为什么简单的数据框不能与Numba中的CUDA目标一起使用？

如何解决为什么简单的数据框不能与Numba中的CUDA目标一起使用？

我正在尝试使用Numba jit在dask数据帧上的GPU上运行。 代码如下。

@jit(target='cuda')
def return_with_trip_times(month):
    duration = month[['tpep_pickup_datetime','tpep_dropoff_datetime']].compute()
    #pickups and dropoffs to unix time
    duration_pickup = [convert_to_unix(x) for x in duration['tpep_pickup_datetime'].values]
    duration_drop = [convert_to_unix(x) for x in duration['tpep_dropoff_datetime'].values]
    #calculate duration of trips
    durations = (np.array(duration_drop) - np.array(duration_pickup))/float(60) #durations is in minutes

    #append durations of trips and speed in miles/hr to a new dataframe
    new_frame = month[['passenger_count','trip_distance','pickup_longitude','pickup_latitude','dropoff_longitude','dropoff_latitude','total_amount']].compute()
    
    new_frame['trip_times'] = durations
    new_frame['pickup_times'] = duration_pickup
    new_frame['Speed'] = 60*(new_frame['trip_distance']/new_frame['trip_times']) #60 multiplied to convert mins to hrs
    #speed is in miles/hr
    
    return new_frame

我收到以下错误。

ValueError: cannot determine Numba type of <class 'pandas.core.frame.DataFrame'>

我检查了numba（jit）的文档，并在其中写明dask数据框可用于numba。请帮忙。