code: def _compute_average_correct(input_, labels, per_example_weights, topk=1):
    
    return _compute_sparse_average_correct(
        input_,
        tf.reshape(tf.argmax(labels, 1), [-1, 1]), per_example_weights, topk=topk)
docs: Returns the numerator and denominator of classifier accuracy.