mobilenet_yolov3_deploy.prototxt

name: "MobileNet-YOLO"
input: "data"
input_shape {
  dim: 1
  dim: 3
  dim: 416
  dim: 416
}


layer {
  name: "conv0"
  type: "Convolution"
  bottom: "data"
  top: "conv0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv0/bn"
  type: "BatchNorm"
  bottom: "conv0"
  top: "conv0"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv0/scale"
  type: "Scale"
  bottom: "conv0"
  top: "conv0"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv0/relu"
  type: "ReLU"
  bottom: "conv0"
  top: "conv0"
}
layer {
  name: "conv1/dw"
  type: "DepthwiseConvolution"
  bottom: "conv0"
  top: "conv1/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 32
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv1/dw/bn"
  type: "BatchNorm"
  bottom: "conv1/dw"
  top: "conv1/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv1/dw/scale"
  type: "Scale"
  bottom: "conv1/dw"
  top: "conv1/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv1/dw/relu"
  type: "ReLU"
  bottom: "conv1/dw"
  top: "conv1/dw"
}
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "conv1/dw"
  top: "conv1"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv1/bn"
  type: "BatchNorm"
  bottom: "conv1"
  top: "conv1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv1/scale"
  type: "Scale"
  bottom: "conv1"
  top: "conv1"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv1/relu"
  type: "ReLU"
  bottom: "conv1"
  top: "conv1"
}
layer {
  name: "conv2/dw"
  type: "DepthwiseConvolution"
  bottom: "conv1"
  top: "conv2/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    group: 64
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv2/dw/bn"
  type: "BatchNorm"
  bottom: "conv2/dw"
  top: "conv2/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv2/dw/scale"
  type: "Scale"
  bottom: "conv2/dw"
  top: "conv2/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv2/dw/relu"
  type: "ReLU"
  bottom: "conv2/dw"
  top: "conv2/dw"
}
layer {
  name: "conv2"
  type: "Convolution"
  bottom: "conv2/dw"
  top: "conv2"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv2/bn"
  type: "BatchNorm"
  bottom: "conv2"
  top: "conv2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv2/scale"
  type: "Scale"
  bottom: "conv2"
  top: "conv2"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv2/relu"
  type: "ReLU"
  bottom: "conv2"
  top: "conv2"
}
layer {
  name: "conv3/dw"
  type: "DepthwiseConvolution"
  bottom: "conv2"
  top: "conv3/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 128
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv3/dw/bn"
  type: "BatchNorm"
  bottom: "conv3/dw"
  top: "conv3/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv3/dw/scale"
  type: "Scale"
  bottom: "conv3/dw"
  top: "conv3/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv3/dw/relu"
  type: "ReLU"
  bottom: "conv3/dw"
  top: "conv3/dw"
}
layer {
  name: "conv3"
  type: "Convolution"
  bottom: "conv3/dw"
  top: "conv3"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv3/bn"
  type: "BatchNorm"
  bottom: "conv3"
  top: "conv3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv3/scale"
  type: "Scale"
  bottom: "conv3"
  top: "conv3"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv3/relu"
  type: "ReLU"
  bottom: "conv3"
  top: "conv3"
}
layer {
  name: "conv4/dw"
  type: "DepthwiseConvolution"
  bottom: "conv3"
  top: "conv4/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    group: 128
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4/dw/bn"
  type: "BatchNorm"
  bottom: "conv4/dw"
  top: "conv4/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv4/dw/scale"
  type: "Scale"
  bottom: "conv4/dw"
  top: "conv4/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv4/dw/relu"
  type: "ReLU"
  bottom: "conv4/dw"
  top: "conv4/dw"
}
layer {
  name: "conv4"
  type: "Convolution"
  bottom: "conv4/dw"
  top: "conv4"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 256
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4/bn"
  type: "BatchNorm"
  bottom: "conv4"
  top: "conv4"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv4/scale"
  type: "Scale"
  bottom: "conv4"
  top: "conv4"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv4/relu"
  type: "ReLU"
  bottom: "conv4"
  top: "conv4"
}
layer {
  name: "conv5/dw"
  type: "DepthwiseConvolution"
  bottom: "conv4"
  top: "conv5/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 256
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 256
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5/dw/bn"
  type: "BatchNorm"
  bottom: "conv5/dw"
  top: "conv5/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv5/dw/scale"
  type: "Scale"
  bottom: "conv5/dw"
  top: "conv5/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv5/dw/relu"
  type: "ReLU"
  bottom: "conv5/dw"
  top: "conv5/dw"
}
layer {
  name: "conv5"
  type: "Convolution"
  bottom: "conv5/dw"
  top: "conv5"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 256
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5/bn"
  type: "BatchNorm"
  bottom: "conv5"
  top: "conv5"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv5/scale"
  type: "Scale"
  bottom: "conv5"
  top: "conv5"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv5/relu"
  type: "ReLU"
  bottom: "conv5"
  top: "conv5"
}
layer {
  name: "conv6/dw"
  type: "DepthwiseConvolution"
  bottom: "conv5"
  top: "conv6/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 256
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    group: 256
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv6/dw/bn"
  type: "BatchNorm"
  bottom: "conv6/dw"
  top: "conv6/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv6/dw/scale"
  type: "Scale"
  bottom: "conv6/dw"
  top: "conv6/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv6/dw/relu"
  type: "ReLU"
  bottom: "conv6/dw"
  top: "conv6/dw"
}
layer {
  name: "conv6"
  type: "Convolution"
  bottom: "conv6/dw"
  top: "conv6"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv6/bn"
  type: "BatchNorm"
  bottom: "conv6"
  top: "conv6"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv6/scale"
  type: "Scale"
  bottom: "conv6"
  top: "conv6"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv6/relu"
  type: "ReLU"
  bottom: "conv6"
  top: "conv6"
}
layer {
  name: "conv7/dw"
  type: "DepthwiseConvolution"
  bottom: "conv6"
  top: "conv7/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 512
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv7/dw/bn"
  type: "BatchNorm"
  bottom: "conv7/dw"
  top: "conv7/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv7/dw/scale"
  type: "Scale"
  bottom: "conv7/dw"
  top: "conv7/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv7/dw/relu"
  type: "ReLU"
  bottom: "conv7/dw"
  top: "conv7/dw"
}
layer {
  name: "conv7"
  type: "Convolution"
  bottom: "conv7/dw"
  top: "conv7"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv7/bn"
  type: "BatchNorm"
  bottom: "conv7"
  top: "conv7"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv7/scale"
  type: "Scale"
  bottom: "conv7"
  top: "conv7"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv7/relu"
  type: "ReLU"
  bottom: "conv7"
  top: "conv7"
}
layer {
  name: "conv8/dw"
  type: "DepthwiseConvolution"
  bottom: "conv7"
  top: "conv8/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    pad: 1
    kernel_size: 3

