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[mlir] Add ContractionOpInterface utility functions for vector matrix multiplication #68945

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Merged
merged 3 commits into from
Oct 18, 2023
Merged

[mlir] Add ContractionOpInterface utility functions for vector matrix multiplication #68945

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e431cc4
Add ContractionOpInterface utility functions for vector matrix multip…
NatashaKnk Oct 13, 2023
f2c6334
Fix capitaliztation
NatashaKnk Oct 13, 2023
58cda1d
Fix tests and add type clarity in util function
NatashaKnk Oct 16, 2023
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33 changes: 33 additions & 0 deletions mlir/include/mlir/Dialect/Linalg/IR/LinalgInterfaces.td
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Original file line number Diff line number Diff line change
Expand Up @@ -86,6 +86,39 @@ def LinalgContractionOpInterface : OpInterface<"ContractionOpInterface"> {
/*methodBody=*/[{
return mlir::isRowMajorBatchMatmul($_op.getIndexingMaps());
}]>,
InterfaceMethod<
/*desc=*/[{
Returns whether the given op has indexing maps that correspond to a
vector-matrix multiplication.
}],
/*retTy=*/"bool",
/*methodName=*/"isVecmat",
/*args=*/(ins),
/*methodBody=*/[{
return mlir::isVecmat($_op.getIndexingMaps());
}]>,
InterfaceMethod<
/*desc=*/[{
Returns whether the given op has indexing maps that correspond to a
matrix-vector multiplication.
}],
/*retTy=*/"bool",
/*methodName=*/"isMatvec",
/*args=*/(ins),
/*methodBody=*/[{
return mlir::isMatvec($_op.getIndexingMaps());
}]>,
InterfaceMethod<
/*desc=*/[{
Returns whether the given op has indexing maps that correspond to a
batched matrix-vector multiplication.
}],
/*retTy=*/"bool",
/*methodName=*/"isBatchMatvec",
/*args=*/(ins),
/*methodBody=*/[{
return mlir::isBatchMatvec($_op.getIndexingMaps());
}]>,
];
}

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18 changes: 18 additions & 0 deletions mlir/include/mlir/Dialect/Utils/StructuredOpsUtils.h
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Expand Up @@ -49,6 +49,24 @@ bool isColumnMajorMatmul(ArrayAttr indexingMaps);
/// the reduction.
bool isRowMajorBatchMatmul(ArrayAttr indexingMaps);

/// Tests whether the given maps describe a vector matrix multiplication. The
/// test is permutation-invariant. Note that this only checks the affine maps
/// from an operation, so does not perform any checks on the math being
/// performed within the reduction.
bool isVecmat(ArrayAttr indexingMaps);

/// Tests whether the given maps describe a matrix vector multiplication. The
/// test is permutation-invariant. Note that this only checks the affine maps
/// from an operation, so does not perform any checks on the math being
/// performed within the reduction.
bool isMatvec(ArrayAttr indexingMaps);

/// Tests whether the given maps describe a batch matrix vector multiplication.
/// The test is permutation-invariant. Note that this only checks the affine
/// maps from an operation, so does not perform any checks on the math being
/// performed within the reduction.
bool isBatchMatvec(ArrayAttr indexingMaps);
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nit: rename to VecMatMul/MatVecMul, VectorMatrixMult/MatrixVectorMult or similar?

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My I kept them as vecmat/matvec since that's what the Linalg op is called. I agree that your version is clearer, but I'm not sure if it's better to stay consistent. Wdyt?

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Yep, fair enough. Thanks!


/// Return positions in `iteratorTypes` that match `iteratorTypeName`.
inline void findPositionsOfType(ArrayRef<utils::IteratorType> iteratorTypes,
utils::IteratorType iteratorTypeName,
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91 changes: 82 additions & 9 deletions mlir/lib/Dialect/Utils/StructuredOpsUtils.cpp
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Expand Up @@ -21,9 +21,9 @@ bool mlir::isRowMajorMatmul(ArrayAttr indexingMaps) {
if (indexingMaps.size() != 3)
return false;

