为什么numba推断类型错误？

Question

用于计算两组矢量之间的距离矩阵的简单函数，如

import numpy as np
from numba import jit

@jit(signature_or_function='(f8[:,:], f8[:,:])',  nopython=True, cache=True, locals={'d': numba.float64[:]})
def foo(prototypes, features):
    protonum   = prototypes.shape[0]
    featurenum = features.shape[0]
    dismatrix = np.zeros(shape=(featurenum, protonum), dtype=np.double)
    for i in range(featurenum):
        feature = features[i,:]
        tmp = (prototypes - feature)**2
        d = np.sqrt(tmp.sum(axis=1))   # (nproto, 1)
        dismatrix[i,:] = d
        idx = d.argmin()
    return dismatrix

输入参数＆＃39;原型＆＃39;是ndarray形状（质子，暗），＆＃39;功能＆＃39;是ndarray形状（featurenum，昏暗）。如果＆nbspthon＆＃39; nopython＆＃39;设置为False，但如果＆nbspthon＆＃39; nopython＆＃39;设置为True。错误消息是

numba.errors.TypingError: Failed at nopython (nopython frontend)
No conversion from float64 to array(float64, 1d, A) for 'd'

似乎numba推断出＆＃39; d＆＃39;错误的是＆＃39; float64＆＃39;而不是float64数组，即使由＆＃39; locals = {＆＃39; d＆＃39;：numba.float64 [：]}＆＃39;明确指定。我有什么地方做错了吗？

Numba版本= 0.23.1，Python 3.5。