name: "pytorch"
input: "data"
input_dim: 1
input_dim: 3
input_dim: 256
input_dim: 256

layer {
    name: "ConvNdBackward1"
    type: "Convolution"
    bottom: "data"
    top: "ConvNdBackward1"
    convolution_param {
        num_output: 8
        group: 1
        pad_h: 1
        pad_w: 1
        kernel_h: 3
        kernel_w: 3
        stride: 2
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward2_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward1"
    top: "BatchNormBackward2"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward2_scale"
    type: "Scale"
    bottom: "BatchNormBackward2"
    top: "BatchNormBackward2"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward3"
    type: "ReLU"
    bottom: "BatchNormBackward2"
    top: "BatchNormBackward2"
}
layer {
    name: "ConvNdBackward4"
    type: "Convolution"
    bottom: "BatchNormBackward2"
    top: "ConvNdBackward4"
    convolution_param {
        num_output: 8
        group: 8
        pad_h: 1
        pad_w: 1
        kernel_h: 3
        kernel_w: 3
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward5_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward4"
    top: "BatchNormBackward5"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward5_scale"
    type: "Scale"
    bottom: "BatchNormBackward5"
    top: "BatchNormBackward5"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward6"
    type: "ReLU"
    bottom: "BatchNormBackward5"
    top: "BatchNormBackward5"
}
layer {
    name: "ConvNdBackward7"
    type: "Convolution"
    bottom: "BatchNormBackward5"
    top: "ConvNdBackward7"
    convolution_param {
        num_output: 16
        group: 1
        pad_h: 0
        pad_w: 0
        kernel_h: 1
        kernel_w: 1
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward8_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward7"
    top: "BatchNormBackward8"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward8_scale"
    type: "Scale"
    bottom: "BatchNormBackward8"
    top: "BatchNormBackward8"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward9"
    type: "ReLU"
    bottom: "BatchNormBackward8"
    top: "BatchNormBackward8"
}
layer {
    name: "ConvNdBackward10"
    type: "Convolution"
    bottom: "BatchNormBackward8"
    top: "ConvNdBackward10"
    convolution_param {
        num_output: 16
        group: 16
        pad_h: 1
        pad_w: 1
        kernel_h: 3
        kernel_w: 3
        stride: 2
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward11_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward10"
    top: "BatchNormBackward11"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward11_scale"
    type: "Scale"
    bottom: "BatchNormBackward11"
    top: "BatchNormBackward11"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward12"
    type: "ReLU"
    bottom: "BatchNormBackward11"
    top: "BatchNormBackward11"
}
layer {
    name: "ConvNdBackward13"
    type: "Convolution"
    bottom: "BatchNormBackward11"
    top: "ConvNdBackward13"
    convolution_param {
        num_output: 32
        group: 1
        pad_h: 0
        pad_w: 0
        kernel_h: 1
        kernel_w: 1
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward14_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward13"
    top: "BatchNormBackward14"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward14_scale"
    type: "Scale"
    bottom: "BatchNormBackward14"
    top: "BatchNormBackward14"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward15"
    type: "ReLU"
    bottom: "BatchNormBackward14"
    top: "BatchNormBackward14"
}
layer {
    name: "ConvNdBackward16"
    type: "Convolution"
    bottom: "BatchNormBackward14"
    top: "ConvNdBackward16"
    convolution_param {
        num_output: 32
        group: 32
        pad_h: 1
        pad_w: 1
        kernel_h: 3
        kernel_w: 3
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward17_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward16"
    top: "BatchNormBackward17"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward17_scale"
    type: "Scale"
    bottom: "BatchNormBackward17"
    top: "BatchNormBackward17"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward18"
    type: "ReLU"
    bottom: "BatchNormBackward17"
    top: "BatchNormBackward17"
}
layer {
    name: "ConvNdBackward19"
    type: "Convolution"
    bottom: "BatchNormBackward17"
    top: "ConvNdBackward19"
    convolution_param {
        num_output: 32
        group: 1
        pad_h: 0
        pad_w: 0
        kernel_h: 1
        kernel_w: 1
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward20_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward19"
    top: "BatchNormBackward20"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward20_scale"
    type: "Scale"
    bottom: "BatchNormBackward20"
    top: "BatchNormBackward20"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward21"
    type: "ReLU"
