Revert "Revert "[mlir python] Add nanobind support (#119232)

Reverts revert #118517 after (hopefully) fixing builders
(https://github.com/llvm/llvm-zorg/pull/328,
https://github.com/llvm/llvm-zor

Revert "Revert "[mlir python] Add nanobind support (#119232)

Reverts revert #118517 after (hopefully) fixing builders
(https://github.com/llvm/llvm-zorg/pull/328,
https://github.com/llvm/llvm-zorg/pull/327)

This reverts commit 61bf308cf2fc32452f14861c102ace89f5f36fec.

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Revert "[mlir python] Add nanobind support for standalone dialects." (#118517)

Reverts llvm/llvm-project#117922 because deps aren't met on some of the
post-commit build bots.

[mlir python] Add nanobind support for standalone dialects. (#117922)

This PR allows out-of-tree dialects to write Python dialect modules
using nanobind instead of pybind11.

It may make sense to

[mlir python] Add nanobind support for standalone dialects. (#117922)

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.

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[mlir][python] Fix how the mlir variadic Python accessor `_ods_equally_sized_accessor` is used (#101132) (#106003)

As reported in https://github.com/llvm/llvm-project/issues/101132, this
fixes two

[mlir][python] Fix how the mlir variadic Python accessor `_ods_equally_sized_accessor` is used (#101132) (#106003)

As reported in https://github.com/llvm/llvm-project/issues/101132, this
fixes two bugs:

1. When accessing variadic operands inside an operation, it must be
accessed as `self.operation.operands` instead of `operation.operands`
2. The implementation of the `equally_sized_accessor` function is doing
wrong arithmetics when calculating the resulting index and group sizes.

I have added a test for the `equally_sized_accessor` function, which did
not have a test previously.

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[mlir][python] auto attribute casting (#97786)

[MLIR] fix _f64ElementsAttr in ir.py (#91176)

[mlir][python] enable registering dialects with the default `Context` (#72488)

[mlir][python] value casting (#69644)

This PR adds "value casting", i.e., a mechanism to wrap `ir.Value` in a
proxy class that overloads dunders such as `__add__`, `__sub__`, and
`__mul__` for fun

[mlir][python] value casting (#69644)

This PR adds "value casting", i.e., a mechanism to wrap `ir.Value` in a
proxy class that overloads dunders such as `__add__`, `__sub__`, and
`__mul__` for fun and great profit.

This is thematically similar to
https://github.com/llvm/llvm-project/commit/bfb1ba752655bf09b35c486f6cc9817dbedfb1bb
and
https://github.com/llvm/llvm-project/commit/9566ee280607d91fa2e5eca730a6765ac84dfd0f.
The example in the test demonstrates the value of the feature (no pun
intended):

```python
@register_value_caster(F16Type.static_typeid)
@register_value_caster(F32Type.static_typeid)
@register_value_caster(F64Type.static_typeid)
@register_value_caster(IntegerType.static_typeid)
class ArithValue(Value):
__add__ = partialmethod(_binary_op, op="add")
__sub__ = partialmethod(_binary_op, op="sub")
__mul__ = partialmethod(_binary_op, op="mul")

a = arith.constant(value=FloatAttr.get(f16_t, 42.42))
b = a + a
# CHECK: ArithValue(%0 = arith.addf %cst, %cst : f16)
print(b)

a = arith.constant(value=FloatAttr.get(f32_t, 42.42))
b = a - a
# CHECK: ArithValue(%1 = arith.subf %cst_0, %cst_0 : f32)
print(b)

a = arith.constant(value=FloatAttr.get(f64_t, 42.42))
b = a * a
# CHECK: ArithValue(%2 = arith.mulf %cst_1, %cst_1 : f64)
print(b)
```

**EDIT**: this now goes through the bindings and thus supports automatic
casting of `OpResult` (including as an element of `OpResultList`),
`BlockArgument` (including as an element of `BlockArgumentList`), as
well as `Value`.

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[mlir][python] fix python_test dialect and I32/I64ElementsBuilder (#70871)

This PR fixes the `I32ElementsAttr` and `I64ElementsAttr` builders and
tests them through the `python_test` dialect.

