fde2f66676f960782c993f7148927c4a4197ab10,spotlight/factorization/explicit.py,ExplicitFactorizationModel,fit,#ExplicitFactorizationModel#,85

Before Change

        for epoch_num in range(self._n_iter):

            users, items, ratings = shuffle(*(interactions.row,
                                              interactions.col,
                                              interactions.data))

            user_ids_tensor = gpu(torch.from_numpy(users),
                                  self._use_cuda)

After Change

                predictions = self._net(user_var, item_var)

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

                self._optimizer.zero_grad()

                loss = loss_fnc(ratings_var, predictions)

Instances