def METHOD_NAME(self):
    if inside_re_worker:
        return
    expand_args_fields(BlenderDatasetMapProvider)
    provider = BlenderDatasetMapProvider(
        base_dir="manifold://co3d/tree/nerf_data/nerf_synthetic/lego",
        object_name="lego",
    )
    dataset_map = provider.get_dataset_map()
    known_matrix = torch.zeros(1, 4, 4)
    known_matrix[0, 0, 0] = 2.7778
    known_matrix[0, 1, 1] = 2.7778
    known_matrix[0, 2, 3] = 1
    known_matrix[0, 3, 2] = 1
    for name, length in [("train", 100), ("val", 100), ("test", 200)]:
        dataset = getattr(dataset_map, name)
        self.assertEqual(len(dataset), length)
        # try getting a value
        value = dataset[0]
        self.assertEqual(value.image_rgb.shape, (3, 800, 800))
        self.assertEqual(value.fg_probability.shape, (1, 800, 800))
        # corner of image is background
        self.assertEqual(value.fg_probability[0, 0, 0], 0)
        self.assertEqual(value.fg_probability.max(), 1.0)
        self.assertIsInstance(value.camera, PerspectiveCameras)
        self.assertEqual(len(value.camera), 1)
        self.assertIsNone(value.camera.K)
        matrix = value.camera.get_projection_transform().get_matrix()
        self.assertClose(matrix, known_matrix, atol=1e-4)
        self.assertIsInstance(value, FrameData)