[clang] [clang-tools-extra] [llvm] [mlir] [mlir] Fix a zero stride canonicalizer crash (PR #74200)
Rik Huijzer via cfe-commits
cfe-commits at lists.llvm.org
Sat Dec 2 09:09:56 PST 2023
https://github.com/rikhuijzer created https://github.com/llvm/llvm-project/pull/74200
This PR fixes https://github.com/llvm/llvm-project/issues/73383 and is another shot at the refactoring proposed in https://github.com/llvm/llvm-project/pull/72885.
>From 22928e7e5da508d8d9dc8d4b7e54f84cccadef06 Mon Sep 17 00:00:00 2001
From: Rik Huijzer <github at huijzer.xyz>
Date: Mon, 20 Nov 2023 09:02:41 +0100
Subject: [PATCH 1/5] [mlir][tensor] Fix canon via `hasNegativeDimension`
---
mlir/include/mlir/Dialect/Tensor/IR/Tensor.h | 6 ++++++
mlir/lib/Dialect/Tensor/IR/TensorOps.cpp | 15 +++++++++++++++
mlir/test/Dialect/Tensor/canonicalize.mlir | 10 ++++++++++
3 files changed, 31 insertions(+)
diff --git a/mlir/include/mlir/Dialect/Tensor/IR/Tensor.h b/mlir/include/mlir/Dialect/Tensor/IR/Tensor.h
index 06642adda42b3..0d027057b3a95 100644
--- a/mlir/include/mlir/Dialect/Tensor/IR/Tensor.h
+++ b/mlir/include/mlir/Dialect/Tensor/IR/Tensor.h
@@ -150,6 +150,12 @@ LogicalResult getOrCreateDestinations(OpBuilder &b, Location loc, Operation *op,
/// Tests if types are the same when ignoring encoding on ranked tensors.
bool isSameTypeWithoutEncoding(Type tp1, Type tp2);
+/// Helper function to check whether the dimensions are non-negative. This
+/// check also occurs in the verifier, but we need it at later stages too
+/// because the verifier ignores dynamic dimensions, but later stages might
+/// have constant folded those to (negative) constants.
+bool hasNegativeDimension(SmallVector<int64_t> shape);
+
/// Function to control the folding of constant and extract slice.
using ControlConstantExtractSliceFusionFn = std::function<bool(ExtractSliceOp)>;
diff --git a/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp b/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp
index e469815496e18..3297ef673ca2e 100644
--- a/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp
+++ b/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp
@@ -125,6 +125,12 @@ bool tensor::isSameTypeWithoutEncoding(Type tp1, Type tp2) {
return tp1 == tp2; // default implementation
}
+bool tensor::hasNegativeDimension(SmallVector<int64_t> shape) {
+ return llvm::any_of(shape, [](int64_t dim) {
+ return !ShapedType::isDynamic(dim) && dim < 0;
+ });
+}
+
/// Compute the dropped dimensions of a rank-reducing tensor.extract_slice op or
/// rank-extending tensor.insert_slice op.
