code: def testSegmentSumWithDynamicNumberOfSegments(self, distribution):
      def dataset_fn(_):
          data = array_ops.zeros(5, dtype=dtypes.int32)
          dataset = get_dataset_from_tensor_slices(data)
          dataset = dataset.batch(3)
          return dataset
  
      input_iterator = iter(
          distribution.distribute_datasets_from_function(dataset_fn)
      )
  
      @def_function.function
      def step_fn(example):
          segment_ids = array_ops.zeros_like_v2(example)
          num_segment = array_ops.shape(example)[0]
          # If number of segments is dynamic, output should be a dynamic shape.
          return math_ops.unsorted_segment_sum(
              example, segment_ids, num_segment
          )
  
      # This assumes that there are exactly 2 replicas
      outputs = distribution.experimental_local_results(
          distribution.run(step_fn, args=(next(input_iterator),))
      )
      self.assertAllEqual((3,), outputs[0].shape)
      self.assertAllEqual((2,), outputs[1].shape)
  
imports: from absl.testing import parameterized
  from tensorflow.python import tf2
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.distribute import combinations
  from tensorflow.python.distribute import device_util
  from tensorflow.python.distribute import distribute_lib
  from tensorflow.python.distribute import reduce_util
  from tensorflow.python.distribute import strategy_combinations
  from tensorflow.python.distribute import test_util
  from tensorflow.python.eager import def_function
  from tensorflow.python.eager import test
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_assert
  from tensorflow.python.ops import map_fn
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.ops.losses import losses
  from tensorflow.python.tpu import tpu
  from tensorflow.python.util import nest
label_desc: Use image node_id 27 for calling the InputIterationTest obj's underlying member method code with example usage: obj.testSegmentSumWithDynamicNumberOfSegments(distribution) and returns: dataset, math_ops