src/paws_train.py [115:145]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    wd = float(args['optimization']['weight_decay'])
    num_epochs = args['optimization']['epochs']
    warmup = args['optimization']['warmup']
    start_lr = args['optimization']['start_lr']
    lr = args['optimization']['lr']
    final_lr = args['optimization']['final_lr']
    mom = args['optimization']['momentum']
    nesterov = args['optimization']['nesterov']

    # -- LOGGING
    folder = args['logging']['folder']
    tag = args['logging']['write_tag']
    # ----------------------------------------------------------------------- #

    # -- init torch distributed backend
    world_size, rank = init_distributed()
    logger.info(f'Initialized (rank/world-size) {rank}/{world_size}')

    # -- log/checkpointing paths
    log_file = os.path.join(folder, f'{tag}_r{rank}.csv')
    save_path = os.path.join(folder, f'{tag}' + '-ep{epoch}.pth.tar')
    latest_path = os.path.join(folder, f'{tag}-latest.pth.tar')
    best_path = os.path.join(folder, f'{tag}' + '-best.pth.tar')
    load_path = None
    if load_model:
        load_path = os.path.join(folder, r_file) if r_file is not None else latest_path

    # -- make csv_logger
    csv_logger = CSVLogger(log_file,
                           ('%d', 'epoch'),
                           ('%d', 'itr'),
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



src/suncet_train.py [107:137]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    wd = float(args['optimization']['weight_decay'])
    num_epochs = args['optimization']['epochs']
    warmup = args['optimization']['warmup']
    start_lr = args['optimization']['start_lr']
    lr = args['optimization']['lr']
    final_lr = args['optimization']['final_lr']
    mom = args['optimization']['momentum']
    nesterov = args['optimization']['nesterov']

    # -- LOGGING
    folder = args['logging']['folder']
    tag = args['logging']['write_tag']
    # ----------------------------------------------------------------------- #

    # -- init torch distributed backend
    world_size, rank = init_distributed()
    logger.info(f'Initialized (rank/world-size) {rank}/{world_size}')

    # -- log/checkpointing paths
    log_file = os.path.join(folder, f'{tag}_r{rank}.csv')
    save_path = os.path.join(folder, f'{tag}' + '-ep{epoch}.pth.tar')
    latest_path = os.path.join(folder, f'{tag}-latest.pth.tar')
    best_path = os.path.join(folder, f'{tag}' + '-best.pth.tar')
    load_path = None
    if load_model:
        load_path = os.path.join(folder, r_file) if r_file is not None else latest_path

    # -- make csv_logger
    csv_logger = CSVLogger(log_file,
                           ('%d', 'epoch'),
                           ('%d', 'itr'),
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -