res_cifar

name: "CIFAR10_resnet"
layer {
  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TRAIN
  }
  transform_param {
    scale: 0.003906
    crop_size: 28
    mirror: true
    mean_file: "examples/cifar10/mean.binaryproto"
  }
  data_param {
    source: "examples/cifar10/cifar10_train_lmdb"
    batch_size: 256
    backend: LMDB
  }
}

layer {
  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TEST
  }
  transform_param {
    scale: 0.003906
    crop_size: 28
    mean_file: "examples/cifar10/mean.binaryproto"
  }
  data_param {
    source: "examples/cifar10/cifar10_train_lmdb"
    batch_size: 256
    backend: LMDB
  }
}


layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data"
  top: "conv1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 16
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "msra"
      variance_norm: AVERAGE
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "bn_conv1"
  type: "BatchNorm"
  bottom: "conv1"
  top: "conv1"
  batch_norm_param {
    use_global_stats: true
  }
}

layer {
  name: "scale_conv1"
  type: "Scale"
  bottom: "conv1"
  top: "conv1"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "relu_conv1"
  type: "ReLU"
  bottom: "conv1"
  top: "conv1"
}

layer {
  name: "res1a_branch1a"
  type: "Convolution"
  bottom: "conv1"
  top: "res1a_branch1a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 16
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "msra"
      variance_norm: AVERAGE
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "bn1a_branch1a"
  type: "BatchNorm"
  bottom: "res1a_branch1a"
  top: "res1a_branch1a"
  batch_norm_param {
    use_global_stats: true
  }
}

layer {
  name: "scale1a_branch1a"
  type: "Scale"
  bottom: "res1a_branch1a"
  top: "res1a_branch1a"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "relu1a_branch1a"
  type: "ReLU"
  bottom: "res1a_branch1a"
  top: "res1a_branch1a"
}

layer {
  name: "res1a_branch1b"
  type: "Convolution"
  bottom: "res1a_branch1a"
  top: "res1a_branch1b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 16
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "msra"
      variance_norm: AVERAGE
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "bn1a_branch1b"
  type: "BatchNorm"
  bottom: "res1a_branch1b"
  top: "res1a_branch1b"
  batch_norm_param {
    use_global_stats: true
  }
}

layer {
  name: "scale1a_branch1b"
  type: "Scale"
  bottom: "res1a_branch1b"
  top: "res1a_branch1b"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "res1a"
  type: "Eltwise"
  bottom: "conv1"
  bottom: "res1a_branch1b"
  top: "res1a"
}

layer {
  name: "relu1a"
  type: "ReLU"
  bottom: "res1a"
  top: "res1a"
}

layer {
  name: "res2a_branch1a"
  type: "Convolution"
  bottom: "res1a"
  top: "res2a_branch1a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 16
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "msra"
      variance_norm: AVERAGE
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "bn2a_branch1a"
  type: "BatchNorm"
  bottom: "res2a_branch1a"
  top: "res2a_branch1a"
  batch_norm_param {
    use_global_stats: true
  }
}

layer {
  name: "scale2a_branch1a"
  type: "Scale"
  bottom: "res2a_branch1a"
  top: "res2a_branch1a"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "relu2a_branch1a"
  type: "ReLU"
  bottom: "res2a_branch1a"
  top: "res2a_branch1a"
}

layer {
  name: "res2a_branch1b"
  type: "Convolution"
  bottom: "res2a_branch1a"
  top: "res2a_branch1b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 16
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "msra"
      variance_norm: AVERAGE
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "bn2a_branch1b"
  type: "BatchNorm"
  bottom: "res2a_branch1b"
  top: "res2a_branch1b"
  batch_norm_param {
    use_global_stats: true
  }
}

layer {
  name: "scale2a_branch1b"
  type: "Scale"
  bottom: "res2a_branch1b"
  top: "res2a_branch1b"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "res2a"
  type: "Eltwise"
  bottom: "res1a"
  bottom: "res2a_branch1b"
  top: "res2a"
}