static llvm::SmallBitVector getDroppedDims(ArrayRef<int64_t> reducedShape,
@@ -1801,6 +1807,10 @@ RankedTensorType ExtractSliceOp::inferCanonicalRankReducedResultType(
dispatchIndexOpFoldResults(offsets, dynamicOffsets, staticOffsets);
dispatchIndexOpFoldResults(sizes, dynamicSizes, staticSizes);
dispatchIndexOpFoldResults(strides, dynamicStrides, staticStrides);
+ if (hasNegativeDimension(staticOffsets))
+ return {};
+ if (hasNegativeDimension(staticSizes))
+ return {};
return ExtractSliceOp::inferCanonicalRankReducedResultType(
desiredResultRank, sourceRankedTensorType, staticOffsets, staticSizes,
staticStrides);
@@ -2370,6 +2380,8 @@ class InsertSliceOpConstantArgumentFolder final
auto sourceType = ExtractSliceOp::inferCanonicalRankReducedResultType(
insertSliceOp.getSourceType().getRank(), insertSliceOp.getDestType(),
mixedOffsets, mixedSizes, mixedStrides);
+ if (!sourceType)
+ return failure();
Value toInsert = insertSliceOp.getSource();
if (sourceType != insertSliceOp.getSourceType()) {
OpBuilder::InsertionGuard g(rewriter);
@@ -2500,6 +2512,8 @@ struct InsertSliceOpSourceCastInserter final
getConstantIntValue(insertSliceOp.getMixedSizes()[i]))
newSrcShape[i] = *constInt;
}
+ // if (hasNegativeDimension(newSrcShape))
+ // return failure();
RankedTensorType newSrcType =
RankedTensorType::get(newSrcShape, srcType.getElementType());
@@ -2521,6 +2535,7 @@ struct InsertSliceOpSourceCastInserter final
rewriter.setInsertionPoint(insertSliceOp->getParentOp());
Value cast = rewriter.create<tensor::CastOp>(
insertSliceOp.getLoc(), newSrcType, insertSliceOp.getSource());
+
rewriter.replaceOpWithNewOp<InsertOpTy>(
insertSliceOp, cast, insertSliceOp.getDest(),
insertSliceOp.getMixedOffsets(), insertSliceOp.getMixedSizes(),
diff --git a/mlir/test/Dialect/Tensor/canonicalize.mlir b/mlir/test/Dialect/Tensor/canonicalize.mlir
index ea8c17640d7c1..88f27d3d36b04 100644
--- a/mlir/test/Dialect/Tensor/canonicalize.mlir
+++ b/mlir/test/Dialect/Tensor/canonicalize.mlir
@@ -1102,6 +1102,16 @@ func.func @no_fold_collapse_of_expand_empty_expr(%arg0: tensor<3x2x2xf32>)
// -----
+func.func @no_fold_extract_slice_negative_offset(%arg0: tensor<8xf32>) -> tensor<?xf32> {
+ %c-1 = arith.constant -1 : index
+ %e = tensor.extract_slice %arg0[1] [%c-1] [1] : tensor<8xf32> to tensor<?xf32>
+ return %e : tensor<?xf32>
+}
+// CHECK-LABEL: func @no_fold_extract_slice_negative_offset
+// CHECK: tensor.extract_slice
+
+// -----
+
func.func @reshape_splat_constant_int32() -> tensor<2x4x2xi32> {
%c0 = arith.constant dense<42> : tensor<2x8xi32>
%0 = tensor.expand_shape %c0 [[0], [1, 2]]
>From ecef5428c160cb72103e06a160c450440ce1f416 Mon Sep 17 00:00:00 2001
From: Rik Huijzer <github at huijzer.xyz>
Date: Mon, 20 Nov 2023 16:27:53 +0100
Subject: [PATCH 2/5] Fix `insert_slice` cast inserter and refactor
---
mlir/include/mlir/Dialect/Tensor/IR/Tensor.h | 6 ------
.../mlir/Dialect/Utils/StaticValueUtils.h | 6 ++++++
mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp | 15 ++++-----------
mlir/lib/Dialect/Tensor/IR/TensorOps.cpp | 18 +++---------------
mlir/lib/Dialect/Utils/StaticValueUtils.cpp | 6 ++++++
mlir/test/Dialect/Tensor/canonicalize.mlir | 14 ++++++++++++++
6 files changed, 33 insertions(+), 32 deletions(-)
diff --git a/mlir/include/mlir/Dialect/Tensor/IR/Tensor.h b/mlir/include/mlir/Dialect/Tensor/IR/Tensor.h
index 0d027057b3a95..06642adda42b3 100644
--- a/mlir/include/mlir/Dialect/Tensor/IR/Tensor.h
+++ b/mlir/include/mlir/Dialect/Tensor/IR/Tensor.h
@@ -150,12 +150,6 @@ LogicalResult getOrCreateDestinations(OpBuilder &b, Location loc, Operation *op,
/// Tests if types are the same when ignoring encoding on ranked tensors.
bool isSameTypeWithoutEncoding(Type tp1, Type tp2);
-/// Helper function to check whether the dimensions are non-negative. This
-/// check also occurs in the verifier, but we need it at later stages too
-/// because the verifier ignores dynamic dimensions, but later stages might
-/// have constant folded those to (negative) constants.
