face-detection-adas-0001.prototxt

name: "mobilenet_ssd_672x384"
input: "data"
input_shape {
  dim: 1
  dim: 3
  dim: 384
  dim: 672
}

layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data"
  top: "conv1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 24
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv1/bn"
  type: "BatchNorm"
  bottom: "conv1"
  top: "conv1"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv1/scale"
  type: "Scale"
  bottom: "conv1"
  top: "conv1"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu1"
  type: "ReLU"
  bottom: "conv1"
  top: "conv1"
}
layer {
  name: "conv2_1/dw"
  type: "Convolution"
  bottom: "conv1"
  top: "conv2_1/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 24
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 24
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv2_1/dw/bn"
  type: "BatchNorm"
  bottom: "conv2_1/dw"
  top: "conv2_1/dw"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv2_1/dw/scale"
  type: "Scale"
  bottom: "conv2_1/dw"
  top: "conv2_1/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu2_1/dw"
  type: "ReLU"
  bottom: "conv2_1/dw"
  top: "conv2_1/dw"
}
layer {
  name: "conv2_1/sep"
  type: "Convolution"
  bottom: "conv2_1/dw"
  top: "conv2_1/sep"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 56
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv2_1/sep/bn"
  type: "BatchNorm"
  bottom: "conv2_1/sep"
  top: "conv2_1/sep"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv2_1/sep/scale"
  type: "Scale"
  bottom: "conv2_1/sep"
  top: "conv2_1/sep"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu2_1/sep"
  type: "ReLU"
  bottom: "conv2_1/sep"
  top: "conv2_1/sep"
}
layer {
  name: "conv2_2/dw"
  type: "Convolution"
  bottom: "conv2_1/sep"
  top: "conv2_2/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 56
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 56
    stride: 2
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv2_2/dw/bn"
  type: "BatchNorm"
  bottom: "conv2_2/dw"
  top: "conv2_2/dw"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv2_2/dw/scale"
  type: "Scale"
  bottom: "conv2_2/dw"
  top: "conv2_2/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu2_2/dw"
  type: "ReLU"
  bottom: "conv2_2/dw"
  top: "conv2_2/dw"
}
layer {
  name: "conv2_2/sep"
  type: "Convolution"
  bottom: "conv2_2/dw"
  top: "conv2_2/sep"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 104
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv2_2/sep/bn"
  type: "BatchNorm"
  bottom: "conv2_2/sep"
  top: "conv2_2/sep"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv2_2/sep/scale"
  type: "Scale"
  bottom: "conv2_2/sep"
  top: "conv2_2/sep"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu2_2/sep"
  type: "ReLU"
  bottom: "conv2_2/sep"
  top: "conv2_2/sep"
}
layer {
  name: "conv3_1/dw"
  type: "Convolution"
  bottom: "conv2_2/sep"
  top: "conv3_1/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 104
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 104
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv3_1/dw/bn"
  type: "BatchNorm"
  bottom: "conv3_1/dw"
  top: "conv3_1/dw"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv3_1/dw/scale"
  type: "Scale"
  bottom: "conv3_1/dw"
  top: "conv3_1/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu3_1/dw"
  type: "ReLU"
  bottom: "conv3_1/dw"
  top: "conv3_1/dw"
}
layer {
  name: "conv3_1/sep"
  type: "Convolution"
  bottom: "conv3_1/dw"
  top: "conv3_1/sep"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 120
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv3_1/sep/bn"
  type: "BatchNorm"
  bottom: "conv3_1/sep"
  top: "conv3_1/sep"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv3_1/sep/scale"
  type: "Scale"
  bottom: "conv3_1/sep"
  top: "conv3_1/sep"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu3_1/sep"
  type: "ReLU"
  bottom: "conv3_1/sep"
  top: "conv3_1/sep"
}
layer {
  name: "conv3_2/dw"
  type: "Convolution"
  bottom: "conv3_1/sep"
  top: "conv3_2/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 120
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 120
    stride: 2
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv3_2/dw/bn"
  type: "BatchNorm"
  bottom: "conv3_2/dw"
  top: "conv3_2/dw"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv3_2/dw/scale"
  type: "Scale"
  bottom: "conv3_2/dw"
  top: "conv3_2/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu3_2/dw"
  type: "ReLU"
  bottom: "conv3_2/dw"
  top: "conv3_2/dw"
}
layer {
  name: "conv3_2/sep"
  type: "Convolution"
  bottom: "conv3_2/dw"
  top: "conv3_2/sep"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 232
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv3_2/sep/bn"
  type: "BatchNorm"
  bottom: "conv3_2/sep"
  top: "conv3_2/sep"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv3_2/sep/scale"
  type: "Scale"
  bottom: "conv3_2/sep"
  top: "conv3_2/sep"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu3_2/sep"
  type: "ReLU"
  bottom: "conv3_2/sep"
  top: "conv3_2/sep"
