Commit Graph

17 Commits

Author SHA1 Message Date
Stella Laurenzo a6e7d024a9 [mlir][python] Add pyi stub files to enable auto completion.
There is no completely automated facility for generating stubs that are both accurate and comprehensive for native modules. After some experimentation, I found that MyPy's stubgen does the best at generating correct stubs with a few caveats that are relatively easy to fix:
  * Some types resolve to cross module symbols incorrectly.
  * staticmethod and classmethod signatures seem to always be completely generic and need to be manually provided.
  * It does not generate an __all__ which, from testing, causes namespace pollution to be visible to IDE code completion.

As a first step, I did the following:
  * Ran `stubgen` for `_mlir.ir`, `_mlir.passmanager`, and `_mlirExecutionEngine`.
  * Manually looked for all instances where unnamed arguments were being emitted (i.e. as 'arg0', etc) and updated the C++ side to include names (and re-ran stubgen to get a good initial state).
  * Made/noted a few structural changes to each `pyi` file to make it minimally functional.
  * Added the `pyi` files to the CMake rules so they are installed and visible.

To test, I added a `.env` file to the root of the project with `PYTHONPATH=...` set as per instructions. Then reload the developer window (in VsCode) and verify that completion works for various changes to test cases.

There are still a number of overly generic signatures, but I want to check in this low-touch baseline before iterating on more ambiguous changes. This is already a big improvement.

Differential Revision: https://reviews.llvm.org/D114679
2021-11-29 19:58:58 -08:00
Uday Bondhugula c89fc1eec3 [MLIR] NFC. Rename MLIR CAPI ExecutionEngine target for consistency
Rename MLIR CAPI ExecutionEngine target for consistency:
MLIRCEXECUTIONENGINE -> MLIRCAPIExecutionEngine in line with other
targets.

Differential Revision: https://reviews.llvm.org/D114596
2021-11-26 00:23:17 +05:30
Stella Laurenzo 132bc6e2d4 Re-apply "[mlir] Allow out-of-tree python building from installed MLIR."
Re-applies D111513:
* Adds a full-fledged Python example dialect and tests to the Standalone example (need to do a bit of tweaking in the top level CMake and lit tests to adapt better to if not building with Python enabled).
* Rips out remnants of custom extension building in favor of pybind11_add_module which does the right thing.
* Makes python and extension sources installable (outputs to src/python/${name} in the install tree): Both Python and C++ extension sources get installed as downstreams need all of this in order to build a derived version of the API.
* Exports sources targets (with our properties that make everything work) by converting them to INTERFACE libraries (which have export support), as recommended for the forseeable future by CMake devs. Renames custom properties to start with lower-case letter, as also recommended/required (groan).
* Adds a ROOT_DIR argument to declare_mlir_python_extension since now all C++ sources for an extension must be under the same directory (to line up at install time).
* Downstreams will need to adapt by:

  * Remove absolute paths from any SOURCES for declare_mlir_python_extension (I believe all downstreams are just using ${CMAKE_CURRENT_SOURCE_DIR} here, which can just be ommitted). May need to set ROOT_DIR if not relative to the current source directory.
  * To allow further downstreams to install/build, will need to make sure that all C++ extension headers are also listed under SOURCES for declare_mlir_python_extension.

This reverts commit 1a6c26d1f5.

Reviewed By: stephenneuendorffer

Differential Revision: https://reviews.llvm.org/D113732
2021-11-14 20:31:34 -08:00
Mehdi Amini 1a6c26d1f5 Revert "[mlir] Allow out-of-tree python building from installed MLIR."
This reverts commit c7be8b7539.

