Integrate Workbench with Google Vertex AI
This guide walks you through integrating the ML Workbench with a notebook on Google Vertex AI.
From the Workbench page in Vertex AI, find your notebook instance and click OPEN JUPYTERLAB to navigate to the JupyterLab web interface. Clickto open a terminal.
From the terminal, run
pip install tigergraph_mlworkbench. This installs the ML Workbench JupyterLab extension.
From the terminal, run the following command to install the
tigergraph-torchPython kernel. Choose the appropriate command depending on whether you are using a CPU or GPU for training:
Once installation finishes, refresh your browser. You should see a small TigerGraph logo on the very left navigation bar and a new Python kernel called TigerGraph Pytorch on the launch page.
With the ML Workbench JupyterLab extension and the
tigergraph-torch kernel installed, the next step is to deploy GDPS on your TigerGraph instance so the Workbench can communicate with your TigerGraph database.