code: def testLogitNormalVarianceApprox(self):
      seed_stream = test_util.test_seed_stream()
      loc = tf.random.uniform(shape=[30], seed=seed_stream())
      scale = tf.random.uniform(
          minval=0.1, maxval=5.0, shape=[30], seed=seed_stream()
      )
      dist = ln_lib.LogitNormal(
          loc=loc, scale=scale, validate_args=True
      )
      x = dist.sample(int(10e3), seed=test_util.test_seed())
      variance_sample = tf.math.reduce_variance(x, axis=0)
      [variance_sample_, variance_approx_] = self.evaluate(
          [variance_sample, dist.variance_approx()]
      )
      self.assertAllClose(
          variance_sample_, variance_approx_, atol=1e-4, rtol=0.03
      )
  
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 3 for calling the LogitNormalTest obj's underlying member method code with example usage: obj.testLogitNormalVarianceApprox() without return types