class_docstr: Test cases for random-number generating operators.
code: def testTruncatedNormalIsInRange(self):
      count = 10000000
      # TODO(b/34339814): make this test work with 16 bit float types.
      for dtype in self._random_types() & {np.float32, np.float64}:
          with self.session():
              with self.test_scope():
                  x = random_ops.truncated_normal(
                      shape=[count], dtype=dtype
                  )
              self._checkTruncatedNormalIsInRange(
                  x,
                  a=-2,
                  b=2,
                  mu=0,
                  sigma=1,
                  count=count,
                  stat_test=True,
              )
  
imports: import math
  from absl.testing import parameterized
  import numpy
  from tensorflow.compiler.tests import xla_test
  from tensorflow.python.framework import dtypes
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops.distributions import special_math
  from tensorflow.python.platform import googletest
label_desc: Use image node_id 9 for calling the RandomOpsTest obj's underlying member method code with example usage: obj.testTruncatedNormalIsInRange() without return types