}
layer {
  name: "conv4_1/dw"
  type: "Convolution"
  bottom: "conv3_2/sep"
  top: "conv4_1/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 232
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 232
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv4_1/dw/bn"
  type: "BatchNorm"
  bottom: "conv4_1/dw"
  top: "conv4_1/dw"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv4_1/dw/scale"
  type: "Scale"
  bottom: "conv4_1/dw"
  top: "conv4_1/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu4_1/dw"
  type: "ReLU"
  bottom: "conv4_1/dw"
  top: "conv4_1/dw"
}
layer {
  name: "conv4_1/sep"
  type: "Convolution"
  bottom: "conv4_1/dw"
  top: "conv4_1/sep"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 232
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv4_1/sep/bn"
  type: "BatchNorm"
  bottom: "conv4_1/sep"
  top: "conv4_1/sep"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv4_1/sep/scale"
  type: "Scale"
  bottom: "conv4_1/sep"
  top: "conv4_1/sep"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu4_1/sep"
  type: "ReLU"
  bottom: "conv4_1/sep"
  top: "conv4_1/sep"
}
layer {
  name: "conv4_2/dw"
  type: "Convolution"
  bottom: "conv4_1/sep"
  top: "conv4_2/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 232
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 232
    stride: 2
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv4_2/dw/bn"
  type: "BatchNorm"
  bottom: "conv4_2/dw"
  top: "conv4_2/dw"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv4_2/dw/scale"
  type: "Scale"
  bottom: "conv4_2/dw"
  top: "conv4_2/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu4_2/dw"
  type: "ReLU"
  bottom: "conv4_2/dw"
  top: "conv4_2/dw"
}
layer {
  name: "conv4_2/sep"
  type: "Convolution"
  bottom: "conv4_2/dw"
  top: "conv4_2/sep"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 360
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv4_2/sep/bn"
  type: "BatchNorm"
  bottom: "conv4_2/sep"
  top: "conv4_2/sep"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv4_2/sep/scale"
  type: "Scale"
  bottom: "conv4_2/sep"
  top: "conv4_2/sep"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu4_2/sep"
  type: "ReLU"
  bottom: "conv4_2/sep"
  top: "conv4_2/sep"
}
layer {
  name: "conv5_1/dw"
  type: "Convolution"
  bottom: "conv4_2/sep"
  top: "conv5_1/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 360
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 360
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv5_1/dw/bn"
  type: "BatchNorm"
  bottom: "conv5_1/dw"
  top: "conv5_1/dw"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv5_1/dw/scale"
  type: "Scale"
  bottom: "conv5_1/dw"
  top: "conv5_1/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu5_1/dw"
  type: "ReLU"
  bottom: "conv5_1/dw"
  top: "conv5_1/dw"
}
layer {
  name: "conv5_1/sep"
  type: "Convolution"
  bottom: "conv5_1/dw"
  top: "conv5_1/sep"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 328
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv5_1/sep/bn"
  type: "BatchNorm"
  bottom: "conv5_1/sep"
  top: "conv5_1/sep"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv5_1/sep/scale"
  type: "Scale"
  bottom: "conv5_1/sep"
  top: "conv5_1/sep"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu5_1/sep"
  type: "ReLU"
  bottom: "conv5_1/sep"
  top: "conv5_1/sep"
}
layer {
  name: "conv5_2/dw"
  type: "Convolution"
  bottom: "conv5_1/sep"
  top: "conv5_2/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 328
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 328
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv5_2/dw/bn"
  type: "BatchNorm"
  bottom: "conv5_2/dw"
  top: "conv5_2/dw"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv5_2/dw/scale"
  type: "Scale"
  bottom: "conv5_2/dw"
  top: "conv5_2/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu5_2/dw"
  type: "ReLU"
  bottom: "conv5_2/dw"
  top: "conv5_2/dw"
}
layer {
  name: "conv5_2/sep"
  type: "Convolution"
  bottom: "conv5_2/dw"
  top: "conv5_2/sep"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 304
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv5_2/sep/bn"
  type: "BatchNorm"
  bottom: "conv5_2/sep"
  top: "conv5_2/sep"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv5_2/sep/scale"
  type: "Scale"
  bottom: "conv5_2/sep"
  top: "conv5_2/sep"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu5_2/sep"
  type: "ReLU"
  bottom: "conv5_2/sep"
  top: "conv5_2/sep"
}
layer {
  name: "conv5_3/dw"
  type: "Convolution"
  bottom: "conv5_2/sep"
  top: "conv5_3/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 304
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 304
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv5_3/dw/bn"
  type: "BatchNorm"
  bottom: "conv5_3/dw"
  top: "conv5_3/dw"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv5_3/dw/scale"
  type: "Scale"
  bottom: "conv5_3/dw"
  top: "conv5_3/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu5_3/dw"
  type: "ReLU"
  bottom: "conv5_3/dw"
  top: "conv5_3/dw"
}