    bottom: "BatchNormBackward20"
    top: "BatchNormBackward20"
}
layer {
    name: "ConvNdBackward22"
    type: "Convolution"
    bottom: "BatchNormBackward20"
    top: "ConvNdBackward22"
    convolution_param {
        num_output: 32
        group: 32
        pad_h: 1
        pad_w: 1
        kernel_h: 3
        kernel_w: 3
        stride: 2
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward23_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward22"
    top: "BatchNormBackward23"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward23_scale"
    type: "Scale"
    bottom: "BatchNormBackward23"
    top: "BatchNormBackward23"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward24"
    type: "ReLU"
    bottom: "BatchNormBackward23"
    top: "BatchNormBackward23"
}
layer {
    name: "ConvNdBackward25"
    type: "Convolution"
    bottom: "BatchNormBackward23"
    top: "ConvNdBackward25"
    convolution_param {
        num_output: 64
        group: 1
        pad_h: 0
        pad_w: 0
        kernel_h: 1
        kernel_w: 1
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward26_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward25"
    top: "BatchNormBackward26"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward26_scale"
    type: "Scale"
    bottom: "BatchNormBackward26"
    top: "BatchNormBackward26"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward27"
    type: "ReLU"
    bottom: "BatchNormBackward26"
    top: "BatchNormBackward26"
}
layer {
    name: "ConvNdBackward28"
    type: "Convolution"
    bottom: "BatchNormBackward26"
    top: "ConvNdBackward28"
    convolution_param {
        num_output: 64
        group: 64
        pad_h: 1
        pad_w: 1
        kernel_h: 3
        kernel_w: 3
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward29_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward28"
    top: "BatchNormBackward29"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward29_scale"
    type: "Scale"
    bottom: "BatchNormBackward29"
    top: "BatchNormBackward29"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward30"
    type: "ReLU"
    bottom: "BatchNormBackward29"
    top: "BatchNormBackward29"
}
layer {
    name: "ConvNdBackward31"
    type: "Convolution"
    bottom: "BatchNormBackward29"
    top: "ConvNdBackward31"
    convolution_param {
        num_output: 64
        group: 1
        pad_h: 0
        pad_w: 0
        kernel_h: 1
        kernel_w: 1
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward32_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward31"
    top: "BatchNormBackward32"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward32_scale"
    type: "Scale"
    bottom: "BatchNormBackward32"
    top: "BatchNormBackward32"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward33"
    type: "ReLU"
    bottom: "BatchNormBackward32"
    top: "BatchNormBackward32"
}
layer {
    name: "ConvNdBackward34"
    type: "Convolution"
    bottom: "BatchNormBackward32"
    top: "ConvNdBackward34"
    convolution_param {
        num_output: 64
        group: 64
        pad_h: 1
        pad_w: 1
        kernel_h: 3
        kernel_w: 3
        stride: 2
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward35_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward34"
    top: "BatchNormBackward35"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward35_scale"
    type: "Scale"
    bottom: "BatchNormBackward35"
    top: "BatchNormBackward35"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward36"
    type: "ReLU"
    bottom: "BatchNormBackward35"
    top: "BatchNormBackward35"
}
layer {
    name: "ConvNdBackward37"
    type: "Convolution"
    bottom: "BatchNormBackward35"
    top: "ConvNdBackward37"
    convolution_param {
        num_output: 128
        group: 1
        pad_h: 0
        pad_w: 0
        kernel_h: 1
        kernel_w: 1
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward38_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward37"
    top: "BatchNormBackward38"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward38_scale"
    type: "Scale"
    bottom: "BatchNormBackward38"
    top: "BatchNormBackward38"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward39"
    type: "ReLU"
    bottom: "BatchNormBackward38"
    top: "BatchNormBackward38"
}
layer {
    name: "ConvNdBackward40"
    type: "Convolution"
    bottom: "BatchNormBackward38"
    top: "ConvNdBackward40"
    convolution_param {
        num_output: 128
        group: 128
        pad_h: 1
        pad_w: 1
        kernel_h: 3
        kernel_w: 3
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward41_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward40"
    top: "BatchNormBackward41"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward41_scale"
    type: "Scale"
    bottom: "BatchNormBackward41"
    top: "BatchNormBackward41"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward42"
