caption_gen.py 文件源码

def build_model(self):
        self.model = classmap[FLAGS.model_type](hidden_size=FLAGS.hidden, 
                                    vocab_size=self.vocab_size, 
                                    encoder_in_size=self.data.feats.shape[-1], 
                                    encoder_in_length=self.data.feats.shape[1],
                                    decoder_in_length=self.data.decoder_in.shape[-1] - 1, 
                                    word2vec_weight=self.w2v_W,
                                    embedding_size=FLAGS.embedding_dim,
                                    neg_sample_num=self.sample_num,
                                    start_id=self.vocab_processor._mapping['<BOS>'],
                                    end_id=self.vocab_processor._mapping['<EOS>'],
                                    Bk=FLAGS.K)
        self.global_step = tf.Variable(0, name='global_step', trainable=False)

        self.optimizer = tf.train.RMSPropOptimizer(FLAGS.lr)

        tvars = tf.trainable_variables()

        grads, _ = tf.clip_by_global_norm(tf.gradients(self.model.cost, tvars), 5)

        self.updates = self.optimizer.apply_gradients(
                        zip(grads, tvars), global_step=self.global_step)
        self.saver = tf.train.Saver(tf.global_variables())