# What
This PR adds a shared library `MLIRPythonSupport` which contains all of
the CRTP classes ike `PyConcreteValue`, `PyConcreteType`,
`PyConcreteAttribute`, as well as other useful code like `Defaulting*`
and etc enabling their reuse in downstream projects. Downstream projects
can now do
```c++
struct PyTestType : mlir::python::MLIR_BINDINGS_PYTHON_DOMAIN::PyConcreteType<PyTestType> {
...
};
class PyTestAttr : public mlir::python::MLIR_BINDINGS_PYTHON_DOMAIN::PyConcreteAttribute<PyTestAttr> {
...
}
NB_MODULE(_mlirPythonTestNanobind, m) {
PyTestType::bind(m);
PyTestAttr::bind(m);
}
```
instead of using the discordant alternative
`mlir_type_subclass`/`mlir_attr_subclass` (same goes for
`PyConcreteValue`/`mlir_value_subclass`).
# Why
This PR is mostly code motion (along with CMake) but before I describe
the changes I want to state the goals/benefits:
1. Currently upstream "core" extensions and "dialect" extensions ([all
of the `Dialect*` extensions
here](d7c734b5a1/mlir/lib/Bindings/Python))
are a two-tier system;
**a**. [core
extensions](https://github.com/llvm/llvm-project/blob/main/mlir/lib/Bindings/Python/IRTypes.cpp#L361)
enjoy first class support as far as type inference[^3], type stub
generation, and ease of implementation, while dialect extensions [have
poorer support](https://reviews.llvm.org/D150927), incorrect type stub
generation much more tedious (boilerplate) implementation;
**b**. Crucially, this two-tiered system is reflected in the fact that
**the two sets of types/attributes are not in the same Python object
hierarchy**. To wit: `isinstance(..., Type)` and `isinstance(...,
Attribute)` are not supported for the dialect extensions[^2];
**c**. Since these types are not exposed in public headers, downstream
users (dialect extensions or not) cannot write functions that overload
on e.g. `PyFloat8*Type` - that's quite a [useful
feature](fdbee98df8/cpp_ext/TorchOps.cpp (L29-L69))!
2. The dialect extensions incur a sizeable performance penalty relative
to the core extensions in that every single trip across the wire (either
`python->cpp` or `cpp->python`) requires work in addition to nanobind's
own casting/construction pipeline;
**a**. When going from `python->cpp`, [we extract the capsule object
from the Python
object](https://github.com/llvm/llvm-project/blob/main/mlir/include/mlir/Bindings/Python/NanobindAdaptors.h#L219C24-L219C46)
and then extract from the capsule the `Mlir*` opaque struct/ptr. This
side isn't so onerous;
**b**. When going from `cpp->python` we call long-hand call Python
`import` APIs and construct the Python object using `_CAPICreate`. Note,
there at least 2 `attr` calls incurred in addition to `_CAPICreate`;
this is already much more [efficiently handled by nanobind
itself](4ba51fcf79/src/nb_internals.h (L381-L382))!
3. This division blocks various features: in some configurations[^1] we
trigger a circular import bug because "dialect" types and attributes
perform an [import of the root `_mlir`
module](bd9651bf78/mlir/include/mlir/Bindings/Python/NanobindAdaptors.h (L585))
when they are created (the types themselves, not even instances of those
types). This blocks type stub generation for dialect extensions (i.e.,
the reason we currently only generate type stubs for `_mlir`).
# How
Prior this was not done/possible because of "ODR" issues but I have
resolved those issues; the basic idea for how we solve this is "move
things we want to share into shared libraries":
1. Move IRCore (stuff like `PyConcreteValue`, `PyConcreteType`,
`PyConcreteAttribute`) into `MLIRPythonSupport`;
- Note, we move the rest of the things in `IRModule.h` (renamed to
`IRCore.h`) because `PyConcreteValue`, `PyConcreteType`,
`PyConcreteAttribute` depend on them. This makes for a bigger PR than
one would hope for but ultimately I think we should give people access
to these classes to use as they see fit (specifically inherit from, but
also liberally use in bindings signatures instead of the opaque `Mlir*`
struct wrappers).
