layer {
  name: "input"
  top: "data"
  type: "DummyData"
  dummy_data_param {
    data_filler {
      value: 0
    }
    shape {
      dim: 1
      dim: 3
      dim: 96
      dim: 96
    }
  }
}

layer {
  name: "datamvn"
  bottom: "data"
  top: "datamvn"
  type: "MVN"
  mvn_param{
    across_channels: true
  }
}

layer {
  name: "datascale"
  type: "Power"
  bottom: "datamvn"
  top: "datascale"
  power_param{
    scale: 50
  }
}


layer {
  name: "conv1"
  type: "Convolution"
  bottom: "datascale"
  top: "conv1"
  convolution_param {
    num_output: 96
    kernel_size: 11
    stride: 4
      pad: 5
  }
}
layer{
  name: "conv1relu"
  type: "ReLU"
  bottom: "conv1"
  top: "conv1"
}


layer {
  name: "pool1"
  type: "Pooling"
  bottom: "conv1"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "norm1"
  type: "LRN"
  bottom: "pool1"
  top: "norm1"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}

layer {
  name: "conv2"
  type: "Convolution"
  bottom: "norm1"
  top: "conv2"
  convolution_param {
    num_output: 256
    kernel_size: 5
    stride: 1
      pad: 2
  }
}
layer{
  name: "conv2relu"
  type: "ReLU"
  bottom: "conv2"
  top: "conv2"
}


layer {
  name: "pool2"
  type: "Pooling"
  bottom: "conv2"
  top: "pool2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "norm2"
  type: "LRN"
  bottom: "pool2"
  top: "norm2"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}

layer {
  name: "conv3"
  type: "Convolution"
  bottom: "norm2"
  top: "conv3"
  convolution_param {
    num_output: 384
    kernel_size: 3
    stride: 1
      pad: 1
  }
}
layer{
  name: "conv3relu"
  type: "ReLU"
  bottom: "conv3"
  top: "conv3"
}



layer {
  name: "conv4"
  type: "Convolution"
  bottom: "conv3"
  top: "conv4"
  convolution_param {
    num_output: 384
    kernel_size: 3
    stride: 1
      pad: 1
  }
}
layer{
  name: "conv4relu"
  type: "ReLU"
  bottom: "conv4"
  top: "conv4"
}



layer {
  name: "conv5"
  type: "Convolution"
  bottom: "conv4"
  top: "conv5"
  convolution_param {
    num_output: 256
    kernel_size: 3
    stride: 1
      pad: 1
  }
}
layer{
  name: "conv5relu"
  type: "ReLU"
  bottom: "conv5"
  top: "conv5"
}


layer {
  name: "pool5"
  type: "Pooling"
  bottom: "conv5"
  top: "pool5"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}

layer {
  name: "fc6"
  type: "InnerProduct"
  bottom: "pool5"
  top: "fc6"
  inner_product_param {
    num_output: 4096
  }
}

layer {
  name: "fc6_silence"
  type: "Silence"
  bottom: "fc6"
}