[mlir][affine] Modify assertion into a user visible diagnostic#136474
Merged
[mlir][affine] Modify assertion into a user visible diagnostic#136474
Conversation
Member
|
@llvm/pr-subscribers-mlir-vector @llvm/pr-subscribers-mlir Author: Prakhar Dixit (Prakhar-Dixit) ChangesFixes #122227 Minimal example crashing : The single loop %i contributes two indices (%row and %col) to the 2D memref access. The permutation map expects one index per vectorized loop dimension, but here one loop (%i) maps to two indices (dim=0 and dim=1). The code detects this when trying to assign the second index (dim=1) to the same vector dimension (perm[0]). Full diff: https://github.com/llvm/llvm-project/pull/136474.diff 2 Files Affected:
diff --git a/mlir/lib/Dialect/Vector/Utils/VectorUtils.cpp b/mlir/lib/Dialect/Vector/Utils/VectorUtils.cpp
index 024e8ccb901de..f15ed4b0d5f84 100644
--- a/mlir/lib/Dialect/Vector/Utils/VectorUtils.cpp
+++ b/mlir/lib/Dialect/Vector/Utils/VectorUtils.cpp
@@ -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;
diff --git a/mlir/test/Dialect/Affine/SuperVectorize/vectorize_unsupported.mlir b/mlir/test/Dialect/Affine/SuperVectorize/vectorize_unsupported.mlir
index 6c1a7c48c4cb1..c8c009f02212b 100644
--- a/mlir/test/Dialect/Affine/SuperVectorize/vectorize_unsupported.mlir
+++ b/mlir/test/Dialect/Affine/SuperVectorize/vectorize_unsupported.mlir
@@ -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: }
\ No newline at end of file
|
Member
|
@llvm/pr-subscribers-mlir-affine Author: Prakhar Dixit (Prakhar-Dixit) ChangesFixes #122227 Minimal example crashing : The single loop %i contributes two indices (%row and %col) to the 2D memref access. The permutation map expects one index per vectorized loop dimension, but here one loop (%i) maps to two indices (dim=0 and dim=1). The code detects this when trying to assign the second index (dim=1) to the same vector dimension (perm[0]). Full diff: https://github.com/llvm/llvm-project/pull/136474.diff 2 Files Affected:
diff --git a/mlir/lib/Dialect/Vector/Utils/VectorUtils.cpp b/mlir/lib/Dialect/Vector/Utils/VectorUtils.cpp
index 024e8ccb901de..f15ed4b0d5f84 100644
--- a/mlir/lib/Dialect/Vector/Utils/VectorUtils.cpp
+++ b/mlir/lib/Dialect/Vector/Utils/VectorUtils.cpp
@@ -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;
diff --git a/mlir/test/Dialect/Affine/SuperVectorize/vectorize_unsupported.mlir b/mlir/test/Dialect/Affine/SuperVectorize/vectorize_unsupported.mlir
index 6c1a7c48c4cb1..c8c009f02212b 100644
--- a/mlir/test/Dialect/Affine/SuperVectorize/vectorize_unsupported.mlir
+++ b/mlir/test/Dialect/Affine/SuperVectorize/vectorize_unsupported.mlir
@@ -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: }
\ No newline at end of file
|
Contributor
Author
joker-eph
reviewed
Apr 20, 2025
joker-eph
reviewed
Apr 22, 2025
joker-eph
reviewed
Apr 22, 2025
Contributor
Author
|
Just a gentle reminder! |
ftynse
approved these changes
Apr 29, 2025
ftynse
approved these changes
Apr 30, 2025
IanWood1
pushed a commit
to IanWood1/llvm-project
that referenced
this pull request
May 6, 2025
…136474) Fixes llvm#122227 The loop’s induction variable (%i) is used to compute two different indices via affine.apply. And the Vectorization Assumption is Violated i.e, Each vectorized loop should contribute at most one non-invariant index. **Minimal example crashing :** ``` #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> } ``` The single loop %i contributes two indices (%row and %col) to the 2D memref access. The permutation map expects one index per vectorized loop dimension, but here one loop (%i) maps to two indices (dim=0 and dim=1). The code detects this when trying to assign the second index (dim=1) to the same vector dimension (perm[0]).
GeorgeARM
pushed a commit
to GeorgeARM/llvm-project
that referenced
this pull request
May 7, 2025
…136474) Fixes llvm#122227 The loop’s induction variable (%i) is used to compute two different indices via affine.apply. And the Vectorization Assumption is Violated i.e, Each vectorized loop should contribute at most one non-invariant index. **Minimal example crashing :** ``` #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> } ``` The single loop %i contributes two indices (%row and %col) to the 2D memref access. The permutation map expects one index per vectorized loop dimension, but here one loop (%i) maps to two indices (dim=0 and dim=1). The code detects this when trying to assign the second index (dim=1) to the same vector dimension (perm[0]).
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
5 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Fixes #122227
The loop’s induction variable (%i) is used to compute two different indices via affine.apply.
And the Vectorization Assumption is Violated i.e, Each vectorized loop should contribute at most one non-invariant index.
Minimal example crashing :
The single loop %i contributes two indices (%row and %col) to the 2D memref access.
The permutation map expects one index per vectorized loop dimension, but here one loop (%i) maps to two indices (dim=0 and dim=1).
The code detects this when trying to assign the second index (dim=1) to the same vector dimension (perm[0]).