Exposes mlir::DialectRegistry to the C API as MlirDialectRegistry along with
helper functions. A hook has been added to MlirDialectHandle that inserts
the dialect into a registry.
A future possible change is removing mlirDialectHandleRegisterDialect in
favor of using mlirDialectHandleInsertDialect, which it is now implemented with.
Differential Revision: https://reviews.llvm.org/D118293
This extends dense attribute element access to support 8b and 16b ints.
Also extends the corresponding parts of the C api.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D117731
BlockArguments gained the ability to have locations attached a while ago, but they
have always been optional. This goes against the core tenant of MLIR where location
information is a requirement, so this commit updates the API to require locations.
Fixes#53279
Differential Revision: https://reviews.llvm.org/D117633
This change adds full python bindings for PDL, including types and operations
with additional mixins to make operation construction more similar to the PDL
syntax.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D117458
Previously, the Python bindings for the Linalg dialect relied on the internal
implementation of core bindings. Most of that functionality was moved, and the
remaining one does not need access to the implementation: it used to accept a
dialect pointer as argument, but it can always be extracted from the operation
that it also accepts; operations are available through PybindAdaptors in an
opaque way. Change the bindings in that direction.
This enables the decoupling of the Linalg dialect Python extension from the
core IR Python extension.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D116649
* set_symbol_name, get_symbol_name, set_visibility, get_visibility, replace_all_symbol_uses, walk_symbol_tables
* In integrations I've been doing, I've been reaching for all of these to do both general IR manipulation and module merging.
* I don't love the replace_all_symbol_uses underlying APIs since they necessitate SYMBOL_COUNT walks and have various sharp edges. I'm hoping that whatever emerges eventually for this can still retain this simple API as a one-shot.
Differential Revision: https://reviews.llvm.org/D114687
The purpose of the change is to make clear whether the user is
retrieving the original function or the wrapper function, in line with
the invoke commands. This new functionality is useful for users that
already have defined their own packed interface, so they do not want the
extra layer of indirection, or for users wanting to the look at the
resulting primary function rather than the wrapper function.
All locations, except the python bindings now have a `lookupPacked`
method that matches the original `lookup` functionality. `lookup`
still exists, but with new semantics.
- `lookup` returns the function with a given name. If `bool f(int,int)`
is compiled, `lookup` will return a reference to `bool(*f)(int,int)`.
- `lookupPacked` returns the packed wrapper of the function with the
given name. If `bool f(int,int)` is compiled, `lookupPacked` will return
`void(*mlir_f)(void**)`.
Differential Revision: https://reviews.llvm.org/D114352
Enables using the same iterator interface to these even though underlying storage is different.
Differential Revision: https://reviews.llvm.org/D113512
- Provide the operator overloads for constructing (semi-)affine expressions in
Python by combining existing expressions with constants.
- Make AffineExpr, AffineMap and IntegerSet hashable in Python.
- Expose the AffineExpr composition functionality.
Reviewed By: gysit, aoyal
Differential Revision: https://reviews.llvm.org/D113010
Symbol tables are a largely useful top-level IR construct, for example, they
make it easy to access functions in a module by name instead of traversing the
list of module's operations to find the corresponding function.
Depends On D112886
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D112821
Provide support for removing an operation from the block that contains it and
moving it back to detached state. This allows for the operation to be moved to
a different block, a common IR manipulation for, e.g., module merging.
Also fix a potential one-past-end iterator dereference in Operation::moveAfter
discovered in the process.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D112700
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
The change is based on the proposal from the following discussion:
https://llvm.discourse.group/t/rfc-memreftype-affine-maps-list-vs-single-item/3968
* Introduce `MemRefLayoutAttr` interface to get `AffineMap` from an `Attribute`
(`AffineMapAttr` implements this interface).
* Store layout as a single generic `MemRefLayoutAttr`.
This change removes the affine map composition feature and related API.
Actually, while the `MemRefType` itself supported it, almost none of the upstream
can work with more than 1 affine map in `MemRefType`.
The introduced `MemRefLayoutAttr` allows to re-implement this feature
in a more stable way - via separate attribute class.
Also the interface allows to use different layout representations rather than affine maps.
For example, the described "stride + offset" form, which is currently supported in ASM parser only,
can now be expressed as separate attribute.
Reviewed By: ftynse, bondhugula
Differential Revision: https://reviews.llvm.org/D111553
* This already half existed in terms of reading the raw buffer backing a DenseElementsAttr.
* Documented the precise expectations of the buffer layout.
* Extended the Python API to support construction from bitcasted buffers, allowing construction of all primitive element types (even those that lack a compatible representation in Python).
* Specifically, the Python API can now load all integer types at all bit widths and all floating point types (f16, f32, f64, bf16).
Differential Revision: https://reviews.llvm.org/D111284
Exposes mlir::TypeID to the C API as MlirTypeID along with various accessors
and helper functions.
Differential Revision: https://reviews.llvm.org/D110897
Add method to get NameLoc. Treat null child location as unknown to avoid
needing to create UnknownLoc in C API where child loc is not needed.
Differential Revision: https://reviews.llvm.org/D108678
* It is pretty clear that no one has tried this yet since it was both incomplete and broken.
