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Add isBatchVecmat utilities for linalg.batch_vecmat #70284

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Merged
merged 1 commit into from
Oct 26, 2023
Merged

Add isBatchVecmat utilities for linalg.batch_vecmat #70284

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11 changes: 11 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 @@ -98,6 +98,17 @@ def LinalgContractionOpInterface : OpInterface<"ContractionOpInterface"> {
return mlir::isVecmat($_op.getIndexingMaps());
}]>,
InterfaceMethod<
/*desc=*/[{
Returns whether the given op has indexing maps that correspond to a
batched vector-matrix multiplication.
}],
/*retTy=*/"bool",
/*methodName=*/"isBatchVecmat",
/*args=*/(ins),
/*methodBody=*/[{
return mlir::isBatchVecmat($_op.getIndexingMaps());
}]>,
InterfaceMethod<
/*desc=*/[{
Returns whether the given op has indexing maps that correspond to a
matrix-vector multiplication.
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6 changes: 6 additions & 0 deletions mlir/include/mlir/Dialect/Utils/StructuredOpsUtils.h
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Expand Up @@ -55,6 +55,12 @@ bool isRowMajorBatchMatmul(ArrayAttr indexingMaps);
/// performed within the reduction.
bool isVecmat(ArrayAttr indexingMaps);

/// Tests whether the given maps describe a batch 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 isBatchVecmat(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
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25 changes: 25 additions & 0 deletions mlir/lib/Dialect/Utils/StructuredOpsUtils.cpp
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Expand Up @@ -120,6 +120,31 @@ bool mlir::isVecmat(ArrayAttr indexingMaps) {
return indexingMaps == maps;
}

bool mlir::isBatchVecmat(ArrayAttr indexingMaps) {
if (indexingMaps.size() != 3)
return false;
AffineMap map0 = cast<AffineMapAttr>(indexingMaps[0]).getValue();
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you could use the infer utils which I find nicer to work with:

llvm-project/mlir/lib/Dialect/Vector/Transforms/VectorTransforms.cpp

Line 1325 in d1556e5

if (maps == infer({{m, k}, {k, n}, {m, n}})) {
your call :)

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i see. nicer indeed, but i was copy and pasting other instances in this file. The move to infer looks like it would be a nice improvement, but should be done for the whole file togeteher, so, in a separate PR.

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

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

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

bool mlir::isMatvec(ArrayAttr indexingMaps) {
if (indexingMaps.size() != 3)
return false;
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52 changes: 52 additions & 0 deletions mlir/unittests/Dialect/Utils/StructuredOpsUtilsTest.cpp
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Expand Up @@ -370,4 +370,56 @@ TEST(isBatchMatvec, WrongDimOrderMatrix) {
EXPECT_THAT(maps, Not(Truly(isBatchMatvec)));
}

TEST(isBatchVecmat, Simple) {
MLIRContext context;

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

EXPECT_THAT(maps, Truly(isBatchVecmat));
}

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

EXPECT_THAT(maps, Truly(isBatchVecmat));
}

TEST(isBatchVecmat, 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(isBatchVecmat)));
}

TEST(isBatchVecmat, WrongDimOrderMatrix) {
MLIRContext context;

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

} // namespace