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: "208_Conv"
  type: "Convolution"
  bottom: "0"
  top: "208"
  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: "209_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "208"
  top: "209"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "209_BatchNormalization"
  type: "Scale"
  bottom: "209"
  top: "209"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "210_Relu"
  type: "ReLU"
  bottom: "209"
  top: "210"
}
layer {
  name: "211_Conv"
  type: "Convolution"
  bottom: "210"
  top: "211"
  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: "212_Conv"
  type: "Convolution"
  bottom: "211"
  top: "212"
  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: "213_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "212"
  top: "213"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "213_BatchNormalization"
  type: "Scale"
  bottom: "213"
  top: "213"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "214_Relu"
  type: "ReLU"
  bottom: "213"
  top: "214"
}
layer {
  name: "215_Conv"
  type: "Convolution"
  bottom: "214"
  top: "215"
  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: "216_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "215"
  top: "216"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "216_BatchNormalization"
  type: "Scale"
  bottom: "216"
  top: "216"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "217_Relu"
  type: "ReLU"
  bottom: "216"
  top: "217"
}
layer {
  name: "218_Conv"
  type: "Convolution"
  bottom: "217"
  top: "218"
  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: "219_Conv"
  type: "Convolution"
  bottom: "218"
  top: "219"
  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: "220_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "219"
  top: "220"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "220_BatchNormalization"
  type: "Scale"
  bottom: "220"
  top: "220"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "221_Conv"
  type: "Convolution"
  bottom: "220"
  top: "221"
  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: "222_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "221"
  top: "222"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "222_BatchNormalization"
  type: "Scale"
  bottom: "222"
  top: "222"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "223_Relu"
  type: "ReLU"
  bottom: "222"
  top: "223"
}
layer {
  name: "224_Conv"
  type: "Convolution"
  bottom: "223"
  top: "224"
  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: "225_Conv"
  type: "Convolution"
  bottom: "224"
  top: "225"
  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: "226_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "225"
  top: "226"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "226_BatchNormalization"
  type: "Scale"
  bottom: "226"
  top: "226"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "227_Add"
  type: "Eltwise"
  bottom: "226"
  bottom: "220"
  top: "227"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "228_Conv"
  type: "Convolution"
  bottom: "227"
  top: "228"
  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: "229_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "228"
  top: "229"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "229_BatchNormalization"
  type: "Scale"
  bottom: "229"
  top: "229"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "230_Relu"
  type: "ReLU"
  bottom: "229"
  top: "230"
}
layer {
  name: "231_Conv"
  type: "Convolution"
  bottom: "230"
  top: "231"
  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: "232_Conv"
  type: "Convolution"
  bottom: "231"
  top: "232"
  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: "233_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "232"
  top: "233"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "233_BatchNormalization"
  type: "Scale"
  bottom: "233"
  top: "233"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "234_Add"
  type: "Eltwise"
  bottom: "233"
  bottom: "227"
  top: "234"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "235_Conv"
  type: "Convolution"
  bottom: "234"
  top: "235"
  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: "236_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "235"
  top: "236"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "236_BatchNormalization"
  type: "Scale"
  bottom: "236"
  top: "236"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "237_Relu"
  type: "ReLU"
  bottom: "236"
  top: "237"
}
layer {
  name: "238_Conv"
  type: "Convolution"
  bottom: "237"
  top: "238"
  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: 2
    dilation: 1
  }
}
layer {
  name: "239_Conv"
  type: "Convolution"
  bottom: "238"
  top: "239"
  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: "240_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "239"
  top: "240"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "240_BatchNormalization"
  type: "Scale"
  bottom: "240"
  top: "240"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "241_Conv"
  type: "Convolution"
  bottom: "240"
  top: "241"
  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: "242_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "241"
  top: "242"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "242_BatchNormalization"
  type: "Scale"
  bottom: "242"
