layer {
  name: "data"
  type: "Input"
  top: "data"
  input_param { shape: { dim:  dim:  dim:  dim:  } }
}

layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data"
  top: "conv1"
  convolution_param {
    num_output:
    kernel_size:
    stride:
    pad:
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "bn_conv1"
  type: "BatchNorm"
  bottom: "conv1"
  top: "conv1"
  batch_norm_param {
    use_global_stats: true
  }
  include {
	phase: TEST
  }
}
layer {
  name: "scale_conv1"
  type: "Scale"
  bottom: "conv1"
  top: "conv1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_conv1"
  type: "ReLU"
  bottom: "conv1"
  top: "conv1"
}
layer {
  name: "conv2"
  type: "Convolution"
  bottom: "conv1"
  top: "conv2"
  convolution_param {
    num_output:
    kernel_size:
    pad:
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "bn_conv2"
  type: "BatchNorm"
  bottom: "conv2"
  top: "conv2"
  batch_norm_param {
    use_global_stats: true
  }
  include {
	phase: TEST
  }
}
layer {
  name: "scale_conv2"
  type: "Scale"
  bottom: "conv2"
  top: "conv2"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_conv2"
  type: "ReLU"
  bottom: "conv2"
  top: "conv2"
}
layer {
  name: "pool2"
  type: "Pooling"
  bottom: "conv2"
  top: "pool2"
  pooling_param {
    pool: MAX
    kernel_size:
    stride:
  }
}
layer {
  name: "conv3"
  type: "Convolution"
  bottom: "pool2"
  top: "conv3"
  convolution_param {
    num_output:
    kernel_size:
    pad:
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "bn_conv3"
  type: "BatchNorm"
  bottom: "conv3"
  top: "conv3"
  batch_norm_param {
    use_global_stats: true
  }
  include {
	phase: TEST
  }
}
layer {
  name: "scale_conv3"
  type: "Scale"
  bottom: "conv3"
  top: "conv3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_conv3"
  type: "ReLU"
  bottom: "conv3"
  top: "conv3"
}
layer {
  name: "conv4"
  type: "Convolution"
  bottom: "conv3"
  top: "conv4"
  convolution_param {
    num_output:
    kernel_size:
    pad:
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "bn_conv4"
  type: "BatchNorm"
  bottom: "conv4"
  top: "conv4"
  batch_norm_param {
    use_global_stats: true
  }
  include {
	phase: TEST
  }
}
layer {
  name: "scale_conv4"
  type: "Scale"
  bottom: "conv4"
  top: "conv4"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_conv4"
  type: "ReLU"
  bottom: "conv4"
  top: "conv4"
}
layer {
  name: "conv5"
  type: "Convolution"
  bottom: "conv4"
  top: "conv5"
  convolution_param {
    num_output:
    kernel_size: 3
    pad: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "bn_conv5"
  type: "BatchNorm"
  bottom: "conv5"
  top: "conv5"
  batch_norm_param {
    use_global_stats: true
  }
  include {
	phase: TEST
  }
}
layer {
  name: "scale_conv5"
  type: "Scale"
  bottom: "conv5"
  top: "conv5"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_conv5"
  type: "ReLU"
  bottom: "conv5"
  top: "conv5"
}
layer {
  name: "pool5"
  type: "Pooling"
  bottom: "conv5"
  top: "pool5"
  pooling_param {
    pool: MAX
    kernel_size:
    stride:
  }
}
layer {
  name: "conv6"
  type: "Convolution"
  bottom: "pool5"
  top: "conv6"
  convolution_param {
    num_output:
    kernel_size:
    pad:
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "bn_conv6"
  type: "BatchNorm"
  bottom: "conv6"
  top: "conv6"
  batch_norm_param {
    use_global_stats: true
  }
  include {
	phase: TEST
  }
}
layer {
  name: "scale_conv6"
  type: "Scale"
  bottom: "conv6"
  top: "conv6"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_conv6"
  type: "ReLU"
  bottom: "conv6"
  top: "conv6"
}
layer {
  name: "conv7"
  type: "Convolution"
  bottom: "conv6"
  top: "conv7"
  convolution_param {
    num_output:
    kernel_size:
    pad:
    weight_filler {
      type: "xavier"
    }
  }
}

