class_docstr: Test cases for stateful random-number generator operators.
class_docstr_tok: ["Test","cases","for","stateful","random-number","generator","operators","."]
code: def testTruncatedNormal(self, alg, dtype):
      self.check_dtype(dtype)
      with ops.device(xla_device_name()):
          gen = random.Generator.from_seed(seed=123, alg=alg)
          n = 100000
          y = gen.truncated_normal(shape=[n], dtype=dtype).numpy()
          random_test_util.test_truncated_normal(
              self.assertEqual,
              self.assertAllClose,
              n,
              y,
              mean_atol=2e-3,
              median_atol=4e-3,
              variance_rtol=1e-2 if dtype == dtypes.bfloat16 else 5e-3,
          )
  
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 16 for calling the StatefulRandomOpsTest obj's underlying member method code with example usage: obj.testTruncatedNormal(alg, dtype) without return types