* Fixes a symbol hiding issues keeping even the generic builder from constructing an operation with successors.
* Adds ODS support for successors.
* Adds CAPI `mlirBlockGetParentRegion`, `mlirRegionEqual` + tests (and missing test for `mlirBlockGetParentOperation`).
* Adds Python property: `Block.region`.
* Adds Python methods: `Block.create_before` and `Block.create_after`.
* Adds Python property: `InsertionPoint.block`.
* Adds new blocks.py test to verify a plausible CFG construction case.
Differential Revision: https://reviews.llvm.org/D108898
* Resolves a TODO by making this configurable by downstreams.
* This seems to be the last thing allowing full use of the Python bindings as a library within another project (i.e. be embedding them).
Differential Revision: https://reviews.llvm.org/D108523
libMLIRPublicAPI.so came into existence early when the Python and C-API were being co-developed because the Python extensions need a single DSO which exports the C-API to link against. It really should never have been exported as a mondo library in the first place, which has caused no end of problems in different linking modes, etc (i.e. the CAPI tests depended on it).
This patch does a mechanical move that:
* Makes the C-API tests link directly to their respective libraries.
* Creates a libMLIRPythonCAPI as part of the Python bindings which assemble to exact DSO that they need.
This has the effect that the C-API is no longer monolithic and can be subset and used piecemeal in a modular fashion, which is necessary for downstreams to only pay for what they use. There are additional, more fundamental changes planned for how the Python API is assembled which should make it more out of tree friendly, but this minimal first step is necessary to break the fragile dependency between the C-API and Python API.
Downstream actions required:
* If using the C-API and linking against MLIRPublicAPI, you must instead link against its constituent components. As a reference, the Python API dependencies are in lib/Bindings/Python/CMakeLists.txt and approximate the full set of dependencies available.
* If you have a Python API project that was previously linking against MLIRPublicAPI (i.e. to add its own C-API DSO), you will want to `s/MLIRPublicAPI/MLIRPythonCAPI/` and all should be as it was. There are larger changes coming in this area but this part is incremental.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D106369
Extend the OpDSL with index attributes. After tensors and scalars, index attributes are the third operand type. An index attribute represents a compile-time constant that is limited to index expressions. A use cases are the strides and dilations defined by convolution and pooling operations.
The patch only updates the OpDSL. The C++ yaml codegen is updated by a followup patch.
Differential Revision: https://reviews.llvm.org/D104711
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
Currently, passes are registered on a per-dialect basis, which
provides the smallest footprint obviously. But for prototyping
and experimentation, a convenience "all passes" module is provided,
which registers all known MLIR passes in one run.
Usage in Python:
import mlir.all_passes_registration
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D103130
Also, fix a small typo where the "unsigned" splat variants were not
being created with an unsigned type.
Differential Revision: https://reviews.llvm.org/D102797
At the moment `MlirModule`s can be converted to `MlirOperation`s, but not
the other way around (at least not without going around the C API). This
makes it impossible to e.g. run passes over a `ModuleOp` created through
`mlirOperationCreate`.
Reviewed By: nicolasvasilache, mehdi_amini
Differential Revision: https://reviews.llvm.org/D102497
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
First set of "boilerplate" to get sparse tensor
passes available through CAPI and Python.
Reviewed By: stellaraccident
Differential Revision: https://reviews.llvm.org/D102362
* Adds dialect registration, hand coded 'encoding' attribute and test.
* An MLIR CAPI tablegen backend for attributes does not exist, and this is a relatively complicated case. I opted to hand code it in a canonical way for now, which will provide a reasonable blueprint for building out the tablegen version in the future.
* Also added a (local) CMake function for declaring new CAPI tests, since it was getting repetitive/buggy.
Differential Revision: https://reviews.llvm.org/D102141
This adds `mlirOperationSetOperand` to the IR C API, similar to the
function to get an operand.
In the Python API, this adds `operands[index] = value` syntax, similar
to the syntax to get an operand with `operands[index]`.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D101398
Add the `getCapsule()` and `createFromCapsule()` methods to the
PyValue class, as well as the necessary interoperability.
Reviewed By: stellaraccident
Differential Revision: https://reviews.llvm.org/D101090
Expose the debug flag as a readable and assignable property of a
dedicated class instead of a write-only function. Actually test the fact
of setting the flag. Move test to a dedicated file, it has zero relation
to context_managers.py where it was added.
Arguably, it should be promoted from mlir.ir to mlir module, but we are
not re-exporting the latter and this functionality is purposefully
hidden so can stay in IR for now. Drop unnecessary export code.
Refactor C API and put Debug into a separate library, fix it to actually
set the flag to the given value.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D100757
When Linalg named ops support was added, captures were omitted
from the body builder. This revision adds support for captures
which allows us to write FillOp in a more idiomatic fashion using
the _linalg_ops_ext mixin support.
This raises an issue in the generation of `_linalg_ops_gen.py` where
```
@property
def result(self):
return self.operation.results[0] if len(self.operation.results) > 1 else None
```.
The condition should be `== 1`.
This will be fixed in a separate commit.
Differential Revision: https://reviews.llvm.org/D100363
Daniel Resnick