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[mlir] [memref] add more checks to the memref.reinterpret_cast #112669

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Merged
merged 4 commits into from
Oct 26, 2024
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[mlir] [memref] add more checks to the memref.reinterpret_cast #112669

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831847d
[mlir] [memref] add more checks to the memref.reinterpret_cast
cxy-1993 Oct 17, 2024
fe54602
enable dynamic in result type + static in operand
cxy-1993 Oct 17, 2024
1423741
fix other conversion and tests
cxy-1993 Oct 22, 2024
a62f73f
fix error message
cxy-1993 Oct 23, 2024
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13 changes: 12 additions & 1 deletion mlir/lib/Dialect/GPU/Transforms/DecomposeMemRefs.cpp
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Expand Up @@ -29,6 +29,17 @@ namespace mlir {

using namespace mlir;

static MemRefType inferCastResultType(Value source, OpFoldResult offset) {
auto sourceType = cast<BaseMemRefType>(source.getType());
SmallVector<int64_t> staticOffsets;
SmallVector<Value> dynamicOffsets;
dispatchIndexOpFoldResults(offset, dynamicOffsets, staticOffsets);
auto stridedLayout =
StridedLayoutAttr::get(source.getContext(), staticOffsets.front(), {});
return MemRefType::get({}, sourceType.getElementType(), stridedLayout,
sourceType.getMemorySpace());
}

static void setInsertionPointToStart(OpBuilder &builder, Value val) {
if (auto *parentOp = val.getDefiningOp()) {
builder.setInsertionPointAfter(parentOp);
Expand Down Expand Up @@ -98,7 +109,7 @@ static Value getFlatMemref(OpBuilder &rewriter, Location loc, Value source,
SmallVector<OpFoldResult> offsetsTemp = getAsOpFoldResult(offsets);
auto &&[base, offset, ignore] =
getFlatOffsetAndStrides(rewriter, loc, source, offsetsTemp);
auto retType = cast<MemRefType>(base.getType());
MemRefType retType = inferCastResultType(base, offset);
return rewriter.create<memref::ReinterpretCastOp>(loc, retType, base, offset,
std::nullopt, std::nullopt);
}
Expand Down
27 changes: 15 additions & 12 deletions mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp
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Expand Up @@ -1892,11 +1892,12 @@ LogicalResult ReinterpretCastOp::verify() {
// Match sizes in result memref type and in static_sizes attribute.
for (auto [idx, resultSize, expectedSize] :
llvm::enumerate(resultType.getShape(), getStaticSizes())) {
if (!ShapedType::isDynamic(resultSize) &&
!ShapedType::isDynamic(expectedSize) && resultSize != expectedSize)
if (!ShapedType::isDynamic(resultSize) && resultSize != expectedSize)
return emitError("expected result type with size = ")
<< expectedSize << " instead of " << resultSize
<< " in dim = " << idx;
<< (ShapedType::isDynamic(expectedSize)
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If I am reading the logic correctly, this check is not needed (here and everywhere below.)

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Thank you for your review. However, I believe these checks are necessary. As the PR description mentions, mismatches between return value data types and operands may lead to other transforms incorrectly obtaining values of the wrong data type, resulting in erroneous outcomes. This submission is specifically designed to address this issue.

? std::string("dynamic")
: std::to_string(expectedSize))
<< " instead of " << resultSize << " in dim = " << idx;
}

// Match offset and strides in static_offset and static_strides attributes. If
Expand All @@ -1910,20 +1911,22 @@ LogicalResult ReinterpretCastOp::verify() {

// Match offset in result memref type and in static_offsets attribute.
int64_t expectedOffset = getStaticOffsets().front();
if (!ShapedType::isDynamic(resultOffset) &&
!ShapedType::isDynamic(expectedOffset) && resultOffset != expectedOffset)
if (!ShapedType::isDynamic(resultOffset) && resultOffset != expectedOffset)
return emitError("expected result type with offset = ")
<< expectedOffset << " instead of " << resultOffset;
<< (ShapedType::isDynamic(expectedOffset)
? std::string("dynamic")
: std::to_string(expectedOffset))
<< " instead of " << resultOffset;

