Jupyter + TensorBoard¶
Getting Started¶
Select Jupyter + TensorBoard as the plugin. Select an option for Python Version and Type within the Application Parameters. The default Log Dir for TensorBoard is $HOME.
TensorBoard & Jupyter will launch in separate browsers.
Below is a simple demonstration using TensorBoard to visualize model performance. The Notebook builds and trains a simple neural network for classifying 28x28 grayscale images into 10 types of clothing. For more information on building & training a simple model using Tensorflow, reference Jupyter + TensorFlow.

The tensorboard_callback saved the log files to the logs folder which is then accessed by TensorBoard.

External References¶
For more information on how to use TensorBoard, please visit tensorflow.org/tensorboard.
For more information on how to use TensorFlow, please visit tensorflow.org.
For more information on how to use the Jupyter family of products, please visit jupyter.org
Version Options & Configurations¶
The Jupyter application includes Conda with Python 2.7, 3.6, 3.7 & 3.8. The CUDA version loaded is dependent upon system and node type.
Node Type | CPU | GPU |
Python | 3.6 / 3.7 / 3.8 | 3.6 / 3.7 / 3.8 |
CudaToolKit | N/A | 11.0.221 |
cuDNN | N/A | 8.0.4 |
TensorFlow | 2.4.1 | 2.4.0 |
PyTorch | 1.7.0 | 1.7.0 |