8000 Advance llvm-project and stablehlo. by stellaraccident · Pull Request #2619 · llvm/torch-mlir · GitHub
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Advance llvm-project and stablehlo. #2619

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Merged
merged 13 commits into from
Dec 8, 2023
Merged

Advance llvm-project and stablehlo. #2619

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b1b05c6
Advance llvm-project and stablehlo.
stellaraccident Dec 8, 2023
d5c83e8
Adapt to attribute signature change in stablehlo.
stellaraccident Dec 8, 2023
740a3ee
Mark TOSA tests as passing that started working.
stellaraccident Dec 8, 2023
5b6535b
Try another tosa permutation.
stellaraccident Dec 8, 2023
f531192
Fix tosa dev version excludes.
stellaraccident Dec 8, 2023
7ef3ef9
Fix version number with failure.
stellaraccident Dec 8, 2023
1ef97a4
Add linalg xfails.
stellaraccident Dec 8, 2023
906846a
Fix version spec
stellaraccident Dec 8, 2023
7ae0538
Fix python syntax
stellaraccident Dec 8, 2023
fcf30bc
xfail on torchdynamo too
stellaraccident Dec 8, 2023
243f3b7
more wtf version stuff
stellaraccident Dec 8, 2023
d8e147c
how is this even working?
stellaraccident Dec 8, 2023
7a76824
revert yaml change
stellaraccident Dec 8, 2023
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2 changes: 1 addition & 1 deletion externals/llvm-project
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Submodule llvm-project updated 3620 files
2 changes: 1 addition & 1 deletion externals/stablehlo
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Submodule stablehlo updated 311 files
2 changes: 1 addition & 1 deletion include/torch-mlir/Conversion/TorchToStablehlo/StablehloLegalizeUtils.h
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Original file line number Diff line number Diff line change
Expand Up @@ -51,7 +51,7 @@ Value promoteType(PatternRewriter &rewriter, Location loc, Value input,
Value promoteAndBroadcast(ConversionPatternRewriter &rewriter, Value input,
TensorType outType);

SmallVector<size_t> toPositiveDims(ArrayRef<int64_t> dims, int64_t rank);
SmallVector<int64_t> toPositiveDims(ArrayRef<int64_t> dims, int64_t rank);

// Get the dimension sizes of the input tensor, given the dimension axes
FailureOr<SmallVector<Value, 4>> getDimSizesOfTensor(PatternRewriter &rewriter,
Expand Down
15 changes: 3 additions & 12 deletions lib/Conversion/TorchToStablehlo/Basic.cpp
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Expand Up @@ -615,12 +615,8 @@ class ConvertAtenTransposeIntOp
SmallVector<int64_t> permValues(inputRank);
std::iota(std::begin(permValues), std::end(permValues), 0);
std::swap(permValues[dim0], permValues[dim1]);
DenseIntElementsAttr permutation = DenseIntElementsAttr::get(
RankedTensorType::get({static_cast<long int>(permValues.size())},
rewriter.getI64Type()),
permValues);
rewriter.replaceOpWithNewOp<stablehlo::TransposeOp>(op, outType, self,
permutation);
permValues);
return success();
}
};
Expand Down Expand Up @@ -793,12 +789,8 @@ LogicalResult ConvertAtenOp<AtenPermuteOp>::matchAndRewrite(
return op.emitError("not all dims are valid");
}

DenseIntElementsAttr permutation = DenseIntElementsAttr::get(
RankedTensorType::get({static_cast<long int>(permValues.size())},
rewriter.getI64Type()),
permValues);
rewriter.replaceOpWithNewOp<stablehlo::TransposeOp>(op, outType, self,
permutation);
permValues);
return success();
}

Expand Down Expand Up @@ -1755,8 +1747,7 @@ LogicalResult ConvertAtenOp<AtenFlipOp>::matchAndRewrite(
}
}

rewriter.replaceOpWithNewOp<stablehlo::ReverseOp>(
op, outType, self, rewriter.getI64TensorAttr(dims));
rewriter.replaceOpWithNewOp<stablehlo::ReverseOp>(op, outType, self, dims);
return success();
}

