encoder.py 文件源码

def apply(self, source_sentence, source_sentence_mask):
        """Produces source annotations, either non-recurrently or with
        a bidirectional RNN architecture.
        """
        # Time as first dimension
        source_sentence = source_sentence.T
        source_sentence_mask = source_sentence_mask.T
        embeddings = self.lookup.apply(source_sentence)
        representation = self.bidirs[0].apply(
                merge(self.fwd_forks[0].apply(embeddings, as_dict=True),
                      {'mask': source_sentence_mask}),
                merge(self.back_forks[0].apply(embeddings, as_dict=True),
                      {'mask': source_sentence_mask}))
        for i in xrange(1, self.n_layers):
            if self.skip_connections:
                inp = tensor.concatenate([representation, embeddings],
                                         axis=2)
            else:
                inp = representation
            representation = self.bidirs[i].apply(
                merge(self.fwd_forks[i].apply(inp, as_dict=True),
                      {'mask': source_sentence_mask}),
                merge(self.back_forks[i].apply(inp, as_dict=True),
                      {'mask': source_sentence_mask})
            )
        return representation, source_sentence_mask