layer {
  name: "relu2a"
  type: "ReLU"
  bottom: "res2a"
  top: "res2a"
}

layer {
  name: "res3a_branch1a"
  type: "Convolution"
  bottom: "res2a"
  top: "res3a_branch1a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 16
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "msra"
      variance_norm: AVERAGE
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "bn3a_branch1a"
  type: "BatchNorm"
  bottom: "res3a_branch1a"
  top: "res3a_branch1a"
  batch_norm_param {
    use_global_stats: true
  }
}

layer {
  name: "scale3a_branch1a"
  type: "Scale"
  bottom: "res3a_branch1a"
  top: "res3a_branch1a"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "relu3a_branch1a"
  type: "ReLU"
  bottom: "res3a_branch1a"
  top: "res3a_branch1a"
}

layer {
  name: "res3a_branch1b"
  type: "Convolution"
  bottom: "res3a_branch1a"
  top: "res3a_branch1b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 16
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "msra"
      variance_norm: AVERAGE
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "bn3a_branch1b"
  type: "BatchNorm"
  bottom: "res3a_branch1b"
  top: "res3a_branch1b"
  batch_norm_param {
    use_global_stats: true
  }
}

layer {
  name: "scale3a_branch1b"
  type: "Scale"
  bottom: "res3a_branch1b"
  top: "res3a_branch1b"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "res3a"
  type: "Eltwise"
  bottom: "res2a"
  bottom: "res3a_branch1b"
  top: "res3a"
}

layer {
  name: "relu3a"
  type: "ReLU"
  bottom: "res3a"
  top: "res3a"
}

layer {
  name: "res1b_branch1a"
  type: "Convolution"
  bottom: "res3a"
  top: "res1b_branch1a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    kernel_size: 3
    stride: 2
    pad: 1
    weight_filler {
      type: "msra"
      variance_norm: AVERAGE
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "bn1b_branch1a"
  type: "BatchNorm"
  bottom: "res1b_branch1a"
  top: "res1b_branch1a"
  batch_norm_param {
    use_global_stats: true
  }
}

layer {
  name: "scale1b_branch1a"
  type: "Scale"
  bottom: "res1b_branch1a"
  top: "res1b_branch1a"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "relu1b_branch1a"
  type: "ReLU"
  bottom: "res1b_branch1a"
  top: "res1b_branch1a"
}

layer {
  name: "res1b_branch1b"
  type: "Convolution"
  bottom: "res1b_branch1a"
  top: "res1b_branch1b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "msra"
      variance_norm: AVERAGE
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "bn1b_branch1b"
  type: "BatchNorm"
  bottom: "res1b_branch1b"
  top: "res1b_branch1b"
  batch_norm_param {
    use_global_stats: true
  }
}

layer {
  name: "scale1b_branch1b"
  type: "Scale"
  bottom: "res1b_branch1b"
  top: "res1b_branch1b"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "res1b_branch2"
  type: "Convolution"
  bottom: "res3a"
  top: "res1b_branch2"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    stride: 2
    pad: 0
    weight_filler {
      type: "msra"
      variance_norm: AVERAGE
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "bn1b_branch2"
  type: "BatchNorm"
  bottom: "res1b_branch2"
  top: "res1b_branch2"
  batch_norm_param {
    use_global_stats: true
  }
}

layer {
  name: "scale1b_branch2"
  type: "Scale"
  bottom: "res1b_branch2"
  top: "res1b_branch2"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "res1b"
  type: "Eltwise"
  bottom: "res1b_branch2"
  bottom: "res1b_branch1b"
  top: "res1b"
}

layer {
  name: "relu1b"
  type: "ReLU"
  bottom: "res1b"
  top: "res1b"
}

layer {
  name: "res2b_branch1a"
  type: "Convolution"
  bottom: "res1b"
  top: "res2b_branch1a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "msra"
      variance_norm: AVERAGE
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "bn2b_branch1a"
  type: "BatchNorm"
  bottom: "res2b_branch1a"
  top: "res2b_branch1a"
  batch_norm_param {
    use_global_stats: true
  }
}

