code: def testCauchyLogSurvivalFunction(self):
      batch_size = 50
      loc = self._rng.randn(batch_size)
      scale = self._rng.rand(batch_size) + 1.0
      x = np.linspace(-10.0, 100.0, batch_size).astype(np.float64)
  
      dist = cauchy.Cauchy(loc=loc, scale=scale, validate_args=True)
  
      sf = dist.log_survival_function(x)
      self.assertAllEqual(
          self.evaluate(dist.batch_shape_tensor()), sf.shape
      )
      self.assertAllEqual(
          self.evaluate(dist.batch_shape_tensor()),
          self.evaluate(sf).shape,
      )
      self.assertAllEqual(dist.batch_shape, sf.shape)
      self.assertAllEqual(dist.batch_shape, self.evaluate(sf).shape)
  
      expected_sf = sp_stats.cauchy(loc, scale).logsf(x)
      self.assertAllClose(
          expected_sf, self.evaluate(sf), atol=0, rtol=1e-5
      )
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import cauchy
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 13 for calling the CauchyTest obj's underlying member method code with example usage: obj.testCauchyLogSurvivalFunction() without return types