本文介绍了如何将学习率添加到摘要中?的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
限时送ChatGPT账号..如何监控 AdamOptimizer 的学习率?在 TensorBoard: Visualizing Learning 中说我需要
How do I monitor learning rate of AdamOptimizer? In TensorBoard: Visualizing Learning is said that I need
通过将 scalar_summary 操作附加到分别输出学习率和损失的节点来收集这些.
Collect these by attaching scalar_summary ops to the nodes that output the learning rate and loss respectively.
我该怎么做?
推荐答案
我认为像下面这样的图形会很好:
I think something like following inside the graph would work fine:
with tf.name_scope("learning_rate"):
global_step = tf.Variable(0)
decay_steps = 1000 # setup your decay step
decay_rate = .95 # setup your decay rate
learning_rate = tf.train.exponential_decay(0.01, global_step, decay_steps, decay_rate, staircase=True, "learning_rate")
tf.scalar_summary('learning_rate', learning_rate)
(当然要让它工作,它需要 tf.merge_all_summaries()
并使用 tf.train.SummaryWriter
将摘要写入登录结束)
(Of course to make it work, it'd require to tf.merge_all_summaries()
and use tf.train.SummaryWriter
to write the summaries to the log in the end)
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