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 copy
  from logging import getLogger
  import numpy
  import torch
  from torch.nn import functional
  import pfrl
  from pfrl.agent import AttributeSavingMixin, BatchAgent
  from pfrl.replay_buffer import ReplayUpdater, batch_experiences
  from pfrl.utils import clip_l2_grad_norm_
  from pfrl.utils.batch_states import batch_states
  from pfrl.utils.copy_param import synchronize_parameters
label_desc: Use image node_id 1 for calling a global function with example usage: _mean_or_nan(xs) and returns: unknown