code: def testLogitNormalMeanApprox(self):
      loc, scale = [-1.5, 0.0, 1.5], 0.4
      dist = ln_lib.LogitNormal(
          loc=loc, scale=scale, validate_args=True
      )
      x = dist.sample(int(10e3), seed=test_util.test_seed())
      [x_, mean_approx_] = self.evaluate([x, dist.mean_approx()])
      self.assertAllMeansClose(
          x_, mean_approx_, axis=0, atol=1e-4, rtol=0.01
      )
  
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 1 for calling the LogitNormalTest obj's underlying member method code with example usage: obj.testLogitNormalMeanApprox() without return types