Commit Graph

149 Commits

Author SHA1 Message Date
Ramkumar Ramachandra
22426110c5 mlir/tblgen: use std::optional in generation
This is part of an effort to migrate from llvm::Optional to
std::optional. This patch changes the way mlir-tblgen generates .inc
files, and modifies tests and documentation appropriately. It is a "no
compromises" patch, and doesn't leave the user with an unpleasant mix of
llvm::Optional and std::optional.

A non-trivial change has been made to ControlFlowInterfaces to split one
constructor into two, relating to a build failure on Windows.

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

Signed-off-by: Ramkumar Ramachandra <r@artagnon.com>

Differential Revision: https://reviews.llvm.org/D138934
2022-12-17 11:13:26 +01:00
Matthias Springer
e07149c91f [mlir][linalg] Add option to generate rank-reducing slices in DropUnitDims
This change extends the `ReplaceUnitExtents` pattern so that users can choose between of two strategies for generating rank reductions:
* CollapseShapeOp / ExpandShapeOp (was already implemented but code was cleaned up; default strategy)
* rank-reducing ExtractSliceOp / InsertSliceOp

Also add helper functions to the memref dialect that we already have on the tensor dialect: `getMixedSizes`, `createCanonicalRankReducingSubViewOp`, `rankReduceIfNeeded`.

We are using ReassociationIndices instead of ReassoicationExprs in many other places and this makes the code easier to read. Also adding a new test case (that also passed before).

Differential Revision: https://reviews.llvm.org/D139947
2022-12-14 14:10:04 +01:00
Matthias Springer
17f36648e6 [mlir][memref] Fold no-op subview(subview(x)) ops
Differential Revision: https://reviews.llvm.org/D140008
2022-12-14 12:47:00 +01:00
Aliia Khasanova
ded75a282a Remove sentinel argument from dispatchIndexOpFoldResults.
Post clean-up after merger of kDynamicSize and kDynamicStrideOrOffset.

Differential Revision: https://reviews.llvm.org/D139929
2022-12-13 14:04:46 +01:00
Quentin Colombet
9cbd136db4 [mlir][NFC] Add a new getStridesAndOffset function
The new function is a wrapper around the regular `getStridesAndOffset`
that offers a more compact way (as in writing less code) of getting the
relevant information.

This method is intended to be used only when it is known that the
LogicalResult of the regular `getStridesAndOffset` must be "succeeded".

This warpper will assert on that.

Differential Revision: https://reviews.llvm.org/D139529
2022-12-07 13:58:28 +00:00
Kazu Hirata
1a36588ec6 [mlir] Use std::nullopt instead of None (NFC)
This patch mechanically replaces None with std::nullopt where the
compiler would warn if None were deprecated.  The intent is to reduce
the amount of manual work required in migrating from Optional to
std::optional.

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
2022-12-03 18:50:27 -08:00
Lorenzo Chelini
a9733b8a5e [MLIR] Adopt DenseI64ArrayAttr in tensor, memref and linalg transform
This commit is a first step toward removing inconsistencies between dynamic
and static attributes (i64 v. index) by dropping `I64ArrayAttr` and
using `DenseI64ArrayAttr` in Tensor, Memref and Linalg Transform ops.
In Linalg Transform ops only `TileToScfForOp` and `TileOp` have been updated.

See related discussion: https://discourse.llvm.org/t/rfc-inconsistency-between-dynamic-and-static-attributes-i64-v-index/66612/1

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D138567
2022-11-25 09:43:30 +01:00
Matthias Springer
f2d91a7ae1 [mlir][utils] Fix invalid reshapes in ComposeCollapseOfExpandOp
Do not generate CollapseShapeOps/ExpandShapeOps that have the same source and result shape. Generate casts instead. Such reshapes became invalid with D138498.

