train_val.prototxt

name: "InceptionV3"
layer {
  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TRAIN
  }
  transform_param {
    mirror: true
    crop_size: 299
    mean_value: 104
    mean_value: 117
    mean_value: 123
  }
  data_param {
    source: "/mnt/disk/ILSVRC2012/300px_ilsvrc12_train_lmdb"
    batch_size: 22
    backend: LMDB
  }
}
layer {
  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TEST
  }
  transform_param {
    mirror: false
    crop_size: 299
    mean_value: 104
    mean_value: 117
    mean_value: 123
  }
  data_param {
    source: "/mnt/disk/ILSVRC2012/300px_ilsvrc12_val_lmdb"
    batch_size: 5
    backend: LMDB
  }
}
layer {
  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TRAIN
  }
  transform_param {
    mirror: true
    crop_size: 299
    mean_file: "/home/smichalowski/DIGITS/digits/jobs/20160627-223013-e18a/mean.binaryproto"
  }
  data_param {
    source: "/home/smichalowski/DIGITS/digits/jobs/20160627-223013-e18a/train_db"
    batch_size: 22
    backend: LMDB
  }
}
layer {
  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TEST
  }
  transform_param {
    mirror: false
    crop_size: 299
    mean_file: "/home/smichalowski/DIGITS/digits/jobs/20160627-223013-e18a/mean.binaryproto"
  }
  data_param {
    source: "/home/smichalowski/DIGITS/digits/jobs/20160627-223013-e18a/val_db"
    batch_size: 5
    backend: LMDB
  }
}
layer {
  name: "conv_conv2d"
  type: "Convolution"
  bottom: "data"
  top: "conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "conv_batchnorm"
  type: "BatchNorm"
  bottom: "conv_conv2d"
  top: "conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "conv_relu"
  type: "ReLU"
  bottom: "conv_conv2d_bn"
  top: "conv_conv2d_relu"
}
layer {
  name: "conv_1_1_conv2d"
  type: "Convolution"
  bottom: "conv_conv2d_relu"
  top: "conv_1_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "conv_1_1_batchnorm"
  type: "BatchNorm"
  bottom: "conv_1_1_conv2d"
  top: "conv_1_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "conv_1_1_relu"
  type: "ReLU"
  bottom: "conv_1_1_conv2d_bn"
  top: "conv_1_1_conv2d_relu"
}
layer {
  name: "conv_2_2_conv2d"
  type: "Convolution"
  bottom: "conv_1_1_conv2d_relu"
  top: "conv_2_2_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "conv_2_2_batchnorm"
  type: "BatchNorm"
  bottom: "conv_2_2_conv2d"
  top: "conv_2_2_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "conv_2_2_relu"
  type: "ReLU"
  bottom: "conv_2_2_conv2d_bn"
  top: "conv_2_2_conv2d_relu"
}
layer {
  name: "pool"
  type: "Pooling"
  bottom: "conv_2_2_conv2d_relu"
  top: "pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
    pad: 0
  }
}
layer {
  name: "conv_3_3_conv2d"
  type: "Convolution"
  bottom: "pool"
  top: "conv_3_3_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 80
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "conv_3_3_batchnorm"
  type: "BatchNorm"
  bottom: "conv_3_3_conv2d"
  top: "conv_3_3_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "conv_3_3_relu"
  type: "ReLU"
  bottom: "conv_3_3_conv2d_bn"
  top: "conv_3_3_conv2d_relu"
}
layer {
  name: "conv_4_4_conv2d"
  type: "Convolution"
  bottom: "conv_3_3_conv2d_relu"
  top: "conv_4_4_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 0
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "conv_4_4_batchnorm"
  type: "BatchNorm"
  bottom: "conv_4_4_conv2d"
  top: "conv_4_4_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "conv_4_4_relu"
  type: "ReLU"
  bottom: "conv_4_4_conv2d_bn"
  top: "conv_4_4_conv2d_relu"
}
layer {
  name: "pool1"
  type: "Pooling"
  bottom: "conv_4_4_conv2d_relu"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
    pad: 0
  }
}
layer {
  name: "mixed_conv_conv2d"
  type: "Convolution"
  bottom: "pool1"
  top: "mixed_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_conv_conv2d"
  top: "mixed_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_conv_relu"
  type: "ReLU"
  bottom: "mixed_conv_conv2d_bn"
  top: "mixed_conv_conv2d_relu"
}
layer {
  name: "mixed_tower_conv_conv2d"
  type: "Convolution"
  bottom: "pool1"
  top: "mixed_tower_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 48
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_tower_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_tower_conv_conv2d"
  top: "mixed_tower_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_tower_conv_relu"
  type: "ReLU"
  bottom: "mixed_tower_conv_conv2d_bn"
  top: "mixed_tower_conv_conv2d_relu"
}
layer {
  name: "mixed_tower_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_tower_conv_conv2d_relu"
  top: "mixed_tower_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 2
    kernel_size: 5
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_tower_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_tower_conv_1_conv2d"
  top: "mixed_tower_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_tower_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_tower_conv_1_conv2d_bn"
  top: "mixed_tower_conv_1_conv2d_relu"
}
layer {
  name: "mixed_tower_1_conv_conv2d"
  type: "Convolution"
  bottom: "pool1"
  top: "mixed_tower_1_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_tower_1_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_tower_1_conv_conv2d"
  top: "mixed_tower_1_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_tower_1_conv_relu"
  type: "ReLU"
  bottom: "mixed_tower_1_conv_conv2d_bn"
  top: "mixed_tower_1_conv_conv2d_relu"
}
layer {
  name: "mixed_tower_1_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_tower_1_conv_conv2d_relu"
  top: "mixed_tower_1_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 96
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_tower_1_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_tower_1_conv_1_conv2d"
  top: "mixed_tower_1_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_tower_1_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_tower_1_conv_1_conv2d_bn"
  top: "mixed_tower_1_conv_1_conv2d_relu"
}
layer {
  name: "mixed_tower_1_conv_2_conv2d"
  type: "Convolution"
  bottom: "mixed_tower_1_conv_1_conv2d_relu"
  top: "mixed_tower_1_conv_2_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 96
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_tower_1_conv_2_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_tower_1_conv_2_conv2d"
  top: "mixed_tower_1_conv_2_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_tower_1_conv_2_relu"
  type: "ReLU"
  bottom: "mixed_tower_1_conv_2_conv2d_bn"
  top: "mixed_tower_1_conv_2_conv2d_relu"
}
layer {
  name: "AVE_pool_mixed_pool"
  type: "Pooling"
  bottom: "pool1"
  top: "AVE_pool_mixed_pool"
  pooling_param {
    pool: AVE
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "mixed_tower_2_conv_conv2d"
  type: "Convolution"
  bottom: "AVE_pool_mixed_pool"
  top: "mixed_tower_2_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_tower_2_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_tower_2_conv_conv2d"
  top: "mixed_tower_2_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_tower_2_conv_relu"
  type: "ReLU"
  bottom: "mixed_tower_2_conv_conv2d_bn"
  top: "mixed_tower_2_conv_conv2d_relu"
}
layer {
  name: "ch_concat_mixed_chconcat"
  type: "Concat"
