code: def testUnconstrainingBijector(self):
      dist = exponential.Exponential(
          rate=[1.0, 2.0, 6.0], validate_args=True
      )
      blockwise_dist = blockwise.Blockwise(dist, validate_args=True)
      x = self.evaluate(
          dist.experimental_default_event_space_bijector()(
              tf.ones(dist.batch_shape)
          )
      )
      x_blockwise = self.evaluate(
          blockwise_dist.experimental_default_event_space_bijector()(
              tf.ones(blockwise_dist.batch_shape)
          )
      )
      self.assertAllEqual(x, x_blockwise)
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import blockwise
  from tensorflow_probability.python.distributions import exponential
  from tensorflow_probability.python.distributions import gamma
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import joint_distribution_coroutine
  from tensorflow_probability.python.distributions import joint_distribution_named
  from tensorflow_probability.python.distributions import joint_distribution_sequential
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import mvn_linear_operator
  from tensorflow_probability.python.distributions import mvn_tril
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 10 for calling the BlockwiseTest obj's underlying member method code with example usage: obj.testUnconstrainingBijector() without return types