layer {
  name: "actual_input_1"
  type: "Input"
  top: "actual_input_1"
  input_param {
    shape {
      dim: 1
      dim: 3
      dim: 512
      dim: 512
    }
  }
}

layer {
  name: "power-data"
  type: "Power"
  bottom: "actual_input_1"
  top: "power-data"
  power_param {
    scale: 0.00390625
    shift: -0.44140625
  }
}
layer {
  name: "714"
  type: "Convolution"
  bottom: "power-data"
  top: "714"
  convolution_param {
    num_output: 32
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 2
    stride_w: 2
    dilation: 1
  }
}
layer {
  name: "715_bn"
  type: "BatchNorm"
  bottom: "714"
  top: "715"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "715"
  type: "Scale"
  bottom: "715"
  top: "715"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "716"
  type: "ReLU"
  bottom: "715"
  top: "716"
}
layer {
  name: "717"
  type: "Convolution"
  bottom: "716"
  top: "717"
  convolution_param {
    num_output: 16
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "718_bn"
  type: "BatchNorm"
  bottom: "717"
  top: "718"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "718"
  type: "Scale"
  bottom: "718"
  top: "718"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "719"
  type: "ReLU"
  bottom: "718"
  top: "719"
}
layer {
  name: "720"
  type: "Convolution"
  bottom: "719"
  top: "720"
  convolution_param {
    num_output: 32
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 2
    stride_w: 2
    dilation: 1
  }
}
layer {
  name: "721_bn"
  type: "BatchNorm"
  bottom: "720"
  top: "721"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "721"
  type: "Scale"
  bottom: "721"
  top: "721"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "722"
  type: "ReLU"
  bottom: "721"
  top: "722"
}
layer {
  name: "723"
  type: "Pooling"
  bottom: "716"
  top: "723"
  pooling_param {
    pool: MAX
    kernel_h: 2
    kernel_w: 2
    stride_h: 2
    stride_w: 2
    pad_h: 0
    pad_w: 0
  }
}
layer {
  name: "724"
  type: "Concat"
  bottom: "722"
  bottom: "723"
  top: "724"
  concat_param {
    axis: 1
  }
}
layer {
  name: "725"
  type: "Convolution"
  bottom: "724"
  top: "725"
  convolution_param {
    num_output: 20
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "726_bn"
  type: "BatchNorm"
  bottom: "725"
  top: "726"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "726"
  type: "Scale"
  bottom: "726"
  top: "726"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "727"
  type: "ReLU"
  bottom: "726"
  top: "727"
}
layer {
  name: "728"
  type: "Convolution"
  bottom: "727"
  top: "728"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "729_bn"
  type: "BatchNorm"
  bottom: "728"
  top: "729"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "729"
  type: "Scale"
  bottom: "729"
  top: "729"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "730"
  type: "ReLU"
  bottom: "729"
  top: "730"
}
layer {
  name: "731"
  type: "Convolution"
  bottom: "730"
  top: "731"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "732_bn"
  type: "BatchNorm"
  bottom: "731"
  top: "732"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "732"
  type: "Scale"
  bottom: "732"
  top: "732"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "733"
  type: "ReLU"
  bottom: "732"
  top: "733"
}
layer {
  name: "734"
  type: "Convolution"
  bottom: "727"
  top: "734"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "735_bn"
  type: "BatchNorm"
  bottom: "734"
  top: "735"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "735"
  type: "Scale"
  bottom: "735"
  top: "735"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "736"
  type: "ReLU"
  bottom: "735"
  top: "736"
}
layer {
  name: "737"
  type: "Convolution"
  bottom: "736"
  top: "737"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "738_bn"
  type: "BatchNorm"
  bottom: "737"
  top: "738"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "738"
  type: "Scale"
  bottom: "738"
  top: "738"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "739"
  type: "ReLU"
  bottom: "738"
  top: "739"
}
layer {
  name: "740"
  type: "Convolution"
  bottom: "739"
  top: "740"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "741_bn"
  type: "BatchNorm"
  bottom: "740"
  top: "741"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "741"
  type: "Scale"
  bottom: "741"
  top: "741"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "742"
  type: "ReLU"
  bottom: "741"
  top: "742"
}
layer {
  name: "743"
  type: "Concat"
  bottom: "727"
  bottom: "733"
  bottom: "742"
  top: "743"
  concat_param {
    axis: 1
  }
}
layer {
  name: "744"
  type: "Convolution"
  bottom: "743"
  top: "744"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "745_bn"
  type: "BatchNorm"
  bottom: "744"
  top: "745"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "745"
  type: "Scale"
  bottom: "745"
  top: "745"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "746"
  type: "ReLU"
  bottom: "745"
  top: "746"
}
layer {
  name: "747"
  type: "Convolution"
  bottom: "746"
  top: "747"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "748_bn"
  type: "BatchNorm"
  bottom: "747"
  top: "748"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "748"
  type: "Scale"
  bottom: "748"
  top: "748"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "749"
  type: "ReLU"
  bottom: "748"
  top: "749"
}
layer {
  name: "750"
  type: "Convolution"
  bottom: "743"
  top: "750"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "751_bn"
  type: "BatchNorm"
  bottom: "750"
  top: "751"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "751"
  type: "Scale"
  bottom: "751"
  top: "751"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "752"
  type: "ReLU"
  bottom: "751"
  top: "752"
}
layer {
  name: "753"
  type: "Convolution"
  bottom: "752"
  top: "753"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "754_bn"
  type: "BatchNorm"
  bottom: "753"
  top: "754"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "754"
  type: "Scale"
  bottom: "754"
  top: "754"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "755"
  type: "ReLU"
  bottom: "754"
  top: "755"
}
layer {
  name: "756"
  type: "Convolution"
  bottom: "755"
  top: "756"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "757_bn"
  type: "BatchNorm"
  bottom: "756"
  top: "757"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "757"
  type: "Scale"
  bottom: "757"
  top: "757"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "758"
  type: "ReLU"
  bottom: "757"
  top: "758"
}
layer {
  name: "759"
  type: "Concat"
  bottom: "743"
  bottom: "749"
  bottom: "758"
  top: "759"
