code: def test_can_jit_creation_of_stateless_surrogate_posterior(self):
      seed = test_util.test_seed(sampler_type="stateless")
      if not JAX_MODE:
          self.skipTest("Test is specific to JAX.")
      import jax  # pylint: disable=g-import-not-at-top
  
      @jax.jit
      def init(seed):
          model = normal.Normal(0.0, 1.0)
          (
              init_fn,
              _,
          ) = surrogate_posteriors.build_factored_surrogate_posterior_stateless(
              event_shape=model.event_shape
          )
          return init_fn(seed)
  
      init(seed)
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.bijectors import fill_triangular
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.bijectors import joint_map
  from tensorflow_probability.python.bijectors import masked_autoregressive
  from tensorflow_probability.python.bijectors import sigmoid
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import deterministic
  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 laplace
  from tensorflow_probability.python.distributions import logistic
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import sample
  from tensorflow_probability.python.distributions import student_t
  from tensorflow_probability.python.experimental.vi import surrogate_posteriors
  from tensorflow_probability.python.internal import nest_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.internal import tf_keras
  from tensorflow_probability.python.vi import optimization
  from tensorflow.python.util import nest
label_desc: Use image node_id 5 for calling the FactoredSurrogatePosterior obj's underlying member method code with example usage: obj.test_can_jit_creation_of_stateless_surrogate_posterior() and returns: init_fn