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ROCm
pytorch
Python2019–2024
ROCm / pytorch

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration. To use PyTorch with latest ROCm releases, see: https://rocm.docs.amd.com/en/latest/rocm-for-ai/pytorch.html

3Distinct people
3Mentions
0Explicit recommenders
261GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Tensors and Dynamic neural networks in Python with strong GPU acceleration. To use PyTorch with latest ROCm releases, see: https://rocm.docs.amd.com/en/latest/rocm-for-ai/pytorch.html

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Where it is used

No documented product use has been verified yet.

What people are saying

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This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year3 dated mentions

Observed mentions: 2019-11-13 14:55:37 UTC to 2024-02-14 00:53:26 UTC.

012019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20192020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20212022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC101
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC101
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC000
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC101

What Hacker News says

3 sources
> AMD's ROCm OCI base images, ROCm docs > "Install ROCm Docker containers" > Base Image: https://rocm.docs.amd.com/projects/install-on-linux/en/lates... links to ROCm/ROCm-docker: https://github.com/ROCm/ROCm-docker which is the source of docker.io/rocm/rocm-terminal: https://hub.docker.com/r/rocm/rocm-terminal : docker run -it --device=/dev/kfd --device=/dev/dri --group-add video rocm/rocm-terminal ROCm docs > "Docker image support matrix": https://rocm.docs.amd.com/projects/install-on-linux/en/lates... ROCm/ROCm-docker//dev/Dockerfile-centos-7-complete: https://github.com/ROCm/ROCm-docker/blob/master/dev/Dockerfi... Bazzite is a ublue (Universal Blue) fork of the Fedora Kinoite (KDE) or Fedora Silverblue (Gnome) rpm-ostree Linux distributions; ublue-os/bazzite//Containerfile : https://github.com/ublue-os/bazzite/blob/main/Containe
Read the rest
rfile#... has, in addition to fan and power controls, automatic updates on desktop, supergfxctl, system76-scheduler, and an fsync kernel: rpm-ostree install rocm-hip \ rocm-opencl \ rocm-clinfo But it's not `rpm-ostree install --apply-live` because its a Containerfile. To install a ublue-os distro, you install any of the Fedora ostree distros: {Silverblue, Kinoite, Sway Atomic, or Budgie Atomic} from e.g. a USB stick and then `rpm-ostree rebase <OCI_host_image_url>`: rpm-ostree rebase ostree-unverified-registry:ghcr.io/ublue-os/bazzite:stable rpm-ostree rebase ostree-unverified-registry:ghcr.io/ublue-os/bazzite-nvidia:stable rpm-ostree rebase ostree-image-signed: ublue-os/config//build/ublue-os-just/40-nvidia.just defines the `ujust configure-nvidia` and `ujust toggle-nvk` commands: https://github.com/ublue-os/config/blob/main/build/ublue-os-... There's a default `distrobox` with pytorch in ublue-os/config//build/ublue-os-just/etc-distrobox/apps.ini: https://github.com/ublue-os/config/blob/main/build/ublue-os-... [mlbox] image=nvcr.io/nvidia/pytorch:23.08-py3 additional_packages="nano git htop" init_hooks="pip3 install huggingface_hub tokenizers transformers accelerate datasets wandb peft bitsandbytes fastcore fastprogress watermark torchmetrics deepspeed" pre-init-hooks="/init_script.sh" nvidia=true pull=true root=false replace=false docker.io/rocm/pytorch: https://hub.docker.com/r/rocm/pytorch pytorch/builder//manywheel/Dockerfile: https://github.com/pytorch/builder/blob/main/manywheel/Docke... ROCm/pytorch//Dockerfile: https://github.com/ROCm/pytorch/blob/main/Dockerfile The ublue-os (and so also bazzite) OCI host image Containerfile has Sunshine installed; which is a 4k HDR 120fps remote desktop solution for gaming. There's a `ujust remove-sunshine` command in system_files/desktop/shared/usr/share/ublue-os/just/80-bazzite.just : https://github.com/ublue-os/bazzite/blob/main/system_files/d... and also kernel args for AMD: pstate-force-enable: rpm-ostree kargs --append-if-missing=amd_pstate=active ublue-os/config//Containerfile: https://github.com/ublue-os/config/blob/main/Containerfile LizardByte/Sunshine: https://github.com/LizardByte/Sunshine moonlight-stream https://github.com/moonlight-stream Anyways, hopefully this PR fixes the immediate issue: https://github.com/invoke-ai/InvokeAI/pull/5714/files conda-forge/pytorch-cpu-feedstock > "Add ROCm variant?": https://github.com/conda-forge/pytorch-cpu-feedstock/issues/... And Fedora supports OCI containers as host images and also podman container images with just systemd to respawn one or a pod of containers.
In AMD funded a drop-in CUDA implementation built on ROCm: It's now open-source
I think PyTorch support is decent, I use it on my Radeon VII a lot. - You can compile on https://lernapparat.de/pytorch-rocm/ (disclaimer my own link) - Arch has support out of the box: https://aur.archlinux.org/packages/python-pytorch-rocm/ - AMD also has a ROCm docker with PyTorch (https://rocmdocs.amd.com/en/latest/Deep_learning/Deep-learni...) - If you know the secret URL (which you can infer from the other URLs on the front page), there are also test wheels for rocm3.8. So AMD got a lot of heat for not supporting Navi (RDNA) with ROCm, but it seems that they are weeding out the things keeping people from running it ( https://github.com/ROCmSoftwarePlatform/pytorch/issues/718 and the links in that look like gfx10 is almost there for rocBlas and MIOpen). We'll see what ROCm 3.9 will bring and what the state of big navi is.
In AMD Reveals the Radeon RX 6000 Series, Coming November 18th

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