code: def testQuantileInverseOfCDF(self, delta):
      lwn = lambertw_f.LambertWNormal(
          loc=2.0, scale=3.0, tailweight=delta
      )
      samples_ = self.evaluate(
          lwn.sample(5, seed=test_util.test_seed())
      )
      cdf_vals = lwn.cdf(samples_)
      self.assertAllClose(lwn.quantile(cdf_vals), samples_, rtol=1e-4)
  
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 7 for calling the LambertWNormalTest obj's underlying member method code with example usage: obj.testQuantileInverseOfCDF(delta) without return types