docstr: Tests that quantiles are correct.
docstr_tok: ["Tests","that","quantiles","are","correct","."]
code: def testQuantileMethod(self):
      """Tests that quantiles are 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=5)
      normal_quantiles = normal.Normal(loc, scale).quantile(values)
      transformed_normal_quantiles = lambertw_transform.LambertWTail(
          shift=loc, scale=scale, tailweight=tailweight
      )(normal_quantiles)
      lambertw_quantiles = lwn.quantile(values)
      self.assertAllClose(
          transformed_normal_quantiles, lambertw_quantiles
      )
  
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 6 for calling the LambertWNormalTest obj's underlying member method code with example usage: obj.testQuantileMethod() without return types