def _BertGlueDataStream(benchmark_id):
  """Returns a Bert-preprocessed data stream for ``benchmark_id``.

  Args:
    benchmark_id: String that indicates the name and data split of a GLUE
        benchmark. Data splits are indicated as underscore suffixes, e.g.,
        ``'cola_t'`` (Cola benchmark, training split), ``'rte_e'`` (RTE
        benchmark, eval/validation split), and ``'mnli_e2'`` (MNLI benchmark,
        alternate "mismatched" eval/validation split).
  """
  benchmark_id = _ensure_eval_suffix(benchmark_id)
  benchmark, split = benchmark_id.rsplit('_', 1)
  glue_data = TFDS(f'glue/{benchmark}',
                   keys=_GLUE_KEYS[benchmark],
                   train=(split == 't'),
                   use_alt_eval=(split == 'e2'))
  return data.Serial(
      glue_data,
      data.Tokenize(),
      data.CreateBertInputs(),
      data.Shuffle(),
      data.PadToLength(),
      data.TruncateToLength(),
      data.Batch(),
  )
Returns a Bert-preprocessed data stream for ``benchmark_id``.

  Args:
    benchmark_id: String that indicates the name and data split of a GLUE
        benchmark. Data splits are indicated as underscore suffixes, e.g.,
        ``'cola_t'`` (Cola benchmark, training split), ``'rte_e'`` (RTE
        benchmark, eval/validation split), and ``'mnli_e2'`` (MNLI benchmark,
        alternate "mismatched" eval/validation split).
  
trax/data/tf_inputs.py