name: "retinaface"
input: "blob1"
input_dim: 1
input_dim: 3
input_dim: 640
input_dim: 640
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "blob1"
  top: "conv_blob1"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 2
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm1"
  type: "BatchNorm"
  bottom: "conv_blob1"
  top: "batch_norm_blob1"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale1"
  type: "Scale"
  bottom: "batch_norm_blob1"
  top: "batch_norm_blob1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu61"
  type: "ReLU6"
  bottom: "batch_norm_blob1"
  top: "relu6_blob1"
}
layer {
  name: "max_pool1"
  type: "Pooling"
  bottom: "relu6_blob1"
  top: "max_pool_blob1"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
    pad: 1
    ceil_mode: true
  }
}
layer {
  name: "conv2"
  type: "Convolution"
  bottom: "max_pool_blob1"
  top: "conv_blob2"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 2
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm2"
  type: "BatchNorm"
  bottom: "conv_blob2"
  top: "batch_norm_blob2"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale2"
  type: "Scale"
  bottom: "batch_norm_blob2"
  top: "batch_norm_blob2"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu62"
  type: "ReLU6"
  bottom: "batch_norm_blob2"
  top: "relu6_blob2"
}
layer {
  name: "max_pool2"
  type: "Pooling"
  bottom: "relu6_blob2"
  top: "max_pool_blob2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
    ceil_mode: true
  }
}
layer {
  name: "max_pool3"
  type: "Pooling"
  bottom: "relu6_blob2"
  top: "max_pool_blob3"
  pooling_param {
    pool: MAX
    kernel_size: 5
    stride: 1
    pad: 2
    ceil_mode: true
  }
}
layer {
  name: "cat1"
  type: "Concat"
  bottom: "relu6_blob2"
  bottom: "max_pool_blob2"
  bottom: "max_pool_blob3"
  top: "cat_blob1"
  concat_param {
    axis: 1
  }
}
layer {
  name: "conv3"
  type: "Convolution"
  bottom: "cat_blob1"
  top: "conv_blob3"
  convolution_param {
    num_output: 48
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm3"
  type: "BatchNorm"
  bottom: "conv_blob3"
  top: "batch_norm_blob3"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale3"
  type: "Scale"
  bottom: "batch_norm_blob3"
  top: "batch_norm_blob3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu63"
  type: "ReLU6"
  bottom: "batch_norm_blob3"
  top: "relu6_blob3"
}
layer {
  name: "split1"
  type: "Slice"
  bottom: "relu6_blob3"
  top: "split_blob1"
  top: "split_blob2"
  slice_param {
    slice_point: 24
    axis: 1
  }
}
layer {
  name: "conv4"
  type: "Convolution"
  bottom: "split_blob2"
  top: "conv_blob4"
  convolution_param {
    num_output: 24
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm4"
  type: "BatchNorm"
  bottom: "conv_blob4"
  top: "batch_norm_blob4"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale4"
  type: "Scale"
  bottom: "batch_norm_blob4"
  top: "batch_norm_blob4"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu64"
  type: "ReLU6"
  bottom: "batch_norm_blob4"
  top: "relu6_blob4"
}
layer {
  name: "conv5"
  type: "Convolution"
  bottom: "relu6_blob4"
  top: "conv_blob5"
  convolution_param {
    num_output: 24
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm5"
  type: "BatchNorm"
  bottom: "conv_blob5"
  top: "batch_norm_blob5"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale5"
  type: "Scale"
  bottom: "batch_norm_blob5"
  top: "batch_norm_blob5"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu65"
  type: "ReLU6"
  bottom: "batch_norm_blob5"
  top: "relu6_blob5"
}
layer {
  name: "conv6"
  type: "Convolution"
  bottom: "relu6_blob5"
  top: "conv_blob6"
  convolution_param {
    num_output: 24
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm6"
  type: "BatchNorm"
  bottom: "conv_blob6"
  top: "batch_norm_blob6"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale6"
  type: "Scale"
  bottom: "batch_norm_blob6"
  top: "batch_norm_blob6"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "add1"
  type: "Eltwise"
  bottom: "split_blob2"
  bottom: "batch_norm_blob6"
  top: "add_blob1"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "conv7"
  type: "Convolution"
  bottom: "add_blob1"
  top: "conv_blob7"
  convolution_param {
    num_output: 24
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm7"
  type: "BatchNorm"
  bottom: "conv_blob7"
  top: "batch_norm_blob7"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale7"
  type: "Scale"
  bottom: "batch_norm_blob7"
  top: "batch_norm_blob7"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu66"
  type: "ReLU6"
  bottom: "batch_norm_blob7"
  top: "relu6_blob6"
}
layer {
  name: "conv8"
  type: "Convolution"
  bottom: "relu6_blob6"
  top: "conv_blob8"
  convolution_param {
    num_output: 24
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm8"
  type: "BatchNorm"
  bottom: "conv_blob8"
  top: "batch_norm_blob8"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale8"
  type: "Scale"
  bottom: "batch_norm_blob8"
  top: "batch_norm_blob8"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu67"
  type: "ReLU6"
  bottom: "batch_norm_blob8"
  top: "relu6_blob7"
}
layer {
  name: "conv9"
  type: "Convolution"
  bottom: "relu6_blob7"
  top: "conv_blob9"
  convolution_param {
    num_output: 24
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm9"
  type: "BatchNorm"
  bottom: "conv_blob9"
  top: "batch_norm_blob9"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale9"
  type: "Scale"
  bottom: "batch_norm_blob9"
