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ZIH
hpcsupport
hpc-compendium
Commits
6fe314d9
Commit
6fe314d9
authored
3 years ago
by
Taras Lazariv
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5 merge requests
!333
Draft: update NGC containers
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Merge preview into main
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Draft: Machine Learning restructuring
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Data Analytics restructuring
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doc.zih.tu-dresden.de/docs/software/tensorboard.md
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@@ -7,11 +7,11 @@ application.
## Using JupyterHub
The easiest way to use TensorBoard is via
[
JupyterHub
](
../access/jupyterhub.md
)
. The default
TensorBoard log directory is set to
`/tmp/<username>/tf-logs`
on the compute node, where Jupyter
session is running. In order to show your own directory with logs, it can be "sym-linked" to the
default folder. Open a "New Launcher" menu (
`Ctrl+Shift+L`
) and select "Terminal" session. It
TensorBoard log directory is set to
`/tmp/<username>/tf-logs`
on the compute node, where Jupyter
session is running. In order to show your own directory with logs, it can be "sym-linked" to the
default folder. Open a "New Launcher" menu (
`Ctrl+Shift+L`
) and select "Terminal" session. It
will start new terminal on the respective compute node. Create a directory
`/tmp/lazariv/tf-logs`
and link it with your log directory
and link it with your log directory
`ln -s <your-tensorboard-target-directory> <local-tf-logs-directory>`
```
Bash
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@@ -41,7 +41,6 @@ marie@compute$ module spider TensorFlow/2.3.1
If TensorBoard occurs in the
`Included extensions`
section of the output, TensorBoard is available.
To use TensorBoard, you have to connect via ssh to the ZIH system as usual, schedule an interactive
job and load a TensorFlow module:
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