code: def set_deterministic(seed=0):
      """Try to configure the system for reproducible results.
  
      Experiment reproducibility is sometimes important.  Pete Warden expounded about this
      in his blog: https://petewarden.com/2018/03/19/the-machine-learning-reproducibility-crisis/
      For Pytorch specifics see: https://pytorch.org/docs/stable/notes/randomness.html#reproducibility
      """
      msglogger.debug("set_deterministic was invoked")
      if seed is None:
          seed = 0
      set_seed(seed)
      torch.backends.cudnn.deterministic = True
      torch.backends.cudnn.benchmark = False
  
imports: import argparse
  from collections import OrderedDict
  from copy import deepcopy
  import logging
  import operator
  import random
  import numpy
  import torch
  import torch.nn
  import torch.backends.cudnn
  import yaml
  import inspect
label_desc: Use image node_id 45 for calling a global function with example usage: set_deterministic(seed) without return types