code: def test_default_event_space_bijector(self):
      def sharded_lp_grad(x):
          dist = sharded.Sharded(
              sample_dist_lib.Sample(
                  exponential.Exponential(1.0), x.shape
              ),
              shard_axis_name=self.axis_name,
          )
          bij = dist.experimental_default_event_space_bijector()
          dist2 = transformed_distribution.TransformedDistribution(
              dist, invert.Invert(bij)
          )
          return gradient.value_and_gradient(dist2.log_prob, (x,))
  
      def lp_grad(x):
          dist = sample_dist_lib.Sample(
              exponential.Exponential(1.0), x.shape
          )
          bij = dist.experimental_default_event_space_bijector()
          dist2 = transformed_distribution.TransformedDistribution(
              dist, invert.Invert(bij)
          )
          return gradient.value_and_gradient(dist2.log_prob, (x,))
  
      x = tf.range(1, 1 + test_lib.NUM_DEVICES, dtype=tf.float32)
      sharded_x = self.shard_values(x)
      sharded_lp, sharded_g = self.per_replica_to_tensor(
          self.strategy_run(sharded_lp_grad, (sharded_x,))
      )
      true_lp, true_g = lp_grad(x)
  
      self.assertAllClose(true_lp, sharded_lp[0])
      self.assertAllCloseNested(true_g, sharded_g)
  
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.distributions import exponential
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import joint_distribution_coroutine
  from tensorflow_probability.python.distributions import log_prob_ratio
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import sample
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.experimental.distribute import joint_distribution
  from tensorflow_probability.python.experimental.distribute import sharded
  from tensorflow_probability.python.experimental.distributions import increment_log_prob
  from tensorflow_probability.python.internal import distribute_test_lib
  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 ShardTest obj's underlying member method code with example usage: obj.test_default_event_space_bijector() and returns: gradient, gradient