layer {
  name: "input"
  type: "Input"
  top: "input"
  input_param {
    shape {
      dim: 1
      dim: 3
      dim: 512
      dim: 512
    }
  }
}
layer {
  name: "339"
  type: "Convolution"
  bottom: "input"
  top: "339"
  convolution_param {
    num_output: 16
    bias_term: false
    group: 1
    pad_h: 3
    pad_w: 3
    kernel_h: 7
    kernel_w: 7
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "340_bn"
  type: "BatchNorm"
  bottom: "339"
  top: "340"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "340"
  type: "Scale"
  bottom: "340"
  top: "340"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "341"
  type: "ReLU"
  bottom: "340"
  top: "341"
}
layer {
  name: "342"
  type: "Convolution"
  bottom: "341"
  top: "342"
  convolution_param {
    num_output: 16
    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: "343_bn"
  type: "BatchNorm"
  bottom: "342"
  top: "343"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "343"
  type: "Scale"
  bottom: "343"
  top: "343"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "344"
  type: "ReLU"
  bottom: "343"
  top: "344"
}
layer {
  name: "345"
  type: "Convolution"
  bottom: "344"
  top: "345"
  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: "346_bn"
  type: "BatchNorm"
  bottom: "345"
  top: "346"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "346"
  type: "Scale"
  bottom: "346"
  top: "346"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "347"
  type: "ReLU"
  bottom: "346"
  top: "347"
}
layer {
  name: "348"
  type: "Pooling"
  bottom: "347"
  top: "348"
  pooling_param {
    pool: MAX
    kernel_h: 2
    kernel_w: 2
    stride_h: 2
    stride_w: 2
    pad_h: 0
    pad_w: 0
  }
}
layer {
  name: "349"
  type: "Convolution"
  bottom: "348"
  top: "349"
  convolution_param {
    num_output: 64
    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: "350_bn"
  type: "BatchNorm"
  bottom: "349"
  top: "350"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "350"
  type: "Scale"
  bottom: "350"
  top: "350"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "351"
  type: "Convolution"
  bottom: "347"
  top: "351"
  convolution_param {
    num_output: 64
    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: "352_bn"
  type: "BatchNorm"
  bottom: "351"
  top: "352"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "352"
  type: "Scale"
  bottom: "352"
  top: "352"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "353"
  type: "ReLU"
  bottom: "352"
  top: "353"
}
layer {
  name: "354"
  type: "Convolution"
  bottom: "353"
  top: "354"
  convolution_param {
    num_output: 64
    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: "355_bn"
  type: "BatchNorm"
  bottom: "354"
  top: "355"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "355"
  type: "Scale"
  bottom: "355"
  top: "355"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "356"
  type: "Eltwise"
  bottom: "355"
  bottom: "350"
  top: "356"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "357"
  type: "ReLU"
  bottom: "356"
  top: "357"
}
layer {
  name: "358"
  type: "Convolution"
  bottom: "357"
  top: "358"
  convolution_param {
    num_output: 64
    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: "359_bn"
  type: "BatchNorm"
  bottom: "358"
  top: "359"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "359"
  type: "Scale"
  bottom: "359"
  top: "359"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "360"
  type: "ReLU"
  bottom: "359"
  top: "360"
}
layer {
  name: "361"
  type: "Convolution"
  bottom: "360"
  top: "361"
  convolution_param {
    num_output: 64
    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: "362_bn"
  type: "BatchNorm"
  bottom: "361"
  top: "362"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "362"
  type: "Scale"
  bottom: "362"
  top: "362"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "363"
  type: "Eltwise"
  bottom: "362"
  bottom: "357"
  top: "363"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "364"
  type: "ReLU"
  bottom: "363"
  top: "364"
}
layer {
  name: "365"
  type: "Concat"
  bottom: "364"
  bottom: "357"
  top: "365"
  concat_param {
    axis: 1
  }
}
layer {
