TestModel.prototxt

name: "TestModel"

input:"data"
input_dim:1
input_dim:3
input_dim:128
input_dim:128

layer {
  name: "conv1_1_1"
  type: "Convolution"
  bottom: "data"
  top: "conv1_1_1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 32
    kernel_size: 3
    stride: 2
    pad: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer {
    bottom: "conv1_1_1"
    top: "conv1_1_1"
    name: "conv1_1_1_bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}

layer {
    bottom: "conv1_1_1"
    top: "conv1_1_1"
    name: "conv1_1_1_scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}

layer {
  name: "conv1_1_1_relu"
  type: "ReLU"
  bottom: "conv1_1_1"
  top: "conv1_1_1"
}



layer {
  name: "conv1_2_1"
  type: "Convolution"
  bottom: "data"
  top: "conv1_2_1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 32
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer {
    bottom: "conv1_2_1"
    top: "conv1_2_1"
    name: "conv1_2_1_bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}

layer {
    bottom: "conv1_2_1"
    top: "conv1_2_1"
    name: "conv1_2_1_scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}

layer {
  name: "conv1_2_1_relu"
  type: "ReLU"
  bottom: "conv1_2_1"
  top: "conv1_2_1"
}

layer {
  name: "conv1_2_2"
  type: "Convolution"
  bottom: "conv1_2_1"
  top: "conv1_2_2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 32
    kernel_size: 3
    stride: 2
    pad: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer {
    bottom: "conv1_2_2"
    top: "conv1_2_2"
    name: "conv1_2_2_bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}

layer {
    bottom: "conv1_2_2"
    top: "conv1_2_2"
    name: "conv1_2_2_scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}

layer {
  name: "conv1_2_2_relu"
  type: "ReLU"
  bottom: "conv1_2_2"
  top: "conv1_2_2"
}

layer {
  name: "conv1_3_1"
  type: "Convolution"
  bottom: "data"
  top: "conv1_3_1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 32
    kernel_size: 3
    stride: 2
    pad: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer {
    bottom: "conv1_3_1"
    top: "conv1_3_1"
    name: "conv1_3_1_bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}

layer {
    bottom: "conv1_3_1"
    top: "conv1_3_1"
    name: "conv1_3_1_scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}

layer {
  name: "conv1_3_1_relu"
  type: "ReLU"
  bottom: "conv1_3_1"
  top: "conv1_3_1"
}