    group: 512
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv8/dw/bn"
  type: "BatchNorm"
  bottom: "conv8/dw"
  top: "conv8/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv8/dw/scale"
  type: "Scale"
  bottom: "conv8/dw"
  top: "conv8/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv8/dw/relu"
  type: "ReLU"
  bottom: "conv8/dw"
  top: "conv8/dw"
}
layer {
  name: "conv8"
  type: "Convolution"
  bottom: "conv8/dw"
  top: "conv8"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv8/bn"
  type: "BatchNorm"
  bottom: "conv8"
  top: "conv8"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv8/scale"
  type: "Scale"
  bottom: "conv8"
  top: "conv8"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv8/relu"
  type: "ReLU"
  bottom: "conv8"
  top: "conv8"
}
layer {
  name: "conv9/dw"
  type: "DepthwiseConvolution"
  bottom: "conv8"
  top: "conv9/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 512
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv9/dw/bn"
  type: "BatchNorm"
  bottom: "conv9/dw"
  top: "conv9/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv9/dw/scale"
  type: "Scale"
  bottom: "conv9/dw"
  top: "conv9/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv9/dw/relu"
  type: "ReLU"
  bottom: "conv9/dw"
  top: "conv9/dw"
}
layer {
  name: "conv9"
  type: "Convolution"
  bottom: "conv9/dw"
  top: "conv9"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv9/bn"
  type: "BatchNorm"
  bottom: "conv9"
  top: "conv9"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv9/scale"
  type: "Scale"
  bottom: "conv9"
  top: "conv9"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv9/relu"
  type: "ReLU"
  bottom: "conv9"
  top: "conv9"
}
layer {
  name: "conv10/dw"
  type: "DepthwiseConvolution"
  bottom: "conv9"
  top: "conv10/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 512
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv10/dw/bn"
  type: "BatchNorm"
  bottom: "conv10/dw"
  top: "conv10/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv10/dw/scale"
  type: "Scale"
  bottom: "conv10/dw"
  top: "conv10/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv10/dw/relu"
  type: "ReLU"
  bottom: "conv10/dw"
  top: "conv10/dw"
}
layer {
  name: "conv10"
  type: "Convolution"
  bottom: "conv10/dw"
  top: "conv10"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv10/bn"
  type: "BatchNorm"
  bottom: "conv10"
  top: "conv10"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv10/scale"
  type: "Scale"
  bottom: "conv10"
  top: "conv10"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv10/relu"
  type: "ReLU"
  bottom: "conv10"
  top: "conv10"
}
layer {
  name: "conv11/dw"
  type: "DepthwiseConvolution"
  bottom: "conv10"
  top: "conv11/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 512
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv11/dw/bn"
  type: "BatchNorm"
  bottom: "conv11/dw"
  top: "conv11/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv11/dw/scale"
  type: "Scale"
  bottom: "conv11/dw"
  top: "conv11/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv11/dw/relu"
  type: "ReLU"
  bottom: "conv11/dw"
  top: "conv11/dw"
}
layer {
  name: "conv11"
  type: "Convolution"
  bottom: "conv11/dw"
  top: "conv11"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv11/bn"
  type: "BatchNorm"
  bottom: "conv11"
  top: "conv11"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv11/scale"
  type: "Scale"
  bottom: "conv11"
  top: "conv11"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv11/relu"
  type: "ReLU"
  bottom: "conv11"
  top: "conv11"
}
layer {
  name: "conv12/dw"
  type: "DepthwiseConvolution"
  bottom: "conv11"
  top: "conv12/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    group: 512
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv12/dw/bn"
  type: "BatchNorm"
  bottom: "conv12/dw"
  top: "conv12/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv12/dw/scale"
  type: "Scale"
  bottom: "conv12/dw"
  top: "conv12/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv12/dw/relu"
  type: "ReLU"
  bottom: "conv12/dw"
  top: "conv12/dw"
}
layer {
  name: "conv12"
  type: "Convolution"
  bottom: "conv12/dw"
  top: "conv12"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 1024
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv12/bn"
  type: "BatchNorm"
  bottom: "conv12"
  top: "conv12"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv12/scale"
  type: "Scale"
  bottom: "conv12"
  top: "conv12"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv12/relu"
  type: "ReLU"
  bottom: "conv12"
  top: "conv12"
}
layer {
  name: "conv13/dw"
  type: "DepthwiseConvolution"
  bottom: "conv12"
  top: "conv13/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 1024
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1024
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv13/dw/bn"
  type: "BatchNorm"
  bottom: "conv13/dw"
  top: "conv13/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv13/dw/scale"
  type: "Scale"
  bottom: "conv13/dw"
  top: "conv13/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv13/dw/relu"
  type: "ReLU"
  bottom: "conv13/dw"
  top: "conv13/dw"
}
layer {
  name: "conv13"
  type: "Convolution"
  bottom: "conv13/dw"
  top: "conv13"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 1024
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv13/bn"
  type: "BatchNorm"
  bottom: "conv13"
  top: "conv13"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv13/scale"
  type: "Scale"
  bottom: "conv13"
  top: "conv13"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv13/relu"
  type: "ReLU"
  bottom: "conv13"
  top: "conv13"
}

