code: def testExpontentialQuantile(self):
      dist = exponential.Exponential(
          rate=[1.0, 2.0], validate_args=True
      )
  
      # Corner cases.
      result = self.evaluate(dist.quantile([0.0, 1.0]))
      self.assertAllClose(result, [0.0, np.inf])
  
      # Two sample values calculated by hand.
      result = self.evaluate(dist.quantile(0.5))
      self.assertAllClose(result, [0.693147, 0.346574])
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import exponential
  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 15 for calling the ExponentialTest obj's underlying member method code with example usage: obj.testExpontentialQuantile() without return types