def METHOD_NAME(m: int, n: Optional[int] = None, t: int = 4,
                        multiplier: float = 3,
                        cls: None = None,
                        subgraph: GraphLike = None,
                        seed: Union[None, int] = None,
                        ) -> BinaryQuadraticModel:
    """Generate an anticluster problem on a Chimera lattice.
    An anticluster problem has weak interactions within a tile and strong
    interactions between tiles.
    Args:
        m: Number of rows in the Chimera lattice.
        n: Number of columns in the Chimera lattice. Defaults to ``m``.
        t: Size of the shore within each Chimera tile.
        multiplier: Strength of the inter-tile edges.
        cls: Deprecated. Does nothing.
        subgraph: A subgraph of the specified Chimera(m, n, t) graph to build the
            anticluster problem on. Can be used to remove nodes and edges.
        seed: Random seed.
    Returns:
        A binary quadratic model.
    .. deprecated:: 0.10.6
        The ``cls`` keyword argument will be removed in 0.12.0.
        It currently does nothing.
    """
    if cls is not None:
        warnings.warn("cls keyword argument is deprecated after 0.10.6 and will "
                      "be removed in 0.11. Does nothing.", DeprecationWarning,
                      stacklevel=2)
    if seed is None:
        seed = numpy.random.randint(2**32, dtype=np.uint32)
    r = numpy.random.RandomState(seed)
    m = int(m)
    if n is None:
        n = m
    else:
        n = int(n)
    t = int(t)
    ldata = np.zeros(m*n*t*2)  # number of nodes
    if m and n and t:
        inrow, incol = zip(*_iter_chimera_tile_edges(m, n, t))
        if m > 1 or n > 1:
            outrow, outcol = zip(*_iter_chimera_intertile_edges(m, n, t))
        else:
            outrow = outcol = tuple()
        qdata = r.choice((-1., 1.), size=len(inrow)+len(outrow))
        qdata[len(inrow):] *= multiplier
        irow = inrow + outrow
        icol = incol + outcol
    else:
        irow = icol = qdata = tuple()
    bqm = BinaryQuadraticModel.from_numpy_vectors(ldata, (irow, icol, qdata), 0.0, SPIN)
    if subgraph is not None:
        nodes, edges = subgraph
        subbqm = BinaryQuadraticModel.empty(SPIN)
        try:
            subbqm.add_variables_from((v, bqm.linear[v]) for v in nodes)
        except KeyError:
            msg = "given 'subgraph' contains nodes not in Chimera({}, {}, {})".format(m, n, t)
            raise ValueError(msg)
        try:
            subbqm.add_interactions_from((u, v, bqm.adj[u][v]) for u, v in edges)
        except KeyError:
            msg = "given 'subgraph' contains edges not in Chimera({}, {}, {})".format(m, n, t)
            raise ValueError(msg)
        bqm = subbqm
    return bqm