code: def _default_trace_fn(state, kernel_results):
      return (
          state.particles,
          state.log_weights,
          kernel_results.parent_indices,
          kernel_results.incremental_log_marginal_likelihood,
      )
  
file_path: probability/tensorflow_probability/python/experimental/mcmc/particle_filter.py
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.experimental.mcmc import sequential_monte_carlo_kernel
  from tensorflow_probability.python.experimental.mcmc import weighted_resampling
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import distribution_util
  from tensorflow_probability.python.internal import docstring_util
  from tensorflow_probability.python.internal import loop_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.mcmc.internal import util
label_desc: Use image node_id 1 for calling a global function with example usage: _default_trace_fn(state, kernel_results) and returns: state,  state,  kernel_results,  kernel_results