Tensorboard: Difference between revisions

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TensorBoard is used for visually monitoring statistics while a neural network trains.
TensorBoard is used for visually monitoring statistics while a neural network trains.


One recommendation for using [https://github.com/tensorflow/tensorboard/blob/master/docs/get_started.ipynb TensorBoard] on HiPerGator is to run TensorBoard monitoring as a separate workload. Many neural network software frameworks are able to stream training data to a TensorBoard log file. Here are the steps to monitor the log separately from your training workload:
One recommendation for using [https://github.com/tensorflow/tensorboard/blob/master/docs/get_started.ipynb TensorBoard] on HiPerGator is to run TensorBoard monitoring as a separate workload. Many neural network software frameworks are able to stream training data to a TensorBoard log file. Here are the steps to monitor the log separately from your training workload:


* Request a 1 CPU 2 GB RAM HiPerGator Desktop via ood.rc.ufl.edu
* Request a 1 CPU 2 GB RAM HiPerGator Desktop or a console session via [https://ood.rc.ufl.edu OnDemand]
* Open a terminal
* Start a tensorboard instance in the resulting terminal/shell:
** Enter command: ml tensorflow
module load tensorflow ubuntu
** Enter command: tensorboard --logdir ./pathtolog
tensorboard --logdir ./pathtolog &
** See printed information including a localhost URL with port number
* Copy the  printed URL
 
* Start a browser:
* Open a second terminal
firefox (or chrome)
** Enter command: ml ubuntu
* Paste the tensorboard URL into the browser's location bar to view the TensorBoard log
** Enter command: firefox (or chrome)
** Paste URL into browser to view TensorBoard log

Revision as of 20:19, 6 August 2021

Back to Tensorflow page

TensorBoard is used for visually monitoring statistics while a neural network trains.

One recommendation for using TensorBoard on HiPerGator is to run TensorBoard monitoring as a separate workload. Many neural network software frameworks are able to stream training data to a TensorBoard log file. Here are the steps to monitor the log separately from your training workload:

  • Request a 1 CPU 2 GB RAM HiPerGator Desktop or a console session via OnDemand
  • Start a tensorboard instance in the resulting terminal/shell:
module load tensorflow ubuntu
tensorboard --logdir ./pathtolog &
  • Copy the printed URL
  • Start a browser:
firefox (or chrome)
  • Paste the tensorboard URL into the browser's location bar to view the TensorBoard log