class_docstr: Tests concurrent sessions executing on the same GPU.
code: def testConcurrentSessions(self):
      n_threads = 4
      threads = []
      results = []
      for _ in range(n_threads):
          session = self.session(graph=ops.Graph(), use_gpu=True)
          results.append(set())
          args = (session, results[-1])
          threads.append(
              threading.Thread(target=self._run_session, args=args)
          )
  
      for thread in threads:
          thread.start()
      for thread in threads:
          thread.join()
  
      flat_results = set(itertools.chain(*results))
      self.assertEqual(
          1,
          len(flat_results),
          "Expected single value, got %r" % flat_results,
      )
  
imports: import itertools
  import threading
  import numpy
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import random_seed
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gradient_checker_v2
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.ops.gen_array_ops import broadcast_gradient_args
  from tensorflow.python.platform import test
label_desc: Use image node_id 2 for calling the GpuMultiSessionMemoryTest obj's underlying member method code with example usage: obj.testConcurrentSessions() without return types