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Differential D123035

[mlir][spirv] Check nullptr before usage to fix crash
ClosedPublic

Authored by antiagainst on Apr 4 2022, 8:25 AM.

Details

Reviewers
ThomasRaoux
mravishankar
hanchung
Commits
rGf1a7e508a5e4: [mlir][spirv] Check nullptr before usage to fix crash

Diff Detail

Event Timeline

antiagainst created this revision.Apr 4 2022, 8:25 AM
Herald added a reviewer: mravishankar. · View Herald TranscriptApr 4 2022, 8:25 AM
Herald added a project: Restricted Project. · View Herald Transcript
Herald added subscribers: sdasgup3, wenzhicui, wrengr and 19 others. · View Herald Transcript
antiagainst requested review of this revision.Apr 4 2022, 8:25 AM
Herald added a project: Restricted Project. · View Herald TranscriptApr 4 2022, 8:25 AM
Herald added subscribers: stephenneuendorffer, nicolasvasilache. · View Herald Transcript
antiagainst added a reviewer: hanchung.Apr 4 2022, 8:27 AM
Harbormaster completed remote builds in B157738: Diff 420192.Apr 4 2022, 8:42 AM
mravishankar accepted this revision.Apr 4 2022, 10:42 AM
This revision is now accepted and ready to land.Apr 4 2022, 10:42 AM
hanchung accepted this revision.Apr 4 2022, 12:13 PM
Closed by commit rGf1a7e508a5e4: [mlir][spirv] Check nullptr before usage to fix crash (authored by antiagainst). · Explain WhyApr 4 2022, 2:20 PM
This revision was automatically updated to reflect the committed changes.
antiagainst added a commit: rGf1a7e508a5e4: [mlir][spirv] Check nullptr before usage to fix crash.

Revision Contents

PathSize
mlir/
lib/
Conversion/
ArithmeticToSPIRV/
3 lines

Diff 420192

mlir/lib/Conversion/ArithmeticToSPIRV/ArithmeticToSPIRV.cpp

Show First 20 Lines • Show All 288 Lines • ▼ Show 20 LinesLogicalResult ConstantCompositeOpPattern::matchAndRewrite(
// arith.constant should only have vector or tenor types. // arith.constant should only have vector or tenor types.
assert((srcType.isa<VectorType, RankedTensorType>())); assert((srcType.isa<VectorType, RankedTensorType>()));
auto dstType = getTypeConverter()->convertType(srcType); auto dstType = getTypeConverter()->convertType(srcType);
if (!dstType) if (!dstType)
return failure(); return failure();
auto dstElementsAttr = constOp.getValue().dyn_cast<DenseElementsAttr>(); auto dstElementsAttr = constOp.getValue().dyn_cast<DenseElementsAttr>();
ShapedType dstAttrType = dstElementsAttr.getType();
if (!dstElementsAttr) if (!dstElementsAttr)
return failure(); return failure();
ShapedType dstAttrType = dstElementsAttr.getType();
// If the composite type has more than one dimensions, perform linearization. // If the composite type has more than one dimensions, perform linearization.
if (srcType.getRank() > 1) { if (srcType.getRank() > 1) {
if (srcType.isa<RankedTensorType>()) { if (srcType.isa<RankedTensorType>()) {
dstAttrType = RankedTensorType::get(srcType.getNumElements(), dstAttrType = RankedTensorType::get(srcType.getNumElements(),
srcType.getElementType()); srcType.getElementType());
dstElementsAttr = dstElementsAttr.reshape(dstAttrType); dstElementsAttr = dstElementsAttr.reshape(dstAttrType);
} else { } else {
// TODO: add support for large vectors. // TODO: add support for large vectors.
▲ Show 20 Lines • Show All 585 Lines • Show Last 20 Lines