caffe/data/lenet_test.prototxt

name: "LeNet-test"
layers {
  layer {
    name: "mnist"
    type: "data"
    source: "data/mnist-test-leveldb"
    batchsize: 100
    scale: 0.00390625
  }
  top: "data"
  top: "label"
}
layers {
  layer {
    name: "conv1"
    type: "conv"
    num_output: 20
    kernelsize: 5
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
  bottom: "data"
  top: "conv1"
}
layers {
  layer {
    name: "pool1"
    type: "pool"
    kernelsize: 2
    stride: 2
    pool: MAX
  }
  bottom: "conv1"
  top: "pool1"
}
layers {
  layer {
    name: "conv2"
    type: "conv"
    num_output: 50
    kernelsize: 5
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
  bottom: "pool1"
  top: "conv2"
}
layers {
  layer {
    name: "pool2"
    type: "pool"
    kernelsize: 2
    stride: 2
    pool: MAX
  }
  bottom: "conv2"
  top: "pool2"
}
layers {
  layer {
    name: "ip1"
    type: "innerproduct"
    num_output: 500
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
  bottom: "pool2"
  top: "ip1"
}
layers {
  layer {
    name: "relu1"
    type: "relu"
  }
  bottom: "ip1"
  top: "ip1"
}
layers {
  layer {
    name: "ip2"
    type: "innerproduct"
    num_output: 10
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
  bottom: "ip1"
  top: "ip2"
}
layers {
  layer {
    name: "prob"
    type: "softmax"
  }
  bottom: "ip2"
  top: "prob"
}
layers {
  layer {
    name: "accuracy"
    type: "accuracy"
  }
  bottom: "prob"
  bottom: "label"
  top: "accuracy"
}