[mlir][IR][NFC] Move free-standing functions to `MemRefType` (#123465)

Turn free-standing `MemRefType`-related helper functions in
`BuiltinTypes.h` into member functions.

[mlir][vector] Switch to using `getNumScalableDims` (nfc) (#100806)

mlir/MathExtras: consolidate with llvm/MathExtras (#95087)

This patch is part of a project to move the Presburger library into
LLVM.

[mlir][linalg] Fix the semantic use of a flag (#90081)

`useInBoundsInsteadOfMasking` was doing the opposite i.e., when set to
true; was updating the mask instead of updating the inBounds.

Make createReadOrMaskedRead and isValidMaskedInputVector vector utilities (#89119)

Made the createReadOrMaskedRead and isValidMaskedInputVector utility
functions - to be accessible outside of the C

Make createReadOrMaskedRead and isValidMaskedInputVector vector utilities (#89119)

Made the createReadOrMaskedRead and isValidMaskedInputVector utility
functions - to be accessible outside of the CU. Needed by the IREE new
TopK implementation.

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[mlir][vector] Add support for scalable vectors to VectorLinearize (#86786)

Adds support for scalable vectors to patterns defined in
VectorLineralize.cpp.

Linearization is disable in 2 notable c

[mlir][vector] Add support for scalable vectors to VectorLinearize (#86786)

Adds support for scalable vectors to patterns defined in
VectorLineralize.cpp.

Linearization is disable in 2 notable cases:
* vectors with more than 1 scalable dimension (we cannot represent
vscale^2),
* vectors initialised with arith.constant that's not a vector splat
(such arith.constant Ops cannot be flattened).

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[mlir][linalg] Enable masked vectorisation for depthwise convolutions (#81625)

This patch adds support for masked vectorisation of depthwise 1D WC
convolutions,`linalg.depthwise_conv_1d_nwc_wc`. Th

[mlir][linalg] Enable masked vectorisation for depthwise convolutions (#81625)

This patch adds support for masked vectorisation of depthwise 1D WC
convolutions,`linalg.depthwise_conv_1d_nwc_wc`. This is implemented by
adding support for masking.

Two major assumptions are made:
* only the channel dimension can be dynamic/scalable (i.e. the
trailing dim),
* when specifying vector sizes to use in the vectoriser, only the size
corresponding to the channel dim is effectively used (other dims are
inferred from the context).

In terms of scalable vectorisation, this should be sufficient to cover
all practical cases (i.e. making arbitrary dim scalable wouldn't make
much sense). As for more generic cases with dynamic shapes (e.g. W or N
dims being dynamic), more work would be needed. In particular, one would
have to consider the filter and input/output tensors separately.

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[mlir][VectorOps] Add unrolling for n-D vector.interleave ops (#80967)

This unrolls n-D vector.interleave ops like:

```mlir
vector.interleave %i, %j : vector<6x3xf32>
```

To a sequence of 1-

[mlir][VectorOps] Add unrolling for n-D vector.interleave ops (#80967)

This unrolls n-D vector.interleave ops like:

```mlir
vector.interleave %i, %j : vector<6x3xf32>
```

To a sequence of 1-D operations:
```mlir
%i_0 = vector.extract %i[0]
%j_0 = vector.extract %j[0]
%res_0 = vector.interleave %i_0, %j_0 : vector<3xf32>
vector.insert %res_0, %result[0] :
// ... repeated x6
```

The 1-D operations can then be directly lowered to LLVM.

Depends on: #80966

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[mlir] Introduce `trailingNDimsContiguous` for MemRefs (#78247)

Extracts logic from `vector::isContiguousSlice` to check whether
the trailing dim of a memref are contiguous into a dedicated hook
i

[mlir] Introduce `trailingNDimsContiguous` for MemRefs (#78247)

Extracts logic from `vector::isContiguousSlice` to check whether
the trailing dim of a memref are contiguous into a dedicated hook
in BuiitinTypes.{h|cpp}.

Follow-up for https://github.com/llvm/llvm-project/pull/76848.

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[mlir][vector] Don't treat memrefs with empty stride as non-contiguous (#76848)

As per the docs [1]:

```
In absence of an explicit layout, a memref is considered to have a
multi-dimensional ide

[mlir][vector] Don't treat memrefs with empty stride as non-contiguous (#76848)

As per the docs [1]:

```
In absence of an explicit layout, a memref is considered to have a
multi-dimensional identity affine map layout.
```

This patch makes sure that MemRefs with no strides (i.e. no explicit
layout) are treated as contiguous when checking whether a particular
vector is a contiguous slice of the given MemRef.

[1] https://mlir.llvm.org/docs/Dialects/Builtin/#layout

Follow-up for #76428.

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[mlir] Check if the stride tensor is empty. (#76428)

Added a check to see if the stride tensor is empty. If so then return
false for isContiguousSlice function.

Possible fix for #74463

[mlir][Vector] Update patterns for flattening vector.xfer Ops (2/N) (#73523)

Updates patterns for flattening `vector.transfer_read` by relaxing the
requirement that the "collapsed" indices are all

[mlir][Vector] Update patterns for flattening vector.xfer Ops (2/N) (#73523)

Updates patterns for flattening `vector.transfer_read` by relaxing the
requirement that the "collapsed" indices are all zero. This enables
collapsing cases like this one:

