name: "landmark"
layer {
  name: "data"
  type: "Input"
  top: "data"
  input_param {
    shape {
      dim: 1
      dim: 1
      dim: 128
      dim: 128
    }
  }
}
layer {
  name: "Convolution1"
  type: "Convolution"
  bottom: "data"
  top: "Convolution1"
  param {
    lr_mult: 1.0
  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "BatchNorm1"
  type: "BatchNorm"
  bottom: "Convolution1"
  top: "Convolution1"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "Scale1"
  type: "Scale"
  bottom: "Convolution1"
  top: "Convolution1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv1"
  type: "ReLU"
  bottom: "Convolution1"
  top: "Convolution1"
}
layer {
  name: "Convolution2"
  type: "Convolution"
  bottom: "Convolution1"
  top: "Convolution2"
  param {
    lr_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "BatchNorm2"
  type: "BatchNorm"
  bottom: "Convolution2"
  top: "Convolution2"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "Scale2"
  type: "Scale"
  bottom: "Convolution2"
  top: "Convolution2"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv2"
  type: "ReLU"
  bottom: "Convolution2"
  top: "Convolution2"
}
layer {
  name: "Convolution3"
  type: "Convolution"
  bottom: "Convolution2"
  top: "Convolution3"
  param {
    lr_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "BatchNorm3"
  type: "BatchNorm"
  bottom: "Convolution3"
  top: "Convolution3"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "Scale3"
  type: "Scale"
  bottom: "Convolution3"
  top: "Convolution3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv3"
  type: "ReLU"
  bottom: "Convolution3"
  top: "Convolution3"
}
layer {
  name: "Convolution4"
  type: "Convolution"
  bottom: "Convolution3"
  top: "Convolution4"
  param {
    lr_mult: 1.0
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "BatchNorm4"
  type: "BatchNorm"
  bottom: "Convolution4"
  top: "Convolution4"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "Scale4"
  type: "Scale"
  bottom: "Convolution4"
  top: "Convolution4"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv4"
  type: "ReLU"
  bottom: "Convolution4"
  top: "Convolution4"
}
layer {
  name: "Convolution5"
  type: "Convolution"
  bottom: "Convolution4"
  top: "Convolution5"
  param {
    lr_mult: 1.0
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "BatchNorm5"
  type: "BatchNorm"
  bottom: "Convolution5"
  top: "Convolution5"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "Scale5"
  type: "Scale"
  bottom: "Convolution5"
  top: "Convolution5"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv5"
  type: "ReLU"
  bottom: "Convolution5"
  top: "Convolution5"
}
layer {
  name: "Convolution6"
  type: "Convolution"
  bottom: "Convolution5"
  top: "Convolution6"
  param {
    lr_mult: 1.0
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "BatchNorm6"
  type: "BatchNorm"
  bottom: "Convolution6"
  top: "Convolution6"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "Scale6"
  type: "Scale"
  bottom: "Convolution6"
  top: "Convolution6"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv6"
  type: "ReLU"
  bottom: "Convolution6"
  top: "Convolution6"
}
layer {
  name: "Convolution7"
  type: "Convolution"
  bottom: "Convolution6"
  top: "Convolution7"
  param {
    lr_mult: 1.0
  }
  convolution_param {
    num_output: 256
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "BatchNorm7"
  type: "BatchNorm"
  bottom: "Convolution7"
  top: "Convolution7"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "Scale7"
  type: "Scale"
  bottom: "Convolution7"
  top: "Convolution7"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv7"
  type: "ReLU"
  bottom: "Convolution7"
  top: "Convolution7"
}
layer {
  name: "Convolution8"
  type: "Convolution"
  bottom: "Convolution7"
  top: "Convolution8"
  param {
    lr_mult: 1.0
  }
  convolution_param {
    num_output: 512
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "BatchNorm8"
  type: "BatchNorm"
  bottom: "Convolution8"
  top: "Convolution8"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "Scale8"
  type: "Scale"
  bottom: "Convolution8"
  top: "Convolution8"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv8"
  type: "ReLU"
  bottom: "Convolution8"
  top: "Convolution8"
}
layer {
  name: "gap1"
  type: "Pooling"
  bottom: "Convolution8"
  top: "gap1"
  pooling_param {
    pool: AVE
    global_pooling: true
  }
}
layer {
  name: "fc1"
  type: "InnerProduct"
  bottom: "gap1"
  top: "fc1"
  inner_product_param {
    num_output: 8
    weight_filler {
      type: "xavier"
    }
  }
}