auto map0 = cast<AffineMapAttr>(indexingMaps[0]).getValue();
auto map1 = cast<AffineMapAttr>(indexingMaps[1]).getValue();
auto map2 = cast<AffineMapAttr>(indexingMaps[2]).getValue();
AffineMap map0 = cast<AffineMapAttr>(indexingMaps[0]).getValue();
AffineMap map1 = cast<AffineMapAttr>(indexingMaps[1]).getValue();
AffineMap map2 = cast<AffineMapAttr>(indexingMaps[2]).getValue();

if (map0.getNumResults() != 2 || map1.getNumResults() != 2 ||
map2.getNumResults() != 2 || map0.getNumInputs() != 3 ||
Expand All @@ -47,9 +47,9 @@ bool mlir::isColumnMajorMatmul(ArrayAttr indexingMaps) {
if (indexingMaps.size() != 3)
return false;

auto map0 = cast<AffineMapAttr>(indexingMaps[0]).getValue();
auto map1 = cast<AffineMapAttr>(indexingMaps[1]).getValue();
auto map2 = cast<AffineMapAttr>(indexingMaps[2]).getValue();
AffineMap map0 = cast<AffineMapAttr>(indexingMaps[0]).getValue();
AffineMap map1 = cast<AffineMapAttr>(indexingMaps[1]).getValue();
AffineMap map2 = cast<AffineMapAttr>(indexingMaps[2]).getValue();

if (map0.getNumResults() != 2 || map1.getNumResults() != 2 ||
map2.getNumResults() != 2 || map0.getNumInputs() != 3 ||
Expand All @@ -73,9 +73,9 @@ bool mlir::isRowMajorBatchMatmul(ArrayAttr indexingMaps) {
if (indexingMaps.size() != 3)
return false;

auto map0 = cast<AffineMapAttr>(indexingMaps[0]).getValue();
auto map1 = cast<AffineMapAttr>(indexingMaps[1]).getValue();
auto map2 = cast<AffineMapAttr>(indexingMaps[2]).getValue();
AffineMap map0 = cast<AffineMapAttr>(indexingMaps[0]).getValue();
AffineMap map1 = cast<AffineMapAttr>(indexingMaps[1]).getValue();
AffineMap map2 = cast<AffineMapAttr>(indexingMaps[2]).getValue();

if (map0.getNumResults() != 3 || map1.getNumResults() != 3 ||
map2.getNumResults() != 3 || map0.getNumInputs() != 4 ||
Expand All @@ -96,6 +96,79 @@ bool mlir::isRowMajorBatchMatmul(ArrayAttr indexingMaps) {
return indexingMaps == maps;
}

bool mlir::isVecmat(ArrayAttr indexingMaps) {
if (indexingMaps.size() != 3)
return false;
AffineMap map0 = cast<AffineMapAttr>(indexingMaps[0]).getValue();
AffineMap map1 = cast<AffineMapAttr>(indexingMaps[1]).getValue();
AffineMap map2 = cast<AffineMapAttr>(indexingMaps[2]).getValue();

if (map0.getNumResults() != 1 || map1.getNumResults() != 2 ||
map2.getNumResults() != 1 || map0.getNumInputs() != 2 ||
map1.getNumInputs() != 2 || map2.getNumInputs() != 2) {
return false;
}

// Extract dimensions for K * KxN -> N
AffineExpr k = map0.getResult(0);
AffineExpr n = map2.getResult(0);
auto *context = indexingMaps.getContext();
auto mapA = AffineMapAttr::get(AffineMap::get(2, 0, {k}, context));
auto mapB = AffineMapAttr::get(AffineMap::get(2, 0, {k, n}, context));
auto mapC = AffineMapAttr::get(AffineMap::get(2, 0, {n}, context));
auto maps = ArrayAttr::get(context, {mapA, mapB, mapC});
return indexingMaps == maps;
}

bool mlir::isMatvec(ArrayAttr indexingMaps) {
if (indexingMaps.size() != 3)
return false;
AffineMap map0 = cast<AffineMapAttr>(indexingMaps[0]).getValue();
AffineMap map1 = cast<AffineMapAttr>(indexingMaps[1]).getValue();
AffineMap map2 = cast<AffineMapAttr>(indexingMaps[2]).getValue();

if (map0.getNumResults() != 2 || map1.getNumResults() != 1 ||
map2.getNumResults() != 1 || map0.getNumInputs() != 2 ||
map1.getNumInputs() != 2 || map2.getNumInputs() != 2) {
return false;
}

