lenet_train_test.prototxt

name: "LeNet"
layers {
  name: "mnist"
  type: DATA
  top: "data"
  top: "label"
  data_param {
    source: "../mnist/data/npow_train_lmdb_raw"
    backend: LMDB
    batch_size: 100
  }
  transform_param {
    scale: 0.00390625
  }
  include: { phase: TRAIN }
}
layers {
  name: "mnist"
  type: DATA
  top: "data"
  top: "label"
  data_param {
    source: "../mnist/data/npow_test_lmdb_raw"
    backend: LMDB
    batch_size: 400
  }
  transform_param {
    scale: 0.00390625
  }
  include: { phase: TEST }
}

layers {
  name: "conv1"
  type: CONVOLUTION
  bottom: "data"
  top: "conv1"
  blobs_lr: 1
  blobs_lr: 2
  convolution_param {
    num_output: 20
    kernel_size: 5
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layers {
  name: "pool1"
  type: POOLING
  bottom: "conv1"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layers {
  name: "conv2"
  type: CONVOLUTION
  bottom: "pool1"
  top: "conv2"
  blobs_lr: 1
  blobs_lr: 2
  convolution_param {
    num_output: 50
    kernel_size: 5
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layers {
  name: "pool2"
  type: POOLING
  bottom: "conv2"
  top: "pool2"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}

#layers {
#  name: "conv3"
#  type: CONVOLUTION
#  bottom: "pool2"
#  top: "conv3"
#  blobs_lr: 1
#  blobs_lr: 2
#  convolution_param {
#    num_output: 500
#    kernel_size: 3
#    stride: 1
#    weight_filler {
#      type: "xavier"
#    }
#    bias_filler {
#      type: "constant"
#    }
#  }
#}
#layers {
#  name: "pool3"
#  type: POOLING
#  bottom: "conv3"
#  top: "pool3"
#  pooling_param {
#    pool: MAX
#    kernel_size: 2
#    stride: 2
#  }
#}

layers {
  name: "ip1"
  type: INNER_PRODUCT
  bottom: "pool2"
  top: "ip1"
  blobs_lr: 1
  blobs_lr: 2
  inner_product_param {
    num_output: 500
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layers {
  name: "relu1"
  type: RELU
  bottom: "ip1"
  top: "ip1"
}
layers {
  name: "ip2"
  type: INNER_PRODUCT
  bottom: "ip1"
  top: "ip2"
  blobs_lr: 1
  blobs_lr: 2
  inner_product_param {
    num_output: 10
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layers {
  name: "accuracy"
  type: ACCURACY
  bottom: "ip2"
  bottom: "label"
  top: "accuracy"
  include: { phase: TEST }
}
#layers {
#  name: "argmax"
#  type: ARGMAX
#  bottom: "ip2"
#  top: "argmax"
#  include: { phase: TEST }
#}
layers {
  name: "loss"
  type: SOFTMAX_LOSS
  bottom: "ip2"
  bottom: "label"
  top: "loss"
}