[Mlir-commits] [mlir] [mlir][transform] Implement `FlattenElementwiseLinalgOp` transform op (PR #81431)
llvmlistbot at llvm.org
llvmlistbot at llvm.org
Tue Feb 13 21:19:57 PST 2024
https://github.com/srcarroll updated https://github.com/llvm/llvm-project/pull/81431
>From 6e05d6a3ed218797ae264fc88f8998a0a4b945dc Mon Sep 17 00:00:00 2001
From: Sam <srcarroll314 at gmail.com>
Date: Sun, 11 Feb 2024 02:33:16 -0600
Subject: [PATCH 1/4] Implement FlattenElementwiseLinalgOp transform
---
.../Linalg/TransformOps/LinalgTransformOps.td | 42 +++++++++
.../TransformOps/LinalgTransformOps.cpp | 87 +++++++++++++++++++
2 files changed, 129 insertions(+)
diff --git a/mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td b/mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td
index 309573a562872f..d8d864d14ea698 100644
--- a/mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td
+++ b/mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td
@@ -2295,6 +2295,48 @@ def ConvertConv2DToImg2ColOp : Op<Transform_Dialect,
}];
}
+//===----------------------------------------------------------------------===//
+// FlattenElementwiseLinalgOp
+//===----------------------------------------------------------------------===//
+
+def FlattenElementwiseLinalgOp : Op<Transform_Dialect,
+ "structured.flatten_elementwise",
+ [FunctionalStyleTransformOpTrait,
+ MemoryEffectsOpInterface,
+ TransformOpInterface,
+ TransformEachOpTrait,
+ ReportTrackingListenerFailuresOpTrait]> {
+ let description = [{
+ Flattens elementwise linalg ops.
+
+ Returns one handle:
+ - Flattened linalg operation.
+
+ #### Return modes:
+
+ Returns a definite failure if target is not isolated from above.
+ Returns a silenceable failure if the pattern application failed.
+ }];
+
+ let arguments = (ins TransformHandleTypeInterface:$target);
+ let results = (outs TransformHandleTypeInterface:$transformed);
+
+ let assemblyFormat =
+ "$target attr-dict `:` functional-type($target, results)";
+
+ let builders = [
+ OpBuilder<(ins "Value":$target)>
+ ];
+
+ let extraClassDeclaration = [{
+ ::mlir::DiagnosedSilenceableFailure applyToOne(
+ ::mlir::transform::TransformRewriter &rewriter,
+ ::mlir::linalg::LinalgOp target,
+ ::mlir::transform::ApplyToEachResultList &results,
+ ::mlir::transform::TransformState &state);
+ }];
+}
+
//===----------------------------------------------------------------------===//
// Transpose Conv2D
//===----------------------------------------------------------------------===//
diff --git a/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp b/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
index 585fd14b40d764..57fce5e7a749f0 100644
--- a/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
+++ b/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
@@ -3243,6 +3243,93 @@ DiagnosedSilenceableFailure transform::ConvertConv2DToImg2ColOp::applyToOne(
return DiagnosedSilenceableFailure::success();
}
+//===----------------------------------------------------------------------===//
+// FlattenElementwiseLinalgOp.
