code: def testImbalancedZipAndRepeat(self):
      smaller_num_elements = 200
      larger_num_elements = 1000
      repetitions = 3
  
      cluster = data_service_test_base.TestCluster(num_workers=1)
      a = dataset_ops.Dataset.range(smaller_num_elements)
      b = dataset_ops.Dataset.range(larger_num_elements)
  
      ds = dataset_ops.Dataset.zip((a, b))
      ds = ds.repeat(repetitions)
      ds = self._make_dynamic_sharding_dataset(ds, cluster)
  
      expected = repetitions * (
          list(
              zip(
                  range(smaller_num_elements),
                  range(smaller_num_elements),
              )
          )
      )
  
      self.assertDatasetProduces(ds, expected)
  
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 17 for calling the DynamicShardingTest obj's underlying member method code with example usage: obj.testImbalancedZipAndRepeat() without return types