Installing ROCm and machine learning frameworks

Installing ROCm and machine learning frameworks#

Applies to Linux


4 min read time

Before getting started, install ROCm and supported machine learning frameworks.


Each release of ROCm supports specific hardware and software configurations. Before installing, consult the System requirements and Installation prerequisites guides.

If you’re new to ROCm, refer to the ROCm quick start install guide for Linux.

If you’re using a Radeon GPU for graphics-accelerated applications, refer to the Radeon installation instructions.

ROCm supports two methods for installation. There is no difference in the final ROCm installation between these two methods. You can also opt for single-version or multi-version installation.


Follow the post-installation instructions to configure your system linker, PATH, and verify the installation.

If you encounter any issues during installation, refer to the Installation troubleshooting guide.

Machine learning frameworks#

ROCm supports popular machine learning frameworks and libraries including PyTorch, TensorFlow, JAX, and DeepSpeed.

Review the framework installation documentation. For ease-of-use, it’s recommended to use official ROCm prebuilt Docker images with the framework pre-installed.

The sections that follow in Training a model are geared for a ROCm with PyTorch installation.