name:"HatNet"
layer {
  name: "data"
  type: "Input"
  top: "data"
  input_param { 
  shape {dim: 1 dim: 3 dim: 120 dim: 120}
  }
   transform_param {
    mean_value: 104
    mean_value: 117
    mean_value: 123
  }
 
}

layer {
  name: "conv_pre"
  type: "Convolution"
  bottom: "data"
  top: "conv_pre"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
    }
  convolution_param {
    num_output: 8
    pad: 0
    kernel_size: 5
    stride: 2
    weight_filler {
      type: "xavier"
      std: 0.07142857142857142
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm1"
  type: "BatchNorm"
  bottom: "conv_pre"
  top: "BatchNorm1"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "Scale1"
  type: "Scale"
  bottom: "BatchNorm1"
  top: "Scale1"
  scale_param {
    bias_term: true
  }
}



layer {
  name: "relu_pre"
  type: "ReLU"
  bottom: "Scale1"
  top: "relu_pre"
}

layer {
  name: "pool_pre"
  type: "Pooling"
  bottom: "relu_pre"
  top: "pool_pre"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}

layer {
  name: "conv1_1"
  type: "Convolution"
  bottom: "pool_pre"
  top: "conv1_1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 16
    pad: 0
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
      std: 0.11785113019775792
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm2"
  type: "BatchNorm"
  bottom: "conv1_1"
  top: "BatchNorm2"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "Scale2"
  type: "Scale"
  bottom: "BatchNorm2"
  top: "Scale2"
  scale_param {
    bias_term: true
  }
}


layer {
  name: "relu1_1"
  type: "ReLU"
  bottom: "Scale2"
  top: "relu1_1"
}

layer {
  name: "conv1_2"
  type: "Convolution"
  bottom: "relu1_1"
  top: "conv1_2"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 16
    pad: 0
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
      std: 0.11785113019775792
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm3"
  type: "BatchNorm"
  bottom: "conv1_2"
  top: "BatchNorm3"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "Scale3"
  type: "Scale"
  bottom: "BatchNorm3"
  top: "Scale3"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "relu1_2"
  type: "ReLU"
  bottom: "Scale3"
  top: "relu1_2"
}

layer {
  name: "pool1"
  type: "Pooling"
  bottom: "relu1_2"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "conv2_1"
  type: "Convolution"
  bottom: "pool1"
  top: "conv2_1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 24
    pad: 0
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
      std: 0.09622504486493763
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm4"
  type: "BatchNorm"
  bottom: "conv2_1"
  top: "BatchNorm4"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "Scale4"
  type: "Scale"
  bottom: "BatchNorm4"
  top: "Scale4"
  scale_param {
    bias_term: true
  }
}


layer {
  name: "relu2_1"
  type: "ReLU"
  bottom: "Scale4"
  top: "relu2_1"
}

layer {
  name: "conv2_2"
  type: "Convolution"
  bottom: "relu2_1"
  top: "conv2_2"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 24
    pad: 0
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
      std: 0.09622504486493763
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm5"
  type: "BatchNorm"
  bottom: "conv2_2"
  top: "BatchNorm5"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "Scale5"
  type: "Scale"
  bottom: "BatchNorm5"
  top: "Scale5"
  scale_param {
    bias_term: true
  }
}


layer {
  name: "relu2_2"
  type: "ReLU"
  bottom: "Scale5"
  top: "relu2_2"
}

layer {
  name: "pool2"
  type: "Pooling"
  bottom: "relu2_2"
  top: "pool2"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}

layer {
  name: "conv3_1"
  type: "Convolution"
  bottom: "pool2"
  top: "conv3_1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 40
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
      std: 0.08333333333333333
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm6"
  type: "BatchNorm"
  bottom: "conv3_1"
  top: "BatchNorm6"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "Scale6"
  type: "Scale"
  bottom: "BatchNorm6"
  top: "Scale6"
  scale_param {
    bias_term: true
  }
}


layer {
  name: "relu3_1"
  type: "ReLU"
  bottom: "Scale6"
  top: "relu3_1"
}
layer {
  name: "conv3_2"
  type: "Convolution"
  bottom: "relu3_1"
  top: "conv3_2"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 80
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
      std: 0.08333333333333333
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm7"
  type: "BatchNorm"
  bottom: "conv3_2"
  top: "BatchNorm7"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "Scale7"
  type: "Scale"
  bottom: "BatchNorm7"
  top: "Scale7"
  scale_param {
    bias_term: true
  }
}


layer {
  name: "relu3_2"
  type: "ReLU"
  bottom: "Scale7"
  top: "relu3_2"
}

layer {
  name: "ip1"
  type: "InnerProduct"
  bottom: "relu3_2"
  top: "ip1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult:2
  }
  inner_product_param {
    num_output: 128
    weight_filler {
      type: "xavier"
      std: 0.001
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "relu_ip1"
  type: "ReLU"
  bottom: "ip1"
  top: "ip1"
}
layer {
  name: "ip2"
  type: "InnerProduct"
  bottom: "ip1"
  top: "ip2"
  param {
    lr_mult: 1
    decay_mult: 10
  }
  param {
    lr_mult: 2
    decay_mult: 10
  }
  inner_product_param {
    num_output: 128
    weight_filler {
      type: "xavier"
      std: 0.001
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "relu_ip2"
  type: "ReLU"
  bottom: "ip2"
  top: "ip2"
}
layer {
  name: "ip3_gender"
  type: "InnerProduct"
  bottom: "ip2"
  top: "ip3_gender"
  param {
    lr_mult: 1
    decay_mult: 10
  }
  param {
    lr_mult: 2
    decay_mult: 10
  }
  inner_product_param {
    num_output: 2
    weight_filler {
      type: "xavier"
      std: 0.001
    }
    bias_filler {
      type: "constant"
    }
  }
}