code: def test_out_of_bounds(self):
      samples = normal.Normal(10.0, 0.1).sample(
          10000, seed=test_util.test_seed()
      )
      results = emp._evaluate_means_assertion(
          self.evaluate(samples),
          expected=0,
          axis=0,
          atol=0.003,
          rtol=1e-6,
      )
      result = results[0]
  
      # The true failure probabiliy should be almost 1
      self.assertGreater(
          result.bootstrap.for_error_rate(1e-9).low_p, 0.9
      )
  
      # Fixing the test by moving the tolerance should be fairly extreme
      suggestion = result.gaussian.for_error_rate(5.6e-7)
      self.assertGreater(suggestion.new_atol, 9.0)
  
      # It shouldn't be possible to fix this by increasing the number of
      # samples, because the empirical mean is out of bounds
      self.assertTrue(suggestion.out_of_bounds)
  
imports: from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import empirical_statistical_testing
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 2 for calling the EmpiricalStatisticalTestingTest obj's underlying member method code with example usage: obj.test_out_of_bounds() without return types