layer {
  name: "0"
  type: "Input"
  top: "0"
  input_param {
    shape {
      dim: 1
      dim: 3
      dim: 128
      dim: 128
    }
  }
}
layer {
  name: "294"
  type: "Convolution"
  bottom: "0"
  top: "294"
  convolution_param {
    num_output: 32
    bias_term: true
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 2
    stride_w: 2
    dilation: 1
  }
}
layer {
  name: "295_bn"
  type: "BatchNorm"
  bottom: "294"
  top: "295"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "295"
  type: "Scale"
  bottom: "295"
  top: "295"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "296"
  type: "ReLU"
  bottom: "295"
  top: "296"
}
layer {
  name: "297"
  type: "Convolution"
  bottom: "296"
  top: "297"
  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: "298_bn"
  type: "BatchNorm"
  bottom: "297"
  top: "298"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "298"
  type: "Scale"
  bottom: "298"
  top: "298"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "299"
  type: "ReLU"
  bottom: "298"
  top: "299"
}
layer {
  name: "300"
  type: "Convolution"
  bottom: "299"
  top: "300"
  convolution_param {
    num_output: 32
    bias_term: true
    group: 32
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "301_bn"
  type: "BatchNorm"
  bottom: "300"
  top: "301"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "301"
  type: "Scale"
  bottom: "301"
  top: "301"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "302"
  type: "ReLU"
  bottom: "301"
  top: "302"
}
layer {
  name: "303"
  type: "Convolution"
  bottom: "302"
  top: "303"
  convolution_param {
    num_output: 12
    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: "304_bn"
  type: "BatchNorm"
  bottom: "303"
  top: "304"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "304"
  type: "Scale"
  bottom: "304"
  top: "304"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "305"
  type: "Convolution"
  bottom: "304"
  top: "305"
  convolution_param {
    num_output: 72
    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: "306_bn"
  type: "BatchNorm"
  bottom: "305"
  top: "306"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "306"
  type: "Scale"
  bottom: "306"
  top: "306"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "307"
  type: "ReLU"
  bottom: "306"
  top: "307"
}
layer {
  name: "308"
  type: "Convolution"
  bottom: "307"
  top: "308"
  convolution_param {
    num_output: 72
    bias_term: true
    group: 72
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 2
    stride_w: 2
    dilation: 1
  }
}
layer {
  name: "309_bn"
  type: "BatchNorm"
  bottom: "308"
  top: "309"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "309"
  type: "Scale"
  bottom: "309"
  top: "309"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "310"
  type: "ReLU"
  bottom: "309"
  top: "310"
}
layer {
  name: "311"
  type: "Convolution"
  bottom: "310"
  top: "311"
  convolution_param {
    num_output: 18
    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: "312_bn"
  type: "BatchNorm"
  bottom: "311"
  top: "312"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "312"
  type: "Scale"
  bottom: "312"
  top: "312"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "313"
  type: "Convolution"
  bottom: "312"
  top: "313"
  convolution_param {
    num_output: 108
    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: "314_bn"
  type: "BatchNorm"
  bottom: "313"
  top: "314"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "314"
  type: "Scale"
  bottom: "314"
  top: "314"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "315"
  type: "ReLU"
  bottom: "314"
  top: "315"
}
layer {
  name: "316"
  type: "Convolution"
  bottom: "315"
  top: "316"
  convolution_param {
    num_output: 108
    bias_term: true
    group: 108
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "317_bn"
  type: "BatchNorm"
  bottom: "316"
  top: "317"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "317"
  type: "Scale"
  bottom: "317"
  top: "317"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "318"
  type: "ReLU"
  bottom: "317"
  top: "318"
}
layer {
  name: "319"
  type: "Convolution"
  bottom: "318"
  top: "319"
  convolution_param {
    num_output: 18
    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: "320_bn"
  type: "BatchNorm"
  bottom: "319"
  top: "320"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "320"
  type: "Scale"
  bottom: "320"
  top: "320"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "321"
  type: "Eltwise"
  bottom: "312"
  bottom: "320"
  top: "321"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "322"
