This change aims to make bazel build more embeeding-friendly.
Namely, when PyTorch is included as an external repo in another project, it is usually included like this
```
native.local_repository(
name = "pytorch",
path = ...,
repo_mapping = repo_mapping,
)
```
Or
```
http_archive(
name = "pytorch",
urls = ...
repo_mapping = repo_mapping,
)
```
In this case, references to `@//` would resolve to the top-level WORKSPACE that includes PyTorch.
That makes upgrades harder because we need to carry around this patch.
Note that under some edge-case circumstances even `//` resolves to the top-level `WORKSPACE`.
This change makes the embedding of the bazel build easier without compromising anything for the main repo, since the `@pytorch//` still refers to the same thing.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/89660
Approved by: https://github.com/kit1980
Summary:
Fixes https://github.com/pytorch/pytorch/issues/35316
On master, bazel cuda build is disabled due to lack of a proper `cu_library` rule. This PR:
- Add `rules_cuda` to the WORKSPACE and forward `cu_library` to `rules_cuda`.
- Use a simple local cuda and cudnn repositories (adopted from TRTorch) for cuda 11.3.
- Fix current broken cuda build.
- Enable cuda build in CI, not just for `:torch` target but all the test binaries to catch undefined symbols.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66241
Reviewed By: ejguan
Differential Revision: D31544091
Pulled By: malfet
fbshipit-source-id: fd3c34d0e8f80fee06f015694a4c13a8e9e12206
Summary:
Including commits to fix Windows CI failure of enable distributed training on Windows PR
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45025
Reviewed By: beauby
Differential Revision: D23807995
Pulled By: mrshenli
fbshipit-source-id: a2f4c1684927ca66d7d3e9920ecb588fb4386f7c