  name: "366"
  type: "Convolution"
  bottom: "365"
  top: "366"
  convolution_param {
    num_output: 64
    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: "367_bn"
  type: "BatchNorm"
  bottom: "366"
  top: "367"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "367"
  type: "Scale"
  bottom: "367"
  top: "367"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "368"
  type: "ReLU"
  bottom: "367"
  top: "368"
}
layer {
  name: "369"
  type: "Pooling"
  bottom: "368"
  top: "369"
  pooling_param {
    pool: MAX
    kernel_h: 2
    kernel_w: 2
    stride_h: 2
    stride_w: 2
    pad_h: 0
    pad_w: 0
  }
}
layer {
  name: "370"
  type: "Pooling"
  bottom: "368"
  top: "370"
  pooling_param {
    pool: MAX
    kernel_h: 2
    kernel_w: 2
    stride_h: 2
    stride_w: 2
    pad_h: 0
    pad_w: 0
  }
}
layer {
  name: "371"
  type: "Convolution"
  bottom: "370"
  top: "371"
  convolution_param {
    num_output: 128
    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: "372_bn"
  type: "BatchNorm"
  bottom: "371"
  top: "372"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "372"
  type: "Scale"
  bottom: "372"
  top: "372"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "373"
  type: "Convolution"
  bottom: "368"
  top: "373"
  convolution_param {
    num_output: 128
    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: "374_bn"
  type: "BatchNorm"
  bottom: "373"
  top: "374"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "374"
  type: "Scale"
  bottom: "374"
  top: "374"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "375"
  type: "ReLU"
  bottom: "374"
  top: "375"
}
layer {
  name: "376"
  type: "Convolution"
  bottom: "375"
  top: "376"
  convolution_param {
    num_output: 128
    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: "377_bn"
  type: "BatchNorm"
  bottom: "376"
  top: "377"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "377"
  type: "Scale"
  bottom: "377"
  top: "377"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "378"
  type: "Eltwise"
  bottom: "377"
  bottom: "372"
  top: "378"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "379"
  type: "ReLU"
  bottom: "378"
  top: "379"
}
layer {
  name: "380"
  type: "Convolution"
  bottom: "379"
  top: "380"
  convolution_param {
    num_output: 128
    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: "381_bn"
  type: "BatchNorm"
  bottom: "380"
  top: "381"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "381"
  type: "Scale"
  bottom: "381"
  top: "381"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "382"
  type: "ReLU"
  bottom: "381"
  top: "382"
}
layer {
  name: "383"
  type: "Convolution"
  bottom: "382"
  top: "383"
  convolution_param {
    num_output: 128
    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: "384_bn"
  type: "BatchNorm"
  bottom: "383"
  top: "384"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "384"
  type: "Scale"
  bottom: "384"
  top: "384"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "385"
  type: "Eltwise"
  bottom: "384"
  bottom: "379"
  top: "385"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "386"
  type: "ReLU"
  bottom: "385"
  top: "386"
}
layer {
  name: "387"
  type: "Concat"
  bottom: "386"
  bottom: "379"
  top: "387"
  concat_param {
    axis: 1
  }
}
layer {
  name: "388"
  type: "Convolution"
  bottom: "387"
  top: "388"
  convolution_param {
    num_output: 128
    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: "389_bn"
  type: "BatchNorm"
  bottom: "388"
  top: "389"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "389"
  type: "Scale"
  bottom: "389"
  top: "389"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "390"
  type: "ReLU"
  bottom: "389"
  top: "390"
}
layer {
  name: "391"
  type: "Convolution"
  bottom: "390"
  top: "391"
  convolution_param {
    num_output: 128
    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: "392_bn"
  type: "BatchNorm"
  bottom: "391"
  top: "392"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "392"
  type: "Scale"
  bottom: "392"
  top: "392"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "393"
  type: "ReLU"
  bottom: "392"
  top: "393"
}
layer {
  name: "394"
