code: def testCauchyQuantile(self):
      batch_size = 50
      loc = self._rng.randn(batch_size)
      scale = self._rng.rand(batch_size) + 1.0
      p = np.linspace(0.000001, 0.999999, batch_size).astype(np.float64)
  
      dist = cauchy.Cauchy(loc=loc, scale=scale, validate_args=True)
      x = dist.quantile(p)
  
      self.assertAllEqual(
          self.evaluate(dist.batch_shape_tensor()), x.shape
      )
      self.assertAllEqual(
          self.evaluate(dist.batch_shape_tensor()),
          self.evaluate(x).shape,
      )
      self.assertAllEqual(dist.batch_shape, x.shape)
      self.assertAllEqual(dist.batch_shape, self.evaluate(x).shape)
  
      expected_x = sp_stats.cauchy(loc, scale).ppf(p)
      self.assertAllClose(expected_x, self.evaluate(x), atol=0.0)
  
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 18 for calling the CauchyTest obj's underlying member method code with example usage: obj.testCauchyQuantile() without return types