  bottom: "mixed_conv_conv2d_relu"
  bottom: "mixed_tower_conv_1_conv2d_relu"
  bottom: "mixed_tower_1_conv_2_conv2d_relu"
  bottom: "mixed_tower_2_conv_conv2d_relu"
  top: "ch_concat_mixed_chconcat"
  concat_param {
    axis: 1
  }
}
layer {
  name: "mixed_1_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_chconcat"
  top: "mixed_1_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_1_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_1_conv_conv2d"
  top: "mixed_1_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_1_conv_relu"
  type: "ReLU"
  bottom: "mixed_1_conv_conv2d_bn"
  top: "mixed_1_conv_conv2d_relu"
}
layer {
  name: "mixed_1_tower_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_chconcat"
  top: "mixed_1_tower_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 48
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_1_tower_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_1_tower_conv_conv2d"
  top: "mixed_1_tower_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_1_tower_conv_relu"
  type: "ReLU"
  bottom: "mixed_1_tower_conv_conv2d_bn"
  top: "mixed_1_tower_conv_conv2d_relu"
}
layer {
  name: "mixed_1_tower_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_1_tower_conv_conv2d_relu"
  top: "mixed_1_tower_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 2
    kernel_size: 5
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_1_tower_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_1_tower_conv_1_conv2d"
  top: "mixed_1_tower_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_1_tower_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_1_tower_conv_1_conv2d_bn"
  top: "mixed_1_tower_conv_1_conv2d_relu"
}
layer {
  name: "mixed_1_tower_1_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_chconcat"
  top: "mixed_1_tower_1_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_1_tower_1_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_1_tower_1_conv_conv2d"
  top: "mixed_1_tower_1_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_1_tower_1_conv_relu"
  type: "ReLU"
  bottom: "mixed_1_tower_1_conv_conv2d_bn"
  top: "mixed_1_tower_1_conv_conv2d_relu"
}
layer {
  name: "mixed_1_tower_1_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_1_tower_1_conv_conv2d_relu"
  top: "mixed_1_tower_1_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 96
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_1_tower_1_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_1_tower_1_conv_1_conv2d"
  top: "mixed_1_tower_1_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_1_tower_1_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_1_tower_1_conv_1_conv2d_bn"
  top: "mixed_1_tower_1_conv_1_conv2d_relu"
}
layer {
  name: "mixed_1_tower_1_conv_2_conv2d"
  type: "Convolution"
  bottom: "mixed_1_tower_1_conv_1_conv2d_relu"
  top: "mixed_1_tower_1_conv_2_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 96
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_1_tower_1_conv_2_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_1_tower_1_conv_2_conv2d"
  top: "mixed_1_tower_1_conv_2_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_1_tower_1_conv_2_relu"
  type: "ReLU"
  bottom: "mixed_1_tower_1_conv_2_conv2d_bn"
  top: "mixed_1_tower_1_conv_2_conv2d_relu"
}
layer {
  name: "AVE_pool_mixed_1_pool"
  type: "Pooling"
  bottom: "ch_concat_mixed_chconcat"
  top: "AVE_pool_mixed_1_pool"
  pooling_param {
    pool: AVE
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "mixed_1_tower_2_conv_conv2d"
  type: "Convolution"
  bottom: "AVE_pool_mixed_1_pool"
  top: "mixed_1_tower_2_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_1_tower_2_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_1_tower_2_conv_conv2d"
  top: "mixed_1_tower_2_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_1_tower_2_conv_relu"
  type: "ReLU"
  bottom: "mixed_1_tower_2_conv_conv2d_bn"
  top: "mixed_1_tower_2_conv_conv2d_relu"
}
layer {
  name: "ch_concat_mixed_1_chconcat"
  type: "Concat"
  bottom: "mixed_1_conv_conv2d_relu"
  bottom: "mixed_1_tower_conv_1_conv2d_relu"
  bottom: "mixed_1_tower_1_conv_2_conv2d_relu"
  bottom: "mixed_1_tower_2_conv_conv2d_relu"
  top: "ch_concat_mixed_1_chconcat"
  concat_param {
    axis: 1
  }
}
layer {
  name: "mixed_2_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_1_chconcat"
  top: "mixed_2_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_2_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_2_conv_conv2d"
  top: "mixed_2_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_2_conv_relu"
  type: "ReLU"
  bottom: "mixed_2_conv_conv2d_bn"
  top: "mixed_2_conv_conv2d_relu"
}
layer {
  name: "mixed_2_tower_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_1_chconcat"
  top: "mixed_2_tower_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 48
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_2_tower_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_2_tower_conv_conv2d"
  top: "mixed_2_tower_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_2_tower_conv_relu"
  type: "ReLU"
  bottom: "mixed_2_tower_conv_conv2d_bn"
  top: "mixed_2_tower_conv_conv2d_relu"
}
layer {
  name: "mixed_2_tower_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_2_tower_conv_conv2d_relu"
  top: "mixed_2_tower_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 2
    kernel_size: 5
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_2_tower_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_2_tower_conv_1_conv2d"
  top: "mixed_2_tower_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_2_tower_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_2_tower_conv_1_conv2d_bn"
  top: "mixed_2_tower_conv_1_conv2d_relu"
}
layer {
  name: "mixed_2_tower_1_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_1_chconcat"
  top: "mixed_2_tower_1_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_2_tower_1_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_2_tower_1_conv_conv2d"
  top: "mixed_2_tower_1_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_2_tower_1_conv_relu"
  type: "ReLU"
  bottom: "mixed_2_tower_1_conv_conv2d_bn"
  top: "mixed_2_tower_1_conv_conv2d_relu"
}
layer {
  name: "mixed_2_tower_1_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_2_tower_1_conv_conv2d_relu"
  top: "mixed_2_tower_1_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 96
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_2_tower_1_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_2_tower_1_conv_1_conv2d"
  top: "mixed_2_tower_1_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_2_tower_1_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_2_tower_1_conv_1_conv2d_bn"
  top: "mixed_2_tower_1_conv_1_conv2d_relu"
}
layer {
  name: "mixed_2_tower_1_conv_2_conv2d"
  type: "Convolution"
  bottom: "mixed_2_tower_1_conv_1_conv2d_relu"
  top: "mixed_2_tower_1_conv_2_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 96
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_2_tower_1_conv_2_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_2_tower_1_conv_2_conv2d"
  top: "mixed_2_tower_1_conv_2_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_2_tower_1_conv_2_relu"
  type: "ReLU"
