tf_tree_lstm.py 文件源码

def process_leafs(self,emb):

        with tf.variable_scope("Composition",reuse=True):
            cUW = tf.get_variable("cUW")
            cb = tf.get_variable("cb")
            U = tf.slice(cUW,[0,0],[self.emb_dim,2*self.hidden_dim])
            b = tf.slice(cb,[0],[2*self.hidden_dim])
            def _recurseleaf(x):

                concat_uo = tf.matmul(tf.expand_dims(x,0),U) + b
                u,o = tf.split(1,2,concat_uo)
                o=tf.nn.sigmoid(o)
                u=tf.nn.tanh(u)

                c = u#tf.squeeze(u)
                h = o * tf.nn.tanh(c)


                hc = tf.concat(1,[h,c])
                hc=tf.squeeze(hc)
                return hc

            hc = tf.map_fn(_recurseleaf,emb)
            return hc