// Match strides in result memref type and in static_strides attribute.
for (auto [idx, resultStride, expectedStride] :
llvm::enumerate(resultStrides, getStaticStrides())) {
if (!ShapedType::isDynamic(resultStride) &&
!ShapedType::isDynamic(expectedStride) &&
resultStride != expectedStride)
if (!ShapedType::isDynamic(resultStride) && resultStride != expectedStride)
return emitError("expected result type with stride = ")
<< expectedStride << " instead of " << resultStride
<< " in dim = " << idx;
<< (ShapedType::isDynamic(expectedStride)
? std::string("dynamic")
: std::to_string(expectedStride))
<< " instead of " << resultStride << " in dim = " << idx;
}

return success();
Expand Down
22 changes: 18 additions & 4 deletions mlir/lib/Dialect/MemRef/Transforms/ExpandOps.cpp
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Expand Up @@ -89,7 +89,8 @@ struct MemRefReshapeOpConverter : public OpRewritePattern<memref::ReshapeOp> {
strides.resize(rank);

Location loc = op.getLoc();
Value stride = rewriter.create<arith::ConstantIndexOp>(loc, 1);
Value stride = nullptr;
int64_t staticStride = 1;
for (int i = rank - 1; i >= 0; --i) {
Value size;
// Load dynamic sizes from the shape input, use constants for static dims.
Expand All @@ -105,9 +106,22 @@ struct MemRefReshapeOpConverter : public OpRewritePattern<memref::ReshapeOp> {
size = rewriter.create<arith::ConstantOp>(loc, sizeAttr);
sizes[i] = sizeAttr;
}
strides[i] = stride;
if (i > 0)
stride = rewriter.create<arith::MulIOp>(loc, stride, size);
if (stride)
strides[i] = stride;
else
strides[i] = rewriter.getIndexAttr(staticStride);

if (i > 0) {
if (stride) {
stride = rewriter.create<arith::MulIOp>(loc, stride, size);
} else if (op.getType().isDynamicDim(i)) {
stride = rewriter.create<arith::MulIOp>(
loc, rewriter.create<arith::ConstantIndexOp>(loc, staticStride),
size);
} else {
staticStride *= op.getType().getDimSize(i);
}
}
}
rewriter.replaceOpWithNewOp<memref::ReinterpretCastOp>(
op, op.getType(), op.getSource(), /*offset=*/rewriter.getIndexAttr(0),
Expand Down
17 changes: 7 additions & 10 deletions mlir/lib/Dialect/MemRef/Transforms/ExpandStridedMetadata.cpp
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Expand Up @@ -507,6 +507,8 @@ getCollapsedStride(memref::CollapseShapeOp collapseShape, OpBuilder &builder,

SmallVector<OpFoldResult> groupStrides;
ArrayRef<int64_t> srcShape = sourceType.getShape();

OpFoldResult lastValidStride = nullptr;
for (int64_t currentDim : reassocGroup) {
// Skip size-of-1 dimensions, since right now their strides may be
// meaningless.
Expand All @@ -517,11 +519,11 @@ getCollapsedStride(memref::CollapseShapeOp collapseShape, OpBuilder &builder,
continue;

int64_t currentStride = strides[currentDim];
groupStrides.push_back(ShapedType::isDynamic(currentStride)
? origStrides[currentDim]
: builder.getIndexAttr(currentStride));
lastValidStride = ShapedType::isDynamic(currentStride)
? origStrides[currentDim]
: builder.getIndexAttr(currentStride);
}
if (groupStrides.empty()) {
if (!lastValidStride) {
// We're dealing with a 1x1x...x1 shape. The stride is meaningless,
// but we still have to make the type system happy.
MemRefType collapsedType = collapseShape.getResultType();
Expand All @@ -543,12 +545,7 @@ getCollapsedStride(memref::CollapseShapeOp collapseShape, OpBuilder &builder,
return {builder.getIndexAttr(finalStride)};
}

// For the general case, we just want the minimum stride
// since the collapsed dimensions are contiguous.
auto minMap = AffineMap::getMultiDimIdentityMap(groupStrides.size(),
builder.getContext());
return {makeComposedFoldedAffineMin(builder, collapseShape.getLoc(), minMap,
groupStrides)};
return {lastValidStride};
}