layer {
  name: "conv15/dw"
  type: "DepthwiseConvolution"
  bottom: "conv13"
  top: "conv15/dw"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 1024
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1024
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv15/dw/bn"
  type: "BatchNorm"
  bottom: "conv15/dw"
  top: "conv15/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv15/dw/scale"
  type: "Scale"
  bottom: "conv15/dw"
  top: "conv15/dw"
  param {
    lr_mult: 1
    decay_mult: 0.0
  }
  param {
    lr_mult: 2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv15/dw/relu"
  type: "ReLU"
  bottom: "conv15/dw"
  top: "conv15/dw"
}
layer {
  name: "conv15"
  type: "Convolution"
  bottom: "conv15/dw"
  top: "conv15"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 1024
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv15/bn"
  type: "BatchNorm"
  bottom: "conv15"
  top: "conv15"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv15/scale"
  type: "Scale"
  bottom: "conv15"
  top: "conv15"
  param {
    lr_mult: 1
    decay_mult: 0.0
  }
  param {
    lr_mult: 2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv15/relu"
  type: "ReLU"
  bottom: "conv15"
  top: "conv15"
}
layer {
  name: "upsample"
  type: "Deconvolution"
  bottom: "conv15"
  top: "upsample"
  param { lr_mult: 1  decay_mult: 1 }
  convolution_param {
    num_output: 512
	group: 512
    kernel_size: 2  stride: 2  pad: 0
    weight_filler: { type: "bilinear" }
    bias_term: false
  }
}

