code: def testLogitNormalMeanAndVariance(self):
      locs, scales = tf.meshgrid(
          tf.linspace(-10.0, 10.0, 10),
          tf.exp(tf.linspace(-3.0, 3.0, 10)),
      )
      dist = ln_lib.LogitNormal(
          loc=locs,
          scale=scales,
          validate_args=True,
          gauss_hermite_scale_limit=1.0,
          num_probit_terms_approx=6,
      )
      means = dist.mean_approx()
      trap_means = logit_normal_mean_trapezoid(locs, scales)
      self.assertAllClose(trap_means, means, rtol=1e-4)
      variances = dist.variance_approx()
      trap_variances = logit_normal_variance_trapezoid(locs, scales)
      self.assertAllClose(trap_variances, variances, rtol=1e-4)
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import bernoulli
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import logitnormal
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 6 for calling the LogitNormalTest obj's underlying member method code with example usage: obj.testLogitNormalMeanAndVariance() without return types