code: def testGroupByWindow(self):
      # Verify that split providers are not propagated into iterators created for
      # the reduce datasets created by the reduce_fn in group_by_window.
      cluster = data_service_test_base.TestCluster(num_workers=2)
      elements = [1, 5, 0]
      ds = dataset_ops.Dataset.from_tensor_slices(elements)
  
      def reduce_fn(_, window):
          return dataset_ops.Dataset.zip(
              (window, dataset_ops.Dataset.range(100))
          )
  
      ds = ds.group_by_window(lambda x: 0, reduce_fn, window_size=3)
      ds = self._make_dynamic_sharding_dataset(ds, cluster)
      # This will fail if the tensor_slices split provider is propagated into the
      # `reduce_fn`, since the `zip` requires either 0 or 2 split providers.
      self.getDatasetOutput(ds)
  
imports: import collections
  from absl.testing import parameterized
  import numpy
  from tensorflow.python.data.experimental.kernel_tests.service import test_base
  from tensorflow.python.data.experimental.ops import data_service_ops
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.kernel_tests import tf_record_test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import readers
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import errors
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 8 for calling the DynamicShardingTest obj's underlying member method code with example usage: obj.testGroupByWindow() and returns: dataset_ops