MobileUnet1by2.prototxt

name: "MOBILENET1by2_hp_Set24_AUX"
#  transform_param {
#    scale: 0.017
#    mirror: false
#    crop_size: 224
#    mean_value: [103.94,116.78,123.68]
#  }
#input: "data"
#input_shape { 
#  dim: 1
#  dim: 3
#  dim: 224
#  dim: 224
#}

layer {
  name: "train_data"
  type: "ImageSegData"
  top: "data"
  top: "label"
  image_data_param {
    root_folder: ""
    source: "trainlist.txt"
    label_type: PIXEL
    batch_size: 16
    shuffle: true
    ignore_label: 255
    new_width: 400
    new_height: 400
  }
  transform_param {
    mirror: true
    crop_size: 320
    mean_value: 103.52
    mean_value: 116.28
    mean_value: 123.675
    scale: 0.017
    #### multi-scale ####
#    scale_factors: 0.75
#    scale_factors: 1
#    scale_factors: 1.25
#    scale_factors: 1.5
#    scale_factors: 2.0
    #### rolation ####
    max_rotation_angle: 10
    #### max_color_shift ####
    max_color_shift: 20
    #### brightness ####
    contrast_brightness_adjustment: true
    min_contrast: 0.5
    max_contrast: 2.5
    #### smooth ####
    smooth_filtering: true
    max_smooth: 6

    apply_probability: 0.5
    debug_params: false

  }
  include: { phase: TRAIN }
}
layer {
  name: "test_data"
  type: "ImageSegData"
  top: "data"
  top: "label"
  image_data_param {
    root_folder: ""
    source: "vallist.txt"
    label_type: PIXEL
    batch_size: 1
    shuffle: true
    ignore_label: 255
    new_width: 400
    new_height: 400
  }
  transform_param {
    mean_value: 103.94
    mean_value: 116.78
    mean_value: 123.68
    crop_size: 320
    scale: 0.017
    mirror: false
  }
  include: { phase: TEST }
}

layer {
  name: "conv1_1by2"
  type: "Convolution"
  bottom: "data"
  top: "conv1_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv1/bn_1by2"
  type: "BatchNorm"
  bottom: "conv1_1by2"
  top: "conv1_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv1/scale_1by2"
  type: "Scale"
  bottom: "conv1_1by2"
  top: "conv1_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu1_1by2"
  type: "ReLU"
  bottom: "conv1_1by2"
  top: "conv1_1by2"
}
layer {
  name: "conv2_1/dw_1by2"
  type: "ConvolutionDepthwise"
  bottom: "conv1_1by2"
  top: "conv2_1/dw_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv2_1/dw/bn_1by2"
  type: "BatchNorm"
  bottom: "conv2_1/dw_1by2"
  top: "conv2_1/dw_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv2_1/dw/scale_1by2"
  type: "Scale"
  bottom: "conv2_1/dw_1by2"
  top: "conv2_1/dw_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu2_1/dw_1by2"
  type: "ReLU"
  bottom: "conv2_1/dw_1by2"
  top: "conv2_1/dw_1by2"
}
layer {
  name: "conv2_1/sep_1by2"
  type: "Convolution"
  bottom: "conv2_1/dw_1by2"
  top: "conv2_1/sep_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv2_1/sep/bn_1by2"
  type: "BatchNorm"
  bottom: "conv2_1/sep_1by2"
  top: "conv2_1/sep_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv2_1/sep/scale_1by2"
  type: "Scale"
  bottom: "conv2_1/sep_1by2"
  top: "conv2_1/sep_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu2_1/sep_1by2"
  type: "ReLU"
  bottom: "conv2_1/sep_1by2"
  top: "conv2_1/sep_1by2"
}
layer {
  name: "conv2_2/dw_1by2"
  type: "ConvolutionDepthwise"
  bottom: "conv2_1/sep_1by2"
  top: "conv2_2/dw_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv2_2/dw/bn_1by2"
  type: "BatchNorm"
  bottom: "conv2_2/dw_1by2"
  top: "conv2_2/dw_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv2_2/dw/scale_1by2"
