layer {
  name: "input.1"
  type: "Input"
  top: "input.1"
  input_param {
    shape {
      dim: 1
      dim: 3
      dim: 224
      dim: 224
    }
  }
}
layer {
  name: "319_Conv"
  type: "Convolution"
  bottom: "input.1"
  top: "319"
  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: "320_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "319"
  top: "320"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "320_BatchNormalization"
  type: "Scale"
  bottom: "320"
  top: "320"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "321_Relu"
  type: "ReLU"
  bottom: "320"
  top: "321"
}
layer {
  name: "322_Conv"
  type: "Convolution"
  bottom: "321"
  top: "322"
  convolution_param {
    num_output: 32
    bias_term: false
    group: 32
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "323_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "322"
  top: "323"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "323_BatchNormalization"
  type: "Scale"
  bottom: "323"
  top: "323"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "324_Relu"
  type: "ReLU"
  bottom: "323"
  top: "324"
}
layer {
  name: "325_Conv"
  type: "Convolution"
  bottom: "324"
  top: "325"
  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: "326_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "325"
  top: "326"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "326_BatchNormalization"
  type: "Scale"
  bottom: "326"
  top: "326"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "327_Conv"
  type: "Convolution"
  bottom: "326"
  top: "327"
  convolution_param {
    num_output: 96
    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: "328_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "327"
  top: "328"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "328_BatchNormalization"
  type: "Scale"
  bottom: "328"
  top: "328"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "329_Relu"
  type: "ReLU"
  bottom: "328"
  top: "329"
}
layer {
  name: "330_Conv"
  type: "Convolution"
  bottom: "329"
  top: "330"
  convolution_param {
    num_output: 96
    bias_term: false
    group: 96
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 2
    stride_w: 2
    dilation: 1
  }
}
layer {
  name: "331_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "330"
  top: "331"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "331_BatchNormalization"
  type: "Scale"
  bottom: "331"
  top: "331"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "332_Relu"
  type: "ReLU"
  bottom: "331"
  top: "332"
}
layer {
  name: "333_Conv"
  type: "Convolution"
  bottom: "332"
  top: "333"
  convolution_param {
    num_output: 24
    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: "334_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "333"
  top: "334"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "334_BatchNormalization"
  type: "Scale"
  bottom: "334"
  top: "334"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "335_Conv"
  type: "Convolution"
  bottom: "334"
  top: "335"
  convolution_param {
    num_output: 144
    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: "336_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "335"
  top: "336"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "336_BatchNormalization"
  type: "Scale"
  bottom: "336"
  top: "336"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "337_Relu"
  type: "ReLU"
  bottom: "336"
  top: "337"
}
layer {
  name: "338_Conv"
  type: "Convolution"
  bottom: "337"
  top: "338"
  convolution_param {
    num_output: 144
    bias_term: false
    group: 144
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "339_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "338"
  top: "339"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "339_BatchNormalization"
  type: "Scale"
  bottom: "339"
  top: "339"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "340_Relu"
  type: "ReLU"
  bottom: "339"
  top: "340"
}
layer {
  name: "341_Conv"
  type: "Convolution"
  bottom: "340"
  top: "341"
  convolution_param {
    num_output: 24
    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: "342_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "341"
  top: "342"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "342_BatchNormalization"
  type: "Scale"
  bottom: "342"
  top: "342"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "343_Add"
  type: "Eltwise"
  bottom: "334"
  bottom: "342"
  top: "343"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "344_Conv"
  type: "Convolution"
  bottom: "343"
  top: "344"
  convolution_param {
    num_output: 144
    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: "345_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "344"
  top: "345"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "345_BatchNormalization"
  type: "Scale"
  bottom: "345"
  top: "345"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "346_Relu"
  type: "ReLU"
  bottom: "345"
  top: "346"
}
layer {
  name: "347_Conv"
  type: "Convolution"
  bottom: "346"
  top: "347"
  convolution_param {
    num_output: 144
    bias_term: false
    group: 144
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 2
    stride_w: 2
    dilation: 1
  }
}
layer {
  name: "348_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "347"
  top: "348"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "348_BatchNormalization"
