code: def testLaplaceLogCDF(self):
      batch_size = 6
      loc = tf.constant([2.0] * batch_size)
      scale = tf.constant([3.0] * batch_size)
      loc_v = 2.0
      scale_v = 3.0
      x = np.array([-2.5, 2.5, -4.0, 0.1, 1.0, 2.0], dtype=np.float32)
  
      dist = laplace.Laplace(loc=loc, scale=scale, validate_args=True)
  
      cdf = dist.log_cdf(x)
      self.assertEqual(cdf.shape, (6,))
      expected_cdf = sp_stats.laplace.logcdf(x, loc_v, scale=scale_v)
      self.assertAllClose(self.evaluate(cdf), expected_cdf)
  
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 laplace
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 6 for calling the LaplaceTest obj's underlying member method code with example usage: obj.testLaplaceLogCDF() without return types