be426ba9d5f569b5eab685d96bb418d11fbb5474,spotlight/factorization/explicit.py,ExplicitFactorizationModel,fit,#ExplicitFactorizationModel#Any#Any#,175

Before Change

                                                         batch_size=self._batch_size)):

                user_var = Variable(batch_user)
                item_var = Variable(batch_item)
                ratings_var = Variable(batch_ratings)

                predictions = self._net(user_var, item_var)

                if self._loss == "poisson":
                    predictions = torch.exp(predictions)

                self._optimizer.zero_grad()

                loss = self._loss_func(ratings_var, predictions)
                epoch_loss += loss.data[0]

                loss.backward()
                self._optimizer.step()

After Change

                self._optimizer.zero_grad()

                loss = self._loss_func(batch_ratings, predictions)
                epoch_loss += loss.item()

                loss.backward()
                self._optimizer.step()

Instances