train_val.prototxt

name: "LogisticRegressionNet"
layers {
  name: "data"
  type: HDF5_DATA
  top: "data"
  top: "label"
  hdf5_data_param {
    source: "data/train.txt"
    batch_size: 1
  }
  include: { phase: TRAIN }
}
layers {
  name: "data"
  type: HDF5_DATA
  top: "data"
  top: "label"
  hdf5_data_param {
    source: "data/test.txt"
    batch_size: 1
  }
  include: { phase: TEST }
}
layers {
  name: "fc1"
  type: INNER_PRODUCT
  bottom: "data"
  top: "fc1"
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1
  weight_decay: 0
  inner_product_param {
    num_output: 1
    weight_filler {
      type: "gaussian"
      std: 0.005
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}
layers {
  name: "loss"
  type: SOFTMAX_LOSS
  bottom: "fc1"
  bottom: "label"
  top: "loss"
}
layers {
  name: "accuracy"
  type: ACCURACY
  bottom: "fc1"
  bottom: "label"
  top: "accuracy"
  include: { phase: TEST }
}