    type: "ReLU"
    bottom: "BatchNormBackward41"
    top: "BatchNormBackward41"
}
layer {
    name: "ConvNdBackward43"
    type: "Convolution"
    bottom: "BatchNormBackward41"
    top: "ConvNdBackward43"
    convolution_param {
        num_output: 128
        group: 1
        pad_h: 0
        pad_w: 0
        kernel_h: 1
        kernel_w: 1
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward44_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward43"
    top: "BatchNormBackward44"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward44_scale"
    type: "Scale"
    bottom: "BatchNormBackward44"
    top: "BatchNormBackward44"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward45"
    type: "ReLU"
    bottom: "BatchNormBackward44"
    top: "BatchNormBackward44"
}
layer {
    name: "ConvNdBackward46"
    type: "Convolution"
    bottom: "BatchNormBackward44"
    top: "ConvNdBackward46"
    convolution_param {
        num_output: 128
        group: 128
        pad_h: 1
        pad_w: 1
        kernel_h: 3
        kernel_w: 3
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward47_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward46"
    top: "BatchNormBackward47"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward47_scale"
    type: "Scale"
    bottom: "BatchNormBackward47"
    top: "BatchNormBackward47"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward48"
    type: "ReLU"
    bottom: "BatchNormBackward47"
    top: "BatchNormBackward47"
}
layer {
    name: "ConvNdBackward49"
    type: "Convolution"
    bottom: "BatchNormBackward47"
    top: "ConvNdBackward49"
    convolution_param {
        num_output: 128
        group: 1
        pad_h: 0
        pad_w: 0
        kernel_h: 1
        kernel_w: 1
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward50_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward49"
    top: "BatchNormBackward50"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward50_scale"
    type: "Scale"
    bottom: "BatchNormBackward50"
    top: "BatchNormBackward50"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward51"
    type: "ReLU"
    bottom: "BatchNormBackward50"
    top: "BatchNormBackward50"
}
layer {
    name: "ConvNdBackward52"
    type: "Convolution"
    bottom: "BatchNormBackward50"
    top: "ConvNdBackward52"
    convolution_param {
        num_output: 128
        group: 128
        pad_h: 1
        pad_w: 1
        kernel_h: 3
        kernel_w: 3
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward53_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward52"
    top: "BatchNormBackward53"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward53_scale"
    type: "Scale"
    bottom: "BatchNormBackward53"
    top: "BatchNormBackward53"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward54"
    type: "ReLU"
    bottom: "BatchNormBackward53"
    top: "BatchNormBackward53"
}
layer {
    name: "ConvNdBackward55"
    type: "Convolution"
    bottom: "BatchNormBackward53"
    top: "ConvNdBackward55"
    convolution_param {
        num_output: 128
        group: 1
        pad_h: 0
        pad_w: 0
        kernel_h: 1
        kernel_w: 1
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward56_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward55"
    top: "BatchNormBackward56"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward56_scale"
    type: "Scale"
    bottom: "BatchNormBackward56"
    top: "BatchNormBackward56"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward57"
    type: "ReLU"
    bottom: "BatchNormBackward56"
    top: "BatchNormBackward56"
}
layer {
    name: "ConvNdBackward58"
    type: "Convolution"
    bottom: "BatchNormBackward56"
    top: "ConvNdBackward58"
    convolution_param {
        num_output: 128
        group: 128
        pad_h: 1
        pad_w: 1
        kernel_h: 3
        kernel_w: 3
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward59_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward58"
    top: "BatchNormBackward59"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward59_scale"
    type: "Scale"
    bottom: "BatchNormBackward59"
    top: "BatchNormBackward59"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward60"
    type: "ReLU"
    bottom: "BatchNormBackward59"
    top: "BatchNormBackward59"
}
layer {
    name: "ConvNdBackward61"
    type: "Convolution"
    bottom: "BatchNormBackward59"
    top: "ConvNdBackward61"
    convolution_param {
        num_output: 128
        group: 1
        pad_h: 0
        pad_w: 0
        kernel_h: 1
        kernel_w: 1
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward62_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward61"
    top: "BatchNormBackward62"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward62_scale"
    type: "Scale"
    bottom: "BatchNormBackward62"