  type: "Convolution"
  bottom: "321"
  top: "322"
  convolution_param {
    num_output: 108
    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: "323_bn"
  type: "BatchNorm"
  bottom: "322"
  top: "323"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "323"
  type: "Scale"
  bottom: "323"
  top: "323"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "324"
  type: "ReLU"
  bottom: "323"
  top: "324"
}
layer {
  name: "325"
  type: "Convolution"
  bottom: "324"
  top: "325"
  convolution_param {
    num_output: 108
    bias_term: true
    group: 108
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 2
    stride_w: 2
    dilation: 1
  }
}
layer {
  name: "326_bn"
  type: "BatchNorm"
  bottom: "325"
  top: "326"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "326"
  type: "Scale"
  bottom: "326"
  top: "326"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "327"
  type: "ReLU"
  bottom: "326"
  top: "327"
}
layer {
  name: "328"
  type: "Convolution"
  bottom: "327"
  top: "328"
  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: "329_bn"
  type: "BatchNorm"
  bottom: "328"
  top: "329"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "329"
  type: "Scale"
  bottom: "329"
  top: "329"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "330"
  type: "Convolution"
  bottom: "329"
  top: "330"
  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: "331_bn"
  type: "BatchNorm"
  bottom: "330"
  top: "331"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "331"
  type: "Scale"
  bottom: "331"
  top: "331"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "332"
  type: "ReLU"
  bottom: "331"
  top: "332"
}
layer {
  name: "333"
  type: "Convolution"
  bottom: "332"
  top: "333"
  convolution_param {
    num_output: 144
    bias_term: true
    group: 144
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "334_bn"
  type: "BatchNorm"
  bottom: "333"
  top: "334"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "334"
  type: "Scale"
  bottom: "334"
  top: "334"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "335"
  type: "ReLU"
  bottom: "334"
  top: "335"
}
layer {
  name: "336"
  type: "Convolution"
  bottom: "335"
  top: "336"
  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: "337_bn"
  type: "BatchNorm"
  bottom: "336"
  top: "337"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "337"
  type: "Scale"
  bottom: "337"
  top: "337"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "338"
  type: "Eltwise"
  bottom: "329"
  bottom: "337"
  top: "338"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "339"
  type: "Convolution"
  bottom: "338"
  top: "339"
  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: "340_bn"
  type: "BatchNorm"
  bottom: "339"
  top: "340"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-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: 144
    bias_term: true
    group: 144
    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: 9.99999974738e-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: 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: "346_bn"
  type: "BatchNorm"
  bottom: "345"
  top: "346"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "346"
  type: "Scale"
  bottom: "346"
  top: "346"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "347"
  type: "Eltwise"
  bottom: "338"
  bottom: "346"
  top: "347"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "348"
  type: "Convolution"
  bottom: "347"
  top: "348"
  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: "349_bn"
  type: "BatchNorm"
  bottom: "348"
  top: "349"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "349"
  type: "Scale"
  bottom: "349"
  top: "349"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "350"
  type: "ReLU"
  bottom: "349"
  top: "350"
}
layer {
  name: "351"
  type: "Convolution"
  bottom: "350"
  top: "351"
  convolution_param {
    num_output: 144
    bias_term: true
    group: 144
    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: 9.99999974738e-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: 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: "355_bn"
  type: "BatchNorm"
  bottom: "354"
  top: "355"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "355"
  type: "Scale"
  bottom: "355"
  top: "355"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "356"
  type: "Convolution"
  bottom: "355"
  top: "356"
  convolution_param {
    num_output: 288
    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: "357_bn"
  type: "BatchNorm"
  bottom: "356"
