code: def testAssertValidSample(self):
      dist = ln_lib.LogitNormal(loc=0.0, scale=3.0, validate_args=True)
      self.evaluate(dist.prob([0.1, 0.3, 0.6]))
      self.evaluate(dist.prob([0.2, 0.3, 0.5]))
      # Either condition can trigger.
      with self.assertRaisesOpError("Sample must be non-negative."):
          self.evaluate(dist.prob([-1.0, 0.1, 0.5]))
      with self.assertRaisesOpError(
          "Sample must be less than or equal to `1`."
      ):
          self.evaluate(dist.prob([0.1, 0.2, 1.2]))
  
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 8 for calling the LogitNormalTest obj's underlying member method code with example usage: obj.testAssertValidSample() without return types