[MemRef] Migrate away from PointerUnion::{is,get} (NFC) (#120202)

Note that PointerUnion::{is,get} have been soft deprecated in
PointerUnion.h:

// FIXME: Replace the uses of is(), get() and dy

[MemRef] Migrate away from PointerUnion::{is,get} (NFC) (#120202)

Note that PointerUnion::{is,get} have been soft deprecated in
PointerUnion.h:

// FIXME: Replace the uses of is(), get() and dyn_cast() with
// isa<T>, cast<T> and the llvm::dyn_cast<T>

I'm not touching PointerUnion::dyn_cast for now because it's a bit
complicated; we could blindly migrate it to dyn_cast_if_present, but
we should probably use dyn_cast when the operand is known to be
non-null.

show more ...

[mlir]Fix compose subview (#80551)

I found a bug in `test-compose-subview`,You can see the example I gave.
```
#map = affine_map<() -> ()>
module {
func.func private @fun(%arg0: memref<10x10xf

[mlir]Fix compose subview (#80551)

I found a bug in `test-compose-subview`,You can see the example I gave.
```
#map = affine_map<() -> ()>
module {
func.func private @fun(%arg0: memref<10x10xf32>, %arg1: memref<5x5xf32>) -> memref<5x5xf32> {
%c0 = arith.constant 0 : index
%c5 = arith.constant 5 : index
%c1 = arith.constant 1 : index
%subview = memref.subview %arg0[0, 0] [5, 5] [1, 1] : memref<10x10xf32> to memref<5x5xf32, strided<[10, 1]>>
%alloc = memref.alloc() : memref<5x5xf32>
scf.for %arg2 = %c0 to %c5 step %c1 {
scf.for %arg3 = %c0 to %c5 step %c1 {
%subview_0 = memref.subview %subview[%arg2, %arg3] [1, 1] [1, 1] : memref<5x5xf32, strided<[10, 1]>> to memref<f32, strided<[], offset: ?>>
%subview_1 = memref.subview %arg1[%arg2, %arg3] [1, 1] [1, 1] : memref<5x5xf32> to memref<f32, strided<[], offset: ?>>
%alloc_2 = memref.alloc() : memref<f32>
linalg.generic {indexing_maps = [#map, #map, #map], iterator_types = []} ins(%subview_0, %subview_1 : memref<f32, strided<[], offset: ?>>, memref<f32, strided<[], offset: ?>>) outs(%alloc_2 : memref<f32>) {
^bb0(%in: f32, %in_4: f32, %out: f32):
%0 = arith.addf %in, %in_4 : f32
linalg.yield %0 : f32
}
%subview_3 = memref.subview %alloc[%arg2, %arg3] [1, 1] [1, 1] : memref<5x5xf32> to memref<f32, strided<[], offset: ?>>
memref.copy %alloc_2, %subview_3 : memref<f32> to memref<f32, strided<[], offset: ?>>
}
}
return %alloc : memref<5x5xf32>
}
func.func @test(%arg0: memref<10x10xf32>, %arg1: memref<5x5xf32>) -> memref<5x5xf32> {
%0 = call @fun(%arg0, %arg1) : (memref<10x10xf32>, memref<5x5xf32>) -> memref<5x5xf32>
return %0 : memref<5x5xf32>
}
}
```
When I run `mlir-opt test.mlir ---test-compose-subview`.
```
test.mlir:14:9: error: 'linalg.generic' op expected operand rank (2) to match the result rank of indexing_map #0 (0)
linalg.generic {indexing_maps = [#map, #map, #map], iterator_types = []} ins(%subview_0, %subview_1 : memref<f32, strided<[], offset: ?>>, memref<f32, strided<[], offset: ?>>) outs(%alloc_2 : memref<f32>) {
^
test1.mlir:14:9: note: see current operation:
"linalg.generic"(%4, %5, %6) <{indexing_maps = [affine_map<() -> ()>, affine_map<() -> ()>, affine_map<() -> ()>], iterator_types = [], operandSegmentSizes = array<i32: 2, 1>}> ({
^bb0(%arg4: f32, %arg5: f32, %arg6: f32):
%8 = "arith.addf"(%arg4, %arg5) <{fastmath = #arith.fastmath<none>}> : (f32, f32) -> f32
"linalg.yield"(%8) : (f32) -> ()
}) : (memref<1x1xf32, strided<[10, 1], offset: ?>>, memref<f32, strided<[], offset: ?>>, memref<f32>) -> ()
```
This PR fixes that.In the meantime I've extended this PR to handle cases
where stride is greater than 1.
```
func.func private @Unknown0(%arg0: memref<10x10xf32>, %arg1: memref<5x5xf32>) -> memref<5x5xf32> {
%c0 = arith.constant 0 : index
%c5 = arith.constant 5 : index
%c1 = arith.constant 1 : index
%subview = memref.subview %arg0[0, 0] [5, 5] [2, 2] : memref<10x10xf32> to memref<5x5xf32, strided<[20, 2]>>
%alloc = memref.alloc() : memref<5x5xf32>
scf.for %arg2 = %c0 to %c5 step %c1 {
scf.for %arg3 = %c0 to %c5 step %c1 {
%subview_0 = memref.subview %subview[%arg2, %arg3] [1, 1] [1, 1] : memref<5x5xf32, strided<[20, 2]>> to memref<f32, strided<[], offset: ?>>
%subview_1 = memref.subview %arg1[%arg2, %arg3] [1, 1] [1, 1] : memref<5x5xf32> to memref<f32, strided<[], offset: ?>>
%alloc_2 = memref.alloc() : memref<f32>
linalg.generic {indexing_maps = [affine_map<() -> ()>, affine_map<() -> ()>, affine_map<() -> ()>], iterator_types = []} ins(%subview_0, %subview_1 : memref<f32, strided<[], offset: ?>>, memref<f32, strided<[], offset: ?>>) outs(%alloc_2 : memref<f32>) {
^bb0(%in: f32, %in_4: f32, %out: f32):
%0 = arith.addf %in, %in_4 : f32
linalg.yield %0 : f32
}
%subview_3 = memref.subview %alloc[%arg2, %arg3] [1, 1] [1, 1] : memref<5x5xf32> to memref<f32, strided<[], offset: ?>>
memref.copy %alloc_2, %subview_3 : memref<f32> to memref<f32, strided<[], offset: ?>>
}
}
return %alloc : memref<5x5xf32>
}
$ mlir-opt test.mlir -test-compose-subview
#map = affine_map<()[s0] -> (s0 * 2)>
#map1 = affine_map<() -> ()>
module {
func.func private @Unknown0(%arg0: memref<10x10xf32>, %arg1: memref<5x5xf32>) -> memref<5x5xf32> {
%c0 = arith.constant 0 : index
%c5 = arith.constant 5 : index
%c1 = arith.constant 1 : index
%alloc = memref.alloc() : memref<5x5xf32>
scf.for %arg2 = %c0 to %c5 step %c1 {
scf.for %arg3 = %c0 to %c5 step %c1 {
%0 = affine.apply #map()[%arg2]
%1 = affine.apply #map()[%arg3]
%subview = memref.subview %arg0[%0, %1] [1, 1] [2, 2] : memref<10x10xf32> to memref<f32, strided<[], offset: ?>>
%subview_0 = memref.subview %arg1[%arg2, %arg3] [1, 1] [1, 1] : memref<5x5xf32> to memref<f32, strided<[], offset: ?>>
%alloc_1 = memref.alloc() : memref<f32>
linalg.generic {indexing_maps = [#map1, #map1, #map1], iterator_types = []} ins(%subview, %subview_0 : memref<f32, strided<[], offset: ?>>, memref<f32, strided<[], offset: ?>>) outs(%alloc_1 : memref<f32>) {
^bb0(%in: f32, %in_3: f32, %out: f32):
%2 = arith.addf %in, %in_3 : f32
linalg.yield %2 : f32
}
%subview_2 = memref.subview %alloc[%arg2, %arg3] [1, 1] [1, 1] : memref<5x5xf32> to memref<f32, strided<[], offset: ?>>
memref.copy %alloc_1, %subview_2 : memref<f32> to memref<f32, strided<[], offset: ?>>
}
}
return %alloc : memref<5x5xf32>
}
}
```

show more ...

[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.

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 patch updates all remaining uses of the deprecated functionality in
mlir/. This was done with clang-tidy as described below and further
modifications to GPUBase.td and OpenMPOpsInterfaces.td.

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:
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.

