code: def test_works_with_transformed_distributions(self):
      dist = jit_public_methods.JitPublicMethods(
          uniform.Uniform(0.0, 1.0)
      )
      td = transformed_distribution.TransformedDistribution(
          distribution=dist,
          bijector=invert.Invert(
              dist.experimental_default_event_space_bijector()
          ),
      )
      if JAX_MODE:
          # TODO(b/184565492): Enable passing shapes to jitted methods in JAX.
          x = tf.zeros([], dtype=td.dtype)
      else:
          x = td.sample(seed=test_util.test_seed())
      td.log_prob(x)
  
imports: import types
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.distributions import uniform
  from tensorflow_probability.python.experimental.util import jit_public_methods
  from tensorflow_probability.python.internal import test_util
  from tensorflow.python.ops import control_flow_util
label_desc: Use image node_id 3 for calling the TracedPublicMethodsTest obj's underlying member method code with example usage: obj.test_works_with_transformed_distributions() without return types