layer {
  name: "conv5_3/sep"
  type: "Convolution"
  bottom: "conv5_3/dw"
  top: "conv5_3/sep"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 248
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv5_3/sep/bn"
  type: "BatchNorm"
  bottom: "conv5_3/sep"
  top: "conv5_3/sep"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv5_3/sep/scale"
  type: "Scale"
  bottom: "conv5_3/sep"
  top: "conv5_3/sep"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu5_3/sep"
  type: "ReLU"
  bottom: "conv5_3/sep"
  top: "conv5_3/sep"
}
layer {
  name: "conv5_4/dw"
  type: "Convolution"
  bottom: "conv5_3/sep"
  top: "conv5_4/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 248
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 248
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv5_4/dw/bn"
  type: "BatchNorm"
  bottom: "conv5_4/dw"
  top: "conv5_4/dw"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv5_4/dw/scale"
  type: "Scale"
  bottom: "conv5_4/dw"
  top: "conv5_4/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu5_4/dw"
  type: "ReLU"
  bottom: "conv5_4/dw"
  top: "conv5_4/dw"
}
layer {
  name: "conv5_4/sep"
  type: "Convolution"
  bottom: "conv5_4/dw"
  top: "conv5_4/sep"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 224
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv5_4/sep/bn"
  type: "BatchNorm"
  bottom: "conv5_4/sep"
  top: "conv5_4/sep"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv5_4/sep/scale"
  type: "Scale"
  bottom: "conv5_4/sep"
  top: "conv5_4/sep"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu5_4/sep"
  type: "ReLU"
  bottom: "conv5_4/sep"
  top: "conv5_4/sep"
}
layer {
  name: "conv5_5/dw"
  type: "Convolution"
  bottom: "conv5_4/sep"
  top: "conv5_5/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 224
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 224
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv5_5/dw/bn"
  type: "BatchNorm"
  bottom: "conv5_5/dw"
  top: "conv5_5/dw"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv5_5/dw/scale"
  type: "Scale"
  bottom: "conv5_5/dw"
  top: "conv5_5/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu5_5/dw"
  type: "ReLU"
  bottom: "conv5_5/dw"
  top: "conv5_5/dw"
}
layer {
  name: "conv5_5/sep"
  type: "Convolution"
  bottom: "conv5_5/dw"
  top: "conv5_5/sep"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 184
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv5_5/sep/bn"
  type: "BatchNorm"
  bottom: "conv5_5/sep"
  top: "conv5_5/sep"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv5_5/sep/scale"
  type: "Scale"
  bottom: "conv5_5/sep"
  top: "conv5_5/sep"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu5_5/sep"
  type: "ReLU"
  bottom: "conv5_5/sep"
  top: "conv5_5/sep"
}
layer {
  name: "conv5_6/dw"
  type: "Convolution"
  bottom: "conv5_5/sep"
  top: "conv5_6/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 184
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 184
    stride: 2
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv5_6/dw/bn"
  type: "BatchNorm"
  bottom: "conv5_6/dw"
  top: "conv5_6/dw"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv5_6/dw/scale"
  type: "Scale"
  bottom: "conv5_6/dw"
  top: "conv5_6/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu5_6/dw"
  type: "ReLU"
  bottom: "conv5_6/dw"
  top: "conv5_6/dw"
}
layer {
  name: "conv5_6/sep"
  type: "Convolution"
  bottom: "conv5_6/dw"
  top: "conv5_6/sep"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 224
    bias_term: true
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv5_6/sep/bn"
  type: "BatchNorm"
  bottom: "conv5_6/sep"
  top: "conv5_6/sep"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv5_6/sep/scale"
  type: "Scale"
  bottom: "conv5_6/sep"
  top: "conv5_6/sep"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu5_6/sep"
  type: "ReLU"
  bottom: "conv5_6/sep"
  top: "conv5_6/sep"
}
layer {
  name: "conv6/dw"
  type: "Convolution"
  bottom: "conv5_6/sep"
  top: "conv6/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 224
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 224
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv6/dw/bn"
  type: "BatchNorm"
  bottom: "conv6/dw"
  top: "conv6/dw"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv6/dw/scale"
  type: "Scale"
  bottom: "conv6/dw"
  top: "conv6/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu6/dw"
  type: "ReLU"
  bottom: "conv6/dw"
  top: "conv6/dw"
}
layer {
  name: "conv6/sep"
  type: "Convolution"
  bottom: "conv6/dw"
  top: "conv6/sep"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv6/sep/bn"
  type: "BatchNorm"
  bottom: "conv6/sep"
  top: "conv6/sep"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv6/sep/scale"
  type: "Scale"
  bottom: "conv6/sep"
  top: "conv6/sep"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu6/sep"
  type: "ReLU"
  bottom: "conv6/sep"
  top: "conv6/sep"
}
layer {
  name: "conv6_1"
  type: "Convolution"
  bottom: "conv6/sep"
  top: "conv6_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 120