  concat_param {
    axis: 1
  }
}
layer {
  name: "760"
  type: "Convolution"
  bottom: "759"
  top: "760"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "761_bn"
  type: "BatchNorm"
  bottom: "760"
  top: "761"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "761"
  type: "Scale"
  bottom: "761"
  top: "761"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "762"
  type: "ReLU"
  bottom: "761"
  top: "762"
}
layer {
  name: "763"
  type: "Convolution"
  bottom: "762"
  top: "763"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "764_bn"
  type: "BatchNorm"
  bottom: "763"
  top: "764"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "764"
  type: "Scale"
  bottom: "764"
  top: "764"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "765"
  type: "ReLU"
  bottom: "764"
  top: "765"
}
layer {
  name: "766"
  type: "Convolution"
  bottom: "759"
  top: "766"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "767_bn"
  type: "BatchNorm"
  bottom: "766"
  top: "767"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "767"
  type: "Scale"
  bottom: "767"
  top: "767"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "768"
  type: "ReLU"
  bottom: "767"
  top: "768"
}
layer {
  name: "769"
  type: "Convolution"
  bottom: "768"
  top: "769"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "770_bn"
  type: "BatchNorm"
  bottom: "769"
  top: "770"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "770"
  type: "Scale"
  bottom: "770"
  top: "770"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "771"
  type: "ReLU"
  bottom: "770"
  top: "771"
}
layer {
  name: "772"
  type: "Convolution"
  bottom: "771"
  top: "772"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "773_bn"
  type: "BatchNorm"
  bottom: "772"
  top: "773"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "773"
  type: "Scale"
  bottom: "773"
  top: "773"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "774"
  type: "ReLU"
  bottom: "773"
  top: "774"
}
layer {
  name: "775"
  type: "Concat"
  bottom: "759"
  bottom: "765"
  bottom: "774"
  top: "775"
  concat_param {
    axis: 1
  }
}
layer {
  name: "776"
  type: "Convolution"
  bottom: "775"
  top: "776"
  convolution_param {
    num_output: 80
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "777_bn"
  type: "BatchNorm"
  bottom: "776"
  top: "777"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "777"
  type: "Scale"
  bottom: "777"
  top: "777"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "778"
  type: "ReLU"
  bottom: "777"
  top: "778"
}
layer {
  name: "779"
  type: "Pooling"
  bottom: "778"
  top: "779"
  pooling_param {
    pool: MAX
    kernel_h: 2
    kernel_w: 2
    stride_h: 2
    stride_w: 2
    pad_h: 0
    pad_w: 0
  }
}
layer {
  name: "780"
  type: "Convolution"
  bottom: "779"
  top: "780"
  convolution_param {
    num_output: 20
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "781_bn"
  type: "BatchNorm"
  bottom: "780"
  top: "781"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "781"
  type: "Scale"
  bottom: "781"
  top: "781"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "782"
  type: "ReLU"
  bottom: "781"
  top: "782"
}
layer {
  name: "783"
  type: "Convolution"
  bottom: "782"
  top: "783"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "784_bn"
  type: "BatchNorm"
  bottom: "783"
  top: "784"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "784"
  type: "Scale"
  bottom: "784"
  top: "784"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "785"
  type: "ReLU"
  bottom: "784"
  top: "785"
}
layer {
  name: "786"
  type: "Convolution"
  bottom: "779"
  top: "786"
  convolution_param {
    num_output: 20
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "787_bn"
  type: "BatchNorm"
  bottom: "786"
  top: "787"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "787"
  type: "Scale"
  bottom: "787"
  top: "787"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "788"
  type: "ReLU"
  bottom: "787"
  top: "788"
}
layer {
  name: "789"
  type: "Convolution"
  bottom: "788"
  top: "789"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "790_bn"
  type: "BatchNorm"
  bottom: "789"
  top: "790"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "790"
  type: "Scale"
  bottom: "790"
  top: "790"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "791"
  type: "ReLU"
  bottom: "790"
  top: "791"
}
layer {
  name: "792"
  type: "Convolution"
  bottom: "791"
  top: "792"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "793_bn"
  type: "BatchNorm"
  bottom: "792"
  top: "793"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "793"
  type: "Scale"
  bottom: "793"
  top: "793"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "794"
  type: "ReLU"
  bottom: "793"
  top: "794"
}
layer {
  name: "795"
  type: "Concat"
  bottom: "779"
  bottom: "785"
  bottom: "794"
  top: "795"
  concat_param {
    axis: 1
  }
}
layer {
  name: "796"
  type: "Convolution"
  bottom: "795"
  top: "796"
  convolution_param {
    num_output: 20
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "797_bn"
  type: "BatchNorm"
  bottom: "796"
  top: "797"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "797"
  type: "Scale"
  bottom: "797"
  top: "797"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "798"
  type: "ReLU"
  bottom: "797"
  top: "798"
}
layer {
  name: "799"
  type: "Convolution"
  bottom: "798"
  top: "799"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "800_bn"
  type: "BatchNorm"
  bottom: "799"
  top: "800"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "800"
  type: "Scale"
  bottom: "800"
  top: "800"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "801"
  type: "ReLU"
  bottom: "800"
  top: "801"
}
layer {
  name: "802"
  type: "Convolution"
  bottom: "795"
  top: "802"
  convolution_param {
    num_output: 20
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "803_bn"
  type: "BatchNorm"
  bottom: "802"
  top: "803"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "803"
  type: "Scale"
  bottom: "803"
  top: "803"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "804"
  type: "ReLU"
  bottom: "803"
  top: "804"
}
layer {
  name: "805"
  type: "Convolution"
  bottom: "804"
  top: "805"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "806_bn"
  type: "BatchNorm"
  bottom: "805"
  top: "806"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "806"
  type: "Scale"
  bottom: "806"
  top: "806"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "807"
  type: "ReLU"
  bottom: "806"
  top: "807"
}
layer {
  name: "808"
  type: "Convolution"
  bottom: "807"
