docstr: Tests that generator invalidates stats if inconsistent types are used.
docstr_tok: ["Tests","that","generator","invalidates","stats","if","inconsistent","types","are","used","."]
code: def test_time_stats_generator_inconsistent_type_invalidation_check(
      self,
  ):
      """Tests that generator invalidates stats if inconsistent types are used."""
      # Absent invalidation, this is expected to give 6 matches.
      input_batches = [
          pa.array(
              [
                  ["2018-11-30", "2018-11-30", "2018-11-30"],
                  ["2018-11-30"],
              ]
          ),
          pa.array([["2018-11-30", "2018-11-30"]]),
          pa.array([[1.0]]),
      ]
      # No domain_info should be generated as the incorrect type of the 1.0 value
      # should invalidate the stats. Absent this type issue, these examples would
      # satisfy the specified match_ratio and values_threshold.
      generator = time_stats_generator.TimeStatsGenerator(
          match_ratio=0.5, values_threshold=1
      )
      self.assertCombinerOutputEqual(
          input_batches,
          generator,
          statistics_pb2.FeatureNameStatistics(),
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from unittest import mock
  from absl.testing import absltest
  from absl.testing import parameterized
  import pyarrow
  from tensorflow_data_validation import types
  from tensorflow_data_validation.statistics.generators import time_stats_generator
  from tensorflow_data_validation.utils import test_util
  from tensorflow_metadata.proto.v0 import schema_pb2
  from tensorflow_metadata.proto.v0 import statistics_pb2
label_desc: Use image node_id 5 for calling the TimeStatsGeneratorTest obj's underlying member method code with example usage: obj.test_time_stats_generator_inconsistent_type_invalidation_check() without return types