code: def _prepare_args(
      log_likelihood_fn,
      state,
      log_likelihood=None,
      description="log_likelihood",
  ):
      """Processes input args to meet list-like assumptions."""
      state_parts = (
          list(state) if mcmc_util.is_list_like(state) else [state]
      )
      state_parts = [
          tf.convert_to_tensor(s, name="current_state")
          for s in state_parts
      ]
  
      log_likelihood = _maybe_call_fn(
          log_likelihood_fn, state_parts, log_likelihood, description
      )
      return [state_parts, log_likelihood]
  
imports: import collections
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.mcmc import kernel
  from tensorflow_probability.python.mcmc.internal import util
label_desc: Use image node_id 4 for calling a global function with example usage: _prepare_args(log_likelihood_fn, state, log_likelihood, description) and returns: list