I'd like to propose a new module `Out-of-tree Backend Integration` via `PrivateUse1` device key. The out-of-tree backend integration via `PrivateUse1` device key has been a recommended mechanism of plug-in third-party accelerator devices into PyTorch. There are already quite a few documents/tutorials on the usage with the primary one as https://docs.pytorch.org/docs/main/accelerator/index.html.
We also saw more and more HW vendors to leverage the `PrivateUse1` mechanism to support their accelerators. For example:
1. Ascend NPU
2. Microsoft MAIA
3. MooreThreads MUSA
4. Cambricon MLU
The scope of `PrivateUse1` based out-of-tree backend integration is composed of two parts:
1. `PrivateUse1` device as an out-of-tree backend that involves:
(a) make `PrivateUse1` a function-complete device as other in-tree devices: i.e., device runtime, autograd, autocast, profiling, distributed, quantization etc.
(b) a pluggable design to allow out-of-tree integration to extend the functionality of `PrivateUse1` such as a backend registration mechanism that allows user-friendly device naming, runtime extension points with either C++ and Python for third-party to plug-in their runtime implementation, customizable tensor implementation for third-party to add extra info/functionality to the tensor and their serialization.
2. OpenReg: A test suite and documentation effort to guarantee the functional correctness of `PrivateUse1` mechanism and to guide HW vendors with the right implementation.
I'm also proposing @FFFrog as the module maintainer for this new module due to his continuous contribution to the design and implementation both parts of the module. Below are the RFCs/Feature Proposals @FFFrog was working on:
1. [An improvement of PrivateUse1 mechanism, facilitating third-party backend integration](https://docs.google.com/document/d/1_2EO5A2Ww3xDwqbhIvs9Nk65-jV0oNYg3XAmNUsHdAY/edit?tab=t.0#heading=h.5vt8c1vo4dc7)
2. [The interoperability Standard of Third-party Backend Integration Mechanism](9bd181e742/RFC-0037-Interoperability-Standard-of-3rd-Backend-Integration-Mechanism.md)
3. [PyTorch Backend Accelerator Integration Verification and Guidance](f6048cbd4f/RFC-0045-PyTorch-Accelerator-Integration-Enhancements.md)
@FFFrog contributed 240+ PRs and a majority of them is related to `PrivateUse1`. (https://github.com/pytorch/pytorch/pulls?q=is%3Apr+author%3Afffrog+). He also reviewed 50+ PRs related to this area. He is also the primary author of OpenReg.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/165958
Approved by: https://github.com/albanD, https://github.com/malfet, https://github.com/ezyang
- Move community and language binding links to the horizontal bar
- Add an intro to the community page.
- Fix the link in the ogp_image
- Fix the link in the version switcher
- Clean up unneeded links
Pull Request resolved: https://github.com/pytorch/pytorch/pull/153090
Approved by: https://github.com/albanD
This file didn't had an overall in a few years so long overdue. Most of the credit goes to @orionr for gathering all of this info.
The main rules we followed:
- No code contributor is removed, they're all placed as emeritus
- Breakdown too big categories to make this document useful to know who to ping
- No category where the code is still in the codebase is removed
- We did not rework the categories (for example to be closer to module: labels) and leave that for later
- All non-emeritus names are ordered by their number of comments on issues related to their topic
Pull Request resolved: https://github.com/pytorch/pytorch/pull/136672
Approved by: https://github.com/eqy, https://github.com/ezyang, https://github.com/seemethere, https://github.com/malfet
The following are all constrained under the ONNX exporter project scope.
- `personal_of_interest.rst`
- Moving folks no longer working on the project to emeritus.
- Adding @justinchuby, @titaiwangms, @shubhambhokare1 and @xadupre,
who have all made countless contributions to this project.
- `CODEOWNERS`
- Removing folks no longer working on the project.
- Updating new owners who will now be notified with PRs related to
the specific file paths.
- `merge_rules.yaml`
- Removing folks no longer working on the project.
🫡
Co-authored-by: Justin Chu <justinchuby@users.noreply.github.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/126364
Approved by: https://github.com/titaiwangms, https://github.com/justinchuby, https://github.com/albanD
Fixed following errors in contribution guide.
"deep neural networks using a **on** tape-based autograd systems." to "deep neural networks **using a tape-based** autograd systems."
"the best entrance **point** and are great places to start." to "the best entrance **points** and are great places to start."
Pull Request resolved: https://github.com/pytorch/pytorch/pull/95454
Approved by: https://github.com/ezyang
Corrected the grammar of a sentence in "Implementing Features or Fixing Bugs" section of the contribution guide.
**Before:**
Issues that are labeled first-new-issue, low, or medium priority provide the best entrance point are great places to start.
**After:**
Issues that are labeled first-new-issue, low, or medium priority provide the best entrance point _and_ are great places to start.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/93014
Approved by: https://github.com/albanD, https://github.com/kit1980
Fixes#83363
This is not a full update yet, but fixes some obvious things: missing modules (torchrec, sparse) and brings a few people from merge_rules.json who are working on the respective modules. There are still discrepancies - e.g. Intel CPU work is split in many categories in merge_rules, but it's better to improve things incrementally.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/84772
Approved by: https://github.com/b0noI, https://github.com/malfet