/// From `reshape_like(memref, subSizes, subStrides))` compute
Expand Down
10 changes: 2 additions & 8 deletions mlir/test/Conversion/MemRefToLLVM/expand-then-convert-to-llvm.mlir
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Expand Up @@ -425,8 +425,6 @@ func.func @collapse_shape_dynamic_with_non_identity_layout(
// CHECK: %[[SIZE1:.*]] = llvm.extractvalue %[[MEM]][3, 1] : !llvm.struct<(ptr, ptr, i64, array<3 x i64>, array<3 x i64>)>
// CHECK: %[[SIZE2:.*]] = llvm.extractvalue %[[MEM]][3, 2] : !llvm.struct<(ptr, ptr, i64, array<3 x i64>, array<3 x i64>)>
// CHECK: %[[STRIDE0:.*]] = llvm.extractvalue %[[MEM]][4, 0] : !llvm.struct<(ptr, ptr, i64, array<3 x i64>, array<3 x i64>)>
// CHECK: %[[STRIDE0_TO_IDX:.*]] = builtin.unrealized_conversion_cast %[[STRIDE0]] : i64 to index
// CHECK: %[[STRIDE0:.*]] = builtin.unrealized_conversion_cast %[[STRIDE0_TO_IDX]] : index to i64
// CHECK: %[[FINAL_SIZE1:.*]] = llvm.mul %[[SIZE1]], %[[SIZE2]] : i64
// CHECK: %[[SIZE1_TO_IDX:.*]] = builtin.unrealized_conversion_cast %[[FINAL_SIZE1]] : i64 to index
// CHECK: %[[FINAL_SIZE1:.*]] = builtin.unrealized_conversion_cast %[[SIZE1_TO_IDX]] : index to i64
Expand Down Expand Up @@ -548,23 +546,19 @@ func.func @collapse_shape_dynamic(%arg0 : memref<1x2x?xf32>) -> memref<1x?xf32>
// CHECK: %[[C0:.*]] = llvm.mlir.constant(0 : index) : i64
// CHECK: %[[SIZE2:.*]] = llvm.extractvalue %[[MEM]][3, 2] : !llvm.struct<(ptr, ptr, i64, array<3 x i64>, array<3 x i64>)>
// CHECK: %[[STRIDE0:.*]] = llvm.extractvalue %[[MEM]][4, 0] : !llvm.struct<(ptr, ptr, i64, array<3 x i64>, array<3 x i64>)>
// CHECK: %[[STRIDE1:.*]] = llvm.extractvalue %[[MEM]][4, 1] : !llvm.struct<(ptr, ptr, i64, array<3 x i64>, array<3 x i64>)>
// CHECK: %[[C2:.*]] = llvm.mlir.constant(2 : index) : i64
// CHECK: %[[FINAL_SIZE1:.*]] = llvm.mul %[[SIZE2]], %[[C2]] : i64
// CHECK: %[[SIZE1_TO_IDX:.*]] = builtin.unrealized_conversion_cast %[[FINAL_SIZE1]] : i64 to index
// CHECK: %[[FINAL_SIZE1:.*]] = builtin.unrealized_conversion_cast %[[SIZE1_TO_IDX]] : index to i64
// CHECK: %[[C1:.*]] = llvm.mlir.constant(1 : index) : i64
// CHECK: %[[MIN_STRIDE1:.*]] = llvm.intr.smin(%[[STRIDE1]], %[[C1]]) : (i64, i64) -> i64
// CHECK: %[[MIN_STRIDE1_TO_IDX:.*]] = builtin.unrealized_conversion_cast %[[MIN_STRIDE1]] : i64 to index
// CHECK: %[[MIN_STRIDE1:.*]] = builtin.unrealized_conversion_cast %[[MIN_STRIDE1_TO_IDX]] : index to i64
// CHECK: %[[DESC:.*]] = llvm.mlir.undef : !llvm.struct<(ptr, ptr, i64, array<2 x i64>, array<2 x i64>)>
// CHECK: %[[DESC0:.*]] = llvm.insertvalue %[[BASE_BUFFER]], %[[DESC]][0] : !llvm.struct<(ptr, ptr, i64, array<2 x i64>, array<2 x i64>)>
// CHECK: %[[DESC1:.*]] = llvm.insertvalue %[[ALIGNED_BUFFER]], %[[DESC0]][1] : !llvm.struct<(ptr, ptr, i64, array<2 x i64>, array<2 x i64>)>
// CHECK: %[[DESC2:.*]] = llvm.insertvalue %[[C0]], %[[DESC1]][2] : !llvm.struct<(ptr, ptr, i64, array<2 x i64>, array<2 x i64>)>
// CHECK: %[[C1:.*]] = llvm.mlir.constant(1 : index) : i64
// CHECK: %[[DESC3:.*]] = llvm.insertvalue %[[C1]], %[[DESC2]][3, 0] : !llvm.struct<(ptr, ptr, i64, array<2 x i64>, array<2 x i64>)>
// CHECK: %[[DESC4:.*]] = llvm.insertvalue %[[STRIDE0]], %[[DESC3]][4, 0] : !llvm.struct<(ptr, ptr, i64, array<2 x i64>, array<2 x i64>)>
// CHECK: %[[DESC5:.*]] = llvm.insertvalue %[[FINAL_SIZE1]], %[[DESC4]][3, 1] : !llvm.struct<(ptr, ptr, i64, array<2 x i64>, array<2 x i64>)>