  top: "808"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "809_bn"
  type: "BatchNorm"
  bottom: "808"
  top: "809"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "809"
  type: "Scale"
  bottom: "809"
  top: "809"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "810"
  type: "ReLU"
  bottom: "809"
  top: "810"
}
layer {
  name: "811"
  type: "Concat"
  bottom: "795"
  bottom: "801"
  bottom: "810"
  top: "811"
  concat_param {
    axis: 1
  }
}
layer {
  name: "812"
  type: "Convolution"
  bottom: "811"
  top: "812"
  convolution_param {
    num_output: 20
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "813_bn"
  type: "BatchNorm"
  bottom: "812"
  top: "813"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "813"
  type: "Scale"
  bottom: "813"
  top: "813"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "814"
  type: "ReLU"
  bottom: "813"
  top: "814"
}
layer {
  name: "815"
  type: "Convolution"
  bottom: "814"
  top: "815"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "816_bn"
  type: "BatchNorm"
  bottom: "815"
  top: "816"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "816"
  type: "Scale"
  bottom: "816"
  top: "816"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "817"
  type: "ReLU"
  bottom: "816"
  top: "817"
}
layer {
  name: "818"
  type: "Convolution"
  bottom: "811"
  top: "818"
  convolution_param {
    num_output: 20
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "819_bn"
  type: "BatchNorm"
  bottom: "818"
  top: "819"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "819"
  type: "Scale"
  bottom: "819"
  top: "819"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "820"
  type: "ReLU"
  bottom: "819"
  top: "820"
}
layer {
  name: "821"
  type: "Convolution"
  bottom: "820"
  top: "821"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "822_bn"
  type: "BatchNorm"
  bottom: "821"
  top: "822"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "822"
  type: "Scale"
  bottom: "822"
  top: "822"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "823"
  type: "ReLU"
  bottom: "822"
  top: "823"
}
layer {
  name: "824"
  type: "Convolution"
  bottom: "823"
  top: "824"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "825_bn"
  type: "BatchNorm"
  bottom: "824"
  top: "825"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "825"
  type: "Scale"
  bottom: "825"
  top: "825"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "826"
  type: "ReLU"
  bottom: "825"
  top: "826"
}
layer {
  name: "827"
  type: "Concat"
  bottom: "811"
  bottom: "817"
  bottom: "826"
  top: "827"
  concat_param {
    axis: 1
  }
}
layer {
  name: "828"
  type: "Convolution"
  bottom: "827"
  top: "828"
  convolution_param {
    num_output: 20
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "829_bn"
  type: "BatchNorm"
  bottom: "828"
  top: "829"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "829"
  type: "Scale"
  bottom: "829"
  top: "829"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "830"
  type: "ReLU"
  bottom: "829"
  top: "830"
}
layer {
  name: "831"
  type: "Convolution"
  bottom: "830"
  top: "831"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "832_bn"
  type: "BatchNorm"
  bottom: "831"
  top: "832"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "832"
  type: "Scale"
  bottom: "832"
  top: "832"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "833"
  type: "ReLU"
  bottom: "832"
  top: "833"
}
layer {
  name: "834"
  type: "Convolution"
  bottom: "827"
  top: "834"
  convolution_param {
    num_output: 20
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "835_bn"
  type: "BatchNorm"
  bottom: "834"
  top: "835"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "835"
  type: "Scale"
  bottom: "835"
  top: "835"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "836"
  type: "ReLU"
  bottom: "835"
  top: "836"
}
layer {
  name: "837"
  type: "Convolution"
  bottom: "836"
  top: "837"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "838_bn"
  type: "BatchNorm"
  bottom: "837"
  top: "838"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "838"
  type: "Scale"
  bottom: "838"
  top: "838"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "839"
  type: "ReLU"
  bottom: "838"
  top: "839"
}
layer {
  name: "840"
  type: "Convolution"
  bottom: "839"
  top: "840"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "841_bn"
  type: "BatchNorm"
  bottom: "840"
  top: "841"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "841"
  type: "Scale"
  bottom: "841"
  top: "841"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "842"
  type: "ReLU"
  bottom: "841"
  top: "842"
}
layer {
  name: "843"
  type: "Concat"
  bottom: "827"
  bottom: "833"
  bottom: "842"
  top: "843"
  concat_param {
    axis: 1
  }
}
layer {
  name: "844"
  type: "Convolution"
  bottom: "843"
  top: "844"
  convolution_param {
    num_output: 160
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "845_bn"
  type: "BatchNorm"
  bottom: "844"
  top: "845"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "845"
  type: "Scale"
  bottom: "845"
  top: "845"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "846"
  type: "ReLU"
  bottom: "845"
  top: "846"
}
layer {
  name: "847"
  type: "Pooling"
  bottom: "846"
  top: "847"
  pooling_param {
    pool: MAX
    kernel_h: 2
    kernel_w: 2
    stride_h: 2
    stride_w: 2
    pad_h: 0
    pad_w: 0
  }
}
layer {
  name: "848"
  type: "Convolution"
  bottom: "847"
  top: "848"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "849_bn"
  type: "BatchNorm"
  bottom: "848"
  top: "849"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "849"
  type: "Scale"
  bottom: "849"
  top: "849"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "850"
  type: "ReLU"
  bottom: "849"
  top: "850"
}
layer {
  name: "851"
  type: "Convolution"
  bottom: "850"
  top: "851"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "852_bn"
  type: "BatchNorm"
  bottom: "851"
  top: "852"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "852"
  type: "Scale"
  bottom: "852"
  top: "852"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "853"
  type: "ReLU"
  bottom: "852"
  top: "853"
}
layer {
  name: "854"
  type: "Convolution"
  bottom: "847"
  top: "854"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "855_bn"
  type: "BatchNorm"
  bottom: "854"
  top: "855"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "855"
  type: "Scale"
  bottom: "855"
  top: "855"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "856"
  type: "ReLU"
  bottom: "855"
  top: "856"
}
layer {
  name: "857"
