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
MemRefType was using a wrong `isa` function in the bindings code, which
could lead to invalid IR being constructed. Also run the verifier in
memref dialect tests.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D111784
When writing the user-facing documentation, I noticed several inconsistencies
and asymmetries in the Python API we provide. Fix them by adding:
- the `owner` property to regions, similarly to blocks;
- the `isinstance` method to any class derived from `PyConcreteAttr`,
`PyConcreteValue` and `PyConreteAffineExpr`, similar to `PyConcreteType` to
enable `isa`-like calls without having to handle exceptions;
- a mechanism to create the first block in the region as we could only create
blocks relative to other blocks, with is impossible in an empty region.
Reviewed By: gysit
Differential Revision: https://reviews.llvm.org/D111556
This exposes creating a CallSiteLoc with a callee & list of frames for
callers. Follows the creation approach in C++ side where a list of
frames may be provided.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D111670
* Need to investigate the proper solution to https://github.com/pybind/pybind11/issues/3336 or engineer something different.
* The attempt to produce an empty buffer_info as a workaround triggers asan/ubsan.
* Usage of this API does not arise naturally in practice yet, and it is more important to be asan/crash clean than have a solution right now.
* Switching back to raising an exception, even though that triggers terminate().
* 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
Provide a couple of quality-of-life usability improvements for Python bindings,
in particular:
* give access to the list of types for the list of op results or block
arguments, similarly to ValueRange->TypeRange,
* allow for constructing empty dictionary arrays,
* support construction of array attributes by concatenating an existing
attribute with a Python list of attributes.
All these are required for the upcoming customization of builtin and standard
ops.
Reviewed By: stellaraccident
Differential Revision: https://reviews.llvm.org/D110946
Without this change, these attributes can only be accessed through the generic
operation attribute dictionary provided the caller knows the special operation
attribute names used for this purpose. Add some Python wrapping to support this
use case.
Also provide access to function arguments usable inside the function along with
a couple of quality-of-life improvements in using block arguments (function
arguments being the arguments of its entry block).
Reviewed By: stellaraccident
Differential Revision: https://reviews.llvm.org/D110758
We weren't retaining the ctypes closures that the ExecutionEngine was
calling back into, leading to mysterious errors.
Open to feedback about how to test this. And an extra pair of eyes to
make sure I caught all the places that need to be aware of this.
Differential Revision: https://reviews.llvm.org/D110661
Enables putting types and attributes in sets and in dicts as keys.
Reviewed By: stellaraccident
Differential Revision: https://reviews.llvm.org/D110301
* ODS generated operations extend _OperationBase and without this, cannot be marshalled to CAPI functions.
* No test case updates: this kind of interop is quite hard to verify with in-tree tests.
Differential Revision: https://reviews.llvm.org/D110030
* Now that packaging has stabilized, removes old mechanisms for loading extensions, preferring direct importing.
* Removes _cext_loader.py, _dlloader.py as unnecessary.
* Fixes the path where the CAPI dll is written on Windows. This enables that path of least resistance loading behavior to work with no further drama (see: https://bugs.python.org/issue36085).
* With this patch, `ninja check-mlir` on Windows with Python bindings works for me, modulo some failures that are actually due to a couple of pre-existing Windows bugs. I think this is the first time the Windows Python bindings have worked upstream.
* Downstream changes needed:
* If downstreams are using the now removed `load_extension`, `reexport_cext`, etc, then those should be replaced with normal import statements as done in this patch.
Reviewed By: jdd, aartbik
Differential Revision: https://reviews.llvm.org/D108489
* This allows multiple MLIR-API embedding downstreams to co-exist in the same process.
* I believe this is the last thing needed to enable isolated embedding.
Differential Revision: https://reviews.llvm.org/D108605
* 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
* For python projects that don't need JIT/ExecutionEngine, cuts the number of files to compile roughly in half (with similar reduction in end binary size).
Differential Revision: https://reviews.llvm.org/D106992
Historically the builtin dialect has had an empty namespace. This has unfortunately created a very awkward situation, where many utilities either have to special case the empty namespace, or just don't work at all right now. This revision adds a namespace to the builtin dialect, and starts to cleanup some of the utilities to no longer handle empty namespaces. For now, the assembly form of builtin operations does not require the `builtin.` prefix. (This should likely be re-evaluated though)
Differential Revision: https://reviews.llvm.org/D105149
* Implements all of the discussed features:
- Links against common CAPI libraries that are self contained.
