code: def testReset(self):
      shape = [2, 3]
      gen = random.Generator.from_seed(0)
      for resetter in [
          lambda g: g.reset(state=[1, 2, 3]),
          lambda g: g.reset_from_seed(1234),
          lambda g: g.reset_from_key_counter(key=1, counter=[2, 3]),
      ]:
          resetter(gen)
          expected_normal = gen.normal(shape)
  
          @def_function.function
          def f(resetter):
              resetter(gen)
              return gen.normal(shape)
  
          def check_results(expected_normal, v):
              self.assertAllEqual(expected_normal, v)
  
          check_results(expected_normal, f(resetter))
          check_results(expected_normal, f(resetter))
  
imports: import os
  import re
  from absl.testing import parameterized
  import numpy
  from tensorflow.python.checkpoint import checkpoint
  from tensorflow.python.eager import context
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import config
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.kernel_tests.random import util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_random_ops
  from tensorflow.python.ops import gen_stateful_random_ops
  from tensorflow.python.ops import logging_ops
  from tensorflow.python.ops import random_ops_util
  from tensorflow.python.ops import stateful_random_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
label_desc: Use image node_id 10 for calling the StatefulRandomOpsTest obj's underlying member method code with example usage: obj.testReset() and returns: gen