torch-mlir/test
Stella Laurenzo 860be09a39
Elide dynamic broadcast checks when in strict symbolic shapes mode. (#2496)
When importing dynamic shaped programs from Dynamo, via torch.compile or
torch.export, we can assume that strict symbolic shape checks have been
done prior to generating torch IR. Among other shape checking, this
eliminates the case where an unknown dimension can be dynamically '1' in
a way that signals a broadcast.

Adds a `isAssumingStrictSymbolicShapes` utility which consults a
`torch.assume_strict_symbolic_shapes` attribute on an enclosing scope
and returns true if present.

In the linalg pipeline, many runtime checks are elided when this returns
true.
2023-09-29 16:45:48 -07:00
..
CAPI test/CAPI/CMakeLists.txt: Depend on FileCheck (#2329) 2023-07-25 10:11:55 +02:00
Conversion Elide dynamic broadcast checks when in strict symbolic shapes mode. (#2496) 2023-09-29 16:45:48 -07:00
Dialect Integrate llvm-project and mlir-hlo. (#2454) 2023-09-12 15:09:57 -07:00
RefBackend [MLIR][TORCH] Add TorchConversionToMLProgram and MLProgramBufferize pass 2022-12-02 13:20:46 +05:30
python Add handling of namespaces to library generator (#2391) 2023-08-11 09:56:19 -07:00
CMakeLists.txt mhlo: migrate conversion to stablehlo (#1840) 2023-02-02 07:29:47 -06:00
lit.cfg.py Expose metadata of torch-mlir types (plus verify DictType key and value types). (#1785) 2023-01-16 10:25:02 -06:00
lit.site.cfg.py.in mhlo: migrate conversion to stablehlo (#1840) 2023-02-02 07:29:47 -06:00