+//===----------------------------------------------------------------------===//
+
+DiagnosedSilenceableFailure transform::FlattenElementwiseLinalgOp::applyToOne(
+ transform::TransformRewriter &rewriter, linalg::LinalgOp target,
+ transform::ApplyToEachResultList &results,
+ transform::TransformState &state) {
+ rewriter.setInsertionPoint(target);
+ auto flatten = [&](linalg::LinalgOp op) -> FailureOr<linalg::GenericOp> {
+ if (!isElementwise(target)) {
+ return rewriter.notifyMatchFailure(
+ target, "only elementwise flattening is supported");
+ }
+ if (!llvm::all_of(target.getIndexingMapsArray(),
+ [](auto map) { return map.isMinorIdentity(); })) {
+ return rewriter.notifyMatchFailure(
+ target, "only minor identity indexing maps is supported");
+ }
+ ShapedType nonEmptyShapeType = nullptr;
+ for (const auto &resultVal : target.getDpsInitsMutable()) {
+ auto resultType = resultVal.get().getType();
+ if (ShapedType resultShapedType = dyn_cast<ShapedType>(resultType)) {
+ if (resultShapedType.getShape().empty())
+ continue;
+ if (nonEmptyShapeType == nullptr) {
+ nonEmptyShapeType = resultShapedType;
+ } else if (resultShapedType != nonEmptyShapeType) {
+ return rewriter.notifyMatchFailure(
+ target, "all operands (except rank 0) must have same types");
+ }
+ }
+ }
+ if (target.hasPureBufferSemantics()) {
+ if (!llvm::all_of(target->getOperands(), [](Value operand) {
+ if (auto memRefTy = dyn_cast<MemRefType>(operand.getType()))
+ return memRefTy.getLayout().isIdentity();
+ return true;
+ })) {
+ return rewriter.notifyMatchFailure(
+ target, "only memrefs with identity layout is supported");
+ }
+ }
+ ReassociationIndices reassociation(nonEmptyShapeType.getRank());
+ std::iota(reassociation.begin(), reassociation.end(), 0);
+ auto flattenOperand = [&](const Value &operand) {
+ return (!isa<MemRefType>(operand.getType()))
+ ? operand
+ : rewriter
+ .create<memref::CollapseShapeOp>(target.getLoc(),
+ operand, reassociation)
+ .getResult();
+ };
+ SmallVector<Value, 2> flattenedInputs(
+ llvm::map_range(target.getDpsInputs(), [&](const Value &operand) {
+ return flattenOperand(operand);
+ }));
+ SmallVector<Value, 2> flattenedInits(
+ llvm::map_range(target.getDpsInits(), [&](const Value &operand) {
+ return flattenOperand(operand);
+ }));
+
+ SmallVector<AffineMap, 4> flattenedMaps(llvm::map_range(
+ llvm::concat<Value>(flattenedInputs, flattenedInits),
+ [&](const Value &val) {
+ if (auto memRefTy = dyn_cast<MemRefType>(val.getType()))
+ return AffineMap::getMinorIdentityMap(1, memRefTy.getRank(),
+ target.getContext());
+ return AffineMap::getMinorIdentityMap(1, 0, target.getContext());
+ }));
+
+ auto flattenedLinalgOp = rewriter.create<linalg::GenericOp>(
+ target.getLoc(), TypeRange(), flattenedInputs, flattenedInits,
+ flattenedMaps,
+ SmallVector<utils::IteratorType>{utils::IteratorType::parallel});
+ flattenedLinalgOp.getRegion().takeBody(target->getRegion(0));
+ return flattenedLinalgOp;
+ return success();
+ };
+ auto maybeFlattened = flatten(target);
+ if (failed(maybeFlattened))
+ return emitDefaultSilenceableFailure(target);
+ results.push_back(*maybeFlattened);
+ rewriter.eraseOp(target);
+ return DiagnosedSilenceableFailure::success();
+}
+
//===----------------------------------------------------------------------===//
// TransposeConv2DOp
//===----------------------------------------------------------------------===//
>From aff79baad62b53f8f10f733d5ff3c0068556549d Mon Sep 17 00:00:00 2001
From: Sam <srcarroll314 at gmail.com>
Date: Sun, 11 Feb 2024 14:57:07 -0600
Subject: [PATCH 2/4] Add a couple regression tests
