llvm-project/mlir/python
Stella Stamenova ac521d9ecd [mlir] Leverage CMake interface libraries for mlir python
This is already partially the case, but we can rely more heavily on interface libraries and how they are imported/exported in other to simplify the implementation of the mlir python functions in Cmake.

This change also makes a couple of other changes:
1) Add a new CMake function which handles "pure" sources. This was done inline previously
2) Moves the headers associated with CAPI libraries to the libraries themselves. These were previously managed in a separate source target. They can now be added directly to the CAPI libraries using DECLARED_HEADERS.
3) Cleanup some dependencies that showed up as an issue during the refactor

This is a big CMake change that should produce no impact on the build of mlir and on the produced *build tree*. However, this change fixes an issue with the *install tree* of mlir which was previously unusable for projects like torch-mlir because both the "pure" and "extension" targets were pointing to either the build or source trees.

Reviewed By: stellaraccident

Differential Revision: https://reviews.llvm.org/D128230
2022-06-28 10:42:58 -07:00
..
mlir Adding a named op for grouped convolutions 2022-06-23 16:32:22 +00:00
.style.yapf
CMakeLists.txt [mlir] Leverage CMake interface libraries for mlir python 2022-06-28 10:42:58 -07:00
requirements.txt Upstream MLIR PyTACO implementation. 2022-01-21 08:38:36 -08:00