qacnn.py 文件源码

def add_hl(self, q_embed, aplus_embed, aminus_embed):
        with tf.variable_scope('HL'):
            W = tf.get_variable('weights', shape=[self.config.embedding_size, self.config.hidden_size], initializer=tf.uniform_unit_scaling_initializer())
            b = tf.get_variable('biases', initializer=tf.constant(0.1, shape=[self.config.hidden_size]))
            h_q = tf.reshape(tf.nn.tanh(tf.matmul(tf.reshape(q_embed, [-1, self.config.embedding_size]), W)+b), [-1, self.config.sequence_length, self.config.hidden_size])
            h_ap = tf.reshape(tf.nn.tanh(tf.matmul(tf.reshape(aplus_embed, [-1, self.config.embedding_size]), W)+b), [-1, self.config.sequence_length, self.config.hidden_size])
            h_am = tf.reshape(tf.nn.tanh(tf.matmul(tf.reshape(aminus_embed, [-1, self.config.embedding_size]), W)+b), [-1, self.config.sequence_length, self.config.hidden_size])
            tf.add_to_collection('total_loss', 0.5*self.config.l2_reg_lambda*tf.nn.l2_loss(W))
            return h_q, h_ap, h_am

    # CNN?