code: def test(predictions, labels, k=1):
      """
      Return precision and recall modeled after fasttext's test
      """
      precision = 0.0
      nexamples = 0
      nlabels = 0
      for prediction, labels in zip(predictions, labels):
          for p in prediction:
              if p in labels:
                  precision += 1
          nexamples += 1
          nlabels += len(labels)
      return (precision / (k * nexamples), precision / nlabels)
  
file_path: fastText/python/fasttext_module/fasttext/util/util.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import numpy
  import sys
  import shutil
  import os
  import gzip
label_desc: Use image node_id 1 for calling a global function with example usage: test(predictions, labels, k) and returns: unknown,  unknown