optimizer.py 文件源码

def zero_grad(self):
        if self.grads_and_vars is None:
            self.grads_and_vars = [(
                tf.Variable(tf.zeros_like(var), dtype=tf.float32, trainable=False),
                var) for var in self.var_list]
        return [tf.assign(gv[0], tf.zeros_like(gv[0]))
                for gv in self.grads_and_vars]