code: def testDefaultBijectorXLA(self, dist_fn):
      self.skip_if_no_xla()
  
      @tf.function(jit_compile=True)
      def fn(x):
          bijector = (
              dist_fn().experimental_default_event_space_bijector()
          )
          ndim = tensorshape_util.rank(x.shape)
          return (
              bijector(x),
              bijector.forward_log_det_jacobian(x, ndim),
              bijector.inverse(0 + bijector(x)),
              bijector.inverse_log_det_jacobian(
                  0 + bijector(x), ndim - 1
              ),
          )
  
      self.evaluate(fn(tf.zeros(dist_fn().loc.shape + (0,))))
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import deterministic
  from tensorflow_probability.python.distributions import gamma
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 22 for calling the VectorDeterministicTest obj's underlying member method code with example usage: obj.testDefaultBijectorXLA(dist_fn) and returns: bijector,  bijector,  bijector,  bijector