  type: "Convolution"
  bottom: "393"
  top: "394"
  convolution_param {
    num_output: 128
    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: "395_bn"
  type: "BatchNorm"
  bottom: "394"
  top: "395"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "395"
  type: "Scale"
  bottom: "395"
  top: "395"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "396"
  type: "Eltwise"
  bottom: "395"
  bottom: "390"
  top: "396"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "397"
  type: "ReLU"
  bottom: "396"
  top: "397"
}
layer {
  name: "398"
  type: "Convolution"
  bottom: "397"
  top: "398"
  convolution_param {
    num_output: 128
    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: "399_bn"
  type: "BatchNorm"
  bottom: "398"
  top: "399"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "399"
  type: "Scale"
  bottom: "399"
  top: "399"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "400"
  type: "ReLU"
  bottom: "399"
  top: "400"
}
layer {
  name: "401"
  type: "Convolution"
  bottom: "400"
  top: "401"
  convolution_param {
    num_output: 128
    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: "402_bn"
  type: "BatchNorm"
  bottom: "401"
  top: "402"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "402"
  type: "Scale"
  bottom: "402"
  top: "402"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "403"
  type: "Eltwise"
  bottom: "402"
  bottom: "397"
  top: "403"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "404"
  type: "ReLU"
  bottom: "403"
  top: "404"
}
layer {
  name: "405"
  type: "Concat"
  bottom: "404"
  bottom: "397"
  bottom: "369"
  bottom: "390"
  top: "405"
  concat_param {
    axis: 1
  }
}
layer {
  name: "406"
  type: "Convolution"
  bottom: "405"
  top: "406"
  convolution_param {
    num_output: 128
    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: "407_bn"
  type: "BatchNorm"
  bottom: "406"
  top: "407"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "407"
  type: "Scale"
  bottom: "407"
  top: "407"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "408"
  type: "ReLU"
  bottom: "407"
  top: "408"
}
layer {
  name: "409"
  type: "Pooling"
  bottom: "408"
  top: "409"
  pooling_param {
    pool: MAX
    kernel_h: 2
    kernel_w: 2
    stride_h: 2
    stride_w: 2
    pad_h: 0
    pad_w: 0
  }
}
layer {
  name: "410"
  type: "Convolution"
  bottom: "408"
  top: "410"
  convolution_param {
    num_output: 128
    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: "411_bn"
  type: "BatchNorm"
  bottom: "410"
  top: "411"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "411"
  type: "Scale"
  bottom: "411"
  top: "411"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "412"
  type: "ReLU"
  bottom: "411"
  top: "412"
}
layer {
  name: "413"
  type: "Convolution"
  bottom: "412"
  top: "413"
  convolution_param {
    num_output: 128
    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: "414_bn"
  type: "BatchNorm"
  bottom: "413"
  top: "414"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "414"
  type: "Scale"
  bottom: "414"
  top: "414"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "415"
  type: "Eltwise"
  bottom: "414"
  bottom: "409"
  top: "415"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "416"
  type: "ReLU"
  bottom: "415"
  top: "416"
}
layer {
  name: "417"
  type: "Convolution"
  bottom: "416"
  top: "417"
  convolution_param {
    num_output: 128
    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: "418_bn"
  type: "BatchNorm"
  bottom: "417"
  top: "418"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "418"
  type: "Scale"
  bottom: "418"
  top: "418"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "419"
  type: "ReLU"
  bottom: "418"
  top: "419"
}
layer {
  name: "420"
  type: "Convolution"
  bottom: "419"
  top: "420"
  convolution_param {
    num_output: 128
    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: "421_bn"
  type: "BatchNorm"
  bottom: "420"
  top: "421"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "421"
  type: "Scale"
  bottom: "421"
  top: "421"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "422"
  type: "Eltwise"
  bottom: "421"
  bottom: "416"
