test_net.py 文件源码

def test_changing_model_reinitializes_optimizer(self, net, data):
        # The idea is that we change the model using `set_params` to
        # add parameters. Since the optimizer depends on the model
        # parameters it needs to be reinitialized.
        X, y = data

        net.set_params(module__nonlin=F.relu)
        net.fit(X, y)

        net.set_params(module__nonlin=nn.PReLU())
        assert isinstance(net.module_.nonlin, nn.PReLU)
        d1 = net.module_.nonlin.weight.data.clone().cpu().numpy()

        # make sure that we do not initialize again by making sure that
        # the network is initialized and by using partial_fit.
        assert net.initialized_
        net.partial_fit(X, y)
        d2 = net.module_.nonlin.weight.data.clone().cpu().numpy()

        # all newly introduced parameters should have been trained (changed)
        # by the optimizer after 10 epochs.
        assert (abs(d2 - d1) > 1e-05).all()