message: [tf.data service] Add test that different workers use independent shuffle orders.
  If shuffle seeds are unspecified, shuffle order should be non-deterministically chosen on each worker.
diff: @@ -31,6 +31,7 @@ from tensorflow.python.eager import def_function
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  +from tensorflow.python.framework import random_seed
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import tensor_array_ops
  @@ -78,6 +79,28 @@ class DataServiceOpsTest(test_base.DatasetTestBase, parameterized.TestCase):
  results = [elem.numpy() for elem in ds]
  self.assertEqual(list(range(num_elements)), results)
  + @combinations.generate(test_base.eager_only_combinations())
  + def testDifferentShuffleOrders(self):
  + random_seed.set_random_seed(None)
  + num_elements = 100
  + master_address = self.create_cluster(2)
  + ds = dataset_ops.Dataset.range(num_elements)
  + ds = ds.shuffle(num_elements)
  + ds = _make_distributed_dataset(ds, master_address)
  + output = [elem.numpy() for elem in ds]
  +
  + # The output will be two sequences of range(num_elements)
  + # non-deterministically interleaved together. If the orders of the elements
  + # were the same, first_order and second_order computed below will be equal.
  + first_order = {}
  + second_order = {}
  + for element in output:
  + if element in first_order:
  + second_order[element] = len(second_order)
  + else:
  + first_order[element] = len(first_order)
  + self.assertNotEqual(first_order, second_order)
  +
  @combinations.generate(test_base.eager_only_combinations())
  def testMultipleEpochs(self):
  num_elements = 3
  