  top: "422"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "423"
  type: "ReLU"
  bottom: "422"
  top: "423"
}
layer {
  name: "424"
  type: "Concat"
  bottom: "423"
  bottom: "416"
  bottom: "409"
  top: "424"
  concat_param {
    axis: 1
  }
}
layer {
  name: "425"
  type: "Convolution"
  bottom: "424"
  top: "425"
  convolution_param {
    num_output: 128
    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: "426_bn"
  type: "BatchNorm"
  bottom: "425"
  top: "426"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "426"
  type: "Scale"
  bottom: "426"
  top: "426"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "427"
  type: "ReLU"
  bottom: "426"
  top: "427"
}
layer {
  name: "428"
  type: "Pooling"
  bottom: "427"
  top: "428"
  pooling_param {
    pool: MAX
    kernel_h: 2
    kernel_w: 2
    stride_h: 2
    stride_w: 2
    pad_h: 0
    pad_w: 0
  }
}
layer {
  name: "429"
  type: "Convolution"
  bottom: "428"
  top: "429"
  convolution_param {
    num_output: 256
    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: "430_bn"
  type: "BatchNorm"
  bottom: "429"
  top: "430"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "430"
  type: "Scale"
  bottom: "430"
  top: "430"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "431"
  type: "Convolution"
  bottom: "427"
  top: "431"
  convolution_param {
    num_output: 256
    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: "432_bn"
  type: "BatchNorm"
  bottom: "431"
  top: "432"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "432"
  type: "Scale"
  bottom: "432"
  top: "432"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "433"
  type: "ReLU"
  bottom: "432"
  top: "433"
}
layer {
  name: "434"
  type: "Convolution"
  bottom: "433"
  top: "434"
  convolution_param {
    num_output: 256
    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: "435_bn"
  type: "BatchNorm"
  bottom: "434"
  top: "435"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "435"
  type: "Scale"
  bottom: "435"
  top: "435"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "436"
  type: "Eltwise"
  bottom: "435"
  bottom: "430"
  top: "436"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "437"
  type: "ReLU"
  bottom: "436"
  top: "437"
}
layer {
  name: "438"
  type: "Convolution"
  bottom: "437"
  top: "438"
  convolution_param {
    num_output: 256
    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: "439_bn"
  type: "BatchNorm"
  bottom: "438"
  top: "439"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "439"
  type: "Scale"
  bottom: "439"
  top: "439"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "440"
  type: "ReLU"
  bottom: "439"
  top: "440"
}
layer {
  name: "441"
  type: "Convolution"
  bottom: "440"
  top: "441"
  convolution_param {
    num_output: 256
    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: "442_bn"
  type: "BatchNorm"
  bottom: "441"
  top: "442"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "442"
  type: "Scale"
  bottom: "442"
  top: "442"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "443"
  type: "Eltwise"
  bottom: "442"
  bottom: "437"
  top: "443"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "444"
  type: "ReLU"
  bottom: "443"
  top: "444"
}
layer {
  name: "445"
  type: "Concat"
  bottom: "444"
  bottom: "437"
  bottom: "428"
  top: "445"
  concat_param {
    axis: 1
  }
}
layer {
  name: "446"
  type: "Convolution"
  bottom: "445"
  top: "446"
  convolution_param {
    num_output: 256
    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: "447_bn"
  type: "BatchNorm"
  bottom: "446"
  top: "447"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "447"
  type: "Scale"
  bottom: "447"
  top: "447"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "448"
  type: "ReLU"
  bottom: "447"
  top: "448"
}
layer {
  name: "449"
  type: "Convolution"
  bottom: "448"
  top: "449"
  convolution_param {
    num_output: 128
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "450_bn"
  type: "BatchNorm"
  bottom: "449"
  top: "450"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "450"
  type: "Scale"
  bottom: "450"
  top: "450"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "451"
