Commit Graph

5 Commits (81119aa0a10d1ee759ac0641e406b89a793a7a48)

Author SHA1 Message Date
Stella Laurenzo 9e52f6235b More progress on PyTorch acap device capture.
* Now gets far enough to capture batch_norm.
* Has some issues still with in-place ops.
* Can materialize constants.
* Includes an upgrade to PyTorch nightly, which has important bug fixes for fallback and boxed kernel dispatch.
* Fixes #78, #79, #80.
* Will do more testing in a follow-up once further bugs are fixed that facilitate getting at the other features.
2020-10-15 21:43:21 -07:00
Stella Laurenzo ad3ddb9edb Implement torch.kernel_call capture.
* Had to stop short of modifying the function return signature because of a missing C-API upstream.
* Committing here is good enough for a test and will resolve the various TODOs about upstream APIs next.
2020-10-06 21:54:28 -07:00
Stella Laurenzo e5433e314f Add capture function arguments.
* Adds at::Tensor -> MlirValue tracking.
* Adds conversions for tensor and scalar types to MLIR types.
* Adds npcomp C APIs for constructing custom types.
* Reworks pybind include so as to get Torch pybind helpers (needed to pass at::Tensor type from Python->C++).
2020-10-01 18:59:58 -07:00
Stella Laurenzo ba03ecc652 Add public API for constructing a module/function to capture PyTorch ops.
* Uses the MLIR-C API since that will save us a lot of grief down the road (i.e. will give PyTorch and libMLIR/libNPCOMP the ability to skew version-wise).
* Quite a few TODOs and not yet populating the function in any way.
2020-09-29 14:23:22 -07:00
Stella Laurenzo b5f010284f Add boilerplate to do device capture (pytorch 1.6).
* Uses the new dispatcher API.
* Just prints to the console for the moment when an op is captured.
* Executes the op through the existing implementation.
2020-09-28 10:30:54 -07:00