[mlir][python] fix `replace=True` for `register_operation` and `register_type_caster` (#70264)

<img
src="https://github.com/llvm/llvm-project/assets/5657668/443852b6-ac25-45bb-a38b-5dfbda09d5a7"
h

[mlir][python] fix `replace=True` for `register_operation` and `register_type_caster` (#70264)

<img
src="https://github.com/llvm/llvm-project/assets/5657668/443852b6-ac25-45bb-a38b-5dfbda09d5a7"
height="400" />
<p></p>


So turns out that none of the `replace=True` things actually work
because of the map caches (except for
`register_attribute_builder(replace=True)`, which doesn't use such a
cache). This was hidden by a series of unfortunate events:

1. `register_type_caster` failure was hidden because it was the same
`TestIntegerRankedTensorType` being replaced with itself (d'oh).
2. `register_operation` failure was hidden behind the "order of events"
in the lifecycle of typical extension import/use. Since extensions are
loaded/registered almost immediately after generated builders are
registered, there is no opportunity for the `operationClassMapCache` to
be populated (through e.g., `module.body.operations[2]` or
`module.body.operations[2].opview` or something). Of course as soon as
you as actually do "late-bind/late-register" the extension, you see it's
not successfully replacing the stale one in `operationClassMapCache`.

I'll take this opportunity to propose we ditch the caches all together.
I've been cargo-culting them but I really don't understand how they
work. There's this comment above `operationClassMapCache`

```cpp
/// Cache of operation name to external operation class object. This is
/// maintained on lookup as a shadow of operationClassMap in order for repeat
/// lookups of the classes to only incur the cost of one hashtable lookup.
llvm::StringMap<pybind11::object> operationClassMapCache;
```

But I don't understand how that's true given that the canonical thing
`operationClassMap` is already a map:

```cpp
/// Map of full operation name to external operation class object.
llvm::StringMap<pybind11::object> operationClassMap;
```

Maybe it wasn't always the case? Anyway things work now but it seems
like an unnecessary layer of complexity for not much gain? But maybe I'm
wrong.

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[mlir][python] Create all missing attribute builders.

This patch adds attribute builders for all buildable attributes from the
builtin dialect that did not previously have any. These builders can be

[mlir][python] Create all missing attribute builders.

This patch adds attribute builders for all buildable attributes from the
builtin dialect that did not previously have any. These builders can be
used to construct attributes of a particular type identified by a string
from a Python argument without knowing the details of how to pass that
Python argument to the attribute constructor. This is used, for example,
in the generated code of the Python bindings of ops.

The list of "all" attributes was produced with:

(
grep -h "ods_ir.AttrBuilder.get" $(find ../build/ -name "*_ops_gen.py") \
| cut -f2 -d"'"
git grep -ho "^def [a-zA-Z0-9_]*" -- include/mlir/IR/CommonAttrConstraints.td \
| cut -f2 -d" "
) | sort -u

Then, I only retained those that had an occurence in
`mlir/include/mlir/IR`. In particular, this drops many dialect-specific
attributes; registering those builders is something that those dialects
should do. Finally, I removed those attrbiutes that had a match in
`mlir/python/mlir/ir.py` already and implemented the remaining ones. The
only ones that still miss a builder now are the following:

* Represent more than one possible attribute type:
- `Any.*Attr` (9x)
- `IntNonNegative`
- `IntPositive`
- `IsNullAttr`
- `ElementsAttr`
* I am not sure what "constant attributes" are:
- `ConstBoolAttrFalse`
- `ConstBoolAttrTrue`
- `ConstUnitAttr`
* `Location` not exposed by Python bindings:
- `LocationArrayAttr`
- `LocationAttr`
* `get` function not implemented in Python bindings:
- `StringElementsAttr`

This patch also fixes a compilation problem with
`I64SmallVectorArrayAttr`.

Reviewed By: makslevental, rkayaith

Differential Revision: https://reviews.llvm.org/D159403

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[MLIR][python bindings] Fix inferReturnTypes + AttrSizedOperandSegments for optional operands

Right now `inferTypeOpInterface.inferReturnTypes` fails because there's a cast in there to `py::sequence

[MLIR][python bindings] Fix inferReturnTypes + AttrSizedOperandSegments for optional operands

Right now `inferTypeOpInterface.inferReturnTypes` fails because there's a cast in there to `py::sequence` which throws a `TypeError` when it tries to cast the `None`s. Note `None`s are inserted into `operands` for omitted operands passed to the generated builder:

```
operands.append(_get_op_result_or_value(start) if start is not None else None)
operands.append(_get_op_result_or_value(stop) if stop is not None else None)
operands.append(_get_op_result_or_value(step) if step is not None else None)
```

Note also that skipping appending to the list operands doesn't work either because [[ https://github.com/llvm/llvm-project/blob/27c37327da67020f938aabf0f6405f57d688441e/mlir/lib/Bindings/Python/IRCore.cpp#L1585 | build generic ]] checks against the number of operand segments expected.

Currently the only way around is to handroll through `ir.Operation.create`.