  top: "357"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "357"
  type: "Scale"
  bottom: "357"
  top: "357"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "358"
  type: "ReLU"
  bottom: "357"
  top: "358"
}
layer {
  name: "359"
  type: "Convolution"
  bottom: "358"
  top: "359"
  convolution_param {
    num_output: 288
    bias_term: true
    group: 288
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "360_bn"
  type: "BatchNorm"
  bottom: "359"
  top: "360"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "360"
  type: "Scale"
  bottom: "360"
  top: "360"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "361"
  type: "ReLU"
  bottom: "360"
  top: "361"
}
layer {
  name: "362"
  type: "Convolution"
  bottom: "361"
  top: "362"
  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: "363_bn"
  type: "BatchNorm"
  bottom: "362"
  top: "363"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "363"
  type: "Scale"
  bottom: "363"
  top: "363"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "364"
  type: "Eltwise"
  bottom: "355"
  bottom: "363"
  top: "364"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "365"
  type: "Convolution"
  bottom: "364"
  top: "365"
  convolution_param {
    num_output: 288
    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: "366_bn"
  type: "BatchNorm"
  bottom: "365"
  top: "366"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "366"
  type: "Scale"
  bottom: "366"
  top: "366"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "367"
  type: "ReLU"
  bottom: "366"
  top: "367"
}
layer {
  name: "368"
  type: "Convolution"
  bottom: "367"
  top: "368"
  convolution_param {
    num_output: 288
    bias_term: true
    group: 288
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "369_bn"
  type: "BatchNorm"
  bottom: "368"
  top: "369"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "369"
  type: "Scale"
  bottom: "369"
  top: "369"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "370"
  type: "ReLU"
  bottom: "369"
  top: "370"
}
layer {
  name: "371"
  type: "Convolution"
  bottom: "370"
  top: "371"
  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: "372_bn"
  type: "BatchNorm"
  bottom: "371"
  top: "372"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "372"
  type: "Scale"
  bottom: "372"
  top: "372"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "373"
  type: "Eltwise"
  bottom: "364"
  bottom: "372"
  top: "373"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "374"
  type: "Convolution"
  bottom: "373"
  top: "374"
  convolution_param {
    num_output: 288
    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: "375_bn"
  type: "BatchNorm"
  bottom: "374"
  top: "375"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "375"
  type: "Scale"
  bottom: "375"
  top: "375"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "376"
  type: "ReLU"
  bottom: "375"
  top: "376"
}
layer {
  name: "377"
  type: "Convolution"
  bottom: "376"
  top: "377"
  convolution_param {
    num_output: 288
    bias_term: true
    group: 288
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "378_bn"
  type: "BatchNorm"
  bottom: "377"
  top: "378"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "378"
  type: "Scale"
  bottom: "378"
  top: "378"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "379"
  type: "ReLU"
  bottom: "378"
  top: "379"
}
layer {
  name: "380"
  type: "Convolution"
  bottom: "379"
  top: "380"
  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: "381_bn"
  type: "BatchNorm"
  bottom: "380"
  top: "381"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "381"
  type: "Scale"
  bottom: "381"
  top: "381"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "382"
  type: "Eltwise"
  bottom: "373"
  bottom: "381"
  top: "382"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "383"
  type: "Convolution"
  bottom: "382"
  top: "383"
  convolution_param {
    num_output: 288
    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: "384_bn"
  type: "BatchNorm"
  bottom: "383"
  top: "384"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "384"
  type: "Scale"
  bottom: "384"
  top: "384"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "385"
  type: "ReLU"
  bottom: "384"
  top: "385"
}
layer {
  name: "386"
  type: "Convolution"
  bottom: "385"
  top: "386"
  convolution_param {
    num_output: 288
    bias_term: true
    group: 288
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "387_bn"
  type: "BatchNorm"
  bottom: "386"
  top: "387"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "387"
  type: "Scale"
