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explicit method call" (#153477)
Reverts llvm/llvm-project#153373
Sanitizer bot is broken
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method call (#153373)
This PR introduces a mechanism to defer JIT engine initialization,
enabling registration of required symbols before global constructor
execution.
## Problem
Modules containing `gpu.module` generate global constructors (e.g.,
kernel load/unload) that execute *during* engine creation. This can
force premature symbol resolution, causing failures when:
- Symbols are registered via `mlirExecutionEngineRegisterSymbol` *after*
creation
- Global constructors exist (even if not directly using unresolved
symbols, e.g., an external function declaration)
- GPU modules introduce mandatory binary loading logic
## Usage
```c
// Create engine without initialization
MlirExecutionEngine jit = mlirExecutionEngineCreate(...);
// Register required symbols
mlirExecutionEngineRegisterSymbol(jit, ...);
// Explicitly initialize (runs global constructors)
mlirExecutionEngineInitialize(jit);
```
---------
Co-authored-by: Mehdi Amini <joker.eph@gmail.com>
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The SystemZ ABI requires that i32 values should be extended when passed
between functions.
This patch fixes some tests that were lacking this, either by adding
some SystemZ specific inlinings of test functions or by disabling the
verification of this with the CL option controlling this.
Fixes #115564
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This patch simplifies the representation of OpenMP loop wrapper
operations by introducing the `NoTerminator` trait and updating
accordingly the verifier for the `LoopWrapperInterface`.
Since loop wrappers are already limited to having exactly one region
containing exactly one block, and this block can only hold a single
`omp.loop_nest` or loop wrapper and an `omp.terminator` that does not
return any values, it makes sense to simplify the representation of loop
wrappers by removing the terminator.
There is an extensive list of Lit tests that needed updating to remove
the `omp.terminator`s adding some noise to this patch, but actual
changes are limited to the definition of the `omp.wsloop`, `omp.simd`,
`omp.distribute` and `omp.taskloop` loop wrapper ops, Flang lowering for
those, `LoopWrapperInterface::verifyImpl()`, SCF to OpenMP conversion
and OpenMP dialect documentation.
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This patch updates the definition of `omp.wsloop` to enforce the
restrictions of a loop wrapper operation.
Related tests are updated but this PR on its own will not pass premerge
tests. All patches in the stack are needed before it can be compiled and
passes tests.
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We've observed that the MLIR Jit Engine fails when the `omp` dialect is used due to a failure to register OpenMP-related translations. This small patch addresses this issue.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D151577
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`mlirPassManagerRun` is currently restricted to running on
`builtin.module` ops, but this restriction doesn't exist on the C++
side. This renames it to `mlirPassManagerRunOnOp` and updates it to take
`MlirOperation` instead of `MlirModule`.
Depends on D143352
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D143354
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Update the FuncToLLVM pass to use the generated constructors and
the generated pass option struct. The hand written constructor
got out of sync after some refactorings. Using a generated constructor
and options struct ensures the everything remains in sync.
Reviewed By: zero9178
This reverts commit 39da46826da82c24ca4407c13ad7feb8e5dc32a1
and relands commit 771d9c05afc2515b474fb53db857716dfdfc1dcf
which was originally reverted due to
https://lab.llvm.org/buildbot#builders/61/builds/39694
Differential Revision: https://reviews.llvm.org/D143733
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The commit breaks the mlir-vulkan runner:
https://lab.llvm.org/buildbot#builders/61/builds/39694
This reverts commit 771d9c05afc2515b474fb53db857716dfdfc1dcf.
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Update the FuncToLLVM pass to use the generated constructors and
the generated pass option struct. The hand written constructor
got out of sync after some refactorings. Using a generated constructor
and options struct ensures the everything remains in sync.
Reviewed By: zero9178
Differential Revision: https://reviews.llvm.org/D143733
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These warnings prevent compilation using clang and
-DLLVM_ENABLE_WERROR=On.
Differential revision: https://reviews.llvm.org/D139322
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Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D136334
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Suggested by @lattner in https://discourse.llvm.org/t/rfc-define-precise-arith-semantics/65507/22.
Tested with:
`ninja check-mlir check-mlir-integration check-mlir-mlir-spirv-cpu-runner check-mlir-mlir-vulkan-runner check-mlir-examples`
and `bazel build --config=generic_clang @llvm-project//mlir:all`.