```mlir
%2 = vector.transfer_read %arg4[%c0, %arg0, %arg1, %c0] ... :
memref<1x43x4x6xi32>, vector<1x2x6xi32>
```

Previously only the following case would be consider for collapsing
(all indices are 0):

```mlir
%2 = vector.transfer_read %arg4[%c0, %c0, %c0, %c0] ... :
memref<1x43x4x6xi32>, vector<1x2x6xi32>
```

Also adds some new comments and renames the `firstContiguousInnerDim`
parameter as `firstDimToCollapse` (the latter better matches the actual
meaning).

Similar updates for `vector.transfer_write` will be implemented in a
follow-up patch.

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[mlir][Vector] Update patterns for flattening vector.xfer Ops (1/N) (#73522)

Updates "flatten vector" patterns to support more cases, namely Ops that
read/write vectors with leading unit dims. For

[mlir][Vector] Update patterns for flattening vector.xfer Ops (1/N) (#73522)

Updates "flatten vector" patterns to support more cases, namely Ops that
read/write vectors with leading unit dims. For example:

```mlir
%0 = vector.transfer_read %arg0[%c0, %c0, %c0, %c0] ... :
memref<5x4x3x2xi8, strided<[24, 6, 2, 1], offset: ?>>, vector<1x1x2x2xi8>
```

Currently, the `vector.transfer_read` above would not be flattened. With
this
change, it will be rewritten as follows:
```mlir
%collapse_shape = memref.collapse_shape %arg0 [[0, 1, 2, 3]] :
memref<5x4x3x2xi8, strided<[24, 6, 2, 1], offset: ?>>
into memref<120xi8, strided<[1], offset: ?>>
%0 = vector.transfer_read %collapse_shape[%c0] ... :
memref<120xi8, strided<[1], offset: ?>>, vector<4xi8>
%1 = vector.shape_cast %0 : vector<4xi8> to vector<1x1x2x2xi8>
```

`hasMatchingInnerContigousShape` is generalised and renamed as
`isContiguousSlice` to better match the updated functionality. A few
test names are updated to better highlight what case is being exercised.

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[mlir][vector] Modernize `vector.transpose` op (#72594)

* Declare arguments/results with `let` statements.
* Rename `transp` to `permutation`.
* Change type of `transp` from `I64ArrayAttr` to `Den

[mlir][vector] Modernize `vector.transpose` op (#72594)

* Declare arguments/results with `let` statements.
* Rename `transp` to `permutation`.
* Change type of `transp` from `I64ArrayAttr` to `DenseI64ArrayAttr`
(provides direct access to `ArrayRef<int64_t>` instead of `ArrayAttr`).

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fix unused variable warnings in conditionals

warning was updated in 92023b15099012a657da07ebf49dd7d94a260f84

[mlir] Move casting calls from methods to function calls

The MLIR classes Type/Attribute/Operation/Op/Value support
cast/dyn_cast/isa/dyn_cast_or_null functionality through llvm's doCast
functionali

[mlir] Move casting calls from methods to function calls

The MLIR classes Type/Attribute/Operation/Op/Value support
cast/dyn_cast/isa/dyn_cast_or_null functionality through llvm's doCast
functionality in addition to defining methods with the same name.
This change begins the migration of uses of the method to the
corresponding function call as has been decided as more consistent.

Note that there still exist classes that only define methods directly,
such as AffineExpr, and this does not include work currently to support
a functional cast/isa call.

Caveats include:
- This clang-tidy script probably has more problems.
- This only touches C++ code, so nothing that is being generated.

Context:
- https://mlir.llvm.org/deprecation/ at "Use the free function variants
for dyn_cast/cast/isa/…"
- Original discussion at https://discourse.llvm.org/t/preferred-casting-style-going-forward/68443

Implementation:
This first patch was created with the following steps. The intention is
to only do automated changes at first, so I waste less time if it's
reverted, and so the first mass change is more clear as an example to
other teams that will need to follow similar steps.

Steps are described per line, as comments are removed by git:
0. Retrieve the change from the following to build clang-tidy with an
additional check:
https://github.com/llvm/llvm-project/compare/main...tpopp:llvm-project:tidy-cast-check
1. Build clang-tidy
2. Run clang-tidy over your entire codebase while disabling all checks
and enabling the one relevant one. Run on all header files also.
3. Delete .inc files that were also modified, so the next build rebuilds
them to a pure state.
4. Some changes have been deleted for the following reasons:
- Some files had a variable also named cast
- Some files had not included a header file that defines the cast
functions
- Some files are definitions of the classes that have the casting
methods, so the code still refers to the method instead of the
function without adding a prefix or removing the method declaration
at the same time.