2. Put all of this code into a nested namespace
`MLIR_BINDINGS_PYTHON_DOMAIN` which is determined by a compile time
define (and tied to `MLIR_BINDINGS_PYTHON_NB_DOMAIN`). This is necessary
in order to prevent conflicts on both symbol name **and** typeid
(necessary for nanobind to not double register binded types) between
multiple bindings libraries (e.g., `torch-mlir`, and `jax`). Note
[nanobind doesn't support `module_local` like
pybind11](https://nanobind.readthedocs.io/en/latest/porting.html#removed-features).
It does support `NB_DOMAIN` but that is not sufficient for
disambiguating typeids across projects (to wit: we currently define
`NB_DOMAIN` and it was still necessary to move everything to a nested
namespace);
3. Build the [nanobind library itself as a shared
object](https://github.com/wjakob/nanobind/blob/master/cmake/nanobind-config.cmake#L127)
(and link it to both the extensions and `MLIRPythonSupport`).
4. CMake to make this work, in-tree, out-of-tree, downstream, upstream,
etc.
# Testing
Three tests are added here
1. `PythonTestModuleNanobind` is ported to use
`PyConcreteType<PyTestType>` instead of `mlir_type_subclass` and
`PyConcreteAttribute<PyTestAttr>` instead of `mlir_atrr_subclass`,
verifying this works for non-core extensions in-tree;
2. `StandaloneExtensionNanobind` is ported to use `struct PyCustomType :
mlir::python::MLIR_BINDINGS_PYTHON_DOMAIN::PyConcreteType<PyCustomType>`
instead of `mlir_type_subclass` verifying this works for non-core
extensions out-of-tree;
3. `StandaloneExtensionNanobind`'s `smoketest` is extended to also load
another bindings package (namely `mlir`) verifying
`MLIR_BINDINGS_PYTHON_DOMAIN` successfully disambiguates symbols and
typeids.
I have also tested this downstream:
https://github.com/llvm/eudsl/pull/287 as well run the following builder
bots:
mlir-nvidia-gcc7:
https://lab.llvm.org/buildbot/#/buildrequests/6654424?redirect_to_build=true
I have also tested against IREE:
https://github.com/iree-org/iree/pull/21916
# Integration
It is highly recommended to set the CMake var
`MLIR_BINDINGS_PYTHON_NB_DOMAIN` (which will also determine
`MLIR_BINDINGS_PYTHON_DOMAIN`) to something unique for each downstream.
This can also be passed explicitly to `add_mlir_python_modules` if your
project builds multiple bindings packages. I added a `WARNING` to this
effect in `AddMLIRPython.cmake`.
[^3]: Python values being typed correctly when exiting from cpp;
[^1]: Specifically when the modules are imported using `importlib`,
which occurs with nanobind's
[stubgen](https://github.com/wjakob/nanobind/blob/master/src/stubgen.py#L965);
[^2]: The workaround we implemented was a class method for the dialect
bindings called `Class.isinstance(...)`;
# Problem:
There are two build system bugs on MacOS in the case where one intends
to use multiple bindings packages simultaneously (same Python
interpreter session):
1. The nanobind modules are built with
[`-Wl,-flat_namespace`](8518d2c405/llvm/cmake/modules/HandleLLVMOptions.cmake (L268))
thereby leading to ambiguous symbols across multiple whatever dylibs;
2. Intra-library symbol resolution (within the C API aggregate dylib)
fails to resolve symbols correctly unless things are built with
`-DCMAKE_C_VISIBILITY_PRESET=hidden -DCMAKE_CXX_VISIBILITY_PRESET=hidden
-DCMAKE_VISIBILITY_INLINES_HIDDEN=ON`.
# Repro:
On a Mac (with this patch applied):
1. Build without `twolevel_namespace` and without hidden vis properties
and run `LIT_FILTER=test.toy ninja check-mlir` (assuming you have
`-DLLVM_BUILD_EXAMPLES=ON -DLLVM_INCLUDE_EXAMPLES=ON`) and you will see:
```
LLVM ERROR: can't create Attribute 'mlir::StringAttr' because storage
uniquer isn't initialized: the dialect was likely not loaded, or the
attribute wasn't added with addAttributes<...>() in the
Dialect::initialize() method.
```
2. Build with `twolevel_namespace` but not hidden vis and run the same
lit test and you will see:
```
LLVM ERROR: Attempting to attach an interface to an unregistered
operation builtin.unrealized_conversion_cast.
