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:description: How to install deep learning frameworks for ROCm
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:keywords: deep learning, frameworks, ROCm, install, PyTorch, TensorFlow, JAX, MAGMA, DeepSpeed, ML, AI
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********************************************
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Installing deep learning frameworks for ROCm
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********************************************
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**********************************
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Deep learning frameworks for ROCm
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**********************************
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ROCm provides a comprehensive ecosystem for deep learning development, including
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:ref:`libraries <artificial-intelligence-apis>` for optimized deep learning operations and ROCm-aware versions of popular
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deep learning frameworks and libraries such as PyTorch, TensorFlow, and JAX. ROCm works closely with these
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frameworks to ensure that framework-specific optimizations take advantage of AMD accelerator and GPU architectures.
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Deep learning frameworks provide environments for machine learning, training, fine-tuning, inference, and performance optimization.
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The following guides provide information on compatibility and supported
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features for these ROCm-enabled deep learning frameworks.
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ROCm offers a complete ecosystem for developing and running deep learning applications efficiently. It also provides ROCm-compatible versions of popular frameworks and libraries, such as PyTorch, TensorFlow, JAX, and others.
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* :doc:`PyTorch compatibility <../compatibility/ml-compatibility/pytorch-compatibility>`
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* :doc:`TensorFlow compatibility <../compatibility/ml-compatibility/tensorflow-compatibility>`
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* :doc:`JAX compatibility <../compatibility/ml-compatibility/jax-compatibility>`
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* :doc:`verl compatibility <../compatibility/ml-compatibility/verl-compatibility>`
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* :doc:`Stanford Megatron-LM compatibility <../compatibility/ml-compatibility/stanford-megatron-lm-compatibility>`
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* :doc:`DGL compatibility <../compatibility/ml-compatibility/dgl-compatibility>`
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* :doc:`Megablocks compatibility <../compatibility/ml-compatibility/megablocks-compatibility>`
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* :doc:`Taichi compatibility <../compatibility/ml-compatibility/taichi-compatibility>`
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The AMD ROCm organization actively contributes to open-source development and collaborates closely with framework organizations. This collaboration ensures that framework-specific optimizations effectively leverage AMD GPUs and accelerators.
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This chart steps through typical installation workflows for installing deep learning frameworks for ROCm.
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The table below summarizes information about ROCm-enabled deep learning frameworks. It includes details on ROCm compatibility and third-party tool support, installation steps and options, and links to GitHub resources. For a complete list of supported framework versions on ROCm, see the :doc:`Compatibility matrix <../compatibility/compatibility-matrix>` topic.
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.. image:: ../data/how-to/framework_install_2024_07_04.png
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:alt: Flowchart for installing ROCm-aware machine learning frameworks
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:align: center
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.. list-table::
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:header-rows: 1
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:widths: 5 3 6 3
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See the installation instructions to get started.
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* - Framework
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- Installation
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- Installation options
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- GitHub
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* :doc:`PyTorch for ROCm <rocm-install-on-linux:install/3rd-party/pytorch-install>`
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* :doc:`TensorFlow for ROCm <rocm-install-on-linux:install/3rd-party/tensorflow-install>`
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* :doc:`JAX for ROCm <rocm-install-on-linux:install/3rd-party/jax-install>`
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* :doc:`verl for ROCm <rocm-install-on-linux:install/3rd-party/verl-install>`
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* :doc:`Stanford Megatron-LM for ROCm <rocm-install-on-linux:install/3rd-party/stanford-megatron-lm-install>`
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* :doc:`DGL for ROCm <rocm-install-on-linux:install/3rd-party/dgl-install>`
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* :doc:`Megablocks for ROCm <rocm-install-on-linux:install/3rd-party/megablocks-install>`
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* :doc:`Taichi for ROCm <rocm-install-on-linux:install/3rd-party/taichi-install>`
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* - `PyTorch <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/pytorch-compatibility.html>`_
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- .. raw:: html
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<a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/pytorch-install.html"><i class="fas fa-link fa-lg"></i></a>
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-
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- `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/pytorch-install.html#using-a-docker-image-with-pytorch-pre-installed>`_
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- `Wheels package <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/pytorch-install.html#using-a-wheels-package>`_
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- `ROCm Base Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/pytorch-install.html#using-the-pytorch-rocm-base-docker-image>`_
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- `Upstream Docker file <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/pytorch-install.html#using-the-pytorch-upstream-dockerfile>`_
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- .. raw:: html
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<a href="https://github.com/ROCm/pytorch"><i class="fab fa-github fa-lg"></i></a>
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* - `TensorFlow <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/tensorflow-compatibility.html>`_