  bottom: "mixed_2_tower_1_conv_2_conv2d_bn"
  top: "mixed_2_tower_1_conv_2_conv2d_relu"
}
layer {
  name: "AVE_pool_mixed_2_pool"
  type: "Pooling"
  bottom: "ch_concat_mixed_1_chconcat"
  top: "AVE_pool_mixed_2_pool"
  pooling_param {
    pool: AVE
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "mixed_2_tower_2_conv_conv2d"
  type: "Convolution"
  bottom: "AVE_pool_mixed_2_pool"
  top: "mixed_2_tower_2_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_2_tower_2_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_2_tower_2_conv_conv2d"
  top: "mixed_2_tower_2_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_2_tower_2_conv_relu"
  type: "ReLU"
  bottom: "mixed_2_tower_2_conv_conv2d_bn"
  top: "mixed_2_tower_2_conv_conv2d_relu"
}
layer {
  name: "ch_concat_mixed_2_chconcat"
  type: "Concat"
  bottom: "mixed_2_conv_conv2d_relu"
  bottom: "mixed_2_tower_conv_1_conv2d_relu"
  bottom: "mixed_2_tower_1_conv_2_conv2d_relu"
  bottom: "mixed_2_tower_2_conv_conv2d_relu"
  top: "ch_concat_mixed_2_chconcat"
  concat_param {
    axis: 1
  }
}
layer {
  name: "mixed_3_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_2_chconcat"
  top: "mixed_3_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    pad: 0
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_3_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_3_conv_conv2d"
  top: "mixed_3_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_3_conv_relu"
  type: "ReLU"
  bottom: "mixed_3_conv_conv2d_bn"
  top: "mixed_3_conv_conv2d_relu"
}
layer {
  name: "mixed_3_tower_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_2_chconcat"
  top: "mixed_3_tower_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_3_tower_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_3_tower_conv_conv2d"
  top: "mixed_3_tower_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_3_tower_conv_relu"
  type: "ReLU"
  bottom: "mixed_3_tower_conv_conv2d_bn"
  top: "mixed_3_tower_conv_conv2d_relu"
}
layer {
  name: "mixed_3_tower_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_3_tower_conv_conv2d_relu"
  top: "mixed_3_tower_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 96
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_3_tower_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_3_tower_conv_1_conv2d"
  top: "mixed_3_tower_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_3_tower_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_3_tower_conv_1_conv2d_bn"
  top: "mixed_3_tower_conv_1_conv2d_relu"
}
layer {
  name: "mixed_3_tower_conv_2_conv2d"
  type: "Convolution"
  bottom: "mixed_3_tower_conv_1_conv2d_relu"
  top: "mixed_3_tower_conv_2_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 96
    bias_term: false
    pad: 0
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_3_tower_conv_2_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_3_tower_conv_2_conv2d"
  top: "mixed_3_tower_conv_2_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_3_tower_conv_2_relu"
  type: "ReLU"
  bottom: "mixed_3_tower_conv_2_conv2d_bn"
  top: "mixed_3_tower_conv_2_conv2d_relu"
}
layer {
  name: "max_pool_mixed_3_pool"
  type: "Pooling"
  bottom: "ch_concat_mixed_2_chconcat"
  top: "max_pool_mixed_3_pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
    pad: 0
  }
}
layer {
  name: "ch_concat_mixed_3_chconcat"
  type: "Concat"
  bottom: "max_pool_mixed_3_pool"
  bottom: "mixed_3_conv_conv2d_relu"
  bottom: "mixed_3_tower_conv_2_conv2d_relu"
  top: "ch_concat_mixed_3_chconcat"
  concat_param {
    axis: 1
  }
}
layer {
  name: "mixed_4_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_3_chconcat"
  top: "mixed_4_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_4_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_4_conv_conv2d"
  top: "mixed_4_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_4_conv_relu"
  type: "ReLU"
  bottom: "mixed_4_conv_conv2d_bn"
  top: "mixed_4_conv_conv2d_relu"
}
layer {
  name: "mixed_4_tower_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_3_chconcat"
  top: "mixed_4_tower_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_4_tower_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_4_tower_conv_conv2d"
  top: "mixed_4_tower_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_4_tower_conv_relu"
  type: "ReLU"
  bottom: "mixed_4_tower_conv_conv2d_bn"
  top: "mixed_4_tower_conv_conv2d_relu"
}
layer {
  name: "mixed_4_tower_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_4_tower_conv_conv2d_relu"
  top: "mixed_4_tower_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 0
    pad_w: 3
    kernel_h: 1
    kernel_w: 7
  }
}
layer {
  name: "mixed_4_tower_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_4_tower_conv_1_conv2d"
  top: "mixed_4_tower_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_4_tower_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_4_tower_conv_1_conv2d_bn"
  top: "mixed_4_tower_conv_1_conv2d_relu"
}
layer {
  name: "mixed_4_tower_conv_2_conv2d"
  type: "Convolution"
  bottom: "mixed_4_tower_conv_1_conv2d_relu"
  top: "mixed_4_tower_conv_2_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 3
    pad_w: 0
    kernel_h: 7
    kernel_w: 1
  }
}
layer {
  name: "mixed_4_tower_conv_2_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_4_tower_conv_2_conv2d"
  top: "mixed_4_tower_conv_2_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_4_tower_conv_2_relu"
  type: "ReLU"
  bottom: "mixed_4_tower_conv_2_conv2d_bn"
  top: "mixed_4_tower_conv_2_conv2d_relu"
}
layer {
  name: "mixed_4_tower_1_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_3_chconcat"
  top: "mixed_4_tower_1_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_4_tower_1_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_4_tower_1_conv_conv2d"
  top: "mixed_4_tower_1_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_4_tower_1_conv_relu"
  type: "ReLU"
  bottom: "mixed_4_tower_1_conv_conv2d_bn"
  top: "mixed_4_tower_1_conv_conv2d_relu"
}
layer {
  name: "mixed_4_tower_1_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_4_tower_1_conv_conv2d_relu"
  top: "mixed_4_tower_1_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 3
    pad_w: 0
    kernel_h: 7
    kernel_w: 1
  }
}
layer {
  name: "mixed_4_tower_1_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_4_tower_1_conv_1_conv2d"
  top: "mixed_4_tower_1_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_4_tower_1_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_4_tower_1_conv_1_conv2d_bn"
  top: "mixed_4_tower_1_conv_1_conv2d_relu"
}
layer {
  name: "mixed_4_tower_1_conv_2_conv2d"
  type: "Convolution"
  bottom: "mixed_4_tower_1_conv_1_conv2d_relu"
  top: "mixed_4_tower_1_conv_2_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 0
    pad_w: 3
    kernel_h: 1
    kernel_w: 7
  }
}
layer {
  name: "mixed_4_tower_1_conv_2_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_4_tower_1_conv_2_conv2d"
  top: "mixed_4_tower_1_conv_2_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_4_tower_1_conv_2_relu"
  type: "ReLU"
  bottom: "mixed_4_tower_1_conv_2_conv2d_bn"
  top: "mixed_4_tower_1_conv_2_conv2d_relu"
}
layer {
  name: "mixed_4_tower_1_conv_3_conv2d"
  type: "Convolution"
  bottom: "mixed_4_tower_1_conv_2_conv2d_relu"