  bottom: "387"
  top: "387"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "388"
  type: "ReLU"
  bottom: "387"
  top: "388"
}
layer {
  name: "389"
  type: "Convolution"
  bottom: "388"
  top: "389"
  convolution_param {
    num_output: 72
    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: "390_bn"
  type: "BatchNorm"
  bottom: "389"
  top: "390"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "390"
  type: "Scale"
  bottom: "390"
  top: "390"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "391"
  type: "Convolution"
  bottom: "390"
  top: "391"
  convolution_param {
    num_output: 432
    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: "392_bn"
  type: "BatchNorm"
  bottom: "391"
  top: "392"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-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: 432
    bias_term: true
    group: 432
    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: 9.99999974738e-06
  }
}
layer {
  name: "395"
  type: "Scale"
  bottom: "395"
  top: "395"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "396"
  type: "ReLU"
  bottom: "395"
  top: "396"
}
layer {
  name: "397"
  type: "Convolution"
  bottom: "396"
  top: "397"
  convolution_param {
    num_output: 72
    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: "398_bn"
  type: "BatchNorm"
  bottom: "397"
  top: "398"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "398"
  type: "Scale"
  bottom: "398"
  top: "398"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "399"
  type: "Eltwise"
  bottom: "390"
  bottom: "398"
  top: "399"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "400"
  type: "Convolution"
  bottom: "399"
  top: "400"
  convolution_param {
    num_output: 432
    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: "401_bn"
  type: "BatchNorm"
  bottom: "400"
  top: "401"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "401"
  type: "Scale"
  bottom: "401"
  top: "401"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "402"
  type: "ReLU"
  bottom: "401"
  top: "402"
}
layer {
  name: "403"
  type: "Convolution"
  bottom: "402"
  top: "403"
  convolution_param {
    num_output: 432
    bias_term: true
    group: 432
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "404_bn"
  type: "BatchNorm"
  bottom: "403"
  top: "404"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "404"
  type: "Scale"
  bottom: "404"
  top: "404"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "405"
  type: "ReLU"
  bottom: "404"
  top: "405"
}
layer {
  name: "406"
  type: "Convolution"
  bottom: "405"
  top: "406"
  convolution_param {
    num_output: 72
    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: 9.99999974738e-06
  }
}
layer {
  name: "407"
  type: "Scale"
  bottom: "407"
  top: "407"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "408"
  type: "Eltwise"
  bottom: "399"
  bottom: "407"
  top: "408"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "409"
  type: "Convolution"
  bottom: "408"
  top: "409"
  convolution_param {
    num_output: 432
    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: "410_bn"
  type: "BatchNorm"
  bottom: "409"
  top: "410"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "410"
  type: "Scale"
  bottom: "410"
  top: "410"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "411"
  type: "ReLU"
  bottom: "410"
  top: "411"
}
layer {
  name: "412"
  type: "Convolution"
  bottom: "411"
  top: "412"
  convolution_param {
    num_output: 432
    bias_term: true
    group: 432
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 2
    stride_w: 2
    dilation: 1
  }
}
layer {
  name: "413_bn"
  type: "BatchNorm"
  bottom: "412"
  top: "413"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "413"
  type: "Scale"
  bottom: "413"
  top: "413"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "414"
  type: "ReLU"
  bottom: "413"
  top: "414"
}
layer {
  name: "415"
  type: "Convolution"
  bottom: "414"
  top: "415"
  convolution_param {
    num_output: 120
    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: "416_bn"
  type: "BatchNorm"
  bottom: "415"
  top: "416"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "416"
  type: "Scale"
  bottom: "416"
  top: "416"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "417"
  type: "Convolution"
  bottom: "416"
  top: "417"
  convolution_param {
    num_output: 720
    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: "418_bn"
  type: "BatchNorm"
  bottom: "417"
  top: "418"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-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: 720