layer {
  name: "scale2b_branch1a"
  type: "Scale"
  bottom: "res2b_branch1a"
  top: "res2b_branch1a"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "relu2b_branch1a"
  type: "ReLU"
  bottom: "res2b_branch1a"
  top: "res2b_branch1a"
}

layer {
  name: "res2b_branch1b"
  type: "Convolution"
  bottom: "res2b_branch1a"
  top: "res2b_branch1b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "msra"
      variance_norm: AVERAGE
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "bn2b_branch1b"
  type: "BatchNorm"
  bottom: "res2b_branch1b"
  top: "res2b_branch1b"
  batch_norm_param {
    use_global_stats: true
  }
}

layer {
  name: "scale2b_branch1b"
  type: "Scale"
  bottom: "res2b_branch1b"
  top: "res2b_branch1b"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "res2b"
  type: "Eltwise"
  bottom: "res1b"
  bottom: "res2b_branch1b"
  top: "res2b"
}

layer {
  name: "relu2b"
  type: "ReLU"
  bottom: "res2b"
  top: "res2b"
}

layer {
  name: "res3b_branch1a"
  type: "Convolution"
  bottom: "res2b"
  top: "res3b_branch1a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "msra"
      variance_norm: AVERAGE
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "bn3b_branch1a"
  type: "BatchNorm"
  bottom: "res3b_branch1a"
  top: "res3b_branch1a"
  batch_norm_param {
    use_global_stats: true
  }
}

layer {
  name: "scale3b_branch1a"
  type: "Scale"
  bottom: "res3b_branch1a"
  top: "res3b_branch1a"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "relu3b_branch1a"
  type: "ReLU"
  bottom: "res3b_branch1a"
  top: "res3b_branch1a"
}

layer {
  name: "res3b_branch1b"
  type: "Convolution"
  bottom: "res3b_branch1a"
  top: "res3b_branch1b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "msra"
      variance_norm: AVERAGE
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "bn3b_branch1b"
  type: "BatchNorm"
  bottom: "res3b_branch1b"
  top: "res3b_branch1b"
  batch_norm_param {
    use_global_stats: true
  }
}

layer {
  name: "scale3b_branch1b"
  type: "Scale"
  bottom: "res3b_branch1b"
  top: "res3b_branch1b"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "res3b"
  type: "Eltwise"
  bottom: "res2b"
  bottom: "res3b_branch1b"
  top: "res3b"
}

layer {
  name: "relu3b"
  type: "ReLU"
  bottom: "res3b"
  top: "res3b"
}

layer {
  name: "res1c_branch1a"
  type: "Convolution"
  bottom: "res3b"
  top: "res1c_branch1a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64
    kernel_size: 3
    stride: 2
    pad: 1
    weight_filler {
      type: "msra"
      variance_norm: AVERAGE
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "bn1c_branch1a"
  type: "BatchNorm"
  bottom: "res1c_branch1a"
  top: "res1c_branch1a"
  batch_norm_param {
    use_global_stats: true
  }
}

layer {
  name: "scale1c_branch1a"
  type: "Scale"
  bottom: "res1c_branch1a"
  top: "res1c_branch1a"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "relu1c_branch1a"
  type: "ReLU"
  bottom: "res1c_branch1a"
  top: "res1c_branch1a"
}

layer {
  name: "res1c_branch1b"
  type: "Convolution"
  bottom: "res1c_branch1a"
  top: "res1c_branch1b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "msra"
      variance_norm: AVERAGE
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "bn1c_branch1b"
  type: "BatchNorm"
  bottom: "res1c_branch1b"
  top: "res1c_branch1b"
  batch_norm_param {
    use_global_stats: true
  }
}

layer {
  name: "scale1c_branch1b"
  type: "Scale"
  bottom: "res1c_branch1b"
  top: "res1c_branch1b"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "res1c_branch2"
  type: "Convolution"
  bottom: "res3b"
  top: "res1c_branch2"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    stride: 2
    pad: 0
    weight_filler {
      type: "msra"
      variance_norm: AVERAGE
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "bn1c_branch2"
  type: "BatchNorm"
  bottom: "res1c_branch2"
  top: "res1c_branch2"
  batch_norm_param {
    use_global_stats: true
  }
}