  top: "batch_norm_blob9"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "add2"
  type: "Eltwise"
  bottom: "add_blob1"
  bottom: "batch_norm_blob9"
  top: "add_blob2"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "cat2"
  type: "Concat"
  bottom: "split_blob1"
  bottom: "add_blob2"
  top: "cat_blob2"
  concat_param {
    axis: 1
  }
}
layer {
  name: "conv10"
  type: "Convolution"
  bottom: "cat_blob2"
  top: "conv_blob10"
  convolution_param {
    num_output: 48
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 2
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm10"
  type: "BatchNorm"
  bottom: "conv_blob10"
  top: "batch_norm_blob10"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale10"
  type: "Scale"
  bottom: "batch_norm_blob10"
  top: "batch_norm_blob10"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu68"
  type: "ReLU6"
  bottom: "batch_norm_blob10"
  top: "relu6_blob8"
}
layer {
  name: "max_pool4"
  type: "Pooling"
  bottom: "relu6_blob8"
  top: "max_pool_blob4"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
    ceil_mode: true
  }
}
layer {
  name: "max_pool5"
  type: "Pooling"
  bottom: "relu6_blob8"
  top: "max_pool_blob5"
  pooling_param {
    pool: MAX
    kernel_size: 5
    stride: 1
    pad: 2
    ceil_mode: true
  }
}
layer {
  name: "cat3"
  type: "Concat"
  bottom: "relu6_blob8"
  bottom: "max_pool_blob4"
  bottom: "max_pool_blob5"
  top: "cat_blob3"
  concat_param {
    axis: 1
  }
}
layer {
  name: "conv11"
  type: "Convolution"
  bottom: "cat_blob3"
  top: "conv_blob11"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm11"
  type: "BatchNorm"
  bottom: "conv_blob11"
  top: "batch_norm_blob11"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale11"
  type: "Scale"
  bottom: "batch_norm_blob11"
  top: "batch_norm_blob11"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu69"
  type: "ReLU6"
  bottom: "batch_norm_blob11"
  top: "relu6_blob9"
}
layer {
  name: "split2"
  type: "Slice"
  bottom: "relu6_blob9"
  top: "split_blob3"
  top: "split_blob4"
  slice_param {
    slice_point: 32
    axis: 1
  }
}
layer {
  name: "conv12"
  type: "Convolution"
  bottom: "split_blob4"
  top: "conv_blob12"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm12"
  type: "BatchNorm"
  bottom: "conv_blob12"
  top: "batch_norm_blob12"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale12"
  type: "Scale"
  bottom: "batch_norm_blob12"
  top: "batch_norm_blob12"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu610"
  type: "ReLU6"
  bottom: "batch_norm_blob12"
  top: "relu6_blob10"
}
layer {
  name: "conv13"
  type: "Convolution"
  bottom: "relu6_blob10"
  top: "conv_blob13"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm13"
  type: "BatchNorm"
  bottom: "conv_blob13"
  top: "batch_norm_blob13"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale13"
  type: "Scale"
  bottom: "batch_norm_blob13"
  top: "batch_norm_blob13"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu611"
  type: "ReLU6"
  bottom: "batch_norm_blob13"
  top: "relu6_blob11"
}
layer {
  name: "conv14"
  type: "Convolution"
  bottom: "relu6_blob11"
  top: "conv_blob14"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm14"
  type: "BatchNorm"
  bottom: "conv_blob14"
  top: "batch_norm_blob14"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale14"
  type: "Scale"
  bottom: "batch_norm_blob14"
  top: "batch_norm_blob14"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "add3"
  type: "Eltwise"
  bottom: "split_blob4"
  bottom: "batch_norm_blob14"
  top: "add_blob3"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "conv15"
  type: "Convolution"
  bottom: "add_blob3"
  top: "conv_blob15"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm15"
  type: "BatchNorm"
  bottom: "conv_blob15"
  top: "batch_norm_blob15"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale15"
  type: "Scale"
  bottom: "batch_norm_blob15"
  top: "batch_norm_blob15"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu612"
  type: "ReLU6"
  bottom: "batch_norm_blob15"
  top: "relu6_blob12"
}
layer {
  name: "conv16"
  type: "Convolution"
  bottom: "relu6_blob12"
  top: "conv_blob16"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm16"
  type: "BatchNorm"
  bottom: "conv_blob16"
  top: "batch_norm_blob16"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale16"
  type: "Scale"
  bottom: "batch_norm_blob16"
  top: "batch_norm_blob16"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu613"
  type: "ReLU6"
  bottom: "batch_norm_blob16"
  top: "relu6_blob13"
}
layer {
  name: "conv17"
  type: "Convolution"
  bottom: "relu6_blob13"
  top: "conv_blob17"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm17"
  type: "BatchNorm"
  bottom: "conv_blob17"
  top: "batch_norm_blob17"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale17"
  type: "Scale"
  bottom: "batch_norm_blob17"
  top: "batch_norm_blob17"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "add4"
  type: "Eltwise"
  bottom: "add_blob3"
  bottom: "batch_norm_blob17"
  top: "add_blob4"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "conv18"
  type: "Convolution"
  bottom: "add_blob4"
  top: "conv_blob18"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm18"
  type: "BatchNorm"
  bottom: "conv_blob18"
  top: "batch_norm_blob18"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale18"
  type: "Scale"
  bottom: "batch_norm_blob18"
  top: "batch_norm_blob18"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu614"
  type: "ReLU6"
  bottom: "batch_norm_blob18"
