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61 lines
2.6 KiB
ReStructuredText
61 lines
2.6 KiB
ReStructuredText
.. meta::
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:description: How to install ROCm and popular deep learning frameworks.
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:keywords: ROCm, AI, LLM, train, fine-tune, FSDP, DeepSpeed, LLaMA, tutorial
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.. _rocm-for-ai-install:
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********************************************
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Installing ROCm and deep learning frameworks
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********************************************
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Before getting started, install ROCm and supported deep learning frameworks.
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.. grid:: 1
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.. grid-item-card:: Pre-install
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Each release of ROCm supports specific hardware and software configurations. Before installing, consult the
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:doc:`System requirements <rocm-install-on-linux:reference/system-requirements>` and
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:doc:`Installation prerequisites <rocm-install-on-linux:install/prerequisites>` guides.
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If you’re new to ROCm, refer to the :doc:`ROCm quick start install guide for Linux
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<rocm-install-on-linux:install/quick-start>`.
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If you’re using a Radeon GPU for graphics-accelerated applications, refer to the
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`Radeon installation instructions <https://rocm.docs.amd.com/projects/radeon/en/latest/docs/install/native_linux/howto_native_linux.html>`_.
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You can install ROCm on :doc:`compatible systems <rocm-install-on-linux:reference/system-requirements>` via your Linux
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distribution's package manager. See the following documentation resources to get started:
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* :doc:`ROCm installation overview <rocm-install-on-linux:install/install-overview>`
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* :doc:`Using your Linux distribution's package manager <rocm-install-on-linux:install/install-methods/package-manager-index>`
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* :ref:`Multi-version installation <rocm-install-on-linux:installation-types>`
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.. grid:: 1
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.. grid-item-card:: Post-install
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Follow the :doc:`post-installation instructions <rocm-install-on-linux:install/post-install>` to
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configure your system linker, PATH, and verify the installation.
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If you encounter any issues during installation, refer to the
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:doc:`Installation troubleshooting <rocm-install-on-linux:reference/install-faq>` guide.
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Deep learning frameworks
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========================
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ROCm supports deep learning frameworks and libraries including `PyTorch
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<https://pytorch.org>`_, `TensorFlow
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<https://tensorflow.org>`_, `JAX <https://jax.readthedocs.io/en/latest>`_, and more.
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Review the :doc:`framework installation documentation <../deep-learning-rocm>`. For ease-of-use, it's recommended to use official ROCm prebuilt Docker
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images with the framework pre-installed.
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Next steps
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==========
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After installing ROCm and your desired ML libraries -- and before running AI workloads -- conduct system health benchmarks
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to test the optimal performance of your AMD hardware. See :doc:`system-setup/index` to get started.
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