  type: "Convolution"
  bottom: "856"
  top: "857"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "858_bn"
  type: "BatchNorm"
  bottom: "857"
  top: "858"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "858"
  type: "Scale"
  bottom: "858"
  top: "858"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "859"
  type: "ReLU"
  bottom: "858"
  top: "859"
}
layer {
  name: "860"
  type: "Convolution"
  bottom: "859"
  top: "860"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "861_bn"
  type: "BatchNorm"
  bottom: "860"
  top: "861"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "861"
  type: "Scale"
  bottom: "861"
  top: "861"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "862"
  type: "ReLU"
  bottom: "861"
  top: "862"
}
layer {
  name: "863"
  type: "Concat"
  bottom: "847"
  bottom: "853"
  bottom: "862"
  top: "863"
  concat_param {
    axis: 1
  }
}
layer {
  name: "864"
  type: "Convolution"
  bottom: "863"
  top: "864"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "865_bn"
  type: "BatchNorm"
  bottom: "864"
  top: "865"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "865"
  type: "Scale"
  bottom: "865"
  top: "865"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "866"
  type: "ReLU"
  bottom: "865"
  top: "866"
}
layer {
  name: "867"
  type: "Convolution"
  bottom: "866"
  top: "867"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "868_bn"
  type: "BatchNorm"
  bottom: "867"
  top: "868"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "868"
  type: "Scale"
  bottom: "868"
  top: "868"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "869"
  type: "ReLU"
  bottom: "868"
  top: "869"
}
layer {
  name: "870"
  type: "Convolution"
  bottom: "863"
  top: "870"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "871_bn"
  type: "BatchNorm"
  bottom: "870"
  top: "871"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "871"
  type: "Scale"
  bottom: "871"
  top: "871"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "872"
  type: "ReLU"
  bottom: "871"
  top: "872"
}
layer {
  name: "873"
  type: "Convolution"
  bottom: "872"
  top: "873"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "874_bn"
  type: "BatchNorm"
  bottom: "873"
  top: "874"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "874"
  type: "Scale"
  bottom: "874"
  top: "874"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "875"
  type: "ReLU"
  bottom: "874"
  top: "875"
}
layer {
  name: "876"
  type: "Convolution"
  bottom: "875"
  top: "876"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "877_bn"
  type: "BatchNorm"
  bottom: "876"
  top: "877"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "877"
  type: "Scale"
  bottom: "877"
  top: "877"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "878"
  type: "ReLU"
  bottom: "877"
  top: "878"
}
layer {
  name: "879"
  type: "Concat"
  bottom: "863"
  bottom: "869"
  bottom: "878"
  top: "879"
  concat_param {
    axis: 1
  }
}
layer {
  name: "880"
  type: "Convolution"
  bottom: "879"
  top: "880"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "881_bn"
  type: "BatchNorm"
  bottom: "880"
  top: "881"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "881"
  type: "Scale"
  bottom: "881"
  top: "881"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "882"
  type: "ReLU"
  bottom: "881"
  top: "882"
}
layer {
  name: "883"
  type: "Convolution"
  bottom: "882"
  top: "883"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "884_bn"
  type: "BatchNorm"
  bottom: "883"
  top: "884"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "884"
  type: "Scale"
  bottom: "884"
  top: "884"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "885"
  type: "ReLU"
  bottom: "884"
  top: "885"
}
layer {
  name: "886"
  type: "Convolution"
  bottom: "879"
  top: "886"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "887_bn"
  type: "BatchNorm"
  bottom: "886"
  top: "887"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "887"
  type: "Scale"
  bottom: "887"
  top: "887"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "888"
  type: "ReLU"
  bottom: "887"
  top: "888"
}
layer {
  name: "889"
  type: "Convolution"
  bottom: "888"
  top: "889"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "890_bn"
  type: "BatchNorm"
  bottom: "889"
  top: "890"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "890"
  type: "Scale"
  bottom: "890"
  top: "890"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "891"
  type: "ReLU"
  bottom: "890"
  top: "891"
}
layer {
  name: "892"
  type: "Convolution"
  bottom: "891"
  top: "892"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "893_bn"
  type: "BatchNorm"
  bottom: "892"
  top: "893"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "893"
  type: "Scale"
  bottom: "893"
  top: "893"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "894"
  type: "ReLU"
  bottom: "893"
  top: "894"
}
layer {
  name: "895"
  type: "Concat"
  bottom: "879"
  bottom: "885"
  bottom: "894"
  top: "895"
  concat_param {
    axis: 1
  }
}
layer {
  name: "896"
  type: "Convolution"
  bottom: "895"
  top: "896"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "897_bn"
  type: "BatchNorm"
  bottom: "896"
  top: "897"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "897"
  type: "Scale"
  bottom: "897"
  top: "897"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "898"
  type: "ReLU"
  bottom: "897"
  top: "898"
}
layer {
  name: "899"
  type: "Convolution"
  bottom: "898"
  top: "899"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "900_bn"
  type: "BatchNorm"
  bottom: "899"
  top: "900"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "900"
  type: "Scale"
  bottom: "900"
  top: "900"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "901"
  type: "ReLU"
  bottom: "900"
  top: "901"
}
layer {
  name: "902"
  type: "Convolution"
  bottom: "895"
  top: "902"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "903_bn"
  type: "BatchNorm"
  bottom: "902"
  top: "903"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "903"
  type: "Scale"
  bottom: "903"
  top: "903"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "904"
  type: "ReLU"
  bottom: "903"
  top: "904"
}
layer {
  name: "905"
  type: "Convolution"
  bottom: "904"
  top: "905"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "906_bn"
  type: "BatchNorm"
  bottom: "905"
  top: "906"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "906"
  type: "Scale"
  bottom: "906"
  top: "906"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "907"
  type: "ReLU"
  bottom: "906"
  top: "907"
}
layer {