-bool hasNegativeDimension(SmallVector<int64_t> shape);
-
/// Function to control the folding of constant and extract slice.
using ControlConstantExtractSliceFusionFn = std::function<bool(ExtractSliceOp)>;
diff --git a/mlir/include/mlir/Dialect/Utils/StaticValueUtils.h b/mlir/include/mlir/Dialect/Utils/StaticValueUtils.h
index 23a366036b9dd..9e39d81e5c4f9 100644
--- a/mlir/include/mlir/Dialect/Utils/StaticValueUtils.h
+++ b/mlir/include/mlir/Dialect/Utils/StaticValueUtils.h
@@ -128,6 +128,12 @@ std::pair<ArrayAttr, SmallVector<Value>>
decomposeMixedValues(Builder &b,
const SmallVectorImpl<OpFoldResult> &mixedValues);
+/// Helper function to check whether the dimensions are non-negative.
+///
+/// This is used to re-check whether dimensions are still non-negative after
+/// constant folding the dynamic dimensions.
+bool hasNegativeDimension(SmallVector<int64_t> values);
+
/// Helper to sort `values` according to matching `keys`.
SmallVector<Value>
getValuesSortedByKey(ArrayRef<Attribute> keys, ArrayRef<Value> values,
diff --git a/mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp b/mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp
index a2fc954ad07fa..dd75ed2500306 100644
--- a/mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp
+++ b/mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp
@@ -2621,17 +2621,10 @@ Type SubViewOp::inferResultType(MemRefType sourceMemRefType,
dispatchIndexOpFoldResults(offsets, dynamicOffsets, staticOffsets);
dispatchIndexOpFoldResults(sizes, dynamicSizes, staticSizes);
dispatchIndexOpFoldResults(strides, dynamicStrides, staticStrides);
-
- // If one of the offsets or sizes is invalid, fail the canonicalization.
- // These checks also occur in the verifier, but they are needed here
- // because some dynamic dimensions may have been constant folded.
- for (int64_t offset : staticOffsets)
- if (offset < 0 && !ShapedType::isDynamic(offset))
- return {};
- for (int64_t size : staticSizes)
- if (size < 0 && !ShapedType::isDynamic(size))
- return {};
-
+ if (hasNegativeDimension(staticOffsets))
+ return {};
+ if (hasNegativeDimension(staticSizes))
+ return {};
return SubViewOp::inferResultType(sourceMemRefType, staticOffsets,
staticSizes, staticStrides);
}
diff --git a/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp b/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp
index 3297ef673ca2e..986e40a2e4eb3 100644
--- a/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp
+++ b/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp
@@ -125,12 +125,6 @@ bool tensor::isSameTypeWithoutEncoding(Type tp1, Type tp2) {
return tp1 == tp2; // default implementation
}
-bool tensor::hasNegativeDimension(SmallVector<int64_t> shape) {
- return llvm::any_of(shape, [](int64_t dim) {
- return !ShapedType::isDynamic(dim) && dim < 0;
- });
-}
-
/// Compute the dropped dimensions of a rank-reducing tensor.extract_slice op or
/// rank-extending tensor.insert_slice op.
static llvm::SmallBitVector getDroppedDims(ArrayRef<int64_t> reducedShape,
@@ -1265,13 +1259,8 @@ struct StaticTensorGenerate : public OpRewritePattern<GenerateOp> {
SmallVector<int64_t> newShape;
operandsAndShape(resultType, dynamicExtents, newOperands, newShape);
- for (int64_t newdim : newShape) {
- // This check also occurs in the verifier, but we need it here too
- // since intermediate passes may have replaced some dynamic dimensions
- // by constants.
