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: "182_Conv"
  type: "Convolution"
  bottom: "0"
  top: "182"
  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: "183_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "182"
  top: "183"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "183_BatchNormalization"
  type: "Scale"
  bottom: "183"
  top: "183"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "184_Relu"
  type: "ReLU"
  bottom: "183"
  top: "184"
}
layer {
  name: "185_Conv"
  type: "Convolution"
  bottom: "184"
  top: "185"
  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: "186_Conv"
  type: "Convolution"
  bottom: "185"
  top: "186"
  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: "187_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "186"
  top: "187"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "187_BatchNormalization"
  type: "Scale"
  bottom: "187"
  top: "187"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "188_Relu"
  type: "ReLU"
  bottom: "187"
  top: "188"
}
layer {
  name: "189_Conv"
  type: "Convolution"
  bottom: "188"
  top: "189"
  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: "190_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "189"
  top: "190"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "190_BatchNormalization"
  type: "Scale"
  bottom: "190"
  top: "190"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "191_Relu"
  type: "ReLU"
  bottom: "190"
  top: "191"
}
layer {
  name: "192_Conv"
  type: "Convolution"
  bottom: "191"
  top: "192"
  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: "193_Conv"
  type: "Convolution"
  bottom: "192"
  top: "193"
  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: "194_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "193"
  top: "194"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "194_BatchNormalization"
  type: "Scale"
  bottom: "194"
  top: "194"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "195_Conv"
  type: "Convolution"
  bottom: "194"
  top: "195"
  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: "196_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "195"
  top: "196"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "196_BatchNormalization"
  type: "Scale"
  bottom: "196"
  top: "196"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "197_Relu"
  type: "ReLU"
  bottom: "196"
  top: "197"
}
layer {
  name: "198_Conv"
  type: "Convolution"
  bottom: "197"
  top: "198"
  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: "199_Conv"
  type: "Convolution"
  bottom: "198"
  top: "199"
  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: "200_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "199"
  top: "200"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "200_BatchNormalization"
  type: "Scale"
  bottom: "200"
  top: "200"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "201_Add"
  type: "Eltwise"
  bottom: "200"
  bottom: "194"
  top: "201"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "202_Conv"
  type: "Convolution"
  bottom: "201"
  top: "202"
  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: "203_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "202"
  top: "203"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "203_BatchNormalization"
  type: "Scale"
  bottom: "203"
  top: "203"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "204_Relu"
  type: "ReLU"
  bottom: "203"
  top: "204"
}
layer {
  name: "205_Conv"
  type: "Convolution"
  bottom: "204"
  top: "205"
  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: "206_Conv"
  type: "Convolution"
  bottom: "205"
  top: "206"
  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: "207_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "206"
  top: "207"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "207_BatchNormalization"
  type: "Scale"
  bottom: "207"
  top: "207"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "208_Add"
  type: "Eltwise"
  bottom: "207"
  bottom: "201"
  top: "208"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "209_Conv"
  type: "Convolution"
  bottom: "208"
  top: "209"
  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: "210_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "209"
  top: "210"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "210_BatchNormalization"
  type: "Scale"
  bottom: "210"
  top: "210"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "211_Relu"
  type: "ReLU"
  bottom: "210"
  top: "211"
}
layer {
  name: "212_Conv"
  type: "Convolution"
  bottom: "211"
  top: "212"
  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: "213_Conv"
  type: "Convolution"
  bottom: "212"
  top: "213"
  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: "214_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "213"
  top: "214"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "214_BatchNormalization"
  type: "Scale"
  bottom: "214"
  top: "214"
  scale_param {
    bias_term: true
  }
}
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: 9.999999747378752e-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: 2
    pad_w: 2
    kernel_h: 5
    kernel_w: 5
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "219_Conv"
  type: "Convolution"
  bottom: "218"
  top: "219"
  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: "220_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "219"
  top: "220"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "220_BatchNormalization"
  type: "Scale"
  bottom: "220"
  top: "220"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "221_Add"
  type: "Eltwise"
  bottom: "220"
  bottom: "214"
  top: "221"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "222_Conv"
  type: "Convolution"
  bottom: "221"
  top: "222"
  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: "223_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "222"
  top: "223"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "223_BatchNormalization"
  type: "Scale"
  bottom: "223"
  top: "223"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "224_Relu"
  type: "ReLU"
  bottom: "223"
  top: "224"
}
layer {
  name: "225_Conv"
  type: "Convolution"
  bottom: "224"
  top: "225"
  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: "226_Conv"
  type: "Convolution"
  bottom: "225"
  top: "226"
  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: "227_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "226"
  top: "227"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "227_BatchNormalization"
  type: "Scale"
