torch-mlir

Commit Graph

Author	SHA1	Message	Date
Stella Laurenzo	bc7c852379	Add more ops from the original integration. * Still need to add a systematic mechanism for discovering gradient ops. * Work needed on the various _ suffixed inplace ops. * Other randoms still not mapped. * Outside of this commit, I do have enough commented/reworked to roughly build but that will take another handful of commits to get going.	2020-09-18 19:11:18 -07:00
Stella Laurenzo	d1ed6d260e	Initial work on a torch op registry. * This extracts metadata from python invocations (nearly) sufficient to generate ODS and a Torch IR translation table for most of the ops. * It also has the side effect of creating a data structure with meaningfully runnable examples suitable for an automated regression test. * There are some ops that are sufficiently complex/weird (like _convolution) that we'll just manually handle those. * See example output: https://gist.github.com/stellaraccident/60a58457b15e9184e224fa98a2658769	2020-08-28 15:20:55 -07:00

Author

SHA1

Message

Date

Stella Laurenzo

bc7c852379

Add more ops from the original integration.

* Still need to add a systematic mechanism for discovering gradient ops.
* Work needed on the various _ suffixed inplace ops.
* Other randoms still not mapped.
* Outside of this commit, I do have enough commented/reworked to roughly build but that will take another handful of commits to get going.

2020-09-18 19:11:18 -07:00

Stella Laurenzo

d1ed6d260e

Initial work on a torch op registry.

* This extracts metadata from python invocations (nearly) sufficient to generate ODS and a Torch IR translation table for most of the ops.
* It also has the side effect of creating a data structure with meaningfully runnable examples suitable for an automated regression test.
* There are some ops that are sufficiently complex/weird (like _convolution) that we'll just manually handle those.
* See example output: https://gist.github.com/stellaraccident/60a58457b15e9184e224fa98a2658769

2020-08-28 15:20:55 -07:00

2 Commits (c69e9fabc5c3b148722335610fe6844f9bdbe137)