Differential Revision: https://reviews.llvm.org/D138557
2022-11-23 13:52:00 +01:00
Matthias Springer
b9745ad812 [mlir][tensor/memref] Disallow Collapse/ExpandShapeOps that do not reduce/increase the rank
CollapseShapeOp/ExpandShapeOp that do not change the rank (or increase/reduce it) are invalid.

Differential Revision: https://reviews.llvm.org/D138498
2022-11-23 09:19:35 +01:00
Matthias Springer
6052b17aab [mlir][tensor] Add dim(expand_shape/collapse_shape) folding
Differential Revision: https://reviews.llvm.org/D138487
2022-11-22 17:34:49 +01:00
Aliia Khasanova
399638f98c Merge kDynamicSize and kDynamicSentinel into one constant.
resolve conflicts

Differential Revision: https://reviews.llvm.org/D138282
2022-11-21 13:01:26 +00:00
Mahesh Ravishankar
fc367dfa67 [mlir] Remove Transforms/SideEffectUtils.h and move the methods into Interface/SideEffectInterfaces.h.
The methods in `SideEffectUtils.h` (and their implementations in
`SideEffectUtils.cpp`) seem to have similar intent to methods already
existing in `SideEffectInterfaces.h`. Move the decleration (and
implementation) from `SideEffectUtils.h` (and `SideEffectUtils.cpp`)
into `SideEffectInterfaces.h` (and `SideEffectInterface.cpp`).

Also drop the `SideEffectInterface::hasNoEffect` method in favor of
`mlir::isMemoryEffectFree` which actually recurses into the operation
instead of just relying on the `hasRecursiveMemoryEffectTrait`
exclusively.

Differential Revision: https://reviews.llvm.org/D137857
2022-11-15 20:07:35 +00:00
Quentin Colombet
42263fb52d [mlir][MemRef] Make reinterpret_cast(extract_strided_metadata) more robust
Prior to this patch the canonicalization pattern that turns
`reinterpret_cast(extract_strided_metadata)` into cast was only applied
when all the input operands of the `reinterpret_cast` are exactly all the
output results of the `extract_strided_metadata`.

This missed simplification opportunities when the values would have hold
the same constant values, but yet, come from different actual values.

E.g., prior to this patch, a pattern of the form:
```
%base, %offset = extract_strided_metadata %source : memref<i16>
reinterpret_cast %base to offset:[0]
```
Wouldn't have been simplified into a simple cast, because %offset is not
directly the same value object as 0.

This patch teaches this pattern how to check if the constant values
match what the results of the `extract_strided_metadata` operation would
have hold.

Differential Revision: https://reviews.llvm.org/D135736
2022-11-14 18:02:15 +00:00
Aliia Khasanova
fb4cedcc1e [mlir][nfc] Clean-up usage of kDynamicSize.
This patch prepares MLIR code base to change the value of kDynamicSize.
https://discourse.llvm.org/t/rfc-unify-kdynamicsize-and-kdynamicstrideoroffset/64534/4

Differential Revision: https://reviews.llvm.org/D136327
2022-10-20 13:54:57 +00:00
Quentin Colombet
98c529652a [mlir][MemRef] Move the forwarding patterns for extract_strided_metadata
The `SimplifyExtractStridedMetadata` pass features a pattern that forward
statically known information (offset, sizes, strides) to their respective
users.

This patch moves this pattern from this pass to the
`extract_strided_metadata` folding patterns.

Differential Revision: https://reviews.llvm.org/D135797
2022-10-18 22:34:50 +00:00
Quentin Colombet
657f68b1f2 [NFC][mlir][MemRef] Make use of InferTypeOpInterface
The `InferTypeOpInterface` generates builders for things it can infer
the types.
Thanks to that interface we can:
- Eliminate a builder for DimOp, and
- Describe how to infer the result types of `extract_strided_metadata`
  from its source, and get a simpler builder as a result

NFC

Differential Revision: https://reviews.llvm.org/D135734
2022-10-14 18:49:37 +00:00
Sanjoy Das
adabce4118 Correctly model undefined behavior in {tensor|memref}.dim
These operations have undefined behavior if the index is not less than the rank of the source tensor / memref, so they cannot be freely speculated like they were before this patch.  After this patch we speculate them only if we can prove that they don't have UB.