Expand Down
16 changes: 5 additions & 11 deletions lib/Conversion/TorchToStablehlo/Linear.cpp
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Expand Up @@ -62,13 +62,9 @@ Value getPermutedTensor(PatternRewriter &rewriter, Operation *op, Value input,
newShape.push_back(inpShape[d]);
}

auto attrTy = RankedTensorType::get({static_cast<int64_t>(transDims.size())},
rewriter.getIntegerType(64));
auto permuteAttr = DenseIntElementsAttr::get(attrTy, transDims);

auto outTy = 10000 RankedTensorType::get(newShape, inputTy.getElementType());
auto result = rewriter.create<stablehlo::TransposeOp>(op->getLoc(), outTy,
input, permuteAttr);
input, transDims);
return result.getResult();
}

Expand Down Expand Up @@ -500,8 +496,8 @@ class ConvertAtenConvolutionOp : public ConvertAtenOp<AtenConvolutionOp> {
for (int64_t i = 0; i <= rank; i++)
transposeDims[i] = i;
std::swap(transposeDims[rank - 1], transposeDims[rank - 2]);
weight = rewriter.create<stablehlo::TransposeOp>(
op->getLoc(), weight, rewriter.getI64TensorAttr(transposeDims));
weight = rewriter.create<stablehlo::TransposeOp>(op->getLoc(), weight,
transposeDims);

// 3. [H, W, ..., G, OC, IC//G] => [H, W, ..., G*OC, IC//G]
weightShapeInt.erase(weightShapeInt.end() - 2);
Expand Down Expand Up @@ -546,12 +542,10 @@ class ConvertAtenConvolutionOp : public ConvertAtenOp<AtenConvolutionOp> {
}
auto transposeTy =
RankedTensorType::get(transposeShape, weightTy.getElementType());
DenseIntElementsAttr permAttr = DenseIntElementsAttr::get(
RankedTensorType::get({nDims}, rewriter.getI64Type()), perm);
auto transposeOp = rewriter.create<stablehlo::TransposeOp>(
op->getLoc(), transposeTy, weight, permAttr);
op->getLoc(), transposeTy, weight, perm);
auto reverseOp = rewriter.create<stablehlo::ReverseOp>(
op->getLoc(), transposeOp, rewriter.getI64TensorAttr({0, 1}));
op->getLoc(), transposeOp, ArrayRef<int64_t>{0, 1});

// Prepare for transposed convolution
SmallVector<int64_t> stablehloStrideVec(nSpatialDims, 1);
Expand Down
16 changes: 8 additions & 8 deletions lib/Conversion/TorchToStablehlo/StablehloLegalizeUtils.cpp
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6D4E
Original file line number Diff line number Diff line change
Expand Up @@ -250,12 +250,12 @@ Value promoteAndBroadcast(ConversionPatternRewriter &rewriter, Value input,
return bcast_op.getResult();
}

SmallVector<size_t> toPositiveDims(ArrayRef<int64_t> dims, int64_t rank) {
SmallVector<size_t> posDims;
SmallVector<int64_t> toPositiveDims(ArrayRef<int64_t> dims, int64_t rank) {
SmallVector<int64_t> posDims;
posDims.reserve(rank);
std::transform(
dims.begin(), dims.end(), std::back_inserter(posDims),
[rank](int64_t d) -> size_t { return toPositiveDim(d, rank); });
[rank](int64_t d) -> int64_t { return toPositiveDim(d, rank); });
return posDims;
}