  type: "Scale"
  bottom: "conv2_2/dw_1by2"
  top: "conv2_2/dw_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu2_2/dw_1by2"
  type: "ReLU"
  bottom: "conv2_2/dw_1by2"
  top: "conv2_2/dw_1by2"
}
layer {
  name: "conv2_2/sep_1by2"
  type: "Convolution"
  bottom: "conv2_2/dw_1by2"
  top: "conv2_2/sep_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv2_2/sep/bn_1by2"
  type: "BatchNorm"
  bottom: "conv2_2/sep_1by2"
  top: "conv2_2/sep_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv2_2/sep/scale_1by2"
  type: "Scale"
  bottom: "conv2_2/sep_1by2"
  top: "conv2_2/sep_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu2_2/sep_1by2"
  type: "ReLU"
  bottom: "conv2_2/sep_1by2"
  top: "conv2_2/sep_1by2"
}
layer {
  name: "conv3_1/dw_1by2"
  type: "ConvolutionDepthwise"
  bottom: "conv2_2/sep_1by2"
  top: "conv3_1/dw_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv3_1/dw/bn_1by2"
  type: "BatchNorm"
  bottom: "conv3_1/dw_1by2"
  top: "conv3_1/dw_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv3_1/dw/scale_1by2"
  type: "Scale"
  bottom: "conv3_1/dw_1by2"
  top: "conv3_1/dw_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu3_1/dw_1by2"
  type: "ReLU"
  bottom: "conv3_1/dw_1by2"
  top: "conv3_1/dw_1by2"
}
layer {
  name: "conv3_1/sep_1by2"
  type: "Convolution"
  bottom: "conv3_1/dw_1by2"
  top: "conv3_1/sep_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv3_1/sep/bn_1by2"
  type: "BatchNorm"
  bottom: "conv3_1/sep_1by2"
  top: "conv3_1/sep_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv3_1/sep/scale_1by2"
  type: "Scale"
  bottom: "conv3_1/sep_1by2"
  top: "conv3_1/sep_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu3_1/sep_1by2"
  type: "ReLU"
  bottom: "conv3_1/sep_1by2"
  top: "conv3_1/sep_1by2"
}
layer {
  name: "conv3_2/dw_1by2"
  type: "ConvolutionDepthwise"
  bottom: "conv3_1/sep_1by2"
  top: "conv3_2/dw_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv3_2/dw/bn_1by2"
  type: "BatchNorm"
  bottom: "conv3_2/dw_1by2"
  top: "conv3_2/dw_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv3_2/dw/scale_1by2"
  type: "Scale"
  bottom: "conv3_2/dw_1by2"
  top: "conv3_2/dw_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu3_2/dw_1by2"
  type: "ReLU"
  bottom: "conv3_2/dw_1by2"
  top: "conv3_2/dw_1by2"
}
layer {
  name: "conv3_2/sep_1by2"
  type: "Convolution"
  bottom: "conv3_2/dw_1by2"
  top: "conv3_2/sep_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv3_2/sep/bn_1by2"
  type: "BatchNorm"
  bottom: "conv3_2/sep_1by2"
  top: "conv3_2/sep_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv3_2/sep/scale_1by2"
  type: "Scale"
  bottom: "conv3_2/sep_1by2"
  top: "conv3_2/sep_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu3_2/sep_1by2"
  type: "ReLU"
  bottom: "conv3_2/sep_1by2"
  top: "conv3_2/sep_1by2"
}
layer {
  name: "conv4_1/dw_1by2"
  type: "ConvolutionDepthwise"
  bottom: "conv3_2/sep_1by2"
  top: "conv4_1/dw_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4_1/dw/bn_1by2"
  type: "BatchNorm"
  bottom: "conv4_1/dw_1by2"
  top: "conv4_1/dw_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv4_1/dw/scale_1by2"
  type: "Scale"
  bottom: "conv4_1/dw_1by2"
  top: "conv4_1/dw_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu4_1/dw_1by2"
  type: "ReLU"
  bottom: "conv4_1/dw_1by2"
  top: "conv4_1/dw_1by2"
}
layer {
  name: "conv4_1/sep_1by2"
