0ad33d606682537466f3430fc6d6ac7d47460f1a,intermediate_source/spatial_transformer_tutorial.py,,,#,146

Before Change

        return F.log_softmax(x, dim=1)


model = Net()
if use_cuda:
    model.cuda()

////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// Training the model
// ------------------
//
// Now, let"s use the SGD algorithm to train the model. The network is
// learning the classification task in a supervised way. In the same time
// the model is learning STN automatically in an end-to-end fashion.


optimizer = optim.SGD(model.parameters(), lr=0.01)


def train(epoch):

After Change

        return F.log_softmax(x, dim=1)


model = Net().to(device)

////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// Training the model
// ------------------
//
// Now, let"s use the SGD algorithm to train the model. The network is
// learning the classification task in a supervised way. In the same time
// the model is learning STN automatically in an end-to-end fashion.


optimizer = optim.SGD(model.parameters(), lr=0.01)


def train(epoch):

Instances