  type: "Scale"
  bottom: "348"
  top: "348"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "349_Relu"
  type: "ReLU"
  bottom: "348"
  top: "349"
}
layer {
  name: "350_Conv"
  type: "Convolution"
  bottom: "349"
  top: "350"
  convolution_param {
    num_output: 32
    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: "351_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "350"
  top: "351"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "351_BatchNormalization"
  type: "Scale"
  bottom: "351"
  top: "351"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "352_Conv"
  type: "Convolution"
  bottom: "351"
  top: "352"
  convolution_param {
    num_output: 192
    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: "353_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "352"
  top: "353"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "353_BatchNormalization"
  type: "Scale"
  bottom: "353"
  top: "353"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "354_Relu"
  type: "ReLU"
  bottom: "353"
  top: "354"
}
layer {
  name: "355_Conv"
  type: "Convolution"
  bottom: "354"
  top: "355"
  convolution_param {
    num_output: 192
    bias_term: false
    group: 192
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "356_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "355"
  top: "356"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "356_BatchNormalization"
  type: "Scale"
  bottom: "356"
  top: "356"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "357_Relu"
  type: "ReLU"
  bottom: "356"
  top: "357"
}
layer {
  name: "358_Conv"
  type: "Convolution"
  bottom: "357"
  top: "358"
  convolution_param {
    num_output: 32
    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: "359_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "358"
  top: "359"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "359_BatchNormalization"
  type: "Scale"
  bottom: "359"
  top: "359"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "360_Add"
  type: "Eltwise"
  bottom: "351"
  bottom: "359"
  top: "360"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "361_Conv"
  type: "Convolution"
  bottom: "360"
  top: "361"
  convolution_param {
    num_output: 192
    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: "362_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "361"
  top: "362"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "362_BatchNormalization"
  type: "Scale"
  bottom: "362"
  top: "362"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "363_Relu"
  type: "ReLU"
  bottom: "362"
  top: "363"
}
layer {
  name: "364_Conv"
  type: "Convolution"
  bottom: "363"
  top: "364"
  convolution_param {
    num_output: 192
    bias_term: false
    group: 192
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "365_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "364"
  top: "365"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "365_BatchNormalization"
  type: "Scale"
  bottom: "365"
  top: "365"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "366_Relu"
  type: "ReLU"
  bottom: "365"
  top: "366"
}
layer {
  name: "367_Conv"
  type: "Convolution"
  bottom: "366"
  top: "367"
  convolution_param {
    num_output: 32
    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: "368_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "367"
  top: "368"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "368_BatchNormalization"
  type: "Scale"
  bottom: "368"
  top: "368"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "369_Add"
  type: "Eltwise"
  bottom: "360"
  bottom: "368"
  top: "369"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "370_Conv"
  type: "Convolution"
  bottom: "369"
  top: "370"
  convolution_param {
    num_output: 192
    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: "371_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "370"
  top: "371"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "371_BatchNormalization"
  type: "Scale"
  bottom: "371"
  top: "371"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "372_Relu"
  type: "ReLU"
  bottom: "371"
  top: "372"
}
layer {
  name: "373_Conv"
  type: "Convolution"
  bottom: "372"
  top: "373"
  convolution_param {
    num_output: 192
    bias_term: false
    group: 192
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 2
    stride_w: 2
    dilation: 1
  }
}
layer {
  name: "374_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "373"
  top: "374"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "374_BatchNormalization"
  type: "Scale"
  bottom: "374"
  top: "374"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "375_Relu"
  type: "ReLU"
  bottom: "374"
  top: "375"
}
layer {
  name: "376_Conv"
  type: "Convolution"
  bottom: "375"
  top: "376"
  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: "377_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "376"
  top: "377"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "377_BatchNormalization"
  type: "Scale"
  bottom: "377"
  top: "377"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "378_Conv"
  type: "Convolution"
  bottom: "377"
  top: "378"
  convolution_param {
    num_output: 384
    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: "379_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "378"