  name: "908"
  type: "Convolution"
  bottom: "907"
  top: "908"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "909_bn"
  type: "BatchNorm"
  bottom: "908"
  top: "909"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "909"
  type: "Scale"
  bottom: "909"
  top: "909"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "910"
  type: "ReLU"
  bottom: "909"
  top: "910"
}
layer {
  name: "911"
  type: "Concat"
  bottom: "895"
  bottom: "901"
  bottom: "910"
  top: "911"
  concat_param {
    axis: 1
  }
}
layer {
  name: "912"
  type: "Convolution"
  bottom: "911"
  top: "912"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "913_bn"
  type: "BatchNorm"
  bottom: "912"
  top: "913"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "913"
  type: "Scale"
  bottom: "913"
  top: "913"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "914"
  type: "ReLU"
  bottom: "913"
  top: "914"
}
layer {
  name: "915"
  type: "Convolution"
  bottom: "914"
  top: "915"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "916_bn"
  type: "BatchNorm"
  bottom: "915"
  top: "916"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "916"
  type: "Scale"
  bottom: "916"
  top: "916"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "917"
  type: "ReLU"
  bottom: "916"
  top: "917"
}
layer {
  name: "918"
  type: "Convolution"
  bottom: "911"
  top: "918"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "919_bn"
  type: "BatchNorm"
  bottom: "918"
  top: "919"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "919"
  type: "Scale"
  bottom: "919"
  top: "919"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "920"
  type: "ReLU"
  bottom: "919"
  top: "920"
}
layer {
  name: "921"
  type: "Convolution"
  bottom: "920"
  top: "921"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "922_bn"
  type: "BatchNorm"
  bottom: "921"
  top: "922"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "922"
  type: "Scale"
  bottom: "922"
  top: "922"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "923"
  type: "ReLU"
  bottom: "922"
  top: "923"
}
layer {
  name: "924"
  type: "Convolution"
  bottom: "923"
  top: "924"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "925_bn"
  type: "BatchNorm"
  bottom: "924"
  top: "925"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "925"
  type: "Scale"
  bottom: "925"
  top: "925"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "926"
  type: "ReLU"
  bottom: "925"
  top: "926"
}
layer {
  name: "927"
  type: "Concat"
  bottom: "911"
  bottom: "917"
  bottom: "926"
  top: "927"
  concat_param {
    axis: 1
  }
}
layer {
  name: "928"
  type: "Convolution"
  bottom: "927"
  top: "928"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "929_bn"
  type: "BatchNorm"
  bottom: "928"
  top: "929"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "929"
  type: "Scale"
  bottom: "929"
  top: "929"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "930"
  type: "ReLU"
  bottom: "929"
  top: "930"
}
layer {
  name: "931"
  type: "Convolution"
  bottom: "930"
  top: "931"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "932_bn"
  type: "BatchNorm"
  bottom: "931"
  top: "932"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "932"
  type: "Scale"
  bottom: "932"
  top: "932"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "933"
  type: "ReLU"
  bottom: "932"
  top: "933"
}
layer {
  name: "934"
  type: "Convolution"
  bottom: "927"
  top: "934"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "935_bn"
  type: "BatchNorm"
  bottom: "934"
  top: "935"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "935"
  type: "Scale"
  bottom: "935"
  top: "935"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "936"
  type: "ReLU"
  bottom: "935"
  top: "936"
}
layer {
  name: "937"
  type: "Convolution"
  bottom: "936"
  top: "937"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "938_bn"
  type: "BatchNorm"
  bottom: "937"
  top: "938"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "938"
  type: "Scale"
  bottom: "938"
  top: "938"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "939"
  type: "ReLU"
  bottom: "938"
  top: "939"
}
layer {
  name: "940"
  type: "Convolution"
  bottom: "939"
  top: "940"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "941_bn"
  type: "BatchNorm"
  bottom: "940"
  top: "941"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "941"
  type: "Scale"
  bottom: "941"
  top: "941"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "942"
  type: "ReLU"
  bottom: "941"
  top: "942"
}
layer {
  name: "943"
  type: "Concat"
  bottom: "927"
  bottom: "933"
  bottom: "942"
  top: "943"
  concat_param {
    axis: 1
  }
}
layer {
  name: "944"
  type: "Convolution"
  bottom: "943"
  top: "944"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "945_bn"
  type: "BatchNorm"
  bottom: "944"
  top: "945"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "945"
  type: "Scale"
  bottom: "945"
  top: "945"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "946"
  type: "ReLU"
  bottom: "945"
  top: "946"
}
layer {
  name: "947"
  type: "Convolution"
  bottom: "946"
  top: "947"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "948_bn"
  type: "BatchNorm"
  bottom: "947"
  top: "948"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "948"
  type: "Scale"
  bottom: "948"
  top: "948"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "949"
  type: "ReLU"
  bottom: "948"
  top: "949"
}
layer {
  name: "950"
  type: "Convolution"
  bottom: "943"
  top: "950"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "951_bn"
  type: "BatchNorm"
  bottom: "950"
  top: "951"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "951"
  type: "Scale"
  bottom: "951"
  top: "951"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "952"
  type: "ReLU"
  bottom: "951"
  top: "952"
}
layer {
  name: "953"
  type: "Convolution"
  bottom: "952"
  top: "953"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "954_bn"
  type: "BatchNorm"
  bottom: "953"
  top: "954"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "954"
  type: "Scale"
  bottom: "954"
  top: "954"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "955"
  type: "ReLU"
  bottom: "954"
  top: "955"
}
layer {
  name: "956"
  type: "Convolution"
  bottom: "955"
  top: "956"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "957_bn"
  type: "BatchNorm"
  bottom: "956"
  top: "957"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "957"
  type: "Scale"
  bottom: "957"
  top: "957"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "958"
  type: "ReLU"
  bottom: "957"
  top: "958"