  top: "242"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "243_Relu"
  type: "ReLU"
  bottom: "242"
  top: "243"
}
layer {
  name: "244_Conv"
  type: "Convolution"
  bottom: "243"
  top: "244"
  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: "245_Conv"
  type: "Convolution"
  bottom: "244"
  top: "245"
  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: "246_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "245"
  top: "246"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "246_BatchNormalization"
  type: "Scale"
  bottom: "246"
  top: "246"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "247_Add"
  type: "Eltwise"
  bottom: "246"
  bottom: "240"
  top: "247"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "248_Conv"
  type: "Convolution"
  bottom: "247"
  top: "248"
  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: "249_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "248"
  top: "249"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "249_BatchNormalization"
  type: "Scale"
  bottom: "249"
  top: "249"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "250_Relu"
  type: "ReLU"
  bottom: "249"
  top: "250"
}
layer {
  name: "251_Conv"
  type: "Convolution"
  bottom: "250"
  top: "251"
  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: "252_Conv"
  type: "Convolution"
  bottom: "251"
  top: "252"
  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: "253_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "252"
  top: "253"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "253_BatchNormalization"
  type: "Scale"
  bottom: "253"
  top: "253"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "254_Add"
  type: "Eltwise"
  bottom: "253"
  bottom: "247"
  top: "254"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "255_Conv"
  type: "Convolution"
  bottom: "254"
  top: "255"
  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: "256_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "255"
  top: "256"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "256_BatchNormalization"
  type: "Scale"
  bottom: "256"
  top: "256"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "257_Relu"
  type: "ReLU"
  bottom: "256"
  top: "257"
}
layer {
  name: "258_Conv"
  type: "Convolution"
  bottom: "257"
  top: "258"
  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: "259_Conv"
  type: "Convolution"
  bottom: "258"
  top: "259"
  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: "260_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "259"
  top: "260"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "260_BatchNormalization"
  type: "Scale"
  bottom: "260"
  top: "260"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "261_Conv"
  type: "Convolution"
  bottom: "260"
  top: "261"
  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: "262_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "261"
  top: "262"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "262_BatchNormalization"
  type: "Scale"
  bottom: "262"
  top: "262"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "263_Relu"
  type: "ReLU"
  bottom: "262"
  top: "263"
}
layer {
  name: "264_Conv"
  type: "Convolution"
  bottom: "263"
  top: "264"
  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: "265_Conv"
  type: "Convolution"
  bottom: "264"
  top: "265"
  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: "266_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "265"
  top: "266"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "266_BatchNormalization"
  type: "Scale"
  bottom: "266"
  top: "266"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "267_Add"
  type: "Eltwise"
  bottom: "266"
  bottom: "260"
  top: "267"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "268_Conv"
  type: "Convolution"
  bottom: "267"
  top: "268"
  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: "269_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "268"
  top: "269"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "269_BatchNormalization"
  type: "Scale"
  bottom: "269"
  top: "269"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "270_Relu"
  type: "ReLU"
  bottom: "269"
  top: "270"
}
layer {
  name: "271_Conv"
  type: "Convolution"
  bottom: "270"
  top: "271"
  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: "272_Conv"
  type: "Convolution"
  bottom: "271"
  top: "272"
  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: "273_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "272"
  top: "273"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "273_BatchNormalization"
  type: "Scale"
  bottom: "273"
  top: "273"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "274_Add"
  type: "Eltwise"
  bottom: "273"
  bottom: "267"
  top: "274"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "275_Conv"
  type: "Convolution"
  bottom: "274"
  top: "275"
  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: "276_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "275"
  top: "276"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "276_BatchNormalization"
  type: "Scale"
  bottom: "276"
  top: "276"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "277_Relu"
  type: "ReLU"
  bottom: "276"
  top: "277"
}
layer {
  name: "278_Conv"
  type: "Convolution"
  bottom: "277"
  top: "278"
