code: def testLogNormalCDF(self):
      loc, scale = 1.5, 0.4
      dist = lognormal.LogNormal(
          loc=loc, scale=scale, validate_args=True
      )
  
      x = np.array([1e-4, 1.0, 2.0], dtype=np.float32)
  
      cdf = dist.cdf(x)
      analytical_cdf = 0.5 + 0.5 * tf.math.erf(
          (np.log(x) - loc) / (scale * np.sqrt(2))
      )
      self.assertAllClose(
          self.evaluate(cdf), self.evaluate(analytical_cdf)
      )
  
file_path: probability/tensorflow_probability/python/distributions/lognormal_test.py
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import lognormal
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 5 for calling the LogNormalTest obj's underlying member method code with example usage: obj.testLogNormalCDF() without return types