  type: "Convolution"
  bottom: "conv4_1/dw_1by2"
  top: "conv4_1/sep_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 0
    kernel_size: 1
    engine: CAFFE
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4_1/sep/bn_1by2"
  type: "BatchNorm"
  bottom: "conv4_1/sep_1by2"
  top: "conv4_1/sep_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv4_1/sep/scale_1by2"
  type: "Scale"
  bottom: "conv4_1/sep_1by2"
  top: "conv4_1/sep_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu4_1/sep_1by2"
  type: "ReLU"
  bottom: "conv4_1/sep_1by2"
  top: "conv4_1/sep_1by2"
}
layer {
  name: "conv4_2/dw_1by2"
  type: "ConvolutionDepthwise"
  bottom: "conv4_1/sep_1by2"
  top: "conv4_2/dw_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4_2/dw/bn_1by2"
  type: "BatchNorm"
  bottom: "conv4_2/dw_1by2"
  top: "conv4_2/dw_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv4_2/dw/scale_1by2"
  type: "Scale"
  bottom: "conv4_2/dw_1by2"
  top: "conv4_2/dw_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu4_2/dw_1by2"
  type: "ReLU"
  bottom: "conv4_2/dw_1by2"
  top: "conv4_2/dw_1by2"
}
layer {
  name: "conv4_2/sep_1by2"
  type: "Convolution"
  bottom: "conv4_2/dw_1by2"
  top: "conv4_2/sep_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4_2/sep/bn_1by2"
  type: "BatchNorm"
  bottom: "conv4_2/sep_1by2"
  top: "conv4_2/sep_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv4_2/sep/scale_1by2"
  type: "Scale"
  bottom: "conv4_2/sep_1by2"
  top: "conv4_2/sep_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu4_2/sep_1by2"
  type: "ReLU"
  bottom: "conv4_2/sep_1by2"
  top: "conv4_2/sep_1by2"
}
layer {
  name: "conv5_1/dw_1by2"
  type: "ConvolutionDepthwise"
  bottom: "conv4_2/sep_1by2"
  top: "conv5_1/dw_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 1
    engine: CAFFE
    dilation: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5_1/dw/bn_1by2"
  type: "BatchNorm"
  bottom: "conv5_1/dw_1by2"
  top: "conv5_1/dw_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv5_1/dw/scale_1by2"
  type: "Scale"
  bottom: "conv5_1/dw_1by2"
  top: "conv5_1/dw_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu5_1/dw_1by2"
  type: "ReLU"
  bottom: "conv5_1/dw_1by2"
  top: "conv5_1/dw_1by2"
}
layer {
  name: "conv5_1/sep_1by2"
  type: "Convolution"
  bottom: "conv5_1/dw_1by2"
  top: "conv5_1/sep_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 0
    kernel_size: 1
    engine: CAFFE
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5_1/sep/bn_1by2"
  type: "BatchNorm"
  bottom: "conv5_1/sep_1by2"
  top: "conv5_1/sep_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv5_1/sep/scale_1by2"
  type: "Scale"
  bottom: "conv5_1/sep_1by2"
  top: "conv5_1/sep_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu5_1/sep_1by2"
  type: "ReLU"
  bottom: "conv5_1/sep_1by2"
  top: "conv5_1/sep_1by2"
}
layer {
  name: "conv5_2/dw_1by2"
  type: "ConvolutionDepthwise"
  bottom: "conv5_1/sep_1by2"
  top: "conv5_2/dw_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 2
    kernel_size: 3
    stride: 1
    engine: CAFFE
    dilation: 2
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5_2/dw/bn_1by2"
  type: "BatchNorm"
  bottom: "conv5_2/dw_1by2"
  top: "conv5_2/dw_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv5_2/dw/scale_1by2"
  type: "Scale"
  bottom: "conv5_2/dw_1by2"
  top: "conv5_2/dw_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu5_2/dw_1by2"
