# ResNet18
name: "ResNet18"
layer {
  name: "train-data"
  type: "Data"
  top: "data"
  top: "label"
  transform_param {
    mirror: true
    crop_size: 224
  }
  data_param {
    batch_size: 32
  }
  include { stage: "train" }
}
layer {
  name: "val-data"
  type: "Data"
  top: "data"
  top: "label"
  transform_param {
    mirror: false
    crop_size: 224
  }
  data_param {
    batch_size: 16
  }
  include { stage: "val" }
}
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data"
  top: "conv1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 3
    kernel_size: 7
    stride: 2
    weight_filler {
      type: "msra"
      std: 0.0005
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}
layer {
  name: "bn_conv1"
  type: "BatchNorm"
  bottom: "conv1"
  top: "conv1_bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  batch_norm_param {
    scale_filler {
      type: "constant"
      value: 1
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "conv1_relu"
  type: "ReLU"
  bottom: "conv1_bn"
  top: "conv1_bn"
}
layer {
  name: "pool1"
  type: "Pooling"
  bottom: "conv1_bn"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "res2a_branch1"
  type: "Convolution"
  bottom: "pool1"
  top: "res2a_branch1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
      std: 0.0005
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}
layer {
  name: "bn2a_branch1"
  type: "BatchNorm"
  bottom: "res2a_branch1"
  top: "res2a_branch1_bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  batch_norm_param {
    scale_filler {
      type: "constant"
      value: 1
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "res2a_branch2a"
  type: "Convolution"
  bottom: "pool1"
  top: "res2a_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
      std: 0.0005
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}
layer {
  name: "bn2a_branch2a"
  type: "BatchNorm"
  bottom: "res2a_branch2a"
  top: "res2a_branch2a_bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  batch_norm_param {
    scale_filler {
      type: "constant"
      value: 1
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "res2a_branch2a_relu"
  type: "ReLU"
  bottom: "res2a_branch2a_bn"
  top: "res2a_branch2a_bn"
}
layer {
  name: "res2a_branch2b"
  type: "Convolution"
  bottom: "res2a_branch2a_bn"
  top: "res2a_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
      std: 0.0005
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}
layer {
  name: "bn2a_branch2b"
  type: "BatchNorm"
  bottom: "res2a_branch2b"
  top: "res2a_branch2b_bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  batch_norm_param {
    scale_filler {
      type: "constant"
      value: 1
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "res2a_branch2b_relu"
  type: "ReLU"
  bottom: "res2a_branch2b_bn"
  top: "res2a_branch2b_bn"
}
layer {
  name: "res2a_branch2c"
  type: "Convolution"
  bottom: "res2a_branch2b_bn"
  top: "res2a_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
      std: 0.0005
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}
layer {
  name: "bn2a_branch2c"
  type: "BatchNorm"
  bottom: "res2a_branch2c"
  top: "res2a_branch2c_bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  batch_norm_param {
    scale_filler {
      type: "constant"
      value: 1
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "res2a"
  type: "Eltwise"
  bottom: "res2a_branch1_bn"
  bottom: "res2a_branch2c_bn"
  top: "res2a"
}
layer {
  name: "res2a_relu"
  type: "ReLU"
  bottom: "res2a"
  top: "res2a"
}
layer {
  name: "res2b_branch2a"
  type: "Convolution"
  bottom: "res2a"
  top: "res2b_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
      std: 0.0005
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}
layer {
  name: "bn2b_branch2a"
  type: "BatchNorm"
  bottom: "res2b_branch2a"
  top: "res2b_branch2a_bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  batch_norm_param {
    scale_filler {
      type: "constant"
      value: 1
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "res2b_branch2a_relu"
  type: "ReLU"
  bottom: "res2b_branch2a_bn"
  top: "res2b_branch2a_bn"
}
layer {
