def METHOD_NAME(self, sharding_type: str) -> None:
    world_size = 2
    backend = "nccl"
    table_name = "free_parameters"
    # Initialize embedding bag on non-meta device, in this case cuda:0
    embedding_tables = EmbeddingBagCollection(
        device=torch.device("cuda:0"),
        tables=[
            EmbeddingBagConfig(
                name=table_name,
                embedding_dim=64,
                num_embeddings=10,
                data_type=DataType.FP32,
            )
        ],
    )
    embedding_tables.load_state_dict(
        {f"embedding_bags.{table_name}.weight": torch.randn(10, 64)}
    )
    self._run_multi_process_test(
        callable=initialize_and_test_parameters,
        embedding_tables=embedding_tables,
        sharding_type=sharding_type,
        sharders=[
            cast(ModuleSharder[torch.nn.Module], EmbeddingBagCollectionSharder())
        ],
        world_size=world_size,
        backend=backend,
        table_name=table_name,
    )