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ZIH
hpcsupport
hpc-compendium
Commits
6c98cd88
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6c98cd88
authored
2 years ago
by
Jan Frenzel
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Corrected indentation in tensorboard.md.
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Clarify Tensorboard from JH, reading log data
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@@ -16,27 +16,19 @@ It will start a new terminal on the respective compute node. Then you can create
...
@@ -16,27 +16,19 @@ It will start a new terminal on the respective compute node. Then you can create
`/tmp/<username>/tf-logs`
and link it with the directory where your own log data is located.
`/tmp/<username>/tf-logs`
and link it with the directory where your own log data is located.
Consider the following commands to do so:
Consider the following commands to do so:
The easiest way to use TensorBoard is via
[
JupyterHub
](
../access/jupyterhub.md
)
. By default,
TensorBoard is configured to read log data from
`/tmp/<username>/tf-logs`
on the compute node on
which the Jupyter session is running. In order to show your own log data from a different directory,
soft-link this directory with
`/tmp/<username>/tf-logs`
in order to make TensorBoard reading your
log data. Note, that the directory
`/tmp/<username>/tf-logs`
might not exist and you have to
create it first. Therefore, open a "New Launcher" (
`Ctrl+Shift+L`
) and select "Terminal" session.
It will start a new terminal on the respective compute node. Then you can create the directory
`/tmp/<username>/tf-logs`
and link it with the directory where your own log data is located.
Assuming you use a line like the following in your code:
Assuming you use a line like the following in your code:
```python
```
python
tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir="/home/marie/logs")
tensorboard_callback
=
tf
.
keras
.
callbacks
.
TensorBoard
(
log_dir
=
"
/home/marie/logs
"
)
```
```
You can then make the TensorBoard available with:
You can then make the TensorBoard available with:
```console
```
bash
marie@compute$
mkdir -p /tmp/$USER/tf-logs
mkdir
-p
/tmp/
$USER
/tf-logs
marie@compute$
ln -s /home/marie/logs /tmp/$USER/tf-logs
ln
-s
/home/marie/logs /tmp/
$USER
/tf-logs
```
```
Update TensorBoard tab if needed with
`F5`
.
Update TensorBoard tab if needed with
`F5`
.
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