07401c8b51d38790f8f40161a7355288b63a7805,paysage/optimizers.py,RMSProp,update,#RMSProp#Any#Any#Any#Any#,77

Before Change

        for key in self.grad:
            self.mean_square_grad[key] = self.mean_square_weight * self.mean_square_grad[key] + (1-self.mean_square_weight)*self.grad[key]**2
            model.params[key] = model.params[key] - self.stepsize * self.grad[key] / numpy.sqrt(self.epsilon + self.mean_square_grad[key])
        model.enforce_weight_decay(lr)        
        model.enforce_constraints()

After Change

    
    def update(self, model, v_data, v_model, epoch):
        self.grad = gradient(model, v_data, v_model)
        if model.weight_decay:
            self.grad["weights"] += model.weight_decay.grad(model.params["weights"])
        for key in self.grad:
            self.mean_square_grad[key] = self.mean_square_weight * self.mean_square_grad[key] + (1-self.mean_square_weight)*self.grad[key]**2
            model.params[key] = model.params[key] - self.stepsize * self.grad[key] / numpy.sqrt(self.epsilon + self.mean_square_grad[key])
        model.enforce_constraints()

Instances