name: "MPIIGaze"
layer {
  name: "MPII_train"
  type: "HDF5Data"
  top: "data"
  top: "label"
  hdf5_data_param {
    source: "examples/mymodel/05/train_list.txt"
    batch_size: 500
  }
  include: { phase: TRAIN }
}


layer {
  name: "MPII_test"
  type: "HDF5Data"
  top: "data"
  top: "label"
  hdf5_data_param {
    source: "examples/mymodel/05/test_list.txt"
    batch_size: 1000
  }
  include: { phase: TEST }
}

layer {
  name: "cutLabel"
  type: "Slice"
  bottom: "label"
  top: "gaze"
  top: "headpose"
  slice_param {
    slice_dim: 1
    slice_point: 3
  }
}

layer {
  name: "conv1/5x5_s1"
  type: "Convolution"
  bottom: "data"
  top: "conv1/5x5_s1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 5
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}

layer {
  name: "conv1/relu_5x5"
  type: "ReLU"
  bottom: "conv1/5x5_s1"
  top: "conv1/5x5_s1"
}

layer {
  name: "pool1/3x3_s2"
  type: "Pooling"
  bottom: "conv1/5x5_s1"
  top: "pool1/3x3_s2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}

layer {
  name: "pool1/norm1"
  type: "LRN"
  bottom: "pool1/3x3_s2"
  top: "pool1/norm1"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}



layer {
  name: "inception_1/1x1"
  type: "Convolution"
  bottom: "pool1/norm1"
  top: "inception_1/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_1/relu_1x1"
  type: "ReLU"
  bottom: "inception_1/1x1"
  top: "inception_1/1x1"
}

layer {
  name: "inception_1/3x3_reduce"
  type: "Convolution"
  bottom: "pool1/norm1"
  top: "inception_1/3x3_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 96
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_1/relu_3x3_reduce"
  type: "ReLU"
  bottom: "inception_1/3x3_reduce"
  top: "inception_1/3x3_reduce"
}
layer {
  name: "inception_1/3x3"
  type: "Convolution"
  bottom: "inception_1/3x3_reduce"
  top: "inception_1/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_1/relu_3x3"
  type: "ReLU"
  bottom: "inception_1/3x3"
  top: "inception_1/3x3"
}

layer {
  name: "inception_1/5x5_reduce"
  type: "Convolution"
  bottom: "pool1/norm1"
  top: "inception_1/5x5_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 16
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_1/relu_5x5_reduce"
  type: "ReLU"
  bottom: "inception_1/5x5_reduce"
  top: "inception_1/5x5_reduce"
}
layer {
  name: "inception_1/5x5"
  type: "Convolution"
  bottom: "inception_1/5x5_reduce"
  top: "inception_1/5x5"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_1/relu_5x5"
  type: "ReLU"
  bottom: "inception_1/5x5"
  top: "inception_1/5x5"
}

layer {
  name: "inception_1/pool"
  type: "Pooling"
  bottom: "pool1/norm1"
  top: "inception_1/pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_1/pool_proj"
  type: "Convolution"
  bottom: "inception_1/pool"
  top: "inception_1/pool_proj"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_1/relu_pool_proj"
  type: "ReLU"
  bottom: "inception_1/pool_proj"
  top: "inception_1/pool_proj"
}
layer {
  name: "inception_1/output"
  type: "Concat"
  bottom: "inception_1/1x1"
  bottom: "inception_1/3x3"
  bottom: "inception_1/5x5"
  bottom: "inception_1/pool_proj"
  top: "inception_1/output"
}



layer {
  name: "pool2/3x3_s2"
  type: "Pooling"
  bottom: "inception_1/output"
  top: "pool2/3x3_s2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}



layer {
  name: "conv2/3x3_s1"
  type: "Convolution"
  bottom: "pool2/3x3_s2"
  top: "conv2/3x3_s1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}

layer {
  name: "conv2/relu_3x3_s1"
  type: "ReLU"
  bottom: "conv2/3x3_s1"
  top: "conv2/3x3_s1"
}

layer {
  name: "pool3/2x2_s2"
  type: "Pooling"
  bottom: "conv2/3x3_s1"
  top: "pool3/2x2_s2"
  pooling_param {
    pool: AVE
    kernel_size: 2
    stride: 2
  }
}

layer {
  name: "ip1"
  type: "InnerProduct"
  bottom: "pool3/2x2_s2"
  top: "ip1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  inner_product_param {
    num_output: 500
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "relu_ip1"
  type: "ReLU"
  bottom: "ip1"
  top: "ip1"
}
layer {
  name: "drop_ip1"
  type: "Dropout"
  bottom: "ip1"
  top: "ip1"
  dropout_param {
    dropout_ratio: 0.5
  }
}

layer {
  name: "concat_headpose_eyeappearance"
  type: "Concat"
  bottom: "ip1"
  bottom: "headpose"
  top: "cat"
}

layer {
  name: "ip2"
  type: "InnerProduct"
  bottom: "cat"
  top: "ip2"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  inner_product_param {
    num_output: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "loss"
  type: "EuclideanLoss"
  bottom: "ip2"
  bottom: "gaze"
  top: "loss"
}