"
  type: "Scale"
  bottom: "conv7_3/dwise/bn"
  top: "conv7_3/dwise/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu7_3/dwise"
  type: "ReLU"
  bottom: "conv7_3/dwise/bn"
  top: "conv7_3/dwise/bn"
}
layer {
  name: "conv7_3/linear"
  type: "Convolution"
  bottom: "conv7_3/dwise/bn"
  top: "conv7_3/linear"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 640
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv7_3/linear/bn"
  type: "BatchNorm"
  bottom: "conv7_3/linear"
  top: "conv7_3/linear/bn"

}
layer {
  name: "conv7_3/linear/scale"
  type: "Scale"
  bottom: "conv7_3/linear/bn"
  top: "conv7_3/linear/bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "block_7_3"
  type: "Eltwise"
  bottom: "block_7_2"
  bottom: "conv7_3/linear/bn"
  top: "block_7_3"
}



# ##### 8_1 is 1x1 pixel large
# layer {
#   name: "conv8_1/expand"
#   type: "Convolution"
#   bottom: "block_7_3"
#   top: "conv8_1/expand"
#   param {
#     lr_mult: 1
#     decay_mult: 1
#   }
#   convolution_param {
#     num_output: 3840
#     bias_term: false
#     kernel_size: 1
#     weight_filler {
#       type: "msra"
#     }
#   }
# }
# layer {
#   name: "conv8_1/expand/bn"
#   type: "BatchNorm"
#   bottom: "conv8_1/expand"
#   top: "conv8_1/expand/bn"

# }
# layer {
#   name: "conv8_1/expand/scale"
#   type: "Scale"
#   bottom: "conv8_1/expand/bn"
#   top: "conv8_1/expand/bn"
#   param {
#     lr_mult: 1
#     decay_mult: 0
#   }
#   param {
#     lr_mult: 1
#     decay_mult: 0
#   }
#   scale_param {
#     bias_term: true
#   }
# }
# layer {
#   name: "relu8_1/expand"
#   type: "ReLU"
#   bottom: "conv8_1/expand/bn"
#   top: "conv8_1/expand/bn"
# }
# layer {
#   name: "conv8_1/dwise"
#   type: "ConvolutionDepthwise"
#   bottom: "conv8_1/expand/bn"
#   top: "conv8_1/dwise"
#   param {
#     lr_mult: 1
#     decay_mult: 1
#   }
#   convolution_param {
#     num_output: 3840
#     bias_term: false
#     kernel_size: 1
#     group: 3840
#     weight_filler {
#       type: "msra"
#     }
#     engine: CAFFE
#   }
# }
# layer {
#   name: "conv8_1/dwise/bn"
#   type: "BatchNorm"
#   bottom: "conv8_1/dwise"
#   top: "conv8_1/dwise/bn"

# }
# layer {
#   name: "conv8_1/dwise/scale"
#   type: "Scale"
#   bottom: "conv8_1/dwise/bn"
#   top: "conv8_1/dwise/bn"
#   param {
#     lr_mult: 1
#     decay_mult: 0
#   }
#   param {
#     lr_mult: 1
#     decay_mult: 0
#   }
#   scale_param {
#     bias_term: true
#   }
# }
# layer {
#   name: "relu8_1/dwise"
#   type: "ReLU"
#   bottom: "conv8_1/dwise/bn"
#   top: "conv8_1/dwise/bn"
# }
# layer {
#   name: "conv8_1/linear"
#   type: "Convolution"
#   bottom: "conv8_1/dwise/bn"
#   top: "conv8_1/linear"
#   param {
#     lr_mult: 1
#     decay_mult: 1
#   }
#   convolution_param {
#     num_output: 1280
#     bias_term: false
#     kernel_size: 1
#     weight_filler {
#       type: "msra"
#     }
#   }
# }
# layer {
#   name: "conv8_1/linear/bn"
#   type: "BatchNorm"
#   bottom: "conv8_1/linear"
#   top: "conv8_1/linear/bn"