  top: "mixed_4_tower_1_conv_3_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 3
    pad_w: 0
    kernel_h: 7
    kernel_w: 1
  }
}
layer {
  name: "mixed_4_tower_1_conv_3_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_4_tower_1_conv_3_conv2d"
  top: "mixed_4_tower_1_conv_3_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_4_tower_1_conv_3_relu"
  type: "ReLU"
  bottom: "mixed_4_tower_1_conv_3_conv2d_bn"
  top: "mixed_4_tower_1_conv_3_conv2d_relu"
}
layer {
  name: "mixed_4_tower_1_conv_4_conv2d"
  type: "Convolution"
  bottom: "mixed_4_tower_1_conv_3_conv2d_relu"
  top: "mixed_4_tower_1_conv_4_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 0
    pad_w: 3
    kernel_h: 1
    kernel_w: 7
  }
}
layer {
  name: "mixed_4_tower_1_conv_4_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_4_tower_1_conv_4_conv2d"
  top: "mixed_4_tower_1_conv_4_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_4_tower_1_conv_4_relu"
  type: "ReLU"
  bottom: "mixed_4_tower_1_conv_4_conv2d_bn"
  top: "mixed_4_tower_1_conv_4_conv2d_relu"
}
layer {
  name: "AVE_pool_mixed_4_pool"
  type: "Pooling"
  bottom: "ch_concat_mixed_3_chconcat"
  top: "AVE_pool_mixed_4_pool"
  pooling_param {
    pool: AVE
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "mixed_4_tower_2_conv_conv2d"
  type: "Convolution"
  bottom: "AVE_pool_mixed_4_pool"
  top: "mixed_4_tower_2_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_4_tower_2_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_4_tower_2_conv_conv2d"
  top: "mixed_4_tower_2_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_4_tower_2_conv_relu"
  type: "ReLU"
  bottom: "mixed_4_tower_2_conv_conv2d_bn"
  top: "mixed_4_tower_2_conv_conv2d_relu"
}
layer {
  name: "ch_concat_mixed_4_chconcat"
  type: "Concat"
  bottom: "mixed_4_conv_conv2d_relu"
  bottom: "mixed_4_tower_conv_2_conv2d_relu"
  bottom: "mixed_4_tower_1_conv_4_conv2d_relu"
  bottom: "mixed_4_tower_2_conv_conv2d_relu"
  top: "ch_concat_mixed_4_chconcat"
  concat_param {
    axis: 1
  }
}
layer {
  name: "mixed_5_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_4_chconcat"
  top: "mixed_5_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_5_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_5_conv_conv2d"
  top: "mixed_5_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_5_conv_relu"
  type: "ReLU"
  bottom: "mixed_5_conv_conv2d_bn"
  top: "mixed_5_conv_conv2d_relu"
}
layer {
  name: "mixed_5_tower_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_4_chconcat"
  top: "mixed_5_tower_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 160
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_5_tower_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_5_tower_conv_conv2d"
  top: "mixed_5_tower_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_5_tower_conv_relu"
  type: "ReLU"
  bottom: "mixed_5_tower_conv_conv2d_bn"
  top: "mixed_5_tower_conv_conv2d_relu"
}
layer {
  name: "mixed_5_tower_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_5_tower_conv_conv2d_relu"
  top: "mixed_5_tower_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 160
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 0
    pad_w: 3
    kernel_h: 1
    kernel_w: 7
  }
}
layer {
  name: "mixed_5_tower_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_5_tower_conv_1_conv2d"
  top: "mixed_5_tower_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_5_tower_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_5_tower_conv_1_conv2d_bn"
  top: "mixed_5_tower_conv_1_conv2d_relu"
}
layer {
  name: "mixed_5_tower_conv_2_conv2d"
  type: "Convolution"
  bottom: "mixed_5_tower_conv_1_conv2d_relu"
  top: "mixed_5_tower_conv_2_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 3
    pad_w: 0
    kernel_h: 7
    kernel_w: 1
  }
}
layer {
  name: "mixed_5_tower_conv_2_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_5_tower_conv_2_conv2d"
  top: "mixed_5_tower_conv_2_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_5_tower_conv_2_relu"
  type: "ReLU"
  bottom: "mixed_5_tower_conv_2_conv2d_bn"
  top: "mixed_5_tower_conv_2_conv2d_relu"
}
layer {
  name: "mixed_5_tower_1_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_4_chconcat"
  top: "mixed_5_tower_1_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 160
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_5_tower_1_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_5_tower_1_conv_conv2d"
  top: "mixed_5_tower_1_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_5_tower_1_conv_relu"
  type: "ReLU"
  bottom: "mixed_5_tower_1_conv_conv2d_bn"
  top: "mixed_5_tower_1_conv_conv2d_relu"
}
layer {
  name: "mixed_5_tower_1_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_5_tower_1_conv_conv2d_relu"
  top: "mixed_5_tower_1_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 160
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 3
    pad_w: 0
    kernel_h: 7
    kernel_w: 1
  }
}
layer {
  name: "mixed_5_tower_1_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_5_tower_1_conv_1_conv2d"
  top: "mixed_5_tower_1_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_5_tower_1_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_5_tower_1_conv_1_conv2d_bn"
  top: "mixed_5_tower_1_conv_1_conv2d_relu"
}
layer {
  name: "mixed_5_tower_1_conv_2_conv2d"
  type: "Convolution"
  bottom: "mixed_5_tower_1_conv_1_conv2d_relu"
  top: "mixed_5_tower_1_conv_2_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 160
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 0
    pad_w: 3
    kernel_h: 1
    kernel_w: 7
  }
}
layer {
  name: "mixed_5_tower_1_conv_2_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_5_tower_1_conv_2_conv2d"
  top: "mixed_5_tower_1_conv_2_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_5_tower_1_conv_2_relu"
  type: "ReLU"
  bottom: "mixed_5_tower_1_conv_2_conv2d_bn"
  top: "mixed_5_tower_1_conv_2_conv2d_relu"
}
layer {
  name: "mixed_5_tower_1_conv_3_conv2d"
  type: "Convolution"
  bottom: "mixed_5_tower_1_conv_2_conv2d_relu"
  top: "mixed_5_tower_1_conv_3_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 160
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 3
    pad_w: 0
    kernel_h: 7
    kernel_w: 1
  }
}
layer {
  name: "mixed_5_tower_1_conv_3_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_5_tower_1_conv_3_conv2d"
  top: "mixed_5_tower_1_conv_3_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_5_tower_1_conv_3_relu"
  type: "ReLU"
  bottom: "mixed_5_tower_1_conv_3_conv2d_bn"
  top: "mixed_5_tower_1_conv_3_conv2d_relu"
}
layer {
  name: "mixed_5_tower_1_conv_4_conv2d"
  type: "Convolution"
  bottom: "mixed_5_tower_1_conv_3_conv2d_relu"
  top: "mixed_5_tower_1_conv_4_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 0
    pad_w: 3
    kernel_h: 1
    kernel_w: 7
  }
}
layer {
  name: "mixed_5_tower_1_conv_4_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_5_tower_1_conv_4_conv2d"
  top: "mixed_5_tower_1_conv_4_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_5_tower_1_conv_4_relu"
  type: "ReLU"
  bottom: "mixed_5_tower_1_conv_4_conv2d_bn"
  top: "mixed_5_tower_1_conv_4_conv2d_relu"
}
layer {
  name: "AVE_pool_mixed_5_pool"
  type: "Pooling"