// CHECK: %[[DESC6:.*]] = llvm.insertvalue %[[MIN_STRIDE1]], %[[DESC5]][4, 1] : !llvm.struct<(ptr, ptr, i64, array<2 x i64>, array<2 x i64>)>
// CHECK: %[[DESC6:.*]] = llvm.insertvalue %[[C1]], %[[DESC5]][4, 1] : !llvm.struct<(ptr, ptr, i64, array<2 x i64>, array<2 x i64>)>
// CHECK: %[[RES:.*]] = builtin.unrealized_conversion_cast %[[DESC6]] : !llvm.struct<(ptr, ptr, i64, array<2 x i64>, array<2 x i64>)> to memref<1x?xf32>
// CHECK: return %[[RES]] : memref<1x?xf32>
// CHECK: }
Expand Down
12 changes: 6 additions & 6 deletions mlir/test/Dialect/GPU/decompose-memrefs.mlir
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Expand Up @@ -7,8 +7,8 @@
// CHECK: gpu.launch
// CHECK-SAME: threads(%[[TX:.*]], %[[TY:.*]], %[[TZ:.*]]) in
// CHECK: %[[IDX:.*]] = affine.apply #[[MAP]]()[%[[TX]], %[[STRIDES]]#0, %[[TY]], %[[STRIDES]]#1, %[[TZ]]]
// CHECK: %[[PTR:.*]] = memref.reinterpret_cast %[[BASE]] to offset: [%[[IDX]]], sizes: [], strides: [] : memref<f32> to memref<f32>
// CHECK: memref.store %[[VAL]], %[[PTR]][] : memref<f32>
// CHECK: %[[PTR:.*]] = memref.reinterpret_cast %[[BASE]] to offset: [%[[IDX]]], sizes: [], strides: [] : memref<f32> to memref<f32, strided<[], offset: ?>>
// CHECK: memref.store %[[VAL]], %[[PTR]][] : memref<f32, strided<[], offset: ?>>
func.func @decompose_store(%arg0 : f32, %arg1 : memref<?x?x?xf32>) {
%c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index
Expand All @@ -33,8 +33,8 @@ func.func @decompose_store(%arg0 : f32, %arg1 : memref<?x?x?xf32>) {
// CHECK: gpu.launch
// CHECK-SAME: threads(%[[TX:.*]], %[[TY:.*]], %[[TZ:.*]]) in
// CHECK: %[[IDX:.*]] = affine.apply #[[MAP]]()[%[[OFFSET]], %[[TX]], %[[STRIDES]]#0, %[[TY]], %[[STRIDES]]#1, %[[TZ]], %[[STRIDES]]#2]
// CHECK: %[[PTR:.*]] = memref.reinterpret_cast %[[BASE]] to offset: [%[[IDX]]], sizes: [], strides: [] : memref<f32> to memref<f32>
// CHECK: memref.store %[[VAL]], %[[PTR]][] : memref<f32>
// CHECK: %[[PTR:.*]] = memref.reinterpret_cast %[[BASE]] to offset: [%[[IDX]]], sizes: [], strides: [] : memref<f32> to memref<f32, strided<[], offset: ?>>
// CHECK: memref.store %[[VAL]], %[[PTR]][] : memref<f32, strided<[], offset: ?>>
func.func @decompose_store_strided(%arg0 : f32, %arg1 : memref<?x?x?xf32, strided<[?, ?, ?], offset: ?>>) {
%c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index
Expand All @@ -59,8 +59,8 @@ func.func @decompose_store_strided(%arg0 : f32, %arg1 : memref<?x?x?xf32, stride
// CHECK: gpu.launch
// CHECK-SAME: threads(%[[TX:.*]], %[[TY:.*]], %[[TZ:.*]]) in
// CHECK: %[[IDX:.*]] = affine.apply #[[MAP]]()[%[[TX]], %[[STRIDES]]#0, %[[TY]], %[[STRIDES]]#1, %[[TZ]]]
// CHECK: %[[PTR:.*]] = memref.reinterpret_cast %[[BASE]] to offset: [%[[IDX]]], sizes: [], strides: [] : memref<f32> to memref<f32>
// CHECK: %[[RES:.*]] = memref.load %[[PTR]][] : memref<f32>
// CHECK: %[[PTR:.*]] = memref.reinterpret_cast %[[BASE]] to offset: [%[[IDX]]], sizes: [], strides: [] : memref<f32> to memref<f32, strided<[], offset: ?>>
// CHECK: %[[RES:.*]] = memref.load %[[PTR]][] : memref<f32, strided<[], offset: ?>>
// CHECK: "test.test"(%[[RES]]) : (f32) -> ()
func.func @decompose_load(%arg0 : memref<?x?x?xf32>) {
%c0 = arith.constant 0 : index
Expand Down
13 changes: 6 additions & 7 deletions mlir/test/Dialect/MemRef/expand-ops.mlir
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Expand Up @@ -52,20 +52,19 @@ func.func @memref_reshape(%input: memref<*xf32>,
// CHECK-SAME: [[SRC:%.*]]: memref<*xf32>,
// CHECK-SAME: [[SHAPE:%.*]]: memref<3xi32>) -> memref<?x?x8xf32> {

