code: def testApproximateVocabulary(
      self,
      input_data,
      make_feature_spec,
      top_k,
      make_expected_vocab_fn,
      store_frequency,
      reserved_tokens,
  ):
      input_metadata = tft.DatasetMetadata.from_feature_spec(
          tft_unit.make_feature_spec_wrapper(make_feature_spec)
      )
  
      def preprocessing_fn(inputs):
          x = inputs["x"]
          weights = inputs.get("weights")
          # Note even though the return value is not used, calling
          # tft.experimental.approximate_vocabulary will generate the vocabulary as
          # a side effect, and since we have named this vocabulary it can be looked
          # up using public APIs.
          tft.experimental.approximate_vocabulary(
              x,
              top_k,
              store_frequency=store_frequency,
              weights=weights,
              vocab_filename="my_approximate_vocab",
              reserved_tokens=reserved_tokens,
              file_format=self._VocabFormat(),
          )
          return inputs
  
      expected_vocab_file_contents = make_expected_vocab_fn(
          self._VocabFormat()
      )
      if reserved_tokens is not None:
          expected_vocab_file_contents = [
              (t, -1) for t in reserved_tokens
          ] + expected_vocab_file_contents
      if not store_frequency:
          expected_vocab_file_contents = [
              token for token, _ in expected_vocab_file_contents
          ]
      self.assertAnalyzeAndTransformResults(
          input_data,
          input_metadata,
          preprocessing_fn,
          expected_vocab_file_contents={
              "my_approximate_vocab": expected_vocab_file_contents
          },
      )
  
imports: import os
  import apache_beam
  import tensorflow
  import tensorflow_transform
  from tensorflow_transform.beam import analyzer_impls
  from tensorflow_transform.beam import impl
  from tensorflow_transform.beam.tft_beam_io import transform_fn_io
  from tensorflow_transform.beam import tft_unit
  from tensorflow_metadata.proto.v0 import schema_pb2
label_desc: Use image node_id 4 for calling the VocabularyIntegrationTest obj's underlying member method code with example usage: obj.testApproximateVocabulary(input_data, make_feature_spec, top_k, make_expected_vocab_fn, store_frequency, reserved_tokens) and returns: inputs