// Extract dimensions for N*K * K -> N
AffineExpr k = map1.getResult(0);
AffineExpr n = map2.getResult(0);
auto *context = indexingMaps.getContext();
auto mapA = AffineMapAttr::get(AffineMap::get(2, 0, {n, k}, context));
auto mapB = AffineMapAttr::get(AffineMap::get(2, 0, {k}, context));
auto mapC = AffineMapAttr::get(AffineMap::get(2, 0, {n}, context));
auto maps = ArrayAttr::get(context, {mapA, mapB, mapC});
return indexingMaps == maps;
}

bool mlir::isBatchMatvec(ArrayAttr indexingMaps) {
if (indexingMaps.size() != 3)
return false;
AffineMap map0 = cast<AffineMapAttr>(indexingMaps[0]).getValue();
AffineMap map1 = cast<AffineMapAttr>(indexingMaps[1]).getValue();
AffineMap map2 = cast<AffineMapAttr>(indexingMaps[2]).getValue();

if (map0.getNumResults() != 3 || map1.getNumResults() != 2 ||
map2.getNumResults() != 2 || map0.getNumInputs() != 3 ||
map1.getNumInputs() != 3 || map2.getNumInputs() != 3) {
return false;
}

// Extract dimensions for B*N*K * B*K -> B*N
AffineExpr b = map0.getResult(0);
AffineExpr k = map1.getResult(1);
AffineExpr n = map2.getResult(1);
auto *context = indexingMaps.getContext();
auto mapA = AffineMapAttr::get(AffineMap::get(3, 0, {b, n, k}, context));
auto mapB = AffineMapAttr::get(AffineMap::get(3, 0, {b, k}, context));
auto mapC = AffineMapAttr::get(AffineMap::get(3, 0, {b, n}, context));
auto maps = ArrayAttr::get(context, {mapA, mapB, mapC});
return indexingMaps == maps;
}

Operation *mlir::clone(OpBuilder &b, Operation *op, TypeRange newResultTypes,
ValueRange newOperands) {
IRMapping bvm;
Expand Down
130 changes: 130 additions & 0 deletions mlir/unittests/Dialect/Utils/StructuredOpsUtilsTest.cpp
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Expand Up @@ -240,4 +240,134 @@ TEST(isRowMajorBatchMatmul, FirstInputSwapped) {
EXPECT_THAT(maps, Not(Truly(isRowMajorBatchMatmul)));
}

TEST(isVecmat, Simple) {
MLIRContext context;

AffineExpr k, n;
bindDims(&context, k, n);
auto mapA = AffineMapAttr::get(AffineMap::get(2, 0, {k}, &context));
auto mapB = AffineMapAttr::get(AffineMap::get(2, 0, {k, n}, &context));
auto mapC = AffineMapAttr::get(AffineMap::get(2, 0, {n}, &context));
auto maps = ArrayAttr::get(&context, {mapA, mapB, mapC});

EXPECT_THAT(maps, Truly(isVecmat));
}

TEST(isVecmat, BindingSwapped) {
MLIRContext context;

AffineExpr k, n;
bindDims(&context, n, k); // bind in different order
auto mapA = AffineMapAttr::get(AffineMap::get(2, 0, {k}, &context));
auto mapB = AffineMapAttr::get(AffineMap::get(2, 0, {k, n}, &context));
auto mapC = AffineMapAttr::get(AffineMap::get(2, 0, {n}, &context));
auto maps = ArrayAttr::get(&context, {mapA, mapB, mapC});

EXPECT_THAT(maps, Truly(isVecmat));
}

TEST(isVecmat, WrongDimOrderMatrix) {
MLIRContext context;

AffineExpr k, n;
bindDims(&context, k, n);
auto mapA = AffineMapAttr::get(AffineMap::get(2, 0, {k}, &context));
auto mapB = AffineMapAttr::get(AffineMap::get(2, 0, {n, k}, &context));
auto mapC = AffineMapAttr::get(AffineMap::get(2, 0, {n}, &context));
auto maps = ArrayAttr::get(&context, {mapA, mapB, mapC});

EXPECT_THAT(maps, Not(Truly(isVecmat)));
}

TEST(isMatvec, Simple) {
MLIRContext context;