// CHECK: [[C1:%.*]] = arith.constant 1 : index
// CHECK: [[C8:%.*]] = arith.constant 8 : index
// CHECK: [[STRIDE_1:%.*]] = arith.muli [[C1]], [[C8]] : index

// CHECK: [[C1_:%.*]] = arith.constant 1 : index
// CHECK: [[DIM_1:%.*]] = memref.load [[SHAPE]]{{\[}}[[C1_]]] : memref<3xi32>
// CHECK: [[C1:%.*]] = arith.constant 1 : index
// CHECK: [[DIM_1:%.*]] = memref.load [[SHAPE]]{{\[}}[[C1]]] : memref<3xi32>
// CHECK: [[SIZE_1:%.*]] = arith.index_cast [[DIM_1]] : i32 to index
// CHECK: [[STRIDE_0:%.*]] = arith.muli [[STRIDE_1]], [[SIZE_1]] : index

// CHECK: [[C8_:%.*]] = arith.constant 8 : index
// CHECK: [[STRIDE_0:%.*]] = arith.muli [[C8_]], [[SIZE_1]] : index

// CHECK: [[C0:%.*]] = arith.constant 0 : index
// CHECK: [[DIM_0:%.*]] = memref.load [[SHAPE]]{{\[}}[[C0]]] : memref<3xi32>
// CHECK: [[SIZE_0:%.*]] = arith.index_cast [[DIM_0]] : i32 to index