    top: "BatchNormBackward62"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward63"
    type: "ReLU"
    bottom: "BatchNormBackward62"
    top: "BatchNormBackward62"
}
layer {
    name: "ConvNdBackward64"
    type: "Convolution"
    bottom: "BatchNormBackward62"
    top: "ConvNdBackward64"
    convolution_param {
        num_output: 128
        group: 128
        pad_h: 1
        pad_w: 1
        kernel_h: 3
        kernel_w: 3
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward65_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward64"
    top: "BatchNormBackward65"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward65_scale"
    type: "Scale"
    bottom: "BatchNormBackward65"
    top: "BatchNormBackward65"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward66"
    type: "ReLU"
    bottom: "BatchNormBackward65"
    top: "BatchNormBackward65"
}
layer {
    name: "ConvNdBackward67"
    type: "Convolution"
    bottom: "BatchNormBackward65"
    top: "ConvNdBackward67"
    convolution_param {
        num_output: 128
        group: 1
        pad_h: 0
        pad_w: 0
        kernel_h: 1
        kernel_w: 1
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward68_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward67"
    top: "BatchNormBackward68"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward68_scale"
    type: "Scale"
    bottom: "BatchNormBackward68"
    top: "BatchNormBackward68"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward69"
    type: "ReLU"
    bottom: "BatchNormBackward68"
    top: "BatchNormBackward68"
}
layer {
    name: "ConvNdBackward70"
    type: "Convolution"
    bottom: "BatchNormBackward68"
    top: "ConvNdBackward70"
    convolution_param {
        num_output: 128
        group: 128
        pad_h: 1
        pad_w: 1
        kernel_h: 3
        kernel_w: 3
        stride: 2
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward71_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward70"
    top: "BatchNormBackward71"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward71_scale"
    type: "Scale"
    bottom: "BatchNormBackward71"
    top: "BatchNormBackward71"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward72"
    type: "ReLU"
    bottom: "BatchNormBackward71"
    top: "BatchNormBackward71"
}
layer {
    name: "ConvNdBackward73"
    type: "Convolution"
    bottom: "BatchNormBackward71"
    top: "ConvNdBackward73"
    convolution_param {
        num_output: 256
        group: 1
        pad_h: 0
        pad_w: 0
        kernel_h: 1
        kernel_w: 1
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward74_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward73"
    top: "BatchNormBackward74"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward74_scale"
    type: "Scale"
    bottom: "BatchNormBackward74"
    top: "BatchNormBackward74"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward75"
    type: "ReLU"
    bottom: "BatchNormBackward74"
    top: "BatchNormBackward74"
}
layer {
    name: "ConvNdBackward76"
    type: "Convolution"
    bottom: "BatchNormBackward74"
    top: "ConvNdBackward76"
    convolution_param {
        num_output: 256
        group: 256
        pad_h: 1
        pad_w: 1
        kernel_h: 3
        kernel_w: 3
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward77_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward76"
    top: "BatchNormBackward77"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward77_scale"
    type: "Scale"
    bottom: "BatchNormBackward77"
    top: "BatchNormBackward77"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward78"
    type: "ReLU"
    bottom: "BatchNormBackward77"
    top: "BatchNormBackward77"
}
layer {
    name: "ConvNdBackward79"
    type: "Convolution"
    bottom: "BatchNormBackward77"
    top: "ConvNdBackward79"
    convolution_param {
        num_output: 256
        group: 1
        pad_h: 0
        pad_w: 0
        kernel_h: 1
        kernel_w: 1
        stride: 1
        dilation: 1
        bias_term: false
    }
}
layer {
    name: "BatchNormBackward80_bn"
    type: "BatchNorm"
    bottom: "ConvNdBackward79"
    top: "BatchNormBackward80"
    batch_norm_param {
        use_global_stats: true
        eps: 1e-05
    }
}
layer {
    name: "BatchNormBackward80_scale"
    type: "Scale"
    bottom: "BatchNormBackward80"
    top: "BatchNormBackward80"
    scale_param {
        bias_term: true
    }
}
layer {
    name: "ThresholdBackward81"
    type: "ReLU"
    bottom: "BatchNormBackward80"
    top: "BatchNormBackward80"
}
layer {
    name: "AvgPool2dBackward82"
    type: "Pooling"
    bottom: "BatchNormBackward80"
    top: "AvgPool2dBackward82"
    pooling_param {
        pool: AVE
        kernel_size: 8
        stride: 8
        pad: 0
    }
}
layer {
    name: "AddmmBackward83"
    type: "InnerProduct"
    bottom: "AvgPool2dBackward82"
    top: "AddmmBackward83"
    inner_product_param {
        num_output: 62
    }
}