code: def testSendRecvPartitionedGraphExecutesSynchronously(self):
      if not context.num_gpus():
          self.skipTest("GPU-only test (requires partitioned graph).")
  
      default_executor = test_util.TestDelta("flr_executor", "default")
      single_threaded = test_util.TestDelta(
          "flr_executor", "single_threaded"
      )
      run_async = test_util.TestDelta("pflr_runsync", "async")
      run_sync = test_util.TestDelta("pflr_runsync", "sync")
      send_only = test_util.TestDelta(
          "subgraph_async_summary", "send_only"
      )
      recv_only = test_util.TestDelta(
          "subgraph_async_summary", "recv_only"
      )
  
      array_ops.fill([2], constant_op.constant(7, dtype=dtypes.int64))
  
      assert default_executor.Get() == 0
      assert single_threaded.Get() > 0
      assert run_async.Get() == 0
      assert run_sync.Get() > 0
      assert send_only.Get() > 0
      assert recv_only.Get() > 0
  
imports: import time
  from tensorflow.python.data.experimental.ops import prefetching_ops
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.eager import benchmarks_test_base
  from tensorflow.python.eager import context
  from tensorflow.python.eager import test
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import bitwise_ops
  from tensorflow.python.ops import critical_section_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops.ragged import ragged_factory_ops
  from tensorflow.python.ops.ragged import ragged_map_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.util import tf_inspect
label_desc: Use image node_id 2 for calling the RunEagerOpAsFunctionInternalsTest obj's underlying member method code with example usage: obj.testSendRecvPartitionedGraphExecutesSynchronously() without return types