def METHOD_NAME(
    self,
    sharders: List[TestEmbeddingCollectionSharder],
    backend: str = "gloo",
    world_size: int = 2,
    local_size: Optional[int] = None,
    model_class: Type[TestSparseNNBase] = TestSequenceSparseNN,
    apply_optimizer_in_backward_config: Optional[
        Dict[str, Tuple[Type[torch.optim.Optimizer], Dict[str, Any]]]
    ] = None,
) -> None:
    self._run_multi_process_test(
        callable=sharding_single_rank_test,
        world_size=world_size,
        local_size=local_size,
        model_class=model_class,
        tables=self.tables,
        embedding_groups=self.embedding_groups,
        sharders=sharders,
        optim=EmbOptimType.EXACT_SGD,
        backend=backend,
        apply_optimizer_in_backward_config=apply_optimizer_in_backward_config,
    )