Depends on D135505.

Reviewed By: mravishankar

Differential Revision: https://reviews.llvm.org/D135748
2022-10-12 17:30:13 -07:00
Sanjoy Das
86771d0b65 Introduce a ConditionallySpeculatable op interface
This patch takes the first step towards a more principled modeling of undefined behavior in MLIR as discussed in the following discourse threads:

 1. https://discourse.llvm.org/t/semantics-modeling-undefined-behavior-and-side-effects/4812
 2. https://discourse.llvm.org/t/rfc-mark-tensor-dim-and-memref-dim-as-side-effecting/65729

This patch in particular does the following:

 1. Introduces a ConditionallySpeculatable OpInterface that dynamically determines whether an Operation can be speculated.
 2. Re-defines `NoSideEffect` to allow undefined behavior, making it necessary but not sufficient for speculation.  Also renames it to `NoMemoryEffect`.
 3. Makes LICM respect the above semantics.
 4. Changes all ops tagged with `NoSideEffect` today to additionally implement ConditionallySpeculatable and mark themselves as always speculatable.  This combined trait is named `Pure`.  This makes this change NFC.

For out of tree dialects:

 1. Replace `NoSideEffect` with `Pure` if the operation does not have any memory effects, undefined behavior or infinite loops.
 2. Replace `NoSideEffect` with `NoSideEffect` otherwise.

The next steps in this process are (I'm proposing to do these in upcoming patches):

 1. Update operations like `tensor.dim`, `memref.dim`, `scf.for`, `affine.for` to implement a correct hook for `ConditionallySpeculatable`.  I'm also happy to update ops in other dialects if the respective dialect owners would like to and can give me some pointers.
 2. Update other passes that speculate operations to consult `ConditionallySpeculatable` in addition to `NoMemoryEffect`.  I could not find any other than LICM on a quick skim, but I could have missed some.
 3. Add some documentation / FAQs detailing the differences between side effects, undefined behavior, speculatabilty.

Reviewed By: rriddle, mehdi_amini

Differential Revision: https://reviews.llvm.org/D135505
2022-10-12 10:56:12 -07:00
Nicolas Vasilache
46869eebdc [mlir][Memref] NFC - Addresult pretty printing to MemrefOps
Differential Revision: https://reviews.llvm.org/D134968
2022-10-04 00:05:16 -07:00
Jakub Kuderski
abc362a107 [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
2022-09-29 11:23:28 -04:00
bixia1
9f13b9346b [mlir][memref] Add realloc op.
Add memref.realloc and canonicalization of the op. Add conversion patterns for
lowering the op to LLVM using unaligned alloc or aligned alloc based on the
conversion option.

Add filecheck tests for parsing and converting the op. Add an integration test.

Reviewed By: ftynse

Differential Revision: https://reviews.llvm.org/D133424
2022-09-21 08:04:00 -07:00
Matthias Springer
04ff6009fc [mlir][tensor][bufferize] Implement getBufferType for Expand/CollapseShapeOp
This function must be implemented for all ops, where the result memref type is different from the input memref type.

Differential Revision: https://reviews.llvm.org/D134331
2022-09-21 18:31:59 +09:00
Johannes Reifferscheid
d7c606f5b7 Fix bufferization of collapse_shape of subviews with size 1 dims.
Currently, there's an optimization that claims dimensions of size 1 are always
contiguous. This is not necessarily the case for subviews.

```
Input:

[
  [
    [0, 1],
    [2, 3]
  ],
  [
    [4, 5]
    [6, 7]
  ]
]

Subview:

  [
    [
      [0, 1],
    ],
    [
      [4, 5]
    ]
  ]
```

The old logic treats this subview as contiguous, when it is not.

