Use callables directly in any_of, count_if, etc (NFC)

[mlir][VectorToLLVM] Fix bug in lowering of vector.reduce fmax/fmin

The lowering of fmax/fmin reduce was ignoring the optional accumulator.

Differential Revision: https://reviews.llvm.org/D129597

[mlir][Vector] Fix reordering of floating point adds during lower of `vector.contract`.

Adding the accumulator value after the `vector.contract` changes the
precision of the operation. This makes su

[mlir][Vector] Fix reordering of floating point adds during lower of `vector.contract`.

Adding the accumulator value after the `vector.contract` changes the
precision of the operation. This makes sure the accumulator is carried
through to `vector.reduce` (and down to LLVM).

Differential Revision: https://reviews.llvm.org/D128674

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[mlir][vector][nfc] Rename index optimizations option

We are using "enable-index-optimizations" and "indexOptimizations" as
names for an optimization that consists of using i32 for indices within
a

[mlir][vector][nfc] Rename index optimizations option

We are using "enable-index-optimizations" and "indexOptimizations" as
names for an optimization that consists of using i32 for indices within
a vector. For instance, when building a vector comparison for mask
generation. The name is confusing and suggests a scope beyond these
vector indices. This change makes the function of the option explicit
in its name.

Differential Revision: https://reviews.llvm.org/D122415

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[mlir] Flip Vector dialect accessors used to prefixed form.

This has been on _Both for a couple of weeks. Flip usages in core with
intention to flip flag to _Prefixed in follow up. Needed to add a c

[mlir] Flip Vector dialect accessors used to prefixed form.

This has been on _Both for a couple of weeks. Flip usages in core with
intention to flip flag to _Prefixed in follow up. Needed to add a couple
of helper methods in AffineOps and Linalg to facilitate a pure flag flip
in follow up as some of these classes are used in templates and so
sensitive to Vector dialect changes.

Differential Revision: https://reviews.llvm.org/D122151

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[mlir][Vector] Enable create_mask for scalable vectors

The way vector.create_mask is currently lowered is
vector-length-dependent, and therefore incompatible with scalable vector
types. This patch a

[mlir][Vector] Enable create_mask for scalable vectors

The way vector.create_mask is currently lowered is
vector-length-dependent, and therefore incompatible with scalable vector
types. This patch adds an alternative lowering path for create_mask
operations that return a scalable vector mask.

Differential Revision: https://reviews.llvm.org/D118248

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[mlir] Trim a huge number of unnecessary dependencies on the Func dialect

The Func has a large number of legacy dependencies carried over from the old
Standard dialect, which was pervasive and conta

[mlir] Trim a huge number of unnecessary dependencies on the Func dialect

The Func has a large number of legacy dependencies carried over from the old
Standard dialect, which was pervasive and contained a large number of varied
operations. With the split of the standard dialect and its demise, a lot of lingering
dead dependencies have survived to the Func dialect. This commit removes a
large majority of then, greatly reducing the dependence surface area of the
Func dialect.

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[mlir] Rename the Standard dialect to the Func dialect

The last remaining operations in the standard dialect all revolve around
FuncOp/function related constructs. This patch simply handles the init

[mlir] Rename the Standard dialect to the Func dialect

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

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[mlir][vector][NFC] Use CombiningKindAttr instead of StringAttr

This makes the op consistent with other ops in vector dialect.

Differential Revision: https://reviews.llvm.org/D119343

[mlir][NFC] Remove a few op builders that simply swap parameter order

Differential Revision: https://reviews.llvm.org/D119093

[mlir] Split std.splat into tensor.splat and vector.splat

This is part of the larger effort to split the standard dialect. This will also allow for pruning some
additional dependencies on Standard (

[mlir] Split std.splat into tensor.splat and vector.splat

This is part of the larger effort to split the standard dialect. This will also allow for pruning some
additional dependencies on Standard (done in a followup).

Differential Revision: https://reviews.llvm.org/D118202

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[mlir][vector][NFC] Split into IR, Transforms and Utils

This reduces the dependencies of the MLIRVector target and makes the dialect consistent with other dialects.

Differential Revision: https://r

[mlir][vector][NFC] Split into IR, Transforms and Utils

This reduces the dependencies of the MLIRVector target and makes the dialect consistent with other dialects.

Differential Revision: https://reviews.llvm.org/D118533

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Apply clang-tidy fixes for performance-for-range-copy to MLIR (NFC)

[mlir][RFC] Add scalable dimensions to VectorType

With VectorType supporting scalable dimensions, we don't need many of
the operations currently present in ArmSVE, like mask generation and
basic ari

[mlir][RFC] Add scalable dimensions to VectorType

With VectorType supporting scalable dimensions, we don't need many of
the operations currently present in ArmSVE, like mask generation and
basic arithmetic instructions. Therefore, this patch also gets
rid of those.

Having built-in scalable vector support also simplifies the lowering of
scalable vector dialects down to LLVMIR.

Scalable dimensions are indicated with the scalable dimensions
between square brackets:

vector<[4]xf32>

Is a scalable vector of 4 single precission floating point elements.

More generally, a VectorType can have a set of fixed-length dimensions
followed by a set of scalable dimensions:

vector<2x[4x4]xf32>

Is a vector with 2 scalable 4x4 vectors of single precission floating
point elements.

