Function benchmark_eval

tools/benchmark.py:123–150

(args)

@torch.no_grad()
def benchmark_eval(args):
    cfg = setup(args)
    model = build_model(cfg)
    model.eval()
    logger.info("Model:\n{}".format(model))
    DetectionCheckpointer(model).load(cfg.MODEL.WEIGHTS)

    cfg.defrost()
    cfg.DATALOADER.NUM_WORKERS = 0
    data_loader = build_detection_test_loader(cfg, cfg.DATASETS.TEST[0])
    dummy_data = list(itertools.islice(data_loader, 100))

    def f():
        while True:
            yield from DatasetFromList(dummy_data, copy=False)

    for _ in range(5):  # warmup
        model(dummy_data[0])

    max_iter = 400
    timer = Timer()
    with tqdm.tqdm(total=max_iter) as pbar:
        for idx, d in enumerate(f()):
            if idx == max_iter:
                break
            model(d)
            pbar.update()
    logger.info("{} iters in {} seconds.".format(max_iter, timer.seconds()))


if __name__ == "__main__":