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authorCullen Rhodes <cullen.rhodes@arm.com>2023-11-20 08:39:34 +0000
committerGitHub <noreply@github.com>2023-11-20 08:39:34 +0000
commitbf897d5d77e974486e37d33e83f50f5ea95390fa (patch)
tree8e43b48b535d289c03c6242789c329ed3be3b473 /mlir/lib/Dialect/Vector/Transforms/VectorTransferOpTransforms.cpp
parentcdf6693f072b97ec42a95f569115ad7f0afd37d5 (diff)
[mlir][vector] Extend TransferReadDropUnitDimsPattern to support partially-static memrefs (#72142)
This patch extends TransferReadDropUnitDimsPattern to support dropping unit dims from partially-static memrefs, for example: %v = vector.transfer_read %base[%c0, %c0], %pad {in_bounds = [true, true]} : memref<?x1xi8, strided<[?, ?], offset: ?>>, vector<[16]x1xi8> Is rewritten as: %dim0 = memref.dim %base, %c0 : memref<?x1xi8, strided<[?, ?], offset: ?>> %subview = memref.subview %base[0, 0] [%dim0, 1] [1, 1] : memref<?x1xi8, strided<[?, ?], offset: ?>> to memref<?xi8, #map1> %v = vector.transfer_read %subview[%c0], %pad {in_bounds = [true]} : memref<?xi8, #map1>, vector<[16]xi8> Scalable vectors are now also supported, the scalable dims were being dropped when creating the rank-reduced vector type. The xfer op can also have a mask of type 'vector.create_mask', which gets rewritten as long as the mask of the unit dim is a constant of 1.
Diffstat (limited to 'mlir/lib/Dialect/Vector/Transforms/VectorTransferOpTransforms.cpp')
-rw-r--r--mlir/lib/Dialect/Vector/Transforms/VectorTransferOpTransforms.cpp127
1 files changed, 99 insertions, 28 deletions
diff --git a/mlir/lib/Dialect/Vector/Transforms/VectorTransferOpTransforms.cpp b/mlir/lib/Dialect/Vector/Transforms/VectorTransferOpTransforms.cpp
index a5f1b28152b9..d2c6ba557b9b 100644
--- a/mlir/lib/Dialect/Vector/Transforms/VectorTransferOpTransforms.cpp
+++ b/mlir/lib/Dialect/Vector/Transforms/VectorTransferOpTransforms.cpp
@@ -260,12 +260,37 @@ void TransferOptimization::storeToLoadForwarding(vector::TransferReadOp read) {
opToErase.push_back(read.getOperation());
}
+/// Returns a copy of `shape` without unit dims.
+static SmallVector<int64_t> getReducedShape(ArrayRef<int64_t> shape) {
+ SmallVector<int64_t> reducedShape;
+ llvm::copy_if(shape, std::back_inserter(reducedShape),
+ [](int64_t dimSize) { return dimSize != 1; });
+ return reducedShape;
+}
+
+/// Converts OpFoldResults to int64_t shape without unit dims.
+static SmallVector<int64_t> getReducedShape(ArrayRef<OpFoldResult> mixedSizes) {
+ SmallVector<int64_t> reducedShape;
+ for (const auto size : mixedSizes) {
+ if (llvm::dyn_cast_if_present<Value>(size)) {
+ reducedShape.push_back(ShapedType::kDynamic);
+ continue;
+ }
+
+ auto value = cast<IntegerAttr>(size.get<Attribute>()).getValue();
+ if (value == 1)
+ continue;
+ reducedShape.push_back(value.getSExtValue());
+ }
+ return reducedShape;
+}
+
/// Drops unit dimensions from the input MemRefType.
-static MemRefType dropUnitDims(MemRefType inputType, ArrayRef<int64_t> offsets,
- ArrayRef<int64_t> sizes,
- ArrayRef<int64_t> strides) {
- SmallVector<int64_t> targetShape = llvm::to_vector(
- llvm::make_filter_range(sizes, [](int64_t sz) { return sz != 1; }));
+static MemRefType dropUnitDims(MemRefType inputType,
+ ArrayRef<OpFoldResult> offsets,
+ ArrayRef<OpFoldResult> sizes,
+ ArrayRef<OpFoldResult> strides) {
+ auto targetShape = getReducedShape(sizes);
Type rankReducedType = memref::SubViewOp::inferRankReducedResultType(
targetShape, inputType, offsets, sizes, strides);
return canonicalizeStridedLayout(cast<MemRefType>(rankReducedType));
@@ -277,17 +302,18 @@ static Value rankReducingSubviewDroppingUnitDims(PatternRewriter &rewriter,
mlir::Location loc,
Value input) {
MemRefType inputType = cast<MemRefType>(input.getType());
- assert(inputType.hasStaticShape());
- SmallVector<int64_t> subViewOffsets(inputType.getRank(), 0);
- SmallVector<int64_t> subViewStrides(inputType.getRank(), 1);
- ArrayRef<int64_t> subViewSizes = inputType.getShape();
- MemRefType resultType =
- dropUnitDims(inputType, subViewOffsets, subViewSizes, subViewStrides);
+ SmallVector<OpFoldResult> offsets(inputType.getRank(),
+ rewriter.getIndexAttr(0));
+ SmallVector<OpFoldResult> sizes = memref::getMixedSizes(rewriter, loc, input);
+ SmallVector<OpFoldResult> strides(inputType.getRank(),
+ rewriter.getIndexAttr(1));
+ MemRefType resultType = dropUnitDims(inputType, offsets, sizes, strides);
+
if (canonicalizeStridedLayout(resultType) ==
canonicalizeStridedLayout(inputType))
return input;
- return rewriter.create<memref::SubViewOp>(
- loc, resultType, input, subViewOffsets, subViewSizes, subViewStrides);
+ return rewriter.create<memref::SubViewOp>(loc, resultType, input, offsets,
+ sizes, strides);
}
/// Returns the number of dims that aren't unit dims.
