如何在简单的python函数中使用numba njit？

Question

我创建了一个简单的函数，即取一个矢量并将结果乘以几个矩阵，其中k只是B和C的长度。一直发生的是该函数给出了错误：

Invalid use of Function(<built-in function dot>) with argument(s) of type(s):
(reflected list(reflected list(float64)), array(float64, 2d, C))
 * parameterized
In definition 0:
    All templates rejected with literals.
In definition 1:
    All templates rejected without literals.

...

def calc(A,k, B, C):
<source elided>
x2 = C[i]
c = np.dot(b,x1)
^

我确保将功能拆分为易于遵循的方法：

@njit(fastmath = True)
def calc(A,k,B,C):
    b = A
    for i in range(k):
        x1 = B[i]
        x2 = C[i]
        c = np.dot(b,x1)
        D = c + x2
        c = np.tanh(D)
        b = c
    return b

是否有解决此问题的好方法？如果是这样，正确的方法是什么？