  top: "relu6_blob14"
}
layer {
  name: "conv19"
  type: "Convolution"
  bottom: "relu6_blob14"
  top: "conv_blob19"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm19"
  type: "BatchNorm"
  bottom: "conv_blob19"
  top: "batch_norm_blob19"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale19"
  type: "Scale"
  bottom: "batch_norm_blob19"
  top: "batch_norm_blob19"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu615"
  type: "ReLU6"
  bottom: "batch_norm_blob19"
  top: "relu6_blob15"
}
layer {
  name: "conv20"
  type: "Convolution"
  bottom: "relu6_blob15"
  top: "conv_blob20"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm20"
  type: "BatchNorm"
  bottom: "conv_blob20"
  top: "batch_norm_blob20"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale20"
  type: "Scale"
  bottom: "batch_norm_blob20"
  top: "batch_norm_blob20"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "add5"
  type: "Eltwise"
  bottom: "add_blob4"
  bottom: "batch_norm_blob20"
  top: "add_blob5"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "cat4"
  type: "Concat"
  bottom: "split_blob3"
  bottom: "add_blob5"
  top: "cat_blob4"
  concat_param {
    axis: 1
  }
}
layer {
  name: "conv21"
  type: "Convolution"
  bottom: "cat_blob4"
  top: "conv_blob21"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 2
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm21"
  type: "BatchNorm"
  bottom: "conv_blob21"
  top: "batch_norm_blob21"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale21"
  type: "Scale"
  bottom: "batch_norm_blob21"
  top: "batch_norm_blob21"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu616"
  type: "ReLU6"
  bottom: "batch_norm_blob21"
  top: "relu6_blob16"
}
layer {
  name: "max_pool6"
  type: "Pooling"
  bottom: "relu6_blob16"
  top: "max_pool_blob6"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
    ceil_mode: true
  }
}
layer {
  name: "max_pool7"
  type: "Pooling"
  bottom: "relu6_blob16"
  top: "max_pool_blob7"
  pooling_param {
    pool: MAX
    kernel_size: 5
    stride: 1
    pad: 2
    ceil_mode: true
  }
}
layer {
  name: "cat5"
  type: "Concat"
  bottom: "relu6_blob16"
  bottom: "max_pool_blob6"
  bottom: "max_pool_blob7"
  top: "cat_blob5"
  concat_param {
    axis: 1
  }
}
layer {
  name: "conv22"
  type: "Convolution"
  bottom: "cat_blob5"
  top: "conv_blob22"
  convolution_param {
    num_output: 96
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm22"
  type: "BatchNorm"
  bottom: "conv_blob22"
  top: "batch_norm_blob22"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale22"
  type: "Scale"
  bottom: "batch_norm_blob22"
  top: "batch_norm_blob22"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu617"
  type: "ReLU6"
  bottom: "batch_norm_blob22"
  top: "relu6_blob17"
}
layer {
  name: "split3"
  type: "Slice"
  bottom: "relu6_blob17"
  top: "split_blob5"
  top: "split_blob6"
  slice_param {
    slice_point: 48
    axis: 1
  }
}
layer {
  name: "conv23"
  type: "Convolution"
  bottom: "split_blob6"
  top: "conv_blob23"
  convolution_param {
    num_output: 48
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm23"
  type: "BatchNorm"
  bottom: "conv_blob23"
  top: "batch_norm_blob23"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale23"
  type: "Scale"
  bottom: "batch_norm_blob23"
  top: "batch_norm_blob23"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu618"
  type: "ReLU6"
  bottom: "batch_norm_blob23"
  top: "relu6_blob18"
}
layer {
  name: "conv24"
  type: "Convolution"
  bottom: "relu6_blob18"
  top: "conv_blob24"
  convolution_param {
    num_output: 48
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm24"
  type: "BatchNorm"
  bottom: "conv_blob24"
  top: "batch_norm_blob24"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale24"
  type: "Scale"
  bottom: "batch_norm_blob24"
  top: "batch_norm_blob24"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu619"
  type: "ReLU6"
  bottom: "batch_norm_blob24"
  top: "relu6_blob19"
}
layer {
  name: "conv25"
  type: "Convolution"
  bottom: "relu6_blob19"
  top: "conv_blob25"
  convolution_param {
    num_output: 48
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm25"
  type: "BatchNorm"
  bottom: "conv_blob25"
  top: "batch_norm_blob25"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale25"
  type: "Scale"
  bottom: "batch_norm_blob25"
  top: "batch_norm_blob25"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "add6"
  type: "Eltwise"
  bottom: "split_blob6"
  bottom: "batch_norm_blob25"
  top: "add_blob6"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "conv26"
  type: "Convolution"
  bottom: "add_blob6"
  top: "conv_blob26"
  convolution_param {
    num_output: 48
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm26"
  type: "BatchNorm"
  bottom: "conv_blob26"
  top: "batch_norm_blob26"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale26"
  type: "Scale"
  bottom: "batch_norm_blob26"
  top: "batch_norm_blob26"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu620"
  type: "ReLU6"
  bottom: "batch_norm_blob26"
  top: "relu6_blob20"
}
layer {
  name: "conv27"
  type: "Convolution"
  bottom: "relu6_blob20"
  top: "conv_blob27"
  convolution_param {
    num_output: 48
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm27"
  type: "BatchNorm"
  bottom: "conv_blob27"
  top: "batch_norm_blob27"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale27"
  type: "Scale"
  bottom: "batch_norm_blob27"
  top: "batch_norm_blob27"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu621"