  type: "ReLU"
  bottom: "450"
  top: "451"
}
layer {
  name: "452"
  type: "Deconvolution"
  bottom: "451"
  top: "452"
  convolution_param {
    num_output: 128
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 4
    kernel_w: 4
    stride_h: 2
    stride_w: 2
  }
}
layer {
  name: "453"
  type: "Eltwise"
  bottom: "452"
  bottom: "427"
  top: "453"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "454"
  type: "Convolution"
  bottom: "453"
  top: "454"
  convolution_param {
    num_output: 128
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "455_bn"
  type: "BatchNorm"
  bottom: "454"
  top: "455"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "455"
  type: "Scale"
  bottom: "455"
  top: "455"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "456"
  type: "ReLU"
  bottom: "455"
  top: "456"
}
layer {
  name: "457"
  type: "Convolution"
  bottom: "427"
  top: "457"
  convolution_param {
    num_output: 128
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "458_bn"
  type: "BatchNorm"
  bottom: "457"
  top: "458"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "458"
  type: "Scale"
  bottom: "458"
  top: "458"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "459"
  type: "ReLU"
  bottom: "458"
  top: "459"
}
layer {
  name: "460"
  type: "Deconvolution"
  bottom: "459"
  top: "460"
  convolution_param {
    num_output: 128
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 4
    kernel_w: 4
    stride_h: 2
    stride_w: 2
  }
}
layer {
  name: "461"
  type: "Eltwise"
  bottom: "460"
  bottom: "408"
  top: "461"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "462"
  type: "Convolution"
  bottom: "461"
  top: "462"
  convolution_param {
    num_output: 128
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "463_bn"
  type: "BatchNorm"
  bottom: "462"
  top: "463"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "463"
  type: "Scale"
  bottom: "463"
  top: "463"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "464"
  type: "ReLU"
  bottom: "463"
  top: "464"
}
layer {
  name: "465"
  type: "Convolution"
  bottom: "456"
  top: "465"
  convolution_param {
    num_output: 128
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "466_bn"
  type: "BatchNorm"
  bottom: "465"
  top: "466"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "466"
  type: "Scale"
  bottom: "466"
  top: "466"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "467"
  type: "ReLU"
  bottom: "466"
  top: "467"
}
layer {
  name: "468"
  type: "Deconvolution"
  bottom: "467"
  top: "468"
  convolution_param {
    num_output: 128
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 4
    kernel_w: 4
    stride_h: 2
    stride_w: 2
  }
}
layer {
  name: "469"
  type: "Eltwise"
  bottom: "468"
  bottom: "464"
  top: "469"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "470"
  type: "Convolution"
  bottom: "469"
  top: "470"
  convolution_param {
    num_output: 128
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "471_bn"
  type: "BatchNorm"
  bottom: "470"
  top: "471"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "471"
  type: "Scale"
  bottom: "471"
  top: "471"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "472"
  type: "ReLU"
  bottom: "471"
  top: "472"
}
layer {
  name: "473"
  type: "Convolution"
  bottom: "408"
  top: "473"
  convolution_param {
    num_output: 64
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "474_bn"
  type: "BatchNorm"
  bottom: "473"
  top: "474"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "474"
  type: "Scale"
  bottom: "474"
  top: "474"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "475"
  type: "ReLU"
  bottom: "474"
  top: "475"
}
layer {
  name: "476"
  type: "Deconvolution"
  bottom: "475"
  top: "476"
  convolution_param {
    num_output: 64
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 4
    kernel_w: 4
    stride_h: 2
    stride_w: 2
  }
}
layer {
  name: "477"
  type: "Eltwise"
  bottom: "476"
  bottom: "368"
  top: "477"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "478"
  type: "Convolution"
  bottom: "477"
  top: "478"
  convolution_param {
    num_output: 64
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "479_bn"
