name: "PNet"
input: "data"
input_dim: 1
input_dim: 3
input_dim: 12
input_dim: 30

layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data"
  top: "conv1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 10
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "PReLU1"
  type: "PReLU"
  bottom: "conv1"
  top: "conv1"
}
layer {
  name: "pool1"
  type: "Pooling"
  bottom: "conv1"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}

layer {
  name: "conv2"
  type: "Convolution"
  bottom: "pool1"
  top: "conv2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 16
    kernel_size: 3
    stride: 1
     weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "PReLU2"
  type: "PReLU"
  bottom: "conv2"
  top: "conv2"
}

layer {
  name: "conv3"
  type: "Convolution"
  bottom: "conv2"
  top: "conv3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    kernel_size: 3
    stride: 1
     weight_filler {
      type: "xavier"
    }
    bias_filler {
	  type: "constant"
      value: 0
    }
  }
}
layer {
  name: "PReLU3"
  type: "PReLU"
  bottom: "conv3"
  top: "conv3"
}



layer {
  name: "conv4j-1"
  type: "Convolution"
  bottom: "conv3"
  top: "conv4-1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 2
    kernel_h:1 
    kernel_w:10  
	stride:1

     weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}




layer {
  name: "conv4j-2"
  type: "Convolution"
  bottom: "conv3"
  top: "conv4-2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 4
    kernel_h:1
    kernel_w:10
	stride: 1

     weight_filler {
      type: "xavier"
	}
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "prob1"
  type: "Softmax"
  bottom: "conv4-1"
  top: "prob1"
}