code: def test_inputs_using_generic_text_dataset_preprocess_fn(self):
      gin.bind_parameter(
          "generic_text_dataset_preprocess_fn.spm_path", _spm_path()
      )
      gin.bind_parameter(
          "generic_text_dataset_preprocess_fn.text_preprocess_fns",
          [lambda ds, training: t5_processors.squad(ds)],
      )
  
      # Just make sure this doesn't throw.
      def data_streams():
          return tf_inputs.data_streams(
              "squad",
              data_dir=_TESTDATA,
              input_name="inputs",
              target_name="targets",
              bare_preprocess_fn=tf_inputs.generic_text_dataset_preprocess_fn,
              shuffle_buffer_size=1,
          )
  
      n_devices = 3
  
      squad_inputs = inputs.batcher(
          data_streams=data_streams,
          max_eval_length=512,
          buckets=(
              [
                  513,
              ],
              [n_devices, n_devices],
          ),
      )
  
      eval_stream = squad_inputs.eval_stream(n_devices)
      inps, tgts, _ = next(eval_stream)
  
      # We can only assert that the batch dim gets divided by n_devices.
      self.assertEqual(inps.shape[0] % n_devices, 0)
      self.assertEqual(tgts.shape[0] % n_devices, 0)
  
imports: import collections
  import os
  from unittest import mock
  import gin
  import numpy
  from t5.data import assert_dataset
  from t5.data import preprocessors
  import tensorflow
  import tensorflow_datasets
  from trax.data import inputs
  from trax.data import tf_inputs
label_desc: Use image node_id 17 for calling the TFInputsTest obj's underlying member method code with example usage: obj.test_inputs_using_generic_text_dataset_preprocess_fn() and returns: tf_inputs