code: def _mean_or_nan(xs):
      """Return its mean a non-empty sequence, numpy.nan for a empty one."""
      return np.mean(xs) if xs else np.nan
  
imports: import collections
  import itertools
  from logging import getLogger
  import random
  import chainer
  import chainer.functions
  import numpy
  import chainerrl
  from chainerrl import agent
  from chainerrl.agents.ppo import _compute_explained_variance
  from chainerrl.agents.ppo import _make_dataset
  from chainerrl.agents.ppo import _make_dataset_recurrent
  from chainerrl.agents.ppo import _yield_subset_of_sequences_with_fixed_number_of_items
  from chainerrl.misc.batch_states import batch_states
label_desc: Use image node_id 8 for calling a global function with example usage: _mean_or_nan(xs) and returns: unknown