---
.../TransformOps/LinalgTransformOps.cpp | 50 +++++++-----
.../Dialect/Linalg/flatten-elementwise.mlir | 77 +++++++++++++++++++
2 files changed, 106 insertions(+), 21 deletions(-)
create mode 100644 mlir/test/Dialect/Linalg/flatten-elementwise.mlir
diff --git a/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp b/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
index 57fce5e7a749f0..15f7f82e24f3a5 100644
--- a/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
+++ b/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
@@ -3252,19 +3252,22 @@ DiagnosedSilenceableFailure transform::FlattenElementwiseLinalgOp::applyToOne(
transform::ApplyToEachResultList &results,
transform::TransformState &state) {
rewriter.setInsertionPoint(target);
- auto flatten = [&](linalg::LinalgOp op) -> FailureOr<linalg::GenericOp> {
+ if (target.getNumLoops() <= 1)
+ return DiagnosedSilenceableFailure::success();
+ auto flatten = [&](linalg::LinalgOp &op) -> FailureOr<linalg::LinalgOp> {
if (!isElementwise(target)) {
return rewriter.notifyMatchFailure(
target, "only elementwise flattening is supported");
}
+ // TODO: Support broadcasting and permutations
if (!llvm::all_of(target.getIndexingMapsArray(),
[](auto map) { return map.isMinorIdentity(); })) {
return rewriter.notifyMatchFailure(
target, "only minor identity indexing maps is supported");
}
ShapedType nonEmptyShapeType = nullptr;
- for (const auto &resultVal : target.getDpsInitsMutable()) {
- auto resultType = resultVal.get().getType();
+ for (const auto &resultVal : target->getOperands()) {
+ auto resultType = resultVal.getType();
if (ShapedType resultShapedType = dyn_cast<ShapedType>(resultType)) {
if (resultShapedType.getShape().empty())
continue;
@@ -3277,6 +3280,7 @@ DiagnosedSilenceableFailure transform::FlattenElementwiseLinalgOp::applyToOne(
}
}
if (target.hasPureBufferSemantics()) {
+ // TODO: Relax restrictions on layout
if (!llvm::all_of(target->getOperands(), [](Value operand) {
if (auto memRefTy = dyn_cast<MemRefType>(operand.getType()))
return memRefTy.getLayout().isIdentity();
@@ -3285,8 +3289,11 @@ DiagnosedSilenceableFailure transform::FlattenElementwiseLinalgOp::applyToOne(
return rewriter.notifyMatchFailure(
target, "only memrefs with identity layout is supported");
}
+ } else {
+ // TODO: Support tensors
+ return rewriter.notifyMatchFailure(target, "tensors are not supported");
}
- ReassociationIndices reassociation(nonEmptyShapeType.getRank());
+ ReassociationIndices reassociation(target.getNumLoops());
std::iota(reassociation.begin(), reassociation.end(), 0);
auto flattenOperand = [&](const Value &operand) {
return (!isa<MemRefType>(operand.getType()))
@@ -3296,37 +3303,38 @@ DiagnosedSilenceableFailure transform::FlattenElementwiseLinalgOp::applyToOne(
operand, reassociation)
.getResult();
};
- SmallVector<Value, 2> flattenedInputs(
- llvm::map_range(target.getDpsInputs(), [&](const Value &operand) {
- return flattenOperand(operand);
- }));
- SmallVector<Value, 2> flattenedInits(
- llvm::map_range(target.getDpsInits(), [&](const Value &operand) {
+ SmallVector<Value, 2> flattenedOperands(
+ llvm::map_range(target->getOperands(), [&](const Value &operand) {
return flattenOperand(operand);
}));
- SmallVector<AffineMap, 4> flattenedMaps(llvm::map_range(
- llvm::concat<Value>(flattenedInputs, flattenedInits),
- [&](const Value &val) {
+ SmallVector<AffineMap, 4> flattenedMaps(
+ llvm::map_range(flattenedOperands, [&](const Value &val) {
if (auto memRefTy = dyn_cast<MemRefType>(val.getType()))
return AffineMap::getMinorIdentityMap(1, memRefTy.getRank(),