  type: "ReLU6"
  bottom: "batch_norm_blob27"
  top: "relu6_blob21"
}
layer {
  name: "conv28"
  type: "Convolution"
  bottom: "relu6_blob21"
  top: "conv_blob28"
  convolution_param {
    num_output: 48
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm28"
  type: "BatchNorm"
  bottom: "conv_blob28"
  top: "batch_norm_blob28"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale28"
  type: "Scale"
  bottom: "batch_norm_blob28"
  top: "batch_norm_blob28"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "add7"
  type: "Eltwise"
  bottom: "add_blob6"
  bottom: "batch_norm_blob28"
  top: "add_blob7"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "conv29"
  type: "Convolution"
  bottom: "add_blob7"
  top: "conv_blob29"
  convolution_param {
    num_output: 48
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm29"
  type: "BatchNorm"
  bottom: "conv_blob29"
  top: "batch_norm_blob29"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale29"
  type: "Scale"
  bottom: "batch_norm_blob29"
  top: "batch_norm_blob29"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu622"
  type: "ReLU6"
  bottom: "batch_norm_blob29"
  top: "relu6_blob22"
}
layer {
  name: "conv30"
  type: "Convolution"
  bottom: "relu6_blob22"
  top: "conv_blob30"
  convolution_param {
    num_output: 48
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm30"
  type: "BatchNorm"
  bottom: "conv_blob30"
  top: "batch_norm_blob30"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale30"
  type: "Scale"
  bottom: "batch_norm_blob30"
  top: "batch_norm_blob30"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu623"
  type: "ReLU6"
  bottom: "batch_norm_blob30"
  top: "relu6_blob23"
}
layer {
  name: "conv31"
  type: "Convolution"
  bottom: "relu6_blob23"
  top: "conv_blob31"
  convolution_param {
    num_output: 48
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm31"
  type: "BatchNorm"
  bottom: "conv_blob31"
  top: "batch_norm_blob31"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale31"
  type: "Scale"
  bottom: "batch_norm_blob31"
  top: "batch_norm_blob31"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "add8"
  type: "Eltwise"
  bottom: "add_blob7"
  bottom: "batch_norm_blob31"
  top: "add_blob8"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "conv32"
  type: "Convolution"
  bottom: "add_blob8"
  top: "conv_blob32"
  convolution_param {
    num_output: 48
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm32"
  type: "BatchNorm"
  bottom: "conv_blob32"
  top: "batch_norm_blob32"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale32"
  type: "Scale"
  bottom: "batch_norm_blob32"
  top: "batch_norm_blob32"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu624"
  type: "ReLU6"
  bottom: "batch_norm_blob32"
  top: "relu6_blob24"
}
layer {
  name: "conv33"
  type: "Convolution"
  bottom: "relu6_blob24"
  top: "conv_blob33"
  convolution_param {
    num_output: 48
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm33"
  type: "BatchNorm"
  bottom: "conv_blob33"
  top: "batch_norm_blob33"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale33"
  type: "Scale"
  bottom: "batch_norm_blob33"
  top: "batch_norm_blob33"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu625"
  type: "ReLU6"
  bottom: "batch_norm_blob33"
  top: "relu6_blob25"
}
layer {
  name: "conv34"
  type: "Convolution"
  bottom: "relu6_blob25"
  top: "conv_blob34"
  convolution_param {
    num_output: 48
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm34"
  type: "BatchNorm"
  bottom: "conv_blob34"
  top: "batch_norm_blob34"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale34"
  type: "Scale"
  bottom: "batch_norm_blob34"
  top: "batch_norm_blob34"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "add9"
  type: "Eltwise"
  bottom: "add_blob8"
  bottom: "batch_norm_blob34"
  top: "add_blob9"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "cat6"
  type: "Concat"
  bottom: "split_blob5"
  bottom: "add_blob9"
  top: "cat_blob6"
  concat_param {
    axis: 1
  }
}
layer {
  name: "conv35"
  type: "Convolution"
  bottom: "cat_blob6"
  top: "conv_blob35"
  convolution_param {
    num_output: 96
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 2
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm35"
  type: "BatchNorm"
  bottom: "conv_blob35"
  top: "batch_norm_blob35"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale35"
  type: "Scale"
  bottom: "batch_norm_blob35"
  top: "batch_norm_blob35"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu626"
  type: "ReLU6"
  bottom: "batch_norm_blob35"
  top: "relu6_blob26"
}
layer {
  name: "max_pool8"
  type: "Pooling"
  bottom: "relu6_blob26"
  top: "max_pool_blob8"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
    ceil_mode: true
  }
}
layer {
  name: "max_pool9"
  type: "Pooling"
  bottom: "relu6_blob26"
  top: "max_pool_blob9"
  pooling_param {
    pool: MAX
    kernel_size: 5
    stride: 1
    pad: 2
    ceil_mode: true
  }
}
layer {
  name: "cat7"
  type: "Concat"
  bottom: "relu6_blob26"
  bottom: "max_pool_blob8"
  bottom: "max_pool_blob9"
  top: "cat_blob7"
  concat_param {
    axis: 1
  }
}
layer {
  name: "conv36"
  type: "Convolution"
  bottom: "cat_blob7"
  top: "conv_blob36"
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm36"
  type: "BatchNorm"
  bottom: "conv_blob36"
  top: "batch_norm_blob36"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale36"
  type: "Scale"
  bottom: "batch_norm_blob36"