```
# Fix
We only do a partial fix here (adding `twolevel_namespace` to Python
bindings modules) because a full fix requires adding visibility
attributes to all object files. I added docs discussing this.
# Why is this not happening on Linux
Using `DYLD_PRINT_BINDINGS=1` I observe that for the checked-in/updated
test (without the fix) `libMLIRPythonCAPI` resolves many of its symbols
to `libStandalonePythonCAPI`:
```
dyld[98449]: looking for weak-def symbol '__ZN4mlir6TypeID3getINS_13AffineMapAttrEEES0_v':
dyld[98449]: found __ZN4mlir6TypeID3getINS_13AffineMapAttrEEES0_v in map, using impl from /Users/maksimlevental/dev_projects/llvm-project/cmake-build-debug/tools/mlir/test/Examples/standalone/python_packages/standalone/mlir_standalone/_mlir_libs/libStandalonePythonCAPI.dylib
dyld[98449]: <libMLIRPythonCAPI.dylib/bind#22> -> 0x11348fa9c <libStandalonePythonCAPI.dylib/__ZN4mlir6TypeID3getINS_13AffineMapAttrEEES0_v>)
dyld[98449]: looking for weak-def symbol '__ZN4mlir6TypeID3getINS_9ArrayAttrEEES0_v':
dyld[98449]: found __ZN4mlir6TypeID3getINS_9ArrayAttrEEES0_v in map, using impl from /Users/maksimlevental/dev_projects/llvm-project/cmake-build-debug/tools/mlir/test/Examples/standalone/python_packages/standalone/mlir_standalone/_mlir_libs/libStandalonePythonCAPI.dylib
dyld[98449]: <libMLIRPythonCAPI.dylib/bind#23> -> 0x11348f990 <libStandalonePythonCAPI.dylib/__ZN4mlir6TypeID3getINS_9ArrayAttrEEES0_v>)
dyld[98449]: looking for weak-def symbol '__ZN4mlir6TypeID3getINS_14DictionaryAttrEEES0_v':
dyld[98449]: found __ZN4mlir6TypeID3getINS_14DictionaryAttrEEES0_v in map, using impl from /Users/maksimlevental/dev_projects/llvm-project/cmake-build-debug/tools/mlir/test/Examples/standalone/python_packages/standalone/mlir_standalone/_mlir_libs/libStandalonePythonCAPI.dylib
dyld[98449]: <libMLIRPythonCAPI.dylib/bind#24> -> 0x11348eec0 <libStandalonePythonCAPI.dylib/__ZN4mlir6TypeID3getINS_14DictionaryAttrEEES0_v>)
```
Turns out this is "expected" behavior:
> It appears on macOS, when a static library is compiled without
-fvisibility=hidden, its C++ template instantiations could lead to
leftover weak symbols that are resolved and bound at runtime
https://joyeecheung.github.io/blog/2025/01/11/executable-loading-and-startup-performance-on-macos/🤷
…consistent
Since the bindings now use nanobind, I changed the code examples and
mentions in the documentation prose to mention nanobind concepts and
symbols wherever applicable.
I also made the spelling of "Python" consistent by choosing the
uppercase name everywhere that's not an executable name, part of a URL,
or directory name.
----------------
Note that I left mentions of `PybindAdaptors.h` in because of
https://github.com/llvm/llvm-project/pull/162309.
Are there any thoughts about adding a virtual environment setup guide
using [uv](https://docs.astral.sh/uv/)? It has gotten pretty popular,
and is much faster than a "vanilla" Python pip install. It can also
bootstrap an interpreter not present on the user's machine, for example
a free-threaded Python build, with the `-p` flag to the `uv venv`
virtual environment creation command.
The MLIR Python bindings now support defining new passes, new rewrite
patterns (through either `RewritePatternSet` or `PDLModule`), as well as
new dialects using the IRDL bindings. Adding a dedicated section to
document these features would make it easier for users to discover and
understand the full capabilities of the Python bindings.
Python-defined passes have been merged into the main branch for some
time now. I believe adding a corresponding section in the documentation
will help more users learn about this feature and understand how to use
it.
This PR adds such a section to the docs of Python bindings, summarizing
the feature and providing an example.
