After the notebook has been provisioned, select OPEN JUPYTERLAB to access the JupyterLab environment. If you’d like to access the sample for this tutorial, you can open a new terminal (File > New > Terminal), and then run:
The left sidebar will refresh after a few moments. You’ll find the sample within ai-platform samples > notebooks > samples > pytorch > lightning.
Setup your TPU node
Next, let’s provision a TPU node that we can use from our notebook instance. From the Cloud Console, go to Compute Engine > TPUs. Select Create TPU Node, and then choose a name of your choice. Then, select a Zone and TPU type, keeping in mind that TPU availability varies per region.
Make sure to select a TPU software version that matches the version you selected for your notebook, in this case
pytorch-1.8. Also, for the purposes of this tutorial, select
datalab-network for the Network, so that you can access your TPU directly from the notebook instance without configuring any networking settings.