  bottom: "ch_concat_mixed_4_chconcat"
  top: "AVE_pool_mixed_5_pool"
  pooling_param {
    pool: AVE
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "mixed_5_tower_2_conv_conv2d"
  type: "Convolution"
  bottom: "AVE_pool_mixed_5_pool"
  top: "mixed_5_tower_2_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_5_tower_2_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_5_tower_2_conv_conv2d"
  top: "mixed_5_tower_2_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_5_tower_2_conv_relu"
  type: "ReLU"
  bottom: "mixed_5_tower_2_conv_conv2d_bn"
  top: "mixed_5_tower_2_conv_conv2d_relu"
}
layer {
  name: "ch_concat_mixed_5_chconcat"
  type: "Concat"
  bottom: "mixed_5_conv_conv2d_relu"
  bottom: "mixed_5_tower_conv_2_conv2d_relu"
  bottom: "mixed_5_tower_1_conv_4_conv2d_relu"
  bottom: "mixed_5_tower_2_conv_conv2d_relu"
  top: "ch_concat_mixed_5_chconcat"
  concat_param {
    axis: 1
  }
}
layer {
  name: "mixed_6_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_5_chconcat"
  top: "mixed_6_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_6_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_6_conv_conv2d"
  top: "mixed_6_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_6_conv_relu"
  type: "ReLU"
  bottom: "mixed_6_conv_conv2d_bn"
  top: "mixed_6_conv_conv2d_relu"
}
layer {
  name: "mixed_6_tower_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_5_chconcat"
  top: "mixed_6_tower_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 160
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_6_tower_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_6_tower_conv_conv2d"
  top: "mixed_6_tower_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_6_tower_conv_relu"
  type: "ReLU"
  bottom: "mixed_6_tower_conv_conv2d_bn"
  top: "mixed_6_tower_conv_conv2d_relu"
}
layer {
  name: "mixed_6_tower_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_6_tower_conv_conv2d_relu"
  top: "mixed_6_tower_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 160
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 0
    pad_w: 3
    kernel_h: 1
    kernel_w: 7
  }
}
layer {
  name: "mixed_6_tower_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_6_tower_conv_1_conv2d"
  top: "mixed_6_tower_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_6_tower_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_6_tower_conv_1_conv2d_bn"
  top: "mixed_6_tower_conv_1_conv2d_relu"
}
layer {
  name: "mixed_6_tower_conv_2_conv2d"
  type: "Convolution"
  bottom: "mixed_6_tower_conv_1_conv2d_relu"
  top: "mixed_6_tower_conv_2_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 3
    pad_w: 0
    kernel_h: 7
    kernel_w: 1
  }
}
layer {
  name: "mixed_6_tower_conv_2_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_6_tower_conv_2_conv2d"
  top: "mixed_6_tower_conv_2_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_6_tower_conv_2_relu"
  type: "ReLU"
  bottom: "mixed_6_tower_conv_2_conv2d_bn"
  top: "mixed_6_tower_conv_2_conv2d_relu"
}
layer {
  name: "mixed_6_tower_1_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_5_chconcat"
  top: "mixed_6_tower_1_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 160
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_6_tower_1_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_6_tower_1_conv_conv2d"
  top: "mixed_6_tower_1_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_6_tower_1_conv_relu"
  type: "ReLU"
  bottom: "mixed_6_tower_1_conv_conv2d_bn"
  top: "mixed_6_tower_1_conv_conv2d_relu"
}
layer {
  name: "mixed_6_tower_1_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_6_tower_1_conv_conv2d_relu"
  top: "mixed_6_tower_1_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 160
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 3
    pad_w: 0
    kernel_h: 7
    kernel_w: 1
  }
}
layer {
  name: "mixed_6_tower_1_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_6_tower_1_conv_1_conv2d"
  top: "mixed_6_tower_1_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_6_tower_1_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_6_tower_1_conv_1_conv2d_bn"
  top: "mixed_6_tower_1_conv_1_conv2d_relu"
}
layer {
  name: "mixed_6_tower_1_conv_2_conv2d"
  type: "Convolution"
  bottom: "mixed_6_tower_1_conv_1_conv2d_relu"
  top: "mixed_6_tower_1_conv_2_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 160
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 0
    pad_w: 3
    kernel_h: 1
    kernel_w: 7
  }
}
layer {
  name: "mixed_6_tower_1_conv_2_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_6_tower_1_conv_2_conv2d"
  top: "mixed_6_tower_1_conv_2_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_6_tower_1_conv_2_relu"
  type: "ReLU"
  bottom: "mixed_6_tower_1_conv_2_conv2d_bn"
  top: "mixed_6_tower_1_conv_2_conv2d_relu"
}
layer {
  name: "mixed_6_tower_1_conv_3_conv2d"
  type: "Convolution"
  bottom: "mixed_6_tower_1_conv_2_conv2d_relu"
  top: "mixed_6_tower_1_conv_3_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 160
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 3
    pad_w: 0
    kernel_h: 7
    kernel_w: 1
  }
}
layer {
  name: "mixed_6_tower_1_conv_3_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_6_tower_1_conv_3_conv2d"
  top: "mixed_6_tower_1_conv_3_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_6_tower_1_conv_3_relu"
  type: "ReLU"
  bottom: "mixed_6_tower_1_conv_3_conv2d_bn"
  top: "mixed_6_tower_1_conv_3_conv2d_relu"
}
layer {
  name: "mixed_6_tower_1_conv_4_conv2d"
  type: "Convolution"
  bottom: "mixed_6_tower_1_conv_3_conv2d_relu"
  top: "mixed_6_tower_1_conv_4_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 0
    pad_w: 3
    kernel_h: 1
    kernel_w: 7
  }
}
layer {
  name: "mixed_6_tower_1_conv_4_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_6_tower_1_conv_4_conv2d"
  top: "mixed_6_tower_1_conv_4_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_6_tower_1_conv_4_relu"
  type: "ReLU"
  bottom: "mixed_6_tower_1_conv_4_conv2d_bn"
  top: "mixed_6_tower_1_conv_4_conv2d_relu"
}
layer {
  name: "AVE_pool_mixed_6_pool"
  type: "Pooling"
  bottom: "ch_concat_mixed_5_chconcat"
  top: "AVE_pool_mixed_6_pool"
  pooling_param {
    pool: AVE
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "mixed_6_tower_2_conv_conv2d"
  type: "Convolution"
  bottom: "AVE_pool_mixed_6_pool"
  top: "mixed_6_tower_2_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_6_tower_2_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_6_tower_2_conv_conv2d"
  top: "mixed_6_tower_2_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_6_tower_2_conv_relu"
  type: "ReLU"
  bottom: "mixed_6_tower_2_conv_conv2d_bn"
  top: "mixed_6_tower_2_conv_conv2d_relu"
}
layer {
  name: "ch_concat_mixed_6_chconcat"
  type: "Concat"
  bottom: "mixed_6_conv_conv2d_relu"
  bottom: "mixed_6_tower_conv_2_conv2d_relu"
  bottom: "mixed_6_tower_1_conv_4_conv2d_relu"
  bottom: "mixed_6_tower_2_conv_conv2d_relu"
  top: "ch_concat_mixed_6_chconcat"
  concat_param {
    axis: 1
  }
}
layer {
  name: "mixed_7_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_6_chconcat"
  top: "mixed_7_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_7_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_7_conv_conv2d"
