def METHOD_NAME(
    self,
    sharding_type: str,
) -> None:
    self.fail("fix test or remove - Test is currently deadlocking and breaking CI")
    ebc = EmbeddingBagCollection(
        tables=[
            EmbeddingBagConfig(
                name="table_0",
                feature_names=["feature_0", "feature_1"],
                embedding_dim=8,
                num_embeddings=10,
            )
        ],
    )
    fused_ebc = fuse_embedding_optimizer(
        ebc,
        optimizer_type=torch.optim.SGD,
        optimizer_kwargs={"lr": 0.02},
        device=torch.device("cuda"),
    )
    #             instance 0   instance 1  instance 2
    # "feature_0"   [0, 1]       None        [2]
    # "feature_1"   [3]          [4]         [5,6,7]
    #
    kjt_input = KeyedJaggedTensor.from_lengths_sync(
        keys=["feature_0", "feature_1"],
        values=torch.LongTensor([0, 1, 2, 3, 4, 5, 6, 7]),
        lengths=torch.LongTensor([2, 0, 1, 1, 1, 3]),
    )
    self._run_multi_process_test(
        callable=sharding_single_rank,
        world_size=2,
        unsharded_model=fused_ebc,
        kjt_input=kjt_input,
        sharders=[TestFusedEBCSharder(sharding_type=sharding_type)],
        backend="nccl",
    )