code: def testIntStringOpsWithDistributedDataset(
      self, string_factory, drop_remainder
  ):
      ri = ragged_int64()
      # To ease testing both dense and ragged strings, pass in the ragged sizes
      # so the dense strings can be sliced to match.
      element_sizes = [len(i) for i in ri]
      ds_dict = {
          "int": ri,
          "str": string_factory(),
          "size": element_sizes,
      }
  
      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)
              # For dense string case, slice it to size of ragged int
              hashed_sliced = hashed[:, : elem["size"][0]]
              # Computation with both feature from string and numeric dataset output
              return reduce_sum(hashed_sliced) + 100 * reduce_sum(
                  elem["int"]
              )
  
          result = []
          for x in dist_dataset:
              result.append(strategy.run(replica_fn, args=(x,)))
          return result
  
      result = distributed_dataset_producer(ds_dict)
      self.assertAllEqual(916, self.evaluate(result[0].values[0]))
      self.assertAllEqual(0, self.evaluate(result[0].values[1]))
      self.assertAllEqual(1605, self.evaluate(result[1].values[0]))
      self.assertAllEqual(602, self.evaluate(result[1].values[1]))
      self.assertAllEqual(0, self.evaluate(result[2].values[0]))
      self.assertAllEqual(916, self.evaluate(result[2].values[1]))
      self.assertAllEqual(408, self.evaluate(result[3].values[0]))
      self.assertAllEqual(813, 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 7 for calling the RaggedFactoryOpsTest obj's underlying member method code with example usage: obj.testIntStringOpsWithDistributedDataset(string_factory, drop_remainder) and returns: result, unknown