Historical context: `PyMlirContext::liveOperations` was an optimization
meant to cut down on the number of Python object allocations and
(partially) a mechanism for updating validity of ops after
transformation. E.g. during walking/transforming the AST. See original
patch [here](https://reviews.llvm.org/D87958).
Inspired by a
[renewed](https://github.com/llvm/llvm-project/pull/139721#issuecomment-3217131918)
interest in https://github.com/llvm/llvm-project/pull/139721 (which has
become a little stale...)
<p align="center">
<img width="504" height="375" alt="image"
src="https://github.com/user-attachments/assets/0daad562-d3d1-4876-8d01-5dba382ab186"
/>
</p>
In the previous go-around
(https://github.com/llvm/llvm-project/pull/92631) there were two issues
which have been resolved
1. ops that were "fetched" under a root op which has been transformed
are no longer reported as invalid. We simply "[formally
forbid](https://github.com/llvm/llvm-project/pull/92631#issuecomment-2119397018)"
this;
2. `Module._CAPICreate(module_capsule)` must now be followed by a
`module._clear_mlir_module()` to prevent double-freeing of the actual
`ModuleOp` object (i.e. calling the dtor on the
`OwningOpRef<ModuleOp>`):
```python
module = ...
module_dup = Module._CAPICreate(module._CAPIPtr)
module._clear_mlir_module()
```
- **the alternative choice** here is to remove the `Module._CAPICreate`
API altogether and replace it with something like `Module._move(module)`
which will do both `Module._CAPICreate` and `module._clear_mlir_module`.
Note, the other approach I explored last year was a [weakref
system](https://github.com/llvm/llvm-project/pull/97340) for
`mlir::Operation` which would effectively hoist this `liveOperations`
thing into MLIR core. Possibly doable but I now believe it's a bad idea.
The other potentially breaking change is `is`, which checks object
equality rather than value equality, will now report `False` because we
are always allocating `new` Python objects (ie that's the whole point of
this change). Users wanting to check equality for `Operation` and
`Module` should use `==`.
This PR allows out-of-tree dialects to write Python dialect modules
using nanobind instead of pybind11.
It may make sense to migrate in-tree dialects and some of the ODS Python
infrastructure to nanobind, but that is a topic for a future change.
This PR makes the following changes:
* adds nanobind to the CMake and Bazel build systems. We also add
robin_map to the Bazel build, which is a dependency of nanobind.
* adds a PYTHON_BINDING_LIBRARY option to various CMake functions, such
as declare_mlir_python_extension, allowing users to select a Python
binding library.
* creates a fork of mlir/include/mlir/Bindings/Python/PybindAdaptors.h
named NanobindAdaptors.h. This plays the same role, using nanobind
instead of pybind11.
* splits CollectDiagnosticsToStringScope out of PybindAdaptors.h and
into a new header mlir/include/mlir/Bindings/Python/Diagnostics.h, since
it is code that is no way related to pybind11 or for that matter,
Python.
* changed the standalone Python extension example to have both pybind11
and nanobind variants.
* changed mlir/python/mlir/dialects/python_test.py to have both pybind11
and nanobind variants.
Notes:
* A slightly unfortunate thing that I needed to do in the CMake
integration was to use FindPython in addition to FindPython3, since
nanobind's CMake integration expects the Python_ names for variables.
Perhaps there's a better way to do this.
This PR replaces the mixin `OpView` extension mechanism with the
standard inheritance mechanism.
Why? Firstly, mixins are not very pythonic (inheritance is usually used
for this), a little convoluted, and too "tight" (can only be used in the
immediately adjacent `_ext.py`). Secondly, it (mixins) are now blocking
are correct implementation of "value builders" (see
[here](https://github.com/llvm/llvm-project/pull/68764)) where the
problem becomes how to choose the correct base class that the value
builder should call.
