code: def testVaryingCountsAndMissing(self):
      # Tests parsing examples of when some examples have missing features
      examples = []
      for i in range(5):
          example = tf.train.Example()
          example.features.feature["other"].int64_list.value.append(0)
          for _ in range(i):
              example.features.feature["num"].int64_list.value.append(i)
          examples.append(example)
      example = tf.train.Example()
      example.features.feature["other"].int64_list.value.append(0)
      examples.append(example)
  
      entries = {}
      for i, example in enumerate(examples):
          self.fs._ParseExample(
              example.features.feature, [], entries, i
          )
  
      info = entries["num"]
      self.assertEqual(2, info["missing"])
      self.assertEqual(4, len(info["counts"]))
      for i in range(4):
          self.assertEqual(i + 1, info["counts"][i])
      self.assertEqual(10, len(info["vals"]))
  
imports: from feature_statistics_generator import FeatureStatisticsGenerator
  import numpy
  import tensorflow
  from tensorflow.python.platform import googletest
label_desc: Use image node_id 9 for calling the FeatureStatisticsGeneratorTest obj's underlying member method code with example usage: obj.testVaryingCountsAndMissing() without return types