  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: "279_Conv"
  type: "Convolution"
  bottom: "278"
  top: "279"
  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: "280_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "279"
  top: "280"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "280_BatchNormalization"
  type: "Scale"
  bottom: "280"
  top: "280"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "281_Conv"
  type: "Convolution"
  bottom: "280"
  top: "281"
  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: "282_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "281"
  top: "282"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "282_BatchNormalization"
  type: "Scale"
  bottom: "282"
  top: "282"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "283_Relu"
  type: "ReLU"
  bottom: "282"
  top: "283"
}
layer {
  name: "284_Conv"
  type: "Convolution"
  bottom: "283"
  top: "284"
  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: "285_Conv"
  type: "Convolution"
  bottom: "284"
  top: "285"
  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: "286_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "285"
  top: "286"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "286_BatchNormalization"
  type: "Scale"
  bottom: "286"
  top: "286"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "287_Add"
  type: "Eltwise"
  bottom: "286"
  bottom: "280"
  top: "287"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "288_Conv"
  type: "Convolution"
  bottom: "287"
  top: "288"
  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: "289_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "288"
  top: "289"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "289_BatchNormalization"
  type: "Scale"
  bottom: "289"
  top: "289"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "290_Relu"
  type: "ReLU"
  bottom: "289"
  top: "290"
}
layer {
  name: "291_Conv"
  type: "Convolution"
  bottom: "290"
  top: "291"
  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: "292_Conv"
  type: "Convolution"
  bottom: "291"
  top: "292"
  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: "293_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "292"
  top: "293"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "293_BatchNormalization"
  type: "Scale"
  bottom: "293"
  top: "293"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "294_Conv"
  type: "Convolution"
  bottom: "293"
  top: "294"
  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: "295_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "294"
  top: "295"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "295_BatchNormalization"
  type: "Scale"
  bottom: "295"
  top: "295"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "296_Relu"
  type: "ReLU"
  bottom: "295"
  top: "296"
}
layer {
  name: "297_Conv"
  type: "Convolution"
  bottom: "296"
  top: "297"
  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: "298_Conv"
  type: "Convolution"
  bottom: "297"
  top: "298"
  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: "299_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "298"
  top: "299"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "299_BatchNormalization"
  type: "Scale"
  bottom: "299"
  top: "299"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "300_Add"
  type: "Eltwise"
  bottom: "299"
  bottom: "293"
  top: "300"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "301_Conv"
  type: "Convolution"
  bottom: "300"
  top: "301"
  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: "302_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "301"
  top: "302"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "302_BatchNormalization"
  type: "Scale"
  bottom: "302"
  top: "302"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "303_Relu"
  type: "ReLU"
  bottom: "302"
  top: "303"
}
layer {
  name: "304_Conv"
  type: "Convolution"
  bottom: "303"
  top: "304"
  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: "305_Conv"
  type: "Convolution"
  bottom: "304"
  top: "305"
  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: "306_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "305"
  top: "306"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "306_BatchNormalization"
  type: "Scale"
  bottom: "306"
  top: "306"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "307_Conv"
  type: "Convolution"
  bottom: "306"
  top: "307"
  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: "308_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "307"
  top: "308"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "308_BatchNormalization"
  type: "Scale"
  bottom: "308"
  top: "308"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "309_Relu"
  type: "ReLU"
  bottom: "308"
  top: "309"
}
layer {
  name: "310_Conv"
  type: "Convolution"
  bottom: "309"
  top: "310"
  convolution_param {
    num_output: 7358
    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: "311_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "310"
  top: "311"
  batch_norm_param {
    use_global_stats: true
    eps: 9.99999974738e-06
  }
}
layer {
  name: "311_BatchNormalization"
  type: "Scale"
  bottom: "311"
  top: "311"
  scale_param {
    bias_term: true
  }
}
layer {
  name:"ArgMax"
  type: "ArgMax"
  bottom: "311"
  top: "ArgMax"
  argmax_param {
    axis: 1
  }
}