From a791200cddf279b558810d9acff873adb4bb86fb Mon Sep 17 00:00:00 2001 From: lazariv <taras.lazariv@tu-dresden.de> Date: Mon, 30 Aug 2021 15:56:36 +0000 Subject: [PATCH] Add TensorBoard JupyterHub documentation --- .../docs/software/tensorboard.md | 35 ++++++++++++++++--- 1 file changed, 30 insertions(+), 5 deletions(-) diff --git a/doc.zih.tu-dresden.de/docs/software/tensorboard.md b/doc.zih.tu-dresden.de/docs/software/tensorboard.md index a2da2b7c6..982225c6b 100644 --- a/doc.zih.tu-dresden.de/docs/software/tensorboard.md +++ b/doc.zih.tu-dresden.de/docs/software/tensorboard.md @@ -3,19 +3,44 @@ TensorBoard is a visualization toolkit for TensorFlow and offers a variety of functionalities such as presentation of loss and accuracy, visualization of the model graph or profiling of the application. -On ZIH systems, TensorBoard is only available as an extension of the TensorFlow module. To check + +## 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 +will start new terminal on the respective compute node. Create a directory `/tmp/lazariv/tf-logs` +and link it with your log directory +`ln -s <your-tensorboard-target-directory> <local-tf-logs-directory>` + +```Bash +mkdir -p /tmp/$USER/tf-logs +ln -s <your-tensorboard-target-directory> /tmp/$USER/tf-logs +``` + +Update TensorBoard tab if needed with `F5`. + +## Using TensorBoard + +On ZIH systems, TensorBoard is also available as an extension of the TensorFlow module. To check whether a specific TensorFlow module provides TensorBoard, use the following command: -```console +```console hl_lines="9" marie@compute$ module spider TensorFlow/2.3.1 [...] -Included extensions -[...] + Included extensions + =================== + absl-py-0.10.0, astor-0.8.0, astunparse-1.6.3, cachetools-4.1.1, gast-0.3.3, + google-auth-1.21.3, google-auth-oauthlib-0.4.1, google-pasta-0.2.0, + grpcio-1.32.0, Keras-Preprocessing-1.1.2, Markdown-3.2.2, oauthlib-3.1.0, opt- + einsum-3.3.0, pyasn1-modules-0.2.8, requests-oauthlib-1.3.0, rsa-4.6, + tensorboard-2.3.0, tensorboard-plugin-wit-1.7.0, TensorFlow-2.3.1, tensorflow- + estimator-2.3.0, termcolor-1.1.0, Werkzeug-1.0.1, wrapt-1.12.1 ``` If TensorBoard occurs in the `Included extensions` section of the output, TensorBoard is available. -## Using TensorBoard To use TensorBoard, you have to connect via ssh to the ZIH system as usual, schedule an interactive job and load a TensorFlow module: -- GitLab