}
layer {
  name: "959"
  type: "Concat"
  bottom: "943"
  bottom: "949"
  bottom: "958"
  top: "959"
  concat_param {
    axis: 1
  }
}
layer {
  name: "960"
  type: "Convolution"
  bottom: "959"
  top: "960"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "961_bn"
  type: "BatchNorm"
  bottom: "960"
  top: "961"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "961"
  type: "Scale"
  bottom: "961"
  top: "961"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "962"
  type: "ReLU"
  bottom: "961"
  top: "962"
}
layer {
  name: "963"
  type: "Convolution"
  bottom: "962"
  top: "963"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "964_bn"
  type: "BatchNorm"
  bottom: "963"
  top: "964"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "964"
  type: "Scale"
  bottom: "964"
  top: "964"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "965"
  type: "ReLU"
  bottom: "964"
  top: "965"
}
layer {
  name: "966"
  type: "Convolution"
  bottom: "959"
  top: "966"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "967_bn"
  type: "BatchNorm"
  bottom: "966"
  top: "967"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "967"
  type: "Scale"
  bottom: "967"
  top: "967"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "968"
  type: "ReLU"
  bottom: "967"
  top: "968"
}
layer {
  name: "969"
  type: "Convolution"
  bottom: "968"
  top: "969"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "970_bn"
  type: "BatchNorm"
  bottom: "969"
  top: "970"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "970"
  type: "Scale"
  bottom: "970"
  top: "970"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "971"
  type: "ReLU"
  bottom: "970"
  top: "971"
}
layer {
  name: "972"
  type: "Convolution"
  bottom: "971"
  top: "972"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "973_bn"
  type: "BatchNorm"
  bottom: "972"
  top: "973"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "973"
  type: "Scale"
  bottom: "973"
  top: "973"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "974"
  type: "ReLU"
  bottom: "973"
  top: "974"
}
layer {
  name: "975"
  type: "Concat"
  bottom: "959"
  bottom: "965"
  bottom: "974"
  top: "975"
  concat_param {
    axis: 1
  }
}
layer {
  name: "976"
  type: "Convolution"
  bottom: "975"
  top: "976"
  convolution_param {
    num_output: 320
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "977_bn"
  type: "BatchNorm"
  bottom: "976"
  top: "977"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "977"
  type: "Scale"
  bottom: "977"
  top: "977"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "978"
  type: "ReLU"
  bottom: "977"
  top: "978"
}
layer {
  name: "979"
  type: "Pooling"
  bottom: "978"
  top: "979"
  pooling_param {
    pool: MAX
    kernel_h: 2
    kernel_w: 2
    stride_h: 2
    stride_w: 2
    pad_h: 0
    pad_w: 0
  }
}
layer {
  name: "980"
  type: "Convolution"
  bottom: "979"
  top: "980"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "981_bn"
  type: "BatchNorm"
  bottom: "980"
  top: "981"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "981"
  type: "Scale"
  bottom: "981"
  top: "981"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "982"
  type: "ReLU"
  bottom: "981"
  top: "982"
}
layer {
  name: "983"
  type: "Convolution"
  bottom: "982"
  top: "983"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "984_bn"
  type: "BatchNorm"
  bottom: "983"
  top: "984"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "984"
  type: "Scale"
  bottom: "984"
  top: "984"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "985"
  type: "ReLU"
  bottom: "984"
  top: "985"
}
layer {
  name: "986"
  type: "Convolution"
  bottom: "979"
  top: "986"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "987_bn"
  type: "BatchNorm"
  bottom: "986"
  top: "987"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "987"
  type: "Scale"
  bottom: "987"
  top: "987"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "988"
  type: "ReLU"
  bottom: "987"
  top: "988"
}
layer {
  name: "989"
  type: "Convolution"
  bottom: "988"
  top: "989"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "990_bn"
  type: "BatchNorm"
  bottom: "989"
  top: "990"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "990"
  type: "Scale"
  bottom: "990"
  top: "990"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "991"
  type: "ReLU"
  bottom: "990"
  top: "991"
}
layer {
  name: "992"
  type: "Convolution"
  bottom: "991"
  top: "992"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "993_bn"
  type: "BatchNorm"
  bottom: "992"
  top: "993"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "993"
  type: "Scale"
  bottom: "993"
  top: "993"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "994"
  type: "ReLU"
  bottom: "993"
  top: "994"
}
layer {
  name: "995"
  type: "Concat"
  bottom: "979"
  bottom: "985"
  bottom: "994"
  top: "995"
  concat_param {
    axis: 1
  }
}
layer {
  name: "996"
  type: "Convolution"
  bottom: "995"
  top: "996"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "997_bn"
  type: "BatchNorm"
  bottom: "996"
  top: "997"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "997"
  type: "Scale"
  bottom: "997"
  top: "997"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "998"
  type: "ReLU"
  bottom: "997"
  top: "998"
}
layer {
  name: "999"
  type: "Convolution"
  bottom: "998"
  top: "999"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1000_bn"
  type: "BatchNorm"
  bottom: "999"
  top: "1000"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1000"
  type: "Scale"
  bottom: "1000"
  top: "1000"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1001"
  type: "ReLU"
  bottom: "1000"
  top: "1001"
}
layer {
  name: "1002"
  type: "Convolution"
  bottom: "995"
  top: "1002"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1003_bn"
  type: "BatchNorm"
  bottom: "1002"
  top: "1003"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1003"
  type: "Scale"
  bottom: "1003"
  top: "1003"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1004"
  type: "ReLU"
  bottom: "1003"
  top: "1004"
}
layer {
  name: "1005"
  type: "Convolution"
  bottom: "1004"
  top: "1005"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1006_bn"
  type: "BatchNorm"
  bottom: "1005"
  top: "1006"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1006"
  type: "Scale"
  bottom: "1006"
  top: "1006"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1007"
  type: "ReLU"
  bottom: "1006"
  top: "1007"
}
layer {
  name: "1008"
  type: "Convolution"
  bottom: "1007"
  top: "1008"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1009_bn"