- if (newdim < 0 && !ShapedType::isDynamic(newdim))
+ if (hasNegativeDimension(newShape))
return failure();
- }
if (newOperands.size() == tensorFromElements.getDynamicExtents().size())
return failure();
@@ -2512,8 +2501,8 @@ struct InsertSliceOpSourceCastInserter final
getConstantIntValue(insertSliceOp.getMixedSizes()[i]))
newSrcShape[i] = *constInt;
}
- // if (hasNegativeDimension(newSrcShape))
- // return failure();
+ if (hasNegativeDimension(newSrcShape))
+ return failure();
RankedTensorType newSrcType =
RankedTensorType::get(newSrcShape, srcType.getElementType());
@@ -2535,7 +2524,6 @@ struct InsertSliceOpSourceCastInserter final
rewriter.setInsertionPoint(insertSliceOp->getParentOp());
Value cast = rewriter.create<tensor::CastOp>(
insertSliceOp.getLoc(), newSrcType, insertSliceOp.getSource());
-
rewriter.replaceOpWithNewOp<InsertOpTy>(
insertSliceOp, cast, insertSliceOp.getDest(),
insertSliceOp.getMixedOffsets(), insertSliceOp.getMixedSizes(),
diff --git a/mlir/lib/Dialect/Utils/StaticValueUtils.cpp b/mlir/lib/Dialect/Utils/StaticValueUtils.cpp
index 8a4ccc990331a..5d777ad74e9e8 100644
--- a/mlir/lib/Dialect/Utils/StaticValueUtils.cpp
+++ b/mlir/lib/Dialect/Utils/StaticValueUtils.cpp
@@ -200,6 +200,12 @@ decomposeMixedValues(Builder &b,
return {b.getI64ArrayAttr(staticValues), dynamicValues};
}
+bool hasNegativeDimension(SmallVector<int64_t> values) {
+ return llvm::any_of(values, [](int64_t value) {
+ return !ShapedType::isDynamic(value) && value < 0;
+ });
+}
+
/// Helper to sort `values` according to matching `keys`.
template <typename K, typename V>
static SmallVector<V>
diff --git a/mlir/test/Dialect/Tensor/canonicalize.mlir b/mlir/test/Dialect/Tensor/canonicalize.mlir
index 88f27d3d36b04..1c0a2e868475f 100644
--- a/mlir/test/Dialect/Tensor/canonicalize.mlir
+++ b/mlir/test/Dialect/Tensor/canonicalize.mlir
@@ -1112,6 +1112,20 @@ func.func @no_fold_extract_slice_negative_offset(%arg0: tensor<8xf32>) -> tensor
// -----
+func.func @no_fold_insert_slice_cast_inserter_negative_offset() -> tensor<?xf32> {
+ %c = arith.constant 0 : index
+ %const = tensor.empty(%c) : tensor<?xf32>
+ %insert_val = tensor.empty(%c) : tensor<?xf32>
+ %c-1 = arith.constant -1 : index
+ %inserted = tensor.insert_slice %insert_val into %const[0][%c-1][1] : tensor<?xf32> into tensor<?xf32>
+ return %inserted : tensor<?xf32>
+}
+// CHECK-LABEL: func @no_fold_insert_slice_cast_inserter_negative_offset
+// CHECK: %[[CAST:.*]] = tensor.cast
+// CHECK: tensor.insert_slice %[[CAST:.+]]
+
+// -----
+
func.func @reshape_splat_constant_int32() -> tensor<2x4x2xi32> {
%c0 = arith.constant dense<42> : tensor<2x8xi32>
%0 = tensor.expand_shape %c0 [[0], [1, 2]]
>From 69637ad2b8915f352c6dae3cab838a04b84c3e10 Mon Sep 17 00:00:00 2001
From: Rik Huijzer <github at huijzer.xyz>
Date: Mon, 20 Nov 2023 16:40:09 +0100
Subject: [PATCH 3/5] Apply `clang-format`
---
mlir/lib/Dialect/Tensor/IR/TensorOps.cpp | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp b/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp
index 986e40a2e4eb3..04a8e43a639f4 100644
--- a/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp
+++ b/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp
