MAmathisfun123·Oct 20, 2026
lol no this is a replacement for https://github.com/pytorch/xla
In Google open-sources TorchTPU, a native PyTorch back end for TPUspytorch
xla
C++2019–2026
pytorch / xla
xla
Enabling PyTorch on XLA Devices (e.g. Google TPU)
12Distinct people
14Mentions
0Explicit recommenders
2.8KGitHub stars
What to know before exploring
What it is
Enabling PyTorch on XLA Devices (e.g. Google TPU)
GitHub
Where it is used
No documented product use was verified in the last source check.
What people are saying
No recommendation phrase was found in the indexed comments.
No classified warning is attached to this page. Read the discussions before treating silence as approval.
Also in these discussions
No other repository is repeatedly linked in the same discussions.
This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:03:16 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 year14 dated mentions
Observed mentions: 2019-05-08 10:26:20 UTC to 2026-10-20 17:47:18 UTC.
* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2019 | 2019-01-01 00:00:00 UTC | 2020-01-01 00:00:00 UTC | 6 | 2 | 4 |
| 2020 | 2020-01-01 00:00:00 UTC | 2021-01-01 00:00:00 UTC | 3 | 0 | 3 |
| 2021 | 2021-01-01 00:00:00 UTC | 2022-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2025 | 2025-01-01 00:00:00 UTC | 2026-01-01 00:00:00 UTC | 2 | 1 | 1 |
| 2026 (partial) | 2026-01-01 00:00:00 UTC | 2027-01-01 00:00:00 UTC | 1 | 0 | 1 |
What Hacker News says
14 sourcesRFC: Evolving PyTorch/XLA for a more native experience on TPU
3 points · Open discussionIf only things were simple [0].
[0] https://github.com/pytorch/xla/issues/9189
In Nvidia Pushes Further into Cloud with GPU Marketplace>Cheers,
> The PyTorch/XLA Team at Google
Meanwhile you have an issue from 5 years ago with 0 support
https://github.com/pytorch/xla/issues/202
In Who uses Google TPUs for inference in production?We both know (and correct me if I'm wrong) that this is an issue with the GCP cloud architecture. https://github.com/pytorch/xla/issues/1858
So you can't blame the PyTorch team. If there's anyone to blame, it's Google Cloud. In the meantime, I don't think there's any harm advertising PyTorch with TPU support if running on TPUs with PyTorch is often much faster than running on GPUs with PyTorch.
In Grid: AI platform from the makers of PyTorch LightningPyTorch already has TPU support via XLA and has been used in research at the scale of billions of parameters.
https://github.com/pytorch/xla
In Standardizing OpenAI’s deep learning framework on PyTorch(I'm one of the Cloud TPU product leads)
We've seen multiple BERT-related PyTorch models training successfully on Cloud TPUs, including training at scale on large, distributed Cloud TPU Pod slices.
Would you consider filing a GitHub issue at https://github.com/pytorch/xla or emailing pytorch-tpu@googlegroups.com to provide a bit more context about the specific issue you encountered?
Here's the current PyTorch/TPU troubleshooting guide, which provides information on how to collect and interpret metrics that are very helpful for debugging:
https://github.com/pytorch/xla/blob/master/TROUBLESHOOTING.m...
Thanks!
In Predicting where AI is going in 2020We have been working with G on TPU support for PyTorch. Have you tried it out? https://github.com/pytorch/xla
In Tensorflow User ExperienceYeah, generally a cloud based approach to training models is better than on your mac. AMD folks have been working on RoCM for some time and it works reasonably well for common models but the AMD GPU HW isn't pervasive like Nvidia GPUs in places like AWS.
If you are looking at using Colab for prototyping, you can also try TPUs which are now supported for PyTorch. Here is the link some additional info including some Colab NBs: https://github.com/pytorch/xla
In 16-inch MacBook ProGitHub – Pytorch/Xla: Enabling PyTorch on Google TPU
8 points · Open discussion> If you switch to PyTorch, what are you going to use for prod deployment? Is there any way to use TPUs?
PyTorch has an optional XLA device, that let's you use TPUs: https://github.com/pytorch/xla
In Tensorflow 2.0Well you'll be glad to know that PyTorch is available (in development form) on the TPU: https://github.com/pytorch/xla
In Google’s Cloud TPU Pods are now publicly available in beta