code: def verify_mesh_dataset_fn(self, mixture_name, train, use_cached):
      if train:
          dataset_fn = mesh_transformer.mesh_train_dataset_fn
          split = tfds.Split.TRAIN
      else:
          dataset_fn = mesh_transformer.mesh_eval_dataset_fn
          split = tfds.Split.VALIDATION
      sequence_length = {"inputs": 13, "targets": 13}
      output = dataset_fn(
          mixture_name,
          sequence_length=sequence_length,
          dataset_split=split,
          use_cached=use_cached,
      )
      if train:
          ds = output
          self.check_ds_shape(ds, sequence_length)
          # Materialize a few batches to test for errors.
          list(zip(range(10), tfds.as_numpy(ds)))
      else:
          self.assertLen(output, 1)
          output = output[0]
          (name, dsfn, postprocess_fn, metric_fns) = output
          self.assertEqual(
              "cached_task" if use_cached else "uncached_task", name
          )
          ds = dsfn()
          self.check_ds_shape(ds, sequence_length)
          # No postprocess_fn is supplied so it should function as a pass-through
          self.assertEqual("test", postprocess_fn("test"))
          # test_utils task has empty metric_fns list
          self.assertEmpty(metric_fns)
          # Materialize the full dataset to test for errors.
          list(tfds.as_numpy(ds))
  
file_path: text-to-text-transfer-transformer/t5/models/mesh_transformer_test.py
imports: from absl.testing import absltest
  import seqio
  from t5.models import mesh_transformer
  import tensorflow.compat.v1
  import tensorflow_datasets
label_desc: Use image node_id 2 for calling the MeshDatasetFnsTest obj's underlying member method code with example usage: obj.verify_mesh_dataset_fn(mixture_name, train, use_cached) without return types