3 Commits

Author SHA1 Message Date
97eb7a281d torchdim Python port (#160236)
The big semantic change (and the reason for this port) is that we no longer monkeypatch Tensor with torchdim's special methods. The new algorithm for handling dispatch is that we first land in `__torch_function__` and we see if a special FCD implementation needs to be dispatch to first, and if there is nothing we fallback to the standard level strategy.

Because there is no longer C binding equivalent of classes, we've condensed _C.Dim and Dim together, and similar for Tensor. This resulted in some bugs as the Python API is sometimes different from the C API. I've attempted to disambiguate these but there may still be mistakes (many early bugs were due to this problem). Dim and DimEntry are especially painful as Dim must abide by Tensor equality semantics, but is pointer equality in C (DimEntry doesn't have this problem). Another difference between C/Python that is subtle is we no longer get implicit conversions from Dim to DimEntry, this also caused some bugs.

Much of the mechanical porting work was done by claude code. I have a separate PR that deletes functorch._C, but it was useful having dim.cpp to point claude at it so I haven't done it in this PR. From a reviewing perspective, I need to re-review that I didn't forget to port anything, some noticeably missing "small" things are patched_dim_method. I am still in progress of carefully doing a side-by-side review of ports; "simplifications" from claude code were also a major source of bugs.

There are two major feature gaps in the implementation:

- DelayedTensor and dot handling are not implemented yet. This should be reasonably easy, just need to do it.  However, for the purposes of sharded propagation it is actually better not to reconstruct matmuls.
- Splitting dimensions with an index like `[x, y]` doesn't work. The problem is that `__getitem__` interprets this as advanced indexing and sends the list to torch.tensor to turn into a tensor, instead of being eligible for `__torch_function__`. I think I might need to hard code a special case for this or something?

Signed-off-by: Edward Yang <ezyang@meta.com>

Pull Request resolved: https://github.com/pytorch/pytorch/pull/160236
Approved by: https://github.com/zdevito, https://github.com/albanD
2025-09-21 03:01:04 +00:00
e6ec0efaf8 Apply UFMT to all non test/torch files (#106205)
Signed-off-by: Edward Z. Yang <ezyang@meta.com>

Pull Request resolved: https://github.com/pytorch/pytorch/pull/106205
Approved by: https://github.com/albanD
2023-07-29 02:56:24 +00:00
d05a11337c [CMake] Add functorch target (#83464)
Move functorch/functorch into `functorch` folder
- Add functorch/CMakeLists.txt that adds `functorch` native python exension
- Modify `setup.py` to package pytorch and functorch together into a single wheel
- Modify `functorch.__version__` is not equal to that of `torch.__version__`
- Add dummy `functorch/setup.py` file for the projects that still want to build it

Differential Revision: [D39058811](https://our.internmc.facebook.com/intern/diff/D39058811)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/83464
Approved by: https://github.com/zou3519
2022-09-14 00:05:33 +00:00