classifiers.py 文件源码

def forward(self, source_sentences, target_sentences):
        """
        Supervised Learning of Universal Sentence Representations from Natural Language Inference Data
        https://arxiv.org/abs/1705.02364

        A Siamese text classification network made w/ the goal of creating sentence embeddings.

        :param source_sentences:  A tuple of Variable's representing padded sentence tensor batch
            [seq. length, batch size, embed. size] and sentence lengths.
        :param target_sentences:  A tuple of Variable's representing padded sentence tensor batch
            [seq. length, batch size, embed. size] and sentence lengths.
        :return: Embedding. (batch size, # classes)
        """

        u = self.encoder(source_sentences)
        v = self.encoder(target_sentences)

        features = torch.cat((u, v, torch.abs(u - v), u * v), 1)
        return self.classifier(features)