    bias_term: true
    group: 720
    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: 9.99999974738e-06
  }
}
layer {
  name: "421"
  type: "Scale"
  bottom: "421"
  top: "421"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "422"
  type: "ReLU"
  bottom: "421"
  top: "422"
}
layer {
  name: "423"
  type: "Convolution"
  bottom: "422"
  top: "423"
  convolution_param {
    num_output: 120
    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: "424_bn"
  type: "BatchNorm"
  bottom: "423"
  top: "424"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "424"
  type: "Scale"
  bottom: "424"
  top: "424"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "425"
  type: "Eltwise"
  bottom: "416"
  bottom: "424"
  top: "425"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "426"
  type: "Convolution"
  bottom: "425"
  top: "426"
  convolution_param {
    num_output: 720
    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: "427_bn"
  type: "BatchNorm"
  bottom: "426"
  top: "427"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "427"
  type: "Scale"
  bottom: "427"
  top: "427"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "428"
  type: "ReLU"
  bottom: "427"
  top: "428"
}
layer {
  name: "429"
  type: "Convolution"
  bottom: "428"
  top: "429"
  convolution_param {
    num_output: 720
    bias_term: true
    group: 720
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    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: 9.99999974738e-06
  }
}
layer {
  name: "430"
  type: "Scale"
  bottom: "430"
  top: "430"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "431"
  type: "ReLU"
  bottom: "430"
  top: "431"
}
layer {
  name: "432"
  type: "Convolution"
  bottom: "431"
  top: "432"
  convolution_param {
    num_output: 120
    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: "433_bn"
  type: "BatchNorm"
  bottom: "432"
  top: "433"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "433"
  type: "Scale"
  bottom: "433"
  top: "433"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "434"
  type: "Eltwise"
  bottom: "425"
  bottom: "433"
  top: "434"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "435"
  type: "Convolution"
  bottom: "434"
  top: "435"
  convolution_param {
    num_output: 720
    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: "436_bn"
  type: "BatchNorm"
  bottom: "435"
  top: "436"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "436"
  type: "Scale"
  bottom: "436"
  top: "436"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "437"
  type: "ReLU"
  bottom: "436"
  top: "437"
}
layer {
  name: "438"
  type: "Convolution"
  bottom: "437"
  top: "438"
  convolution_param {
    num_output: 720
    bias_term: true
    group: 720
    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: 9.99999974738e-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: 240
    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: "442_bn"
  type: "BatchNorm"
  bottom: "441"
  top: "442"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "442"
  type: "Scale"
  bottom: "442"
  top: "442"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "443"
  type: "Convolution"
  bottom: "442"
  top: "443"
  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: "444_bn"
  type: "BatchNorm"
  bottom: "443"
  top: "444"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "444"
  type: "Scale"
  bottom: "444"
  top: "444"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "445"
  type: "ReLU"
  bottom: "444"
  top: "445"
}
layer {
  name: "446"
  type: "Pooling"
  bottom: "445"
  top: "446"
  pooling_param {
    pool: AVE
    kernel_h: 4
    kernel_w: 4
    stride_h: 4
    stride_w: 4
    pad_h: 0
    pad_w: 0
  }
}
layer {
  name: "448"
  type: "Flatten"
  bottom: "446"
  top: "448"
}
layer {
  name: "449"
  type: "InnerProduct"
  bottom: "448"
  top: "449"
  inner_product_param {
    num_output: 32
    bias_term: true
  }
}
layer {
  name: "450"
  type: "ReLU"
  bottom: "449"
  top: "450"
}
layer {
  name: "451"
  type: "InnerProduct"
  bottom: "450"
  top: "451"
  inner_product_param {
    num_output: 64
    bias_term: true
  }
}
layer {
  name: "452_bn"
  type: "BatchNorm"
  bottom: "451"
  top: "452"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "452"
  type: "Scale"
  bottom: "452"
  top: "452"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "453"
  type: "InnerProduct"
  bottom: "452"
  top: "453"
  inner_product_param {
    num_output: 2
    bias_term: true
  }
}
layer {
	bottom: "453"
	top: "prob"
	name: "prob"
	type: "Softmax"
}