layer {
  name: "conv1_3_2"
  type: "Convolution"
  bottom: "conv1_3_1"
  top: "conv1_3_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv1_3_2_relu"
  type: "ReLU"
  bottom: "conv1_3_2"
  top: "conv1_3_2"
}
layer {
  name: "conv1_3_3"
  type: "Convolution"
  bottom: "conv1_3_2"
  top: "conv1_3_3"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv1_3_3_relu"
  type: "ReLU"
  bottom: "conv1_3_3"
  top: "conv1_3_3"
}
layer {
  name: "feature1"
  type: "Concat"
  bottom: "conv1_1_1"
  bottom: "conv1_2_2"
  bottom: "conv1_3_3"
  top: "feature1"
}
layer {
  name: "conv2_1"
  type: "Convolution"
  bottom: "feature1"
  top: "conv2_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv2_1_relu"
  type: "ReLU"
  bottom: "conv2_1"
  top: "conv2_1"
}
layer {
  name: "conv2_2"
  type: "Convolution"
  bottom: "conv2_1"
  top: "conv2_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv2_2_relu"
  type: "ReLU"
  bottom: "conv2_2"
  top: "conv2_2"
}
layer {
  name: "conv2_3"
  type: "Convolution"
  bottom: "conv2_2"
  top: "conv2_3"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv2_3_relu"
  type: "ReLU"
  bottom: "conv2_3"
  top: "conv2_3"
}
layer {
  name: "conv2_4"
  type: "Convolution"
  bottom: "conv2_3"
  top: "conv2_4"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv2_4_relu"
  type: "ReLU"
  bottom: "conv2_4"
  top: "conv2_4"
}
layer {
  name: "conv2_5"
  type: "Convolution"
  bottom: "conv2_4"
  top: "conv2_5"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv2_5_relu"
  type: "ReLU"
  bottom: "conv2_5"
  top: "conv2_5"
}
layer {
  name: "conv2_6"
  type: "Convolution"
  bottom: "conv2_5"
  top: "conv2_6"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv2_6_relu"
  type: "ReLU"
  bottom: "conv2_6"
  top: "conv2_6"
}
layer {
  name: "conv2_7"
  type: "Convolution"
  bottom: "conv2_6"
  top: "conv2_7"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv2_7_relu"
  type: "ReLU"
  bottom: "conv2_7"
  top: "conv2_7"
}
layer {
  name: "conv2_8"
  type: "Convolution"
  bottom: "conv2_7"
  top: "conv2_8"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv2_8_relu"
  type: "ReLU"
  bottom: "conv2_8"
  top: "conv2_8"
}
layer {
  name: "feature2"
  type: "Concat"
  bottom: "conv2_2"
  bottom: "conv2_4"
  bottom: "conv2_6"
  bottom: "conv2_8"
  top: "feature2"
}
layer {
  name: "conv3_1_1b"
  type: "Convolution"
  bottom: "feature2"
  top: "conv3_1_1b"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    pad: 0
    kernel_size: 1
    stride: 2
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv3_1_1"
  type: "Convolution"
  bottom: "feature2"
  top: "conv3_1_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "relu_conv3_1_1"
  type: "ReLU"
  bottom: "conv3_1_1"
  top: "conv3_1_1"
}
layer {
  name: "conv3_1_2"
  type: "Convolution"
  bottom: "conv3_1_1"
  top: "conv3_1_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "res_conv3_1_2"
  type: "Eltwise"
  bottom: "conv3_1_1b"
  bottom: "conv3_1_2"
  top: "res_conv3_1_2"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "relu_res_conv3_1_2"
  type: "ReLU"
  bottom: "res_conv3_1_2"
  top: "res_conv3_1_2"
}
layer {
  name: "conv3_2_1"
  type: "Convolution"
  bottom: "res_conv3_1_2"
  top: "conv3_2_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "relu_conv3_2_1"
  type: "ReLU"
  bottom: "conv3_2_1"
  top: "conv3_2_1"
}
layer {
  name: "conv3_2_2"
  type: "Convolution"
  bottom: "conv3_2_1"
  top: "conv3_2_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "res_conv3_2_2"
  type: "Eltwise"
  bottom: "res_conv3_1_2"
  bottom: "conv3_2_2"
  top: "res_conv3_2_2"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "relu_res_conv3_2_2"