# }
# layer {
#   name: "conv8_1/linear/scale"
#   type: "Scale"
#   bottom: "conv8_1/linear/bn"
#   top: "conv8_1/linear/bn"
#   param {
#     lr_mult: 1
#     decay_mult: 0
#   }
#   param {
#     lr_mult: 1
#     decay_mult: 0
#   }
#   scale_param {
#     bias_term: true
#   }
# }
# layer {
#   name: "conv8_2/expand"
#   type: "Convolution"
#   bottom: "conv8_1/linear/bn"
#   top: "conv8_2/expand"
#   param {
#     lr_mult: 1
#     decay_mult: 1
#   }
#   convolution_param {
#     num_output: 7680
#     bias_term: false
#     kernel_size: 1
#     weight_filler {
#       type: "msra"
#     }
#   }
# }
# layer {
#   name: "conv8_2/expand/bn"
#   type: "BatchNorm"
#   bottom: "conv8_2/expand"
#   top: "conv8_2/expand/bn"

# }
# layer {
#   name: "conv8_2/expand/scale"
#   type: "Scale"
#   bottom: "conv8_2/expand/bn"
#   top: "conv8_2/expand/bn"
#   param {
#     lr_mult: 1
#     decay_mult: 0
#   }
#   param {
#     lr_mult: 1
#     decay_mult: 0
#   }
#   scale_param {
#     bias_term: true
#   }
# }
# layer {
#   name: "relu8_2/expand"
#   type: "ReLU"
#   bottom: "conv8_2/expand/bn"
#   top: "conv8_2/expand/bn"
# }
# layer {
#   name: "conv8_2/dwise"
#   type: "ConvolutionDepthwise"
#   bottom: "conv8_2/expand/bn"
#   top: "conv8_2/dwise"
#   param {
#     lr_mult: 1
#     decay_mult: 1
#   }
#   convolution_param {
#     num_output: 7680
#     bias_term: false
#     kernel_size: 1
#     group: 7680
#     weight_filler {
#       type: "msra"
#     }
#     engine: CAFFE
#   }
# }
# layer {
#   name: "conv8_2/dwise/bn"
#   type: "BatchNorm"
#   bottom: "conv8_2/dwise"
#   top: "conv8_2/dwise/bn"

# }
# layer {
#   name: "conv8_2/dwise/scale"
#   type: "Scale"
#   bottom: "conv8_2/dwise/bn"
#   top: "conv8_2/dwise/bn"
#   param {
#     lr_mult: 1
#     decay_mult: 0
#   }
#   param {
#     lr_mult: 1
#     decay_mult: 0
#   }
#   scale_param {
#     bias_term: true
#   }
# }
# layer {
#   name: "relu8_2/dwise"
#   type: "ReLU"
#   bottom: "conv8_2/dwise/bn"
#   top: "conv8_2/dwise/bn"
# }
# layer {
#   name: "conv8_2/linear"
#   type: "Convolution"
#   bottom: "conv8_2/dwise/bn"
#   top: "conv8_2/linear"
#   param {
#     lr_mult: 1
#     decay_mult: 1
#   }
#   convolution_param {
#     num_output: 1280
#     bias_term: false
#     kernel_size: 1
#     weight_filler {
#       type: "msra"
#     }
#   }
# }
# layer {
#   name: "conv8_2/linear/bn"
#   type: "BatchNorm"
#   bottom: "conv8_2/linear"
#   top: "conv8_2/linear/bn"

# }
# layer {
#   name: "conv8_2/linear/scale"
#   type: "Scale"
#   bottom: "conv8_2/linear/bn"
#   top: "conv8_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_8_2"
#   type: "Eltwise"
#   bottom: "conv8_1/linear/bn"
#   bottom: "conv8_2/linear/bn"
#   top: "block_8_2"
# }