// CHECK: [[RESULT:%.*]] = memref.reinterpret_cast [[SRC]]
// CHECK-SAME: to offset: [0], sizes: {{\[}}[[SIZE_0]], [[SIZE_1]], 8],
// CHECK-SAME: strides: {{\[}}[[STRIDE_0]], [[STRIDE_1]], [[C1]]]
// CHECK-SAME: strides: {{\[}}[[STRIDE_0]], 8, 1]
// CHECK-SAME: : memref<*xf32> to memref<?x?x8xf32>
21 changes: 6 additions & 15 deletions mlir/test/Dialect/MemRef/expand-strided-metadata.mlir
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Expand Up @@ -931,19 +931,15 @@ func.func @extract_aligned_pointer_as_index_of_unranked_source(%arg0: memref<*xf
// = min(7, 1)
// = 1
//
// CHECK-DAG: #[[$STRIDE0_MIN_MAP:.*]] = affine_map<()[s0] -> (s0)>
// CHECK-DAG: #[[$SIZE0_MAP:.*]] = affine_map<()[s0, s1] -> ((s0 * s1) * 4)>
// CHECK-DAG: #[[$STRIDE1_MIN_MAP:.*]] = affine_map<()[s0, s1] -> (s0, s1, 42)>
// CHECK: #[[$SIZE0_MAP:.*]] = affine_map<()[s0, s1] -> ((s0 * s1) * 4)>
// CHECK-LABEL: func @simplify_collapse(
// CHECK-SAME: %[[ARG:.*]]: memref<?x?x4x?x6x7xi32>)
//
// CHECK: %[[BASE:.*]], %[[OFFSET:.*]], %[[SIZES:.*]]:6, %[[STRIDES:.*]]:6 = memref.extract_strided_metadata %[[ARG]] : memref<?x?x4x?x6x7xi32>
//
// CHECK-DAG: %[[DYN_STRIDE0:.*]] = affine.min #[[$STRIDE0_MIN_MAP]]()[%[[STRIDES]]#0]
// CHECK-DAG: %[[DYN_SIZE1:.*]] = affine.apply #[[$SIZE0_MAP]]()[%[[SIZES]]#1, %[[SIZES]]#3]
// CHECK-DAG: %[[DYN_STRIDE1:.*]] = affine.min #[[$STRIDE1_MIN_MAP]]()[%[[STRIDES]]#1, %[[STRIDES]]#2]
// CHECK: %[[DYN_SIZE1:.*]] = affine.apply #[[$SIZE0_MAP]]()[%[[SIZES]]#1, %[[SIZES]]#3]
//
// CHECK: %[[COLLAPSE_VIEW:.*]] = memref.reinterpret_cast %[[BASE]] to offset: [0], sizes: [%[[SIZES]]#0, %[[DYN_SIZE1]], 42], strides: [%[[DYN_STRIDE0]], %[[DYN_STRIDE1]], 1]
// CHECK: %[[COLLAPSE_VIEW:.*]] = memref.reinterpret_cast %[[BASE]] to offset: [0], sizes: [%[[SIZES]]#0, %[[DYN_SIZE1]], 42], strides: [%[[STRIDES]]#0, 42, 1]
func.func @simplify_collapse(%arg : memref<?x?x4x?x6x7xi32>)
-> memref<?x?x42xi32> {

