class_docstr: A JDMixin that shards the log_prob calculation.
code: def _default_event_space_bijector(self, *args, **kwargs):
      if args or kwargs:
          return _DefaultJointBijector(
              self.experimental_pin(*args, **kwargs)
          )
      return _DefaultJointBijector(self)
  
imports: import functools
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.distributions import joint_distribution
  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 log_prob_ratio
  from tensorflow_probability.python.internal import auto_composite_tensor
  from tensorflow_probability.python.internal import distribute_lib
  from tensorflow_probability.python.internal import samplers
label_desc: Use image node_id 3 for calling the JointDistributionDistributedMixin obj's underlying member method code with example usage: obj._default_event_space_bijector() and returns: _DefaultJointBijector, _DefaultJointBijector