Description

Download pre-configured setup files to quick launch an NVIDIA TAO Jupyter Notebook on Azure Machine Learning with the appropriate resources (Compute Cluster and Environment) and fine-tune a TAO pretrained model, the set up is done using the NGC-AzureML Quick Launch Toolkit. azureml-ngc-tools is a CLI toolkit that enables you to launch a fully setup Jupyter notebook environment on AzureML with a combination of NGC assets pre-installed.

These ready-to-use config files work seamlessly with the NGC-AzureML Quick Launch CLI Toolkit (azureml-ngc-tools) to provide you direct access to a fully setup and optimally configured Azure Machine Learning environment with the TAO SDK container and the additional resources required for this example, pre-installed for you.

The two ready-to-use files are:

• azure_config.json: Defines the most optimal Azure environment setup for this use-case. Simply insert your Azure credentials in the indicated fields and use right away.

• ngc_config.json: Pre-installs the TAO SDK, and several TAO Notebooks that the user could run on AzureML to learn more about TAO. It includes the Object Detection using TAO DetectNet_v2 Notebook that produces a fine tuned model ready to be deployed as an AzureML Triton Inference Endpoint. No modifications are required; use this file as is.

Usage Instructions

After inserting your Azure credentials in the azure_config.json file downloaded from here, quick launch a ready-to-use Jupyter notebook on AzureML with the following bash commands:

pip install azureml-ngc-tools


azureml-ngc-tools --login azure_config.json --app ngc_config.json