```
ninja -C $BUILD_DIR clang-tidy

run-clang-tidy -clang-tidy-binary=$BUILD_DIR/bin/clang-tidy -checks='-*,misc-cast-functions'\
-header-filter=mlir/ mlir/* -fix

rm -rf $BUILD_DIR/tools/mlir/**/*.inc

git restore mlir/lib/IR mlir/lib/Dialect/DLTI/DLTI.cpp\
mlir/lib/Dialect/Complex/IR/ComplexDialect.cpp\
mlir/lib/**/IR/\
mlir/lib/Dialect/SparseTensor/Transforms/SparseVectorization.cpp\
mlir/lib/Dialect/Vector/Transforms/LowerVectorMultiReduction.cpp\
mlir/test/lib/Dialect/Test/TestTypes.cpp\
mlir/test/lib/Dialect/Transform/TestTransformDialectExtension.cpp\
mlir/test/lib/Dialect/Test/TestAttributes.cpp\
mlir/unittests/TableGen/EnumsGenTest.cpp\
mlir/test/python/lib/PythonTestCAPI.cpp\
mlir/include/mlir/IR/
```

Differential Revision: https://reviews.llvm.org/D150123

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[mlir][vector] Generalize vector.transpose lowering to n-D vectors

The existing vector.transpose lowering patterns only triggers if the
input vector is 2D. The revision extends the pattern to handle

[mlir][vector] Generalize vector.transpose lowering to n-D vectors

The existing vector.transpose lowering patterns only triggers if the
input vector is 2D. The revision extends the pattern to handle n-D
vectors which are effectively 2-D vectors (e.g., vector<1x4x1x8x1).

It refactors a common check about 2-D vectors from X86Vector
lowering to VectorUtils.h so it can be reused by both sides.

Reviewed By: dcaballe

Differential Revision: https://reviews.llvm.org/D149908

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[mlir][Affine][NFC] Wrap dialect in "affine" namespace

This cleanup aligns the affine dialect with all the other dialects.

Differential Revision: https://reviews.llvm.org/D148687

[NFC][mlir] VectorUtils / IndexingUtils simplifications and cleanups

This revision refactors and cleans up a bunch of infra related to vector, shapes and indexing into more reusable APIs.

Different

[NFC][mlir] VectorUtils / IndexingUtils simplifications and cleanups

This revision refactors and cleans up a bunch of infra related to vector, shapes and indexing into more reusable APIs.

Differential Revision: https://reviews.llvm.org/D138501

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Return None instead of Optional<T>() (NFC)

This patch replaces:

return Optional<T>();

with:

return None;

to make the migration from llvm::Optional to std::optional easier.
Specifically, I ca

Return None instead of Optional<T>() (NFC)

This patch replaces:

return Optional<T>();

with:

return None;

to make the migration from llvm::Optional to std::optional easier.
Specifically, I can deprecate None (in my source tree, that is) to
identify all the instances of None that should be replaced with
std::nullopt.

Note that "return None" far outnumbers "return Optional<T>();". There
are more than 2000 instances of "return None" in our source tree.

All of the instances in this patch come from functions that return
Optional<T> except Archive::findSym and ASTNodeImporter::import, where
we return Expected<Optional<T>>. Note that we can construct
Expected<Optional<T>> from any parameter convertible to Optional<T>,
which None certainly is.

This is part of an effort to migrate from llvm::Optional to
std::optional:

https://discourse.llvm.org/t/deprecating-llvm-optional-x-hasvalue-getvalue-getvalueor/63716

Differential Revision: https://reviews.llvm.org/D138464

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[mlir][arith] Fix -Wunused-but-set-variable

[mlir][arith] Change dialect name from Arithmetic to Arith

Suggested by @lattner in https://discourse.llvm.org/t/rfc-define-precise-arith-semantics/65507/22.

Tested with:
`ninja check-mlir check-ml

[mlir][arith] Change dialect name from Arithmetic to Arith

Suggested by @lattner in https://discourse.llvm.org/t/rfc-define-precise-arith-semantics/65507/22.

Tested with:
`ninja check-mlir check-mlir-integration check-mlir-mlir-spirv-cpu-runner check-mlir-mlir-vulkan-runner check-mlir-examples`

and `bazel build --config=generic_clang @llvm-project//mlir:all`.

Reviewed By: lattner, Mogball, rriddle, jpienaar, mehdi_amini

Differential Revision: https://reviews.llvm.org/D134762

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[mlir] Use C++17 structured bindings instead of std::tie where applicable. NFCI

[mlir][vector] Fix crash in vector.reduction canonicalization

since vector.reduce support accumulator in all the cases remove the
assert assuming old definition.

Differential Revision: https://revi

[mlir][vector] Fix crash in vector.reduction canonicalization

since vector.reduce support accumulator in all the cases remove the
assert assuming old definition.

Differential Revision: https://reviews.llvm.org/D129602

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Don't use Optional::hasValue (NFC)