- Stops using the 'python/' directory at the root for everything, opening the namespace up for multiple projects to embed the MLIR python API.
- Separates declaration of sources (py and C++) needed to build the extension from building, allowing external projects to build custom assemblies from core parts of the API.
- Makes the core python API relocatable (i.e. it could be embedded as something like 'npcomp.ir', 'npcomp.dialects', etc). Still a bit more to do to make it truly isolated but the main structural reset is done.
- When building statically, installed python packages are completely self contained, suitable for direct setup and upload to PyPi, et al.
- Lets external projects assemble their own CAPI common runtime library that all extensions use. No more possibilities for TypeID issues.
- Begins modularizing the API so that external projects that just include a piece pay only for what they use.
* I also rolled in a re-organization of the native libraries that matches how I was packaging these out of tree and is a better layering (i.e. all libraries go into a nested _mlir_libs package). There is some further cleanup that I resisted since it would have required source changes that I'd rather do in a followup once everything stabilizes.
* Note that I made a somewhat odd choice in choosing to recompile all extensions for each project they are included into (as opposed to compiling once and just linking). While not leveraged yet, this will let us set definitions controlling the namespacing of the extensions so that they can be made to not conflict across projects (with preprocessor definitions).
* This will be a relatively substantial breaking change for downstreams. I will handle the npcomp migration and will coordinate with the circt folks before landing. We should stage this and make sure it isn't causing problems before landing.
* Fixed a couple of absolute imports that were causing issues.
Differential Revision: https://reviews.llvm.org/D106520
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
Adds `owner` python call to `mlir.ir.Value`.
Assuming that `PyValue.parentOperation` is intended to be the value's owner, this fixes the construction of it from `PyOpOperandList`.
Reviewed By: stellaraccident
Differential Revision: https://reviews.llvm.org/D103853
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
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
* The PybindAdaptors.h file has been evolving across different sub-projects (npcomp, circt) and has been successfully used for out of tree python API interop/extensions and defining custom types.
* Since sparse_tensor.encoding is the first in-tree custom attribute we are supporting, it seemed like the right time to upstream this header and use it to define the attribute in a way that we can support for both in-tree and out-of-tree use (prior, I had not wanted to upstream dead code which was not used in-tree).
* Adapted the circt version of `mlir_type_subclass`, also providing an `mlir_attribute_subclass`. As we get a bit of mileage on this, I would like to transition the builtin types/attributes to this mechanism and delete the old in-tree only `PyConcreteType` and `PyConcreteAttribute` template helpers (which cannot work reliably out of tree as they depend on internals).
* Added support for defaulting the MlirContext if none is passed so that we can support the same idioms as in-tree versions.
There is quite a bit going on here and I can split it up if needed, but would prefer to keep the first use and the header together so sending out in one patch.
Differential Revision: https://reviews.llvm.org/D102144
* NFC but has some fixes for CMake glitches discovered along the way (things not cleaning properly, co-mingled depends).
* Includes previously unsubmitted fix in D98681 and a TODO to fix it more appropriately in a smaller followup.
Differential Revision: https://reviews.llvm.org/D101493
* This makes them consistent with custom types/attributes, whose constructors will do a type checked conversion. Of course, the base classes can represent everything so never error.
* More importantly, this makes it possible to subclass Type and Attribute out of tree in sensible ways.
Differential Revision: https://reviews.llvm.org/D101734
This will allow the bindings to be built as a library and reused in out-of-tree
projects that want to provide bindings on top of MLIR bindings.
Reviewed By: stellaraccident, mikeurbach
Differential Revision: https://reviews.llvm.org/D101075
The patch extends the OpDSL with support for:
- Constant values
- Capture scalar parameters
- Access the iteration indices using the index operation
- Provide predefined floating point and integer types.
Up to now the patch only supports emitting the new nodes. The C++/yaml path is not fully implemented. The fill_rng_2d operation defined in emit_structured_generic.py makes use of the new DSL constructs.
Differential Revision: https://reviews.llvm.org/D101364
This adds a method to directly invoke `mlirOperationDestroy` on the
MlirOperation wrapped by a PyOperation.
Reviewed By: stellaraccident, mehdi_amini
Differential Revision: https://reviews.llvm.org/D101422
Previously, this API would return the PyObjectRef, rather than the
underlying PyOperation.
Reviewed By: stellaraccident
Differential Revision: https://reviews.llvm.org/D101416
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
