docstr: Tests that output of the cdf method is correct.
docstr_tok: ["Tests","that","output","of","the","cdf","method","is","correct","."]
code: def testCDFMethod(self):
      """Tests that output of the cdf method is correct."""
      tailweight = 0.0
      loc = 2.0
      scale = 3.0
      lwn = lambertw_f.LambertWNormal(
          loc=loc, scale=scale, tailweight=tailweight
      )
  
      values = np.random.uniform(low=0.0, high=1.0, size=10)
      quantiles = normal.Normal(loc, scale).quantile(values)
      heavy_tailed_values = lambertw_transform.LambertWTail(
          shift=loc, scale=scale, tailweight=tailweight
      )(quantiles)
      lambertw_normal_values = lwn.cdf(heavy_tailed_values)
      self.assertAllClose(values, lambertw_normal_values)
  
imports: import math
  from absl.testing import parameterized
  import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import lambertw_transform
  from tensorflow_probability.python.distributions import lambertw_f
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import student_t
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.distributions import uniform
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.internal import tf_keras
label_desc: Use image node_id 5 for calling the LambertWNormalTest obj's underlying member method code with example usage: obj.testCDFMethod() without return types