def METHOD_NAME(device):
    if torch.cuda.is_available():
        coco_train_gpu = coco_torch.load_dataset(train=True, object_type='VisionData', n_samples=200, device=device,
                                                 pin_memory=False)
        coco_test_gpu = coco_torch.load_dataset(train=False, object_type='VisionData', n_samples=200, device=device,
                                                pin_memory=False)
        suite = full_suite(imaginery_kwarg='just to make sure all checks have kwargs in the init')
        arguments = (dict(train_dataset=coco_train_gpu, test_dataset=coco_test_gpu),)
        for args in arguments:
            result = suite.run(**args)
            length = get_expected_results_length(suite, args)
            validate_suite_result(result, length)