* For python projects that don't need JIT/ExecutionEngine, cuts the number of files to compile roughly in half (with similar reduction in end binary size).
Differential Revision: https://reviews.llvm.org/D106992
* The PybindAdaptors.h file has been evolving across different sub-projects (npcomp, circt) and has been successfully used for out of tree python API interop/extensions and defining custom types.
* Since sparse_tensor.encoding is the first in-tree custom attribute we are supporting, it seemed like the right time to upstream this header and use it to define the attribute in a way that we can support for both in-tree and out-of-tree use (prior, I had not wanted to upstream dead code which was not used in-tree).
* Adapted the circt version of `mlir_type_subclass`, also providing an `mlir_attribute_subclass`. As we get a bit of mileage on this, I would like to transition the builtin types/attributes to this mechanism and delete the old in-tree only `PyConcreteType` and `PyConcreteAttribute` template helpers (which cannot work reliably out of tree as they depend on internals).
* Added support for defaulting the MlirContext if none is passed so that we can support the same idioms as in-tree versions.
There is quite a bit going on here and I can split it up if needed, but would prefer to keep the first use and the header together so sending out in one patch.
Differential Revision: https://reviews.llvm.org/D102144
This will allow the bindings to be built as a library and reused in out-of-tree
projects that want to provide bindings on top of MLIR bindings.
Reviewed By: stellaraccident, mikeurbach
Differential Revision: https://reviews.llvm.org/D101075
This revision adds support to properly add the body of registered
builtin named linalg ops.
At this time, indexing_map and iterator_type support is still
missing so the op is not executable yet.
Differential Revision: https://reviews.llvm.org/D99578
* IRModules.cpp -> (IRCore.cpp, IRAffine.cpp, IRAttributes.cpp, IRTypes.cpp).
* The individual pieces now compile in the 5-15s range whereas IRModules.cpp was starting to approach a minute (didn't capture a before time).
* More fine grained splitting is possible, but this represents the most obvious.
Differential Revision: https://reviews.llvm.org/D98978
This offers the ability to create a JIT and invoke a function by passing
ctypes pointers to the argument and the result.
Differential Revision: https://reviews.llvm.org/D97523
This only exposes the ability to round-trip a textual pipeline at the
moment.
To exercise it, we also bind the libTransforms in a new Python extension. This
does not include any interesting bindings, but it includes all the
mechanism to add separate native extensions and load them dynamically.
As such passes in libTransforms are only registered after `import
mlir.transforms`.
To support this global registration, the TableGen backend is also
extended to bind to the C API the group registration for passes.
Reviewed By: stellaraccident
Differential Revision: https://reviews.llvm.org/D90819
* All functions that return an Operation now return an OpView.
* All functions that accept an Operation now accept an _OperationBase, which both Operation and OpView extend and can resolve to the backing Operation.
* Moves user-facing instance methods from Operation -> _OperationBase so that both can have the same API.
* Concretely, this means that if there are custom op classes defined (i.e. in Python), any iteration or creation will return the appropriate instance (i.e. if you get/create an std.addf, you will get an instance of the mlir.dialects.std.AddFOp class, getting full access to any custom API it exposes).
* Refactors all __eq__ methods after realizing the proper way to do this for _OperationBase.
Differential Revision: https://reviews.llvm.org/D90584
* Still rough edges that need more sugar but the bones are there. Notes left in the test case for things that can be improved.
* Does not actually yield custom OpViews yet for traversing. Will rework that in a followup.
Differential Revision: https://reviews.llvm.org/D89932
Summary:
* Native '_mlir' extension module.
* Python mlir/__init__.py trampoline module.
* Lit test that checks a message.
* Uses some cmake configurations that have worked for me in the past but likely needs further elaboration.
Subscribers: mgorny, mehdi_amini, rriddle, jpienaar, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, stephenneuendorffer, Joonsoo, grosul1, Kayjukh, jurahul, msifontes
Tags: #mlir
Differential Revision: https://reviews.llvm.org/D83279
Stella Laurenzo