Expand Down Expand Up @@ -1046,15 +1042,12 @@ func.func @simplify_collapse_with_dim_of_size1_and_non_1_stride
// We just return the first dynamic one for this group.
//
//
// CHECK-DAG: #[[$STRIDE0_MIN_MAP:.*]] = affine_map<()[s0, s1] -> (s0, s1)>
// CHECK-LABEL: func @simplify_collapse_with_dim_of_size1_and_resulting_dyn_stride(
// CHECK-SAME: %[[ARG:.*]]: memref<2x3x1x1x1xi32, strided<[?, ?, ?, ?, 2]
//
// CHECK: %[[BASE:.*]], %[[OFFSET:.*]], %[[SIZES:.*]]:5, %[[STRIDES:.*]]:5 = memref.extract_strided_metadata %[[ARG]] : memref<2x3x1x1x1xi32, strided<[?, ?, ?, ?, 2], offset: ?>>
//
// CHECK-DAG: %[[DYN_STRIDE0:.*]] = affine.min #[[$STRIDE0_MIN_MAP]]()[%[[STRIDES]]#0, %[[STRIDES]]#1]
//
// CHECK: %[[COLLAPSE_VIEW:.*]] = memref.reinterpret_cast %[[BASE]] to offset: [%[[OFFSET]]], sizes: [6, 1], strides: [%[[DYN_STRIDE0]], %[[STRIDES]]#2]
// CHECK: %[[COLLAPSE_VIEW:.*]] = memref.reinterpret_cast %[[BASE]] to offset: [%[[OFFSET]]], sizes: [6, 1], strides: [%[[STRIDES]]#1, %[[STRIDES]]#2]
func.func @simplify_collapse_with_dim_of_size1_and_resulting_dyn_stride
(%arg0: memref<2x3x1x1x1xi32, strided<[?, ?, ?, ?, 2], offset: ?>>)
-> memref<6x1xi32, strided<[?, ?], offset: ?>> {
Expand Down Expand Up @@ -1083,8 +1076,7 @@ func.func @simplify_collapse_with_dim_of_size1_and_resulting_dyn_stride
// Stride 2 = origStride5
// = 1
//
// CHECK-DAG: #[[$SIZE0_MAP:.*]] = affine_map<()[s0, s1] -> ((s0 * s1) * 4)>
// CHECK-DAG: #[[$STRIDE0_MAP:.*]] = affine_map<()[s0] -> (s0)>
// CHECK: #[[$SIZE0_MAP:.*]] = affine_map<()[s0, s1] -> ((s0 * s1) * 4)>
// CHECK-LABEL: func @extract_strided_metadata_of_collapse(
// CHECK-SAME: %[[ARG:.*]]: memref<?x?x4x?x6x7xi32>)
//
Expand All @@ -1094,10 +1086,9 @@ func.func @simplify_collapse_with_dim_of_size1_and_resulting_dyn_stride
//
// CHECK-DAG: %[[BASE:.*]], %[[OFFSET:.*]], %[[SIZES:.*]]:6, %[[STRIDES:.*]]:6 = memref.extract_strided_metadata %[[ARG]] : memref<?x?x4x?x6x7xi32>
//
// CHECK-DAG: %[[DYN_STRIDE0:.*]] = affine.min #[[$STRIDE0_MAP]]()[%[[STRIDES]]#0]
// CHECK-DAG: %[[DYN_SIZE1:.*]] = affine.apply #[[$SIZE0_MAP]]()[%[[SIZES]]#1, %[[SIZES]]#3]
//
// CHECK: return %[[BASE]], %[[C0]], %[[SIZES]]#0, %[[DYN_SIZE1]], %[[C42]], %[[DYN_STRIDE0]], %[[C42]], %[[C1]]
// CHECK: return %[[BASE]], %[[C0]], %[[SIZES]]#0, %[[DYN_SIZE1]], %[[C42]], %[[STRIDES]]#0, %[[C42]], %[[C1]]
func.func @extract_strided_metadata_of_collapse(%arg : memref<?x?x4x?x6x7xi32>)
-> (memref<i32>, index,
index, index, index,
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9 changes: 9 additions & 0 deletions mlir/test/Dialect/MemRef/invalid.mlir
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Expand Up @@ -217,6 +217,15 @@ func.func @memref_reinterpret_cast_no_map_but_offset(%in: memref<?xf32>) {

// -----

func.func @memref_reinterpret_cast_offset_mismatch_dynamic(%in: memref<?xf32>, %offset : index) {
// expected-error @+1 {{expected result type with offset = dynamic instead of 0}}
%out = memref.reinterpret_cast %in to offset: [%offset], sizes: [10], strides: [1]
: memref<?xf32> to memref<10xf32>
return
}

// -----

func.func @memref_reinterpret_cast_no_map_but_stride(%in: memref<?xf32>) {
// expected-error @+1 {{expected result type with stride = 10 instead of 1 in dim = 0}}
%out = memref.reinterpret_cast %in to offset: [0], sizes: [10], strides: [10]
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