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Commit 6fe314d9 authored by Taras Lazariv's avatar Taras Lazariv
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Fix linter

parent a791200c
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5 merge requests!333Draft: update NGC containers,!322Merge preview into main,!319Merge preview into main,!279Draft: Machine Learning restructuring,!258Data Analytics restructuring
...@@ -7,11 +7,11 @@ application. ...@@ -7,11 +7,11 @@ application.
## Using JupyterHub ## Using JupyterHub
The easiest way to use TensorBoard is via [JupyterHub](../access/jupyterhub.md). The default 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 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 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 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` 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>` `ln -s <your-tensorboard-target-directory> <local-tf-logs-directory>`
```Bash ```Bash
...@@ -41,7 +41,6 @@ marie@compute$ module spider TensorFlow/2.3.1 ...@@ -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. 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 To use TensorBoard, you have to connect via ssh to the ZIH system as usual, schedule an interactive
job and load a TensorFlow module: job and load a TensorFlow module:
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