  type: "ReLU"
  bottom: "res_conv3_2_2"
  top: "res_conv3_2_2"
}
layer {
  name: "conv3_3_1"
  type: "Convolution"
  bottom: "res_conv3_2_2"
  top: "conv3_3_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "relu_conv3_3_1"
  type: "ReLU"
  bottom: "conv3_3_1"
  top: "conv3_3_1"
}
layer {
  name: "conv3_3_2"
  type: "Convolution"
  bottom: "conv3_3_1"
  top: "conv3_3_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "res_conv3_3_2"
  type: "Eltwise"
  bottom: "res_conv3_2_2"
  bottom: "conv3_3_2"
  top: "res_conv3_3_2"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "relu_res_conv3_3_2"
  type: "ReLU"
  bottom: "res_conv3_3_2"
  top: "res_conv3_3_2"
}
layer {
  name: "conv3_4_1"
  type: "Convolution"
  bottom: "res_conv3_3_2"
  top: "conv3_4_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "relu_conv3_4_1"
  type: "ReLU"
  bottom: "conv3_4_1"
  top: "conv3_4_1"
}
layer {
  name: "conv3_4_2"
  type: "Convolution"
  bottom: "conv3_4_1"
  top: "conv3_4_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "res_conv3_4_2"
  type: "Eltwise"
  bottom: "res_conv3_3_2"
  bottom: "conv3_4_2"
  top: "res_conv3_4_2"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "relu_res_conv3_4_2"
  type: "ReLU"
  bottom: "res_conv3_4_2"
  top: "res_conv3_4_2"
}
layer {
  name: "conv3_5_1"
  type: "Convolution"
  bottom: "res_conv3_4_2"
  top: "conv3_5_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "relu_conv3_5_1"
  type: "ReLU"
  bottom: "conv3_5_1"
  top: "conv3_5_1"
}
layer {
  name: "conv3_5_2"
  type: "Convolution"
  bottom: "conv3_5_1"
  top: "conv3_5_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "res_conv3_5_2"
  type: "Eltwise"
  bottom: "res_conv3_4_2"
  bottom: "conv3_5_2"
  top: "res_conv3_5_2"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "relu_res_conv3_5_2"
  type: "ReLU"
  bottom: "res_conv3_5_2"
  top: "res_conv3_5_2"
}
layer {
  name: "conv3_6_1"
  type: "Convolution"
  bottom: "res_conv3_5_2"
  top: "conv3_6_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "relu_conv3_6_1"
  type: "ReLU"
  bottom: "conv3_6_1"
  top: "conv3_6_1"
}
layer {
  name: "conv3_6_2"
  type: "Convolution"
  bottom: "conv3_6_1"
  top: "conv3_6_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "res_conv3_6_2"
  type: "Eltwise"
  bottom: "res_conv3_5_2"
  bottom: "conv3_6_2"
  top: "res_conv3_6_2"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "relu_res_conv3_6_2"
  type: "ReLU"
  bottom: "res_conv3_6_2"
  top: "res_conv3_6_2"
}
layer {
  name: "feature3"
  type: "Concat"
  bottom: "res_conv3_2_2"
  bottom: "res_conv3_4_2"
  bottom: "res_conv3_6_2"
  top: "feature3"
}
layer {
  name: "conv4_1_1b"
  type: "Convolution"
  bottom: "feature3"
  top: "conv4_1_1b"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    stride: 2
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv4_1_1"
  type: "Convolution"
  bottom: "feature3"
  top: "conv4_1_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "relu_conv4_1_1"
  type: "ReLU"
  bottom: "conv4_1_1"
  top: "conv4_1_1"
}
layer {
  name: "conv4_1_2"
  type: "Convolution"
  bottom: "conv4_1_1"
  top: "conv4_1_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "res_conv4_1_2"
  type: "Eltwise"
  bottom: "conv4_1_1b"
  bottom: "conv4_1_2"
  top: "res_conv4_1_2"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "relu_res_conv4_1_2"
  type: "ReLU"
  bottom: "res_conv4_1_2"
  top: "res_conv4_1_2"
}
layer {
  name: "conv4_2_1"
  type: "Convolution"
  bottom: "res_conv4_1_2"
  top: "conv4_2_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "relu_conv4_2_1"
  type: "ReLU"
