如何在 TensorBoard 中显示不同的运行? [英] How do display different runs in TensorBoard?

问题描述

TensorBoard 似乎具有显示多个不同运行并切换它们的功能.

TensorBoard seems to have a feature to display multiple different runs and toggle them.

如何在此处显示多个运行以及如何为它们分配名称以区分它们?

How can I make multiple runs show up here and how can assign a name to them to differentiate them?

推荐答案

除了 TensorBoard 扫描子目录(这样你可以在运行时传递一个包含目录的目录)，你还可以明确地将多个目录传递给 TensorBoard 并给出自定义名称(来自 --help 输出的示例):

In addition to TensorBoard scanning subdirectories (so you can pass a directory containing the directories with your runs), you can also pass multiple directories to TensorBoard explicitly and give custom names (example taken from the --help output):

tensorboard --logdir=name1:/path/to/logs/1,name2:/path/to/logs/2

更多信息可以在 TensorBoard 文档.

在 TensorBoard 的最新版本中，这种方式的别名需要不同的参数，但不鼓励使用它(引自 github 上的当前文档 - 上面链接):

In recent versions of TensorBoard, aliasing this way requires a different argument, however its use is discouraged (quote from current documentation on github - linked above):

Logdir &Logdir_spec(传统模式)

你也可以传递一个逗号分隔的日志目录列表，和TensorBoard 将监视每个目录.您还可以将名称分配给通过在名称和名称之间放置一个冒号来实现单个日志目录路径，如

You may also pass a comma separated list of log directories, and TensorBoard will watch each directory. You can also assign names to individual log directories by putting a colon between the name and the path, as in

tensorboard --logdir_spec name1:/path/to/logs/1,name2:/path/to/logs/2

不鼓励使用此标志 (--logdir_spec)，通常可以避免使用.TensorBoard 递归遍历日志目录；对于细粒度控制，更喜欢使用符号链接树.某些功能在以下情况下可能无法使用使用 --logdir_spec 而不是 --logdir.

This flag (--logdir_spec) is discouraged and can usually be avoided. TensorBoard walks log directories recursively; for finer-grained control, prefer using a symlink tree. Some features may not work when using --logdir_spec instead of --logdir.

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