code: def testLogisticLogSurvivalFunction(self):
      batch_size = 6
      np_loc = np.array([2.0] * batch_size, dtype=np.float32)
      loc = tf.constant(np_loc)
      scale = 1.5
  
      dist = logistic.Logistic(loc, scale, validate_args=True)
      x = np.array([2.5, 2.5, 4.0, 0.1, 1.0, 2.0], dtype=np.float32)
      logsurvival_function = dist.log_survival_function(x)
      expected_logsurvival_function = stats.logistic.logsf(
          x, np_loc, scale
      )
  
      self.assertEqual(logsurvival_function.shape, (6,))
      self.assertAllClose(
          self.evaluate(logsurvival_function),
          expected_logsurvival_function,
      )
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import logistic
  from tensorflow_probability.python.internal import reparameterization
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 6 for calling the LogisticTest obj's underlying member method code with example usage: obj.testLogisticLogSurvivalFunction() without return types