From 6fe314d9266bdaa3b9fed1ecbda22cd0eec838c4 Mon Sep 17 00:00:00 2001
From: lazariv <taras.lazariv@tu-dresden.de>
Date: Mon, 30 Aug 2021 15:57:09 +0000
Subject: [PATCH] Fix linter

---
 doc.zih.tu-dresden.de/docs/software/tensorboard.md | 9 ++++-----
 1 file changed, 4 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 982225c6b..83d8f2b0b 100644
--- a/doc.zih.tu-dresden.de/docs/software/tensorboard.md
+++ b/doc.zih.tu-dresden.de/docs/software/tensorboard.md
@@ -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
@@ -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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