def METHOD_NAME(self, config, devices):
    config_file = get_config_file(config)
    img = osp.join(get_repo_dir(), 'tests/data/coco/000000000785.jpg')
    for device in devices:
        if device == 'cuda' and not torch.cuda.is_available():
            # Skip the test if cuda is required but unavailable
            continue
        model = init_model(config_file, device=device)
        # test inference from image
        results = inference_bottomup(model, img=imread(img))
        self.assertTrue(is_list_of(results, PoseDataSample))
        self.assertEqual(len(results), 1)
        self.assertTrue(results[0].pred_instances.keypoints.shape,
                        (1, 17, 2))
        # test inference from file
        results = inference_bottomup(model, img=img)
        self.assertTrue(is_list_of(results, PoseDataSample))
        self.assertEqual(len(results), 1)
        self.assertTrue(results[0].pred_instances.keypoints.shape,
                        (1, 17, 2))