  type: "ReLU"
  bottom: "conv5_2/dw_1by2"
  top: "conv5_2/dw_1by2"
}
layer {
  name: "conv5_2/sep_1by2"
  type: "Convolution"
  bottom: "conv5_2/dw_1by2"
  top: "conv5_2/sep_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5_2/sep/bn_1by2"
  type: "BatchNorm"
  bottom: "conv5_2/sep_1by2"
  top: "conv5_2/sep_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv5_2/sep/scale_1by2"
  type: "Scale"
  bottom: "conv5_2/sep_1by2"
  top: "conv5_2/sep_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu5_2/sep_1by2"
  type: "ReLU"
  bottom: "conv5_2/sep_1by2"
  top: "conv5_2/sep_1by2"
}
layer {
  name: "conv5_3/dw_1by2"
  type: "ConvolutionDepthwise"
  bottom: "conv5_2/sep_1by2"
  top: "conv5_3/dw_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 5
    kernel_size: 3
    stride: 1
    engine: CAFFE
    dilation: 5
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5_3/dw/bn_1by2"
  type: "BatchNorm"
  bottom: "conv5_3/dw_1by2"
  top: "conv5_3/dw_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv5_3/dw/scale_1by2"
  type: "Scale"
  bottom: "conv5_3/dw_1by2"
  top: "conv5_3/dw_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu5_3/dw_1by2"
  type: "ReLU"
  bottom: "conv5_3/dw_1by2"
  top: "conv5_3/dw_1by2"
}
layer {
  name: "conv5_3/sep_1by2"
  type: "Convolution"
  bottom: "conv5_3/dw_1by2"
  top: "conv5_3/sep_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5_3/sep/bn_1by2"
  type: "BatchNorm"
  bottom: "conv5_3/sep_1by2"
  top: "conv5_3/sep_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv5_3/sep/scale_1by2"
  type: "Scale"
  bottom: "conv5_3/sep_1by2"
  top: "conv5_3/sep_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu5_3/sep_1by2"
  type: "ReLU"
  bottom: "conv5_3/sep_1by2"
  top: "conv5_3/sep_1by2"
}
layer {
  name: "conv5_4/dw_1by2"
  type: "ConvolutionDepthwise"
  bottom: "conv5_3/sep_1by2"
  top: "conv5_4/dw_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 7
    kernel_size: 3
    stride: 1
    engine: CAFFE
    dilation: 7
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5_4/dw/bn_1by2"
  type: "BatchNorm"
  bottom: "conv5_4/dw_1by2"
  top: "conv5_4/dw_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv5_4/dw/scale_1by2"
  type: "Scale"
  bottom: "conv5_4/dw_1by2"
  top: "conv5_4/dw_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu5_4/dw_1by2"
  type: "ReLU"
  bottom: "conv5_4/dw_1by2"
  top: "conv5_4/dw_1by2"
}
layer {
  name: "conv5_4/sep_1by2"
  type: "Convolution"
  bottom: "conv5_4/dw_1by2"
  top: "conv5_4/sep_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5_4/sep/bn_1by2"
  type: "BatchNorm"
  bottom: "conv5_4/sep_1by2"
  top: "conv5_4/sep_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv5_4/sep/scale_1by2"
  type: "Scale"
  bottom: "conv5_4/sep_1by2"
  top: "conv5_4/sep_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu5_4/sep_1by2"
  type: "ReLU"
  bottom: "conv5_4/sep_1by2"
  top: "conv5_4/sep_1by2"
}
layer {
  name: "conv5_5/dw_1by2"
  type: "ConvolutionDepthwise"
  bottom: "conv5_4/sep_1by2"
  top: "conv5_5/dw_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 1
    kernel_size: 3
    engine: CAFFE
    stride: 1
    dilation: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5_5/dw/bn_1by2"
  type: "BatchNorm"
  bottom: "conv5_5/dw_1by2"
  top: "conv5_5/dw_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv5_5/dw/scale_1by2"
  type: "Scale"