  name: "res2b_branch2b"
  type: "Convolution"
  bottom: "res2b_branch2a_bn"
  top: "res2b_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
      std: 0.0005
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}
layer {
  name: "bn2b_branch2b"
  type: "BatchNorm"
  bottom: "res2b_branch2b"
  top: "res2b_branch2b_bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  batch_norm_param {
    scale_filler {
      type: "constant"
      value: 1
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "res2b_branch2b_relu"
  type: "ReLU"
  bottom: "res2b_branch2b_bn"
  top: "res2b_branch2b_bn"
}
layer {
  name: "res2b_branch2c"
  type: "Convolution"
  bottom: "res2b_branch2b_bn"
  top: "res2b_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
      std: 0.0005
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}
layer {
  name: "bn2b_branch2c"
  type: "BatchNorm"
  bottom: "res2b_branch2c"
  top: "res2b_branch2c_bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  batch_norm_param {
    scale_filler {
      type: "constant"
      value: 1
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "res2b"
  type: "Eltwise"
  bottom: "res2a"
  bottom: "res2b_branch2c_bn"
  top: "res2b"
}
layer {
  name: "res2b_relu"
  type: "ReLU"
  bottom: "res2b"
  top: "res2b"
}
layer {
  name: "res2c_branch2a"
  type: "Convolution"
  bottom: "res2b"
  top: "res2c_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
      std: 0.0005
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}
layer {
  name: "bn2c_branch2a"
  type: "BatchNorm"
  bottom: "res2c_branch2a"
  top: "res2c_branch2a_bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  batch_norm_param {
    scale_filler {
      type: "constant"
      value: 1
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "res2c_branch2a_relu"
  type: "ReLU"
  bottom: "res2c_branch2a_bn"
  top: "res2c_branch2a_bn"
}
layer {
  name: "res2c_branch2b"
  type: "Convolution"
  bottom: "res2c_branch2a_bn"
  top: "res2c_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
      std: 0.0005
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}
layer {
  name: "bn2c_branch2b"
  type: "BatchNorm"
  bottom: "res2c_branch2b"
  top: "res2c_branch2b_bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  batch_norm_param {
    scale_filler {
      type: "constant"
      value: 1
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "res2c_branch2b_relu"
  type: "ReLU"
  bottom: "res2c_branch2b_bn"
  top: "res2c_branch2b_bn"
}
layer {
  name: "res2c_branch2c"
  type: "Convolution"
  bottom: "res2c_branch2b_bn"
  top: "res2c_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
      std: 0.0005
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}
layer {
  name: "bn2c_branch2c"
  type: "BatchNorm"
  bottom: "res2c_branch2c"
  top: "res2c_branch2c_bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  batch_norm_param {
    scale_filler {
      type: "constant"
      value: 1
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "res2c"
  type: "Eltwise"
  bottom: "res2b"
  bottom: "res2c_branch2c_bn"
  top: "res2c"
}
layer {
  name: "res2c_relu"
  type: "ReLU"
  bottom: "res2c"
  top: "res2c"
}
layer {
  name: "res3a_branch1"
  type: "Convolution"
  bottom: "res2c"
  top: "res3a_branch1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 2
    weight_filler {
      type: "msra"
      std: 0.0005
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}
layer {
  name: "bn3a_branch1"
  type: "BatchNorm"
  bottom: "res3a_branch1"
  top: "res3a_branch1_bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  batch_norm_param {
    scale_filler {
      type: "constant"
      value: 1
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "res3a_branch2a"
  type: "Convolution"
  bottom: "res2c"
  top: "res3a_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 0
    kernel_size: 1
    stride: 2
    weight_filler {
      type: "msra"
      std: 0.0005
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}
layer {
  name: "bn3a_branch2a"
  type: "BatchNorm"
  bottom: "res3a_branch2a"
  top: "res3a_branch2a_bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  batch_norm_param {