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv6_1/bn"
  type: "BatchNorm"
  bottom: "conv6_1"
  top: "conv6_1"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv6_1/bn/scale"
  type: "Scale"
  bottom: "conv6_1"
  top: "conv6_1"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "relu6_1"
  type: "ReLU"
  bottom: "conv6_1"
  top: "conv6_1"
}
layer {
  name: "conv6_2/dw"
  type: "Convolution"
  bottom: "conv6_1"
  top: "conv6_2/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 120
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 120
    stride: 2
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv6_2/dw/bn"
  type: "BatchNorm"
  bottom: "conv6_2/dw"
  top: "conv6_2/dw"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv6_2/dw/bn/scale"
  type: "Scale"
  bottom: "conv6_2/dw"
  top: "conv6_2/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "relu6_2/dw"
  type: "ReLU"
  bottom: "conv6_2/dw"
  top: "conv6_2/dw"
}
layer {
  name: "conv6_2_new"
  type: "Convolution"
  bottom: "conv6_2/dw"
  top: "conv6_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 152
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv6_2/bn"
  type: "BatchNorm"
  bottom: "conv6_2"
  top: "conv6_2"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv6_2/bn/scale"
  type: "Scale"
  bottom: "conv6_2"
  top: "conv6_2"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "relu6_2"
  type: "ReLU"
  bottom: "conv6_2"
  top: "conv6_2"
}
layer {
  name: "conv7_1"
  type: "Convolution"
  bottom: "conv6_2"
  top: "conv7_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 112
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv7_1/bn"
  type: "BatchNorm"
  bottom: "conv7_1"
  top: "conv7_1"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv7_1/bn/scale"
  type: "Scale"
  bottom: "conv7_1"
  top: "conv7_1"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "relu7_1"
  type: "ReLU"
  bottom: "conv7_1"
  top: "conv7_1"
}
layer {
  name: "conv7_2/dw"
  type: "Convolution"
  bottom: "conv7_1"
  top: "conv7_2/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 112
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 112
    stride: 2
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv7_2/dw/bn"
  type: "BatchNorm"
  bottom: "conv7_2/dw"
  top: "conv7_2/dw"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv7_2/dw/bn/scale"
  type: "Scale"
  bottom: "conv7_2/dw"
  top: "conv7_2/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "relu7_2/dw"
  type: "ReLU"
  bottom: "conv7_2/dw"
  top: "conv7_2/dw"
}
layer {
  name: "conv7_2_new"
  type: "Convolution"
  bottom: "conv7_2/dw"
  top: "conv7_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 168
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv7_2/bn"
  type: "BatchNorm"
  bottom: "conv7_2"
  top: "conv7_2"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv7_2/bn/scale"
  type: "Scale"
  bottom: "conv7_2"
  top: "conv7_2"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "relu7_2"
  type: "ReLU"
  bottom: "conv7_2"
  top: "conv7_2"
}
layer {
  name: "conv8_1"
  type: "Convolution"
  bottom: "conv7_2"
  top: "conv8_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 120
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv8_1/bn"
  type: "BatchNorm"
  bottom: "conv8_1"
  top: "conv8_1"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv8_1/bn/scale"
  type: "Scale"
  bottom: "conv8_1"
  top: "conv8_1"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "relu8_1"
  type: "ReLU"
  bottom: "conv8_1"
  top: "conv8_1"
}
layer {
  name: "conv8_2/dw"
  type: "Convolution"
  bottom: "conv8_1"
  top: "conv8_2/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 120
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 120
    stride: 2
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv8_2/dw/bn"
  type: "BatchNorm"
  bottom: "conv8_2/dw"
  top: "conv8_2/dw"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv8_2/dw/bn/scale"
  type: "Scale"
  bottom: "conv8_2/dw"
  top: "conv8_2/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "relu8_2/dw"
  type: "ReLU"
  bottom: "conv8_2/dw"
  top: "conv8_2/dw"
}
layer {
  name: "conv8_2_new"
  type: "Convolution"
  bottom: "conv8_2/dw"
  top: "conv8_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 200
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv8_2/bn"
  type: "BatchNorm"
  bottom: "conv8_2"
  top: "conv8_2"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv8_2/bn/scale"
  type: "Scale"
  bottom: "conv8_2"
  top: "conv8_2"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "relu8_2"
  type: "ReLU"
  bottom: "conv8_2"
  top: "conv8_2"
}
layer {
  name: "conv9_1"
  type: "Convolution"
  bottom: "conv8_2"
  top: "conv9_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv9_1/bn"
  type: "BatchNorm"
  bottom: "conv9_1"
  top: "conv9_1"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv9_1/bn/scale"
  type: "Scale"
  bottom: "conv9_1"
  top: "conv9_1"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "relu9_1"
  type: "ReLU"
  bottom: "conv9_1"
