This clarifies that this is an LLVM specific variable and avoids
potential conflicts with other projects.
Differential Revision: https://reviews.llvm.org/D119918
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 ${CMAKE_CURRENT_SOURCE_DIR} here, which can just be ommitted). May need to set ROOT_DIR if not relative to the current source directory.
* To allow further downstreams to install/build, will need to make sure that all C++ extension headers are also listed under SOURCES for declare_mlir_python_extension.
This reverts commit 1a6c26d1f5.
Reviewed By: stephenneuendorffer
Differential Revision: https://reviews.llvm.org/D113732
* Depends on D111504, which provides the boilerplate for building aggregate shared libraries from installed MLIR.
* Adds a full-fledged Python example dialect and tests to the Standalone example (need to do a bit of tweaking in the top level CMake and lit tests to adapt better to if not building with Python enabled).
* Rips out remnants of custom extension building in favor of `pybind11_add_module` which does the right thing.
* Makes python and extension sources installable (outputs to src/python/${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
* Incorporates a reworked version of D106419 (which I have closed but has comments on it).
* Extends the standalone example to include a minimal CAPI (for registering its dialect) and a test which, from out of tree, creates an aggregate dylib and links a little sample program against it. This will likely only work today in *static* MLIR builds (until the TypeID fiasco is finally put to bed). It should work on all platforms, though (including Windows - albeit I haven't tried this exact incarnation there).
* This is the biggest pre-requisite to being able to build out of tree MLIR Python-based projects from an installed MLIR/LLVM.
* I am rather nauseated by the CMake shenanigans I had to endure to get this working. The primary complexity, above and beyond the previous patch is because (with no reason given), it is impossible to export target properties that contain generator expressions... because, of course it isn't. In this case, the primary reason we use generator expressions on the individual embedded libraries is to support arbitrary ordering. Since that need doesn't apply to out of tree (which import everything via FindPackage at the outset), we fall back to a more imperative way of doing the same thing if we detect that the target was imported. Gross, but I don't expect it to need a lot of maintenance.
* There should be a relatively straight-forward path from here to rebase libMLIR.so on top of this facility and also make it include the CAPI.
Differential Revision: https://reviews.llvm.org/D111504
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
Port the translation of five dialects that define LLVM IR intrinsics
(LLVMAVX512, LLVMArmNeon, LLVMArmSVE, NVVM, ROCDL) to the new dialect
interface-based mechanism. This allows us to remove individual translations
that were created for each of these dialects and just use one common
MLIR-to-LLVM-IR translation that potentially supports all dialects instead,
based on what is registered and including any combination of translatable
dialects. This removal was one of the main goals of the refactoring.
To support the addition of GPU-related metadata, the translation interface is
extended with the `amendOperation` function that allows the interface
implementation to post-process any translated operation with dialect attributes
from the dialect for which the interface is implemented regardless of the
operation's dialect. This is currently applied to "kernel" functions, but can
be used to construct other metadata in dialect-specific ways without
necessarily affecting operations.
Depends On D96591, D96504
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D96592
Multi-configuration generators (such as Visual Studio and Xcode) allow the specification of a build flavor at build time instead of config time, so the lit configuration files need to support that - and they do for the most part. There are several places that had one of two issues (or both!):
1) Paths had %(build_mode)s set up, but then not configured, resulting in values that would not work correctly e.g. D:/llvm-build/%(build_mode)s/bin/dsymutil.exe
2) Paths did not have %(build_mode)s set up, but instead contained $(Configuration) (which is the value for Visual Studio at configuration time, for Xcode they would have had the equivalent) e.g. "D:/llvm-build/$(Configuration)/lib".
This seems to indicate that we still have a lot of fragility in the configurations, but also that a number of these paths are never used (at least on Windows) since the errors appear to have been there a while.
This patch fixes the configurations and it has been tested with Ninja and Visual Studio to generate the correct paths. We should consider removing some of these settings altogether.
Reviewed By: JDevlieghere, mehdi_amini
Differential Revision: https://reviews.llvm.org/D96427
This changes the behavior of constructing MLIRContext to no longer load globally
registered dialects on construction. Instead Dialects are only loaded explicitly
on demand:
- the Parser is lazily loading Dialects in the context as it encounters them
during parsing. This is the only purpose for registering dialects and not load
them in the context.
- Passes are expected to declare the dialects they will create entity from
(Operations, Attributes, or Types), and the PassManager is loading Dialects into
the Context when starting a pipeline.