  type: "BatchNorm"
  bottom: "1008"
  top: "1009"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1009"
  type: "Scale"
  bottom: "1009"
  top: "1009"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1010"
  type: "ReLU"
  bottom: "1009"
  top: "1010"
}
layer {
  name: "1011"
  type: "Concat"
  bottom: "995"
  bottom: "1001"
  bottom: "1010"
  top: "1011"
  concat_param {
    axis: 1
  }
}
layer {
  name: "1012"
  type: "Convolution"
  bottom: "1011"
  top: "1012"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1013_bn"
  type: "BatchNorm"
  bottom: "1012"
  top: "1013"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1013"
  type: "Scale"
  bottom: "1013"
  top: "1013"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1014"
  type: "ReLU"
  bottom: "1013"
  top: "1014"
}
layer {
  name: "1015"
  type: "Convolution"
  bottom: "1014"
  top: "1015"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1016_bn"
  type: "BatchNorm"
  bottom: "1015"
  top: "1016"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1016"
  type: "Scale"
  bottom: "1016"
  top: "1016"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1017"
  type: "ReLU"
  bottom: "1016"
  top: "1017"
}
layer {
  name: "1018"
  type: "Convolution"
  bottom: "1011"
  top: "1018"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1019_bn"
  type: "BatchNorm"
  bottom: "1018"
  top: "1019"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1019"
  type: "Scale"
  bottom: "1019"
  top: "1019"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1020"
  type: "ReLU"
  bottom: "1019"
  top: "1020"
}
layer {
  name: "1021"
  type: "Convolution"
  bottom: "1020"
  top: "1021"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1022_bn"
  type: "BatchNorm"
  bottom: "1021"
  top: "1022"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1022"
  type: "Scale"
  bottom: "1022"
  top: "1022"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1023"
  type: "ReLU"
  bottom: "1022"
  top: "1023"
}
layer {
  name: "1024"
  type: "Convolution"
  bottom: "1023"
  top: "1024"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1025_bn"
  type: "BatchNorm"
  bottom: "1024"
  top: "1025"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1025"
  type: "Scale"
  bottom: "1025"
  top: "1025"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1026"
  type: "ReLU"
  bottom: "1025"
  top: "1026"
}
layer {
  name: "1027"
  type: "Concat"
  bottom: "1011"
  bottom: "1017"
  bottom: "1026"
  top: "1027"
  concat_param {
    axis: 1
  }
}
layer {
  name: "1028"
  type: "Convolution"
  bottom: "1027"
  top: "1028"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1029_bn"
  type: "BatchNorm"
  bottom: "1028"
  top: "1029"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1029"
  type: "Scale"
  bottom: "1029"
  top: "1029"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1030"
  type: "ReLU"
  bottom: "1029"
  top: "1030"
}
layer {
  name: "1031"
  type: "Convolution"
  bottom: "1030"
  top: "1031"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1032_bn"
  type: "BatchNorm"
  bottom: "1031"
  top: "1032"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1032"
  type: "Scale"
  bottom: "1032"
  top: "1032"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1033"
  type: "ReLU"
  bottom: "1032"
  top: "1033"
}
layer {
  name: "1034"
  type: "Convolution"
  bottom: "1027"
  top: "1034"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1035_bn"
  type: "BatchNorm"
  bottom: "1034"
  top: "1035"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1035"
  type: "Scale"
  bottom: "1035"
  top: "1035"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1036"
  type: "ReLU"
  bottom: "1035"
  top: "1036"
}
layer {
  name: "1037"
  type: "Convolution"
  bottom: "1036"
  top: "1037"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1038_bn"
  type: "BatchNorm"
  bottom: "1037"
  top: "1038"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1038"
  type: "Scale"
  bottom: "1038"
  top: "1038"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1039"
  type: "ReLU"
  bottom: "1038"
  top: "1039"
}
layer {
  name: "1040"
  type: "Convolution"
  bottom: "1039"
  top: "1040"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1041_bn"
  type: "BatchNorm"
  bottom: "1040"
  top: "1041"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1041"
  type: "Scale"
  bottom: "1041"
  top: "1041"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1042"
  type: "ReLU"
  bottom: "1041"
  top: "1042"
}
layer {
  name: "1043"
  type: "Concat"
  bottom: "1027"
  bottom: "1033"
  bottom: "1042"
  top: "1043"
  concat_param {
    axis: 1
  }
}
layer {
  name: "1044"
  type: "Convolution"
  bottom: "1043"
  top: "1044"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1045_bn"
  type: "BatchNorm"
  bottom: "1044"
  top: "1045"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1045"
  type: "Scale"
  bottom: "1045"
  top: "1045"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1046"
  type: "ReLU"
  bottom: "1045"
  top: "1046"
}
layer {
  name: "1047"
  type: "Convolution"
  bottom: "1046"
  top: "1047"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1048_bn"
  type: "BatchNorm"
  bottom: "1047"
  top: "1048"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1048"
  type: "Scale"
  bottom: "1048"
  top: "1048"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1049"
  type: "ReLU"
  bottom: "1048"
  top: "1049"
}
layer {
  name: "1050"
  type: "Convolution"
  bottom: "1043"
  top: "1050"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1051_bn"
  type: "BatchNorm"
  bottom: "1050"
  top: "1051"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1051"
  type: "Scale"
  bottom: "1051"
  top: "1051"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1052"
  type: "ReLU"
  bottom: "1051"
  top: "1052"
}
layer {
  name: "1053"
  type: "Convolution"
  bottom: "1052"
  top: "1053"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1054_bn"
  type: "BatchNorm"
  bottom: "1053"
  top: "1054"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1054"
  type: "Scale"
  bottom: "1054"
  top: "1054"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1055"
  type: "ReLU"
  bottom: "1054"
  top: "1055"
}
layer {
  name: "1056"
  type: "Convolution"
  bottom: "1055"
  top: "1056"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1057_bn"
  type: "BatchNorm"
  bottom: "1056"
  top: "1057"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1057"
  type: "Scale"
  bottom: "1057"
  top: "1057"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1058"