  type: "BatchNorm"
  bottom: "478"
  top: "479"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "479"
  type: "Scale"
  bottom: "479"
  top: "479"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "480"
  type: "ReLU"
  bottom: "479"
  top: "480"
}
layer {
  name: "481"
  type: "Convolution"
  bottom: "464"
  top: "481"
  convolution_param {
    num_output: 64
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "482_bn"
  type: "BatchNorm"
  bottom: "481"
  top: "482"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "482"
  type: "Scale"
  bottom: "482"
  top: "482"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "483"
  type: "ReLU"
  bottom: "482"
  top: "483"
}
layer {
  name: "484"
  type: "Deconvolution"
  bottom: "483"
  top: "484"
  convolution_param {
    num_output: 64
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 4
    kernel_w: 4
    stride_h: 2
    stride_w: 2
  }
}
layer {
  name: "485"
  type: "Eltwise"
  bottom: "484"
  bottom: "480"
  top: "485"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "486"
  type: "Convolution"
  bottom: "485"
  top: "486"
  convolution_param {
    num_output: 64
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "487_bn"
  type: "BatchNorm"
  bottom: "486"
  top: "487"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "487"
  type: "Scale"
  bottom: "487"
  top: "487"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "488"
  type: "ReLU"
  bottom: "487"
  top: "488"
}
layer {
  name: "489"
  type: "Convolution"
  bottom: "472"
  top: "489"
  convolution_param {
    num_output: 64
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "490_bn"
  type: "BatchNorm"
  bottom: "489"
  top: "490"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "490"
  type: "Scale"
  bottom: "490"
  top: "490"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "491"
  type: "ReLU"
  bottom: "490"
  top: "491"
}
layer {
  name: "492"
  type: "Deconvolution"
  bottom: "491"
  top: "492"
  convolution_param {
    num_output: 64
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 4
    kernel_w: 4
    stride_h: 2
    stride_w: 2
  }
}
layer {
  name: "493"
  type: "Eltwise"
  bottom: "492"
  bottom: "488"
  top: "493"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "494"
  type: "Convolution"
  bottom: "493"
  top: "494"
  convolution_param {
    num_output: 64
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "495_bn"
  type: "BatchNorm"
  bottom: "494"
  top: "495"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "495"
  type: "Scale"
  bottom: "495"
  top: "495"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "496"
  type: "ReLU"
  bottom: "495"
  top: "496"
}
layer {
  name: "497"
  type: "Convolution"
  bottom: "472"
  top: "497"
  convolution_param {
    num_output: 64
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "498_bn"
  type: "BatchNorm"
  bottom: "497"
  top: "498"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "498"
  type: "Scale"
  bottom: "498"
  top: "498"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "499"
  type: "ReLU"
  bottom: "498"
  top: "499"
}
layer {
  name: "500"
  type: "Deconvolution"
  bottom: "499"
  top: "500"
  convolution_param {
    num_output: 64
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 4
    kernel_w: 4
    stride_h: 2
    stride_w: 2
  }
}
layer {
  name: "501"
  type: "Eltwise"
  bottom: "500"
  bottom: "496"
  top: "501"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "502"
  type: "Convolution"
  bottom: "501"
  top: "502"
  convolution_param {
    num_output: 64
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "503_bn"
  type: "BatchNorm"
  bottom: "502"
  top: "503"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "503"
  type: "Scale"
  bottom: "503"
  top: "503"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "504"
  type: "ReLU"
  bottom: "503"
  top: "504"
}
layer {
  name: "505"
  type: "Convolution"
  bottom: "456"
  top: "505"
  convolution_param {
    num_output: 64
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "506_bn"
  type: "BatchNorm"
  bottom: "505"
  top: "506"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "506"