Reviewed By: lattner, Mogball, rriddle, jpienaar, mehdi_amini
Differential Revision: https://reviews.llvm.org/D134762
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constructor
See #57475
Differential Revision: https://reviews.llvm.org/D134752
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This reverts commit 2be8af8f0e0780901213b6fd3013a5268ddc3359.
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The patch introduces the required changes to update the pass declarations and definitions to use the new autogenerated files and allow dropping the old infrastructure.
Reviewed By: mehdi_amini, rriddle
Differential Review: https://reviews.llvm.org/D132838
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A number of mlir tests `FAIL` on Solaris/sparcv9 with `Target has no JIT
support`. This patch fixes that by mimicing `clang/test/lit.cfg.py` which
implements a `host-supports-jit` keyword for this. The gtest-based unit
tests don't support `REQUIRES:`, so lack of support needs to be hardcoded
there.
Tested on `amd64-pc-solaris2.11` (`check-mlir` results unchanged) and
`sparcv9-sun-solaris2.11` (only one unrelated failure left).
Differential Revision: https://reviews.llvm.org/D131151
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registration/loading activities.
Since the very first commits, the Python and C MLIR APIs have had mis-placed registration/load functionality for dialects, extensions, etc. This was done pragmatically in order to get bootstrapped and then just grew in. Downstreams largely bypass and do their own thing by providing various APIs to register things they need. Meanwhile, the C++ APIs have stabilized around this and it would make sense to follow suit.
The thing we have observed in canonical usage by downstreams is that each downstream tends to have native entry points that configure its installation to its preferences with one-stop APIs. This patch leans in to this approach with `RegisterEverything.h` and `mlir._mlir_libs._mlirRegisterEverything` being the one-stop entry points for the "upstream packages". The `_mlir_libs.__init__.py` now allows customization of the environment and Context by adding "initialization modules" to the `_mlir_libs` package. If present, `_mlirRegisterEverything` is treated as such a module. Others can be added by downstreams by adding a `_site_initialize_{i}.py` module, where '{i}' is a number starting with zero. The number will be incremented and corresponding module loaded until one is not found. Initialization modules can:
* Perform load time customization to the global environment (i.e. registering passes, hooks, etc).
* Define a `register_dialects(registry: DialectRegistry)` function that can extend the `DialectRegistry` that will be used to bootstrap the `Context`.
* Define a `context_init_hook(context: Context)` function that will be added to a list of callbacks which will be invoked after dialect registration during `Context` initialization.
Note that the `MLIRPythonExtension.RegisterEverything` is not included by default when building a downstream (its corresponding behavior was prior). For downstreams which need the default MLIR initialization to take place, they must add this back in to their Python CMake build just like they add their own components (i.e. to `add_mlir_python_common_capi_library` and `add_mlir_python_modules`). It is perfectly valid to not do this, in which case, only the things explicitly depended on and initialized by downstreams will be built/packaged. If the downstream has not been set up for this, it is recommended to simply add this back for the time being and pay the build time/package size cost.
CMake changes:
* `MLIRCAPIRegistration` -> `MLIRCAPIRegisterEverything` (renamed to signify what it does and force an evaluation: a number of places were incidentally linking this very expensive target)
* `MLIRPythonSoure.Passes` removed (without replacement: just drop)
* `MLIRPythonExtension.AllPassesRegistration` removed (without replacement: just drop)
* `MLIRPythonExtension.Conversions` removed (without replacement: just drop)
* `MLIRPythonExtension.Transforms` removed (without replacement: just drop)
Header changes:
* `mlir-c/Registration.h` is deleted. Dialect registration functionality is now in `IR.h`. Registration of upstream features are in `mlir-c/RegisterEverything.h`. When updating MLIR and a couple of downstreams, I found that proper usage was commingled so required making a choice vs just blind S&R.
Python APIs removed:
* mlir.transforms and mlir.conversions (previously only had an __init__.py which indirectly triggered `mlirRegisterTransformsPasses()` and `mlirRegisterConversionPasses()` respectively). Downstream impact: Remove these imports if present (they now happen as part of default initialization).
* mlir._mlir_libs._all_passes_registration, mlir._mlir_libs._mlirTransforms, mlir._mlir_libs._mlirConversions. Downstream impact: None expected (these were internally used).