  type: "ReLU"
  bottom: "1057"
  top: "1058"
}
layer {
  name: "1059"
  type: "Concat"
  bottom: "1043"
  bottom: "1049"
  bottom: "1058"
  top: "1059"
  concat_param {
    axis: 1
  }
}
layer {
  name: "1060"
  type: "Convolution"
  bottom: "1059"
  top: "1060"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1061_bn"
  type: "BatchNorm"
  bottom: "1060"
  top: "1061"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1061"
  type: "Scale"
  bottom: "1061"
  top: "1061"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1062"
  type: "ReLU"
  bottom: "1061"
  top: "1062"
}
layer {
  name: "1063"
  type: "Convolution"
  bottom: "1062"
  top: "1063"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1064_bn"
  type: "BatchNorm"
  bottom: "1063"
  top: "1064"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1064"
  type: "Scale"
  bottom: "1064"
  top: "1064"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1065"
  type: "ReLU"
  bottom: "1064"
  top: "1065"
}
layer {
  name: "1066"
  type: "Convolution"
  bottom: "1059"
  top: "1066"
  convolution_param {
    num_output: 40
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1067_bn"
  type: "BatchNorm"
  bottom: "1066"
  top: "1067"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1067"
  type: "Scale"
  bottom: "1067"
  top: "1067"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1068"
  type: "ReLU"
  bottom: "1067"
  top: "1068"
}
layer {
  name: "1069"
  type: "Convolution"
  bottom: "1068"
  top: "1069"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1070_bn"
  type: "BatchNorm"
  bottom: "1069"
  top: "1070"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1070"
  type: "Scale"
  bottom: "1070"
  top: "1070"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1071"
  type: "ReLU"
  bottom: "1070"
  top: "1071"
}
layer {
  name: "1072"
  type: "Convolution"
  bottom: "1071"
  top: "1072"
  convolution_param {
    num_output: 10
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1073_bn"
  type: "BatchNorm"
  bottom: "1072"
  top: "1073"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1073"
  type: "Scale"
  bottom: "1073"
  top: "1073"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1074"
  type: "ReLU"
  bottom: "1073"
  top: "1074"
}
layer {
  name: "1075"
  type: "Concat"
  bottom: "1059"
  bottom: "1065"
  bottom: "1074"
  top: "1075"
  concat_param {
    axis: 1
  }
}
layer {
  name: "1076"
  type: "Convolution"
  bottom: "1075"
  top: "1076"
  convolution_param {
    num_output: 440
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1077_bn"
  type: "BatchNorm"
  bottom: "1076"
  top: "1077"
  batch_norm_param {
    use_global_stats: true
    eps: 0.0010000000475
  }
}
layer {
  name: "1077"
  type: "Scale"
  bottom: "1077"
  top: "1077"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1078"
  type: "ReLU"
  bottom: "1077"
  top: "1078"
}
layer {
  name: "1079"
  type: "Convolution"
  bottom: "1078"
  top: "1079"
  convolution_param {
    num_output: 48
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1080_bn"
  type: "BatchNorm"
  bottom: "1079"
  top: "1080"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "1080"
  type: "Scale"
  bottom: "1080"
  top: "1080"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1081"
  type: "ReLU"
  bottom: "1080"
  top: "1081"
}
layer {
  name: "1082"
  type: "Convolution"
  bottom: "978"
  top: "1082"
  convolution_param {
    num_output: 48
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1083_bn"
  type: "BatchNorm"
  bottom: "1082"
  top: "1083"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "1083"
  type: "Scale"
  bottom: "1083"
  top: "1083"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1084"
  type: "ReLU"
  bottom: "1083"
  top: "1084"
}
layer {
  name: "1085"
  type: "Convolution"
  bottom: "846"
  top: "1085"
  convolution_param {
    num_output: 48
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1086_bn"
  type: "BatchNorm"
  bottom: "1085"
  top: "1086"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "1086"
  type: "Scale"
  bottom: "1086"
  top: "1086"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1087"
  type: "ReLU"
  bottom: "1086"
  top: "1087"
}
layer {
  name: "1088"
  type: "Deconvolution"
  bottom: "1081"
  top: "1088"
  convolution_param {
    num_output: 48
    bias_term: true
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 2
    kernel_w: 2
    stride_h: 2
    stride_w: 2
  }
}
layer {
  name: "1089"
  type: "Eltwise"
  bottom: "1084"
  bottom: "1088"
  top: "1089"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "1090"
  type: "Deconvolution"
  bottom: "1089"
  top: "1090"
  convolution_param {
    num_output: 48
    bias_term: true
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 2
    kernel_w: 2
    stride_h: 2
    stride_w: 2
  }
}
layer {
  name: "1091"
  type: "Eltwise"
  bottom: "1087"
  bottom: "1090"
  top: "1091"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "1092"
  type: "Deconvolution"
  bottom: "1091"
  top: "1092"
  convolution_param {
    num_output: 48
    bias_term: true
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 2
    kernel_w: 2
    stride_h: 2
    stride_w: 2
  }
}
layer {
  name: "1093"
  type: "Convolution"
  bottom: "1092"
  top: "1093"
  convolution_param {
    num_output: 48
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1094_bn"
  type: "BatchNorm"
  bottom: "1093"
  top: "1094"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "1094"
  type: "Scale"
  bottom: "1094"
  top: "1094"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "1095"
  type: "ReLU"
  bottom: "1094"
  top: "1095"
}
layer {
  name: "output_score"
  type: "Convolution"
  bottom: "1095"
  top: "output_score"
  convolution_param {
    num_output: 1
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1098"
  type: "Convolution"
  bottom: "1095"
  top: "1098"
  convolution_param {
    num_output: 48
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "1099"
  type: "ReLU"
  bottom: "1098"
  top: "1099"
}
layer {
  name: "1100"
  type: "Convolution"
  bottom: "1099"
  top: "1100"
  convolution_param {
    num_output: 4
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "output_reg"
  type: "Sigmoid"
  bottom: "1100"
  top: "output_reg"
}
layer {
  name: "reg-x1"
  type: "Power"
  bottom: "output_reg"
  top: "reg-x1"
  power_param {
    scale: 1000
    shift: -500
  }
}
layer {
  name: "output_rot"
  type: "Convolution"
  bottom: "1095"
  top: "output_rot"
  convolution_param {
    num_output: 1
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}