The scale of the scalable dimensions can be obtained with the Vector
operation:

%vs = vector.vscale

This change is being discussed in the discourse RFC:

https://llvm.discourse.group/t/rfc-add-built-in-support-for-scalable-vector-types/4484

Differential Revision: https://reviews.llvm.org/D111819

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[mlir][Vector] Support 0-D vectors in `BitCastOp`

The implementation only allows to bit-cast between two 0-D vectors. We could
probably support casting from/to vectors like `vector<1xf32>`, but I wa

[mlir][Vector] Support 0-D vectors in `BitCastOp`

The implementation only allows to bit-cast between two 0-D vectors. We could
probably support casting from/to vectors like `vector<1xf32>`, but I wasn't
convinced that this would be important and it would require breaking the
invariant that `BitCastOp` works only on vectors with equal rank.

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D114854

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Revert "[MLIR] Update Vector To LLVM conversion to be aware of assume_alignment"

This reverts commit 29a50c5864ddab283c1ff38694fb5926ce37b39a.

After LLVM lowering, the original patch incorrectly mo

Revert "[MLIR] Update Vector To LLVM conversion to be aware of assume_alignment"

This reverts commit 29a50c5864ddab283c1ff38694fb5926ce37b39a.

After LLVM lowering, the original patch incorrectly moved alignment
information across an unconstrained GEP operation. This is only correct
for some index offsets in the GEP. It seems that the best approach is,
in fact, to rely on LLVM to propagate information from the llvm.assume()
to users.

Thanks to Thomas Raoux for catching this.

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[mlir][Vector] Support 0-D vectors in `VectorPrintOpConversion`

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D114549

[mlir][Vector] Thread 0-d vectors through InsertElementOp.

This revision makes concrete use of 0-d vectors to extend the semantics of
InsertElementOp.

Reviewed By: dcaballe, pifon2a

Differential R

[mlir][Vector] Thread 0-d vectors through InsertElementOp.

This revision makes concrete use of 0-d vectors to extend the semantics of
InsertElementOp.

Reviewed By: dcaballe, pifon2a

Differential Revision: https://reviews.llvm.org/D114388

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[mlir][Vector] Thread 0-d vectors through ExtractElementOp.

This revision starts making concrete use of 0-d vectors to extend the semantics of
ExtractElementOp.
In the process a new VectorOfAnyRank

[mlir][Vector] Thread 0-d vectors through ExtractElementOp.

This revision starts making concrete use of 0-d vectors to extend the semantics of
ExtractElementOp.
In the process a new VectorOfAnyRank Tablegen OpBase.td is added to allow progressive transition to supporting 0-d vectors by gradually opting in.

Differential Revision: https://reviews.llvm.org/D114387

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[mlir][Linalg] Add bounded recursion declaration to FMAOp -> LLVM conversion.

FMAOp -> LLVM conversion is done progressively by peeling off 1 dimension from FMAOp at each pattern iteration. Add the

[mlir][Linalg] Add bounded recursion declaration to FMAOp -> LLVM conversion.

FMAOp -> LLVM conversion is done progressively by peeling off 1 dimension from FMAOp at each pattern iteration. Add the recursively bounded property declaration to the pattern so that the rewriter can apply it multiple times.

Without this, FMAOps with 3+D do not lower to LLVM.

Differential Revision: https://reviews.llvm.org/D113886

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[mlir:DialectConversion] Restructure how argument/target materializations get invoked

The current implementation invokes materializations
whenever an input operand does not have a mapping for the
de

[mlir:DialectConversion] Restructure how argument/target materializations get invoked

The current implementation invokes materializations
whenever an input operand does not have a mapping for the
desired type, i.e. it requires materialization at the earliest possible
point. This conflicts with goal of dialect conversion (and also the
current documentation) which states that a materialization is only
required if the materialization is supposed to persist after the
conversion process has finished.

This revision refactors this such that whenever a target
materialization "might" be necessary, we insert an
unrealized_conversion_cast to act as a temporary materialization.
This allows for deferring the invocation of the user
materialization hooks until the end of the conversion process,
where we actually have a better sense if it's actually
necessary. This has several benefits:

* In some cases a target materialization hook is no longer
necessary
When performing a full conversion, there are some situations
where a temporary materialization is necessary. Moving forward,
these users won't need to provide any target materializations,
as the temporary materializations do not require the user to
provide materialization hooks.

* getRemappedValue can now handle values that haven't been
converted yet
Before this commit, it wasn't well supported to get the remapped
value of a value that hadn't been converted yet (making it
difficult/impossible to convert multiple operations in many
situations). This commit updates getRemappedValue to properly
handle this case by inserting temporary materializations when
necessary.

Another code-health related benefit is that with this change we
can move a majority of the complexity related to materializations
to the end of the conversion process, instead of handling adhoc
while conversion is happening.

Differential Revision: https://reviews.llvm.org/D111620

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[mlir][Vector] NFC - Add option to hook vector.transpose lowering to strategies.

This revision also moves some code around to improve overall structure.

Differential Revision: https://reviews.llvm.

[mlir][Vector] NFC - Add option to hook vector.transpose lowering to strategies.

This revision also moves some code around to improve overall structure.

Differential Revision: https://reviews.llvm.org/D112437

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[mlir][Vector] NFC - Extract rewrites related to insert/extract strided slice in a separate file.

Differential Revision: https://reviews.llvm.org/D112301

[mlir][RFC] Refactor layout representation in MemRefType

The change is based on the proposal from the following discussion:
https://llvm.discourse.group/t/rfc-memreftype-affine-maps-list-vs-single-i

[mlir][RFC] Refactor layout representation in MemRefType

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

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[MLIR] Replace std ops with arith dialect ops

Precursor: https://reviews.llvm.org/D110200

Removed redundant ops from the standard dialect that were moved to the
`arith` or `math` dialects.

Renamed

[MLIR] Replace std ops with arith dialect ops

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

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