In 2017, we released the
dbutils.tensorboard.start()API to manage and use TensorBoard inside Databricks python notebooks. This API only permits one active TensorBoard process on a cluster at any given time – which hinders multi-tenant use-cases. Early last year, TensorBoard released its own API for notebooks via the
%tensorboardpython magic command. This API not only starts TensorBoard processes but also exposes the TensorBoard’s command line arguments in the notebook environment. In addition, it embeds the TensorBoard UI inside notebooks, whereas the
dbutils.tensorboard.startAPI prints a link to open TensorBoard in a new tab.
Read on to see how you can use it.