Return a new handle with specified storage type, shape, dtype and context.

    Empty handle is only used to hold results

    Returns
    -------
    handle
        A new empty ndarray handle

def _new_alloc_handle(stype, shape, ctx, delay_alloc, dtype, aux_types, aux_shapes=None):
    """Return a new handle with specified storage type, shape, dtype and context.

    Empty handle is only used to hold results

    Returns
    -------
    handle
        A new empty ndarray handle
    """
    hdl = NDArrayHandle()
    for aux_t in aux_types:
        if np.dtype(aux_t) != np.dtype("int64"):
            raise NotImplementedError("only int64 is supported for aux types")
    aux_type_ids = [int(_DTYPE_NP_TO_MX[np.dtype(aux_t).type]) for aux_t in aux_types]
    aux_shapes = [(0,) for aux_t in aux_types] if aux_shapes is None else aux_shapes
    aux_shape_lens = [len(aux_shape) for aux_shape in aux_shapes]
    aux_shapes = py_sum(aux_shapes, ())
    num_aux = mx_uint(len(aux_types))
    check_call(_LIB.MXNDArrayCreateSparseEx(
        ctypes.c_int(int(_STORAGE_TYPE_STR_TO_ID[stype])),
        c_array_buf(mx_uint, native_array('I', shape)),
        mx_uint(len(shape)),
        ctypes.c_int(ctx.device_typeid),
        ctypes.c_int(ctx.device_id),
        ctypes.c_int(int(delay_alloc)),
        ctypes.c_int(int(_DTYPE_NP_TO_MX[np.dtype(dtype).type])),
        num_aux,
        c_array_buf(ctypes.c_int, native_array('i', aux_type_ids)),
        c_array_buf(mx_uint, native_array('I', aux_shape_lens)),
        c_array_buf(mx_uint, native_array('I', aux_shapes)),
        ctypes.byref(hdl)))
    return hdl