layer {
  name: "conv16/dw"
  type: "DepthwiseConvolution"
  bottom: "upsample"
  top: "conv16/dw"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 512
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv16/dw/bn"
  type: "BatchNorm"
  bottom: "conv16/dw"
  top: "conv16/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv16/dw/scale"
  type: "Scale"
  bottom: "conv16/dw"
  top: "conv16/dw"
  param {
    lr_mult: 1
    decay_mult: 0.0
  }
  param {
    lr_mult: 2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv16/dw/relu"
  type: "ReLU"
  bottom: "conv16/dw"
  top: "conv16/dw"
}
layer {
  name: "conv16"
  type: "Convolution"
  bottom: "conv16/dw"
  top: "conv16"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv16/bn"
  type: "BatchNorm"
  bottom: "conv16"
  top: "conv16"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv16/scale"
  type: "Scale"
  bottom: "conv16"
  top: "conv16"
  param {
    lr_mult: 1
    decay_mult: 0.0
  }
  param {
    lr_mult: 2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv16/relu"
  type: "ReLU"
  bottom: "conv16"
  top: "conv16"
}
layer {
  name: "conv17/dw"
  type: "DepthwiseConvolution"
  bottom: "conv11"
  top: "conv17/dw"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 512
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv17/dw/bn"
  type: "BatchNorm"
  bottom: "conv17/dw"
  top: "conv17/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv17/dw/scale"
  type: "Scale"
  bottom: "conv17/dw"
  top: "conv17/dw"
  param {
    lr_mult: 1
    decay_mult: 0.0
  }
  param {
    lr_mult: 2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv17/dw/relu"
  type: "ReLU"
  bottom: "conv17/dw"
  top: "conv17/dw"
}
layer {
  name: "conv17"
  type: "Convolution"
  bottom: "conv17/dw"
  top: "conv17"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv17/bn"
  type: "BatchNorm"
  bottom: "conv17"
  top: "conv17"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv17/scale"
  type: "Scale"
  bottom: "conv17"
  top: "conv17"
  param {
    lr_mult: 1
    decay_mult: 0.0
  }
  param {
    lr_mult: 2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv17/relu"
  type: "ReLU"
  bottom: "conv17"
  top: "conv17"
}
layer {
  name: "conv17/sum"
  type: "Eltwise"
  bottom: "conv16"
  bottom: "conv17"
  top: "conv17/sum"
}

layer {
  name: "conv18/dw"
  type: "DepthwiseConvolution"
  bottom: "conv17/sum"
  top: "conv18/dw"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 512
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv18/dw/bn"
  type: "BatchNorm"
  bottom: "conv18/dw"
  top: "conv18/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv18/dw/scale"
  type: "Scale"
  bottom: "conv18/dw"
  top: "conv18/dw"
  param {
    lr_mult: 1
    decay_mult: 0.0
  }
  param {
    lr_mult: 2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv18/dw/relu"
  type: "ReLU"
  bottom: "conv18/dw"
  top: "conv18/dw"
}
layer {
  name: "conv18"
  type: "Convolution"
  bottom: "conv18/dw"
  top: "conv18"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv18/bn"
  type: "BatchNorm"
  bottom: "conv18"
  top: "conv18"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv18/scale"
  type: "Scale"
  bottom: "conv18"
  top: "conv18"
  param {
    lr_mult: 1
    decay_mult: 0.0
  }
  param {
    lr_mult: 2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv18/relu"
  type: "ReLU"
  bottom: "conv18"
  top: "conv18"
}



