Commit Graph

10 Commits (919b599ebe57b1402b1aca21fa54799cc1e0cd91)

Author SHA1 Message Date
Suraj Sudhir cba91a9b96
[ONNX][TOSA] Adds ONNX to TOSA e2e tests (#3358)
- Refactors OnnxBackend to be generic and consume any Torch backend.

---------

Signed-off-by: Suraj Sudhir <suraj.sudhir@arm.com>
2024-05-16 21:44:26 -07:00
Suraj Sudhir 0ca88028cd
[FxImporter][TOSA] Enable FxImporter to TOSA e2e tests (#3349)
Signed-off-by: Suraj Sudhir <suraj.sudhir@arm.com>
2024-05-15 14:37:30 -07:00
Stella Laurenzo 6877302504
[NFC reformat] Applies pre-commit formatting to Python files. (#3244)
This is a large change because prior to this point, Python files in the
project were not consistently formatted. This reformats them all with
black defaults.

Based on experience with prior projects, if you have a dev/long-term
branch with Python patches, you can minimize merge conflicts prior to
rebasing to include this commit by running `black` on your modified
Python files, squashing, and then rebasing/merging.
2024-04-27 14:16:31 -07:00
penguin_wwy 0a6073414d
[FxImporter] Add fx importer to stablehlo e2e test config (#3183) 2024-04-18 21:29:17 -07:00
Rob Suderman 0e77de996a
[torch] Add support for `torch.view` with dynamic shapes (#3164)
We can map to `tensor.reshape` for handling multiple output dynamic
shapes. Later we can perform a more complex analysis for indentifying
expand/collapse cases from the tensor.reshape.

Initially we planned to handle this identification at the `torch` level
however it will be easier to handle once converted to core
mlir-dialects.
2024-04-18 11:47:19 -07:00
penguin_wwy 10b6062d41
[CI] Enable the tests for fx_importer in the CI (#3168)
Replace the torchdynamo e2e with the fx_importer e2e
2024-04-15 21:20:23 -07:00
penguin_wwy 45eaeaaf36
[FxImporter] Add FxImporter config in e2e-test (#3151) 2024-04-12 16:07:56 -07:00
Rob Suderman 074f112d6a
[onnx] Add testing using the `onnx` compilation using torch tests (#2795)
We can route the torch tests via `onnx` using the `torch.onnx.export`
tooling. We can then reimport, lower to torch, and compile to linalg to
validate the onnx path is working correctly.

The current implementation exposes some failures in the `onnx` path so
we cannot enable the onnx test suite yet due to segmentation faults.
2024-02-15 10:17:13 -08:00
Yuanqiang Liu f3e8199a6d
[Stablehlo] add refbackend (#2712) 2024-02-16 01:08:48 +08:00
Stella Laurenzo 6961f0a247
Re-organize project structure to separate PyTorch dependencies from core project. (#2542)
This is a first step towards the structure we discussed here:
https://gist.github.com/stellaraccident/931b068aaf7fa56f34069426740ebf20

There are two primary goals:

1. Separate the core project (C++ dialects and conversions) from the
hard PyTorch dependencies. We move all such things into projects/pt1 as
a starting point since they are presently entangled with PT1-era APIs.
Additional work can be done to disentangle components from that
(specifically LTC is identified as likely ultimately living in a
`projects/ltc`).
2. Create space for native PyTorch2 Dynamo-based infra to be upstreamed
without needing to co-exist with the original TorchScript path.

Very little changes in this path with respect to build layering or
options. These can be updated in a followup without commingling
directory structure changes.

This also takes steps toward a couple of other layering enhancements:

* Removes the llvm-external-projects/torch-mlir-dialects sub-project,
collapsing it into the main tree.
* Audits and fixes up the core C++ build to account for issues found
while moving things. This is just an opportunistic pass through but
roughly ~halves the number of build actions for the project from the
high 4000's to the low 2000's.

It deviates from the discussed plan by having a `projects/` tree instead
of `compat/`. As I was thinking about it, this will better accommodate
the follow-on code movement.

Once things are roughly in place and the CI passing, followups will
focus on more in-situ fixes and cleanups.
2023-11-02 19:45:55 -07:00