@@ -1260,7 +1260,7 @@ struct StaticTensorGenerate : public OpRewritePattern<GenerateOp> {
operandsAndShape(resultType, dynamicExtents, newOperands, newShape);
if (hasNegativeDimension(newShape))
- return failure();
+ return failure();
if (newOperands.size() == tensorFromElements.getDynamicExtents().size())
return failure();
>From ecd074dc485485ebf6b7ae7aa5ee52cb397994ca Mon Sep 17 00:00:00 2001
From: Rik Huijzer <github at huijzer.xyz>
Date: Sat, 2 Dec 2023 18:02:31 +0100
Subject: [PATCH 4/5] Refactor
---
.../mlir/Dialect/Utils/StaticValueUtils.h | 36 ++++++++++++++-----
mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp | 7 ++--
mlir/lib/Dialect/Tensor/IR/TensorOps.cpp | 16 +++------
mlir/lib/Dialect/Utils/StaticValueUtils.cpp | 33 +++++++++++++----
mlir/test/Dialect/MemRef/canonicalize.mlir | 12 +++++++
5 files changed, 75 insertions(+), 29 deletions(-)
diff --git a/mlir/include/mlir/Dialect/Utils/StaticValueUtils.h b/mlir/include/mlir/Dialect/Utils/StaticValueUtils.h
index 768f0ac1abe56..a1853438ccf7f 100644
--- a/mlir/include/mlir/Dialect/Utils/StaticValueUtils.h
+++ b/mlir/include/mlir/Dialect/Utils/StaticValueUtils.h
@@ -128,12 +128,6 @@ std::pair<ArrayAttr, SmallVector<Value>>
decomposeMixedValues(Builder &b,
const SmallVectorImpl<OpFoldResult> &mixedValues);
-/// Helper function to check whether the dimensions are non-negative.
-///
-/// This is used to re-check whether dimensions are still non-negative after
-/// constant folding the dynamic dimensions.
-bool hasNegativeDimension(SmallVector<int64_t> values);
-
/// Helper to sort `values` according to matching `keys`.
SmallVector<Value>
getValuesSortedByKey(ArrayRef<Attribute> keys, ArrayRef<Value> values,
@@ -145,12 +139,36 @@ SmallVector<int64_t>
getValuesSortedByKey(ArrayRef<Attribute> keys, ArrayRef<int64_t> values,
llvm::function_ref<bool(Attribute, Attribute)> compare);
+/// Helper function to check whether the passed in `sizes` or `values` are
+/// valid. This can be used to re-check whether dimensions are still valid
+/// after constant folding the dynamic dimensions.
+bool hasValidSizesOffsets(SmallVector<int64_t> sizesOrOffsets);
+
+/// Helper function to check whether the passed in `strides` are valid. This
+/// can be used to re-check whether dimensions are still valid after constant
+/// folding the dynamic dimensions.
+bool hasValidStrides(SmallVector<int64_t> strides);
+
/// Returns "success" when any of the elements in `ofrs` is a constant value. In
/// that case the value is replaced by an attribute. Returns "failure" when no
-/// folding happened. If `onlyNonNegative` is set, only non-negative constant
-/// values are folded.
+/// folding happened. If `onlyNonNegative` and `onlyNonZero` are set, only
+/// non-negative and non-zero constant values are folded respectively.
LogicalResult foldDynamicIndexList(SmallVectorImpl<OpFoldResult> &ofrs,
- bool onlyNonNegative = false);
+ bool onlyNonNegative = false,
+ bool onlyNonZero = false);
+
+/// Returns "success" when any of the elements in `OffsetsOrSizes` is a
+/// constant value. In that case the value is replaced by an attribute. Returns
+/// "failure" when no folding happened. Invalid values are not folded to avoid
+/// canonicalization crashes.
