TensorBoard is a powerful visualization tool when building machine learning models. However it can quickly become quite unwieldy as the number of model versions and runs increases.

What is TensorBoard Projects

TensorBoard Projects provides a UI to manage Tensorboard runs and allows you to easily:

• Visualize runs for a given model
• Archive Runs
• Delete Runs
• Add metadata to individual runss
• Start TensorBoard dashboard for a subset of model runs
• Write documentation for a model

As the project is still very much in development, please report any issues or features you would like to see added !

What TensorBoard Projects isn't

TensorBoard projects is not an experiment tracking solution, it simply allows you to better manage TensorBoard runs.

If you are looking for a fully fledgeed experiment tracking solution, you can look into:

• ClearML
• Comet
• MLFlow
• Weights and Biases and others

Using TensorBoard Projects

Tensorboard Projects can be installed from PyPI using pip install tensorboard-projects.

Once Tensorboard Projects is installed, you can start the UI using:

tensorboard-projects ui

In order to assist with running this on a remote machine, the following arguments are supported:

• --backend-store-uri: Storage location of metadata, defaults to ~/.tensorboard_projects
• --ip: Host for the API, use 0.0.0.0 to access from a remote machine
• --port: Port to run UI on remote machien