Numba 与 numpy.random.binomial 的兼容性

如何解决Numba 与 numpy.random.binomial 的兼容性

我试图使用 numba 来加速我的代码的一部分，该部分根据成功概率数组生成伯努利随机变量数组。大致如下：

import numpy as np
from numba import njit

@njit
def Bernoulli(a,b,c):
    prob = np.array from some calculation to a,b and c
    accepted = np.random.binomial(1,prob)
    return accepted

Bernoulli(a,c)

但是，出现这个错误代码：

There are 2 candidate implementations:
  - Of which 2 did not match due to:
  Overload in function 'Numpy_negative_binomial.generic': File: numba\core\typing\randomdecl.py: Line 171.
    With argument(s): '(int64,array(float64,1d,C))':
   No match for registered cases:
    * (int64,float64) -> int64

我理解这是因为当前的 numba 实现不支持成功概率数组作为 np.random.binomial 的参数。这样对吗？
如果是这样，此实现是否是解决问题的有效方法？

@njit(parallel = True)
def Bernoulli(a,b and c
    accepted = np.zeros(N)
    for i in prange(N):
        accepted[i] = np.random.binomial(1,prob[i])
    return accepted