+LogicalResult
+foldDynamicOffsetSizeList(SmallVectorImpl<OpFoldResult> &offsetsOrSizes);
+
+/// Returns "success" when any of the elements in `strides` is a constant
+/// value. In that case the value is replaced by an attribute. Returns
+/// "failure" when no folding happened. Invalid values are not folded to avoid
+/// canonicalization crashes.
+LogicalResult foldDynamicStrideList(SmallVectorImpl<OpFoldResult> &strides);
/// Return the number of iterations for a loop with a lower bound `lb`, upper
/// bound `ub` and step `step`.
diff --git a/mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp b/mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp
index f222011a2edf5..c6d947a2427db 100644
--- a/mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp
+++ b/mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp
@@ -22,6 +22,7 @@
#include "mlir/Interfaces/ViewLikeInterface.h"
#include "llvm/ADT/STLExtras.h"
#include "llvm/ADT/SmallBitVector.h"
+#include <cstdint>
using namespace mlir;
using namespace mlir::memref;
@@ -2581,9 +2582,11 @@ Type SubViewOp::inferResultType(MemRefType sourceMemRefType,
dispatchIndexOpFoldResults(offsets, dynamicOffsets, staticOffsets);
dispatchIndexOpFoldResults(sizes, dynamicSizes, staticSizes);
dispatchIndexOpFoldResults(strides, dynamicStrides, staticStrides);
- if (hasNegativeDimension(staticOffsets))
+ if (!hasValidSizesOffsets(staticOffsets))
return {};
- if (hasNegativeDimension(staticSizes))
+ if (!hasValidSizesOffsets(staticSizes))
+ return {};
+ if (!hasValidStrides(staticStrides))
return {};
return SubViewOp::inferResultType(sourceMemRefType, staticOffsets,
staticSizes, staticStrides);
diff --git a/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp b/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp
index eab1d261b1064..94b7b734f88fe 100644
--- a/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp
+++ b/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp
@@ -1446,7 +1446,7 @@ struct StaticTensorGenerate : public OpRewritePattern<GenerateOp> {
SmallVector<int64_t> newShape;
operandsAndShape(resultType, dynamicExtents, newOperands, newShape);
- if (hasNegativeDimension(newShape))
+ if (!hasValidSizesOffsets(newShape))
return failure();
if (newOperands.size() == tensorFromElements.getDynamicExtents().size())
@@ -1983,10 +1983,6 @@ RankedTensorType ExtractSliceOp::inferCanonicalRankReducedResultType(
dispatchIndexOpFoldResults(offsets, dynamicOffsets, staticOffsets);
dispatchIndexOpFoldResults(sizes, dynamicSizes, staticSizes);
dispatchIndexOpFoldResults(strides, dynamicStrides, staticStrides);
- if (hasNegativeDimension(staticOffsets))
- return {};
- if (hasNegativeDimension(staticSizes))
- return {};
return ExtractSliceOp::inferCanonicalRankReducedResultType(
desiredResultRank, sourceRankedTensorType, staticOffsets, staticSizes,
staticStrides);
@@ -2547,17 +2543,15 @@ class InsertSliceOpConstantArgumentFolder final
SmallVector<OpFoldResult> mixedStrides(insertSliceOp.getMixedStrides());
// No constant operands were folded, just return;
- if (failed(foldDynamicIndexList(mixedOffsets, /*onlyNonNegative=*/true)) &&
- failed(foldDynamicIndexList(mixedSizes, /*onlyNonNegative=*/true)) &&
- failed(foldDynamicIndexList(mixedStrides)))
+ if (failed(foldDynamicOffsetSizeList(mixedOffsets)) &&
+ failed(foldDynamicOffsetSizeList(mixedSizes)) &&
+ failed(foldDynamicStrideList(mixedStrides)))
return failure();
// Create the new op in canonical form.
