[mlir] Use value instead of getValue (NFC)

[mlir] Use has_value instead of hasValue (NFC)

[mlir] Flip accessors to prefixed form (NFC)

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

[mlir][memref][NFC] Silence compiler warnings

[mlir][memref] Improve type inference for rank-reducing subviews

The result shape of a rank-reducing subview cannot be inferred in the general case. Just the result rank is not enough. The only thin

[mlir][memref] Improve type inference for rank-reducing subviews

The result shape of a rank-reducing subview cannot be inferred in the general case. Just the result rank is not enough. The only thing that we can infer is the layout map.

This change also improves the bufferization patterns of tensor.extract_slice and tensor.insert_slice to fully support rank-reducing operations.

Differential Revision: https://reviews.llvm.org/D129144

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[mlir] Flip MemRef dialect to _Both (NFC)

Revert "Don't use Optional::hasValue (NFC)"

This reverts commit aa8feeefd3ac6c78ee8f67bf033976fc7d68bc6d.

Don't use Optional::hasValue (NFC)

[mlir][memref] Fix layout map computation in inferRankReducedResultType

Differential Revision: https://reviews.llvm.org/D128160

[mlir] Don't use Optional::getValue (NFC)

[mlir] Don't use Optional::hasValue (NFC)

[mlir][MemRef] Fix a crash when expanding a scalar shape

In this case the reassociation is empty, yielding no strides for the
result type.

Differential Revision: https://reviews.llvm.org/D127232

[AsmParser] Introduce a new "Argument" abstraction + supporting logic

MLIR has a common pattern for "arguments" that uses syntax
like `%x : i32 {attrs} loc("sourceloc")` which is implemented
in adho

[AsmParser] Introduce a new "Argument" abstraction + supporting logic

MLIR has a common pattern for "arguments" that uses syntax
like `%x : i32 {attrs} loc("sourceloc")` which is implemented
in adhoc ways throughout the codebase. The approach this uses
is verbose (because it is implemented with parallel arrays) and
inconsistent (e.g. lots of things drop source location info).

Solve this by introducing OpAsmParser::Argument and make addRegion
(which sets up BlockArguments for the region) take it. Convert the
world to propagating this down. This means that we correctly
capture and propagate source location information in a lot more
cases (e.g. see the affine.for testcase example), and it also
simplifies much code.

Differential Revision: https://reviews.llvm.org/D124649

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Fix CollapsedLayoutMap for dim size 1 case

This change fixes `CollapsedLayoutMap` for cases where the collapsed
dims are size 1. The cases where inner most dims are size 1 and
noncontiguous can be r

Fix CollapsedLayoutMap for dim size 1 case

This change fixes `CollapsedLayoutMap` for cases where the collapsed
dims are size 1. The cases where inner most dims are size 1 and
noncontiguous can be represented by the strided form and therefore can
be allowed. For such cases, the new stride should be of the next entry
in an association whose dimension is not size 1. If the next entry is
dynamic, it's not possible to decide which stride to use at compilation
time and the stride is set to dynamic.

Differential Revision: https://reviews.llvm.org/D124137

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[mlir] Move isGuaranteedCollapsible to CollapseShapeOp (NFC).

It seems more natural than to have it as a static method of ExpandShapeOp.
Also fix a typo ("the the" -> "the").

Differential Revision:

[mlir] Move isGuaranteedCollapsible to CollapseShapeOp (NFC).

It seems more natural than to have it as a static method of ExpandShapeOp.
Also fix a typo ("the the" -> "the").

Differential Revision: https://reviews.llvm.org/D124234

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Apply clang-tidy fixes for performance-for-range-copy in MemRefOps.cpp (NFC)

[mlir][tensor] Fix verifier and bufferization of collapse_shape

Insert a buffer copy unless the dims are guaranteed to be collapsible. In the verifier, accept collapses unless they are guaranteed to

[mlir][tensor] Fix verifier and bufferization of collapse_shape

Insert a buffer copy unless the dims are guaranteed to be collapsible. In the verifier, accept collapses unless they are guaranteed to be non-collapsible.

Differential Revision: https://reviews.llvm.org/D123316

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Revert "Revert "[mlir] Rewrite canonicalization of collapse(expand) and expand(collapse).""

This reverts commit 96e9b6c9dc60946f08399def879a19395bc98107.

[mlir][MemRef] Allow transposed layouts in ExpandShapeOp.

https://reviews.llvm.org/D122641 introduced fixes to the ExpandShapeOp verifier
but also introduced an artificial layout limitation that pre

[mlir][MemRef] Allow transposed layouts in ExpandShapeOp.

https://reviews.llvm.org/D122641 introduced fixes to the ExpandShapeOp verifier
but also introduced an artificial layout limitation that prevents the consideration of transposed layouts.

This revision fixes the omissions and reimplements the logic using saturated arithmetic which is more
idiomatic and avoids leaking internal implementation details.

Tests cases are added for transposed layouts.

Reviewed By: springerm

Differential Revision: https://reviews.llvm.org/D122845

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Revert "[mlir] Rewrite canonicalization of collapse(expand) and expand(collapse)."

This reverts commit 64f659bee67b5a024defeb3cd2ecf65e1ad8c0a7.

An invalid tensor.expand_shape op is generated with

Revert "[mlir] Rewrite canonicalization of collapse(expand) and expand(collapse)."

This reverts commit 64f659bee67b5a024defeb3cd2ecf65e1ad8c0a7.