  top: "mixed_7_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_7_conv_relu"
  type: "ReLU"
  bottom: "mixed_7_conv_conv2d_bn"
  top: "mixed_7_conv_conv2d_relu"
}
layer {
  name: "mixed_7_tower_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_6_chconcat"
  top: "mixed_7_tower_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_7_tower_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_7_tower_conv_conv2d"
  top: "mixed_7_tower_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_7_tower_conv_relu"
  type: "ReLU"
  bottom: "mixed_7_tower_conv_conv2d_bn"
  top: "mixed_7_tower_conv_conv2d_relu"
}
layer {
  name: "mixed_7_tower_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_7_tower_conv_conv2d_relu"
  top: "mixed_7_tower_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 0
    pad_w: 3
    kernel_h: 1
    kernel_w: 7
  }
}
layer {
  name: "mixed_7_tower_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_7_tower_conv_1_conv2d"
  top: "mixed_7_tower_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_7_tower_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_7_tower_conv_1_conv2d_bn"
  top: "mixed_7_tower_conv_1_conv2d_relu"
}
layer {
  name: "mixed_7_tower_conv_2_conv2d"
  type: "Convolution"
  bottom: "mixed_7_tower_conv_1_conv2d_relu"
  top: "mixed_7_tower_conv_2_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 3
    pad_w: 0
    kernel_h: 7
    kernel_w: 1
  }
}
layer {
  name: "mixed_7_tower_conv_2_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_7_tower_conv_2_conv2d"
  top: "mixed_7_tower_conv_2_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_7_tower_conv_2_relu"
  type: "ReLU"
  bottom: "mixed_7_tower_conv_2_conv2d_bn"
  top: "mixed_7_tower_conv_2_conv2d_relu"
}
layer {
  name: "mixed_7_tower_1_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_6_chconcat"
  top: "mixed_7_tower_1_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_7_tower_1_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_7_tower_1_conv_conv2d"
  top: "mixed_7_tower_1_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_7_tower_1_conv_relu"
  type: "ReLU"
  bottom: "mixed_7_tower_1_conv_conv2d_bn"
  top: "mixed_7_tower_1_conv_conv2d_relu"
}
layer {
  name: "mixed_7_tower_1_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_7_tower_1_conv_conv2d_relu"
  top: "mixed_7_tower_1_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 3
    pad_w: 0
    kernel_h: 7
    kernel_w: 1
  }
}
layer {
  name: "mixed_7_tower_1_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_7_tower_1_conv_1_conv2d"
  top: "mixed_7_tower_1_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_7_tower_1_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_7_tower_1_conv_1_conv2d_bn"
  top: "mixed_7_tower_1_conv_1_conv2d_relu"
}
layer {
  name: "mixed_7_tower_1_conv_2_conv2d"
  type: "Convolution"
  bottom: "mixed_7_tower_1_conv_1_conv2d_relu"
  top: "mixed_7_tower_1_conv_2_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 0
    pad_w: 3
    kernel_h: 1
    kernel_w: 7
  }
}
layer {
  name: "mixed_7_tower_1_conv_2_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_7_tower_1_conv_2_conv2d"
  top: "mixed_7_tower_1_conv_2_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_7_tower_1_conv_2_relu"
  type: "ReLU"
  bottom: "mixed_7_tower_1_conv_2_conv2d_bn"
  top: "mixed_7_tower_1_conv_2_conv2d_relu"
}
layer {
  name: "mixed_7_tower_1_conv_3_conv2d"
  type: "Convolution"
  bottom: "mixed_7_tower_1_conv_2_conv2d_relu"
  top: "mixed_7_tower_1_conv_3_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 3
    pad_w: 0
    kernel_h: 7
    kernel_w: 1
  }
}
layer {
  name: "mixed_7_tower_1_conv_3_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_7_tower_1_conv_3_conv2d"
  top: "mixed_7_tower_1_conv_3_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_7_tower_1_conv_3_relu"
  type: "ReLU"
  bottom: "mixed_7_tower_1_conv_3_conv2d_bn"
  top: "mixed_7_tower_1_conv_3_conv2d_relu"
}
layer {
  name: "mixed_7_tower_1_conv_4_conv2d"
  type: "Convolution"
  bottom: "mixed_7_tower_1_conv_3_conv2d_relu"
  top: "mixed_7_tower_1_conv_4_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 0
    pad_w: 3
    kernel_h: 1
    kernel_w: 7
  }
}
layer {
  name: "mixed_7_tower_1_conv_4_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_7_tower_1_conv_4_conv2d"
  top: "mixed_7_tower_1_conv_4_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_7_tower_1_conv_4_relu"
  type: "ReLU"
  bottom: "mixed_7_tower_1_conv_4_conv2d_bn"
  top: "mixed_7_tower_1_conv_4_conv2d_relu"
}
layer {
  name: "AVE_pool_mixed_7_pool"
  type: "Pooling"
  bottom: "ch_concat_mixed_6_chconcat"
  top: "AVE_pool_mixed_7_pool"
  pooling_param {
    pool: AVE
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "mixed_7_tower_2_conv_conv2d"
  type: "Convolution"
  bottom: "AVE_pool_mixed_7_pool"
  top: "mixed_7_tower_2_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_7_tower_2_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_7_tower_2_conv_conv2d"
  top: "mixed_7_tower_2_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_7_tower_2_conv_relu"
  type: "ReLU"
  bottom: "mixed_7_tower_2_conv_conv2d_bn"
  top: "mixed_7_tower_2_conv_conv2d_relu"
}
layer {
  name: "ch_concat_mixed_7_chconcat"
  type: "Concat"
  bottom: "mixed_7_conv_conv2d_relu"
  bottom: "mixed_7_tower_conv_2_conv2d_relu"
  bottom: "mixed_7_tower_1_conv_4_conv2d_relu"
  bottom: "mixed_7_tower_2_conv_conv2d_relu"
  top: "ch_concat_mixed_7_chconcat"
  concat_param {
    axis: 1
  }
}
layer {
  name: "mixed_8_tower_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_7_chconcat"
  top: "mixed_8_tower_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_8_tower_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_8_tower_conv_conv2d"
  top: "mixed_8_tower_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_8_tower_conv_relu"
  type: "ReLU"
  bottom: "mixed_8_tower_conv_conv2d_bn"
  top: "mixed_8_tower_conv_conv2d_relu"
}
layer {
  name: "mixed_8_tower_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_8_tower_conv_conv2d_relu"
  top: "mixed_8_tower_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 320
    bias_term: false
    pad: 0
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_8_tower_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_8_tower_conv_1_conv2d"
  top: "mixed_8_tower_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_8_tower_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_8_tower_conv_1_conv2d_bn"
  top: "mixed_8_tower_conv_1_conv2d_relu"
}
layer {
  name: "mixed_8_tower_1_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_7_chconcat"
  top: "mixed_8_tower_1_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_8_tower_1_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_8_tower_1_conv_conv2d"
  top: "mixed_8_tower_1_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_8_tower_1_conv_relu"
  type: "ReLU"
  bottom: "mixed_8_tower_1_conv_conv2d_bn"
  top: "mixed_8_tower_1_conv_conv2d_relu"
}
layer {
  name: "mixed_8_tower_1_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_8_tower_1_conv_conv2d_relu"
  top: "mixed_8_tower_1_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 0
    pad_w: 3