This changes simplifies the configuration of the registration: a compiler only
need to load the dialect for the IR it will emit, and the optimizer is
self-contained and load the required Dialects. For example in the Toy tutorial,
the compiler only needs to load the Toy dialect in the Context, all the others
(linalg, affine, std, LLVM, ...) are automatically loaded depending on the
optimization pipeline enabled.
To adjust to this change, stop using the existing dialect registration: the
global registry will be removed soon.
1) For passes, you need to override the method:
virtual void getDependentDialects(DialectRegistry ®istry) const {}
and registery on the provided registry any dialect that this pass can produce.
Passes defined in TableGen can provide this list in the dependentDialects list
field.
2) For dialects, on construction you can register dependent dialects using the
provided MLIRContext: `context.getOrLoadDialect<DialectName>()`
This is useful if a dialect may canonicalize or have interfaces involving
another dialect.
3) For loading IR, dialect that can be in the input file must be explicitly
registered with the context. `MlirOptMain()` is taking an explicit registry for
this purpose. See how the standalone-opt.cpp example is setup:
mlir::DialectRegistry registry;
registry.insert<mlir::standalone::StandaloneDialect>();
registry.insert<mlir::StandardOpsDialect>();
Only operations from these two dialects can be in the input file. To include all
of the dialects in MLIR Core, you can populate the registry this way:
mlir::registerAllDialects(registry);
4) For `mlir-translate` callback, as well as frontend, Dialects can be loaded in
the context before emitting the IR: context.getOrLoadDialect<ToyDialect>()
Differential Revision: https://reviews.llvm.org/D85622
This changes the behavior of constructing MLIRContext to no longer load globally
registered dialects on construction. Instead Dialects are only loaded explicitly
on demand:
- the Parser is lazily loading Dialects in the context as it encounters them
during parsing. This is the only purpose for registering dialects and not load
them in the context.
- Passes are expected to declare the dialects they will create entity from
(Operations, Attributes, or Types), and the PassManager is loading Dialects into
the Context when starting a pipeline.
This changes simplifies the configuration of the registration: a compiler only
need to load the dialect for the IR it will emit, and the optimizer is
self-contained and load the required Dialects. For example in the Toy tutorial,
the compiler only needs to load the Toy dialect in the Context, all the others
(linalg, affine, std, LLVM, ...) are automatically loaded depending on the
optimization pipeline enabled.
To adjust to this change, stop using the existing dialect registration: the
global registry will be removed soon.
1) For passes, you need to override the method:
virtual void getDependentDialects(DialectRegistry ®istry) const {}
and registery on the provided registry any dialect that this pass can produce.
Passes defined in TableGen can provide this list in the dependentDialects list
field.
2) For dialects, on construction you can register dependent dialects using the
provided MLIRContext: `context.getOrLoadDialect<DialectName>()`
This is useful if a dialect may canonicalize or have interfaces involving
another dialect.
3) For loading IR, dialect that can be in the input file must be explicitly
registered with the context. `MlirOptMain()` is taking an explicit registry for
this purpose. See how the standalone-opt.cpp example is setup:
mlir::DialectRegistry registry;
registry.insert<mlir::standalone::StandaloneDialect>();
registry.insert<mlir::StandardOpsDialect>();
Only operations from these two dialects can be in the input file. To include all
of the dialects in MLIR Core, you can populate the registry this way:
mlir::registerAllDialects(registry);
4) For `mlir-translate` callback, as well as frontend, Dialects can be loaded in
the context before emitting the IR: context.getOrLoadDialect<ToyDialect>()
Differential Revision: https://reviews.llvm.org/D85622
Summary: Add a test to check if the standalone dialect is registered within standalone-opt. Similar to the mlir-opt commandline.mlir test.
Reviewers: Kayjukh, stephenneuendorffer
Reviewed By: Kayjukh
Subscribers: mehdi_amini, rriddle, jpienaar, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, grosul1, frgossen, jurahul, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D80764
This adds a minimal out-of-tree dialect template which can be used to start work on a standalone dialect implementation without having to integrate it in the main LLVM tree.
It mostly sets up the directory structure and provides CMakeLists.txt files to build a dialect library, an opt-like tool to operate on that dialect as well as tests. It could be expanded in the future to add examples of more user-defined operations, types, attributes, generated enums, transforms, etc. and linked to a tutorial.
Differential Revision: https://reviews.llvm.org/D77133
Sam McCall