code: def testProbs(self):
      # survival functions
      # P(Y > 0) = sigmoid(1) = 0.7310586
      # P(Y > 1) = sigmoid(0) = 0.5
      # P(Y > 2) = sigmoid(-1) = 0.26894143
  
      # probs
      # P(Y = 0) = 1. - sigmoid(1) = 0.2689414
      # P(Y = 1) = sigmoid(1) - sigmoid(0) = 0.2310586
      # P(Y = 2) = sigmoid(0) - sigmoid(-1) = 0.23105857
      # P(Y = 3) = sigmoid(-1) = 0.26894143
      expected_probs = [0.2689414, 0.2310586, 0.23105857, 0.26894143]
      expected_survival_probs = 1.0 - np.cumsum(expected_probs)
      dist = ol.OrderedLogistic(cutpoints=[-1.0, 0.0, 1.0], loc=0.0)
  
      categorical_probs = self.evaluate(dist.categorical_probs())
      self.assertAllClose(expected_probs, categorical_probs, atol=1e-6)
  
      probs = np.flip(self.evaluate(dist.prob([3, 2, 1, 0])))
      self.assertAllClose(expected_probs, probs, atol=1e-6)
  
      survival_probs = self.evaluate(
          dist.survival_function([0, 1, 2, 3])
      )
      self.assertAllClose(
          expected_survival_probs, survival_probs, atol=1e-6
      )
  
      zero_probs = self.evaluate(dist.prob([-1, 4]))
      self.assertAllClose([0.0, 0.0], zero_probs, atol=1e-6)
  
      out_of_bounds_survival_probs = self.evaluate(
          dist.survival_function([-2, -1, 4, 5])
      )
      self.assertAllClose(
          [1.0, 1.0, 0.0, 0.0], out_of_bounds_survival_probs, atol=1e-6
      )
  
imports: import itertools
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import ascending
  from tensorflow_probability.python.distributions import categorical
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import logistic
  from tensorflow_probability.python.distributions import ordered_logistic
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 5 for calling the OrderedLogisticTest obj's underlying member method code with example usage: obj.testProbs() without return types