layer {
  name: "upsample2"
  type: "Deconvolution"
  bottom: "conv18"
  top: "upsample2"
  param { lr_mult: 1  decay_mult: 1 }
  convolution_param {
    num_output: 256
	group: 256
    kernel_size: 2  stride: 2  pad: 0
    weight_filler: { type: "bilinear" }
    bias_term: false
  }
}
layer {
  name: "conv19/dw"
  type: "DepthwiseConvolution"
  bottom: "upsample2"
  top: "conv19/dw"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 256
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 256
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv19/dw/bn"
  type: "BatchNorm"
  bottom: "conv19/dw"
  top: "conv19/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv19/dw/scale"
  type: "Scale"
  bottom: "conv19/dw"
  top: "conv19/dw"
  param {
    lr_mult: 1
    decay_mult: 0.0
  }
  param {
    lr_mult: 2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv19/dw/relu"
  type: "ReLU"
  bottom: "conv19/dw"
  top: "conv19/dw"
}
layer {
  name: "conv19"
  type: "Convolution"
  bottom: "conv19/dw"
  top: "conv19"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 256
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv19/bn"
  type: "BatchNorm"
  bottom: "conv19"
  top: "conv19"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv19/scale"
  type: "Scale"
  bottom: "conv19"
  top: "conv19"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv19/relu"
  type: "ReLU"
  bottom: "conv19"
  top: "conv19"
}
layer {
  name: "conv20/dw"
  type: "DepthwiseConvolution"
  bottom: "conv5"
  top: "conv20/dw"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 256
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 256
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv20/dw/bn"
  type: "BatchNorm"
  bottom: "conv20/dw"
  top: "conv20/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv20/dw/scale"
  type: "Scale"
  bottom: "conv20/dw"
  top: "conv20/dw"
  param {
    lr_mult: 1
    decay_mult: 0.0
  }
  param {
    lr_mult: 2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv20/dw/relu"
  type: "ReLU"
  bottom: "conv20/dw"
  top: "conv20/dw"
}
layer {
  name: "conv20"
  type: "Convolution"
  bottom: "conv20/dw"
  top: "conv20"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 256
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv20/bn"
  type: "BatchNorm"
  bottom: "conv20"
  top: "conv20"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv20/scale"
  type: "Scale"
  bottom: "conv20"
  top: "conv20"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv20/relu"
  type: "ReLU"
  bottom: "conv20"
  top: "conv20"
}
layer {
  name: "conv20/sum"
  type: "Eltwise"
  bottom: "conv19"
  bottom: "conv20"
  top: "conv20/sum"
}
layer {
  name: "conv21/dw"
  type: "DepthwiseConvolution"
  bottom: "conv20/sum"
  top: "conv21/dw"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 256
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 256
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv21/dw/bn"
  type: "BatchNorm"
  bottom: "conv21/dw"
  top: "conv21/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv21/dw/scale"
  type: "Scale"
  bottom: "conv21/dw"
  top: "conv21/dw"
  param {
    lr_mult: 1
    decay_mult: 0.0
  }
  param {
    lr_mult: 2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv21/dw/relu"
  type: "ReLU"
  bottom: "conv21/dw"
  top: "conv21/dw"
}
layer {
  name: "conv21"
  type: "Convolution"
  bottom: "conv21/dw"
  top: "conv21"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv21/bn"
  type: "BatchNorm"
  bottom: "conv21"
  top: "conv21"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv21/scale"
  type: "Scale"
  bottom: "conv21"
  top: "conv21"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv21/relu"
  type: "ReLU"
  bottom: "conv21"
  top: "conv21"
}

layer {
  name: "conv22"
  type: "Convolution"
  bottom: "conv15"
  top: "conv22"
    param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 27
    kernel_size: 1
    pad: 0
    stride: 1
    weight_filler {
      type: "msra"
    }
	bias_filler {
      value: 0
    }
  }
}

layer {
  name: "conv23"
  type: "Convolution"
  bottom: "conv18"
  top: "conv23"
    param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 27
    kernel_size: 1
    pad: 0
    stride: 1
    weight_filler {
      type: "msra"
    }
	bias_filler {
      value: 0
    }
  }
}

layer {
  name: "conv24"
  type: "Convolution"
  bottom: "conv21"
  top: "conv24"
    param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 27
    kernel_size: 1
    pad: 0
    stride: 1
    weight_filler {
      type: "msra"
    }
	bias_filler {
      value: 0
    }
  }
}
layer {
  name: "detection_out"
  type: "Yolov3DetectionOutput"
  bottom: "conv22"
  bottom: "conv23"
  bottom: "conv24"
  top: "detection_out"
 
  yolov3_detection_output_param {
    confidence_threshold: 0.01
	nms_threshold: 0.45
    num_classes: 4
	
	#10,13,  16,30,  33,23,  30,61,  62,45,  59,119,  116,90,  156,198,  373,326
	
    biases: 10
    biases: 20
    biases: 19
    biases: 59
    biases: 22
    biases: 26
    biases: 36
    biases: 37
    biases: 39
    biases: 108
	biases: 54
    biases: 56
	biases: 82
    biases: 81
    biases: 101
    biases: 138
	biases: 183
    biases: 175
	
    mask:6
    mask:7
    mask:8
    mask:3
    mask:4
    mask:5	
    mask:0
    mask:1
    mask:2
    anchors_scale:32
    anchors_scale:16
	anchors_scale:8
    mask_group_num:3
  }
}