layer {
  name: "bn_conv7"
  type: "BatchNorm"
  bottom: "conv7"
  top: "conv7"
  batch_norm_param {
    use_global_stats: true
  }
  include {
	phase: TEST
  }
}
layer {
  name: "scale_conv7"
  type: "Scale"
  bottom: "conv7"
  top: "conv7"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_con7"
  type: "ReLU"
  bottom: "conv7"
  top: "conv7"
}
layer {
  name: "conv8"
  type: "Convolution"
  bottom: "conv7"
  top: "conv8"
  convolution_param {
    num_output:
    kernel_size:
    pad:
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "bn_conv8"
  type: "BatchNorm"
  bottom: "conv8"
  top: "conv8"
  batch_norm_param {
    use_global_stats: true
  }
  include {
	phase: TEST
  }
}
layer {
  name: "scale_conv8"
  type: "Scale"
  bottom: "conv8"
  top: "conv8"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_conv8"
  type: "ReLU"
  bottom: "conv8"
  top: "conv8"
}
layer {
  name: "pool8"
  type: "Pooling"
  bottom: "conv8"
  top: "pool8"
  pooling_param {
    pool: MAX
    kernel_size:
    stride:
  }
}
layer {
  name: "conv9"
  type: "Convolution"
  bottom: "pool8"
  top: "conv9"
  convolution_param {
    num_output:
    kernel_size:
    pad:
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "bn_conv9"
  type: "BatchNorm"
  bottom: "conv9"
  top: "conv9"
  batch_norm_param {
    use_global_stats: true
  }
  include {
	phase: TEST
  }
}
layer {
  name: "scale_conv9"
  type: "Scale"
  bottom: "conv9"
  top: "conv9"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_conv9"
  type: "ReLU"
  bottom: "conv9"
  top: "conv9"
}
layer {
  name: "conv10"
  type: "Convolution"
  bottom: "conv9"
  top: "conv10"
  convolution_param {
    num_output:
    kernel_size:
    pad: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "bn_conv10"
  type: "BatchNorm"
  bottom: "conv10"
  top: "conv10"
  batch_norm_param {
    use_global_stats: true
  }
  include {
	phase: TEST
  }
}
layer {
  name: "scale_conv10"
  type: "Scale"
  bottom: "conv10"
  top: "conv10"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_con10"
  type: "ReLU"
  bottom: "conv10"
  top: "conv10"
}
layer {
  name: "conv11"
  type: "Convolution"
  bottom: "conv10"
  top: "conv11"
  convolution_param {
    num_output:
    kernel_size:
    pad:
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "bn_conv11"
  type: "BatchNorm"
  bottom: "conv11"
  top: "conv11"
  batch_norm_param {
    use_global_stats: true
  }
  include {
	phase: TEST
  }
}
layer {
  name: "scale_conv11"
  type: "Scale"
  bottom: "conv11"
  top: "conv11"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_conv11"
  type: "ReLU"
  bottom: "conv11"
  top: "conv11"
}
layer {
  name: "pool11"
  type: "Pooling"
  bottom: "conv11"
  top: "pool11"
  pooling_param {
    pool: MAX
    kernel_size:
    stride:
  }
}
layer {
  name: "conv12"
  type: "Convolution"
  bottom: "pool11"
  top: "conv12"
  convolution_param {
    num_output:
    kernel_size:
    pad:
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "bn_conv12"
  type: "BatchNorm"
  bottom: "conv12"
  top: "conv12"
  batch_norm_param {
    use_global_stats: true
  }
  include {
	phase: TEST
  }
}
layer {
  name: "scale_conv12"
  type: "Scale"
  bottom: "conv12"
  top: "conv12"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_conv12"
  type: "ReLU"
  bottom: "conv12"
  top: "conv12"
}
layer {
  name: "conv13"
  type: "Convolution"
  bottom: "conv12"
  top: "conv13"
  convolution_param {
    num_output:
    kernel_size:
    pad:
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "bn_conv13"
  type: "BatchNorm"
  bottom: "conv13"
  top: "conv13"
  batch_norm_param {
    use_global_stats: true
  }
  include {
	phase: TEST
  }
}
layer {
  name: "scale_conv13"
  type: "Scale"
  bottom: "conv13"
  top: "conv13"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_con13"
  type: "ReLU"
  bottom: "conv13"
  top: "conv13"
}
layer {
  name: "conv14"
  type: "Convolution"
  bottom: "conv13"
  top: "conv14"
  convolution_param {
    num_output:
    kernel_size:
    pad:
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "bn_conv14"
  type: "BatchNorm"
  bottom: "conv14"
  top: "conv14"
  batch_norm_param {
    use_global_stats: true
  }
  include {
	phase: TEST
  }
}
layer {
  name: "scale_conv14"
  type: "Scale"
  bottom: "conv14"
  top: "conv14"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_conv14"
  type: "ReLU"
  bottom: "conv14"
  top: "conv14"
}

layer {
  name: "conv_final"
  type: "Convolution"
  bottom: "conv14"
  top: "conv_final"
  convolution_param {
    num_output:
    kernel_size:
    weight_filler {
      type: "gaussian"
      mean:
      std:
    }
  }
}
layer {
  name: "relu_conv_final"
  type: "ReLU"
  bottom: "conv_final"
  top: "conv_final"
}
layer {
  name: "pool_final"
  type: "Pooling"
  bottom: "conv_final"
  top: "pool_final"
  pooling_param {
    pool: AVE
    global_pooling: true
  }
}