def METHOD_NAME(self):
    dataset = load(self.test_data_path)
    dataset = dataset.map(
        lambda x: (
            transformer.pad_or_trim_tensors(
                transformer.transform_to_vehicle_frame(x)
            )
        )
    )
    example = next(iter(dataset))
    # Laser points.
    self.assertEqual(example["point_xyz"].shape, [199600, 3])
    self.assertEqual(example["point_feature"].shape, [199600, 4])
    self.assertEqual(example["point_mask"].shape, [199600])
    point_xyz_mean = tf.reduce_mean(example["point_xyz"], axis=0)
    self.assertAllClose(point_xyz_mean, example["pose"][:3, 3], atol=100)
    point_feature_mean = tf.reduce_mean(example["point_feature"], axis=0)
    self.assertAllGreater(point_feature_mean[0], 0)
    self.assertAllGreater(tf.abs(point_feature_mean[1]), 1e-6)
    self.assertAllGreater(point_feature_mean[2:4], 0)
    self.assertTrue(tf.math.reduce_any(example["point_mask"]))
    # Laser labels.
    self.assertEqual(example["label_box_id"].shape[0], 1000)
    self.assertEqual(example["label_box_meta"].shape[0], 1000)
    self.assertEqual(example["label_box_class"].shape[0], 1000)
    self.assertEqual(example["label_box_density"].shape[0], 1000)
    self.assertEqual(example["label_box_mask"].shape, [1000])
    self.assertTrue(tf.math.reduce_any(example["label_box_mask"]))
    self.assertAllGreater(
        tf.math.reduce_max(example["label_point_class"]), 0
    )