code: def testRandomSeed(self):
      test_cases = [
          # Each test case is a tuple with input to get_seed:
          # (input_graph_seed, input_op_seed)
          # and output from get_seed:
          # (output_graph_seed, output_op_seed)
          ((None, None), (None, None)),
          ((None, 1), (random_seed.DEFAULT_GRAPH_SEED, 1)),
          ((1, 1), (1, 1)),
          (
              (0, 0),
              (0, 2**31 - 1),
          ),  # Avoid nondeterministic (0, 0) output
          (
              (2**31 - 1, 0),
              (0, 2**31 - 1),
          ),  # Don't wrap to (0, 0) either
          (
              (0, 2**31 - 1),
              (0, 2**31 - 1),
          ),  # Wrapping for the other argument
      ]
      if context.executing_eagerly():
          # operation seed is random number generated based on global seed.
          # it's not tested due to possibility of platform or version difference.
          pass
      else:
          # 0 will be the default_graph._lastid.
          test_cases.append(((1, None), (1, 0)))
      for tc in test_cases:
          tinput, toutput = tc[0], tc[1]
          random_seed.set_random_seed(tinput[0])
          g_seed, op_seed = random_seed.get_seed(tinput[1])
          msg = "test_case = {0}, got {1}, want {2}".format(
              tinput, (g_seed, op_seed), toutput
          )
          self.assertEqual((g_seed, op_seed), toutput, msg=msg)
          random_seed.set_random_seed(None)
  
imports: from tensorflow.python.eager import context
  from tensorflow.python.framework import random_seed
  from tensorflow.python.framework import test_util
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling the RandomSeedTest obj's underlying member method code with example usage: obj.testRandomSeed() without return types