auto sourceType = ExtractSliceOp::inferCanonicalRankReducedResultType(
insertSliceOp.getSourceType().getRank(), insertSliceOp.getDestType(),
mixedOffsets, mixedSizes, mixedStrides);
- if (!sourceType)
- return failure();
Value toInsert = insertSliceOp.getSource();
if (sourceType != insertSliceOp.getSourceType()) {
OpBuilder::InsertionGuard g(rewriter);
@@ -2692,7 +2686,7 @@ struct InsertSliceOpSourceCastInserter final
newSrcShape[i] = *constInt;
}
}
- if (hasNegativeDimension(newSrcShape))
+ if (!hasValidSizesOffsets(newSrcShape))
return failure();
RankedTensorType newSrcType =
diff --git a/mlir/lib/Dialect/Utils/StaticValueUtils.cpp b/mlir/lib/Dialect/Utils/StaticValueUtils.cpp
index 4f606e17a4d59..0c8a88da789e2 100644
--- a/mlir/lib/Dialect/Utils/StaticValueUtils.cpp
+++ b/mlir/lib/Dialect/Utils/StaticValueUtils.cpp
@@ -200,12 +200,6 @@ decomposeMixedValues(Builder &b,
return {b.getI64ArrayAttr(staticValues), dynamicValues};
}
-bool hasNegativeDimension(SmallVector<int64_t> values) {
- return llvm::any_of(values, [](int64_t value) {
- return !ShapedType::isDynamic(value) && value < 0;
- });
-}
-
/// Helper to sort `values` according to matching `keys`.
template <typename K, typename V>
static SmallVector<V>
@@ -262,8 +256,20 @@ std::optional<int64_t> constantTripCount(OpFoldResult lb, OpFoldResult ub,
return mlir::ceilDiv(*ubConstant - *lbConstant, *stepConstant);
}
+bool hasValidSizesOffsets(SmallVector<int64_t> sizesOrOffsets) {
+ return llvm::none_of(sizesOrOffsets, [](int64_t value) {
+ return !ShapedType::isDynamic(value) && value < 0;
+ });
+}
+
+bool hasValidStrides(SmallVector<int64_t> strides) {
+ return llvm::none_of(strides, [](int64_t value) {
+ return !ShapedType::isDynamic(value) && value == 0;
+ });
+}
+
LogicalResult foldDynamicIndexList(SmallVectorImpl<OpFoldResult> &ofrs,
- bool onlyNonNegative) {
+ bool onlyNonNegative, bool onlyNonZero) {
bool valuesChanged = false;
for (OpFoldResult &ofr : ofrs) {
if (ofr.is<Attribute>())
@@ -273,6 +279,8 @@ LogicalResult foldDynamicIndexList(SmallVectorImpl<OpFoldResult> &ofrs,
// Note: All ofrs have index type.
if (onlyNonNegative && *getConstantIntValue(attr) < 0)
continue;
+ if (onlyNonZero && *getConstantIntValue(attr) == 0)
+ continue;
ofr = attr;
valuesChanged = true;
}
@@ -280,4 +288,15 @@ LogicalResult foldDynamicIndexList(SmallVectorImpl<OpFoldResult> &ofrs,
return success(valuesChanged);
}
+LogicalResult
+foldDynamicOffsetSizeList(SmallVectorImpl<OpFoldResult> &offsetsOrSizes) {
+ return foldDynamicIndexList(offsetsOrSizes, /*onlyNonNegative=*/true,
+ /*onlyNonZero=*/false);
+}
+
+LogicalResult foldDynamicStrideList(SmallVectorImpl<OpFoldResult> &strides) {
+ return foldDynamicIndexList(strides, /*onlyNonNegative=*/false,
+ /*onlyNonZero=*/true);
+}
+
} // namespace mlir
diff --git a/mlir/test/Dialect/MemRef/canonicalize.mlir b/mlir/test/Dialect/MemRef/canonicalize.mlir
index a1f8673638ff8..d3406c630f6dd 100644
--- a/mlir/test/Dialect/MemRef/canonicalize.mlir
+++ b/mlir/test/Dialect/MemRef/canonicalize.mlir
@@ -191,6 +191,18 @@ func.func @no_fold_subview_negative_size(%input: memref<4x1024xf32>) -> memref<?