target.getContext());
return AffineMap::getMinorIdentityMap(1, 0, target.getContext());
}));
- auto flattenedLinalgOp = rewriter.create<linalg::GenericOp>(
- target.getLoc(), TypeRange(), flattenedInputs, flattenedInits,
- flattenedMaps,
- SmallVector<utils::IteratorType>{utils::IteratorType::parallel});
- flattenedLinalgOp.getRegion().takeBody(target->getRegion(0));
- return flattenedLinalgOp;
- return success();
+ rewriter.modifyOpInPlace(op, [&]() {
+ op->setOperands(flattenedOperands);
+ // TODO: Find a more general way to determine if op requires explicit
+ // indexing_maps and iterator_types
+ if (isa<linalg::GenericOp>(op)) {
+ op->setAttr("indexing_maps",
+ rewriter.getAffineMapArrayAttr(flattenedMaps));
+ op->setAttr(
+ "iterator_types",
+ rewriter.getArrayAttr({IteratorTypeAttr::get(
+ rewriter.getContext(), utils::IteratorType::parallel)}));
+ }
+ });
+ return op;
};
auto maybeFlattened = flatten(target);
if (failed(maybeFlattened))
return emitDefaultSilenceableFailure(target);
results.push_back(*maybeFlattened);
- rewriter.eraseOp(target);
return DiagnosedSilenceableFailure::success();
}
diff --git a/mlir/test/Dialect/Linalg/flatten-elementwise.mlir b/mlir/test/Dialect/Linalg/flatten-elementwise.mlir
new file mode 100644
index 00000000000000..e360fc3ff51784
--- /dev/null
+++ b/mlir/test/Dialect/Linalg/flatten-elementwise.mlir
@@ -0,0 +1,77 @@
+// RUN: mlir-opt %s -transform-interpreter -split-input-file | FileCheck %s
+
+// CHECK-LABEL: func.func @fill(
+// CHECK-SAME: %[[ARG0:.*]]: f32,
+// CHECK-SAME: %[[ARG1:.*]]: memref<32x7xf32>
+// CHECK-NEXT: %[[FLATTENED:.*]] = memref.collapse_shape %[[ARG1]] {{\[}}[0, 1]]
+// CHECK-NEXT: linalg.fill ins(%[[ARG0]] : f32) outs(%[[FLATTENED]] : memref<224xf32>)
+func.func @fill(%cst: f32, %arg: memref<32x7xf32>) {
+ linalg.fill ins(%cst: f32) outs(%arg: memref<32x7xf32>)
+ return
+}
+
+module attributes {transform.with_named_sequence} {
+ transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
+ %0 = transform.structured.match interface{LinalgOp} in %arg1 : (!transform.any_op) -> !transform.any_op
+ %flattened = transform.structured.flatten_elementwise %0
+ : (!transform.any_op) -> !transform.any_op
+ transform.yield
+ }
+}
+
+// -----
+
+// CHECK-LABEL: func.func @map(
+// CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]*]]: memref<32x7xf32>
+// CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]*]]: memref<32x7xf32>
+// CHECK-SAME: %[[ARG2:[a-zA-Z0-9_]*]]: memref<32x7xf32>
+// CHECK-NEXT: %[[FLATTENED_0:.*]] = memref.collapse_shape %[[ARG0]] {{\[}}[0, 1]]
+// CHECK-NEXT: %[[FLATTENED_1:.*]] = memref.collapse_shape %[[ARG1]] {{\[}}[0, 1]]
+// CHECK-NEXT: %[[FLATTENED_2:.*]] = memref.collapse_shape %[[ARG2]] {{\[}}[0, 1]]
+// CHECK-NEXT: linalg.map { arith.addf } ins(%[[FLATTENED_0]], %[[FLATTENED_1]] : memref<224xf32>, memref<224xf32>) outs(%[[FLATTENED_2]] : memref<224xf32>)
+func.func @map(%arg0: memref<32x7xf32>, %arg1: memref<32x7xf32>, %arg2: memref<32x7xf32>) {
+ linalg.map {arith.addf} ins(%arg0, %arg1: memref<32x7xf32>, memref<32x7xf32>) outs(%arg2: memref<32x7xf32>)
+ return
+}
+
+module attributes {transform.with_named_sequence} {
+ transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
+ %0 = transform.structured.match interface{LinalgOp} in %arg1 : (!transform.any_op) -> !transform.any_op
+ %flattened = transform.structured.flatten_elementwise %0
+ : (!transform.any_op) -> !transform.any_op
+ transform.yield
+ }
+}
+
+// -----
+
+// CHECK: #[[$MAP0:.*]] = affine_map<(d0) -> (d0)>
+// CHECK-LABEL: func.func @generic
+// CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]*]]: memref<32x7xf32>
+// CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]*]]: memref<32x7xf32>
+// CHECK-SAME: %[[ARG2:[a-zA-Z0-9_]*]]: memref<32x7xf32>
+// CHECK-NEXT: %[[FLATTENED_0:.*]] = memref.collapse_shape %[[ARG0]] {{\[}}[0, 1]]
+// CHECK-NEXT: %[[FLATTENED_1:.*]] = memref.collapse_shape %[[ARG1]] {{\[}}[0, 1]]
+// CHECK-NEXT: %[[FLATTENED_2:.*]] = memref.collapse_shape %[[ARG2]] {{\[}}[0, 1]]
+// CHECK-NEXT: linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]], #[[$MAP0]]], iterator_types = ["parallel"]} ins(%[[FLATTENED_0]], %[[FLATTENED_1]] : memref<224xf32>, memref<224xf32>) outs(%[[FLATTENED_2]] : memref<224xf32>)
+// CHECK-NEXT: ^bb0(%[[A:.*]]: f32, %[[B:.*]]: f32, %[[C:.*]]: f32)
+// CHECK-NEXT: %[[SUM:.*]] = arith.addf %[[A]], %[[B]]
+// CHECK-NEXT: linalg.yield %[[SUM]]
+#map = affine_map<(d0, d1) -> (d0, d1)>
+func.func @generic( %arg0: memref<32x7xf32>, %arg1: memref<32x7xf32>, %arg2: memref<32x7xf32>) {
+ linalg.generic {indexing_maps = [#map, #map, #map], iterator_types = ["parallel", "parallel"]} ins(%arg0, %arg1: memref<32x7xf32>, memref<32x7xf32>) outs(%arg2: memref<32x7xf32>) {
+ ^bb0(%a: f32, %b: f32, %c: f32):
+ %0 = arith.addf %a, %b : f32
+ linalg.yield %0 : f32
+ }
+ return
+}
+
+module attributes {transform.with_named_sequence} {
+ transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
+ %0 = transform.structured.match interface{LinalgOp} in %arg1 : (!transform.any_op) -> !transform.any_op
+ %flattened = transform.structured.flatten_elementwise %0
+ : (!transform.any_op) -> !transform.any_op
+ transform.yield
+ }
+}
\ No newline at end of file
>From cd0ebb1051264dbffd4c0fb1a386150a05ff6ef2 Mon Sep 17 00:00:00 2001
From: Sam <srcarroll314 at gmail.com>
Date: Tue, 13 Feb 2024 22:27:00 -0600
Subject: [PATCH 3/4] Refactor `collapseOpIterationDims` to work for all linalg
ops
---
.../Dialect/Linalg/Transforms/Transforms.h | 3 +-
.../Linalg/Transforms/ElementwiseOpFusion.cpp | 60 ++++++++-----------
2 files changed, 27 insertions(+), 36 deletions(-)
diff --git a/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h b/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h
index a848d12fbbb50e..a566745185ad99 100644
--- a/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h
+++ b/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h
@@ -1081,9 +1081,8 @@ bool areDimSequencesPreserved(ArrayRef<AffineMap> maps,
/// When valid, the method also collapses the operands of the op. Returns
/// replacement values of the results of the original `linalgOp` by inserting
/// reshapes to get back values of compatible types.
-template <typename LinalgType>
FailureOr<SmallVector<Value>>
-collapseOpIterationDims(LinalgType op,
+collapseOpIterationDims(LinalgOp op,
ArrayRef<ReassociationIndices> foldedIterationDims,
RewriterBase &rewriter);
diff --git a/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp b/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp
index 286b07669a47f5..ce58caa6c39aad 100644
--- a/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp
@@ -1449,12 +1449,8 @@ void generateCollapsedIndexingRegion(Location loc, Block *block,
}
}
-template <typename LinalgType>
-Operation *createCollapsedOp(LinalgType op,
- const CollapsingInfo &collapsingInfo,
- RewriterBase &rewriter) {
- static_assert(llvm::is_one_of<LinalgType, GenericOp, CopyOp>::value,
- "unsupported linalg op type to create");
+LinalgOp createCollapsedOp(LinalgOp op, const CollapsingInfo &collapsingInfo,
+ RewriterBase &rewriter) {
Location loc = op->getLoc();
// Get the input operands.