  top: "379"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "379_BatchNormalization"
  type: "Scale"
  bottom: "379"
  top: "379"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "380_Relu"
  type: "ReLU"
  bottom: "379"
  top: "380"
}
layer {
  name: "381_Conv"
  type: "Convolution"
  bottom: "380"
  top: "381"
  convolution_param {
    num_output: 384
    bias_term: false
    group: 384
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "382_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "381"
  top: "382"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "382_BatchNormalization"
  type: "Scale"
  bottom: "382"
  top: "382"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "383_Relu"
  type: "ReLU"
  bottom: "382"
  top: "383"
}
layer {
  name: "384_Conv"
  type: "Convolution"
  bottom: "383"
  top: "384"
  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: "385_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "384"
  top: "385"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "385_BatchNormalization"
  type: "Scale"
  bottom: "385"
  top: "385"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "386_Add"
  type: "Eltwise"
  bottom: "377"
  bottom: "385"
  top: "386"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "387_Conv"
  type: "Convolution"
  bottom: "386"
  top: "387"
  convolution_param {
    num_output: 384
    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: "388_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "387"
  top: "388"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "388_BatchNormalization"
  type: "Scale"
  bottom: "388"
  top: "388"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "389_Relu"
  type: "ReLU"
  bottom: "388"
  top: "389"
}
layer {
  name: "390_Conv"
  type: "Convolution"
  bottom: "389"
  top: "390"
  convolution_param {
    num_output: 384
    bias_term: false
    group: 384
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "391_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "390"
  top: "391"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "391_BatchNormalization"
  type: "Scale"
  bottom: "391"
  top: "391"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "392_Relu"
  type: "ReLU"
  bottom: "391"
  top: "392"
}
layer {
  name: "393_Conv"
  type: "Convolution"
  bottom: "392"
  top: "393"
  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: "394_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "393"
  top: "394"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "394_BatchNormalization"
  type: "Scale"
  bottom: "394"
  top: "394"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "395_Add"
  type: "Eltwise"
  bottom: "386"
  bottom: "394"
  top: "395"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "396_Conv"
  type: "Convolution"
  bottom: "395"
  top: "396"
  convolution_param {
    num_output: 384
    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: "397_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "396"
  top: "397"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "397_BatchNormalization"
  type: "Scale"
  bottom: "397"
  top: "397"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "398_Relu"
  type: "ReLU"
  bottom: "397"
  top: "398"
}
layer {
  name: "399_Conv"
  type: "Convolution"
  bottom: "398"
  top: "399"
  convolution_param {
    num_output: 384
    bias_term: false
    group: 384
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "400_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "399"
  top: "400"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "400_BatchNormalization"
  type: "Scale"
  bottom: "400"
  top: "400"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "401_Relu"
  type: "ReLU"
  bottom: "400"
  top: "401"
}
layer {
  name: "402_Conv"
  type: "Convolution"
  bottom: "401"
  top: "402"
  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: "403_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "402"
  top: "403"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "403_BatchNormalization"
  type: "Scale"
  bottom: "403"
  top: "403"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "404_Add"
  type: "Eltwise"
  bottom: "395"
  bottom: "403"
  top: "404"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "405_Conv"
  type: "Convolution"
  bottom: "404"
  top: "405"
  convolution_param {
    num_output: 384
    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: "406_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "405"
  top: "406"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "406_BatchNormalization"
  type: "Scale"
  bottom: "406"
  top: "406"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "407_Relu"
  type: "ReLU"
  bottom: "406"
  top: "407"
}
layer {
  name: "408_Conv"
  type: "Convolution"
  bottom: "407"
  top: "408"
  convolution_param {
    num_output: 384
    bias_term: false
    group: 384
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "409_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "408"
  top: "409"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "409_BatchNormalization"
  type: "Scale"
  bottom: "409"
  top: "409"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "410_Relu"
  type: "ReLU"
  bottom: "409"
  top: "410"
}
layer {
  name: "411_Conv"
  type: "Convolution"
  bottom: "410"
  top: "411"
  convolution_param {