  bottom: "conv5_5/dw_1by2"
  top: "conv5_5/dw_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu5_5/dw_1by2"
  type: "ReLU"
  bottom: "conv5_5/dw_1by2"
  top: "conv5_5/dw_1by2"
}
layer {
  name: "conv5_5/sep_1by2"
  type: "Convolution"
  bottom: "conv5_5/dw_1by2"
  top: "conv5_5/sep_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 0
    engine: CAFFE
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5_5/sep/bn_1by2"
  type: "BatchNorm"
  bottom: "conv5_5/sep_1by2"
  top: "conv5_5/sep_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv5_5/sep/scale_1by2"
  type: "Scale"
  bottom: "conv5_5/sep_1by2"
  top: "conv5_5/sep_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu5_5/sep_1by2"
  type: "ReLU"
  bottom: "conv5_5/sep_1by2"
  top: "conv5_5/sep_1by2"
}
layer {
  name: "conv5_6/dw_1by2"
  type: "ConvolutionDepthwise"
  bottom: "conv5_5/sep_1by2"
  top: "conv5_6/dw_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 2
    engine: CAFFE
    kernel_size: 3
    stride: 1
    dilation: 2
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5_6/dw/bn_1by2"
  type: "BatchNorm"
  bottom: "conv5_6/dw_1by2"
  top: "conv5_6/dw_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv5_6/dw/scale_1by2"
  type: "Scale"
  bottom: "conv5_6/dw_1by2"
  top: "conv5_6/dw_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu5_6/dw_1by2"
  type: "ReLU"
  bottom: "conv5_6/dw_1by2"
  top: "conv5_6/dw_1by2"
}
layer {
  name: "conv5_6/sep_1by2"
  type: "Convolution"
  bottom: "conv5_6/dw_1by2"
  top: "conv5_6/sep_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 0
    engine: CAFFE
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5_6/sep/bn_1by2"
  type: "BatchNorm"
  bottom: "conv5_6/sep_1by2"
  top: "conv5_6/sep_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv5_6/sep/scale_1by2"
  type: "Scale"
  bottom: "conv5_6/sep_1by2"
  top: "conv5_6/sep_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu5_6/sep_1by2"
  type: "ReLU"
  bottom: "conv5_6/sep_1by2"
  top: "conv5_6/sep_1by2"
}
layer {
  name: "conv6/dw_1by2"
  type: "ConvolutionDepthwise"
  bottom: "conv5_6/sep_1by2"
  top: "conv6/dw_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 5
    kernel_size: 3
    stride: 1
    engine: CAFFE
    dilation: 5
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv6/dw/bn_1by2"
  type: "BatchNorm"
  bottom: "conv6/dw_1by2"
  top: "conv6/dw_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv6/dw/scale_1by2"
  type: "Scale"
  bottom: "conv6/dw_1by2"
  top: "conv6/dw_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu6/dw_1by2"
  type: "ReLU"
  bottom: "conv6/dw_1by2"
  top: "conv6/dw_1by2"
}
layer {
  name: "conv6/sep_1by2"
  type: "Convolution"
  bottom: "conv6/dw_1by2"
  top: "conv6/sep_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv6/sep/bn_1by2"
  type: "BatchNorm"
  bottom: "conv6/sep_1by2"
  top: "conv6/sep_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv6/sep/scale_1by2"
  type: "Scale"
  bottom: "conv6/sep_1by2"
  top: "conv6/sep_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "relu6/sep_1by2"
  type: "ReLU"
  bottom: "conv6/sep_1by2"
  top: "conv6/sep_1by2"
}
layer {
  name: "concat1_1by2"
  type: "Concat"
  bottom: "conv6/sep_1by2"
  bottom: "conv5_5/sep_1by2"
  top: "concat1_1by2"
  concat_param {
    concat_dim:1
  }
}


layer {
  name: "concat1_1by2/dw"
  type: "ConvolutionDepthwise"
  bottom: "concat1_1by2"