@@ -1479,14 +1475,17 @@ Operation *createCollapsedOp(LinalgType op,
resultTypes.push_back(newOutput.getType());
}
- if (isa<linalg::CopyOp>(op)) {
- return rewriter.create<linalg::CopyOp>(loc, inputOperands[0],
- outputOperands[0]);
- }
+ Operation *collapsedOp = clone(
+ rewriter, op, resultTypes,
+ llvm::to_vector(llvm::concat<Value>(inputOperands, outputOperands)));
// Get the iterator types for the operand.
- SmallVector<utils::IteratorType> iteratorTypes =
- getCollapsedOpIteratorTypes(op.getIteratorTypesArray(), collapsingInfo);
+ SmallVector<Attribute> iteratorTypes = llvm::map_to_vector(
+ getCollapsedOpIteratorTypes(op.getIteratorTypesArray(), collapsingInfo),
+ [&](utils::IteratorType itTy) {
+ return cast<Attribute>(
+ IteratorTypeAttr::get(rewriter.getContext(), itTy));
+ });
// Get the indexing maps.
auto indexingMaps =
@@ -1494,25 +1493,22 @@ Operation *createCollapsedOp(LinalgType op,
return getCollapsedOpIndexingMap(map, collapsingInfo);
});
- Operation *collapsedOp = rewriter.create<linalg::GenericOp>(
- loc, resultTypes, inputOperands, outputOperands, indexingMaps,
- iteratorTypes, [](OpBuilder &builder, Location loc, ValueRange args) {});
- Block *origOpBlock = &op->getRegion(0).front();
- Block *collapsedOpBlock = &collapsedOp->getRegion(0).front();
- rewriter.mergeBlocks(origOpBlock, collapsedOpBlock,
- collapsedOpBlock->getArguments());
+ // TODO: Find a more general way to determine if op requires explicit
+ // indexing_maps and iterator_types
+ if (isa<linalg::GenericOp>(op)) {
+ collapsedOp->setAttr("indexing_maps",
+ rewriter.getAffineMapArrayAttr(indexingMaps));
+ collapsedOp->setAttr("iterator_types",
+ rewriter.getArrayAttr(iteratorTypes));
+ }
- return collapsedOp;
+ return cast<LinalgOp>(collapsedOp);
}
/// Implementation of fusion with reshape operation by collapsing dimensions.
-template <typename LinalgType>
FailureOr<SmallVector<Value>> mlir::linalg::collapseOpIterationDims(
- LinalgType op, ArrayRef<ReassociationIndices> foldedIterationDims,
+ LinalgOp op, ArrayRef<ReassociationIndices> foldedIterationDims,
RewriterBase &rewriter) {
- static_assert(llvm::is_one_of<LinalgType, GenericOp, CopyOp>::value,
- "unsupported linalg op type to collapse");
-
// Bail on trivial no-op cases.
if (op.getNumLoops() <= 1 || foldedIterationDims.empty() ||
llvm::all_of(foldedIterationDims, [](ReassociationIndicesRef foldedDims) {
@@ -1541,8 +1537,7 @@ FailureOr<SmallVector<Value>> mlir::linalg::collapseOpIterationDims(
}
// Bail on non-canonical ranges.
