[MLIR][python binding] Add OpaqueAttribute to python binding.

Reviewed By: ftynse

Differential Revision: https://reviews.llvm.org/D120847

[mlir][python] Support more types in IntegerAttr.value

Previously only accessing values for `index` and signless int types
would work; signed and unsigned ints would hit an assert in
`IntegerAttr::g

[mlir][python] Support more types in IntegerAttr.value

Previously only accessing values for `index` and signless int types
would work; signed and unsigned ints would hit an assert in
`IntegerAttr::getInt`. This exposes `IntegerAttr::get{S,U}Int` to the C
API and calls the appropriate function from the python bindings.

Reviewed By: ftynse

Differential Revision: https://reviews.llvm.org/D120194

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[mlir][python] 8b/16b DenseIntElements access

This extends dense attribute element access to support 8b and 16b ints.
Also extends the corresponding parts of the C api.

Reviewed By: ftynse

Differe

[mlir][python] 8b/16b DenseIntElements access

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

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Apply clang-tidy fixes for performance-unnecessary-value-param to MLIR (NFC)

Reviewed By: Mogball

Differential Revision: https://reviews.llvm.org/D116250

Fix more clang-tidy cleanups in mlir/ (NFC)

Fix clang-tidy issues in mlir/ (NFC)

Differential Revision: https://reviews.llvm.org/D115956

Fix clang-tidy issues in mlir/ (NFC)

Reviewed By: ftynse

Differential Revision: https://reviews.llvm.org/D115956

[mlir][python] Add pyi stub files to enable auto completion.

There is no completely automated facility for generating stubs that are both accurate and comprehensive for native modules. After some ex

[mlir][python] Add pyi stub files to enable auto completion.

There is no completely automated facility for generating stubs that are both accurate and comprehensive for native modules. After some experimentation, I found that MyPy's stubgen does the best at generating correct stubs with a few caveats that are relatively easy to fix:
* Some types resolve to cross module symbols incorrectly.
* staticmethod and classmethod signatures seem to always be completely generic and need to be manually provided.
* It does not generate an __all__ which, from testing, causes namespace pollution to be visible to IDE code completion.

As a first step, I did the following:
* Ran `stubgen` for `_mlir.ir`, `_mlir.passmanager`, and `_mlirExecutionEngine`.
* Manually looked for all instances where unnamed arguments were being emitted (i.e. as 'arg0', etc) and updated the C++ side to include names (and re-ran stubgen to get a good initial state).
* Made/noted a few structural changes to each `pyi` file to make it minimally functional.
* Added the `pyi` files to the CMake rules so they are installed and visible.

To test, I added a `.env` file to the root of the project with `PYTHONPATH=...` set as per instructions. Then reload the developer window (in VsCode) and verify that completion works for various changes to test cases.

There are still a number of overly generic signatures, but I want to check in this low-touch baseline before iterating on more ambiguous changes. This is already a big improvement.

Differential Revision: https://reviews.llvm.org/D114679

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[mlir][python] Add a __contains__ method to the python bindings for DictionaryAttr.

This makes it easier to check in python whether a certain attribute is there.

Differential Revision: https://revi

[mlir][python] Add a __contains__ method to the python bindings for DictionaryAttr.

This makes it easier to check in python whether a certain attribute is there.

Differential Revision: https://reviews.llvm.org/D112814

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[mlir][python] Temporarily disable test for converting unsupported DenseElementsAttr types to a buffer.

* Need to investigate the proper solution to https://github.com/pybind/pybind11/issues/3336 or

[mlir][python] Temporarily disable test for converting unsupported DenseElementsAttr types to a buffer.

* 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().

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[mlir] Extend C and Python API to support bulk loading of DenseElementsAttr.

* This already half existed in terms of reading the raw buffer backing a DenseElementsAttr.
* Documented the precise expe

[mlir] Extend C and Python API to support bulk loading of DenseElementsAttr.

* 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

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[mlir][python] Usability improvements for Python bindings

Provide a couple of quality-of-life usability improvements for Python bindings,
in particular:

* give access to the list of types for the

[mlir][python] Usability improvements for Python bindings

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

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[mlir][python] Apply py::module_local() to all classes.

* This allows multiple MLIR-API embedding downstreams to co-exist in the same process.
* I believe this is the last thing needed to enable iso

[mlir][python] Apply py::module_local() to all classes.

* 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

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[mlir] Move PyConcreteAttribute to header. NFC.

This allows out-of-tree users to derive PyConcreteAttribute to bind custom
attributes.

Reviewed By: nicolasvasilache

Differential Revision: https://

[mlir] Move PyConcreteAttribute to header. NFC.

This allows out-of-tree users to derive PyConcreteAttribute to bind custom
attributes.

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D101063

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[mlir] introduce "encoding" attribute to tensor type

This CL introduces a generic attribute (called "encoding") on tensors.
The attribute currently does not carry any concrete information, but the t

[mlir] introduce "encoding" attribute to tensor type

This CL introduces a generic attribute (called "encoding") on tensors.
The attribute currently does not carry any concrete information, but the type
system already correctly determines that tensor<8xi1,123> != tensor<8xi1,321>.
The attribute will be given meaning through an interface in subsequent CLs.

See ongoing discussion on discourse:

[RFC] Introduce a sparse tensor type to core MLIR
https://llvm.discourse.group/t/rfc-introduce-a-sparse-tensor-type-to-core-mlir/2944

A sparse tensor will look something like this:

```
// named alias with all properties we hold dear:
#CSR = {
// individual named attributes
}

// actual sparse tensor type:
tensor<?x?xf64, #CSR>
```

I see the following rough 5 step plan going forward:

(1) introduce this format attribute in this CL, currently still empty
(2) introduce attribute interface that gives it "meaning", focused on sparse in first phase
(3) rewrite sparse compiler to use new type, remove linalg interface and "glue"
(4) teach passes to deal with new attribute, by rejecting/asserting on non-empty attribute as simplest solution, or doing meaningful rewrite in the longer run
(5) add FE support, document, test, publicize new features, extend "format" meaning to other domains if useful

Reviewed By: stellaraccident, bondhugula

Differential Revision: https://reviews.llvm.org/D99548

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NFC: Break up the mlir python bindings into individual sources.

* IRModules.cpp -> (IRCore.cpp, IRAffine.cpp, IRAttributes.cpp, IRTypes.cpp).
* The individual pieces now compile in the 5-15s range w

NFC: Break up the mlir python bindings into individual sources.

* IRModules.cpp -> (IRCore.cpp, IRAffine.cpp, IRAttributes.cpp, IRTypes.cpp).
* The individual pieces now compile in the 5-15s range whereas IRModules.cpp was starting to approach a minute (didn't capture a before time).
* More fine grained splitting is possible, but this represents the most obvious.

Differential Revision: https://reviews.llvm.org/D98978

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