    kernel_h: 1
    kernel_w: 7
  }
}
layer {
  name: "mixed_8_tower_1_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_8_tower_1_conv_1_conv2d"
  top: "mixed_8_tower_1_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_8_tower_1_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_8_tower_1_conv_1_conv2d_bn"
  top: "mixed_8_tower_1_conv_1_conv2d_relu"
}
layer {
  name: "mixed_8_tower_1_conv_2_conv2d"
  type: "Convolution"
  bottom: "mixed_8_tower_1_conv_1_conv2d_relu"
  top: "mixed_8_tower_1_conv_2_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 3
    pad_w: 0
    kernel_h: 7
    kernel_w: 1
  }
}
layer {
  name: "mixed_8_tower_1_conv_2_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_8_tower_1_conv_2_conv2d"
  top: "mixed_8_tower_1_conv_2_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_8_tower_1_conv_2_relu"
  type: "ReLU"
  bottom: "mixed_8_tower_1_conv_2_conv2d_bn"
  top: "mixed_8_tower_1_conv_2_conv2d_relu"
}
layer {
  name: "mixed_8_tower_1_conv_3_conv2d"
  type: "Convolution"
  bottom: "mixed_8_tower_1_conv_2_conv2d_relu"
  top: "mixed_8_tower_1_conv_3_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 0
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_8_tower_1_conv_3_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_8_tower_1_conv_3_conv2d"
  top: "mixed_8_tower_1_conv_3_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_8_tower_1_conv_3_relu"
  type: "ReLU"
  bottom: "mixed_8_tower_1_conv_3_conv2d_bn"
  top: "mixed_8_tower_1_conv_3_conv2d_relu"
}
layer {
  name: "MAX_pool_mixed_8_pool"
  type: "Pooling"
  bottom: "ch_concat_mixed_7_chconcat"
  top: "MAX_pool_mixed_8_pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
    pad: 0
  }
}
layer {
  name: "ch_concat_mixed_8_chconcat"
  type: "Concat"
  bottom: "mixed_8_tower_conv_1_conv2d_relu"
  bottom: "mixed_8_tower_1_conv_3_conv2d_relu"
  bottom: "MAX_pool_mixed_8_pool"
  top: "ch_concat_mixed_8_chconcat"
  concat_param {
    axis: 1
  }
}
layer {
  name: "mixed_9_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_8_chconcat"
  top: "mixed_9_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 320
    bias_term: false
    pad: 0
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    kernel_h: 1
    kernel_w: 1
  }
}
layer {
  name: "mixed_9_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_9_conv_conv2d"
  top: "mixed_9_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_9_conv_relu"
  type: "ReLU"
  bottom: "mixed_9_conv_conv2d_bn"
  top: "mixed_9_conv_conv2d_relu"
}
layer {
  name: "mixed_9_tower_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_8_chconcat"
  top: "mixed_9_tower_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_9_tower_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_9_tower_conv_conv2d"
  top: "mixed_9_tower_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_9_tower_conv_relu"
  type: "ReLU"
  bottom: "mixed_9_tower_conv_conv2d_bn"
  top: "mixed_9_tower_conv_conv2d_relu"
}
layer {
  name: "mixed_9_tower_mixed_conv_conv2d"
  type: "Convolution"
  bottom: "mixed_9_tower_conv_conv2d_relu"
  top: "mixed_9_tower_mixed_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 0
    pad_w: 1
    kernel_h: 1
    kernel_w: 3
  }
}
layer {
  name: "mixed_9_tower_mixed_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_9_tower_mixed_conv_conv2d"
  top: "mixed_9_tower_mixed_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_9_tower_mixed_conv_relu"
  type: "ReLU"
  bottom: "mixed_9_tower_mixed_conv_conv2d_bn"
  top: "mixed_9_tower_mixed_conv_conv2d_relu"
}
layer {
  name: "mixed_9_tower_mixed_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_9_tower_conv_conv2d_relu"
  top: "mixed_9_tower_mixed_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 1
    pad_w: 0
    kernel_h: 3
    kernel_w: 1
  }
}
layer {
  name: "mixed_9_tower_mixed_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_9_tower_mixed_conv_1_conv2d"
  top: "mixed_9_tower_mixed_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_9_tower_mixed_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_9_tower_mixed_conv_1_conv2d_bn"
  top: "mixed_9_tower_mixed_conv_1_conv2d_relu"
}
layer {
  name: "mixed_9_tower_1_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_8_chconcat"
  top: "mixed_9_tower_1_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 448
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_9_tower_1_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_9_tower_1_conv_conv2d"
  top: "mixed_9_tower_1_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_9_tower_1_conv_relu"
  type: "ReLU"
  bottom: "mixed_9_tower_1_conv_conv2d_bn"
  top: "mixed_9_tower_1_conv_conv2d_relu"
}
layer {
  name: "mixed_9_tower_1_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_9_tower_1_conv_conv2d_relu"
  top: "mixed_9_tower_1_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_9_tower_1_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_9_tower_1_conv_1_conv2d"
  top: "mixed_9_tower_1_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_9_tower_1_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_9_tower_1_conv_1_conv2d_bn"
  top: "mixed_9_tower_1_conv_1_conv2d_relu"
}
layer {
  name: "mixed_9_tower_1_mixed_conv_conv2d"
  type: "Convolution"
  bottom: "mixed_9_tower_1_conv_1_conv2d_relu"
  top: "mixed_9_tower_1_mixed_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 0
    pad_w: 1
    kernel_h: 1
    kernel_w: 3
  }
}
layer {
  name: "mixed_9_tower_1_mixed_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_9_tower_1_mixed_conv_conv2d"
  top: "mixed_9_tower_1_mixed_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_9_tower_1_mixed_conv_relu"
  type: "ReLU"
  bottom: "mixed_9_tower_1_mixed_conv_conv2d_bn"
  top: "mixed_9_tower_1_mixed_conv_conv2d_relu"
}
layer {
  name: "mixed_9_tower_1_mixed_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_9_tower_1_conv_1_conv2d_relu"
  top: "mixed_9_tower_1_mixed_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 1
    pad_w: 0
    kernel_h: 3
    kernel_w: 1
  }
}
layer {
  name: "mixed_9_tower_1_mixed_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_9_tower_1_mixed_conv_1_conv2d"
  top: "mixed_9_tower_1_mixed_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_9_tower_1_mixed_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_9_tower_1_mixed_conv_1_conv2d_bn"
  top: "mixed_9_tower_1_mixed_conv_1_conv2d_relu"
}
layer {
  name: "AVE_pool_mixed_9_pool"
  type: "Pooling"
  bottom: "ch_concat_mixed_8_chconcat"
  top: "AVE_pool_mixed_9_pool"
  pooling_param {
    pool: AVE
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "mixed_9_tower_2_conv_conv2d"
  type: "Convolution"
  bottom: "AVE_pool_mixed_9_pool"
  top: "mixed_9_tower_2_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_9_tower_2_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_9_tower_2_conv_conv2d"
  top: "mixed_9_tower_2_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_9_tower_2_conv_relu"
  type: "ReLU"
  bottom: "mixed_9_tower_2_conv_conv2d_bn"
  top: "mixed_9_tower_2_conv_conv2d_relu"
}
layer {
  name: "ch_concat_mixed_9_chconcat"
  type: "Concat"
  bottom: "mixed_9_conv_conv2d_relu"
  bottom: "mixed_9_tower_mixed_conv_conv2d_relu"
