Python,与joblib并行化:多参数延迟

from joblib import Parallel, delayed
import numpy

def processInput(i,j):
    for k in range(len(i)):
        i[k] = 1
    for t in range(len(b)):
        j[t] = 0
return i,j

a = numpy.eye(3)
b = numpy.eye(3)

num_cores = 2
(a,b) = Parallel(n_jobs=num_cores)(delayed(processInput)(i,j) for i,j in zip(a,b))

但我得到了以下错误:太多值无法解包(预期为2)

还有一点,有没有一种更紧凑的方法来处理矩阵,比如下面的方法(实际上不会修改任何东西)?

from joblib import Parallel, delayed
def processInput(i,j):
    for k in i:
        k = 1
    for t in b:
        t = 0
return i,j

无论如何,我希望避免使用has_shareable_memory,以避免实际脚本中可能出现的不良交互和较低的性能(?)