code: def _log_average_probs_process_args(
      logits, validate_args, sample_axis, event_axis
  ):
      """Processes args for `log_average_probs`."""
      rank = ps.rank(logits)
      if sample_axis is None or validate_args:
          event_axis = ps.reshape(
              ps.non_negative_axis(event_axis, rank), shape=[-1]
          )
      if sample_axis is None:
          sample_axis = ps.setdiff1d(ps.range(rank), event_axis)
      elif validate_args:
          sample_axis = ps.reshape(
              ps.non_negative_axis(sample_axis, rank), shape=[-1]
          )
      return sample_axis, event_axis
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import distribution_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.math.generic import reduce_logmeanexp
label_desc: Use image node_id 14 for calling a global function with example usage: _log_average_probs_process_args(logits, validate_args, sample_axis, event_axis) and returns: sample_axis,  event_axis