keras_models.py 文件源码

def build(self):
        subject = self.subject
        relation = self.relation
        object_ = self.get_object()
        embedding_size = self.model_params.get('n_embed_dims', 100)

        # add embedding layers
        embedding_rel = Embedding(input_dim=self.config['n_words'],
                                  output_dim=self.model_params.get('n_embed_dims', 100),
                                  init='he_uniform',
                                  mask_zero=False)
        embedding_ent = Embedding(input_dim=self.config['n_words'],
                                  output_dim=self.model_params.get('n_embed_dims', 100),
                                  init='he_uniform',
                                  W_constraint=unitnorm(axis=1),
                                  mask_zero=False)
        subject_embedding = embedding_ent(subject)
        relation_embedding = embedding_rel(relation)
        object_embedding = embedding_ent(object_)

        subject_output = Reshape((embedding_size,))(subject_embedding)
        relation_output = Reshape((embedding_size,))(relation_embedding)
        object_output = Reshape((embedding_size,))(object_embedding)

        return subject_output, relation_output, object_output