Skip to content

[mlir][affine] Modify assertion into a user visible diagnostic #136474

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 6 commits into from
Apr 30, 2025
Merged

[mlir][affine] Modify assertion into a user visible diagnostic #136474

Show file tree
Hide file tree
Changes from 1 commit
Commits
Show all changes
6 commits
Select commit Hold shift + click to select a range
84157c0
[mlir][affine] Modify assertion into a user visible diagnostic
Prakhar-Dixit Apr 20, 2025
8112d1a
Add check to ensure pass fails gracefully
Prakhar-Dixit Apr 22, 2025
24acbf9
typo fix
Prakhar-Dixit Apr 22, 2025
99f6885
Create a helper function to avoid code duplication
Prakhar-Dixit Apr 22, 2025
2052b9d
modify code with best practices
Prakhar-Dixit Apr 30, 2025
827b352
modify
Prakhar-Dixit Apr 30, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
10 changes: 8 additions & 2 deletions mlir/lib/Dialect/Vector/Utils/VectorUtils.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -141,8 +141,14 @@ static AffineMap makePermutationMap(
unsigned countInvariantIndices = 0;
for (unsigned dim = 0; dim < numIndices; ++dim) {
if (!invariants.count(indices[dim])) {
assert(perm[kvp.second] == getAffineConstantExpr(0, context) &&
"permutationMap already has an entry along dim");
if (perm[kvp.second] != getAffineConstantExpr(0, context)) {
auto loopOp = cast<affine::AffineForOp>(kvp.first);
loopOp->emitError(
"loop induction variable is used in multiple indices, which is "
"unsupported for vectorization. Consider using nested loops "
"instead of a single loop with affine.apply.");
return AffineMap();
}
perm[kvp.second] = getAffineDimExpr(dim, context);
} else {
++countInvariantIndices;
Expand Down
35 changes: 35 additions & 0 deletions mlir/test/Dialect/Affine/SuperVectorize/vectorize_unsupported.mlir
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -9,3 +9,38 @@ func.func @unparallel_loop_reduction_unsupported(%in: memref<256x512xf32>, %out:
}
return
}

// -----

#map = affine_map<(d0)[s0] -> (d0 mod s0)>
#map1 = affine_map<(d0)[s0] -> (d0 floordiv s0)>

func.func @single_loop_unrolling_2D_access_pattern(%arg0: index) -> memref<2x2xf32> {
%c2 = arith.constant 2 : index
%cst = arith.constant 1.0 : f32
%alloc = memref.alloc() : memref<2x2xf32>

affine.for %i = 0 to 4 {
%row = affine.apply #map1(%i)[%c2]
%col = affine.apply #map(%i)[%c2]
affine.store %cst, %alloc[%row, %col] : memref<2x2xf32>
}

return %alloc : memref<2x2xf32>
}

// CHECK: #[[$ATTR_0:.+]] = affine_map<(d0)[s0] -> (d0 floordiv s0)>
// CHECK: #[[$ATTR_1:.+]] = affine_map<(d0)[s0] -> (d0 mod s0)>

// CHECK-LABEL: func.func @single_loop_unrolling_2D_access_pattern(
// CHECK-SAME: %[[VAL_0:[0-9]+|[a-zA-Z$._-][a-zA-Z0-9$._-]*]]: index) -> memref<2x2xf32> {
// CHECK: %[[VAL_1:.*]] = arith.constant 2 : index
// CHECK: %[[VAL_2:.*]] = arith.constant 1.000000e+00 : f32
// CHECK: %[[VAL_3:.*]] = memref.alloc() : memref<2x2xf32>
// CHECK: affine.for %[[VAL_4:.*]] = 0 to 4 {
// CHECK: %[[VAL_5:.*]] = affine.apply #[[$ATTR_0]](%[[VAL_4]]){{\[}}%[[VAL_1]]]
// CHECK: %[[VAL_6:.*]] = affine.apply #[[$ATTR_1]](%[[VAL_4]]){{\[}}%[[VAL_1]]]
// CHECK: affine.store %[[VAL_2]], %[[VAL_3]]{{\[}}%[[VAL_5]], %[[VAL_6]]] : memref<2x2xf32>
// CHECK: }
// CHECK: return %[[VAL_3]] : memref<2x2xf32>
// CHECK: }
Loading