  bottom: "conv4_2_1"
  top: "conv4_2_1"
}
layer {
  name: "conv4_2_2"
  type: "Convolution"
  bottom: "conv4_2_1"
  top: "conv4_2_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "res_conv4_2_2"
  type: "Eltwise"
  bottom: "res_conv4_1_2"
  bottom: "conv4_2_2"
  top: "res_conv4_2_2"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "relu_res_conv4_2_2"
  type: "ReLU"
  bottom: "res_conv4_2_2"
  top: "res_conv4_2_2"
}
layer {
  name: "conv4_3_1"
  type: "Convolution"
  bottom: "res_conv4_2_2"
  top: "conv4_3_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "relu_conv4_3_1"
  type: "ReLU"
  bottom: "conv4_3_1"
  top: "conv4_3_1"
}
layer {
  name: "conv4_3_2"
  type: "Convolution"
  bottom: "conv4_3_1"
  top: "conv4_3_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "res_conv4_3_2"
  type: "Eltwise"
  bottom: "res_conv4_2_2"
  bottom: "conv4_3_2"
  top: "res_conv4_3_2"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "relu_res_conv4_3_2"
  type: "ReLU"
  bottom: "res_conv4_3_2"
  top: "res_conv4_3_2"
}
layer {
  name: "conv4_4_1"
  type: "Convolution"
  bottom: "res_conv4_3_2"
  top: "conv4_4_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "relu_conv4_4_1"
  type: "ReLU"
  bottom: "conv4_4_1"
  top: "conv4_4_1"
}
layer {
  name: "conv4_4_2"
  type: "Convolution"
  bottom: "conv4_4_1"
  top: "conv4_4_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "res_conv4_4_2"
  type: "Eltwise"
  bottom: "res_conv4_3_2"
  bottom: "conv4_4_2"
  top: "res_conv4_4_2"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "relu_res_conv4_4_2"
  type: "ReLU"
  bottom: "res_conv4_4_2"
  top: "res_conv4_4_2"
}
layer {
  name: "conv4_5_1"
  type: "Convolution"
  bottom: "res_conv4_4_2"
  top: "conv4_5_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "relu_conv4_5_1"
  type: "ReLU"
  bottom: "conv4_5_1"
  top: "conv4_5_1"
}
layer {
  name: "conv4_5_2"
  type: "Convolution"
  bottom: "conv4_5_1"
  top: "conv4_5_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "res_conv4_5_2"
  type: "Eltwise"
  bottom: "res_conv4_4_2"
  bottom: "conv4_5_2"
  top: "res_conv4_5_2"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "relu_res_conv4_5_2"
  type: "ReLU"
  bottom: "res_conv4_5_2"
  top: "res_conv4_5_2"
}
layer {
  name: "conv4_6_1"
  type: "Convolution"
  bottom: "res_conv4_5_2"
  top: "conv4_6_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "relu_conv4_6_1"
  type: "ReLU"
  bottom: "conv4_6_1"
  top: "conv4_6_1"
}
layer {
  name: "conv4_6_2"
  type: "Convolution"
  bottom: "conv4_6_1"
  top: "conv4_6_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "res_conv4_6_2"
  type: "Eltwise"
  bottom: "res_conv4_5_2"
  bottom: "conv4_6_2"
  top: "res_conv4_6_2"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "relu_res_conv4_6_2"
  type: "ReLU"
  bottom: "res_conv4_6_2"
  top: "res_conv4_6_2"
}
layer {
  name: "feature4"
  type: "Concat"
  bottom: "res_conv4_2_2"
  bottom: "res_conv4_4_2"
  bottom: "res_conv4_6_2"
  top: "feature4"
}
layer {
  name: "conv5_1_1b"
  type: "Convolution"
  bottom: "feature4"
  top: "conv5_1_1b"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 1
    stride: 2
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv5_1_1"
  type: "Convolution"
  bottom: "feature4"
  top: "conv5_1_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 1
    stride: 2
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "relu_conv5_1_1"
  type: "ReLU"
  bottom: "conv5_1_1"
  top: "conv5_1_1"
}
layer {
  name: "conv5_1_2"
  type: "Convolution"
  bottom: "conv5_1_1"
  top: "conv5_1_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "res_conv5_1_2"