    scale_filler {
      type: "constant"
      value: 1
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "res3a_branch2a_relu"
  type: "ReLU"
  bottom: "res3a_branch2a_bn"
  top: "res3a_branch2a_bn"
}
layer {
  name: "res3a_branch2b"
  type: "Convolution"
  bottom: "res3a_branch2a_bn"
  top: "res3a_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
      std: 0.0005
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}
layer {
  name: "bn3a_branch2b"
  type: "BatchNorm"
  bottom: "res3a_branch2b"
  top: "res3a_branch2b_bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  batch_norm_param {
    scale_filler {
      type: "constant"
      value: 1
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "res3a_branch2b_relu"
  type: "ReLU"
  bottom: "res3a_branch2b_bn"
  top: "res3a_branch2b_bn"
}
layer {
  name: "res3a_branch2c"
  type: "Convolution"
  bottom: "res3a_branch2b_bn"
  top: "res3a_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
      std: 0.0005
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}
layer {
  name: "bn3a_branch2c"
  type: "BatchNorm"
  bottom: "res3a_branch2c"
  top: "res3a_branch2c_bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  batch_norm_param {
    scale_filler {
      type: "constant"
      value: 1
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "res3a"
  type: "Eltwise"
  bottom: "res3a_branch1_bn"
  bottom: "res3a_branch2c_bn"
  top: "res3a"
}
layer {
  name: "res3a_relu"
  type: "ReLU"
  bottom: "res3a"
  top: "res3a"
}
layer {
  name: "res3b_branch2a"
  type: "Convolution"
  bottom: "res3a"
  top: "res3b_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
      std: 0.0005
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}
layer {
  name: "bn3b_branch2a"
  type: "BatchNorm"
  bottom: "res3b_branch2a"
  top: "res3b_branch2a_bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  batch_norm_param {
    scale_filler {
      type: "constant"
      value: 1
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "res3b_branch2a_relu"
  type: "ReLU"
  bottom: "res3b_branch2a_bn"
  top: "res3b_branch2a_bn"
}
layer {
  name: "res3b_branch2b"
  type: "Convolution"
  bottom: "res3b_branch2a_bn"
  top: "res3b_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
      std: 0.0005
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}
layer {
  name: "bn3b_branch2b"
  type: "BatchNorm"
  bottom: "res3b_branch2b"
  top: "res3b_branch2b_bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  batch_norm_param {
    scale_filler {
      type: "constant"
      value: 1
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "res3b_branch2b_relu"
  type: "ReLU"
  bottom: "res3b_branch2b_bn"
  top: "res3b_branch2b_bn"
}
layer {
  name: "res3b_branch2c"
  type: "Convolution"
  bottom: "res3b_branch2b_bn"
  top: "res3b_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
      std: 0.0005
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}
layer {
  name: "bn3b_branch2c"
  type: "BatchNorm"
  bottom: "res3b_branch2c"
  top: "res3b_branch2c_bn"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  param {
    lr_mult: 1
    decay_mult: 0
  }
  batch_norm_param {
    scale_filler {
      type: "constant"
      value: 1
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "res3b"
  type: "Eltwise"
  bottom: "res3a"
  bottom: "res3b_branch2c_bn"
  top: "res3b"
}
layer {
  name: "res3b_relu"
  type: "ReLU"
  bottom: "res3b"
  top: "res3b"
}
layer {
  name: "pool2"
  type: "Pooling"
  bottom: "res3b"
  top: "pool2"
  pooling_param {
    pool: AVE
    kernel_size: 7
    stride: 1
  }
}
layer {
  name: "fclayer"
  type: "InnerProduct"
  bottom: "pool2"
  top: "fclayer"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "accuracy"
  type: "Accuracy"
  bottom: "fclayer"
  bottom: "label"
  top: "accuracy"
  include { stage: "val" }
}
layer {
  name: "loss"
  type: "SoftmaxWithLoss"
  bottom: "fclayer"
  bottom: "label"
  top: "loss"
  exclude { stage: "deploy" }
}
layer {
  name: "softmax"
  type: "Softmax"
  bottom: "fclayer"
  top: "softmax"
  include { stage: "deploy" }
}