  bottom: "227"
  top: "227"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "228_Add"
  type: "Eltwise"
  bottom: "227"
  bottom: "221"
  top: "228"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "229_Conv"
  type: "Convolution"
  bottom: "228"
  top: "229"
  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: "230_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "229"
  top: "230"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "230_BatchNormalization"
  type: "Scale"
  bottom: "230"
  top: "230"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "231_Relu"
  type: "ReLU"
  bottom: "230"
  top: "231"
}
layer {
  name: "232_Conv"
  type: "Convolution"
  bottom: "231"
  top: "232"
  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: "233_Conv"
  type: "Convolution"
  bottom: "232"
  top: "233"
  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: "234_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "233"
  top: "234"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "234_BatchNormalization"
  type: "Scale"
  bottom: "234"
  top: "234"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "235_Conv"
  type: "Convolution"
  bottom: "234"
  top: "235"
  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: "236_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "235"
  top: "236"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-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: 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: "239_Conv"
  type: "Convolution"
  bottom: "238"
  top: "239"
  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: "240_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "239"
  top: "240"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "240_BatchNormalization"
  type: "Scale"
  bottom: "240"
  top: "240"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "241_Add"
  type: "Eltwise"
  bottom: "240"
  bottom: "234"
  top: "241"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "242_Conv"
  type: "Convolution"
  bottom: "241"
  top: "242"
  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: "243_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "242"
  top: "243"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "243_BatchNormalization"
  type: "Scale"
  bottom: "243"
  top: "243"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "244_Relu"
  type: "ReLU"
  bottom: "243"
  top: "244"
}
layer {
  name: "245_Conv"
  type: "Convolution"
  bottom: "244"
  top: "245"
  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: "246_Conv"
  type: "Convolution"
  bottom: "245"
  top: "246"
  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: "247_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "246"
  top: "247"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "247_BatchNormalization"
  type: "Scale"
  bottom: "247"
  top: "247"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "248_Add"
  type: "Eltwise"
  bottom: "247"
  bottom: "241"
  top: "248"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "249_Conv"
  type: "Convolution"
  bottom: "248"
  top: "249"
  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: "250_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "249"
  top: "250"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "250_BatchNormalization"
  type: "Scale"
  bottom: "250"
  top: "250"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "251_Relu"
  type: "ReLU"
  bottom: "250"
  top: "251"
}
layer {
  name: "252_Conv"
  type: "Convolution"
  bottom: "251"
  top: "252"
  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: "253_Conv"
  type: "Convolution"
  bottom: "252"
  top: "253"
  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: "254_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "253"
  top: "254"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "254_BatchNormalization"
  type: "Scale"
  bottom: "254"
  top: "254"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "255_Conv"
  type: "Convolution"
  bottom: "254"
  top: "255"
  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: "256_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "255"
  top: "256"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-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: 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: "259_Conv"
  type: "Convolution"
  bottom: "258"
  top: "259"
  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: "260_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "259"
  top: "260"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "260_BatchNormalization"
  type: "Scale"
  bottom: "260"
  top: "260"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "261_Add"
  type: "Eltwise"
  bottom: "260"
  bottom: "254"
  top: "261"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "262_Conv"
  type: "Convolution"
  bottom: "261"
  top: "262"
  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: "263_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "262"
  top: "263"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "263_BatchNormalization"
  type: "Scale"
  bottom: "263"
  top: "263"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "264_Relu"
  type: "ReLU"
  bottom: "263"
  top: "264"
}
layer {
  name: "265_Conv"
  type: "Convolution"
  bottom: "264"
  top: "265"
  convolution_param {
    num_output: 384
    bias_term: false
    group: 384
    pad_h: 0
    pad_w: 2
    kernel_h: 2
    kernel_w: 5
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "266_Conv"
  type: "Convolution"
  bottom: "265"
  top: "266"
  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: "267_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "266"
  top: "267"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "267_BatchNormalization"
  type: "Scale"
  bottom: "267"
  top: "267"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "268_Conv"
  type: "Convolution"
  bottom: "267"
  top: "268"
  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: "269_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "268"
  top: "269"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-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: 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: "272_BatchNormalization_bn"
  type: "BatchNorm"
  bottom: "271"
  top: "272"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "272_BatchNormalization"
  type: "Scale"
  bottom: "272"
  top: "272"
  scale_param {
    bias_term: true
  }
}
layer {
  name:"ArgMax"
  type: "ArgMax"
  bottom: "272"
  top: "ArgMax"
  argmax_param {
    axis: 1
  }
}