level2_model.py 文件源码

def build_inference(self):
        embed = self.embedding
        context = self.context
        hidden = self.hidden
        features = self._cnn_encoding(embedding=embed, context=context, hidden=hidden)
        c = tf.zeros([tf.shape(self.context)[0], self.H])
        h = tf.zeros([tf.shape(self.context)[0], self.H])
        (self.init_c, self.init_h) = self._lstm(h, c, features, reuse=False)
        _ = self._decode_lstm(self.init_h)
        _ = self._word_embedding(inputs=tf.fill([tf.shape(features)[0]], self._start))

        self.in_word = tf.placeholder(tf.int32, [None])
        x = self._word_embedding(inputs=self.in_word, reuse=True)

        self.c_feed = tf.placeholder(tf.float32, [None, self.H])
        self.h_feed = tf.placeholder(tf.float32, [None, self.H])
        (self.c, self.h) = self._lstm(self.h_feed, self.c_feed, x, reuse=True)
        self.log_softmax = self._decode_lstm(self.h, reuse=True)