having trouble with fused types and ndarray of arbitrary dimensions

I would like to write a function using ndarrarys of fused types.  The
only restriction I would like on the input arrays is that they be
broadcastable.

My first attempt was:
    ctypedef fused fused1:
        np.int32_t
        np.int64_t

    ctypedef fused fused2:
        np.int32_t
        np.int64_t
        np.float64_t
        np.float32_t

    def labeled_reduce(np.ndarray[fused1] labels, np.ndarray[fused2]
values, ops)
       print "called with", labels.dtype, values.dtype, ops

But that requires that labels and values be 1D.

I ended up writing it like this:
    def _labeled_reduce(np.ndarray labels, np.ndarray values, fused1
labelexample, fused2 valueexample, ops=0):
       print "called with", labels.dtype, values.dtype, ops

    def labeled_reduce(np.ndarray labels, np.ndarray values, ops):
       typemap = {np.float32 : 'float32_t',
                  np.float64 : 'float64_t',
                  np.int32   : 'int32_t',