  top: "batch_norm_blob36"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu627"
  type: "ReLU6"
  bottom: "batch_norm_blob36"
  top: "relu6_blob27"
}
layer {
  name: "split4"
  type: "Slice"
  bottom: "relu6_blob27"
  top: "split_blob7"
  top: "split_blob8"
  slice_param {
    slice_point: 64
    axis: 1
  }
}
layer {
  name: "conv37"
  type: "Convolution"
  bottom: "split_blob8"
  top: "conv_blob37"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm37"
  type: "BatchNorm"
  bottom: "conv_blob37"
  top: "batch_norm_blob37"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale37"
  type: "Scale"
  bottom: "batch_norm_blob37"
  top: "batch_norm_blob37"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu628"
  type: "ReLU6"
  bottom: "batch_norm_blob37"
  top: "relu6_blob28"
}
layer {
  name: "conv38"
  type: "Convolution"
  bottom: "relu6_blob28"
  top: "conv_blob38"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm38"
  type: "BatchNorm"
  bottom: "conv_blob38"
  top: "batch_norm_blob38"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale38"
  type: "Scale"
  bottom: "batch_norm_blob38"
  top: "batch_norm_blob38"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu629"
  type: "ReLU6"
  bottom: "batch_norm_blob38"
  top: "relu6_blob29"
}
layer {
  name: "conv39"
  type: "Convolution"
  bottom: "relu6_blob29"
  top: "conv_blob39"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm39"
  type: "BatchNorm"
  bottom: "conv_blob39"
  top: "batch_norm_blob39"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale39"
  type: "Scale"
  bottom: "batch_norm_blob39"
  top: "batch_norm_blob39"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "add10"
  type: "Eltwise"
  bottom: "split_blob8"
  bottom: "batch_norm_blob39"
  top: "add_blob10"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "conv40"
  type: "Convolution"
  bottom: "add_blob10"
  top: "conv_blob40"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm40"
  type: "BatchNorm"
  bottom: "conv_blob40"
  top: "batch_norm_blob40"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale40"
  type: "Scale"
  bottom: "batch_norm_blob40"
  top: "batch_norm_blob40"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu630"
  type: "ReLU6"
  bottom: "batch_norm_blob40"
  top: "relu6_blob30"
}
layer {
  name: "conv41"
  type: "Convolution"
  bottom: "relu6_blob30"
  top: "conv_blob41"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm41"
  type: "BatchNorm"
  bottom: "conv_blob41"
  top: "batch_norm_blob41"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale41"
  type: "Scale"
  bottom: "batch_norm_blob41"
  top: "batch_norm_blob41"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu631"
  type: "ReLU6"
  bottom: "batch_norm_blob41"
  top: "relu6_blob31"
}
layer {
  name: "conv42"
  type: "Convolution"
  bottom: "relu6_blob31"
  top: "conv_blob42"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm42"
  type: "BatchNorm"
  bottom: "conv_blob42"
  top: "batch_norm_blob42"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale42"
  type: "Scale"
  bottom: "batch_norm_blob42"
  top: "batch_norm_blob42"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "add11"
  type: "Eltwise"
  bottom: "add_blob10"
  bottom: "batch_norm_blob42"
  top: "add_blob11"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "cat8"
  type: "Concat"
  bottom: "split_blob7"
  bottom: "add_blob11"
  top: "cat_blob8"
  concat_param {
    axis: 1
  }
}
layer {
  name: "conv43"
  type: "Convolution"
  bottom: "cat_blob2"
  top: "conv_blob43"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm43"
  type: "BatchNorm"
  bottom: "conv_blob43"
  top: "batch_norm_blob43"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale43"
  type: "Scale"
  bottom: "batch_norm_blob43"
  top: "batch_norm_blob43"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu632"
  type: "ReLU6"
  bottom: "batch_norm_blob43"
  top: "relu6_blob32"
}
layer {
  name: "conv44"
  type: "Convolution"
  bottom: "cat_blob4"
  top: "conv_blob44"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm44"
  type: "BatchNorm"
  bottom: "conv_blob44"
  top: "batch_norm_blob44"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale44"
  type: "Scale"
  bottom: "batch_norm_blob44"
  top: "batch_norm_blob44"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu633"
  type: "ReLU6"
  bottom: "batch_norm_blob44"
  top: "relu6_blob33"
}
layer {
  name: "conv45"
  type: "Convolution"
  bottom: "cat_blob6"
  top: "conv_blob45"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm45"
  type: "BatchNorm"
  bottom: "conv_blob45"
  top: "batch_norm_blob45"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale45"
  type: "Scale"
  bottom: "batch_norm_blob45"
  top: "batch_norm_blob45"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu634"
  type: "ReLU6"
  bottom: "batch_norm_blob45"
  top: "relu6_blob34"
}
layer {
  name: "conv46"
  type: "Convolution"
  bottom: "cat_blob8"
  top: "conv_blob46"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm46"
  type: "BatchNorm"
  bottom: "conv_blob46"
  top: "batch_norm_blob46"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale46"
  type: "Scale"
  bottom: "batch_norm_blob46"
  top: "batch_norm_blob46"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu635"
  type: "ReLU6"
  bottom: "batch_norm_blob46"
  top: "relu6_blob35"
}
layer {
  name: "upsample1"
  type: "Deconvolution"
  bottom: "relu6_blob35"
  top: "upsample_blob1"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 2
    group: 64
    stride: 2
