code: def _type_spec(self):
      # If `kwargs_split_fn` is the default, omit it so the type spec is
      # serializable.
      if self._kwargs_split_fn is _default_kwargs_split_fn:
          omit_kwargs = ("parameters", "kwargs_split_fn")
      else:
          omit_kwargs = ("parameters",)
      return _TransformedDistributionSpec.from_instance(
          self,
          omit_kwargs=omit_kwargs,
          non_identifying_kwargs=("name",),
      )
  
imports: import functools
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import ldj_ratio
  from tensorflow_probability.python.distributions import batch_broadcast
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import log_prob_ratio
  from tensorflow_probability.python.internal import auto_composite_tensor
  from tensorflow_probability.python.internal import distribution_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import tensorshape_util
label_desc: Use image node_id 2 for calling the TransformedDistribution obj's underlying member method code with example usage: obj._type_spec() and returns: _TransformedDistributionSpec