Reviewed By: rkayaith

Differential Revision: https://reviews.llvm.org/D151409

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[MLIR][python bindings] Add TypeCaster for returning refined types from python APIs

depends on D150839

This diff uses `MlirTypeID` to register `TypeCaster`s (i.e., `[](PyType pyType) -> DerivedTy {

[MLIR][python bindings] Add TypeCaster for returning refined types from python APIs

depends on D150839

This diff uses `MlirTypeID` to register `TypeCaster`s (i.e., `[](PyType pyType) -> DerivedTy { return pyType; }`) for all concrete types (i.e., `PyConcrete<...>`) that are then queried for (by `MlirTypeID`) and called in `struct type_caster<MlirType>::cast`. The result is that anywhere an `MlirType mlirType` is returned from a python binding, that `mlirType` is automatically cast to the correct concrete type. For example:

```
c0 = arith.ConstantOp(f32, 0.0)
# CHECK: F32Type(f32)
print(repr(c0.result.type))

unranked_tensor_type = UnrankedTensorType.get(f32)
unranked_tensor = tensor.FromElementsOp(unranked_tensor_type, [c0]).result

# CHECK: UnrankedTensorType
print(type(unranked_tensor.type).__name__)
# CHECK: UnrankedTensorType(tensor<*xf32>)
print(repr(unranked_tensor.type))
```

This functionality immediately extends to typed attributes (i.e., `attr.type`).

The diff also implements similar functionality for `mlir_type_subclass`es but in a slightly different way - for such types (which have no cpp corresponding `class` or `struct`) the user must provide a type caster in python (similar to how `AttrBuilder` works) or in cpp as a `py::cpp_function`.

Reviewed By: ftynse

Differential Revision: https://reviews.llvm.org/D150927

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[NFC][Py Reformat] Reformat python files in mlir subdir

This is an ongoing series of commits that are reformatting our
Python code.

Reformatting is done with `black`.

If you end up having problems

[NFC][Py Reformat] Reformat python files in mlir subdir

This is an ongoing series of commits that are reformatting our
Python code.

Reformatting is done with `black`.

If you end up having problems merging this commit because you
have made changes to a python file, the best way to handle that
is to run git checkout --ours <yourfile> and then reformat it
with black.

If you run into any problems, post to discourse about it and
we will try to help.

RFC Thread below:

https://discourse.llvm.org/t/rfc-document-and-standardize-python-code-style

Differential Revision: https://reviews.llvm.org/D150782

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[MLIR][python bindings] Expose TypeIDs in python

This diff adds python bindings for `MlirTypeID`. It paves the way for returning accurately typed `Type`s from python APIs (see D150927) and then furt

[MLIR][python bindings] Expose TypeIDs in python

This diff adds python bindings for `MlirTypeID`. It paves the way for returning accurately typed `Type`s from python APIs (see D150927) and then further along building type "conscious" `Value` APIs (see D150413).

Reviewed By: ftynse

Differential Revision: https://reviews.llvm.org/D150839

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[MLIR][python bindings] Add more basic AttrBuilder for _ops_gen.py files

Add more attribute builders, such as "F32Attr", "F64Attr" and "F64ArrayAttr", which are useful to create operations by python

[MLIR][python bindings] Add more basic AttrBuilder for _ops_gen.py files

Add more attribute builders, such as "F32Attr", "F64Attr" and "F64ArrayAttr", which are useful to create operations by python bindings. For example, tosa.clamp in _tosa_ops_gen.py need 'F32Attr'.

Reviewed By: ftynse

Differential Revision: https://reviews.llvm.org/D150757

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[MLIR] Add InferShapedTypeOpInterface bindings

Add C and python bindings for InferShapedTypeOpInterface
and ShapedTypeComponents. This allows users to invoke
InferShapedTypeOpInterface for ops that

[MLIR] Add InferShapedTypeOpInterface bindings

Add C and python bindings for InferShapedTypeOpInterface
and ShapedTypeComponents. This allows users to invoke
InferShapedTypeOpInterface for ops that implement it.

Reviewed By: ftynse

Differential Revision: https://reviews.llvm.org/D149494

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[MLIR][python bindings] implement `PyValue` subclassing to enable operator overloading

Differential Revision: https://reviews.llvm.org/D147758

[mlir][tblgen][ods][python] Use keyword-only arguments for optional builder arguments in generated Python bindings

This diff modifies `mlir-tblgen` to generate Python Operation class `__init__()`
fu

[mlir][tblgen][ods][python] Use keyword-only arguments for optional builder arguments in generated Python bindings

This diff modifies `mlir-tblgen` to generate Python Operation class `__init__()`
functions that use Python keyword-only arguments.

