Running TAO Toolkit in the Cloud

TAO Toolkit v5.3.0

Training Deep Learning models can be a very resource intensive process. To get an accurate model, you need several hours of training time and data on the order gigabytes. Apart from the training, you will also need to run several experiments to get the best hyper-parameter configuration. These reasons make running the NVIDIA TAO Toolkit on the Cloud an appealing option.

TAO Toolkit 3.0-21.08 is designed to run interactively on a virtual machine. The following sections describe how to run TAO Toolkit on different cloud services like Amazon Web Services (AWS), Google Cloud Platform (GCP), etc.

  1. Running TAO Toolkit on AWS

  2. Running TAO Toolkit on GCP

  3. Running TAO Toolkit on Azure

  4. Running TAO Toolkit on Google Colab

  5. Running TAO Toolkit on AWS EKS

  6. Running TAO Toolkit on Azure AKS


Running TAO Toolkit over the cloud requires users to lease and instantiate Virtual Machines. This can be expensive if left unattended. Don’t forget to close/shut down your instances when you are done with the training.

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