class_docstr: Test cases for random-number generating operators.
code: def _implParameterizedTruncatedNormalIsInRange(
      self, a, b, mu, sigma, count, stat_test
  ):
      # 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.parameterized_truncated_normal(
                      shape=[count],
                      dtype=dtype,
                      means=mu,
                      stddevs=sigma,
                      minvals=a,
                      maxvals=b,
                  )
              self._checkTruncatedNormalIsInRange(
                  x,
                  a=a,
                  b=b,
                  mu=mu,
                  sigma=sigma,
                  count=count,
                  stat_test=stat_test,
              )
  
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 10 for calling the RandomOpsTest obj's underlying member method code with example usage: obj._implParameterizedTruncatedNormalIsInRange(a, b, mu, sigma, count, stat_test) without return types