- SmallVector<Range> loopRanges =
- cast<LinalgOp>(op.getOperation()).createLoopRanges(rewriter, op.getLoc());
+ SmallVector<Range> loopRanges = op.createLoopRanges(rewriter, op.getLoc());
auto opFoldIsConstantValue = [](OpFoldResult ofr, int64_t value) {
if (auto attr = llvm::dyn_cast_if_present<Attribute>(ofr))
return cast<IntegerAttr>(attr).getInt() == value;
@@ -1558,8 +1553,7 @@ FailureOr<SmallVector<Value>> mlir::linalg::collapseOpIterationDims(
op, "expected all loop ranges to have zero start and unit stride");
}
- LinalgType collapsedOp = cast<LinalgType>(
- createCollapsedOp<LinalgType>(op, collapsingInfo, rewriter));
+ LinalgOp collapsedOp = createCollapsedOp(op, collapsingInfo, rewriter);
Location loc = op->getLoc();
if (collapsedOp.hasIndexSemantics()) {
@@ -1632,9 +1626,8 @@ class FoldWithProducerReshapeOpByCollapsing
continue;
}
- std::optional<SmallVector<Value>> replacements =
- collapseOpIterationDims<linalg::GenericOp>(
- genericOp, collapsableIterationDims, rewriter);
+ std::optional<SmallVector<Value>> replacements = collapseOpIterationDims(
+ genericOp, collapsableIterationDims, rewriter);
if (!replacements) {
return rewriter.notifyMatchFailure(
genericOp, "failed to do the fusion by collapsing transformation");
@@ -1675,8 +1668,7 @@ class CollapseLinalgDimensions : public OpRewritePattern<LinalgType> {
}
std::optional<SmallVector<Value>> replacements =
- collapseOpIterationDims<LinalgType>(op, collapsableIterationDims,
- rewriter);
+ collapseOpIterationDims(op, collapsableIterationDims, rewriter);
if (!replacements) {
return rewriter.notifyMatchFailure(op, "failed to collapse dimensions");
}
>From 9d0b35a3a4d84179ab88357e9208ea9ab4b149ea Mon Sep 17 00:00:00 2001
From: Sam <srcarroll314 at gmail.com>
Date: Tue, 13 Feb 2024 23:19:12 -0600
Subject: [PATCH 4/4] Refactor `FlattenElementwiseLinalgOp` to use
`collapseOpIterationDims`
---
.../Dialect/Linalg/Transforms/Transforms.h | 7 +++-
.../TransformOps/LinalgTransformOps.cpp | 40 ++-----------------
.../Linalg/Transforms/ElementwiseOpFusion.cpp | 16 ++++----
3 files changed, 17 insertions(+), 46 deletions(-)
diff --git a/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h b/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h
index a566745185ad99..65cf19e7a4fcd6 100644
--- a/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h
+++ b/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h
@@ -1074,6 +1074,11 @@ bool isDimSequencePreserved(AffineMap map, ReassociationIndicesRef dimSequence);
bool areDimSequencesPreserved(ArrayRef<AffineMap> maps,
ArrayRef<ReassociationIndices> dimSequences);
+struct CollapseResult {
+ SmallVector<Value> results;
+ LinalgOp collapsedOp;
+};
+
/// Collapses dimensions of linalg.generic/linalg.copy operation. A precondition
/// to calling this method is that for each list in `foldedIterationDim`, the
/// sequence of dimensions is contiguous in domains of all `indexing_maps` of
@@ -1081,7 +1086,7 @@ bool areDimSequencesPreserved(ArrayRef<AffineMap> maps,
/// When valid, the method also collapses the operands of the op. Returns
/// replacement values of the results of the original `linalgOp` by inserting
/// reshapes to get back values of compatible types.