    weight_filler {
      type: "xavier"
    }
    engine: CAFFE
    dilation: 1
  }
}
layer {
  name: "crop1"
  type: "Crop"
  bottom: "upsample_blob1"
  bottom: "relu6_blob34"
  top: "crop0"
  crop_param { 
    axis: 2    
    offset: 0 
    offset: 0
  } 
}
layer {
  name: "add12"
  type: "Eltwise"
  bottom: "relu6_blob34"
  bottom: "crop0"
  top: "add_blob12"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "upsample2"
  type: "Deconvolution"
  bottom: "relu6_blob34"
  top: "upsample_blob2"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 2
    group: 64
    stride: 2
    weight_filler {
      type: "xavier"
    }
    engine: CAFFE
    dilation: 1
  }
}
layer {
  name: "crop2"
  type: "Crop"
  bottom: "upsample_blob2"
  bottom: "relu6_blob33"
  top: "crop2"
  crop_param { 
    axis: 2    
    offset: 0 
    offset: 0
  } 
}
layer {
  name: "add13"
  type: "Eltwise"
  bottom: "crop2"
  bottom: "relu6_blob33"
  top: "add_blob13"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "upsample3"
  type: "Deconvolution"
  bottom: "relu6_blob33"
  top: "upsample_blob3"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 2
    group: 64
    stride: 2
    weight_filler {
      type: "xavier"
    }
    engine: CAFFE
    dilation: 1
  }
}
layer {
  name: "crop3"
  type: "Crop"
  bottom: "upsample_blob3"
  bottom: "relu6_blob32"
  top: "crop3"
  crop_param { 
    axis: 2    
    offset: 0 
    offset: 0
 } 
}
layer {
  name: "add14"
  type: "Eltwise"
  bottom: "crop3"
  bottom: "relu6_blob32"
  top: "add_blob14"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "conv47"
  type: "Convolution"
  bottom: "add_blob14"
  top: "conv_blob47"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm47"
  type: "BatchNorm"
  bottom: "conv_blob47"
  top: "batch_norm_blob47"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale47"
  type: "Scale"
  bottom: "batch_norm_blob47"
  top: "batch_norm_blob47"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu636"
  type: "ReLU6"
  bottom: "batch_norm_blob47"
  top: "relu6_blob36"
}
layer {
  name: "conv48"
  type: "Convolution"
  bottom: "relu6_blob36"
  top: "conv_blob48"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm48"
  type: "BatchNorm"
  bottom: "conv_blob48"
  top: "batch_norm_blob48"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale48"
  type: "Scale"
  bottom: "batch_norm_blob48"
  top: "batch_norm_blob48"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu637"
  type: "ReLU6"
  bottom: "batch_norm_blob48"
  top: "relu6_blob37"
}
layer {
  name: "conv49"
  type: "Convolution"
  bottom: "relu6_blob37"
  top: "conv_blob49"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm49"
  type: "BatchNorm"
  bottom: "conv_blob49"
  top: "batch_norm_blob49"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale49"
  type: "Scale"
  bottom: "batch_norm_blob49"
  top: "batch_norm_blob49"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu638"
  type: "ReLU6"
  bottom: "batch_norm_blob49"
  top: "relu6_blob38"
}
layer {
  name: "conv50"
  type: "Convolution"
  bottom: "relu6_blob38"
  top: "conv_blob50"
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm50"
  type: "BatchNorm"
  bottom: "conv_blob50"
  top: "batch_norm_blob50"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale50"
  type: "Scale"
  bottom: "batch_norm_blob50"
  top: "batch_norm_blob50"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu639"
  type: "ReLU6"
  bottom: "batch_norm_blob50"
  top: "relu6_blob39"
}
layer {
  name: "conv51"
  type: "Convolution"
  bottom: "relu6_blob39"
  top: "conv_blob51"
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm51"
  type: "BatchNorm"
  bottom: "conv_blob51"
  top: "batch_norm_blob51"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale51"
  type: "Scale"
  bottom: "batch_norm_blob51"
  top: "batch_norm_blob51"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu640"
  type: "ReLU6"
  bottom: "batch_norm_blob51"
  top: "relu6_blob40"
}
layer {
  name: "conv52"
  type: "Convolution"
  bottom: "relu6_blob40"
  top: "conv_blob52"
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm52"
  type: "BatchNorm"
  bottom: "conv_blob52"
  top: "batch_norm_blob52"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale52"
  type: "Scale"
  bottom: "batch_norm_blob52"
  top: "batch_norm_blob52"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu641"
  type: "ReLU6"
  bottom: "batch_norm_blob52"
  top: "relu6_blob41"
}
layer {
  name: "cat9"
  type: "Concat"
  bottom: "relu6_blob37"
  bottom: "relu6_blob39"
  bottom: "relu6_blob41"
  top: "cat_blob9"
  concat_param {
    axis: 1
  }
}
layer {
  name: "conv53"
  type: "Convolution"
  bottom: "add_blob13"
  top: "conv_blob53"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm53"
  type: "BatchNorm"
  bottom: "conv_blob53"
  top: "batch_norm_blob53"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale53"
  type: "Scale"
  bottom: "batch_norm_blob53"
  top: "batch_norm_blob53"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu642"
  type: "ReLU6"
  bottom: "batch_norm_blob53"
  top: "relu6_blob42"
}
layer {
  name: "conv54"
  type: "Convolution"
  bottom: "relu6_blob42"
  top: "conv_blob54"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm54"
  type: "BatchNorm"
  bottom: "conv_blob54"
  top: "batch_norm_blob54"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale54"
  type: "Scale"
  bottom: "batch_norm_blob54"
  top: "batch_norm_blob54"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu643"
  type: "ReLU6"
