import tensorflow as tf

      filtered_value_node,
      vocab_filename=vocab_filename,
      store_frequency=store_frequency,
      fingerprint_shuffle=fingerprint_shuffle,
      input_dtype=input_dtype,
      file_format=file_format,
      # LINT.IfChange(input_is_sorted)
      input_is_sorted=(top_k is not None and key_fn is None and
                       not fingerprint_shuffle)
      # LINT.ThenChange(beam/analyzer_impls.py:top_k_impl)
  )

  scope = tf.compat.v1.get_default_graph().get_name_scope()
  unfiltered_vocab_size_node = nodes.apply_operation(
      analyzer_nodes.VocabularyCount,
      merge_output_value_node,
      label=f'VocabularyCountUnfiltered[{scope}]')
  unfiltered_vocab_size = analyzer_nodes.bind_future_as_tensor(
      unfiltered_vocab_size_node,
      analyzer_nodes.TensorInfo(tf.int64, [], None),
      name=f'{vocab_filename}_unpruned_vocab_size')
  filtered_vocab_size_node = nodes.apply_operation(
      analyzer_nodes.VocabularyCount,
      filtered_value_node,
