class_docstr: Tests for TopkUniquesStatsGenerator.
class_docstr_tok: ["Tests","for","TopkUniquesStatsGenerator","."]
code: def test_schema_claims_categorical_but_actually_float(self):
      schema = text_format.Parse(
          """
      feature {
        name: "a"
        type: INT
        int_domain { is_categorical: true }
      }""",
          schema_pb2.Schema(),
      )
      inputs = [
          pa.RecordBatch.from_arrays(
              [pa.array([], type=pa.list_(pa.float32()))], ["a"]
          )
      ]
      generator = (
          top_k_uniques_stats_generator.TopKUniquesStatsGenerator(
              schema=schema,
              num_top_values=3,
              num_rank_histogram_buckets=3,
          )
      )
      self.assertSlicingAwareTransformOutputEqual(
          inputs,
          generator,
          expected_results=[],
          add_default_slice_key_to_input=True,
          add_default_slice_key_to_output=True,
      )
  
imports: from absl.testing import absltest
  import pyarrow
  from tensorflow_data_validation import types
  from tensorflow_data_validation.statistics.generators import top_k_uniques_stats_generator
  from tensorflow_data_validation.utils import test_util
  from tensorflow_data_validation.utils.example_weight_map import ExampleWeightMap
  from google.protobuf import text_format
  from tensorflow_metadata.proto.v0 import schema_pb2
  from tensorflow_metadata.proto.v0 import statistics_pb2
label_desc: Use image node_id 15 for calling the TopkUniquesStatsGeneratorTest obj's underlying member method code with example usage: obj.test_schema_claims_categorical_but_actually_float() without return types