Walkthrough: Customize Your Environment

Use this documentation to learn how to customize your container environment by adding a package to your to NVIDIA AI Workbench project. For the full list, see Quickstart Guides.

The base container that you choose when you create your AI Workbench project might not have all the features that you need. You can customize your project by installing additional packages, customizing mounts, and defining new environment variables.

In this walkthrough, you use the AI Workbench desktop application to perform the following tasks:

Open AI Workbench and Start Your Project Environment
Customize Your Project by Installing a Package
Rebuild Your Project Environment
Test by Using Your New Package in Code

Note

To create your own fully custom container, see Advanced Walkthrough: Use Your Own Container instead.

Prerequisites

Before you complete the steps in this walkthrough, you need the following:

NVIDIA AI Workbench is installed on your local system. For more information, see Install AI Workbench.
A basic test project. If you don’t have one, see Basic Quickstart.

Open AI Workbench and Start Your Project Environment

Start AI Workbench by double clicking the icon on your desktop, or by searching for the program and pressing enter. The icon has the NVIDIA logo in it.

AI Workbench starts and the My Locations page appears.
On the My Locations page, for Select a location, click Local.

AI Workbench connects to the location and the My Projects page appears.
Click the project that you want to use for this walkthrough.

The project opens.
Click Environment, and then click Start Environment.

Customize Your Project by Installing a Package

Use the following procedure to add a package to your AI Workbench project.

Near the top of the AI Workbench window, click Open JupyterLab.

JupyterLab opens in your default browser ready for you to start working.
In JupyterLab, in the file browser, double-click requirements.txt to open it.

The file opens and you should see an entry for jupyterlab.
Move to the first empty line in the file, type numpy, and then save the file.
In JupyterLab, choose File, and then click Shut Down. Confirm shut down and close the browser tab.

Rebuild Your Project Environment

Whenever you change your project environment, you must rebuild the project before you can access the changes. Use the following procedure to rebuild your environment.

In AI Workbench, on the Environment page, if your environment is running, click Stop Environment.

Wait until you see READY next to Environment.
Click Start Build.

The project builds. Wait until you see Build Ready in the status bar.
Scroll to the Packages section and verify that you see numpy in the list.
Click Start Environment.

Test by Using Your New Package in Code

After you add the package to your project and rebuild the container environment, you can use the new package in your code.

Near the top of the AI Workbench window, click Open JupyterLab.

JupyterLab opens in your default browser ready for you to start working.
In JupyterLab, navigate to the code folder. If your project already has a notebook, click to open it. Otherwise; create a new notebook by choosing Python 3 (ipykernel).

In your notebook, enter the following code and then click run.

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            import numpy as np

Enter the following code and then click run.

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            print(np.e)

You should see the following output which is the value of e.

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            2.718281828459045

Save your notebook.
In JupyterLab, choose File, and then click Shut Down. Confirm shut down and close the browser tab.
In AI Workbench, wait until you see 0 apps running in the status bar.
Click Environment, and then click Stop Environment.