    num_output: 96
    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: "412_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "411"
  top: "412"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "412_BatchNormalization"
  type: "Scale"
  bottom: "412"
  top: "412"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "413_Conv"
  type: "Convolution"
  bottom: "412"
  top: "413"
  convolution_param {
    num_output: 576
    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: "414_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "413"
  top: "414"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "414_BatchNormalization"
  type: "Scale"
  bottom: "414"
  top: "414"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "415_Relu"
  type: "ReLU"
  bottom: "414"
  top: "415"
}
layer {
  name: "416_Conv"
  type: "Convolution"
  bottom: "415"
  top: "416"
  convolution_param {
    num_output: 576
    bias_term: false
    group: 576
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "417_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "416"
  top: "417"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "417_BatchNormalization"
  type: "Scale"
  bottom: "417"
  top: "417"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "418_Relu"
  type: "ReLU"
  bottom: "417"
  top: "418"
}
layer {
  name: "419_Conv"
  type: "Convolution"
  bottom: "418"
  top: "419"
  convolution_param {
    num_output: 96
    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: "420_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "419"
  top: "420"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "420_BatchNormalization"
  type: "Scale"
  bottom: "420"
  top: "420"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "421_Add"
  type: "Eltwise"
  bottom: "412"
  bottom: "420"
  top: "421"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "422_Conv"
  type: "Convolution"
  bottom: "421"
  top: "422"
  convolution_param {
    num_output: 576
    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: "423_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "422"
  top: "423"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "423_BatchNormalization"
  type: "Scale"
  bottom: "423"
  top: "423"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "424_Relu"
  type: "ReLU"
  bottom: "423"
  top: "424"
}
layer {
  name: "425_Conv"
  type: "Convolution"
  bottom: "424"
  top: "425"
  convolution_param {
    num_output: 576
    bias_term: false
    group: 576
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "426_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "425"
  top: "426"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "426_BatchNormalization"
  type: "Scale"
  bottom: "426"
  top: "426"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "427_Relu"
  type: "ReLU"
  bottom: "426"
  top: "427"
}
layer {
  name: "428_Conv"
  type: "Convolution"
  bottom: "427"
  top: "428"
  convolution_param {
    num_output: 96
    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: "429_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "428"
  top: "429"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "429_BatchNormalization"
  type: "Scale"
  bottom: "429"
  top: "429"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "430_Add"
  type: "Eltwise"
  bottom: "421"
  bottom: "429"
  top: "430"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "431_Conv"
  type: "Convolution"
  bottom: "430"
  top: "431"
  convolution_param {
    num_output: 576
    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: "432_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "431"
  top: "432"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "432_BatchNormalization"
  type: "Scale"
  bottom: "432"
  top: "432"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "433_Relu"
  type: "ReLU"
  bottom: "432"
  top: "433"
}
layer {
  name: "434_Conv"
  type: "Convolution"
  bottom: "433"
  top: "434"
  convolution_param {
    num_output: 576
    bias_term: false
    group: 576
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 2
    stride_w: 2
    dilation: 1
  }
}
layer {
  name: "435_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "434"
  top: "435"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "435_BatchNormalization"
  type: "Scale"
  bottom: "435"
  top: "435"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "436_Relu"
  type: "ReLU"
  bottom: "435"
  top: "436"
}
layer {
  name: "437_Conv"
  type: "Convolution"
  bottom: "436"
  top: "437"
  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: "438_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "437"
  top: "438"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "438_BatchNormalization"
  type: "Scale"
  bottom: "438"
  top: "438"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "439_Conv"
  type: "Convolution"
  bottom: "438"
  top: "439"
  convolution_param {
    num_output: 960
    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: "440_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "439"
  top: "440"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "440_BatchNormalization"
  type: "Scale"
  bottom: "440"
  top: "440"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "441_Relu"
  type: "ReLU"
  bottom: "440"
  top: "441"
}
layer {
  name: "442_Conv"
  type: "Convolution"