  top: "conv9_1"
}
layer {
  name: "conv9_2/dw"
  type: "Convolution"
  bottom: "conv9_1"
  top: "conv9_2/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 64
    stride: 2
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv9_2/dw/bn"
  type: "BatchNorm"
  bottom: "conv9_2/dw"
  top: "conv9_2/dw"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv9_2/dw/bn/scale"
  type: "Scale"
  bottom: "conv9_2/dw"
  top: "conv9_2/dw"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "relu9_2/dw"
  type: "ReLU"
  bottom: "conv9_2/dw"
  top: "conv9_2/dw"
}
layer {
  name: "conv9_2_new"
  type: "Convolution"
  bottom: "conv9_2/dw"
  top: "conv9_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv9_2/bn"
  type: "BatchNorm"
  bottom: "conv9_2"
  top: "conv9_2"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "conv9_2/bn/scale"
  type: "Scale"
  bottom: "conv9_2"
  top: "conv9_2"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1.0
    }
    bias_term: true
    bias_filler {
      value: 0.0
    }
  }
}
layer {
  name: "relu9_2"
  type: "ReLU"
  bottom: "conv9_2"
  top: "conv9_2"
}
layer {
  name: "conv5_5/sep/reduce"
  type: "Convolution"
  bottom: "conv5_5/sep"
  top: "conv5_5/sep/reduced"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 16
    bias_term: true
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv5_5/sep/reduced/relu"
  type: "ReLU"
  bottom: "conv5_5/sep/reduced"
  top: "conv5_5/sep/reduced"
}
layer {
  name: "conv6/sep/reduce"
  type: "Convolution"
  bottom: "conv6/sep"
  top: "conv6/sep/reduced"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 16
    bias_term: true
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv6/sep/reduced/relu"
  type: "ReLU"
  bottom: "conv6/sep/reduced"
  top: "conv6/sep/reduced"
}
layer {
  name: "conv6_2/reduce"
  type: "Convolution"
  bottom: "conv6_2"
  top: "conv6_2/reduced"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 16
    bias_term: true
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv6_2/reduced/relu"
  type: "ReLU"
  bottom: "conv6_2/reduced"
  top: "conv6_2/reduced"
}
layer {
  name: "conv7_2/reduce"
  type: "Convolution"
  bottom: "conv7_2"
  top: "conv7_2_reduced"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 16
    bias_term: true
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv7_2_reduced/relu"
  type: "ReLU"
  bottom: "conv7_2_reduced"
  top: "conv7_2_reduced"
}
layer {
  name: "conv8_2/reduce"
  type: "Convolution"
  bottom: "conv8_2"
  top: "conv8_2_reduced"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 16
    bias_term: true
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv8_2_reduced/relu"
  type: "ReLU"
  bottom: "conv8_2_reduced"
  top: "conv8_2_reduced"
}
layer {
  name: "conv9_2/reduce"
  type: "Convolution"
  bottom: "conv9_2"
  top: "conv9_2_reduced"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 16
    bias_term: true
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv9_2_reduced/relu"
  type: "ReLU"
  bottom: "conv9_2_reduced"
  top: "conv9_2_reduced"
}
layer {
  name: "conv4_3_0_norm_mbox_loc"
  type: "Convolution"
  bottom: "conv5_5/sep"
  top: "conv4_3_0_norm_mbox_loc"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 16
    bias_term: true
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv4_3_0_norm_mbox_loc_perm"
  type: "Permute"
  bottom: "conv4_3_0_norm_mbox_loc"
  top: "conv4_3_0_norm_mbox_loc_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "conv4_3_0_norm_mbox_loc_flat"
  type: "Flatten"
  bottom: "conv4_3_0_norm_mbox_loc_perm"
  top: "conv4_3_0_norm_mbox_loc_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "pre_conv4_3_0_norm_mbox_conf_64"
  type: "Convolution"
  bottom: "conv5_5/sep/reduced"
  top: "pre_conv4_3_0_norm_mbox_conf_64"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 16
    bias_term: true
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "pre_conv4_3_0_norm_mbox_conf/bn"
  type: "BatchNorm"
  bottom: "pre_conv4_3_0_norm_mbox_conf_64"
  top: "pre_conv4_3_0_norm_mbox_conf_64"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "pre_conv4_3_0_norm_mbox_conf/scale"
  type: "Scale"
  bottom: "pre_conv4_3_0_norm_mbox_conf_64"
  top: "pre_conv4_3_0_norm_mbox_conf_64"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "pre_conv4_3_0_norm_mbox_conf/relu"
  type: "ReLU"
  bottom: "pre_conv4_3_0_norm_mbox_conf_64"
  top: "pre_conv4_3_0_norm_mbox_conf_64"
}
layer {
  name: "conv4_3_0_norm_mbox_conf_64"
  type: "Convolution"
  bottom: "pre_conv4_3_0_norm_mbox_conf_64"
  top: "conv4_3_0_norm_mbox_conf_64"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 8
    bias_term: true
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv4_3_0_norm_mbox_conf_perm"
  type: "Permute"
  bottom: "conv4_3_0_norm_mbox_conf_64"
  top: "conv4_3_0_norm_mbox_conf_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "conv4_3_0_norm_mbox_conf_flat"
  type: "Flatten"
  bottom: "conv4_3_0_norm_mbox_conf_perm"
  top: "conv4_3_0_norm_mbox_conf_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "conv4_3_0_norm_mbox_priorbox"