Reviewed By: ftynse

Differential Revision: https://reviews.llvm.org/D134026
2022-09-16 11:32:30 +02:00
Alex Zinenko
46b90a7b5d [mlir] make remaining memref dialect ops produce strided layouts
The three following ops in the memref dialect: transpose, expand_shape,
collapse_shape, have been originally designed to operate on memrefs with
strided layouts but had to go through the affine map representation as the type
did not support anything else. Make these ops produce memref values with
StridedLayoutAttr instead now that it is available.

Depends On D133938

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D133947
2022-09-16 10:56:48 +02:00
Alex Zinenko
2791162b01 [mlir] make memref.subview produce strided layout
Memref subview operation has been initially designed to work on memrefs with
strided layouts only and has never supported anything else. Port it to use the
recently added StridedLayoutAttr instead of extracting the strided from
implicitly from affine maps.

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D133938
2022-09-16 10:56:46 +02:00
Alex Zinenko
519847fefc [mlir] materialize strided memref layout as attribute
Introduce a new attribute to represent the strided memref layout. Strided
layouts are omnipresent in code generation flows and are the only kind of
layouts produced and supported by a half of operation in the memref dialect
(view-related, shape-related). However, they are internally represented as
affine maps that require a somewhat fragile extraction of the strides from the
linear form that also comes with an overhead. Furthermore, textual
representation of strided layouts as affine maps is difficult to read: compare
`affine_map<(d0, d1, d2)[s0, s1] -> (d0*32 + d1*s0 + s1 + d2)>` with
`strides: [32, ?, 1], offset: ?`. While a rudimentary support for parsing a
syntactically sugared version of the strided layout has existed in the codebase
for a long time, it does not go as far as this commit to make the strided
layout a first-class attribute in the IR.

This introduces the attribute and updates the tests that using the pre-existing
sugared form to use the new attribute instead. Most memref created
programmatically, e.g., in passes, still use the affine form with further
extraction of strides and will be updated separately.

Update and clean-up the memref type documentation that has gotten stale and has
been referring to the details of affine map composition that are long gone.

See https://discourse.llvm.org/t/rfc-materialize-strided-memref-layout-as-an-attribute/64211.

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D132864
2022-08-30 17:19:58 +02:00
Quentin Colombet
ba916c0cf6 [mlir][MemRef] Canonicalize reinterpret_cast(extract_strided_metadata)
Add a canonicalizetion step for
reinterpret_cast(extract_strided_metadata).
This step replaces this sequence of operations by either:
- A noop, i.e., the original memref is directly used, or
- A plain cast of the original memref

The choice is ultimately made based on whether the original memref type
is equal to what the reinterpret_cast iss producing. For instance, the
reinterpret_cast could be changing some dimensions from static to
dynamic and in such case, we need to keep a cast.

The transformation is currently only performed when the reinterpret_cast
uses exactly the same arguments as what the extract_strided_metadata
produces. It may be possible to be more aggressive here but I wanted to
start with a relatively simple MLIR patch for my first one!

Differential Revision: https://reviews.llvm.org/D132776
2022-08-29 17:00:50 +00:00
Jeff Niu
e179532284 [mlir] Remove types from attributes
This patch removes the `type` field from `Attribute` along with the
`Attribute::getType` accessor.

Going forward, this means that attributes in MLIR will no longer have
types as a first-class concept. This patch lays the groundwork to
incrementally remove or refactor code that relies on generic attributes
being typed. The immediate impact will be on attributes that rely on
`Attribute` containing a type, such as `IntegerAttr`,
`DenseElementsAttr`, and `ml_program::ExternAttr`, which will now need
to define a type parameter on their storage classes. This will save
memory as all other attribute kinds will no longer contain a type.

