code: def testReduceSparse(
      self,
      num_processes,
      required_gpus,
      implementation,
      reduce_op,
      prefer_unique_instance_key,
  ):
      if (
          required_gpus == 0
          and implementation == CommunicationImplementation.NCCL
      ):
          self.skipTest("Skip CPU + NCCL combination")
      if (
          num_processes != required_gpus
          and implementation == CommunicationImplementation.NCCL
      ):
          self.skipTest(
              "Skip NCCL combination with mismatched process and GPU "
              "count. NCCL requires physical GPUs for every process."
          )
      if (
          num_processes != required_gpus
          and implementation == CommunicationImplementation.AUTO
      ):
          self.skipTest(
              "Skip potential NCCL combination (AUTO) with mismatched "
              "process and GPU count. NCCL requires physical GPUs for "
              "every process."
          )
      options = self.RunOptions(
          mode=[
              "func_graph"
          ],  # Sparse reduce is not supported in eager.
          num_processes=num_processes,
          gpus_per_process=required_gpus,
          reduce_op=reduce_op,
          communication_options=collective_util.Options(
              implementation=implementation
          ),
          prefer_unique_instance_key=prefer_unique_instance_key,
      )
      group_size = options.num_processes * (
          options.gpus_per_process or 1
      )
  
      inputs_data = [
          IndexedSlicesValue(
              values=[[1.0], [2.0]], indices=[0, 1], dense_shape=[10, 1]
          ),
          IndexedSlicesValue(
              values=[[3.0], [4.0]], indices=[1, 2], dense_shape=[10, 1]
          ),
          IndexedSlicesValue(
              values=[[5.0], [6.0]], indices=[7, 8], dense_shape=[10, 1]
          ),
          IndexedSlicesValue(
              values=[[7.0], [8.0]], indices=[3, 2], dense_shape=[10, 1]
          ),
      ]
      inputs = inputs_data[0:group_size]
  
      if group_size == 1:
          expect = IndexedSlices(
              values=[[1.0], [2.0]], indices=[0, 1], dense_shape=[10, 1]
          )
      elif group_size == 2:
          expect = IndexedSlices(
              values=[[1.0], [2.0], [3.0], [4.0]],
              indices=[0, 1, 1, 2],
              dense_shape=[10, 1],
          )
      elif group_size == 4:
          expect = IndexedSlices(
              values=[
                  [1.0],
                  [2.0],
                  [3.0],
                  [4.0],
                  [5.0],
                  [6.0],
                  [7.0],
                  [8.0],
              ],
              indices=[0, 1, 1, 2, 7, 8, 3, 2],
              dense_shape=[10, 1],
          )
  
      self.reduce_and_verify(inputs, expect, options)
  
imports: import collections
  import os
  import threading
  import time
  from absl.testing import parameterized
  from tensorflow.core.protobuf import config_pb2
  from tensorflow.core.protobuf import tensorflow_server_pb2
  from tensorflow.python.distribute import cluster_resolver
  from tensorflow.python.distribute import collective_util
  from tensorflow.python.distribute import combinations
  from tensorflow.python.distribute import cross_device_ops
  from tensorflow.python.distribute import cross_device_utils
  from tensorflow.python.distribute import device_util
  from tensorflow.python.distribute import multi_process_runner
  from tensorflow.python.distribute import multi_worker_test_base
  from tensorflow.python.distribute import reduce_util
  from tensorflow.python.distribute import test_util
  from tensorflow.python.distribute import values
  from tensorflow.python.eager import context
  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 indexed_slices
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import collective_ops
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import math_ops
  from tensorflow.python.util import nest
label_desc: Use image node_id 7 for calling the CollectiveOpsTest obj's underlying member method code with example usage: obj.testReduceSparse(num_processes, required_gpus, implementation, reduce_op, prefer_unique_instance_key) without return types