  type: "PriorBox"
  bottom: "conv5_5/sep"
  bottom: "data"
  top: "conv4_3_0_norm_mbox_priorbox"
  prior_box_param {
    min_size: 16.0
    max_size: 38.4
    aspect_ratio: 2.0
    flip: true
    clip: false
    variance: 0.1
    variance: 0.1
    variance: 0.2
    variance: 0.2
    step: 16.0
    offset: 0.5
  }
}
layer {
  name: "conv4_3_norm_mbox_loc"
  type: "Convolution"
  bottom: "conv5_5/sep"
  top: "conv4_3_norm_mbox_loc"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 16
    bias_term: true
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv4_3_norm_mbox_loc_perm"
  type: "Permute"
  bottom: "conv4_3_norm_mbox_loc"
  top: "conv4_3_norm_mbox_loc_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "conv4_3_norm_mbox_loc_flat"
  type: "Flatten"
  bottom: "conv4_3_norm_mbox_loc_perm"
  top: "conv4_3_norm_mbox_loc_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "pre_conv4_3_norm_mbox_conf_64"
  type: "Convolution"
  bottom: "conv5_5/sep/reduced"
  top: "pre_conv4_3_norm_mbox_conf_64"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 16
    bias_term: true
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "pre_conv4_3_norm_mbox_conf/bn"
  type: "BatchNorm"
  bottom: "pre_conv4_3_norm_mbox_conf_64"
  top: "pre_conv4_3_norm_mbox_conf_64"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "pre_conv4_3_norm_mbox_conf/scale"
  type: "Scale"
  bottom: "pre_conv4_3_norm_mbox_conf_64"
  top: "pre_conv4_3_norm_mbox_conf_64"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "pre_conv4_3_norm_mbox_conf/relu"
  type: "ReLU"
  bottom: "pre_conv4_3_norm_mbox_conf_64"
  top: "pre_conv4_3_norm_mbox_conf_64"
}
layer {
  name: "conv4_3_norm_mbox_conf_64"
  type: "Convolution"
  bottom: "pre_conv4_3_norm_mbox_conf_64"
  top: "conv4_3_norm_mbox_conf_64"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 8
    bias_term: true
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv4_3_norm_mbox_conf_perm"
  type: "Permute"
  bottom: "conv4_3_norm_mbox_conf_64"
  top: "conv4_3_norm_mbox_conf_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "conv4_3_norm_mbox_conf_flat"
  type: "Flatten"
  bottom: "conv4_3_norm_mbox_conf_perm"
  top: "conv4_3_norm_mbox_conf_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "conv4_3_norm_mbox_priorbox"
  type: "PriorBox"
  bottom: "conv5_5/sep"
  bottom: "data"
  top: "conv4_3_norm_mbox_priorbox"
  prior_box_param {
    min_size: 38.4
    max_size: 76.8
    aspect_ratio: 2.0
    flip: true
    clip: false
    variance: 0.1
    variance: 0.1
    variance: 0.2
    variance: 0.2
    step: 16.0
    offset: 0.5
  }
}
layer {
  name: "fc7_mbox_loc"
  type: "Convolution"
  bottom: "conv6/sep"
  top: "fc7_mbox_loc"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 24
    bias_term: true
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "fc7_mbox_loc_perm"
  type: "Permute"
  bottom: "fc7_mbox_loc"
  top: "fc7_mbox_loc_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "fc7_mbox_loc_flat"
  type: "Flatten"
  bottom: "fc7_mbox_loc_perm"
  top: "fc7_mbox_loc_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "pre_fc7_mbox_conf_64"
  type: "Convolution"
  bottom: "conv6/sep/reduced"
  top: "pre_fc7_mbox_conf_64"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 16
    bias_term: true
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "pre_fc7_mbox_conf/bn"
  type: "BatchNorm"
  bottom: "pre_fc7_mbox_conf_64"
  top: "pre_fc7_mbox_conf_64"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "pre_fc7_mbox_conf/scale"
  type: "Scale"
  bottom: "pre_fc7_mbox_conf_64"
  top: "pre_fc7_mbox_conf_64"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "pre_fc7_mbox_conf/relu"
  type: "ReLU"
  bottom: "pre_fc7_mbox_conf_64"
  top: "pre_fc7_mbox_conf_64"
}
layer {
  name: "fc7_mbox_conf_64"
  type: "Convolution"
  bottom: "pre_fc7_mbox_conf_64"
  top: "fc7_mbox_conf_64"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 12
    bias_term: true
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "fc7_mbox_conf_perm"
  type: "Permute"
  bottom: "fc7_mbox_conf_64"
  top: "fc7_mbox_conf_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "fc7_mbox_conf_flat"
  type: "Flatten"
  bottom: "fc7_mbox_conf_perm"
  top: "fc7_mbox_conf_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "fc7_mbox_priorbox"
  type: "PriorBox"
  bottom: "conv6/sep"
  bottom: "data"
  top: "fc7_mbox_priorbox"
  prior_box_param {
    min_size: 76.8
    max_size: 142.08
    aspect_ratio: 2.0
    aspect_ratio: 3.0
    flip: true
    clip: false
    variance: 0.1
    variance: 0.1
    variance: 0.2
    variance: 0.2
    step: 32.0
    offset: 0.5
  }
}
layer {
  name: "conv6_2_mbox_loc"
  type: "Convolution"
  bottom: "conv6_2"
  top: "conv6_2_mbox_loc"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 24
    bias_term: true
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv6_2_mbox_loc_perm"
  type: "Permute"
  bottom: "conv6_2_mbox_loc"
  top: "conv6_2_mbox_loc_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "conv6_2_mbox_loc_flat"
  type: "Flatten"