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- .. raw:: html
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<a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/tensorflow-install.html"><i class="fas fa-link fa-lg"></i></a>
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-
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- `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/tensorflow-install.html#using-a-docker-image-with-tensorflow-pre-installed>`_
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- `Wheels package <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/tensorflow-install.html#using-a-wheels-package>`_
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.. note::
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- .. raw:: html
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<a href="https://github.com/ROCm/tensorflow-upstream"><i class="fab fa-github fa-lg"></i></a>
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* - `JAX <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/jax-compatibility.html>`_
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- .. raw:: html
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<a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/jax-install.html"><i class="fas fa-link fa-lg"></i></a>
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-
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- `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/jax-install.html#using-a-prebuilt-docker-image>`_
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- .. raw:: html
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<a href="https://github.com/ROCm/jax"><i class="fab fa-github fa-lg"></i></a>
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* - `verl <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/verl-compatibility.html>`_
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- .. raw:: html
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<a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/verl-install.html"><i class="fas fa-link fa-lg"></i></a>
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- `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/verl-install.html#use-a-prebuilt-docker-image-with-verl-pre-installed>`_
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- .. raw:: html
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<a href="https://github.com/ROCm/verl"><i class="fab fa-github fa-lg"></i></a>
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* - `Stanford Megatron-LM <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/stanford-megatron-lm-compatibility.html>`_
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- .. raw:: html
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<a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/stanford-megatron-lm-install.html"><i class="fas fa-link fa-lg"></i></a>
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-
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- `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/stanford-megatron-lm-install.html#use-a-prebuilt-docker-image-with-stanford-megatron-lm-pre-installed>`_
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- .. raw:: html
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<a href="https://github.com/ROCm/Stanford-Megatron-LM"><i class="fab fa-github fa-lg"></i></a>
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* - `DGL <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/dgl-compatibility.html>`_
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- .. raw:: html
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<a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/dgl-install.html"><i class="fas fa-link fa-lg"></i></a>
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-
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- `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/dgl-install.html#use-a-prebuilt-docker-image-with-dgl-pre-installed>`_
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- .. raw:: html
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<a href="https://github.com/ROCm/dgl"><i class="fab fa-github fa-lg"></i></a>
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* - `Megablocks <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/megablocks-compatibility.html>`_
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- .. raw:: html
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<a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/megablocks-install.html"><i class="fas fa-link fa-lg"></i></a>
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-
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- `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/megablocks-install.html#using-a-prebuilt-docker-image-with-megablocks-pre-installed>`_
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- .. raw:: html
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<a href="https://github.com/ROCm/megablocks"><i class="fab fa-github fa-lg"></i></a>
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* - `Taichi <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/taichi-compatibility.html>`_
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- .. raw:: html
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<a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/taichi-install.html"><i class="fas fa-link fa-lg"></i></a>
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-
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- `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/taichi-install.html#use-a-prebuilt-docker-image-with-taichi-pre-installed>`_
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- `Wheels package <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/taichi-install.html#use-a-wheels-package>`_
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- .. raw:: html
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<a href="https://github.com/ROCm/taichi"><i class="fab fa-github fa-lg"></i></a>
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For guidance on installing ROCm itself, refer to :doc:`ROCm installation for Linux <rocm-install-on-linux:index>`.
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Learn how to use your ROCm deep learning environment for training, fine-tuning, inference, and performance optimization
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through the following guides.
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* :doc:`rocm-for-ai/index`
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* :doc:`Training <rocm-for-ai/training/index>`
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* :doc:`Use ROCm for training <rocm-for-ai/training/index>`
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* :doc:`Use ROCm for fine-tuning LLMs <rocm-for-ai/fine-tuning/index>`
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* :doc:`Use ROCm for AI inference <rocm-for-ai/inference/index>`
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* :doc:`Use ROCm for AI inference optimization <rocm-for-ai/inference-optimization/index>`
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* :doc:`Fine-tuning LLMs <rocm-for-ai/fine-tuning/index>`
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* :doc:`Inference <rocm-for-ai/inference/index>`
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* :doc:`Inference optimization <rocm-for-ai/inference-optimization/index>`
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