Previously, all `__init__()` function arguments were positional. Python code to
create MLIR Operations was required to provide values for ALL builder arguments,
including optional arguments (attributes and operands). Callers that did not
provide, for example, an optional attribute would be forced to provide `None`
as an argument for EACH optional attribute. Proposed changes in this diff use
`tblgen` record information (as provided by ODS) to generate keyword arguments
for:
- optional operands
- optional attributes (which includes unit attributes)
- default-valued attributes

These `__init__()` function keyword arguments have default `None` values (i.e.
the argument form is `optionalAttr=None`), allowing callers to create Operations
more easily.

Note that since optional arguments become keyword-only arguments (since they are
placed after the bare `*` argument), this diff will require ALL optional
operands and attributes to be provided using explicit keyword syntax. This may,
in the short term, break any out-of-tree Python code that provided values via
positional arguments. However, in the long term, it seems that requiring
keywords for optional arguments will be more robust to operation changes that
add arguments.

Tests were modified to reflect the updated Operation builder calling convention.

This diff partially addresses the requests made in the github issue below.

https://github.com/llvm/llvm-project/issues/54932

Reviewed By: stellaraccident, mikeurbach

Differential Revision: https://reviews.llvm.org/D124717

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[mlir] Better error message in PybindAdaptors.h

When attempting to cast a pybind11 handle to an MLIR C API object through
capsules, the binding code would attempt to directly access the "_CAPIPtr"
a

[mlir] Better error message in PybindAdaptors.h

When attempting to cast a pybind11 handle to an MLIR C API object through
capsules, the binding code would attempt to directly access the "_CAPIPtr"
attribute on the object, leading to a rather obscure AttributeError when the
attribute was missing, e.g., on non-MLIR types. Check for its presence and
throw a TypeError instead.

Depends On D117646

Reviewed By: stellaraccident

Differential Revision: https://reviews.llvm.org/D117658

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[mlir] Rework subclass construction in PybindAdaptors.h

The constructor function was being defined without indicating its "__init__"
name, which made it interpret it as a regular fuction rather than

[mlir] Rework subclass construction in PybindAdaptors.h

The constructor function was being defined without indicating its "__init__"
name, which made it interpret it as a regular fuction rather than a
constructor. When overload resolution failed, Pybind would attempt to print the
arguments actually passed to the function, including "self", which is not
initialized since the constructor couldn't be called. This would result in
"__repr__" being called with "self" referencing an uninitialized MLIR C API
object, which in turn would cause undefined behavior when attempting to print
in C++. Even if the correct name is provided, the mechanism used by
PybindAdaptors.h to bind constructors directly as "__init__" functions taking
"self" is deprecated by Pybind. The new mechanism does not seem to have access
to a fully-constructed "self" object (i.e., the constructor in C++ takes a
`pybind11::detail::value_and_holder` that cannot be forwarded back to Python).

Instead, redefine "__new__" to perform the required checks (there are no
additional initialization needed for attributes and types as they are all
wrappers around a C++ pointer). "__new__" can call its equivalent on a
superclass without needing "self".

Bump pybind11 dependency to 3.8.0, which is the first version that allows one
to redefine "__new__".

Reviewed By: stellaraccident

Differential Revision: https://reviews.llvm.org/D117646

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[mlir][Python] Fix generation of accessors for Optional

Previously, in case there was only one `Optional` operand/result within
the list, we would always return `None` from the accessor, e.g., for a

[mlir][Python] Fix generation of accessors for Optional

Previously, in case there was only one `Optional` operand/result within
the list, we would always return `None` from the accessor, e.g., for a
single optional result we would generate:

```
return self.operation.results[0] if len(self.operation.results) > 1 else None
```

But what we really want is to return `None` only if the length of
`results` is smaller than the total number of element groups (i.e.,
the optional operand/result is in fact missing).

This commit also renames a few local variables in the generator to make
the distinction between `isVariadic()` and `isVariableLength()` a bit
more clear.

Reviewed By: ftynse

Differential Revision: https://reviews.llvm.org/D113855

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[mlir][python] Infer result types in generated constructors whenever possible

In several cases, operation result types can be unambiguously inferred from
operands and attributes at operation constru

[mlir][python] Infer result types in generated constructors whenever possible

In several cases, operation result types can be unambiguously inferred from
operands and attributes at operation construction time. Stop requiring the user
to provide these types as arguments in the ODS-generated constructors in Python
bindings. In particular, handle the SameOperandAndResultTypes and
FirstAttrDerivedResultType traits as well as InferTypeOpInterface using the
recently added interface support. This is a significant usability improvement
for IR construction, similar to what C++ ODS provides.

Depends On D111656

Reviewed By: gysit

Differential Revision: https://reviews.llvm.org/D111811

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[mlir] support interfaces in Python bindings

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

[mlir] support interfaces in Python bindings

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

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Defend early against operation created without a registered dialect

Reviewed By: rriddle

Differential Revision: https://reviews.llvm.org/D105961