70e4d7fe60a9658bb27b9f5fb67592a1222b2ec3,spotlight/sequence/implicit.py,ImplicitSequenceModel,fit,#ImplicitSequenceModel#Any#Any#,60

Before Change


        

        sequences = interactions.sequences.astype(np.int64)
        targets = interactions.targets.astype(np.int64)

        self._num_items = interactions.num_items

        if self._representation == "pooling":
            self._net = PoolNet(self._num_items,
                                self._embedding_dim,
                                sparse=self._sparse)
        elif self._representation == "cnn":
            self._net = CNNNet(self._num_items,
                               self._embedding_dim,
                               sparse=self._sparse)
        else:
            self._net = LSTMNet(self._num_items,
                                self._embedding_dim,
                                sparse=self._sparse)

        if self._optimizer is None:
            self._optimizer = optim.Adam(
                self._net.parameters(),
                weight_decay=self._l2,
                lr=self._learning_rate
            )

        if self._loss == "pointwise":
            loss_fnc = pointwise_loss
        elif self._loss == "bpr":
            loss_fnc = bpr_loss
        else:
            loss_fnc = hinge_loss

        for epoch_num in range(self._n_iter):

            sequences, targets = shuffle(sequences,
                                         targets,
                                         random_state=self._random_state)

            sequences_tensor = gpu(torch.from_numpy(sequences),
                                   self._use_cuda)
            targets_tensor = gpu(torch.from_numpy(targets),
                                 self._use_cuda)

            epoch_loss = 0.0

            for (batch_sequence,

After Change



                sequence_var = Variable(batch_sequence)

                user_representation, _ = self._net.user_representation(
                    sequence_var
                )
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 7

Instances


Project Name: maciejkula/spotlight
Commit Name: 70e4d7fe60a9658bb27b9f5fb67592a1222b2ec3
Time: 2017-07-06
Author: maciej.kula@gmail.com
File Name: spotlight/sequence/implicit.py
Class Name: ImplicitSequenceModel
Method Name: fit


Project Name: maciejkula/spotlight
Commit Name: aa1eb21d82804500e2357cde21b18bcf6f87825a
Time: 2017-08-02
Author: maciej.kula@gmail.com
File Name: spotlight/factorization/implicit.py
Class Name: ImplicitFactorizationModel
Method Name: predict


Project Name: maciejkula/spotlight
Commit Name: aa1eb21d82804500e2357cde21b18bcf6f87825a
Time: 2017-08-02
Author: maciej.kula@gmail.com
File Name: spotlight/factorization/explicit.py
Class Name: ExplicitFactorizationModel
Method Name: predict