code: def testAllReduceCombinerWithIndirectDependency(self):
      # The purpose of this test is to validate the depdency check in AllReduce
      # AllReduce combiner (dtensor_allreduce_combine_optimization). Specifically,
      # the side effects from indirect dependency.
      self.skipForPathways("TODO(b/260775095)")
      self.skipForDeviceType(
          ["TPU"],
          "This test requires 8 TPU cores.",
          unless_device_count_equals_to=8,
      )
  
      # Create and use an eight-device mesh just for this test.
      global_ids = test_util.create_device_ids_array((8,))
      local_ids = np.ravel(global_ids).tolist()
      mesh_dict = {
          device: layout_lib.Mesh(
              [_MESH_DIM_X],
              global_ids,
              local_ids,
              test_util.create_device_list((8,), device),
          )
          for device in ("CPU", "GPU", "TPU")
      }
  
      mesh = self.configTestMesh(mesh_dict)
      first_dim_sharded_layout_1d = Layout.batch_sharded(
          mesh, _MESH_DIM_X, rank=1
      )
  
      init_value = constant_op.constant(
          np.ones(32), dtype=dtypes.float32
      )
      init_value = api.relayout(init_value, first_dim_sharded_layout_1d)
  
      # 2nd reduction indrectly depend on the 1st reduction
      @polymorphic_function.function
      def func(v):
          a = math_ops.reduce_sum(v)
          v.assign_add(v + a)
          b = math_ops.reduce_sum(v)
          return b
  
      v = d_variable.DVariable(init_value)
      dtensor_result = func(v)
  
      # Replicate the scenario above without using dtensor
      expected_result = constant_op.constant(
          np.ones(32), dtype=dtypes.float32
      )
      expected_result += expected_result + math_ops.reduce_sum(
          expected_result
      )
      expected_result = math_ops.reduce_sum(expected_result)
  
      self.assertDTensorEqual(
          expected_result,
          Layout.replicated(mesh=mesh, rank=0),
          dtensor_result,
      )
  
imports: import os
  from absl.testing import parameterized
  import numpy
  from tensorflow.dtensor.python import api
  from tensorflow.dtensor.python import config
  from tensorflow.dtensor.python import d_variable
  from tensorflow.dtensor.python import dtensor_device
  from tensorflow.dtensor.python import layout
  from tensorflow.dtensor.python.tests import test_backend_util
  from tensorflow.dtensor.python.tests import test_util
  from tensorflow.python.eager.polymorphic_function import polymorphic_function
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_array_ops
  from tensorflow.python.ops import gen_math_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 5 for calling the CollectiveTestWithCustomMesh obj's underlying member method code with example usage: obj.testAllReduceCombinerWithIndirectDependency() and returns: b