def get_updates(self, params, cost):
        updates = []
        grads = T.grad(cost, params)
        grads = clip_norms(grads, self.clipnorm)
        for p,g in zip(params,grads):
            g = self.regularizer.gradient_regularize(p, g)
            acc = theano.shared(p.get_value() * 0.)
            acc_t = acc + g ** 2
            updates.append((acc, acc_t))

            p_t = p - (self.lr / T.sqrt(acc_t + self.epsilon)) * g
            p_t = self.regularizer.weight_regularize(p_t)
            updates.append((p, p_t))
        return updates
dataset/ETHPy150Open IndicoDataSolutions/Passage/passage/updates.py/Adagrad.get_updates/original