code: def testLogNormalPDF(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)
  
      log_pdf = dist.log_prob(x)
      analytical_log_pdf = -np.log(x * scale * np.sqrt(2 * np.pi)) - (
          np.log(x) - loc
      ) ** 2 / (2.0 * scale**2)
  
      self.assertAllClose(self.evaluate(log_pdf), analytical_log_pdf)
  
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 4 for calling the LogNormalTest obj's underlying member method code with example usage: obj.testLogNormalPDF() without return types