C-APIs changed:
* mlirRegisterAllDialects(MlirContext) now takes an MlirDialectRegistry instead. It also used to trigger loading of all dialects, which was already marked with a TODO to remove -- it no longer does, and for direct use, dialects must be explicitly loaded. Downstream impact: Direct C-API users must ensure that needed dialects are loaded or call `mlirContextLoadAllAvailableDialects(MlirContext)` to emulate the prior behavior. Also see the `ir.c` test case (e.g. ` mlirContextGetOrLoadDialect(ctx, mlirStringRefCreateFromCString("func"));`).
* mlirDialectHandle* APIs were moved from Registration.h (which now is restricted to just global/upstream registration) to IR.h, arguably where it should have been. Downstream impact: include correct header (likely already doing so).
C-APIs added:
* mlirContextLoadAllAvailableDialects(MlirContext): Corresponds to C++ API with the same purpose.
Python APIs added:
* mlir.ir.DialectRegistry: Mapping for an MlirDialectRegistry.
* mlir.ir.Context.append_dialect_registry(MlirDialectRegistry)
* mlir.ir.Context.load_all_available_dialects()
* mlir._mlir_libs._mlirAllRegistration: New native extension that exposes a `register_dialects(MlirDialectRegistry)` entry point and performs all upstream pass/conversion/transforms registration on init. In this first step, we eagerly load this as part of the __init__.py and use it to monkey patch the Context to emulate prior behavior.
* Type caster and capsule support for MlirDialectRegistry
This should make it possible to build downstream Python dialects that only depend on a subset of MLIR. See: https://github.com/llvm/llvm-project/issues/56037
Here is an example PR, minimally adapting IREE to these changes: https://github.com/iree-org/iree/pull/9638/files In this situation, IREE is opting to not link everything, since it is already configuring the Context to its liking. For projects that would just like to not think about it and pull in everything, add `MLIRPythonExtension.RegisterEverything` to the list of Python sources getting built, and the old behavior will continue.
Reviewed By: mehdi_amini, ftynse
Differential Revision: https://reviews.llvm.org/D128593
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The tests actually require the target triple to match the host, rather than just having the host in the list of available targets. This change removes `llvm_has_native_target` and instead uses the `native` feature from the lit configuration.
Reviewed By: stellaraccident
Differential Revision: https://reviews.llvm.org/D126011
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operations
The special case parsing of operations in the `func` dialect is being removed, and
operations will require the dialect namespace prefix.
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This commit moves FuncOp out of the builtin dialect, and into the Func
dialect. This move has been planned in some capacity from the moment
we made FuncOp an operation (years ago). This commit handles the
functional aspects of the move, but various aspects are left untouched
to ease migration: func::FuncOp is re-exported into mlir to reduce
the actual API churn, the assembly format still accepts the unqualified
`func`. These temporary measures will remain for a little while to
simplify migration before being removed.
Differential Revision: https://reviews.llvm.org/D121266
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The current StandardToLLVM conversion patterns only really handle
the Func dialect. The pass itself adds patterns for Arithmetic/CFToLLVM, but
those should be/will be split out in a followup. This commit focuses solely
on being an NFC rename.
Aside from the directory change, the pattern and pass creation API have been renamed:
* populateStdToLLVMFuncOpConversionPattern -> populateFuncToLLVMFuncOpConversionPattern
* populateStdToLLVMConversionPatterns -> populateFuncToLLVMConversionPatterns
* createLowerToLLVMPass -> createConvertFuncToLLVMPass
Differential Revision: https://reviews.llvm.org/D120778
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This makes `ninja check-mlir` work without the host targets configured.
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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
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Add support to Python bindings for the MLIR execution engine to load a
specified list of shared libraries - for eg. to use MLIR runtime
utility libraries.
Differential Revision: https://reviews.llvm.org/D104009
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Provide an option to specify optimization level when creating an
ExecutionEngine via the MLIR JIT Python binding. Not only is the
specified optimization level used for code generation, but all LLVM
optimization passes at the optimization level are also run prior to
machine code generation (akin to the mlir-cpu-runner tool).
Default opt level continues to remain at level two (-O2).
Contributions in part from Prashant Kumar <prashantk@polymagelabs.com>
as well.
Differential Revision: https://reviews.llvm.org/D102551
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This adds minimalistic bindings for the execution engine, allowing to
invoke the JIT from the C API. This is still quite early and
experimental and shouldn't be considered stable in any way.
Differential Revision: https://reviews.llvm.org/D96651
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