class_docstr: Test cases for stateful random-number generator operators.
class_docstr_tok: ["Test","cases","for","stateful","random-number","generator","operators","."]
code: def _testRngIsNotConstant(self, rng, dtype):
      # Tests that 'rng' does not always return the same value.
      # The random-number generator, if working correctly, should produce the
      # same output multiple times with low probability.
      x = rng(dtype).numpy()
      y = rng(dtype).numpy()
      self.assertFalse(np.array_equal(x, y))
  
imports: import itertools
  import os
  from absl.testing import parameterized
  import numpy
  from tensorflow.compiler.tests import xla_test
  from tensorflow.python.client import device_lib
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import config
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors_impl
  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 gen_stateful_random_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 flags
  from tensorflow.python.platform import test
label_desc: Use image node_id 8 for calling the StatefulRandomOpsTest obj's underlying member method code with example usage: obj._testRngIsNotConstant(rng, dtype) without return types