layer {
  name: "scale1c_branch2"
  type: "Scale"
  bottom: "res1c_branch2"
  top: "res1c_branch2"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "res1c"
  type: "Eltwise"
  bottom: "res1c_branch2"
  bottom: "res1c_branch1b"
  top: "res1c"
}

layer {
  name: "relu1c"
  type: "ReLU"
  bottom: "res1c"
  top: "res1c"
}

layer {
  name: "res2c_branch1a"
  type: "Convolution"
  bottom: "res1c"
  top: "res2c_branch1a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "msra"
      variance_norm: AVERAGE
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "bn2c_branch1a"
  type: "BatchNorm"
  bottom: "res2c_branch1a"
  top: "res2c_branch1a"
  batch_norm_param {
    use_global_stats: true
  }
}

layer {
  name: "scale2c_branch1a"
  type: "Scale"
  bottom: "res2c_branch1a"
  top: "res2c_branch1a"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "relu2c_branch1a"
  type: "ReLU"
  bottom: "res2c_branch1a"
  top: "res2c_branch1a"
}

layer {
  name: "res2c_branch1b"
  type: "Convolution"
  bottom: "res2c_branch1a"
  top: "res2c_branch1b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "msra"
      variance_norm: AVERAGE
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "bn2c_branch1b"
  type: "BatchNorm"
  bottom: "res2c_branch1b"
  top: "res2c_branch1b"
  batch_norm_param {
    use_global_stats: true
  }
}

layer {
  name: "scale2c_branch1b"
  type: "Scale"
  bottom: "res2c_branch1b"
  top: "res2c_branch1b"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "res2c"
  type: "Eltwise"
  bottom: "res1c"
  bottom: "res2c_branch1b"
  top: "res2c"
}

layer {
  name: "relu2c"
  type: "ReLU"
  bottom: "res2c"
  top: "res2c"
}

layer {
  name: "res3c_branch1a"
  type: "Convolution"
  bottom: "res2c"
  top: "res3c_branch1a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "msra"
      variance_norm: AVERAGE
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "bn3c_branch1a"
  type: "BatchNorm"
  bottom: "res3c_branch1a"
  top: "res3c_branch1a"
  batch_norm_param {
    use_global_stats: true
  }
}

layer {
  name: "scale3c_branch1a"
  type: "Scale"
  bottom: "res3c_branch1a"
  top: "res3c_branch1a"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "relu3c_branch1a"
  type: "ReLU"
  bottom: "res3c_branch1a"
  top: "res3c_branch1a"
}

layer {
  name: "res3c_branch1b"
  type: "Convolution"
  bottom: "res3c_branch1a"
  top: "res3c_branch1b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "msra"
      variance_norm: AVERAGE
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "bn3c_branch1b"
  type: "BatchNorm"
  bottom: "res3c_branch1b"
  top: "res3c_branch1b"
  batch_norm_param {
    use_global_stats: true
  }
}

layer {
  name: "scale3c_branch1b"
  type: "Scale"
  bottom: "res3c_branch1b"
  top: "res3c_branch1b"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "res3c"
  type: "Eltwise"
  bottom: "res2c"
  bottom: "res3c_branch1b"
  top: "res3c"
}

layer {
  name: "relu3c"
  type: "ReLU"
  bottom: "res3c"
  top: "res3c"
}

layer {
  name: "pool_res"
  type: "Pooling"
  bottom: "res3c"
  top: "pool_res"
  pooling_param {
    pool: AVE
    kernel_size: 7
    stride: 1
  }
}

layer {
  bottom: "pool_res"
  top: "fc10"
  name: "fc10"
  type: "InnerProduct"
  inner_product_param {
    num_output: 10
  }
}

layer {
  name: "accuracy"
  type: "Accuracy"
  bottom: "fc10"
  bottom: "label"
  top: "accuracy"
  include {
    phase: TEST
  }
}
layer {
  name: "loss"
  type: "SoftmaxWithLoss"
  bottom: "fc10"
  bottom: "label"
  top: "loss"
}