  bottom: "conv6_2_mbox_loc_perm"
  top: "conv6_2_mbox_loc_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "pre_conv6_2_mbox_conf_64"
  type: "Convolution"
  bottom: "conv6_2/reduced"
  top: "pre_conv6_2_mbox_conf_64"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 16
    bias_term: true
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "pre_conv6_2_mbox_conf/bn"
  type: "BatchNorm"
  bottom: "pre_conv6_2_mbox_conf_64"
  top: "pre_conv6_2_mbox_conf_64"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "pre_conv6_2_mbox_conf/scale"
  type: "Scale"
  bottom: "pre_conv6_2_mbox_conf_64"
  top: "pre_conv6_2_mbox_conf_64"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "pre_conv6_2_mbox_conf/relu"
  type: "ReLU"
  bottom: "pre_conv6_2_mbox_conf_64"
  top: "pre_conv6_2_mbox_conf_64"
}
layer {
  name: "conv6_2_mbox_conf_64"
  type: "Convolution"
  bottom: "pre_conv6_2_mbox_conf_64"
  top: "conv6_2_mbox_conf_64"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 12
    bias_term: true
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv6_2_mbox_conf_perm"
  type: "Permute"
  bottom: "conv6_2_mbox_conf_64"
  top: "conv6_2_mbox_conf_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "conv6_2_mbox_conf_flat"
  type: "Flatten"
  bottom: "conv6_2_mbox_conf_perm"
  top: "conv6_2_mbox_conf_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "conv6_2_mbox_priorbox"
  type: "PriorBox"
  bottom: "conv6_2"
  bottom: "data"
  top: "conv6_2_mbox_priorbox"
  prior_box_param {
    min_size: 142.08
    max_size: 207.36
    aspect_ratio: 2.0
    aspect_ratio: 3.0
    flip: true
    clip: false
    variance: 0.1
    variance: 0.1
    variance: 0.2
    variance: 0.2
    step: 64.0
    offset: 0.5
  }
}
layer {
  name: "conv7_2_mbox_loc"
  type: "Convolution"
  bottom: "conv7_2"
  top: "conv7_2_mbox_loc"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 24
    bias_term: true
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv7_2_mbox_loc_perm"
  type: "Permute"
  bottom: "conv7_2_mbox_loc"
  top: "conv7_2_mbox_loc_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "conv7_2_mbox_loc_flat"
  type: "Flatten"
  bottom: "conv7_2_mbox_loc_perm"
  top: "conv7_2_mbox_loc_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "pre_conv7_2_mbox_conf_64"
  type: "Convolution"
  bottom: "conv7_2_reduced"
  top: "pre_conv7_2_mbox_conf_64"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 16
    bias_term: true
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "pre_conv7_2_mbox_conf/bn"
  type: "BatchNorm"
  bottom: "pre_conv7_2_mbox_conf_64"
  top: "pre_conv7_2_mbox_conf_64"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "pre_conv7_2_mbox_conf/scale"
  type: "Scale"
  bottom: "pre_conv7_2_mbox_conf_64"
  top: "pre_conv7_2_mbox_conf_64"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "pre_conv7_2_mbox_conf/relu"
  type: "ReLU"
  bottom: "pre_conv7_2_mbox_conf_64"
  top: "pre_conv7_2_mbox_conf_64"
}
layer {
  name: "conv7_2_mbox_conf_64"
  type: "Convolution"
  bottom: "pre_conv7_2_mbox_conf_64"
  top: "conv7_2_mbox_conf_64"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 12
    bias_term: true
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv7_2_mbox_conf_perm"
  type: "Permute"
  bottom: "conv7_2_mbox_conf_64"
  top: "conv7_2_mbox_conf_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "conv7_2_mbox_conf_flat"
  type: "Flatten"
  bottom: "conv7_2_mbox_conf_perm"
  top: "conv7_2_mbox_conf_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "conv7_2_mbox_priorbox"
  type: "PriorBox"
  bottom: "conv7_2"
  bottom: "data"
  top: "conv7_2_mbox_priorbox"
  prior_box_param {
    min_size: 207.36
    max_size: 272.64
    aspect_ratio: 2.0
    aspect_ratio: 3.0
    flip: true
    clip: false
    variance: 0.1
    variance: 0.1
    variance: 0.2
    variance: 0.2
    step: 100.0
    offset: 0.5
  }
}
layer {
  name: "conv8_2_mbox_loc"
  type: "Convolution"
  bottom: "conv8_2"
  top: "conv8_2_mbox_loc"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 16
    bias_term: true
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv8_2_mbox_loc_perm"
  type: "Permute"
  bottom: "conv8_2_mbox_loc"
  top: "conv8_2_mbox_loc_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "conv8_2_mbox_loc_flat"
  type: "Flatten"
  bottom: "conv8_2_mbox_loc_perm"
  top: "conv8_2_mbox_loc_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "pre_conv8_2_mbox_conf_64"
  type: "Convolution"
  bottom: "conv8_2_reduced"
  top: "pre_conv8_2_mbox_conf_64"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 16
    bias_term: true
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "pre_conv8_2_mbox_conf/bn"
  type: "BatchNorm"
  bottom: "pre_conv8_2_mbox_conf_64"
  top: "pre_conv8_2_mbox_conf_64"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "pre_conv8_2_mbox_conf/scale"
  type: "Scale"
  bottom: "pre_conv8_2_mbox_conf_64"
  top: "pre_conv8_2_mbox_conf_64"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "pre_conv8_2_mbox_conf/relu"
  type: "ReLU"
  bottom: "pre_conv8_2_mbox_conf_64"