AffineExpr k, n;
bindDims(&context, k, n);
auto mapA = AffineMapAttr::get(AffineMap::get(2, 0, {n, k}, &context));
auto mapB = AffineMapAttr::get(AffineMap::get(2, 0, {k}, &context));
auto mapC = AffineMapAttr::get(AffineMap::get(2, 0, {n}, &context));
auto maps = ArrayAttr::get(&context, {mapA, mapB, mapC});

EXPECT_THAT(maps, Truly(isMatvec));
}

TEST(isMatvec, BindingSwapped) {
MLIRContext context;

AffineExpr k, n;
bindDims(&context, n, k); // bind in different order
auto mapA = AffineMapAttr::get(AffineMap::get(2, 0, {n, k}, &context));
auto mapB = AffineMapAttr::get(AffineMap::get(2, 0, {k}, &context));
auto mapC = AffineMapAttr::get(AffineMap::get(2, 0, {n}, &context));
auto maps = ArrayAttr::get(&context, {mapA, mapB, mapC});

EXPECT_THAT(maps, Truly(isMatvec));
}

TEST(isMatvec, WrongDimOrderMatrix) {
MLIRContext context;

AffineExpr k, n;
bindDims(&context, k, n);
auto mapA = AffineMapAttr::get(AffineMap::get(2, 0, {k, n}, &context));
auto mapB = AffineMapAttr::get(AffineMap::get(2, 0, {k}, &context));
auto mapC = AffineMapAttr::get(AffineMap::get(2, 0, {n}, &context));
auto maps = ArrayAttr::get(&context, {mapA, mapB, mapC});

EXPECT_THAT(maps, Not(Truly(isMatvec)));
}

TEST(isBatchMatvec, Simple) {
MLIRContext context;

AffineExpr batch, k, n;
bindDims(&context, batch, k, n);
auto mapA = AffineMapAttr::get(AffineMap::get(3, 0, {batch, n, k}, &context));
auto mapB = AffineMapAttr::get(AffineMap::get(3, 0, {batch, k}, &context));
auto mapC = AffineMapAttr::get(AffineMap::get(3, 0, {batch, n}, &context));
auto maps = ArrayAttr::get(&context, {mapA, mapB, mapC});

EXPECT_THAT(maps, Truly(isBatchMatvec));
}

TEST(isBatchMatvec, BindingSwapped) {
MLIRContext context;

AffineExpr batch, k, n;
bindDims(&context, batch, n, k); // bind in different order
auto mapA = AffineMapAttr::get(AffineMap::get(3, 0, {batch, n, k}, &context));
auto mapB = AffineMapAttr::get(AffineMap::get(3, 0, {batch, k}, &context));
auto mapC = AffineMapAttr::get(AffineMap::get(3, 0, {batch, n}, &context));
auto maps = ArrayAttr::get(&context, {mapA, mapB, mapC});

EXPECT_THAT(maps, Truly(isBatchMatvec));
}

TEST(isBatchMatvec, Matmul) {
MLIRContext context;

AffineExpr m, n, k;
bindDims(&context, m, n, k);
auto mapA = AffineMapAttr::get(AffineMap::get(3, 0, {m, k}, &context));
auto mapB = AffineMapAttr::get(AffineMap::get(3, 0, {k, n}, &context));
auto mapC = AffineMapAttr::get(AffineMap::get(3, 0, {m, n}, &context));
auto maps = ArrayAttr::get(&context, {mapA, mapB, mapC});

EXPECT_THAT(maps, Not(Truly(isBatchMatvec)));
}

TEST(isBatchMatvec, WrongDimOrderMatrix) {
MLIRContext context;

AffineExpr batch, k, n;
bindDims(&context, batch, k, n);
auto mapA = AffineMapAttr::get(AffineMap::get(3, 0, {batch, k, n}, &context));
auto mapB = AffineMapAttr::get(AffineMap::get(3, 0, {batch, k}, &context));
auto mapC = AffineMapAttr::get(AffineMap::get(3, 0, {batch, n}, &context));
auto maps = ArrayAttr::get(&context, {mapA, mapB, mapC});

EXPECT_THAT(maps, Not(Truly(isBatchMatvec)));
}

} // namespace