  bottom: "mixed_9_tower_mixed_conv_1_conv2d_relu"
  bottom: "mixed_9_tower_1_mixed_conv_conv2d_relu"
  bottom: "mixed_9_tower_1_mixed_conv_1_conv2d_relu"
  bottom: "mixed_9_tower_2_conv_conv2d_relu"
  top: "ch_concat_mixed_9_chconcat"
  concat_param {
    axis: 1
  }
}
layer {
  name: "mixed_10_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_9_chconcat"
  top: "mixed_10_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 320
    bias_term: false
    pad: 0
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    kernel_h: 1
    kernel_w: 1
  }
}
layer {
  name: "mixed_10_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_10_conv_conv2d"
  top: "mixed_10_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_10_conv_relu"
  type: "ReLU"
  bottom: "mixed_10_conv_conv2d_bn"
  top: "mixed_10_conv_conv2d_relu"
}
layer {
  name: "mixed_10_tower_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_9_chconcat"
  top: "mixed_10_tower_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_10_tower_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_10_tower_conv_conv2d"
  top: "mixed_10_tower_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_10_tower_conv_relu"
  type: "ReLU"
  bottom: "mixed_10_tower_conv_conv2d_bn"
  top: "mixed_10_tower_conv_conv2d_relu"
}
layer {
  name: "mixed_10_tower_mixed_conv_conv2d"
  type: "Convolution"
  bottom: "mixed_10_tower_conv_conv2d_relu"
  top: "mixed_10_tower_mixed_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 0
    pad_w: 1
    kernel_h: 1
    kernel_w: 3
  }
}
layer {
  name: "mixed_10_tower_mixed_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_10_tower_mixed_conv_conv2d"
  top: "mixed_10_tower_mixed_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_10_tower_mixed_conv_relu"
  type: "ReLU"
  bottom: "mixed_10_tower_mixed_conv_conv2d_bn"
  top: "mixed_10_tower_mixed_conv_conv2d_relu"
}
layer {
  name: "mixed_10_tower_mixed_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_10_tower_conv_conv2d_relu"
  top: "mixed_10_tower_mixed_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 1
    pad_w: 0
    kernel_h: 3
    kernel_w: 1
  }
}
layer {
  name: "mixed_10_tower_mixed_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_10_tower_mixed_conv_1_conv2d"
  top: "mixed_10_tower_mixed_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_10_tower_mixed_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_10_tower_mixed_conv_1_conv2d_bn"
  top: "mixed_10_tower_mixed_conv_1_conv2d_relu"
}
layer {
  name: "mixed_10_tower_1_conv_conv2d"
  type: "Convolution"
  bottom: "ch_concat_mixed_9_chconcat"
  top: "mixed_10_tower_1_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 448
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_10_tower_1_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_10_tower_1_conv_conv2d"
  top: "mixed_10_tower_1_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_10_tower_1_conv_relu"
  type: "ReLU"
  bottom: "mixed_10_tower_1_conv_conv2d_bn"
  top: "mixed_10_tower_1_conv_conv2d_relu"
}
layer {
  name: "mixed_10_tower_1_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_10_tower_1_conv_conv2d_relu"
  top: "mixed_10_tower_1_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_10_tower_1_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_10_tower_1_conv_1_conv2d"
  top: "mixed_10_tower_1_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_10_tower_1_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_10_tower_1_conv_1_conv2d_bn"
  top: "mixed_10_tower_1_conv_1_conv2d_relu"
}
layer {
  name: "mixed_10_tower_1_mixed_conv_conv2d"
  type: "Convolution"
  bottom: "mixed_10_tower_1_conv_1_conv2d_relu"
  top: "mixed_10_tower_1_mixed_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 0
    pad_w: 1
    kernel_h: 1
    kernel_w: 3
  }
}
layer {
  name: "mixed_10_tower_1_mixed_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_10_tower_1_mixed_conv_conv2d"
  top: "mixed_10_tower_1_mixed_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_10_tower_1_mixed_conv_relu"
  type: "ReLU"
  bottom: "mixed_10_tower_1_mixed_conv_conv2d_bn"
  top: "mixed_10_tower_1_mixed_conv_conv2d_relu"
}
layer {
  name: "mixed_10_tower_1_mixed_conv_1_conv2d"
  type: "Convolution"
  bottom: "mixed_10_tower_1_conv_1_conv2d_relu"
  top: "mixed_10_tower_1_mixed_conv_1_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    pad_h: 1
    pad_w: 0
    kernel_h: 3
    kernel_w: 1
  }
}
layer {
  name: "mixed_10_tower_1_mixed_conv_1_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_10_tower_1_mixed_conv_1_conv2d"
  top: "mixed_10_tower_1_mixed_conv_1_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_10_tower_1_mixed_conv_1_relu"
  type: "ReLU"
  bottom: "mixed_10_tower_1_mixed_conv_1_conv2d_bn"
  top: "mixed_10_tower_1_mixed_conv_1_conv2d_relu"
}
layer {
  name: "MAX_pool_mixed_10_pool"
  type: "Pooling"
  bottom: "ch_concat_mixed_9_chconcat"
  top: "MAX_pool_mixed_10_pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "mixed_10_tower_2_conv_conv2d"
  type: "Convolution"
  bottom: "MAX_pool_mixed_10_pool"
  top: "mixed_10_tower_2_conv_conv2d"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 192
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "mixed_10_tower_2_conv_batchnorm"
  type: "BatchNorm"
  bottom: "mixed_10_tower_2_conv_conv2d"
  top: "mixed_10_tower_2_conv_conv2d_bn"
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  param {
    lr_mult: 0.0
  }
  batch_norm_param {
    use_global_stats: false
    moving_average_fraction: 0.9997
    eps: 0.001
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    engine: CUDNN
  }
}
layer {
  name: "mixed_10_tower_2_conv_relu"
  type: "ReLU"
  bottom: "mixed_10_tower_2_conv_conv2d_bn"
  top: "mixed_10_tower_2_conv_conv2d_relu"
}
layer {
  name: "ch_concat_mixed_10_chconcat"
  type: "Concat"
  bottom: "mixed_10_conv_conv2d_relu"
  bottom: "mixed_10_tower_mixed_conv_conv2d_relu"
  bottom: "mixed_10_tower_mixed_conv_1_conv2d_relu"
  bottom: "mixed_10_tower_1_mixed_conv_conv2d_relu"
  bottom: "mixed_10_tower_1_mixed_conv_1_conv2d_relu"
  bottom: "mixed_10_tower_2_conv_conv2d_relu"
  top: "ch_concat_mixed_10_chconcat"
  concat_param {
    axis: 1
  }
}
layer {
  name: "global_pool"
  type: "Pooling"
  bottom: "ch_concat_mixed_10_chconcat"
  top: "global_pool"
  pooling_param {
    pool: AVE
    kernel_size: 8
    stride: 1
    pad: 0
  }
}
layer {
  name: "drop"
  type: "Dropout"
  bottom: "global_pool"
  top: "global_pool"
  dropout_param {
    dropout_ratio: 0.8
  }
}
layer {
  name: "flatten"
  type: "Flatten"
  bottom: "global_pool"
  top: "flatten"
}
layer {
  name: "fc1"
  type: "InnerProduct"
  bottom: "flatten"
  top: "fc1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  inner_product_param {
    num_output: 1000
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "loss"
  type: "SoftmaxWithLoss"
  bottom: "fc1"
  bottom: "label"
  top: "loss"
}
layer {
  name: "acc/top-1"
  type: "Accuracy"
  bottom: "fc1"
  bottom: "label"
  top: "acc/top-1"
  include {
    phase: TEST
  }
}
layer {
  name: "acc/top-5"
  type: "Accuracy"
  bottom: "fc1"
  bottom: "label"
  top: "acc/top-5"
  include {
    phase: TEST
  }
  accuracy_param {
    top_k: 5
  }
}