name: "onet"
layer {
  name: "data"
  type: "Input"
  top: "data"
  input_param {
    shape {
      dim: 1
      dim: 3
      dim: 34
      dim: 94
    }
  }
}
layer {
  name: "Convolution1"
  type: "Convolution"
  bottom: "data"
  top: "Convolution1"
  param {
    lr_mult: 1.0
  }
  convolution_param {
    num_output: 32
    bias_term: true
    stride: 1
    weight_filler {
      type: "xavier"
    }
    kernel_h: 3
    kernel_w: 3
  }
}
layer {
  name: "conv1"
  type: "PReLU"
  bottom: "Convolution1"
  top: "Convolution1"
}
layer {
  name: "pool1"
  type: "Pooling"
  bottom: "Convolution1"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_h: 3
    kernel_w: 3
    stride_h: 2
    stride_w: 2
  }
}
layer {
  name: "Convolution2"
  type: "Convolution"
  bottom: "pool1"
  top: "Convolution2"
  param {
    lr_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: true
    stride: 1
    weight_filler {
      type: "xavier"
    }
    kernel_h: 5
    kernel_w: 3
  }
}
layer {
  name: "conv2"
  type: "PReLU"
  bottom: "Convolution2"
  top: "Convolution2"
}
layer {
  name: "pool2"
  type: "Pooling"
  bottom: "Convolution2"
  top: "pool2"
  pooling_param {
    pool: MAX
    kernel_h: 3
    kernel_w: 3
    stride_h: 2
    stride_w: 2
  }
}
layer {
  name: "Convolution3"
  type: "Convolution"
  bottom: "pool2"
  top: "Convolution3"
  param {
    lr_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: true
    stride: 1
    weight_filler {
      type: "xavier"
    }
    kernel_h: 5
    kernel_w: 3
  }
}
layer {
  name: "conv3"
  type: "PReLU"
  bottom: "Convolution3"
  top: "Convolution3"
}
layer {
  name: "pool3"
  type: "Pooling"
  bottom: "Convolution3"
  top: "pool3"
  pooling_param {
    pool: MAX
    kernel_h: 2
    kernel_w: 2
    stride_h: 2
    stride_w: 2
  }
}
layer {
  name: "Convolution4"
  type: "Convolution"
  bottom: "pool3"
  top: "Convolution4"
  param {
    lr_mult: 1.0
  }
  convolution_param {
    num_output: 128
    bias_term: true
    stride: 1
    weight_filler {
      type: "xavier"
    }
    kernel_h: 1
    kernel_w: 1
  }
}
layer {
  name: "conv4"
  type: "PReLU"
  bottom: "Convolution4"
  top: "Convolution4"
}
layer {
  name: "fc1"
  type: "InnerProduct"
  bottom: "Convolution4"
  top: "fc1"
  inner_product_param {
    num_output: 256
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "d1"
  type: "Dropout"
  bottom: "fc1"
  top: "fc1"
  dropout_param {
    dropout_ratio: 0.25
  }
}
layer {
  name: "prelu1"
  type: "PReLU"
  bottom: "fc1"
  top: "fc1"
}
layer {
  name: "fc2"
  type: "InnerProduct"
  bottom: "fc1"
  top: "fc2"
  inner_product_param {
    num_output: 2
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fc3"
  type: "InnerProduct"
  bottom: "fc1"
  top: "fc3"
  inner_product_param {
    num_output: 4
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "prob1"
  type: "Softmax"
  bottom: "fc2"
  top: "prob1"
}