```
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
```

Differential Revision: https://reviews.llvm.org/D151542

show more ...

[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

show more ...

[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

[mlir] (NFC) run clang-format on all files

[mlir] Flip accessors to prefixed form (NFC)

Another mechanical sweep to keep diff small for flip to _Prefixed.

Rename PatternRewriteSet::insert to add

insert is soft deprecated, so remove all references so it's less likely
to be used and can be easily removed in the future.

Differential Revision: https://re

Rename PatternRewriteSet::insert to add

insert is soft deprecated, so remove all references so it's less likely
to be used and can be easily removed in the future.

Differential Revision: https://reviews.llvm.org/D120021

show more ...

[mlir] Finish replacing OwningRewritePatternList with RewritePatternSet

OwningRewritePatternList has been deprecated for ~10 months now, we can remove
the leftover using directives at this point.

D

[mlir] Finish replacing OwningRewritePatternList with RewritePatternSet

OwningRewritePatternList has been deprecated for ~10 months now, we can remove
the leftover using directives at this point.

Differential Revision: https://reviews.llvm.org/D118287

show more ...

[mlir] Move ComposeSubView+ExpandOps from Standard to MemRef

These transformations already operate on memref operations (as part of
splitting up the standard dialect). Now that the operations have m

[mlir] Move ComposeSubView+ExpandOps from Standard to MemRef

These transformations already operate on memref operations (as part of
splitting up the standard dialect). Now that the operations have moved,
it's time for these transformations to move as well.

Differential Revision: https://reviews.llvm.org/D118285

show more ...