code: def testOpsWithDistributedDataset(
      self, string_factory, drop_remainder
  ):
      def distributed_dataset_producer(t):
          strategy = mirrored_strategy.MirroredStrategy(
              ["GPU:0", "GPU:1"]
          )
          ragged_ds = dataset_ops.Dataset.from_tensor_slices(t).batch(
              2, drop_remainder
          )
          dist_dataset = strategy.experimental_distribute_dataset(
              ragged_ds
          )
  
          @def_function.function
          def replica_fn(elem):
              # Example of typical preprocessing of string to numeric feature
              hashed = string_to_hash_bucket(elem["str"], 10)
              return 1000 * hashed
  
          result = []
          for x in dist_dataset:
              result.append(strategy.run(replica_fn, args=(x,)))
          return result
  
      ds_dict = {"str": string_factory()}
      result = distributed_dataset_producer(ds_dict)
      expect_length = [len(i) for i in ds_dict["str"]]
      self.assertAllEqual(
          [[5000, 3000, 5000, 3000][: expect_length[0]]],
          self.evaluate(result[0].values[0]),
      )
      self.assertAllEqual(
          [[9000, 9000, 9000, 9000][: expect_length[1]]],
          self.evaluate(result[0].values[1]),
      )
      self.assertAllEqual(
          [[0, 3000, 2000, 9000][: expect_length[2]]],
          self.evaluate(result[1].values[0]),
      )
      self.assertAllEqual(
          [[2000, 9000, 9000, 9000][: expect_length[3]]],
          self.evaluate(result[1].values[1]),
      )
      self.assertAllEqual(
          [[9000, 9000, 9000, 9000][: expect_length[4]]],
          self.evaluate(result[2].values[0]),
      )
      self.assertAllEqual(
          [[5000, 3000, 5000, 3000][: expect_length[5]]],
          self.evaluate(result[2].values[1]),
      )
      self.assertAllEqual(
          [[5000, 3000, 9000, 9000][: expect_length[6]]],
          self.evaluate(result[3].values[0]),
      )
      self.assertAllEqual(
          [[2000, 3000, 5000, 3000][: expect_length[7]]],
          self.evaluate(result[3].values[1]),
      )
  
imports: from absl.testing import parameterized
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import multi_device_iterator_ops
  from tensorflow.python.distribute import mirrored_strategy
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import map_fn
  from tensorflow.python.ops.math_ops import reduce_sum
  from tensorflow.python.ops.ragged import ragged_factory_ops
  from tensorflow.python.ops.string_ops import string_to_hash_bucket
  from tensorflow.python.platform import test
label_desc: Use image node_id 6 for calling the RaggedFactoryOpsTest obj's underlying member method code with example usage: obj.testOpsWithDistributedDataset(string_factory, drop_remainder) and returns: result, unknown