code: def checkpoint(function, *args):
      """Checkpoint a model or part of the model.
      This has been directly copied from torch.utils.checkpoint."""
  
      all_outputs = []
      CheckpointFunction.apply(function, all_outputs, *args)
      if len(all_outputs) == 1:
          return all_outputs[0]
      else:
          return tuple(all_outputs)
  
imports: import copy
  import torch
  import contextlib
  from deepspeed import comm
  import weakref
  import mmap
  from torch import _C
  from deepspeed.runtime.config import DeepSpeedConfig
  from deepspeed.utils import logger
  from deepspeed.runtime.utils import copy_to_device, move_to_device, see_memory_usage, bwc_tensor_model_parallel_rank
  from deepspeed.utils.timer import SynchronizedWallClockTimer, FORWARD_GLOBAL_TIMER
  from deepspeed.accelerator import get_accelerator
label_desc: Use image node_id 16 for calling a global function with example usage: checkpoint(function) and returns: all_outputs, tuple