layer {
  name: "input"
  type: "Input"
  top: "data"
  input_param {
    shape {
      dim: 1
      dim: 1
      dim: 32
      dim: 512
    }
  }
}
layer {
	name: "power-data"
	type: "Power"
	bottom: "data"
	top: "0"
	power_param {
		scale: 0.0039215686274
		shift: -0.67
	}
}
layer {
  name: "308_Conv"
  type: "Convolution"
  bottom: "0"
  top: "308"
  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: "309_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "308"
  top: "309"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "309_BatchNormalization"
  type: "Scale"
  bottom: "309"
  top: "309"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "310_Relu"
  type: "ReLU"
  bottom: "309"
  top: "310"
}
layer {
  name: "311_Conv"
  type: "Convolution"
  bottom: "310"
  top: "311"
  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: "312_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "311"
  top: "312"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "312_BatchNormalization"
  type: "Scale"
  bottom: "312"
  top: "312"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "313_Relu"
  type: "ReLU"
  bottom: "312"
  top: "313"
}
layer {
  name: "314_Conv"
  type: "Convolution"
  bottom: "313"
  top: "314"
  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: "315_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "314"
  top: "315"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "315_BatchNormalization"
  type: "Scale"
  bottom: "315"
  top: "315"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "316_Conv"
  type: "Convolution"
  bottom: "315"
  top: "316"
  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: "317_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "316"
  top: "317"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "317_BatchNormalization"
  type: "Scale"
  bottom: "317"
  top: "317"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "318_Relu"
  type: "ReLU"
  bottom: "317"
  top: "318"
}
layer {
  name: "319_Conv"
  type: "Convolution"
  bottom: "318"
  top: "319"
  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: "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: 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: "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_Conv"
  type: "Convolution"
  bottom: "323"
  top: "324"
  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: "325_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "324"
  top: "325"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "325_BatchNormalization"
  type: "Scale"
  bottom: "325"
  top: "325"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "326_Relu"
  type: "ReLU"
  bottom: "325"
  top: "326"
}
layer {
  name: "327_Conv"
  type: "Convolution"
  bottom: "326"
  top: "327"
  convolution_param {
    num_output: 72
    bias_term: false
    group: 72
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    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: 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: "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_Add"
  type: "Eltwise"
  bottom: "331"
  bottom: "323"
  top: "332"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "333_Conv"
  type: "Convolution"
  bottom: "332"
  top: "333"
  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: "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_Relu"
  type: "ReLU"
  bottom: "334"
  top: "335"
}
layer {
  name: "336_Conv"
  type: "Convolution"
  bottom: "335"
  top: "336"
  convolution_param {
    num_output: 72
    bias_term: false
    group: 72
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "337_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "336"
  top: "337"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "337_BatchNormalization"
  type: "Scale"
  bottom: "337"
  top: "337"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "338_Relu"
  type: "ReLU"
  bottom: "337"
  top: "338"
}
layer {
  name: "339_Conv"
  type: "Convolution"
  bottom: "338"
  top: "339"
  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: "340_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "339"
  top: "340"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "340_BatchNormalization"
  type: "Scale"
  bottom: "340"
  top: "340"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "341_Add"
  type: "Eltwise"
  bottom: "340"
  bottom: "332"
  top: "341"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "342_Conv"
  type: "Convolution"
  bottom: "341"
  top: "342"
  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: "343_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "342"
  top: "343"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "343_BatchNormalization"
  type: "Scale"
  bottom: "343"
  top: "343"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "344_Relu"
  type: "ReLU"
  bottom: "343"
  top: "344"
}
layer {
  name: "345_Conv"
  type: "Convolution"
  bottom: "344"
  top: "345"
  convolution_param {
    num_output: 72
    bias_term: false
    group: 72
    pad_h: 2
    pad_w: 2
    kernel_h: 5
    kernel_w: 5
    stride_h: 2
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "346_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "345"
  top: "346"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "346_BatchNormalization"
  type: "Scale"
  bottom: "346"
  top: "346"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "347_Relu"
  type: "ReLU"
  bottom: "346"
  top: "347"
}
layer {
  name: "348_Conv"
  type: "Convolution"
  bottom: "347"
  top: "348"
  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: "349_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "348"
  top: "349"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "349_BatchNormalization"
  type: "Scale"
  bottom: "349"
  top: "349"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "350_Conv"
  type: "Convolution"
  bottom: "349"
  top: "350"
  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: "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_Relu"
  type: "ReLU"
  bottom: "351"
  top: "352"
}
layer {
  name: "353_Conv"
  type: "Convolution"
  bottom: "352"
  top: "353"
  convolution_param {
    num_output: 96
    bias_term: false
    group: 96
    pad_h: 2
    pad_w: 2
    kernel_h: 5
    kernel_w: 5
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "354_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "353"
  top: "354"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "354_BatchNormalization"
  type: "Scale"
  bottom: "354"
  top: "354"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "355_Relu"
  type: "ReLU"
  bottom: "354"
  top: "355"