-FailureOr<SmallVector<Value>>
+FailureOr<CollapseResult>
collapseOpIterationDims(LinalgOp op,
ArrayRef<ReassociationIndices> foldedIterationDims,
RewriterBase &rewriter);
diff --git a/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp b/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
index 15f7f82e24f3a5..25e72ab273833e 100644
--- a/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
+++ b/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
@@ -3254,7 +3254,7 @@ DiagnosedSilenceableFailure transform::FlattenElementwiseLinalgOp::applyToOne(
rewriter.setInsertionPoint(target);
if (target.getNumLoops() <= 1)
return DiagnosedSilenceableFailure::success();
- auto flatten = [&](linalg::LinalgOp &op) -> FailureOr<linalg::LinalgOp> {
+ auto flatten = [&](linalg::LinalgOp &op) -> FailureOr<CollapseResult> {
if (!isElementwise(target)) {
return rewriter.notifyMatchFailure(
target, "only elementwise flattening is supported");
@@ -3295,46 +3295,12 @@ DiagnosedSilenceableFailure transform::FlattenElementwiseLinalgOp::applyToOne(
}
ReassociationIndices reassociation(target.getNumLoops());
std::iota(reassociation.begin(), reassociation.end(), 0);
- auto flattenOperand = [&](const Value &operand) {
- return (!isa<MemRefType>(operand.getType()))
- ? operand
- : rewriter
- .create<memref::CollapseShapeOp>(target.getLoc(),
- operand, reassociation)
- .getResult();
- };
- SmallVector<Value, 2> flattenedOperands(
- llvm::map_range(target->getOperands(), [&](const Value &operand) {
- return flattenOperand(operand);
- }));
-
- SmallVector<AffineMap, 4> flattenedMaps(
- llvm::map_range(flattenedOperands, [&](const Value &val) {
- if (auto memRefTy = dyn_cast<MemRefType>(val.getType()))
- return AffineMap::getMinorIdentityMap(1, memRefTy.getRank(),
- target.getContext());
- return AffineMap::getMinorIdentityMap(1, 0, target.getContext());
- }));
-
- rewriter.modifyOpInPlace(op, [&]() {
- op->setOperands(flattenedOperands);
- // TODO: Find a more general way to determine if op requires explicit
- // indexing_maps and iterator_types
- if (isa<linalg::GenericOp>(op)) {
- op->setAttr("indexing_maps",
- rewriter.getAffineMapArrayAttr(flattenedMaps));
- op->setAttr(
- "iterator_types",
- rewriter.getArrayAttr({IteratorTypeAttr::get(
- rewriter.getContext(), utils::IteratorType::parallel)}));
- }
- });
- return op;
+ return collapseOpIterationDims(op, reassociation, rewriter);
};
auto maybeFlattened = flatten(target);
if (failed(maybeFlattened))
return emitDefaultSilenceableFailure(target);
- results.push_back(*maybeFlattened);
+ results.push_back((*maybeFlattened).collapsedOp);
return DiagnosedSilenceableFailure::success();
}
diff --git a/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp b/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp
index ce58caa6c39aad..b81b67474565ee 100644
--- a/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp
@@ -1506,7 +1506,7 @@ LinalgOp createCollapsedOp(LinalgOp op, const CollapsingInfo &collapsingInfo,
}
/// Implementation of fusion with reshape operation by collapsing dimensions.
-FailureOr<SmallVector<Value>> mlir::linalg::collapseOpIterationDims(
+FailureOr<CollapseResult> mlir::linalg::collapseOpIterationDims(
LinalgOp op, ArrayRef<ReassociationIndices> foldedIterationDims,
RewriterBase &rewriter) {
// Bail on trivial no-op cases.
@@ -1594,7 +1594,7 @@ FailureOr<SmallVector<Value>> mlir::linalg::collapseOpIterationDims(
results.push_back(collapsedOpResult);
}
}
- return results;
+ return CollapseResult{.results = results, .collapsedOp = collapsedOp};
}
namespace {
@@ -1626,14 +1626,14 @@ class FoldWithProducerReshapeOpByCollapsing
continue;
}
- std::optional<SmallVector<Value>> replacements = collapseOpIterationDims(
+ std::optional<CollapseResult> collapseResult = collapseOpIterationDims(
genericOp, collapsableIterationDims, rewriter);
- if (!replacements) {
+ if (!collapseResult) {
return rewriter.notifyMatchFailure(
genericOp, "failed to do the fusion by collapsing transformation");
}
- rewriter.replaceOp(genericOp, *replacements);
+ rewriter.replaceOp(genericOp, (*collapseResult).results);
return success();
}
return failure();
@@ -1667,12 +1667,12 @@ class CollapseLinalgDimensions : public OpRewritePattern<LinalgType> {
op, "specified dimensions cannot be collapsed");
}
- std::optional<SmallVector<Value>> replacements =
+ std::optional<CollapseResult> collapseResult =
collapseOpIterationDims(op, collapsableIterationDims, rewriter);
- if (!replacements) {
+ if (!collapseResult) {
return rewriter.notifyMatchFailure(op, "failed to collapse dimensions");
}
- rewriter.replaceOp(op, *replacements);
+ rewriter.replaceOp(op, (*collapseResult).results);
return success();
}
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