  type: "Scale"
  bottom: "506"
  top: "506"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "507"
  type: "ReLU"
  bottom: "506"
  top: "507"
}
layer {
  name: "508"
  type: "Deconvolution"
  bottom: "507"
  top: "508"
  convolution_param {
    num_output: 64
    bias_term: false
    group: 1
    pad_h: 2
    pad_w: 2
    kernel_h: 8
    kernel_w: 8
    stride_h: 4
    stride_w: 4
  }
}
layer {
  name: "509"
  type: "Eltwise"
  bottom: "508"
  bottom: "504"
  top: "509"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "510"
  type: "Convolution"
  bottom: "509"
  top: "510"
  convolution_param {
    num_output: 64
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "511_bn"
  type: "BatchNorm"
  bottom: "510"
  top: "511"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "511"
  type: "Scale"
  bottom: "511"
  top: "511"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "512"
  type: "ReLU"
  bottom: "511"
  top: "512"
}
layer {
  name: "513"
  type: "Convolution"
  bottom: "512"
  top: "513"
  convolution_param {
    num_output: 256
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "514"
  type: "ReLU"
  bottom: "513"
  top: "514"
}
layer {
  name: "515"
  type: "Convolution"
  bottom: "514"
  top: "515"
  convolution_param {
    num_output: 1
    bias_term: true
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "516"
  type: "Convolution"
  bottom: "512"
  top: "516"
  convolution_param {
    num_output: 256
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "517"
  type: "ReLU"
  bottom: "516"
  top: "517"
}
layer {
  name: "wh"
  type: "Convolution"
  bottom: "517"
  top: "wh"
  convolution_param {
    num_output: 2
    bias_term: true
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "519"
  type: "Convolution"
  bottom: "512"
  top: "519"
  convolution_param {
    num_output: 256
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "520"
  type: "ReLU"
  bottom: "519"
  top: "520"
}
layer {
  name: "kps"
  type: "Convolution"
  bottom: "520"
  top: "kps"
  convolution_param {
    num_output: 34
    bias_term: true
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "522"
  type: "Convolution"
  bottom: "512"
  top: "522"
  convolution_param {
    num_output: 256
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "523"
  type: "ReLU"
  bottom: "522"
  top: "523"
}
layer {
  name: "reg"
  type: "Convolution"
  bottom: "523"
  top: "reg"
  convolution_param {
    num_output: 2
    bias_term: true
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "525"
  type: "Convolution"
  bottom: "512"
  top: "525"
  convolution_param {
    num_output: 256
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "526"
  type: "ReLU"
  bottom: "525"
  top: "526"
}
layer {
  name: "527"
  type: "Convolution"
  bottom: "526"
  top: "527"
  convolution_param {
    num_output: 17
    bias_term: true
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "528"
  type: "Convolution"
  bottom: "512"
  top: "528"
  convolution_param {
    num_output: 256
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "529"
  type: "ReLU"
  bottom: "528"
  top: "529"
}
layer {
  name: "kp_offset"
  type: "Convolution"
  bottom: "529"
  top: "kp_offset"
  convolution_param {
    num_output: 2
    bias_term: true
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "531"
  type: "Sigmoid"
  bottom: "515"
  top: "531"
}
layer {
  name: "nms_hm"
  type: "Pooling"
  bottom: "531"
  top: "nms_hm"
  pooling_param {
    pool: MAX
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    pad_h: 1
    pad_w: 1
  }
}
layer {
  name: "hm"
  type: "Pooling"
  bottom: "531"
  top: "hm"
  pooling_param {
    pool: MAX
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    pad_h: 0
    pad_w: 0
  }
}
layer {
  name: "534"
  type: "Sigmoid"
  bottom: "527"
  top: "534"
}
layer {
  name: "nms_hm_kp"
  type: "Pooling"
  bottom: "534"
  top: "nms_hm_kp"
  pooling_param {
    pool: MAX
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    pad_h: 1
    pad_w: 1
  }
}
layer {
  name: "hm_kp"
  type: "Pooling"
  bottom: "534"
  top: "hm_kp"
  pooling_param {
    pool: MAX
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    pad_h: 0
    pad_w: 0
  }
}