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Update LLVM Tag to 2c1fa734 (#1670) 

Summary of changes:
 - Change ShapedType::kDynamicSize -> ShapedType::kDynamic
 - llvm::NoneType has been deprecated, change convertScalarToDtype to use llvm::None
pull/1672/head
Eric Kunze 2022-12-01 20:38:28 -08:00 committed by GitHub
parent 88db99946b
commit 3fc27cf6ca
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GPG Key ID: 4AEE18F83AFDEB23
8 changed files with 27 additions and 27 deletions
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10
externals/llvm-external-projects/torch-mlir-dialects/lib/Dialect/TMTensor/IR/TMTensorOps.cpp vendored
View File

@ -120,8 +120,8 @@ LogicalResult ScanOp::verify() {
}
if (llvm::any_of(llvm::zip(expectedAccumulatorShape, accumulatorShape),
[](std::tuple<int64_t, int64_t> s) {
return std::get<0>(s) != ShapedType::kDynamicSize &&
std::get<1>(s) != ShapedType::kDynamicSize &&
return std::get<0>(s) != ShapedType::kDynamic &&
std::get<1>(s) != ShapedType::kDynamic &&
std::get<0>(s) != std::get<1>(s);
})) {
return emitOpError("incompatible input/accumulator shapes");
@ -134,8 +134,8 @@ LogicalResult ScanOp::verify() {
}
if (llvm::any_of(llvm::zip(inputShapes, outputShapes),
[](std::tuple<int64_t, int64_t> s) {
return std::get<0>(s) != ShapedType::kDynamicSize &&
std::get<1>(s) != ShapedType::kDynamicSize &&
return std::get<0>(s) != ShapedType::kDynamic &&
std::get<1>(s) != ShapedType::kDynamic &&
std::get<0>(s) != std::get<1>(s);
})) {
return emitOpError("incompatible input/output shapes");
@ -291,7 +291,7 @@ LogicalResult ScatterOp::verify() {
return emitOpError("expected indices to be of rank 2 of i32 element type");
}
auto indexDepth = getIndexDepth();
if (indexDepth == ShapedType::kDynamicSize) {
if (indexDepth == ShapedType::kDynamic) {
return emitOpError("expected index depth is static");
}

2
externals/llvm-project vendored

@ -1 +1 @@
Subproject commit 147fe9de29dc13c14835127b35280c4d95c8e8ba
Subproject commit 2c1fa734598c9470139720565fbf624a5156ec03

2
externals/mlir-hlo vendored

@ -1 +1 @@
Subproject commit 1944b5fa6062ec4c065d726c9c5d64f1487ee8c5
Subproject commit dabc58a95b8bcd1140ffb0062730b81745d41724

2
include/torch-mlir/Conversion/Utils/Utils.h
View File

@ -84,7 +84,7 @@ SmallVector<Value> getTypeConvertedValues(OpBuilder &b, Location loc,
// should be converted builtin types.
Value convertScalarToDtype(
OpBuilder &b, Location loc, Value scalar, Type dtype,
llvm::Optional<Type> srcOriginalDtype = llvm::NoneType());
llvm::Optional<Type> srcOriginalDtype = llvm::None);
// Return the number of elements of a tensor if the shape is static; otherwise,
// return -1.

14
lib/Conversion/TorchToMhlo/Linear.cpp
View File

@ -88,12 +88,12 @@ RankedTensorType castContractingDim(PatternRewriter &rewriter, Operation *op,
auto lhsContractingDimSize = lhsShape[lhsContractingDim];
auto rhsContractingDimSize = rhsShape[rhsContractingDim];
if (lhsContractingDimSize != rhsContractingDimSize) {
if (lhsContractingDimSize == ShapedType::kDynamicSize &&
if (lhsContractingDimSize == ShapedType::kDynamic &&
rhsContractingDimSize >= 0) {
lhsShape[lhsContractingDim] = rhsContractingDimSize;
auto newRankTy = RankedTensorType::get(lhsShape, lhsTy.getElementType());
lhs = rewriter.create<tensor::CastOp>(op->getLoc(), newRankTy, lhs);
} else if (rhsContractingDimSize == ShapedType::kDynamicSize &&
} else if (rhsContractingDimSize == ShapedType::kDynamic &&
lhsContractingDimSize >= 0) {
rhsShape[rhsContractingDim] = lhsContractingDimSize;
auto newRankTy = RankedTensorType::get(rhsShape, rhsTy.getElementType());
@ -112,7 +112,7 @@ RankedTensorType castContractingDim(PatternRewriter &rewriter, Operation *op,
break;
if (k == rhsResultDim || k == rhsContractingDim)
continue;
if (outShape[b] == ShapedType::kDynamicSize && rhsShape[k] >= 0) {
if (outShape[b] == ShapedType::kDynamic && rhsShape[k] >= 0) {
outShape[b] = rhsShape[k];
}
b++;
@ -477,7 +477,7 @@ public:
weightShapeVec[0] = ICDivGValue;
weightShapeVec.insert(weightShapeVec.begin(), GValue);
if (weightShapeInt[0] == ShapedType::kDynamicSize) {
if (weightShapeInt[0] == ShapedType::kDynamic) {
weightShapeInt.insert(weightShapeInt.begin(), groups);
} else {
weightShapeInt[0] /= groups;
@ -499,7 +499,7 @@ public:
// 3. [IC//G, G, OC, H, W, ...] => [IC//G, G*OC, H, W, ...]
weightShapeInt.erase(weightShapeInt.begin());
if (weightShapeInt[1] != ShapedType::kDynamicSize) {
if (weightShapeInt[1] != ShapedType::kDynamic) {
weightShapeInt[1] *= groups;
}
weightShapeVec.erase(weightShapeVec.begin());
@ -533,7 +533,7 @@ public:
auto finalOutShape = outType.getShape();
std::copy(finalOutShape.begin(), finalOutShape.end(), outShape.begin());
for (int i = 2; i < nDims; ++i) {
if (finalOutShape[i] == ShapedType::kDynamicSize)
if (finalOutShape[i] == ShapedType::kDynamic)
continue;
outShape[i] = finalOutShape[i] - outputPadding[i - 2];
}
@ -745,7 +745,7 @@ public:
// Kernel size must be constant.
auto weightShape = weightTy.getShape();
for (int i = 2; i < nDims; ++i) {
if (weightShape[i] == ShapedType::kDynamicSize) {
if (weightShape[i] == ShapedType::kDynamic) {
return rewriter.notifyMatchFailure(
op, "only constant kernel size is supported");
}