}
layer {
  name: "356_Conv"
  type: "Convolution"
  bottom: "355"
  top: "356"
  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: "357_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "356"
  top: "357"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "357_BatchNormalization"
  type: "Scale"
  bottom: "357"
  top: "357"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "358_Add"
  type: "Eltwise"
  bottom: "357"
  bottom: "349"
  top: "358"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "359_Conv"
  type: "Convolution"
  bottom: "358"
  top: "359"
  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: "360_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "359"
  top: "360"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "360_BatchNormalization"
  type: "Scale"
  bottom: "360"
  top: "360"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "361_Relu"
  type: "ReLU"
  bottom: "360"
  top: "361"
}
layer {
  name: "362_Conv"
  type: "Convolution"
  bottom: "361"
  top: "362"
  convolution_param {
    num_output: 96
    bias_term: false
    group: 96
    pad_h: 2
    pad_w: 2
    kernel_h: 5
    kernel_w: 5
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "363_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "362"
  top: "363"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "363_BatchNormalization"
  type: "Scale"
  bottom: "363"
  top: "363"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "364_Relu"
  type: "ReLU"
  bottom: "363"
  top: "364"
}
layer {
  name: "365_Conv"
  type: "Convolution"
  bottom: "364"
  top: "365"
  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: "366_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "365"
  top: "366"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "366_BatchNormalization"
  type: "Scale"
  bottom: "366"
  top: "366"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "367_Add"
  type: "Eltwise"
  bottom: "366"
  bottom: "358"
  top: "367"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "368_Conv"
  type: "Convolution"
  bottom: "367"
  top: "368"
  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: "369_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "368"
  top: "369"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "369_BatchNormalization"
  type: "Scale"
  bottom: "369"
  top: "369"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "370_Relu"
  type: "ReLU"
  bottom: "369"
  top: "370"
}
layer {
  name: "371_Conv"
  type: "Convolution"
  bottom: "370"
  top: "371"
  convolution_param {
    num_output: 192
    bias_term: false
    group: 192
    pad_h: 2
    pad_w: 2
    kernel_h: 5
    kernel_w: 5
    stride_h: 2
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "372_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "371"
  top: "372"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "372_BatchNormalization"
  type: "Scale"
  bottom: "372"
  top: "372"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "373_Relu"
  type: "ReLU"
  bottom: "372"
  top: "373"
}
layer {
  name: "374_Conv"
  type: "Convolution"
  bottom: "373"
  top: "374"
  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: "375_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "374"
  top: "375"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "375_BatchNormalization"
  type: "Scale"
  bottom: "375"
  top: "375"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "376_Conv"
  type: "Convolution"
  bottom: "375"
  top: "376"
  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: "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_Relu"
  type: "ReLU"
  bottom: "377"
  top: "378"
}
layer {
  name: "379_Conv"
  type: "Convolution"
  bottom: "378"
  top: "379"
  convolution_param {
    num_output: 288
    bias_term: false
    group: 288
    pad_h: 2
    pad_w: 2
    kernel_h: 5
    kernel_w: 5
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "380_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "379"
  top: "380"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "380_BatchNormalization"
  type: "Scale"
  bottom: "380"
  top: "380"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "381_Relu"
  type: "ReLU"
  bottom: "380"
  top: "381"
}
layer {
  name: "382_Conv"
  type: "Convolution"
  bottom: "381"
  top: "382"
  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: "383_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "382"
  top: "383"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "383_BatchNormalization"
  type: "Scale"
  bottom: "383"
  top: "383"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "384_Add"
  type: "Eltwise"
  bottom: "383"
  bottom: "375"
  top: "384"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "385_Conv"
  type: "Convolution"
  bottom: "384"
  top: "385"
  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: "386_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "385"
  top: "386"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "386_BatchNormalization"
  type: "Scale"
  bottom: "386"
  top: "386"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "387_Relu"
  type: "ReLU"
  bottom: "386"
  top: "387"
}
layer {
  name: "388_Conv"
  type: "Convolution"
  bottom: "387"
  top: "388"
  convolution_param {
    num_output: 288
    bias_term: false
    group: 288
    pad_h: 2
    pad_w: 2
    kernel_h: 5
    kernel_w: 5
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "389_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "388"
  top: "389"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "389_BatchNormalization"
  type: "Scale"
  bottom: "389"
  top: "389"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "390_Relu"
  type: "ReLU"
  bottom: "389"
  top: "390"
}
layer {
  name: "391_Conv"
  type: "Convolution"
  bottom: "390"
  top: "391"
  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: "392_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "391"
  top: "392"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "392_BatchNormalization"
  type: "Scale"
  bottom: "392"
  top: "392"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "393_Add"
  type: "Eltwise"
  bottom: "392"
  bottom: "384"
  top: "393"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "394_Conv"
  type: "Convolution"
  bottom: "393"
  top: "394"
  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: "395_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "394"
  top: "395"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "395_BatchNormalization"
  type: "Scale"
  bottom: "395"
  top: "395"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "396_Relu"