This PR looks big/complicated but appearances are deceiving; 4 things
were needed to make this work:
1. Drop `skipDefaultBuilders` in
`OpPythonBindingGen::emitDefaultOpBuilders`
2. Former mixin extension classes are converted to inherit from the
generated `OpView` instead of being "mixins"
a. extension classes that simply were calling into an already generated
`super().__init__` continue to do so
b. (almost all) extension classes that were calling `self.build_generic`
because of a lack of default builder being generated can now also just
call `super().__init__`
3. To handle the [lone single
use-case](https://sourcegraph.com/search?q=context%3Aglobal+select_opview_mixin&patternType=standard&sm=1&groupBy=repo)
of `select_opview_mixin`, namely
[linalg](https://github.com/llvm/llvm-project/blob/main/mlir/python/mlir/dialects/_linalg_ops_ext.py#L38),
only a small change was necessary in `opdsl/lang/emitter.py` (thanks to
the emission/generation of default builders/`__init__`s)
4. since the `extend_opview_class` decorator is removed, we need a way
to register extension classes as the desired `OpView` that `op.opview`
conjures into existence; so we do the standard thing and just enable
replacing the existing registered `OpView` i.e.,
`register_operation(_Dialect, replace=True)`.
Note, the upgrade path for the common case is to change an extension to
inherit from the generated builder and decorate it with
`register_operation(_Dialect, replace=True)`. In the slightly more
complicated case where `super().__init(self.build_generic(...))` is
called in the extension's `__init__`, this needs to be updated to call
`__init__` in `OpView`, i.e., the grandparent (see updated docs).
Note, also `<DIALECT>_ext.py` files/modules will no longer be automatically loaded.
Note, the PR has 3 base commits that look funny but this was done for
the purpose of tracking the line history of moving the
`<DIALECT>_ops_ext.py` class into `<DIALECT>.py` and updating (commit
labeled "fix").
This functionality has been replaced by TypeCasters (see D151840)
depends on D154468
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D154469
Fix Python 3.6.9 issue encountered due to type checking here. Will
add back in follow up.
This reverts commit 1f47fee2948ef48781084afe0426171d000d7997.
For cases where we can automatically construct the Attribute allow for more
user-friendly input. This is consistent with C++ builder generation as well
choice of which single builder to generate here (most
specialized/user-friendly).
Registration of attribute builders from more pythonic input is all Python side.
The downside is that
* extra checking to see if user provided a custom builder in op builders,
* the ODS attribute name is load bearing
upside is that
* easily change these/register dialect specific ones in downstream projects,
* adding support/changing to different convenience builders are all along with
the rest of the convenience functions in Python (and no additional changes
to tablegen file or recompilation needed);
Allow for both building with Attributes as well as raw inputs. This change
should therefore be backwards compatible as well as allow for avoiding
recreating Attribute where already available.
Differential Revision: https://reviews.llvm.org/D139568
This removes any potential confusion with the `getType` accessors
which correspond to SSA results of an operation, and makes it
clear what the intent is (i.e. to represent the type of the function).
Differential Revision: https://reviews.llvm.org/D121762
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
The last remaining operations in the standard dialect all revolve around
FuncOp/function related constructs. This patch simply handles the initial
renaming (which by itself is already huge), but there are a large number
of cleanups unlocked/necessary afterwards:
* Removing a bunch of unnecessary dependencies on Func
* Cleaning up the From/ToStandard conversion passes
* Preparing for the move of FuncOp to the Func dialect
See the discussion at https://discourse.llvm.org/t/standard-dialect-the-final-chapter/6061
Differential Revision: https://reviews.llvm.org/D120624
Documentation exists about the details of the API but is missing a
description of the overall structure per dialect.
Reviewed By: shabalin
Differential Revision: https://reviews.llvm.org/D117002
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
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
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
Until now, we only had documentation oriented towards developers of the
bindings. Provide some documentation for users of the bindings that don't want
or need to understand the inner workings.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D111540
* 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
Fix inconsistent MLIR CMake variable names. Consistently name them as
MLIR_ENABLE_<feature>.
Eg: MLIR_CUDA_RUNNER_ENABLED -> MLIR_ENABLE_CUDA_RUNNER
MLIR follows (or has mostly followed) the convention of naming
cmake enabling variables in the from MLIR_ENABLE_... etc. Using a
convention here is easy and also important for convenience. A counter
pattern was started with variables named MLIR_..._ENABLED. This led to a
sequence of related counter patterns: MLIR_CUDA_RUNNER_ENABLED,
MLIR_ROCM_RUNNER_ENABLED, etc.. From a naming standpoint, the imperative
form is more meaningful. Additional discussion at:
https://llvm.discourse.group/t/mlir-cmake-enable-variable-naming-convention/3520
Switch all inconsistent ones to the ENABLE form. Keep the couple of old
mappings needed until buildbot config is migrated.
