code: def testDTypeToType(self):
      self.assertEqual(
          self.gfsg.fs_proto.INT,
          self.gfsg.DtypeToType(np.dtype(np.int32)),
      )
      # Boolean and time types treated as int
      self.assertEqual(
          self.gfsg.fs_proto.INT, self.gfsg.DtypeToType(np.dtype(bool))
      )
      self.assertEqual(
          self.gfsg.fs_proto.INT,
          self.gfsg.DtypeToType(np.dtype(np.datetime64)),
      )
      self.assertEqual(
          self.gfsg.fs_proto.INT,
          self.gfsg.DtypeToType(np.dtype(np.timedelta64)),
      )
      self.assertEqual(
          self.gfsg.fs_proto.FLOAT,
          self.gfsg.DtypeToType(np.dtype(np.float32)),
      )
      self.assertEqual(
          self.gfsg.fs_proto.STRING,
          self.gfsg.DtypeToType(np.dtype(str)),
      )
      # Unsupported types treated as string for now
      self.assertEqual(
          self.gfsg.fs_proto.STRING,
          self.gfsg.DtypeToType(np.dtype(np.void)),
      )
  
file_path: facets/facets_overview/facets_overview/generic_feature_statistics_generator_test.py
imports: from facets_overview.generic_feature_statistics_generator import GenericFeatureStatisticsGenerator
  import numpy
  import pandas
  from tensorflow.python.platform import googletest
label_desc: Use image node_id 5 for calling the GenericFeatureStatisticsGeneratorTest obj's underlying member method code with example usage: obj.testDTypeToType() without return types