def main()

in distributed_training/src_dir/main_trainer.py [0:0]

• 16 lines of code
• 4 McCabe index (conditional complexity)

def main():
    print("start main function")
    args = args_fn()
    args.exp_cnt = 0
    print(
        "args.data_parallel : {} , args.model_parallel : {}, args.apex : {} , args.num_gpus : {}, args.num_classes"
        .format(args.data_parallel, args.model_parallel, args.apex,
                args.num_gpus, args.num_classes))

    args.use_cuda = int(args.num_gpus) > 0
    
#     os.environ['PYTHONWARNINGS'] = 'ignore:semaphore_tracker:UserWarning'

    args.kwargs = {
        'num_workers': 16,
        'pin_memory': True
    } if args.use_cuda else {}
    args.device = torch.device("cuda" if args.use_cuda else "cpu")
    if args.exp_cnt == 0:
        args = dis_util.dist_init(train, args)