  type: "Eltwise"
  bottom: "conv5_1_1b"
  bottom: "conv5_1_2"
  top: "res_conv5_1_2"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "relu_res_conv5_1_2"
  type: "ReLU"
  bottom: "res_conv5_1_2"
  top: "res_conv5_1_2"
}
layer {
  name: "conv5_2_1"
  type: "Convolution"
  bottom: "res_conv5_1_2"
  top: "conv5_2_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "relu_conv5_2_1"
  type: "ReLU"
  bottom: "conv5_2_1"
  top: "conv5_2_1"
}
layer {
  name: "conv5_2_2"
  type: "Convolution"
  bottom: "conv5_2_1"
  top: "conv5_2_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "res_conv5_2_2"
  type: "Eltwise"
  bottom: "res_conv5_1_2"
  bottom: "conv5_2_2"
  top: "res_conv5_2_2"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "relu_res_conv5_2_2"
  type: "ReLU"
  bottom: "res_conv5_2_2"
  top: "res_conv5_2_2"
}
layer {
  name: "conv5_3_1"
  type: "Convolution"
  bottom: "res_conv5_2_2"
  top: "conv5_3_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "relu_conv5_3_1"
  type: "ReLU"
  bottom: "conv5_3_1"
  top: "conv5_3_1"
}
layer {
  name: "conv5_3_2"
  type: "Convolution"
  bottom: "conv5_3_1"
  top: "conv5_3_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "res_conv5_3_2"
  type: "Eltwise"
  bottom: "res_conv5_2_2"
  bottom: "conv5_3_2"
  top: "res_conv5_3_2"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "relu_res_conv5_3_2"
  type: "ReLU"
  bottom: "res_conv5_3_2"
  top: "res_conv5_3_2"
}
layer {
  name: "conv5_4_1"
  type: "Convolution"
  bottom: "res_conv5_3_2"
  top: "conv5_4_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "relu_conv5_4_1"
  type: "ReLU"
  bottom: "conv5_4_1"
  top: "conv5_4_1"
}
layer {
  name: "conv5_4_2"
  type: "Convolution"
  bottom: "conv5_4_1"
  top: "conv5_4_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "res_conv5_4_2"
  type: "Eltwise"
  bottom: "res_conv5_3_2"
  bottom: "conv5_4_2"
  top: "res_conv5_4_2"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "relu_res_conv5_4_2"
  type: "ReLU"
  bottom: "res_conv5_4_2"
  top: "res_conv5_4_2"
}
layer {
  name: "conv5_5_1"
  type: "Convolution"
  bottom: "res_conv5_4_2"
  top: "conv5_5_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "relu_conv5_5_1"
  type: "ReLU"
  bottom: "conv5_5_1"
  top: "conv5_5_1"
}
layer {
  name: "conv5_5_2"
  type: "Convolution"
  bottom: "conv5_5_1"
  top: "conv5_5_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "res_conv5_5_2"
  type: "Eltwise"
  bottom: "res_conv5_4_2"
  bottom: "conv5_5_2"
  top: "res_conv5_5_2"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "relu_res_conv5_5_2"
  type: "ReLU"
  bottom: "res_conv5_5_2"
  top: "res_conv5_5_2"
}
layer {
  name: "conv5_6_1"
  type: "Convolution"
  bottom: "res_conv5_5_2"
  top: "conv5_6_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "relu_conv5_6_1"
  type: "ReLU"
  bottom: "conv5_6_1"
  top: "conv5_6_1"
}
layer {
  name: "conv5_6_2"
  type: "Convolution"
  bottom: "conv5_6_1"
  top: "conv5_6_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "res_conv5_6_2"
  type: "Eltwise"
  bottom: "res_conv5_5_2"
  bottom: "conv5_6_2"
  top: "res_conv5_6_2"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "relu_res_conv5_6_2"
  type: "ReLU"
  bottom: "res_conv5_6_2"
  top: "res_conv5_6_2"
}
layer {
  name: "feature5"
  type: "Concat"
  bottom: "res_conv5_2_2"
  bottom: "res_conv5_4_2"
  bottom: "res_conv5_6_2"
  top: "feature5"
}
layer {
  name: "fc5_"
  type: "InnerProduct"
  bottom: "feature5"
  top: "fc5_"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  inner_product_param {
    num_output: 512
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}