// -----
+// CHECK-LABEL: func @no_fold_subview_zero_stride
+// CHECK: %[[SUBVIEW:.+]] = memref.subview
+// CHECK: return %[[SUBVIEW]]
+func.func @no_fold_subview_zero_stride(%arg0 : memref<10xf32>) -> memref<1xf32, strided<[?], offset: 1>> {
+ %c0 = arith.constant 0 : index
+ %c1 = arith.constant 1 : index
+ %1 = memref.subview %arg0[1] [1] [%c0] : memref<10xf32> to memref<1xf32, strided<[?], offset: 1>>
+ return %1 : memref<1xf32, strided<[?], offset: 1>>
+}
+
+// -----
+
// CHECK-LABEL: func @no_fold_of_store
// CHECK: %[[cst:.+]] = memref.cast %arg
// CHECK: memref.store %[[cst]]
>From 9a577af49dfc360587a4e45195a6a26b75eab083 Mon Sep 17 00:00:00 2001
From: Rik Huijzer <github at huijzer.xyz>
Date: Sat, 2 Dec 2023 18:06:05 +0100
Subject: [PATCH 5/5] Cleanup
---
mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp | 1 -
mlir/test/Dialect/Tensor/canonicalize.mlir | 24 ----------------------
2 files changed, 25 deletions(-)
diff --git a/mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp b/mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp
index c6d947a2427db..b2d52e400e52d 100644
--- a/mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp
+++ b/mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp
@@ -22,7 +22,6 @@
#include "mlir/Interfaces/ViewLikeInterface.h"
#include "llvm/ADT/STLExtras.h"
#include "llvm/ADT/SmallBitVector.h"
-#include <cstdint>
using namespace mlir;
using namespace mlir::memref;
diff --git a/mlir/test/Dialect/Tensor/canonicalize.mlir b/mlir/test/Dialect/Tensor/canonicalize.mlir
index 77978e0896a28..84c44a09aa3dd 100644
--- a/mlir/test/Dialect/Tensor/canonicalize.mlir
+++ b/mlir/test/Dialect/Tensor/canonicalize.mlir
@@ -1179,30 +1179,6 @@ func.func @no_fold_collapse_of_expand_empty_expr(%arg0: tensor<3x2x2xf32>)
// -----
-func.func @no_fold_extract_slice_negative_offset(%arg0: tensor<8xf32>) -> tensor<?xf32> {
- %c-1 = arith.constant -1 : index
- %e = tensor.extract_slice %arg0[1] [%c-1] [1] : tensor<8xf32> to tensor<?xf32>
- return %e : tensor<?xf32>
-}
-// CHECK-LABEL: func @no_fold_extract_slice_negative_offset
-// CHECK: tensor.extract_slice
-
-// -----
-
-func.func @no_fold_insert_slice_cast_inserter_negative_offset() -> tensor<?xf32> {
- %c = arith.constant 0 : index
- %const = tensor.empty(%c) : tensor<?xf32>
- %insert_val = tensor.empty(%c) : tensor<?xf32>
- %c-1 = arith.constant -1 : index
- %inserted = tensor.insert_slice %insert_val into %const[0][%c-1][1] : tensor<?xf32> into tensor<?xf32>
- return %inserted : tensor<?xf32>
-}
-// CHECK-LABEL: func @no_fold_insert_slice_cast_inserter_negative_offset
-// CHECK: %[[CAST:.*]] = tensor.cast
-// CHECK: tensor.insert_slice %[[CAST:.+]]
-
-// -----
-
func.func @reshape_splat_constant_int32() -> tensor<2x4x2xi32> {
%c0 = arith.constant dense<42> : tensor<2x8xi32>
%0 = tensor.expand_shape %c0 [[0], [1, 2]]
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