code: def multiprocessing(context: Optional[str] = None):
      import torch.multiprocessing
  
      if context is None:
          return torch.multiprocessing
      return torch.multiprocessing.get_context(context)
  
imports: from functools import reduce
  from numbers import Number
  from operator import mul
  from typing import Optional, Union, Sequence, Callable, List, Tuple
  import numpy
  import torch
  import ivy
  from ivy.func_wrapper import with_unsupported_dtypes, _update_torch_views
  from .None import backend_version, is_variable
  from ...ivy.general import _broadcast_to
label_desc: Use image node_id 21 for calling a global function with example usage: multiprocessing(context) and returns: torch, torch