code: def test_docstring_example_stochastic_fibonacci(self):
      initial_state_prior = poisson.Poisson(5.0)
      initial_state_with_history_prior = (
          particle_filter_augmentation.augment_prior_with_state_history(
              initial_state_prior, history_size=2
          )
      )
  
      initial_state_with_history_prior.sample(8)
  
      @particle_filter_augmentation.augment_with_state_history
      def fibonacci_transition_fn(_, state_with_history):
          expected_next_element = tf.reduce_sum(
              state_with_history.state_history[:, -2:], axis=1
          )
          return poisson.Poisson(rate=expected_next_element)
  
      def observation_fn(_, state_with_history):
          return poisson.Poisson(rate=state_with_history.state)
  
      particle_filter.infer_trajectories(
          observations=tf.convert_to_tensor(
              [4.0, 11.0, 16.0, 23.0, 40.0, 69.0, 100.0]
          ),
          initial_state_prior=initial_state_with_history_prior,
          transition_fn=fibonacci_transition_fn,
          observation_fn=observation_fn,
          num_particles=8,
          seed=test_util.test_seed(),
      )
  
file_path: probability/tensorflow_probability/python/experimental/mcmc/particle_filter_augmentation_test.py
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import deterministic
  from tensorflow_probability.python.distributions import joint_distribution_named
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import poisson
  from tensorflow_probability.python.experimental.mcmc import particle_filter
  from tensorflow_probability.python.experimental.mcmc import particle_filter_augmentation
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 2 for calling the _ParticleFilterUtilTest obj's underlying member method code with example usage: obj.test_docstring_example_stochastic_fibonacci() and returns: poisson, poisson