Build is broken (multiple buildbots)
2021-11-12 02:30:53 +00:00
Stella Laurenzo c7be8b7539 [mlir] Allow out-of-tree python building from installed MLIR.
* Depends on D111504, which provides the boilerplate for building aggregate shared libraries from installed MLIR.
* Adds a full-fledged Python example dialect and tests to the Standalone example (need to do a bit of tweaking in the top level CMake and lit tests to adapt better to if not building with Python enabled).
* Rips out remnants of custom extension building in favor of `pybind11_add_module` which does the right thing.
* Makes python and extension sources installable (outputs to src/python/${name} in the install tree): Both Python and C++ extension sources get installed as downstreams need all of this in order to build a derived version of the API.
* Exports sources targets (with our properties that make everything work) by converting them to INTERFACE libraries (which have export support), as recommended for the forseeable future by CMake devs. Renames custom properties to start with lower-case letter, as also recommended/required (groan).
* Adds a ROOT_DIR argument to `declare_mlir_python_extension` since now all C++ sources for an extension must be under the same directory (to line up at install time).
* Need to validate against a downstream or two and adjust, prior to submitting.

Downstreams will need to adapt by:

* Remove absolute paths from any SOURCES for `declare_mlir_python_extension` (I believe all downstreams are just using `${CMAKE_CURRENT_SOURCE_DIR}` here, which can just be ommitted). May need to set `ROOT_DIR` if not relative to the current source directory.
* To allow further downstreams to install/build, will need to make sure that all C++ extension headers are also listed under SOURCES for `declare_mlir_python_extension`.

Reviewed By: stephenneuendorffer, mikeurbach

Differential Revision: https://reviews.llvm.org/D111513
2021-11-11 18:04:31 -08:00
Stella Laurenzo d86688fb1f [mlir][python] Segment MLIR Python test dialect to avoid testonly dependency.
With https://reviews.llvm.org/rG14c9207063bb00823a5126131e50c93f6e288bd3, the build is broken with -DMLIR_INCLUDE_TESTS=OFF. This patch fixes the build and we may want to do a better fix to the layering in a followup.

Differential Revision: https://reviews.llvm.org/D112560
2021-10-26 18:47:36 +00:00
Alex Zinenko 14c9207063 [mlir] support interfaces in Python bindings
Introduce the initial support for operation interfaces in C API and Python
bindings. Interfaces are a key component of MLIR's extensibility and should be
available in bindings to make use of full potential of MLIR.

This initial implementation exposes InferTypeOpInterface all the way to the
Python bindings since it can be later used to simplify the operation
construction methods by inferring their return types instead of requiring the
user to do so. The general infrastructure for binding interfaces is defined and
InferTypeOpInterface can be used as an example for binding other interfaces.

Reviewed By: gysit

Differential Revision: https://reviews.llvm.org/D111656
2021-10-25 12:50:42 +02:00
Alex Zinenko 2b55e14384 [mlir] fix python bindings cmake 2021-10-13 17:29:45 +02:00
Mogball a54f4eae0e [MLIR] Replace std ops with arith dialect ops
Precursor: https://reviews.llvm.org/D110200

Removed redundant ops from the standard dialect that were moved to the
`arith` or `math` dialects.

Renamed all instances of operations in the codebase and in tests.

Reviewed By: rriddle, jpienaar

Differential Revision: https://reviews.llvm.org/D110797
2021-10-13 03:07:03 +00:00
Alex Zinenko 3a3a09f654 [mlir][python] Provide more convenient wrappers for std.ConstantOp
Constructing a ConstantOp using the default-generated API is verbose and
requires to specify the constant type twice: for the result type of the
operation and for the type of the attribute. It also requires to explicitly
construct the attribute. Provide custom constructors that take the type once
and accept a raw value instead of the attribute. This requires dynamic dispatch
based on type in the constructor. Also provide the corresponding accessors to
raw values.

In addition, provide a "refinement" class ConstantIndexOp similar to what
exists in C++. Unlike other "op view" Python classes, operations cannot be
automatically downcasted to this class since it does not correspond to a
specific operation name. It only exists to simplify construction of the
operation.

Depends On D110946

Reviewed By: stellaraccident

Differential Revision: https://reviews.llvm.org/D110947
2021-10-04 11:45:27 +02:00
Alex Zinenko 93a6b49d38 [mlir][python] provide bindings for ops from the sparse_tensor dialect
Previously, the dialect was exposed for linking and pass management purposes,
but we did not generate op classes for it. Generate them.