  top: "pre_conv8_2_mbox_conf_64"
}
layer {
  name: "conv8_2_mbox_conf_64"
  type: "Convolution"
  bottom: "pre_conv8_2_mbox_conf_64"
  top: "conv8_2_mbox_conf_64"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 8
    bias_term: true
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv8_2_mbox_conf_perm"
  type: "Permute"
  bottom: "conv8_2_mbox_conf_64"
  top: "conv8_2_mbox_conf_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "conv8_2_mbox_conf_flat"
  type: "Flatten"
  bottom: "conv8_2_mbox_conf_perm"
  top: "conv8_2_mbox_conf_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "conv8_2_mbox_priorbox"
  type: "PriorBox"
  bottom: "conv8_2"
  bottom: "data"
  top: "conv8_2_mbox_priorbox"
  prior_box_param {
    min_size: 272.64
    max_size: 337.92
    aspect_ratio: 2.0
    flip: true
    clip: false
    variance: 0.1
    variance: 0.1
    variance: 0.2
    variance: 0.2
    step: 150.0
    offset: 0.5
  }
}
layer {
  name: "conv9_2_mbox_loc"
  type: "Convolution"
  bottom: "conv9_2"
  top: "conv9_2_mbox_loc"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 16
    bias_term: true
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv9_2_mbox_loc_perm"
  type: "Permute"
  bottom: "conv9_2_mbox_loc"
  top: "conv9_2_mbox_loc_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "conv9_2_mbox_loc_flat"
  type: "Flatten"
  bottom: "conv9_2_mbox_loc_perm"
  top: "conv9_2_mbox_loc_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "pre_conv9_2_mbox_conf_64"
  type: "Convolution"
  bottom: "conv9_2_reduced"
  top: "pre_conv9_2_mbox_conf_64"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 16
    bias_term: true
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "pre_conv9_2_mbox_conf/bn"
  type: "BatchNorm"
  bottom: "pre_conv9_2_mbox_conf_64"
  top: "pre_conv9_2_mbox_conf_64"
  batch_norm_param {
    moving_average_fraction: 0.9997
    eps: 0.001
  }
}
layer {
  name: "pre_conv9_2_mbox_conf/scale"
  type: "Scale"
  bottom: "pre_conv9_2_mbox_conf_64"
  top: "pre_conv9_2_mbox_conf_64"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "pre_conv9_2_mbox_conf/relu"
  type: "ReLU"
  bottom: "pre_conv9_2_mbox_conf_64"
  top: "pre_conv9_2_mbox_conf_64"
}
layer {
  name: "conv9_2_mbox_conf_64"
  type: "Convolution"
  bottom: "pre_conv9_2_mbox_conf_64"
  top: "conv9_2_mbox_conf_64"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 8
    bias_term: true
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv9_2_mbox_conf_perm"
  type: "Permute"
  bottom: "conv9_2_mbox_conf_64"
  top: "conv9_2_mbox_conf_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "conv9_2_mbox_conf_flat"
  type: "Flatten"
  bottom: "conv9_2_mbox_conf_perm"
  top: "conv9_2_mbox_conf_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "conv9_2_mbox_priorbox"
  type: "PriorBox"
  bottom: "conv9_2"
  bottom: "data"
  top: "conv9_2_mbox_priorbox"
  prior_box_param {
    min_size: 337.92
    max_size: 403.2
    aspect_ratio: 2.0
    flip: true
    clip: false
    variance: 0.1
    variance: 0.1
    variance: 0.2
    variance: 0.2
    step: 300.0
    offset: 0.5
  }
}
layer {
  name: "mbox_loc"
  type: "Concat"
  bottom: "conv4_3_0_norm_mbox_loc_flat"
  bottom: "conv4_3_norm_mbox_loc_flat"
  bottom: "fc7_mbox_loc_flat"
  bottom: "conv6_2_mbox_loc_flat"
  bottom: "conv7_2_mbox_loc_flat"
  bottom: "conv8_2_mbox_loc_flat"
  bottom: "conv9_2_mbox_loc_flat"
  top: "mbox_loc"
  concat_param {
    axis: 1
  }
}
layer {
  name: "mbox_conf_16"
  type: "Concat"
  bottom: "conv4_3_0_norm_mbox_conf_flat"
  bottom: "conv4_3_norm_mbox_conf_flat"
  bottom: "fc7_mbox_conf_flat"
  bottom: "conv6_2_mbox_conf_flat"
  bottom: "conv7_2_mbox_conf_flat"
  bottom: "conv8_2_mbox_conf_flat"
  bottom: "conv9_2_mbox_conf_flat"
  top: "mbox_conf_16"
  concat_param {
    axis: 1
  }
}
layer {
  name: "mbox_priorbox"
  type: "Concat"
  bottom: "conv4_3_0_norm_mbox_priorbox"
  bottom: "conv4_3_norm_mbox_priorbox"
  bottom: "fc7_mbox_priorbox"
  bottom: "conv6_2_mbox_priorbox"
  bottom: "conv7_2_mbox_priorbox"
  bottom: "conv8_2_mbox_priorbox"
  bottom: "conv9_2_mbox_priorbox"
  top: "mbox_priorbox"
  concat_param {
    axis: 2
  }
}
layer {
  name: "mbox_conf_reshape"
  type: "Reshape"
  bottom: "mbox_conf_16"
  top: "mbox_conf_reshape"
  reshape_param {
    shape {
      dim: 0
      dim: -1
      dim: 2
    }
  }
}
layer {
  name: "mbox_conf_softmax"
  type: "Softmax"
  bottom: "mbox_conf_reshape"
  top: "mbox_conf_softmax"
  softmax_param {
    axis: 2
  }
}
layer {
  name: "mbox_conf_flatten"
  type: "Flatten"
  bottom: "mbox_conf_softmax"
  top: "mbox_conf_flatten"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "detection_out"
  type: "DetectionOutput"
  bottom: "mbox_loc"
  bottom: "mbox_conf_flatten"
  bottom: "mbox_priorbox"
  top: "detection_out"
  include {
    phase: TEST
  }
  detection_output_param {
    num_classes: 2
    share_location: true
    background_label_id: 0
    nms_param {
      nms_threshold: 0.45
      top_k: 400
    }
    code_type: CENTER_SIZE
    keep_top_k: 200
    confidence_threshold: 0.01
  }
}