def main()

in evaluate.py [0:0]

• 12 lines of code
• 3 McCabe index (conditional complexity)

def main():
    args = parser.parse_args()
    if args.train_percent in {1, 10}:
        args.train_files = urllib.request.urlopen(f'https://raw.githubusercontent.com/google-research/simclr/master/imagenet_subsets/{args.train_percent}percent.txt').readlines()
    args.ngpus_per_node = torch.cuda.device_count()
    if 'SLURM_JOB_ID' in os.environ:
        signal.signal(signal.SIGUSR1, handle_sigusr1)
        signal.signal(signal.SIGTERM, handle_sigterm)
    # single-node distributed training
    args.rank = 0
    args.dist_url = f'tcp://localhost:{random.randrange(49152, 65535)}'
    args.world_size = args.ngpus_per_node
    torch.multiprocessing.spawn(main_worker, (args,), args.ngpus_per_node)