  bottom: "batch_norm_blob54"
  top: "relu6_blob43"
}
layer {
  name: "conv55"
  type: "Convolution"
  bottom: "relu6_blob43"
  top: "conv_blob55"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm55"
  type: "BatchNorm"
  bottom: "conv_blob55"
  top: "batch_norm_blob55"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale55"
  type: "Scale"
  bottom: "batch_norm_blob55"
  top: "batch_norm_blob55"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu644"
  type: "ReLU6"
  bottom: "batch_norm_blob55"
  top: "relu6_blob44"
}
layer {
  name: "conv56"
  type: "Convolution"
  bottom: "relu6_blob44"
  top: "conv_blob56"
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm56"
  type: "BatchNorm"
  bottom: "conv_blob56"
  top: "batch_norm_blob56"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale56"
  type: "Scale"
  bottom: "batch_norm_blob56"
  top: "batch_norm_blob56"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu645"
  type: "ReLU6"
  bottom: "batch_norm_blob56"
  top: "relu6_blob45"
}
layer {
  name: "conv57"
  type: "Convolution"
  bottom: "relu6_blob45"
  top: "conv_blob57"
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm57"
  type: "BatchNorm"
  bottom: "conv_blob57"
  top: "batch_norm_blob57"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale57"
  type: "Scale"
  bottom: "batch_norm_blob57"
  top: "batch_norm_blob57"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu646"
  type: "ReLU6"
  bottom: "batch_norm_blob57"
  top: "relu6_blob46"
}
layer {
  name: "conv58"
  type: "Convolution"
  bottom: "relu6_blob46"
  top: "conv_blob58"
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm58"
  type: "BatchNorm"
  bottom: "conv_blob58"
  top: "batch_norm_blob58"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale58"
  type: "Scale"
  bottom: "batch_norm_blob58"
  top: "batch_norm_blob58"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu647"
  type: "ReLU6"
  bottom: "batch_norm_blob58"
  top: "relu6_blob47"
}
layer {
  name: "cat10"
  type: "Concat"
  bottom: "relu6_blob43"
  bottom: "relu6_blob45"
  bottom: "relu6_blob47"
  top: "cat_blob10"
  concat_param {
    axis: 1
  }
}
layer {
  name: "conv59"
  type: "Convolution"
  bottom: "add_blob12"
  top: "conv_blob59"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm59"
  type: "BatchNorm"
  bottom: "conv_blob59"
  top: "batch_norm_blob59"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale59"
  type: "Scale"
  bottom: "batch_norm_blob59"
  top: "batch_norm_blob59"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu648"
  type: "ReLU6"
  bottom: "batch_norm_blob59"
  top: "relu6_blob48"
}
layer {
  name: "conv60"
  type: "Convolution"
  bottom: "relu6_blob48"
  top: "conv_blob60"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm60"
  type: "BatchNorm"
  bottom: "conv_blob60"
  top: "batch_norm_blob60"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale60"
  type: "Scale"
  bottom: "batch_norm_blob60"
  top: "batch_norm_blob60"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu649"
  type: "ReLU6"
  bottom: "batch_norm_blob60"
  top: "relu6_blob49"
}
layer {
  name: "conv61"
  type: "Convolution"
  bottom: "relu6_blob49"
  top: "conv_blob61"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm61"
  type: "BatchNorm"
  bottom: "conv_blob61"
  top: "batch_norm_blob61"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale61"
  type: "Scale"
  bottom: "batch_norm_blob61"
  top: "batch_norm_blob61"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu650"
  type: "ReLU6"
  bottom: "batch_norm_blob61"
  top: "relu6_blob50"
}
layer {
  name: "conv62"
  type: "Convolution"
  bottom: "relu6_blob50"
  top: "conv_blob62"
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm62"
  type: "BatchNorm"
  bottom: "conv_blob62"
  top: "batch_norm_blob62"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale62"
  type: "Scale"
  bottom: "batch_norm_blob62"
  top: "batch_norm_blob62"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu651"
  type: "ReLU6"
  bottom: "batch_norm_blob62"
  top: "relu6_blob51"
}
layer {
  name: "conv63"
  type: "Convolution"
  bottom: "relu6_blob51"
  top: "conv_blob63"
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm63"
  type: "BatchNorm"
  bottom: "conv_blob63"
  top: "batch_norm_blob63"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale63"
  type: "Scale"
  bottom: "batch_norm_blob63"
  top: "batch_norm_blob63"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu652"
  type: "ReLU6"
  bottom: "batch_norm_blob63"
  top: "relu6_blob52"
}
layer {
  name: "conv64"
  type: "Convolution"
  bottom: "relu6_blob52"
  top: "conv_blob64"
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm64"
  type: "BatchNorm"
  bottom: "conv_blob64"
  top: "batch_norm_blob64"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale64"
  type: "Scale"
  bottom: "batch_norm_blob64"
  top: "batch_norm_blob64"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu653"
  type: "ReLU6"
  bottom: "batch_norm_blob64"
  top: "relu6_blob53"
}
layer {
  name: "cat11"
  type: "Concat"
  bottom: "relu6_blob49"
  bottom: "relu6_blob51"
  bottom: "relu6_blob53"
  top: "cat_blob11"
  concat_param {
    axis: 1
  }
}
layer {
  name: "conv65"
  type: "Convolution"
  bottom: "relu6_blob35"
  top: "conv_blob65"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm65"
  type: "BatchNorm"
  bottom: "conv_blob65"
  top: "batch_norm_blob65"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale65"
  type: "Scale"
