layer {
  name: "mdata"
  type: "Input"
  top: "mdata"
  input_param{ shape: {dim :64 dim: 3 dim: 5 dim: 5}}
  transform_param {
    mirror: true
    mean_value: 40.706
    mean_value: 35.677
    mean_value: 32.971
  }
}
layer {
  name: "mconv1"
  type: "Convolution"
  bottom: "mdata"
  top: "mconv1"
  convolution_param {
    num_output: 384
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
  }
}
layer {
  name: "relu1"
  type: "ReLU"
  bottom: "mconv1"
  top: "mconv1"
}
layer {
  name: "conv5"
  type: "Convolution"
  bottom: "mconv1"
  top: "conv5"
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    group: 2
    stride: 1
  }
}
layer {
  name: "relu5"
  type: "ReLU"
  bottom: "conv5"
  top: "conv5"
}
layer {
  name: "mfc7"
  type: "InnerProduct"
  bottom: "conv5"
  top: "mfc7"
  inner_product_param {
    num_output: 4096
  }
}
layer {
  name: "relu7"
  type: "ReLU"
  bottom: "mfc7"
  top: "mfc7"
}
layer {
  name: "mfc8"
  type: "InnerProduct"
  bottom: "mfc7"
  top: "mfc8"
  inner_product_param {
    num_output: 4
  }
}
layer {
  name: "probs"
  type: "Softmax"
  bottom: "mfc8"
  top: "probs"
}
