This is adding a new interface (`BytecodeOpInterface`) to allow operations to
opt-in skipping conversion to attribute and serializing properties to native
bytecode.
The scheme relies on a new section where properties are stored in sequence
{ size, serialize_properties }, ...
The operations are storing the index of a properties, a table of offset is
built when loading the properties section the first time.
This is a re-commit of 837d1ce0dc which conflicted with another patch upgrading
the bytecode and the collision wasn't properly resolved before.
Differential Revision: https://reviews.llvm.org/D151065
This reverts commit ca5a12fd69d4acf70c08f797cbffd714dd548348
and follow-up fixes:
df34c288c428eb4b867c8075def48b3d1727d60b
07dc906883af660780cf6d0cc1044f7e74dab83e
ab80ad0095083fda062c23ac90df84c40b4332c8
837d1ce0dc8eec5b17255291b3462e6296cb369b
The first commit was incomplete and broken, I'll prepare a new version
later, in the meantime pull this work out of tree.
This is adding a new interface (`BytecodeOpInterface`) to allow operations to
opt-in skipping conversion to attribute and serializing properties to native
bytecode.
The scheme relies on a new section where properties are stored in sequence
{ size, serialize_properties }, ...
The operations are storing the index of a properties, a table of offset is
built when loading the properties section the first time.
Back-deployment to version prior to 4 are relying on getAttrDictionnary() which
we intend to deprecate and remove: that is putting a de-factor end-of-support
horizon for supporting deployments to version older than 4.
Differential Revision: https://reviews.llvm.org/D151065
Implementation of Pass and Dialect Plugins that mirrors LLVM Pass Plugin
implementation from the new pass manager.
Currently the implementation only supports using the pass-pipeline option
for adding passes. This restriction is imposed by the `PassPipelineCLParser`
variable in mlir/lib/Tools/mlir-opt/MlirOptMain.cpp:114 that loads the
parse options statically before parsing the cmd line args.
```
mlir-opt stanalone-plugin.mlir --load-dialect-plugin=lib/libStandalonePlugin.so --pass-pipeline="builtin.module(standalone-switch-bar-foo)"
```
Reviewed By: rriddle, mehdi_amini
Differential Revision: https://reviews.llvm.org/D147053
Implementation of Pass and Dialect Plugins that mirrors LLVM Pass Plugin implementation from the new pass manager.
Currently the implementation only supports using the pass-pipeline option for adding passes. This restriction is imposed by the `PassPipelineCLParser` variable in mlir/lib/Tools/mlir-opt/MlirOptMain.cpp:114 that loads the parse options statically before parsing the cmd line args.
```
mlir-opt stanalone-plugin.mlir --load-dialect-plugin=lib/libStandalonePlugin.so --pass-pipeline="builtin.module(standalone-switch-bar-foo)"
```
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D147053
Implementation of Pass and Dialect Plugins that mirrors LLVM Pass Plugin implementation from the new pass manager.
Currently the implementation only supports using the pass-pipeline option for adding passes. This restriction is imposed by the `PassPipelineCLParser` variable in mlir/lib/Tools/mlir-opt/MlirOptMain.cpp:114 that loads the parse options statically before parsing the cmd line args.
```
mlir-opt stanalone-plugin.mlir --load-dialect-plugin=lib/libStandalonePlugin.so --pass-pipeline="builtin.module(standalone-switch-bar-foo)"
```
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D147053
This extends the standalone example to illustrate how to structure the
files needed to create own types.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D143715
This patch takes the first step towards a more principled modeling of undefined behavior in MLIR as discussed in the following discourse threads:
1. https://discourse.llvm.org/t/semantics-modeling-undefined-behavior-and-side-effects/4812
2. https://discourse.llvm.org/t/rfc-mark-tensor-dim-and-memref-dim-as-side-effecting/65729
This patch in particular does the following:
1. Introduces a ConditionallySpeculatable OpInterface that dynamically determines whether an Operation can be speculated.
2. Re-defines `NoSideEffect` to allow undefined behavior, making it necessary but not sufficient for speculation. Also renames it to `NoMemoryEffect`.
3. Makes LICM respect the above semantics.
4. Changes all ops tagged with `NoSideEffect` today to additionally implement ConditionallySpeculatable and mark themselves as always speculatable. This combined trait is named `Pure`. This makes this change NFC.
For out of tree dialects:
1. Replace `NoSideEffect` with `Pure` if the operation does not have any memory effects, undefined behavior or infinite loops.
