[mlir][test] Require JIT support in JIT tests

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
impl

[mlir][test] Require JIT support in JIT tests

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

(cherry picked from commit ca98e0dd6cf59907f07201c4282dcafeeea11a91)

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[mlir] Overhaul C/Python registration APIs to properly scope registration/loading activities.

Since the very first commits, the Python and C MLIR APIs have had mis-placed registration/load functiona

[mlir] Overhaul C/Python registration APIs to properly scope 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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[mlir] Use 'native' instead of 'llvm_has_native_target' in the mlir tests

The tests actually require the target triple to match the host, rather than just having the host in the list of available ta

[mlir] Use 'native' instead of 'llvm_has_native_target' in the mlir tests

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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[mlir][NFC] Update remaining textual references of un-namespaced `func` operations

The special case parsing of operations in the `func` dialect is being removed, and
operations will require the dial

[mlir][NFC] Update remaining textual references of un-namespaced `func` 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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[mlir] Move the Builtin FuncOp to the Func dialect

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

[mlir] Move the Builtin FuncOp to the Func dialect

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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[mlir][NFC] Rename StandardToLLVM to FuncToLLVM

The current StandardToLLVM conversion patterns only really handle
the Func dialect. The pass itself adds patterns for Arithmetic/CFToLLVM, but
those s

[mlir][NFC] Rename StandardToLLVM to FuncToLLVM

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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Mark some MLIR tests as requiring the native target to be configured

This makes `ninja check-mlir` work without the host targets configured.

[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

[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

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[MLIR] Execution engine python binding support for shared libraries

Add support to Python bindings for the MLIR execution engine to load a
specified list of shared libraries - for eg. to use MLIR ru

[MLIR] Execution engine python binding support for shared libraries

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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[MLIR][PYTHON] Provide opt level for ExecutionEngine Python binding

Provide an option to specify optimization level when creating an
ExecutionEngine via the MLIR JIT Python binding. Not only is the

[MLIR][PYTHON] Provide opt level for ExecutionEngine Python binding

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 <[email protected]>
as well.

Differential Revision: https://reviews.llvm.org/D102551

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Add C bindings for mlir::ExecutionEngine

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

Add C bindings for mlir::ExecutionEngine

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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