optim.py 文件源码

def __call__(self, opt):
        norm = np.sqrt(_sum_sqnorm([p.grad for p in opt.target.params(False)]))
        if norm == 0:
            return
        rate = self.threshold / norm
        if rate < 1:
            for param in opt.target.params(False):
                grad = param.grad
                with cuda.get_device_from_array(grad):
                    grad *= rate