class_docstr: Copy of ForkingPickler of `multiprocessing` module
class_docstr_tok: ["Copy","of","ForkingPickler","of","`","multiprocessing","`","module"]
docstr: Constructor of ForkingPickler
docstr_tok: ["Constructor","of","ForkingPickler"]
code: def __init__(self, *args):
      """Constructor of ForkingPickler"""
      super().__init__(*args)
      self.dispatch_table = self._copyreg_dispatch_table.copy()
      self.dispatch_table.update(self._extra_reducers)
  
imports: import copyreg
  import io
  import os
  import pickle
  import random
  import traceback
  import types
  from contextlib import suppress
  from dataclasses import _is_dataclass_instance, asdict
  from inspect import signature
  from time import time
  from typing import Any, List, Union
  import numpy
  import torch
  import torch.distributed
  import torch.multiprocessing
  import torch.nn
  from transformers.file_utils import ModelOutput
  from parallelformers.parallel.engine import ParallelEngine
  from parallelformers.policies.base import Policy
label_desc: Use image node_id 1 to create a new ForkingPickler object from inherited base classes: pickle with example: obj = ForkingPickler()