  top: "concat1_1by2/dw"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    bias_term: false
    pad: 7
    kernel_size: 3
    stride: 1
    dilation: 7
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "concat1_1by2/dw/bn"
  type: "BatchNorm"
  bottom: "concat1_1by2/dw"
  top: "concat1_1by2/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "concat1_1by2/dw/scale"
  type: "Scale"
  bottom: "concat1_1by2/dw"
  top: "concat1_1by2/dw"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "reluconcat1_1by2/dw"
  type: "ReLU"
  bottom: "concat1_1by2/dw"
  top: "concat1_1by2/dw"
}
layer {
  name: "concat1_1by2/sep"
  type: "Convolution"
  bottom: "concat1_1by2/dw"
  top: "concat1_1by2/sep"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "concat1_1by2/sep/bn"
  type: "BatchNorm"
  bottom: "concat1_1by2/sep"
  top: "concat1_1by2/sep"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "concat1_1by2/sep/scale"
  type: "Scale"
  bottom: "concat1_1by2/sep"
  top: "concat1_1by2/sep"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "reluconcat1_1by2/sep"
  type: "ReLU"
  bottom: "concat1_1by2/sep"
  top: "concat1_1by2/sep"
}
layer {
  name: "up2_1by2"
  type: "Deconvolution"
  bottom: "concat1_1by2/sep"
  top: "up2_1by2"
  param {
    lr_mult: 0.1
    decay_mult: 1
  }
  convolution_param {
    weight_filler: { type: "bilinear" }
    num_output: 128
    group: 128
    bias_term: false
    kernel_size: 4
    stride: 2
    pad: 1
  }
}
layer {
  name: "concat2_1by2"
  type: "Concat"
  bottom: "up2_1by2"
  bottom: "conv4_1/sep_1by2"
  top: "concat2_1by2"
  concat_param {
    concat_dim:1
  }
}


layer {
  name: "concat2_1by2/dw"
  type: "ConvolutionDepthwise"
  bottom: "concat2_1by2"
  top: "concat2_1by2/dw"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 1
    dilation: 1
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "concat2_1by2/dw/bn"
  type: "BatchNorm"
  bottom: "concat2_1by2/dw"
  top: "concat2_1by2/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "concat2_1by2/dw/scale"
  type: "Scale"
  bottom: "concat2_1by2/dw"
  top: "concat2_1by2/dw"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "reluconcat2_1by2/dw"
  type: "ReLU"
  bottom: "concat2_1by2/dw"
  top: "concat2_1by2/dw"
}
layer {
  name: "concat2_1by2/sep"
  type: "Convolution"
  bottom: "concat2_1by2/dw"
  top: "concat2_1by2/sep"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "concat2_1by2/sep/bn"
  type: "BatchNorm"
  bottom: "concat2_1by2/sep"
  top: "concat2_1by2/sep"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "concat2_1by2/sep/scale"
  type: "Scale"
  bottom: "concat2_1by2/sep"
  top: "concat2_1by2/sep"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "reluconcat2_1by2/sep"
  type: "ReLU"
  bottom: "concat2_1by2/sep"
  top: "concat2_1by2/sep"
}
layer {
  name: "up3_1by2"
  type: "Deconvolution"
  bottom: "concat2_1by2/sep"
  top: "up3_1by2"
  param {
    lr_mult: 0.1
    decay_mult: 1
  }
  convolution_param {
    weight_filler: { type: "bilinear" }
    num_output: 64
    group: 64
    bias_term: false
    kernel_size: 4
    stride: 2
    pad: 1
  }
}
layer {
  name: "concat3_1by2"
  type: "Concat"
  bottom: "up3_1by2"
  bottom: "conv3_1/sep_1by2"
  top: "concat3_1by2"
  concat_param {
    concat_dim:1
  }
}
layer {
  name: "concat3_1by2/dw"
  type: "ConvolutionDepthwise"
  bottom: "concat3_1by2"
  top: "concat3_1by2/dw"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 2