  bottom: "441"
  top: "442"
  convolution_param {
    num_output: 960
    bias_term: false
    group: 960
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "443_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "442"
  top: "443"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "443_BatchNormalization"
  type: "Scale"
  bottom: "443"
  top: "443"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "444_Relu"
  type: "ReLU"
  bottom: "443"
  top: "444"
}
layer {
  name: "445_Conv"
  type: "Convolution"
  bottom: "444"
  top: "445"
  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: "446_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "445"
  top: "446"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "446_BatchNormalization"
  type: "Scale"
  bottom: "446"
  top: "446"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "447_Add"
  type: "Eltwise"
  bottom: "438"
  bottom: "446"
  top: "447"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "448_Conv"
  type: "Convolution"
  bottom: "447"
  top: "448"
  convolution_param {
    num_output: 960
    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: "449_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "448"
  top: "449"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "449_BatchNormalization"
  type: "Scale"
  bottom: "449"
  top: "449"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "450_Relu"
  type: "ReLU"
  bottom: "449"
  top: "450"
}
layer {
  name: "451_Conv"
  type: "Convolution"
  bottom: "450"
  top: "451"
  convolution_param {
    num_output: 960
    bias_term: false
    group: 960
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "452_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "451"
  top: "452"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "452_BatchNormalization"
  type: "Scale"
  bottom: "452"
  top: "452"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "453_Relu"
  type: "ReLU"
  bottom: "452"
  top: "453"
}
layer {
  name: "454_Conv"
  type: "Convolution"
  bottom: "453"
  top: "454"
  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: "455_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "454"
  top: "455"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "455_BatchNormalization"
  type: "Scale"
  bottom: "455"
  top: "455"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "456_Add"
  type: "Eltwise"
  bottom: "447"
  bottom: "455"
  top: "456"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "457_Conv"
  type: "Convolution"
  bottom: "456"
  top: "457"
  convolution_param {
    num_output: 960
    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: "458_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "457"
  top: "458"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "458_BatchNormalization"
  type: "Scale"
  bottom: "458"
  top: "458"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "459_Relu"
  type: "ReLU"
  bottom: "458"
  top: "459"
}
layer {
  name: "460_Conv"
  type: "Convolution"
  bottom: "459"
  top: "460"
  convolution_param {
    num_output: 960
    bias_term: false
    group: 960
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "461_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "460"
  top: "461"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "461_BatchNormalization"
  type: "Scale"
  bottom: "461"
  top: "461"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "462_Relu"
  type: "ReLU"
  bottom: "461"
  top: "462"
}
layer {
  name: "463_Conv"
  type: "Convolution"
  bottom: "462"
  top: "463"
  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: "464_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "463"
  top: "464"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "464_BatchNormalization"
  type: "Scale"
  bottom: "464"
  top: "464"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "465_Conv"
  type: "Convolution"
  bottom: "464"
  top: "465"
  convolution_param {
    num_output: 1280
    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: "466_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "465"
  top: "466"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "466_BatchNormalization"
  type: "Scale"
  bottom: "466"
  top: "466"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "467_Relu"
  type: "ReLU"
  bottom: "466"
  top: "467"
}
layer {
  name: "468_AveragePool"
  type: "Pooling"
  bottom: "467"
  top: "468"
  pooling_param {
    pool: AVE
    kernel_h: 7
    kernel_w: 7
    stride_h: 7
    stride_w: 7
    pad_h: 0
    pad_w: 0
  }
}
layer {
  name: "470_Reshape"
  type: "Reshape"
  bottom: "468"
  top: "470"
  reshape_param {
    shape {
      dim: -1
      dim: 1280
    }
  }
}
layer {
  name: "471_Gemm"
  type: "InnerProduct"
  bottom: "470"
  top: "471"
  inner_product_param {
    num_output: 410
    bias_term: true
  }
}
layer {
  name: "472_Gemm"
  type: "InnerProduct"
  bottom: "470"
  top: "472"
  inner_product_param {
    num_output: 113
    bias_term: true
  }
}
layer {
  name: "473_Gemm"
  type: "InnerProduct"
  bottom: "470"
  top: "473"
  inner_product_param {
    num_output: 1
    bias_term: true
  }
}
layer {
  name: "474_Sigmoid"
  type: "Sigmoid"
  bottom: "471"
  top: "474"
}
layer {
  name: "475_Sigmoid"
  type: "Sigmoid"
  bottom: "472"
  top: "475"
}
layer {
  name: "476_Sigmoid"
  type: "Sigmoid"
  bottom: "473"
  top: "476"
}