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ROCm/docs/how-to/deep-learning-rocm.rst
Pratik Basyal 353d2fe1c1 2nd POC for How to Use ROCm for AI (#282) (#4299)
* New TOC for ROCm for AI developed

Co-authored-by: Peter Park <peter.park@amd.com>
2025-01-27 15:49:21 -05:00

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.. meta::
:description: How to install deep learning frameworks for ROCm
:keywords: deep learning, frameworks, ROCm, install, PyTorch, TensorFlow, JAX, MAGMA, DeepSpeed, ML, AI
********************************************
Installing deep learning frameworks for ROCm
********************************************
ROCm provides a comprehensive ecosystem for deep learning development, including
:ref:`libraries <artificial-intelligence-apis>` for optimized deep learning operations and ROCm-aware versions of popular
deep learning frameworks and libraries such as PyTorch, TensorFlow, and JAX. ROCm works closely with these
frameworks to ensure that framework-specific optimizations take advantage of AMD accelerator and GPU architectures.
The following guides provide information on compatibility and supported
features for these ROCm-enabled deep learning frameworks.
* :doc:`PyTorch compatibility <../compatibility/ml-compatibility/pytorch-compatibility>`
* :doc:`TensorFlow compatibility <../compatibility/ml-compatibility/tensorflow-compatibility>`
* :doc:`JAX compatibility <../compatibility/ml-compatibility/jax-compatibility>`
This chart steps through typical installation workflows for installing deep learning frameworks for ROCm.
.. image:: ../data/how-to/framework_install_2024_07_04.png
:alt: Flowchart for installing ROCm-aware machine learning frameworks
:align: center
See the installation instructions to get started.
* :doc:`PyTorch for ROCm <rocm-install-on-linux:install/3rd-party/pytorch-install>`
* :doc:`TensorFlow for ROCm <rocm-install-on-linux:install/3rd-party/tensorflow-install>`
* :doc:`JAX for ROCm <rocm-install-on-linux:install/3rd-party/jax-install>`
.. note::
For guidance on installing ROCm itself, refer to :doc:`ROCm installation for Linux <rocm-install-on-linux:index>`.
Learn how to use your ROCm deep learning environment for training, fine-tuning, inference, and performance optimization
through the following guides.
* :doc:`rocm-for-ai/index`
* :doc:`Training <rocm-for-ai/training/index>`
* :doc:`Fine-tuning LLMs <rocm-for-ai/fine-tuning/index>`
* :doc:`Inference <rocm-for-ai/inference/index>`
* :doc:`Inference optimization <rocm-for-ai/inference-optimization/index>`