code: def testLargerBatchSize(self):
      with tf.Session() as sess:
          with tempfile.NamedTemporaryFile(
              mode="w+t", delete=False
          ) as vocab:
              raw_data = {
                  "label": ["1", "2"],
                  "text_a": [
                      "The boy jumped into the air.",
                      "The cat sat on a hat.",
                  ],
                  "lang": ["en", "en"],
              }
              expected_wordpieces = [
                  "The",
                  "[UNK]",
                  "jumped",
                  "in",
                  "##to",
                  "the",
                  "air",
                  ".",
                  "The",
                  "cat",
                  "sat",
                  "on",
                  "a",
                  "h",
                  "##at",
                  ".",
              ]
              vocab.writelines([word + "\n" for word in self.vocab])
              vocab.flush()
              preprocessing_fn = utils.metrics_preprocessing_fn(
                  vocab.name, "text_a", "lang"
              )
              outputs = preprocessing_fn(raw_data)
              tf.tables_initializer().run()
              outputs = sess.run(outputs)
  
              self.assertSequenceAlmostEqual(
                  outputs["lang"], ["en", "en"]
              )
              self.assertSequenceAlmostEqual(
                  outputs["num_preserved_chars"], [20, 16]
              )
              self.assertSequenceAlmostEqual(
                  outputs["num_dropped_chars"], [3, 0]
              )
              self.assertSequenceAlmostEqual(
                  outputs["wordpieces"].values, expected_wordpieces
              )
              self.assertSequenceAlmostEqual(
                  outputs["num_non_unk_wordpieces"], [7, 8]
              )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import logging
  import tempfile
  from absl.testing import absltest
  import apache_beam
  from apache_beam.testing.test_pipeline import TestPipeline
  from apache_beam.testing.util import assert_that
  from apache_beam.testing.util import equal_to
  import tensorflow.compat.v1
  from tensorflow_text.tools.wordpiece_vocab import utils
label_desc: Use image node_id 3 for calling the MetricsPreprocessingFnTest obj's underlying member method code with example usage: obj.testLargerBatchSize() without return types