context_encoding.py 文件源码

def process_leafs(self,emb):
        #emb: [num_leaves, emd_dim]    
        with tf.variable_scope("btp_Composition",reuse=True):
            cU = tf.get_variable("cU",[self.emb_dim,2*self.hidden_dim])
            cb = tf.get_variable("cb",[4*self.hidden_dim])
            b = tf.slice(cb,[0],[2*self.hidden_dim])
            #??????input gate?forget gate,????output gate ?Input value
            def _recurseleaf(x):
                #[1, emb_dim], [emb_dim, 2*self.hidden_dim]
                concat_uo = tf.matmul(tf.expand_dims(x,0),cU) + b
                #?concat_uo???
                #[1*hidden_dim] [1*hidden_dim]
                u,o = tf.split(axis=1,num_or_size_splits=2,value=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(axis=1,values=[h,c])
                hc=tf.squeeze(hc)
                return hc
        hc = tf.map_fn(_recurseleaf,emb)
        #hc [num_leaves, 2*hidden_dim]
        return hc