An invalid tensor.expand_shape op is generated with the commit. To repro:

$ mlir-opt -canonicalize a.mlir

```
func @foo(%0: tensor<1x1xf32>, %1: tensor<1x1xf32>, %2: tensor<1x1xf32>) -> tensor<1x1xf32> {
%cst = arith.constant 0.000000e+00 : f32
%3 = linalg.init_tensor [8, 1] : tensor<8x1xf32>
%4 = linalg.fill ins(%cst : f32) outs(%3 : tensor<8x1xf32>) -> tensor<8x1xf32>
%5 = tensor.collapse_shape %0 [] : tensor<1x1xf32> into tensor<f32>
%6 = tensor.insert_slice %5 into %4[0, 0] [1, 1] [1, 1] : tensor<f32> into tensor<8x1xf32>
%7 = linalg.init_tensor [8, 1] : tensor<8x1xf32>
%8 = linalg.fill ins(%cst : f32) outs(%7 : tensor<8x1xf32>) -> tensor<8x1xf32>
%9 = tensor.collapse_shape %2 [] : tensor<1x1xf32> into tensor<f32>
%10 = tensor.insert_slice %9 into %8[0, 0] [1, 1] [1, 1] : tensor<f32> into tensor<8x1xf32>
%11 = tensor.collapse_shape %6 [[0, 1]] : tensor<8x1xf32> into tensor<8xf32>
%12 = linalg.init_tensor [8] : tensor<8xf32>
%13 = linalg.generic {indexing_maps = [affine_map<(d0) -> (d0)>, affine_map<(d0) -> (d0)>], iterator_types = ["parallel"]} ins(%11 : tensor<8xf32>) outs(%12 : tensor<8xf32>) {
^bb0(%arg3: f32, %arg4: f32):
linalg.yield %arg3 : f32
} -> tensor<8xf32>
%14 = tensor.expand_shape %13 [[0, 1, 2, 3]] : tensor<8xf32> into tensor<1x1x8x1xf32>
%15 = tensor.collapse_shape %1 [] : tensor<1x1xf32> into tensor<f32>
%16 = linalg.init_tensor [] : tensor<f32>
%17 = linalg.generic {indexing_maps = [affine_map<() -> ()>, affine_map<() -> ()>], iterator_types = []} ins(%15 : tensor<f32>) outs(%16 : tensor<f32>) {
^bb0(%arg3: f32, %arg4: f32):
linalg.yield %arg3 : f32
} -> tensor<f32>
%18 = tensor.expand_shape %17 [] : tensor<f32> into tensor<1x1x1x1xf32>
%19 = tensor.collapse_shape %10 [[0, 1]] : tensor<8x1xf32> into tensor<8xf32>
%20 = linalg.init_tensor [8] : tensor<8xf32>
%21 = linalg.generic {indexing_maps = [affine_map<(d0) -> (d0)>, affine_map<(d0) -> (d0)>], iterator_types = ["parallel"]} ins(%19 : tensor<8xf32>) outs(%20 : tensor<8xf32>) {
^bb0(%arg3: f32, %arg4: f32):
linalg.yield %arg3 : f32
} -> tensor<8xf32>
%22 = tensor.expand_shape %21 [[0, 1, 2, 3]] : tensor<8xf32> into tensor<1x1x8x1xf32>
%23 = linalg.mmt4d {comment = "f32*f32->f32, aarch64, matrix*vector"} ins(%14, %18 : tensor<1x1x8x1xf32>, tensor<1x1x1x1xf32>) outs(%22 : tensor<1x1x8x1xf32>) -> tensor<1x1x8x1xf32>
%24 = tensor.collapse_shape %23 [[0, 1, 2, 3]] : tensor<1x1x8x1xf32> into tensor<8xf32>
%25 = linalg.init_tensor [8] : tensor<8xf32>
%26 = linalg.generic {indexing_maps = [affine_map<(d0) -> (d0)>, affine_map<(d0) -> (d0)>], iterator_types = ["parallel"]} ins(%24 : tensor<8xf32>) outs(%25 : tensor<8xf32>) {
^bb0(%arg3: f32, %arg4: f32):
linalg.yield %arg3 : f32
} -> tensor<8xf32>
%27 = tensor.expand_shape %26 [[0, 1]] : tensor<8xf32> into tensor<8x1xf32>
%28 = tensor.extract_slice %27[0, 0] [1, 1] [1, 1] : tensor<8x1xf32> to tensor<f32>
%29 = tensor.expand_shape %28 [] : tensor<f32> into tensor<1x1xf32>
return %29 : tensor<1x1xf32>
}
```

Differential Revision: https://reviews.llvm.org/D123161

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[mlir] Rewrite canonicalization of collapse(expand) and expand(collapse).

Differential Revision: https://reviews.llvm.org/D122666

[mlir][memref][NFC] Remove unused function

This fixes a compiler warning.

[mlir][memref] Fix CollapseShapeOp verifier

Differential Revision: https://reviews.llvm.org/D122647

[mlir][memref] Fix ExpandShapeOp verifier

* Complete rewrite of the verifier.
* CollapseShapeOp verifier will be updated in a subsequent commit.
* Update and expand op documentation.
* Add a new bui

[mlir][memref] Fix ExpandShapeOp verifier

* Complete rewrite of the verifier.
* CollapseShapeOp verifier will be updated in a subsequent commit.
* Update and expand op documentation.
* Add a new builder that infers the result type based on the source type, result shape and reassociation indices. In essence, only the result layout map is inferred.

Differential Revision: https://reviews.llvm.org/D122641

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[mlir][MemRef] Fix warning on unsigned comparison

Fix warning in clang introduced in D121766.

Reviewed By: mehdi_amini

Differential Revision: https://reviews.llvm.org/D122333