Differential Revision: https://reviews.llvm.org/D102976
* 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
* Also adds some verbiage about upgrading `pip` itself, since this is a
common source of issues.
Differential Revision: https://reviews.llvm.org/D99522
* Only leaf packages are non-namespace packages. This allows most of the top levels to be split into different directories or deployment packages. In the previous state, the presence of __init__.py files at each level meant that the entire tree could only ever exist in one physical directory on the path.
* This changes the API usage slightly: `import mlir` will no longer do a deep import of `mlir.ir`, etc. This may necessitate some client code changes.
* Dialect gen code was restructured so that the user is responsible for providing the `my_dialect.py` file, which then must import its peer `_my_dialect_ops_gen`. This gives complete control of the dialect namespace to the user instead of to tablegen code, allowing further dialect-specific python APIs.
* Correspondingly, the previous extension modules `_my_dialect.py` are now `_my_dialect_ops_ext.py`.
* Now that the `linalg` namespace is open, moved the `linalg_opdsl` tool into it.
* This may require some corresponding downstream adjustments to npcomp, circt, et al:
* Probably some shallow imports need to be converted to deep imports (i.e. not `import mlir` brings in the world).
* Each tablegen generated dialect now needs an explicit `foo.py` which does a `from ._foo_ops_gen import *`. This is similar to the way that generated code operates in the C++ world.
* If providing dialect op extensions, those need to be moved from `_foo.py` -> `_foo_ops_ext.py`.
Differential Revision: https://reviews.llvm.org/D98096
* As discussed, fixes the ordering or (operands, results) -> (results, operands) in various `create` like methods.
* Fixes a syntax error in an ODS accessor method.
* Removes the linalg example in favor of a test case that exercises the same.
* Fixes FuncOp visibility to properly use None instead of the empty string and defaults it to None.
* Implements what was documented for requiring that trailing __init__ args `loc` and `ip` are keyword only.
* Adds a check to `InsertionPoint.insert` so that if attempting to insert past the terminator, an exception is raised telling you what to do instead. Previously, this would crash downstream (i.e. when trying to print the resultant module).
* Renames `_ods_build_default` -> `build_generic` and documents it.
* Removes `result` from the list of prohibited words and for single-result ops, defaults to naming the result `result`, thereby matching expectations and what is already implemented on the base class.
* This was intended to be a relatively small set of changes to be inlined with the broader support for ODS generating the most specific builder, but it spidered out once actually testing various combinations, so rolling up separately.
Differential Revision: https://reviews.llvm.org/D95320
* This allows us to hoist trait level information for regions and sized-variadic to class level attributes (_ODS_REGIONS, _ODS_OPERAND_SEGMENTS, _ODS_RESULT_SEGMENTS).
* Eliminates some splicey python generated code in favor of a native helper for it.
* Makes it possible to implement custom, variadic and region based builders with one line of python, without needing to manually code access to the segment attributes.
* Needs follow-on work for region based callbacks and support for SingleBlockImplicitTerminator.
* A follow-up will actually add ODS support for generating custom Python builders that delegate to this new method.
* Also includes the start of an e2e sample for constructing linalg ops where this limitation was discovered (working progressively through this example and cleaning up as I go).
Differential Revision: https://reviews.llvm.org/D94738
* Development setup recommendations.
* Test updates to match what we actually do.
* Update cmake variable `PYTHON_EXECUTABLE` -> `Python3_EXECUTABLE` to match the upgrade to python3 repo wide.
* Makes `pip install pybind11` do the right thing with no further config.
* Since we now require a version of pybind11 greater than many LTS OS installs (>=2.6), a more convenient way to get a recent version is preferable.
* Also adds the version spec to find_package so it will skip older versions that may be lying around.
* Tested the full matrix of old system install, no system install, pip install and no pip install.
Differential Revision: https://reviews.llvm.org/D91903
- Add `mlirElementsAttrGetType` C API.
- Add `def_buffer` binding to PyDenseElementsAttribute.
- Implement the protocol to access the buffer.
Differential Revision: https://reviews.llvm.org/D91021
