This topic covers setup instructions and the necessary files to build, test, and run TensorFlow with ROCm support in a Docker environment.

github.com › ROCm › tensorflow-upstream

GitHub - ROCm/tensorflow-upstream: TensorFlow ROCm port · GitHub

We maintain tensorflow-rocm whl packages on PyPI here, to install tensorflow-rocm package using pip:

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Discussions

How To guide : PyTorch/Tensorflow on AMD (ROCm) in Windows PC

Good work! Hopefully, ROCm does catch on eventually. More on reddit.com

r/learnmachinelearning

March 18, 2025

Unable to install Tensorflow-rocm for Good AMD ROCm Setup - AI Discussions - DeepLearning.AI

I have a good ROCm setup on my AMD Ryzen 7 4800H CPU with Radeon 5600M GPU running on Red Hat Linux 9. My system RAM is 32GB and my video RAM is 6GB. I use rocminfo to see a good install, then rocm-clinfo to see a good install of rocm opencl. I can get OpenCL to use my GPU for machine learning ... More on community.deeplearning.ai

community.deeplearning.ai

April 6, 2023

[D] ROCm vs CUDA

Don't think too much. Just get the CUDA-enabled GPU. Time is money when you are creating a ML software. We mustn't forget it. More on reddit.com

r/MachineLearning

July 30, 2022

What to expect from machine learning on AMD?

You will need to use Linux and install the ROCm software stack: https://github.com/RadeonOpenCompute/ROCm I do deep learning on a Vega Frontier Edition and as of a month or so ago, I had to compile pytorch from source in order to get it to work. Compatibility and development is very rapid, however, and it's likely you can just work off one of their docker images. Tensorflow support is currently a bit more mature than pytorch. In pytorch, once you have it installed and set up, it's the exact same as if you had an nvidia card--just call .cuda() or .to(device) and carry on. Performance, not sure. People have not really benchmarked non-vega cards for DL since they only recently got official ROCm support. Radeon VII is about 75% the speed of RTX 2080 Ti on vision tasks, Vega FE is about 50-75% the speed of Radeon VII. People have posted benchmark results on this subreddit. More on reddit.com

r/Amd

March 21, 2019

Videos

15:34

YouTube

Install ROCm 3.0 and tensorflow on Ubuntu - AMD RX 580 GPU - YouTube

February 8, 2020

youtube.com

TensorFlow on AMD ROCm: Installation and Performance ...

12:03

YouTube

PyTorch/TensorFlow on AMD: Beginner's Guide to ROCm on Linux - YouTube

August 24, 2025

04:25

YouTube

AMD HIP Tutorial, 11-2, Tensorflow on ROCm - YouTube

April 25, 2024

20:27

YouTube

ROCm 5.3 on Ubuntu 22.10 / 22.04 with Pytorch and Tensorflow - ...

November 3, 2022

08:36

YouTube

ROCm 3.3 on Ubuntu 20.04 with tensorflow python 3.8 - Fixing ...

April 26, 2020

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Docker Hub

hub.docker.com › r › rocm › tensorflow

rocm/tensorflow - Docker Image

This repo host the docker images for Tensorflow releases with ROCm backend support.

PyPI

pypi.org › project › tensorflow-rocm

tensorflow-rocm · PyPI

Download URL: tensorflow_rocm-2.14.0.600-cp39-cp39-manylinux2014_x86_64.whl

      » pip install tensorflow-rocm

Published Jan 10, 2024

Version 2.14.0.600

Homepage https://www.tensorflow.org/

Casey Primozic

cprimozic.net › notes › posts › setting-up-tensorflow-with-rocm-on-7900-xtx

Setting Up TensorFlow with ROCm on the 7900 XTX :: Casey Primozic's Notes

June 9, 2023 - Running sudo amdgpu-install --usecase=rocm --no-dkms worked for me. I followed the rest of the instructions setting some user groups and rebooting, and things seemed to be in good shape. The next step was building a custom TensorFlow that works with ROCm version 5.5 and the 7900 XTX.

reddit.com › r/learnmachinelearning › how to guide : pytorch/tensorflow on amd (rocm) in windows pc

r/learnmachinelearning on Reddit: How To guide : PyTorch/Tensorflow on AMD (ROCm) in Windows PC

March 18, 2025 -

WARNING - OUTDATED & doesn't work anymore

In a classic AMD fashion, nothing below works anymore. If the new documentation is better than before, take it as a warning: AMD software & support constantly changes and you will have to very often restart from scratch.