2. Replace `NoSideEffect` with `NoSideEffect` otherwise.
The next steps in this process are (I'm proposing to do these in upcoming patches):
1. Update operations like `tensor.dim`, `memref.dim`, `scf.for`, `affine.for` to implement a correct hook for `ConditionallySpeculatable`. I'm also happy to update ops in other dialects if the respective dialect owners would like to and can give me some pointers.
2. Update other passes that speculate operations to consult `ConditionallySpeculatable` in addition to `NoMemoryEffect`. I could not find any other than LICM on a quick skim, but I could have missed some.
3. Add some documentation / FAQs detailing the differences between side effects, undefined behavior, speculatabilty.
Reviewed By: rriddle, mehdi_amini
Differential Revision: https://reviews.llvm.org/D135505
Most dialects have already flipped to prefixed, and the intention to switch
has been telegraphed for a while.
Differential Revision: https://reviews.llvm.org/D133179
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
Marked all dialects that could be (reasonably) easily flipped to _Both
prefix. Updating the accessors to prefixed form will happen in follow
up, this was to flush out conflicts and to mark all dialects explicitly
as I plan to flip OpBase default to _Prefixed to avoid needing to
migrate new dialects.
Except for Standalone example which got flipped to _Prefixed.
Differential Revision: https://reviews.llvm.org/D128027
This allows for inferring the result types of operations in certain situations by using the type of
an operand. This commit allowed for automatically supporting type inference for many more
operations with no additional effort, e.g. nearly all Arithmetic operations now support
result type inferrence with no additional changes.
Differential Revision: https://reviews.llvm.org/D124581
- Remove the `{Op,Attr,Type}Trait` TableGen classes and replace with `Trait`
- Rename `OpTraitList` to `TraitList` and use it in a few places
The bulk of this change is a mechanical s/OpTrait/Trait/ throughout the codebase.
Reviewed By: rriddle, jpienaar, herhut
Differential Revision: https://reviews.llvm.org/D118543
Step towards removing the hard coded behavior for this trait and to instead use common interface.
Differential Revision: https://reviews.llvm.org/D114208
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 ${CMAKE_CURRENT_SOURCE_DIR} here, which can just be ommitted). May need to set ROOT_DIR if not relative to the current source directory.
* To allow further downstreams to install/build, will need to make sure that all C++ extension headers are also listed under SOURCES for declare_mlir_python_extension.
This reverts commit 1a6c26d1f52999edbfbf6a978ae3f0e6759ea755.
Reviewed By: stephenneuendorffer
Differential Revision: https://reviews.llvm.org/D113732
* Depends on D111504, which provides the boilerplate for building aggregate shared libraries from installed MLIR.
* Adds a full-fledged Python example dialect and tests to the Standalone example (need to do a bit of tweaking in the top level CMake and lit tests to adapt better to if not building with Python enabled).
* Rips out remnants of custom extension building in favor of `pybind11_add_module` which does the right thing.
* Makes python and extension sources installable (outputs to src/python/${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
This is useful for expressing specific table-gen options, like selecting
a particular dialect to print.
Use it to fix the documentation for the `pdl_interp` dialect which is now
generating the first dialect it finds in its input which is `pdl`.
Differential Revision: https://reviews.llvm.org/D100517
Implement Bug 46698, making ODS synthesize a getType() method that returns a
specific C++ class for OneResult methods where we know that class. This eliminates
a common source of casts in things like:
myOp.getType().cast<FIRRTLType>().getPassive()
because we know that myOp always returns a FIRRTLType. This also encourages
op authors to type their results more tightly (which is also good for
verification).
I chose to implement this by splitting the OneResult trait into itself plus a
OneTypedResult trait, given that many things are using `hasTrait<OneResult>`
to conditionalize various logic.
While this changes makes many many ops get more specific getType() results, it
is generally drop-in compatible with the previous behavior because 'x.cast<T>()'
is allowed when x is already known to be a T. The one exception to this is that
we need declarations of the types used by ops, which is why a couple headers
needed additional #includes.
I updated a few things in tree to remove the now-redundant `.cast<>`'s, but there
are probably many more than can be removed.
Differential Revision: https://reviews.llvm.org/D93790
This normalize the name of the tablegen file with the name of the generated
files (SideEffectInterfaces.h.inc) and the other Interface tablegen files,
which all end in Interface(s).td
Differential Revision: https://reviews.llvm.org/D79517
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
