code: def master_process(args):
      return (not args.no_cuda and dist.get_rank() == 0) or (
          args.no_cuda and args.local_rank == -1
      )
  
imports: import os
  import sys
  import time
  import logging
  import numpy
  import random
  import json
  import torch
  import torch.distributed
  from torch.utils.data import DataLoader, Dataset
  from torch.utils.data.sampler import RandomSampler, SequentialSampler
  from torch.utils.data.distributed import DistributedSampler
  from tqdm import tqdm
  from turing.logger import Logger
  from turing.utils import get_sample_writer
  from turing.models import BertMultiTask
  from turing.dataset import PreTrainingDataset, PretrainBatch, PretrainDataType
  from turing.sources import PretrainingDataCreator, WikiPretrainingDataCreator, TokenInstance
  from pytorch_pretrained_bert.tokenization import BertTokenizer
  from pytorch_pretrained_bert.optimization import BertAdam, warmup_linear, warmup_linear_decay_exp, warmup_exp_decay_exp, warmup_exp_decay_poly
  from utils import get_argument_parser, is_time_to_exit
  from bing_bert_dataset_provider import BingBertDatasetProvider
  from nvidia_bert_dataset_provider import NvidiaBertDatasetProvider
  import deepspeed
  from deepspeed.utils.logging import logger
label_desc: Use image node_id 5 for calling a global function with example usage: master_process(args) and returns: unknown