Please refer to updated AMD doc for the latest version: https://rocm.docs.amd.com/projects/radeon-ryzen/en/latest/docs/install/installrad/wsl/howto_wsl.html

Outdated, kept here as a souvenir for emotional reasons (god have I spent hours for that, probably more than the time GPU acceleration made me gain):

A small How To guide for using pytorch/tensorflow in your windows PC on your AMD GPU

Hey everyone, since the last posts on that matter are now outdated, I figured an update could be welcome for some people. Note that I have not tried this method with tensorflow, I only added it here since there is some doc about it done by AMD.

Step 0 : have a supported GPU.

This tuto will focus on using WSL, and only a handfull of GPUs are supported. You can find the list here :

https://rocm.docs.amd.com/projects/radeon/en/latest/docs/compatibility/wsl/wsl_compatibility.html#gpu-support-matrix
This is the only GPU list that matters. If your GPU is not here you cannot use pytorch/tensorflow on windows this way.

Step 1 : Install WSL on your windows PC.
Simply follow this official guide from microsoft : https://learn.microsoft.com/en-us/windows/wsl/install

Or do it the dirty but easy way and install ubuntu 24.04 LTS from the microsoft store : https://apps.microsoft.com/detail/9NZ3KLHXDJP5?hl=neutral&gl=CH&ocid=pdpshare

To be sure, please make sure that the version you pick is supported here : https://rocm.docs.amd.com/projects/radeon/en/latest/docs/compatibility/wsl/wsl_compatibility.html#os-support-matrix

Reboot your PC

Step 2 : Install ROCm on WSL
Start WSL (you should have an ubuntu app you can launch like any other applications)
Install ROCm using this script : https://rocm.docs.amd.com/projects/radeon/en/latest/docs/install/wsl/install-radeon.html#install-amd-unified-driver-package-repositories-and-installer-script
Follow their instructions and run their scripts untill you can run the command rocminfo. It should display the model of your GPU alongside several other infos.

Reboot your PC

Step 3 : Install pytorch/tensorflow with ROCm build
For pytorch, you should straight up follow this guide : https://rocm.docs.amd.com/projects/radeon/en/latest/docs/install/wsl/install-pytorch.html#install-methods

For tensorflow, you first need to install MIGraphX : https://rocm.docs.amd.com/projects/radeon/en/latest/docs/install/native_linux/install-migraphx.html and then tensorflow for rocm : https://rocm.docs.amd.com/projects/radeon/en/latest/docs/install/native_linux/install-tensorflow.html#pip-installation

Step 4 : Enjoy

You should have everything set to start working. I've personally set up a jupyter server on WSL ( https://harshityadav95.medium.com/jupyter-notebook-in-windows-subsystem-for-linux-wsl-8b46fdf0a536 ) allowing me to connect to it from VSCode.

This was mainly a wrap up of already existing doc by AMD. Thumbs up to them as their doc was improved a lot since I first tried it. Hope this helps ! Hopefully, you'll be one day able to use pytorch with rocm without WSL on more gpus, you can follow this issue if you're interested in it -> https://github.com/pytorch/pytorch/issues/109204

Top answer

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Good work! Hopefully, ROCm does catch on eventually.

2 of 2

Thank you, this was very helpful and worked great!

AMD ROCm

rocm.docs.amd.com › projects › radeon-ryzen › en › latest › docs › install › installrad › native_linux › install-tensorflow.html

Install TensorFlow for ROCm — Use ROCm on Radeon and Ryzen

TensorFlow is an open-source library for solving machine-learning, deep-learning, and artificial-intelligence problems. It can be used to solve many problems across different sectors and industries but primarily focuses on training and inference in neural networks.

Find elsewhere

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Madebymikal

madebymikal.com › tensorflow-rocm-and-version-mismatches

Tensorflow, ROCm, and version mismatches – Made by Mikal

September 21, 2025 - pip3 install uv uv pip install tensorflow==2.19.0 uv pip install -U tensorflow-rocm==2.19.0 \ -f https://repo.radeon.com/rocm/manylinux/rocm-rel-7.0/

Arch Linux

aur.archlinux.org › packages › tensorflow-rocm

AUR (en) - tensorflow-rocm

rocm-hip-sdk (opencl-amd-devAUR, rocm-binAUR, rocm-gfx101x-binAUR, rocm-gfx103x-binAUR, rocm-gfx110x-binAUR, rocm-gfx120x-binAUR, rocm-gfx1150-binAUR, rocm-gfx1151-binAUR, rocm-gfx1152-binAUR, rocm-nightly-gfx120x-all-binAUR, rocm-nightly-gfx1151-binAUR, rocm-nightly-gfx110x-binAUR) bazel (bazel3-binAUR, bazelisk-gitAUR, bazelisk) (make) ... Show 6 more dependencies... ... If you are interested in submitting patches, please use my github repo: https://github.com/lubosz/tensorflow-rocm

TensorFlow

blog.tensorflow.org › 2018 › 08 › amd-rocm-gpu-support-for-tensorflow.html

AMD ROCm GPU support for TensorFlow — The TensorFlow Blog

ROCm, the Radeon Open Ecosystem, is our open-source software foundation for GPU computing on Linux. Our TensorFlow implementation leverages MIOpen, a library of highly optimized GPU routines for deep learning.