Moreover, it will not be possible to generically query the type of an
attribute directly. This patch provides an attribute interface
`TypedAttr` that implements only one method, `getType`, which can be
used to generically query the types of attributes that implement the
interface. This interface can be used to retain the concept of a "typed
attribute". The ODS-generated accessor for a `type` parameter
automatically implements this method.

Next steps will be to refactor the assembly formats of certain operations
that rely on `parseAttribute(type)` and `printAttributeWithoutType` to
remove special handling of type elision until `type` can be removed from
the dialect parsing hook entirely; and incrementally remove uses of
`TypedAttr`.

Reviewed By: lattner, rriddle, jpienaar

Differential Revision: https://reviews.llvm.org/D130092
2022-07-31 20:01:31 -04:00
Kazu Hirata
c27d815249 [mlir] Use value instead of getValue (NFC) 2022-07-14 00:19:59 -07:00
Kazu Hirata
491d27013d [mlir] Use has_value instead of hasValue (NFC) 2022-07-13 00:57:02 -07:00
Jacques Pienaar
136d746ec7 [mlir] Flip accessors to prefixed form (NFC)
Another mechanical sweep to keep diff small for flip to _Prefixed.
2022-07-10 21:19:11 -07:00
Matthias Springer
58809a1eb1 [mlir][memref][NFC] Silence compiler warnings 2022-07-05 17:01:40 +02:00
Matthias Springer
6c3c5f8069 [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
2022-07-05 16:49:07 +02:00
Jacques Pienaar
655dc02cb0 [mlir] Flip MemRef dialect to _Both (NFC) 2022-06-26 20:45:25 -07:00
Kazu Hirata
3b7c3a654c Revert "Don't use Optional::hasValue (NFC)"
This reverts commit aa8feeefd3.
2022-06-25 11:56:50 -07:00
Kazu Hirata
aa8feeefd3 Don't use Optional::hasValue (NFC) 2022-06-25 11:55:57 -07:00
Matthias Springer
858be16670 [mlir][memref] Fix layout map computation in inferRankReducedResultType
Differential Revision: https://reviews.llvm.org/D128160
2022-06-21 10:08:26 +02:00
Kazu Hirata
6d5fc1e3d5 [mlir] Don't use Optional::getValue (NFC) 2022-06-20 23:20:25 -07:00
Kazu Hirata
037f09959a [mlir] Don't use Optional::hasValue (NFC) 2022-06-20 11:22:37 -07:00
Benjamin Kramer
6eb0f8e285 [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
2022-06-08 09:37:40 +02:00
Chris Lattner
d85eb4e2d6 [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
2022-04-29 12:19:34 -07:00
Yi Zhang
1cddcfdc3c 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
2022-04-22 17:48:24 -04:00
Adrian Kuegel
a74e5a89b9 [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
2022-04-22 10:31:25 +02:00
Mehdi Amini
722a3a58e2 Apply clang-tidy fixes for performance-for-range-copy in MemRefOps.cpp (NFC) 2022-04-19 07:23:12 +00:00
Matthias Springer
d7a9bf9143 [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
2022-04-08 18:20:40 +09:00
Alexander Belyaev
747b10be95 Revert "Revert "[mlir] Rewrite canonicalization of collapse(expand) and expand(collapse).""
This reverts commit 96e9b6c9dc.
2022-04-06 12:18:30 +02:00
Nicolas Vasilache
fc8f465a00 [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
2022-04-06 04:19:30 -04:00
Hanhan Wang
96e9b6c9dc Revert "[mlir] Rewrite canonicalization of collapse(expand) and expand(collapse)."
This reverts commit 64f659bee6.

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
2022-04-05 15:05:41 -07:00
Alexander Belyaev
64f659bee6 [mlir] Rewrite canonicalization of collapse(expand) and expand(collapse).
Differential Revision: https://reviews.llvm.org/D122666
2022-04-05 10:03:07 +02:00
Matthias Springer
566975a252 [mlir][memref][NFC] Remove unused function
This fixes a compiler warning.
2022-03-31 17:16:03 +09:00