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D110819
2021-09-30 15:53:16 +02:00
Alex Zinenko 8c1b785ce1 [mlir][python] provide bindings for the SCF dialect
This is an important core dialect that has not been exposed previously. Set up
the default bindings generation and provide a nicer wrapper for the `for` loop
with access to the loop configuration and body.

Depends On D110758

Reviewed By: stellaraccident

Differential Revision: https://reviews.llvm.org/D110759
2021-09-30 09:38:15 +02:00
Stella Laurenzo cb7b03819a [mlir][python] Simplify python extension loading.
* Now that packaging has stabilized, removes old mechanisms for loading extensions, preferring direct importing.
* Removes _cext_loader.py, _dlloader.py as unnecessary.
* Fixes the path where the CAPI dll is written on Windows. This enables that path of least resistance loading behavior to work with no further drama (see: https://bugs.python.org/issue36085).
* With this patch, `ninja check-mlir` on Windows with Python bindings works for me, modulo some failures that are actually due to a couple of pre-existing Windows bugs. I think this is the first time the Windows Python bindings have worked upstream.
* Downstream changes needed:
  * If downstreams are using the now removed `load_extension`, `reexport_cext`, etc, then those should be replaced with normal import statements as done in this patch.

Reviewed By: jdd, aartbik

Differential Revision: https://reviews.llvm.org/D108489
2021-09-03 00:43:28 +00:00
Stella Laurenzo 5b2e7f50a6 [MLIR][python] Export CAPI headers.
* Adds source targets (not included in the full set that downstreams use by default) to bundle mlir-c/ headers into the mlir/_mlir_libs/include directory.
* Adds a minimal entry point to get include and library directories.
* Used by npcomp to export a full CAPI (which is then used by the Torch extension to link npcomp).

Reviewed By: mikeurbach

Differential Revision: https://reviews.llvm.org/D107090
2021-07-29 19:06:32 +00:00
Stella Laurenzo 0cdf491501 Break apart the MLIR ExecutionEngine from core python module.
* 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
2021-07-28 23:59:32 +00:00
Stella Laurenzo 310c9496d8 Re-engineer MLIR python build support.
* Implements all of the discussed features:
  - Links against common CAPI libraries that are self contained.
  - Stops using the 'python/' directory at the root for everything, opening the namespace up for multiple projects to embed the MLIR python API.
  - Separates declaration of sources (py and C++) needed to build the extension from building, allowing external projects to build custom assemblies from core parts of the API.
  - Makes the core python API relocatable (i.e. it could be embedded as something like 'npcomp.ir', 'npcomp.dialects', etc). Still a bit more to do to make it truly isolated but the main structural reset is done.
  - When building statically, installed python packages are completely self contained, suitable for direct setup and upload to PyPi, et al.
  - Lets external projects assemble their own CAPI common runtime library that all extensions use. No more possibilities for TypeID issues.
  - Begins modularizing the API so that external projects that just include a piece pay only for what they use.
* I also rolled in a re-organization of the native libraries that matches how I was packaging these out of tree and is a better layering (i.e. all libraries go into a nested _mlir_libs package). There is some further cleanup that I resisted since it would have required source changes that I'd rather do in a followup once everything stabilizes.
* Note that I made a somewhat odd choice in choosing to recompile all extensions for each project they are included into (as opposed to compiling once and just linking). While not leveraged yet, this will let us set definitions controlling the namespacing of the extensions so that they can be made to not conflict across projects (with preprocessor definitions).
* This will be a relatively substantial breaking change for downstreams. I will handle the npcomp migration and will coordinate with the circt folks before landing. We should stage this and make sure it isn't causing problems before landing.
* Fixed a couple of absolute imports that were causing issues.

Differential Revision: https://reviews.llvm.org/D106520
2021-07-27 15:54:58 +00:00
Stella Laurenzo 9f3f6d7bd8 Move MLIR python sources to mlir/python.
* NFC but has some fixes for CMake glitches discovered along the way (things not cleaning properly, co-mingled depends).
* Includes previously unsubmitted fix in D98681 and a TODO to fix it more appropriately in a smaller followup.

Differential Revision: https://reviews.llvm.org/D101493
2021-05-03 18:36:48 +00:00