@@ -295,12 +321,44 @@ static int getReducedRank(ArrayRef<int64_t> shape) {
return llvm::count_if(shape, [](int64_t dimSize) { return dimSize != 1; });
}
-/// Returns a copy of `shape` without unit dims.
-static SmallVector<int64_t> getReducedShape(ArrayRef<int64_t> shape) {
- SmallVector<int64_t> reducedShape;
- llvm::copy_if(shape, std::back_inserter(reducedShape),
- [](int64_t dimSize) { return dimSize != 1; });
- return reducedShape;
+/// Trims non-scalable one dimensions from `oldType` and returns the result
+/// type.
+static VectorType trimNonScalableUnitDims(VectorType oldType) {
+ SmallVector<int64_t> newShape;
+ SmallVector<bool> newScalableDims;
+ for (auto [dimIdx, dimSize] : llvm::enumerate(oldType.getShape())) {
+ if (dimSize == 1 && !oldType.getScalableDims()[dimIdx])
+ continue;
+ newShape.push_back(dimSize);
+ newScalableDims.push_back(oldType.getScalableDims()[dimIdx]);
+ }
+ return VectorType::get(newShape, oldType.getElementType(), newScalableDims);
+}
+
+// Rewrites vector.create_mask 'op' to drop non-scalable one dimensions.
+static FailureOr<Value>
+createMaskDropNonScalableUnitDims(PatternRewriter &rewriter, Location loc,
+ vector::CreateMaskOp op) {
+ auto type = op.getType();
+ auto reducedType = trimNonScalableUnitDims(type);
+ if (reducedType.getRank() == type.getRank())
+ return failure();
+
+ SmallVector<Value> reducedOperands;
+ for (auto [dim, dimIsScalable, operand] : llvm::zip_equal(
+ type.getShape(), type.getScalableDims(), op.getOperands())) {
+ if (dim == 1 && !dimIsScalable) {
+ // If the mask for the unit dim is not a constant of 1, do nothing.
+ auto constant = operand.getDefiningOp<arith::ConstantIndexOp>();
+ if (!constant || (constant.value() != 1))
+ return failure();
+ continue;
+ }
+ reducedOperands.push_back(operand);
+ }
+ return rewriter
+ .create<vector::CreateMaskOp>(loc, reducedType, reducedOperands)
+ .getResult();
}
namespace {
@@ -320,9 +378,7 @@ class TransferReadDropUnitDimsPattern
Value source = transferReadOp.getSource();
MemRefType sourceType = dyn_cast<MemRefType>(source.getType());
// TODO: support tensor types.
- if (!sourceType || !sourceType.hasStaticShape())
- return failure();
- if (sourceType.getNumElements() != vectorType.getNumElements())
+ if (!sourceType)
return failure();
// TODO: generalize this pattern, relax the requirements here.
if (transferReadOp.hasOutOfBoundsDim())
@@ -335,23 +391,38 @@ class TransferReadDropUnitDimsPattern
return failure();
// Check if the reduced vector shape matches the reduced source shape.
// Otherwise, this case is not supported yet.
- int vectorReducedRank = getReducedRank(vectorType.getShape());
- if (reducedRank != vectorReducedRank)
+ auto reducedVectorType = trimNonScalableUnitDims(vectorType);
+ if (reducedRank != reducedVectorType.getRank())
return failure();
if (llvm::any_of(transferReadOp.getIndices(), [](Value v) {
return getConstantIntValue(v) != static_cast<int64_t>(0);
}))
return failure();
+
+ Value maskOp = transferReadOp.getMask();
+ if (maskOp) {
+ auto createMaskOp = maskOp.getDefiningOp<vector::CreateMaskOp>();
+ if (!createMaskOp)
+ return rewriter.notifyMatchFailure(
+ transferReadOp, "unsupported mask op, only 'vector.create_mask' is "
+ "currently supported");
+ FailureOr<Value> rankReducedCreateMask =
+ createMaskDropNonScalableUnitDims(rewriter, loc, createMaskOp);
+ if (failed(rankReducedCreateMask))
+ return failure();
+ maskOp = *rankReducedCreateMask;
+ }
+
Value reducedShapeSource =
rankReducingSubviewDroppingUnitDims(rewriter, loc, source);
Value c0 = rewriter.create<arith::ConstantIndexOp>(loc, 0);
SmallVector<Value> zeros(reducedRank, c0);
auto identityMap = rewriter.getMultiDimIdentityMap(reducedRank);
- auto reducedVectorType = VectorType::get(
- getReducedShape(vectorType.getShape()), vectorType.getElementType());
-
+ SmallVector<bool> inBounds(reducedVectorType.getRank(), true);
auto newTransferReadOp = rewriter.create<vector::TransferReadOp>(
- loc, reducedVectorType, reducedShapeSource, zeros, identityMap);
+ loc, reducedVectorType, reducedShapeSource, zeros, identityMap,
+ transferReadOp.getPadding(), maskOp,
+ rewriter.getBoolArrayAttr(inBounds));
auto shapeCast = rewriter.createOrFold<vector::ShapeCastOp>(
loc, vectorType, newTransferReadOp);
rewriter.replaceOp(transferReadOp, shapeCast);