code: def test_uneven_batched_dataset(self):
      elements = [[1, 2, 3], [1, 2], [1, 2, 3, 4]]
      dataset = dataset_ops.Dataset.from_generator(
          lambda: elements, dtypes.int64
      ).repeat()
      strategy = mwms.MultiWorkerMirroredStrategy()
      with self.assertRaisesRegex(
          ValueError, "requires a static batch size"
      ):
          strategy.experimental_distribute_dataset(dataset)
  
imports: import json
  import os
  from absl import flags
  from absl.testing import parameterized
  import numpy
  from tensorflow.dtensor.python import api
  from tensorflow.dtensor.python import d_variable
  from tensorflow.dtensor.python import layout
  from tensorflow.dtensor.python.tests import multi_client_test_util
  from tensorflow.dtensor.python.tests import test_backend_util
  from tensorflow.dtensor.python.tests import test_util
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.distribute import distribute_lib
  from tensorflow.python.distribute import reduce_util
  from tensorflow.python.distribute.cluster_resolver import tfconfig_cluster_resolver
  from tensorflow.python.distribute.experimental import dtensor_util
  from tensorflow.python.distribute.experimental import multi_worker_mirrored_strategy
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import config
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import stateless_random_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
label_desc: Use image node_id 3 for calling the StrategyDatasetTest obj's underlying member method code with example usage: obj.test_uneven_batched_dataset() without return types