AMD ROCm

rocm.docs.amd.com › projects › install-on-linux › en › latest › how-to › docker.html

Run ROCm Docker containers — ROCm installation (Linux)

June 5, 2026 - Running ROCm workloads in Docker containers on AMD GPUs

AMD ROCm

rocm.docs.amd.com › projects › radeon-ryzen › en › latest › index.html

Use ROCm on Radeon and Ryzen — Use ROCm on Radeon and Ryzen

ROCm™ 7.2.1 supports the latest Radeon™ 9000 Series (RDNA™ 4) and select 7000 Series (RDNA™ 3) GPUs, and introduces support for Ryzen™ APUs, enabling cost-effective, local development and inference for researchers and engineers using Pytorch.

Wikipedia

en.wikipedia.org › wiki › PyTorch

PyTorch - Wikipedia

2 weeks ago - PyTorch supports various sub-types of multi-dimensional arrays, or Tensors. PyTorch Tensors are similar to NumPy Arrays, but can also be operated on by a CUDA-capable NVIDIA GPU. PyTorch has also been developing support for other GPU platforms, for example, AMD's ROCm and Apple's Metal Framework.

History PyTorch tensors PyTorch neural networks PyTorch Serialized File Format Example

Ahenriksson

ahenriksson.com › posts › how-to-install-tensorflow-with-gpu-support-for-amd-on-debian-buster

How to Install Tensorflow With Gpu Support for Amd on Debian Buster - ahenriksson.com

January 28, 2020 - wget -qO - http://repo.radeon.com/rocm/apt/debian/rocm.gpg.key | sudo apt-key add - echo 'deb [arch=amd64] http://repo.radeon.com/rocm/apt/debian/ xenial main' | sudo tee /etc/apt/sources.list.d/rocm.list sudo apt update ... This example is from Aymeric Damien’s TensorFlow examples.

There and back again

preining.info › blog › 2020 › 05 › switching-from-nvidia-to-amd-including-tensorflow

Switching from NVIDIA to AMD (including tensorflow) | There and back again

May 14, 2020 - There is already work done to make Tensorflow run on ROCm, the tensorflow-rocm project.

DeepLearning.AI

community.deeplearning.ai › ai discussions

Unable to install Tensorflow-rocm for Good AMD ROCm Setup - AI Discussions - DeepLearning.AI

April 6, 2023 - I have a good ROCm setup on my AMD Ryzen 7 4800H CPU with Radeon 5600M GPU running on Red Hat Linux 9. My system RAM is 32GB and my video RAM is 6GB. I use rocminfo to see a good install, then rocm-clinfo to see a good install of rocm opencl. I can get OpenCL to use my GPU for machine learning ...

WikiWiki

wikiwiki.jp › sd_toshiaki › 最近の主な出来事

最近の主な出来事 - としあきdiffusion Wiki*

(7/5) 6月頃から、9070XTとROCm TheRockの組み合わせで結構良い速度を出してるとしあきのスクショを見かけるようになってきた。 TheRockはいまだ開発中なので現状では人柱向けではあるが、今後に期待したい。

Medium

medium.com › @qztseng › install-and-build-tensorflow2-3-on-amd-gpu-with-rocm-7c812f922f57

Install and Build Tensorflow2.3 on AMD GPU with ROCm | by Qingzong TSENG | Medium

October 9, 2020 - Then what ? Let’s try build the tensorflow package from source. Following the guide on the ROCm tensorflow-upstream, with a slight modification on running ./configure to enable ROCm and have CPU optimization with -march=native flag.

AMD

amd.com › https://www.amd.com/en.html › developer central › ml development with amd radeon™

Getting Started Guide: Using AMD ROCm™ Software on Radeon™ GPUs

May 22, 2025 - Support for Hugging Face models and tools on Radeon GPUs using ROCm, allowing users to unlock the full potential of LLMs on their desktop systems.

AMD ROCm

rocm.docs.amd.com

AMD ROCm documentation — ROCm Documentation

ROCm supports multiple programming languages and programming interfaces such as HIP, OpenCL, and OpenMP, as explained in the Programming guide.