grad_norm_exmple.py

# 梯度裁剪
# https://github.com/tensorflow/models/blob/56cbd1f2770f1e7386db43af37f6f11b4d85e3da/tutorials/rnn/ptb/ptb_word_lm.py#L159-L165
tvars = tf.trainable_variables()
grads, _ = tf.clip_by_global_norm(tf.gradients(self._cost, tvars),
                                  config.max_grad_norm)
optimizer = tf.train.GradientDescentOptimizer(self._lr)
self._train_op = optimizer.apply_gradients(
    zip(grads, tvars),
    global_step=tf.train.get_or_create_global_step())