    kernel_size: 3
    stride: 1
    dilation: 2
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "concat3_1by2/dw/bn"
  type: "BatchNorm"
  bottom: "concat3_1by2/dw"
  top: "concat3_1by2/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "concat3_1by2/dw/scale"
  type: "Scale"
  bottom: "concat3_1by2/dw"
  top: "concat3_1by2/dw"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "reluconcat3_1by2/dw"
  type: "ReLU"
  bottom: "concat3_1by2/dw"
  top: "concat3_1by2/dw"
}
layer {
  name: "concat3_1by2/sep"
  type: "Convolution"
  bottom: "concat3_1by2/dw"
  top: "concat3_1by2/sep"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "concat3_1by2/sep/bn"
  type: "BatchNorm"
  bottom: "concat3_1by2/sep"
  top: "concat3_1by2/sep"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "concat3_1by2/sep/scale"
  type: "Scale"
  bottom: "concat3_1by2/sep"
  top: "concat3_1by2/sep"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "reluconcat3_1by2/sep"
  type: "ReLU"
  bottom: "concat3_1by2/sep"
  top: "concat3_1by2/sep"
}
layer {
  name: "up4_1by2"
  type: "Deconvolution"
  bottom: "concat3_1by2/sep"
  top: "up4_1by2"
  param {
    lr_mult: 0.1
    decay_mult: 1
  }
  convolution_param {
    weight_filler: { type: "bilinear" }
    num_output: 32
    group: 32
    bias_term: false
    kernel_size: 4
    stride: 2
    pad: 1
  }
}
layer {
  name: "concat4_1by2"
  type: "Concat"
  bottom: "up4_1by2"
  bottom: "conv2_1/sep_1by2"
  top: "concat4_1by2"
  concat_param {
    concat_dim:1
  }
}
layer {
  name: "concat4_1by2/dw"
  type: "ConvolutionDepthwise"
  bottom: "concat4_1by2"
  top: "concat4_1by2/dw"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 5
    kernel_size: 3
    stride: 1
    dilation: 5
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "concat4_1by2/dw/bn"
  type: "BatchNorm"
  bottom: "concat4_1by2/dw"
  top: "concat4_1by2/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "concat4_1by2/dw/scale"
  type: "Scale"
  bottom: "concat4_1by2/dw"
  top: "concat4_1by2/dw"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "reluconcat4_1by2/dw"
  type: "ReLU"
  bottom: "concat4_1by2/dw"
  top: "concat4_1by2/dw"
}
layer {
  name: "concat4_1by2/sep"
  type: "Convolution"
  bottom: "concat4_1by2/dw"
  top: "concat4_1by2/sep"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "concat4_1by2/sep/bn"
  type: "BatchNorm"
  bottom: "concat4_1by2/sep"
  top: "concat4_1by2/sep"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "concat4_1by2/sep/scale"
  type: "Scale"
  bottom: "concat4_1by2/sep"
  top: "concat4_1by2/sep"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "reluconcat4_1by2/sep"
  type: "ReLU"
  bottom: "concat4_1by2/sep"
  top: "concat4_1by2/sep"
}
layer {
  name: "concat5_1by2"
  type: "Concat"
  bottom: "concat4_1by2/sep"
  bottom: "conv1_1by2"
  top: "concat5_1by2"
  concat_param {
    concat_dim:1
  }
}
layer {
  name: "conv_concat5_1by2"
  type: "Convolution"
  bottom: "concat5_1by2"
  top: "conv_concat5_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 7
    kernel_size: 3
    stride: 1
    dilation: 7
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv_concat5_1by2/bn"
  type: "BatchNorm"
  bottom: "conv_concat5_1by2"
  top: "conv_concat5_1by2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv_concat5_1by2/scale"
  type: "Scale"
  bottom: "conv_concat5_1by2"
  top: "conv_concat5_1by2"