6
lib/Conversion/TorchToMhlo/Pooling.cpp
View File

@ -279,9 +279,9 @@ LogicalResult ConvertAtenOp<AtenMaxPool2dWithIndicesOp>::matchAndRewrite(
SmallVector<int64_t> initIndexShapeForType(inputShape.begin(),
inputShape.end() - 2);
if (inputShape[inputRank - 1] == ShapedType::kDynamicSize ||
inputShape[inputRank - 2] == ShapedType::kDynamicSize) {
initIndexShapeForType.push_back(ShapedType::kDynamicSize);
if (inputShape[inputRank - 1] == ShapedType::kDynamic ||
inputShape[inputRank - 2] == ShapedType::kDynamic) {
initIndexShapeForType.push_back(ShapedType::kDynamic);
} else {
initIndexShapeForType.push_back(inputShape[inputRank - 1] *
inputShape[inputRank - 2]);

4
lib/Conversion/TorchToMhlo/ViewLike.cpp
View File

@ -308,7 +308,7 @@ LogicalResult ConvertAtenOp<AtenSqueezeOp>::matchAndRewrite(
dims.reserve(rank);
for (int r = 0; r < rank; ++r) {
auto dSize = selfTy.getShape()[r];
if (dSize == ShapedType::kDynamicSize)
if (dSize == ShapedType::kDynamic)
return rewriter.notifyMatchFailure(
op, "the size of the dimension being squeezed can't be unknown");
if (dSize != 1)
@ -353,7 +353,7 @@ LogicalResult ConvertAtenOp<AtenSqueezeDimOp>::matchAndRewrite(
dim = toPositiveDim(dim, rank);
if (selfTy.getShape()[dim] != 1) {
if (selfTy.getShape()[dim] == ShapedType::kDynamicSize)
if (selfTy.getShape()[dim] == ShapedType::kDynamic)
return rewriter.notifyMatchFailure(
op, "the size of the dimension being squeezed is can't be unknown");

10
lib/Conversion/Utils/Utils.cpp
View File

@ -331,21 +331,21 @@ int64_t getNumberOfElements(RankedTensorType inputType) {
SmallVector<int64_t> makeShapeLLVMCompatible(ArrayRef<int64_t> shape) {
SmallVector<int64_t> updatedShape(shape);
int64_t kDynamicSize = ShapedType::kDynamicSize;
int64_t kDynamic = ShapedType::kDynamic;
for (unsigned i = 0; i < shape.size(); i++) {
assert(shape[i] >= 0 || shape[i] == kUnknownSize);
if (shape[i] == kUnknownSize)
updatedShape[i] = kDynamicSize;
updatedShape[i] = kDynamic;
}
return updatedShape;
}
SmallVector<int64_t> makeShapeTorchCompatible(ArrayRef<int64_t> shape) {
SmallVector<int64_t> updatedShape(shape);
int64_t kDynamicSize = ShapedType::kDynamicSize;
int64_t kDynamic = ShapedType::kDynamic;
for (unsigned i = 0; i < shape.size(); i++) {
assert(shape[i] >= 0 || shape[i] == kDynamicSize);
if (shape[i] == kDynamicSize)
assert(shape[i] >= 0 || shape[i] == kDynamic);
if (shape[i] == kDynamic)
updatedShape[i] = kUnknownSize;
}
return updatedShape;