def train()

in floresv1/scripts/train.py [0:0]

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

def train(src, tgt, train_config, savedir, databin):
    # expect to have 'hyperparameters', 'src', 'tgt', 'databin' in train_config
    os.makedirs(savedir, exist_ok=True)

    logpath = os.path.join(savedir, 'train.log')
    checkpoint = os.path.join(savedir, 'checkpoint_best.pt')

    if check_last_line(logpath, 'done') and os.path.exists(checkpoint):
        print(f"Training is finished. Best checkpoint: {checkpoint}")
        return

    cuda_visible_devices = list(range(torch.cuda.device_count()))
    num_visible_gpu = len(cuda_visible_devices)
    num_gpu = min(train_config['gpu'], 2**int(math.log2(num_visible_gpu)))
    cuda_devices_clause = f"CUDA_VISIBLE_DEVICES={','.join([str(i) for i in cuda_visible_devices[:num_gpu]])}"
    update_freq = train_config['gpu'] / num_gpu
    call(f"""{cuda_devices_clause} fairseq-train {databin} \