encoders.py 文件源码

def _get_embedding_layer(self, embedding_file=None):
        if self.embedding_layer is None:
            if embedding_file is None:
                if not self.tune_embedding:
                    print >>sys.stderr, "Pretrained embedding is not given. Setting tune_embedding to True."
                    self.tune_embedding = True
                embedding = None
            else:
                # Put the embedding in a list for Keras to treat it as initiali weights of the embedding
                # layer.
                embedding = [self.data_processor.get_embedding_matrix(embedding_file, onto_aware=False)]
            vocab_size = self.data_processor.get_vocab_size(onto_aware=False)
            self.embedding_layer = Embedding(input_dim=vocab_size, output_dim=self.embed_dim,
                                             weights=embedding, trainable=self.tune_embedding,
                                             mask_zero=True, name="embedding")
        return self.embedding_layer