guidedbackprop.py 文件源码

def __init__(self, model, stdev_spread=.15, n_samples=25, magnitude=True):
        super(GuidedBackpropSmoothGrad, self).__init__(
            model, stdev_spread, n_samples, magnitude)
        for key, funcs in model.predictor.functions.items():
            ismatch = re.match(self.pattern, key)
            if ismatch:
                funcs[-1] = GuidedBackpropReLU()