def benchmark_data_loading()

in slowfast/utils/benchmark.py [0:0]

• 68 lines of code
• 7 McCabe index (conditional complexity)

def benchmark_data_loading(cfg):
    """
    Benchmark the speed of data loading in PySlowFast.
    Args:

        cfg (CfgNode): configs. Details can be found in
            slowfast/config/defaults.py
    """
    # Set up environment.
    setup_environment()
    # Set random seed from configs.
    np.random.seed(cfg.RNG_SEED)
    torch.manual_seed(cfg.RNG_SEED)

    # Setup logging format.
    logging.setup_logging(cfg.OUTPUT_DIR)

    # Print config.
    logger.info("Benchmark data loading with config:")
    logger.info(pprint.pformat(cfg))

    timer = Timer()
    dataloader = loader.construct_loader(cfg, "train")
    logger.info(
        "Initialize loader using {:.2f} seconds.".format(timer.seconds())
    )
    # Total batch size across different machines.
    batch_size = cfg.TRAIN.BATCH_SIZE * cfg.NUM_SHARDS
    log_period = cfg.BENCHMARK.LOG_PERIOD
    epoch_times = []
    # Test for a few epochs.
    for cur_epoch in range(cfg.BENCHMARK.NUM_EPOCHS):
        timer = Timer()
        timer_epoch = Timer()
        iter_times = []
        if cfg.BENCHMARK.SHUFFLE:
            loader.shuffle_dataset(dataloader, cur_epoch)
        for cur_iter, _ in enumerate(tqdm.tqdm(dataloader)):
            if cur_iter > 0 and cur_iter % log_period == 0:
                iter_times.append(timer.seconds())
                ram_usage, ram_total = misc.cpu_mem_usage()
                logger.info(
                    "Epoch {}: {} iters ({} videos) in {:.2f} seconds. "
                    "RAM Usage: {:.2f}/{:.2f} GB.".format(
                        cur_epoch,
                        log_period,
                        log_period * batch_size,
                        iter_times[-1],
                        ram_usage,
                        ram_total,
                    )
                )
                timer.reset()
        epoch_times.append(timer_epoch.seconds())
        ram_usage, ram_total = misc.cpu_mem_usage()
        logger.info(
            "Epoch {}: in total {} iters ({} videos) in {:.2f} seconds. "
            "RAM Usage: {:.2f}/{:.2f} GB.".format(
                cur_epoch,
                len(dataloader),
                len(dataloader) * batch_size,
                epoch_times[-1],
                ram_usage,
                ram_total,
            )
        )
        logger.info(
            "Epoch {}: on average every {} iters ({} videos) take {:.2f}/{:.2f} "
            "(avg/std) seconds.".format(
                cur_epoch,
                log_period,
                log_period * batch_size,
                np.mean(iter_times),
                np.std(iter_times),
            )
        )
    logger.info(
        "On average every epoch ({} videos) takes {:.2f}/{:.2f} "
        "(avg/std) seconds.".format(
            len(dataloader) * batch_size,
            np.mean(epoch_times),
            np.std(epoch_times),
        )
    )