  type: "ReLU"
  bottom: "395"
  top: "396"
}
layer {
  name: "397_Conv"
  type: "Convolution"
  bottom: "396"
  top: "397"
  convolution_param {
    num_output: 288
    bias_term: false
    group: 288
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "398_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "397"
  top: "398"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "398_BatchNormalization"
  type: "Scale"
  bottom: "398"
  top: "398"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "399_Relu"
  type: "ReLU"
  bottom: "398"
  top: "399"
}
layer {
  name: "400_Conv"
  type: "Convolution"
  bottom: "399"
  top: "400"
  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: "401_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "400"
  top: "401"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "401_BatchNormalization"
  type: "Scale"
  bottom: "401"
  top: "401"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "402_Conv"
  type: "Convolution"
  bottom: "401"
  top: "402"
  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: "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_Relu"
  type: "ReLU"
  bottom: "403"
  top: "404"
}
layer {
  name: "405_Conv"
  type: "Convolution"
  bottom: "404"
  top: "405"
  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: "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: 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: "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_Add"
  type: "Eltwise"
  bottom: "409"
  bottom: "401"
  top: "410"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "411_Conv"
  type: "Convolution"
  bottom: "410"
  top: "411"
  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: "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_Relu"
  type: "ReLU"
  bottom: "412"
  top: "413"
}
layer {
  name: "414_Conv"
  type: "Convolution"
  bottom: "413"
  top: "414"
  convolution_param {
    num_output: 384
    bias_term: false
    group: 384
    pad_h: 0
    pad_w: 2
    kernel_h: 1
    kernel_w: 5
    stride_h: 2
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "415_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "414"
  top: "415"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "415_BatchNormalization"
  type: "Scale"
  bottom: "415"
  top: "415"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "416_Relu"
  type: "ReLU"
  bottom: "415"
  top: "416"
}
layer {
  name: "417_Conv"
  type: "Convolution"
  bottom: "416"
  top: "417"
  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: "418_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "417"
  top: "418"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "418_BatchNormalization"
  type: "Scale"
  bottom: "418"
  top: "418"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "419_Conv"
  type: "Convolution"
  bottom: "418"
  top: "419"
  convolution_param {
    num_output: 512
    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_Relu"
  type: "ReLU"
  bottom: "420"
  top: "421"
}
layer {
  name: "422_Conv"
  type: "Convolution"
  bottom: "421"
  top: "422"
  convolution_param {
    num_output: 512
    bias_term: false
    group: 512
    pad_h: 0
    pad_w: 2
    kernel_h: 1
    kernel_w: 5
    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: 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_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_Add"
  type: "Eltwise"
  bottom: "426"
  bottom: "418"
  top: "427"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "428_Conv"
  type: "Convolution"
  bottom: "427"
  top: "428"
  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: "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_Relu"
  type: "ReLU"
  bottom: "429"
  top: "430"
}
layer {
  name: "431_Conv"
  type: "Convolution"
  bottom: "430"
  top: "431"
  convolution_param {
    num_output: 384
    bias_term: false
    group: 384
    pad_h: 0
    pad_w: 1
    kernel_h: 1
    kernel_w: 3
    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: 152
    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: "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_Conv"
  type: "Convolution"
  bottom: "435"
  top: "436"
  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: "437_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "436"
  top: "437"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "437_BatchNormalization"
  type: "Scale"
  bottom: "437"
  top: "437"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "438_Relu"
  type: "ReLU"
  bottom: "437"
  top: "438"
}
layer {
  name: "439_Conv"
  type: "Convolution"
  bottom: "438"
  top: "439"
  convolution_param {
    num_output: 96
    bias_term: true
    group: 1
    pad_h: 0
    pad_w: 2
    kernel_h: 1
    kernel_w: 5
    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: "438"
  top: "442"
  convolution_param {
    num_output: 96
    bias_term: true
    group: 1
    pad_h: 0
    pad_w: 2
    kernel_h: 1
    kernel_w: 5
    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_Sigmoid"
  type: "Sigmoid"
  bottom: "444"
  top: "445"
}
layer {
  name: "446_Mul"
  type: "Eltwise"
  bottom: "441"
  bottom: "445"
  top: "446"
  eltwise_param {
    operation: PROD
  }
}
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: 10
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "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_Conv"
  type: "Convolution"
  bottom: "447"
  top: "450"
  convolution_param {
    num_output: 1
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "451_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "450"
  top: "451"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "451_BatchNormalization"
  type: "Scale"
  bottom: "451"
  top: "451"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "452_Conv"
  type: "Convolution"
  bottom: "447"
  top: "452"
  convolution_param {
    num_output: 1
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "453_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "452"
  top: "453"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "453_BatchNormalization"
  type: "Scale"
  bottom: "453"
  top: "453"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "454_Conv"
  type: "Convolution"
  bottom: "447"
  top: "454"
  convolution_param {
    num_output: 1
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "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_Concat"
  type: "Concat"
  bottom: "449"
  bottom: "451"
  bottom: "453"
  bottom: "455"
  top: "456"
  concat_param {
    axis: 1
  }
}
layer {
  name:"ArgMax"
  type: "ArgMax"
  bottom: "456"
  top: "ArgMax"
  argmax_param {
    axis: 1
  }
}