def process_main()

in main.py [0:0]

• 32 lines of code
• 9 McCabe index (conditional complexity)

def process_main(rank, sel, fname, world_size, devices):
    import os
    os.environ['CUDA_VISIBLE_DEVICES'] = str(devices[rank].split(':')[-1])

    import logging
    logging.basicConfig()
    logger = logging.getLogger()

    logger.info(f'called-params {sel} {fname}')

    # -- load script params
    params = None
    with open(fname, 'r') as y_file:
        params = yaml.load(y_file, Loader=yaml.FullLoader)
        logger.info('loaded params...')
        if rank == 0:
            pp = pprint.PrettyPrinter(indent=4)
            pp.pprint(params)

    if rank == 0:
        dump = os.path.join(params['logging']['folder'], f'params-{sel}.yaml')
        with open(dump, 'w') as f:
            yaml.dump(params, f)

    world_size, rank = init_distributed(rank_and_world_size=(rank, world_size))

    # -- make sure all processes correctly initialized torch-distributed
    logger.info(f'Running {sel} (rank: {rank}/{world_size})')

    # -- turn off info-logging for ranks > 0, otherwise too much std output
    if rank == 0:
        logger.setLevel(logging.INFO)
    else:
        logger.setLevel(logging.ERROR)

    if sel == 'paws_train':
        return paws(params)
    elif sel == 'suncet_train':
        return suncet(params)
    elif sel == 'fine_tune':
        return fine_tune(params)
    elif sel == 'snn_fine_tune':
        return snn_fine_tune(params)