Build and Run a Sample Using the Command Line
Intel® AI Analytics Toolkit
In this section, you will run a simple "Hello World" project to familiarize yourself with the process of building projects, and then build your own project.
NOTE:
If you have not already configured your development environment, go to Configure your system then return to this page. If you have already completed the steps to configure your system, continue with the steps below.
Build and Run a Sample Project
The samples below must be cloned to your system before you can build the sample project:
| Name of Sample | Description | How to Clone and Build |
| TensorFlow HelloWorld | TensorFlow optimized on Intel hardware enables Intel® DNNL calls by default. It implements an example neural network with one convolution layer and one ReLU layer. | Clone TensorFlow_HelloWorld sample, then follow the directions in README.md to build and run the sample. |
| For more samples, browse the full GitHub repository: Intel® oneAPI AI Analytics Toolkit Code Samples. | ||
To see a list of components that support CMake, see Use CMake to with oneAPI Applications.
Build Your Own Project
No special modifications to your existing Python projects are required to start using them with this toolkit. For new projects, the process closely follows the process used for creating sample Hello World projects. Refer to the Hello World README files for instructions.
Maximizing Performance
You can get documentation to help you maximize performance for either TensorFlow or PyTorch.
Parent topic: Get Started with the Intel® AI Analytics Toolkit