code: def mnist(training):
    
    if training:
      data_filename = 'train-images-idx3-ubyte.gz'
      labels_filename = 'train-labels-idx1-ubyte.gz'
      count = 60000
    else:
      data_filename = 't10k-images-idx3-ubyte.gz'
      labels_filename = 't10k-labels-idx1-ubyte.gz'
      count = 10000
    data_filename = maybe_download(MNIST_URL, data_filename)
    labels_filename = maybe_download(MNIST_URL, labels_filename)
  
    return (mnist_extract_data(data_filename, count),
            mnist_extract_labels(labels_filename, count))
docs: Downloads MNIST and loads it into numpy arrays.