70e4d7fe60a9658bb27b9f5fb67592a1222b2ec3,spotlight/sequence/representations.py,LSTMNet,user_representation,#LSTMNet#Any#,70

Before Change

    def user_representation(self, item_sequences):

        sequence_embeddings = self.item_embeddings(item_sequences)

        user_representations, (hidden, cell) = self.lstm(sequence_embeddings)

        return hidden.view(-1, self.embedding_dim)

After Change

    def user_representation(self, item_sequences):

        // Make the embedding dimension the channel dimension
        sequence_embeddings = (self.item_embeddings(item_sequences)
                               .permute(0, 2, 1))
        // Add a trailing dimension of 1
        sequence_embeddings = (sequence_embeddings
                               .unsqueeze(3))
        // Pad it with zeros from left
        sequence_embeddings = (F.pad(sequence_embeddings,
                                     (0, 0, 1, 0))
                               .squeeze(3))
        sequence_embeddings = sequence_embeddings.permute(0, 2, 1)

        user_representations, _ = self.lstm(sequence_embeddings)
        user_representations = user_representations.permute(0, 2, 1)

Instances