  bottom: "batch_norm_blob65"
  top: "batch_norm_blob65"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu654"
  type: "ReLU6"
  bottom: "batch_norm_blob65"
  top: "relu6_blob54"
}
layer {
  name: "conv66"
  type: "Convolution"
  bottom: "relu6_blob54"
  top: "conv_blob66"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm66"
  type: "BatchNorm"
  bottom: "conv_blob66"
  top: "batch_norm_blob66"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale66"
  type: "Scale"
  bottom: "batch_norm_blob66"
  top: "batch_norm_blob66"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu655"
  type: "ReLU6"
  bottom: "batch_norm_blob66"
  top: "relu6_blob55"
}
layer {
  name: "conv67"
  type: "Convolution"
  bottom: "relu6_blob55"
  top: "conv_blob67"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm67"
  type: "BatchNorm"
  bottom: "conv_blob67"
  top: "batch_norm_blob67"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale67"
  type: "Scale"
  bottom: "batch_norm_blob67"
  top: "batch_norm_blob67"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu656"
  type: "ReLU6"
  bottom: "batch_norm_blob67"
  top: "relu6_blob56"
}
layer {
  name: "conv68"
  type: "Convolution"
  bottom: "relu6_blob56"
  top: "conv_blob68"
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm68"
  type: "BatchNorm"
  bottom: "conv_blob68"
  top: "batch_norm_blob68"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale68"
  type: "Scale"
  bottom: "batch_norm_blob68"
  top: "batch_norm_blob68"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu657"
  type: "ReLU6"
  bottom: "batch_norm_blob68"
  top: "relu6_blob57"
}
layer {
  name: "conv69"
  type: "Convolution"
  bottom: "relu6_blob57"
  top: "conv_blob69"
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm69"
  type: "BatchNorm"
  bottom: "conv_blob69"
  top: "batch_norm_blob69"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale69"
  type: "Scale"
  bottom: "batch_norm_blob69"
  top: "batch_norm_blob69"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu658"
  type: "ReLU6"
  bottom: "batch_norm_blob69"
  top: "relu6_blob58"
}
layer {
  name: "conv70"
  type: "Convolution"
  bottom: "relu6_blob58"
  top: "conv_blob70"
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm70"
  type: "BatchNorm"
  bottom: "conv_blob70"
  top: "batch_norm_blob70"
  batch_norm_param {
    use_global_stats: true
    eps: 9.9999997e-06
  }
}
layer {
  name: "bn_scale70"
  type: "Scale"
  bottom: "batch_norm_blob70"
  top: "batch_norm_blob70"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu659"
  type: "ReLU6"
  bottom: "batch_norm_blob70"
  top: "relu6_blob59"
}
layer {
  name: "cat12"
  type: "Concat"
  bottom: "relu6_blob55"
  bottom: "relu6_blob57"
  bottom: "relu6_blob59"
  top: "cat_blob12"
  concat_param {
    axis: 1
  }
}
layer {
  name: "conv71"
  type: "Convolution"
  bottom: "cat_blob9"
  top: "conv_blob71"
  convolution_param {
    num_output: 8
    bias_term: true
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
    dilation: 1
  }
}
layer {
  name: "conv72"
  type: "Convolution"
  bottom: "cat_blob9"
  top: "conv_blob72"
  convolution_param {
    num_output: 16
    bias_term: true
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
    dilation: 1
  }
}
layer {
  name: "conv73"
  type: "Convolution"
  bottom: "cat_blob9"
  top: "conv_blob73"
  convolution_param {
    num_output: 40
    bias_term: true
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
    dilation: 1
  }
}
layer {
  name: "conv74"
  type: "Convolution"
  bottom: "cat_blob10"
  top: "conv_blob74"
  convolution_param {
    num_output: 6
    bias_term: true
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
    dilation: 1
  }
}
layer {
  name: "conv75"
  type: "Convolution"
  bottom: "cat_blob10"
  top: "conv_blob75"
  convolution_param {
    num_output: 12
    bias_term: true
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
    dilation: 1
  }
}
layer {
  name: "conv76"
  type: "Convolution"
  bottom: "cat_blob10"
  top: "conv_blob76"
  convolution_param {
    num_output: 30
    bias_term: true
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
    dilation: 1
  }
}
layer {
  name: "conv77"
  type: "Convolution"
  bottom: "cat_blob11"
  top: "conv_blob77"
  convolution_param {
    num_output: 6
    bias_term: true
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
    dilation: 1
  }
}
layer {
  name: "conv78"
  type: "Convolution"
  bottom: "cat_blob11"
  top: "conv_blob78"
  convolution_param {
    num_output: 12
    bias_term: true
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
    dilation: 1
  }
}
layer {
  name: "conv79"
  type: "Convolution"
  bottom: "cat_blob11"
  top: "conv_blob79"
  convolution_param {
    num_output: 30
    bias_term: true
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
    dilation: 1
  }
}
layer {
  name: "conv80"
  type: "Convolution"
  bottom: "cat_blob12"
  top: "conv_blob80"
  convolution_param {
    num_output: 4
    bias_term: true
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
    dilation: 1
  }
}
layer {
  name: "conv81"
  type: "Convolution"
  bottom: "cat_blob12"
  top: "conv_blob81"
  convolution_param {
    num_output: 8
    bias_term: true
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
    dilation: 1
  }
}
layer {
  name: "conv82"
  type: "Convolution"
  bottom: "cat_blob12"
  top: "conv_blob82"
  convolution_param {
    num_output: 20
    bias_term: true
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
    dilation: 1
  }
}