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "reluconv_concat5_1by2"
  type: "ReLU"
  bottom: "conv_concat5_1by2"
  top: "conv_concat5_1by2"
}
layer {
  name: "score_fr_1by2"
  type: "Convolution"
  bottom: "conv_concat5_1by2"
  top: "score_fr_1by2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 1
    engine: CAFFE
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "up5_1by2"
  type: "Deconvolution"
  bottom: "score_fr_1by2"
  top: "up5_1by2"
  param {
    lr_mult: 0.1
    decay_mult: 1
  }
  convolution_param {
    weight_filler: { type: "bilinear" }
    num_output: 1
    group: 1
    bias_term: false
    kernel_size: 4
    stride: 2
    pad: 1
  }
}
layer {
  name: "sigmoid_1by2"
  type: "Sigmoid"
  bottom: "up5_1by2"
  top: "up5_1by2"
}
layer {
  name: "loss_1by2"
  type: "DiceCoefLoss"
  bottom: "up5_1by2"
  bottom: "label"
  top: "loss_1by2"
  loss_weight: 1
  include: { phase: TRAIN }
}
layer {
  name: "accuracy_1by2"
  type: "Accuracy"
  bottom: "up5_1by2"
  bottom: "label"
  top: "IOU_test_1by2"
  include {
    phase: TEST
  }
}

#### auxi loss 16 ####

layer {
  name: "seg_scale1by2"
  type: "Resize"
  bottom: "label"
  top: "seg_scale1by2"
  resize_param {
    function_type: FACTOR_GIVEN
    intepolation_type: NEAREST
    resize_factor: 0.5
  }
  include: { phase: TRAIN }
}

layer {
  name: "concat4_1by2_scale1by2/1x1"
  type: "Convolution"
  bottom: "concat4_1by2"
  top: "concat4_1by2_scale1by2/1x1"
  param { lr_mult: 1.0 decay_mult: 1.0}
  param { lr_mult: 2.0 decay_mult: 0 }
  convolution_param {
    engine: CAFFE
    num_output: 64
    kernel_size: 1 pad: 0 stride: 1
    weight_filler { type: "msra"  } 
    bias_filler { type: "constant" value: 0 }
  }
  include: { phase: TRAIN }
}
layer {
  name: "concat4_1by2_scale1by2/3x3"
  type: "Convolution"
  bottom: "concat4_1by2_scale1by2/1x1"
  top: "concat4_1by2_scale1by2/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    engine: CAFFE
    num_output: 1
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
  include: { phase: TRAIN }
}
layer {
  name: "loss_scale1by2"
  type: "DiceCoefLoss"
  bottom: "concat4_1by2_scale1by2/3x3"
  bottom: "seg_scale1by2"
  top: "loss_scale1by2"
  loss_weight: 0.6
  include: { phase: TRAIN }
}


#### auxi loss 8 ####

layer {
  name: "seg_scale1by4"
  type: "Resize"
  bottom: "label"
  top: "seg_scale1by4"
  resize_param {
    function_type: FACTOR_GIVEN
    intepolation_type: NEAREST
    resize_factor: 0.25
  }
  include: { phase: TRAIN }
}

layer {
  name: "concat4_1by2_scale1by4/1x1"
  type: "Convolution"
  bottom: "concat3_1by2"
  top: "concat4_1by2_scale1by4/1x1"
  param { lr_mult: 1.0 decay_mult: 1.0}
  param { lr_mult: 2.0 decay_mult: 0 }
  convolution_param {
    engine: CAFFE
    num_output: 64
    kernel_size: 1 pad: 0 stride: 1
    weight_filler { type: "msra"  } 
    bias_filler { type: "constant" value: 0 }
  }
  include: { phase: TRAIN }
}
layer {
  name: "concat4_1by2_scale1by4/3x3"
  type: "Convolution"
  bottom: "concat4_1by2_scale1by4/1x1"
  top: "concat4_1by2_scale1by4/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    engine: CAFFE
    num_output: 1
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
  include: { phase: TRAIN }
}
layer {
  name: "loss_scale1by4"
  type: "DiceCoefLoss"
  bottom: "concat4_1by2_scale1by4/3x3"
  bottom: "seg_scale1by4"
  top: "loss_scale1by4"
  loss_weight: 0.3
  include: { phase: TRAIN }
}