Expand Down Expand Up @@ -316,10 +316,10 @@ FailureOr<Value> unsqueezeTensor(PatternRewriter &rewriter, Operation *op,
op, "failed to get dimension sizes of the input");

auto dimSizes = *dimSizesInfo;
auto rank = dimSizes.size();
size_t newRank = rank + inputUnsqzDims.size();
int64_t rank = dimSizes.size();
int64_t newRank = rank + inputUnsqzDims.size();
auto unsqzDims = toPositiveDims(inputUnsqzDims, newRank);
for (size_t k = 0, sz = unsqzDims.size(); k < sz; ++k)
for (int64_t k = 0, sz = unsqzDims.size(); k < sz; ++k)
if (k > 1 && unsqzDims[k] <= unsqzDims[k - 1])
return rewriter.notifyMatchFailure(
op, "unsqueeze dimensions must be specified in order");
Expand All @@ -335,8 +335,8 @@ FailureOr<Value> unsqueezeTensor(PatternRewriter &rewriter, Operation *op,
std::vector<int64_t> newShape;
newDimSizes.reserve(newRank);
newShape.reserve(newRank);
for (size_t k = 0, i = 0, j = 0; k < newRank; ++k) {
if (j < unsqzDims.size() && unsqzDims[j] == k) {
for (int64_t k = 0, i = 0, j = 0; k < newRank; ++k) {
if (j < static_cast<int64_t>(unsqzDims.size()) && unsqzDims[j] == k) {
newDimSizes.push_back(one);
newShape.push_back(1);
j++;
Expand Down
41 changes: 24 additions & 17 deletions projects/pt1/e2e_testing/xfail_sets.py
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Expand Up @@ -13,6 +13,8 @@
from torch_mlir_e2e_test.test_suite import COMMON_TORCH_MLIR_LOWERING_XFAILS
from torch_mlir._version import torch_version_for_comparison, version

print(f"TORCH_VERSION_FOR_COMPARISON =", torch_version_for_comparison())

LINALG_XFAIL_SET = COMMON_TORCH_MLIR_LOWERING_XFAILS | {
# Lowering Torch Backend IR -> Linalg-on-Tensors Backend IR failed
# 'linalg.depthwise_conv_2d_nchw_chw' op inferred input/output operand #1 has shape's dimension #0 to be 4, but found 8
Expand All @@ -21,6 +23,14 @@
"IscloseStaticModuleTrue_basic"
}

if torch_version_for_comparison() >= version.parse("2.2.0.dev20231204"):
LINALG_XFAIL_SET |= {
"Conv2dWithPaddingDilationStrideStaticModule_grouped",
"Conv2dWithPaddingDilationStrideStaticModule_grouped_multiplier",
"ConvolutionModule2DGroups_basic",
}


TORCHDYNAMO_XFAIL_SET = {
#### General TorchDynamo/PyTorch errors

Expand Down Expand Up @@ -306,10 +316,11 @@
"ArangeStartOutViewModule_basic",
}

if torch_version_for_comparison() < version.parse("2.1.0.dev"):
TORCHDYNAMO_XFAIL_SET -= {
"ScaledDotProductAttentionSameModule_basic",
"ScaledDotProductAttentionDifferentModule_basic",
if torch_version_for_comparison() >= version.parse("2.2.0.dev20231204"):
TORCHDYNAMO_XFAIL_SET |= {
"Conv2dWithPaddingDilationStrideStaticModule_grouped",
"Conv2dWithPaddingDilationStrideStaticModule_grouped_multiplier",
"ConvolutionModule2DGroups_basic",
}

TORCHDYNAMO_CRASHING_SET = {
Expand Down Expand Up @@ -1305,6 +1316,10 @@
"MeanModule_basic",
"ArangeStartOutModule_basic",
"ArangeStartOutViewModule_basic",
"Conv2dBiasNoPaddingModule_basic",
"Conv2dNoPaddingModule_basic",
"Conv2dWithPaddingDilationStrideModule_basic",
"Conv2dWithPaddingModule_basic",
}

MAKE_FX_TOSA_PASS_SET = (TOSA_PASS_SET | {
Expand Down Expand Up @@ -1335,20 +1350,12 @@
# failed to legalize operation 'torch.aten.to.dtype' that was explicitly marked illegal
"AtenEyeModuleInt2D_basic",
"AtenEyeMModuleInt2D_basic",
}

if torch_version_for_comparison() < version.parse("2.1.0.dev"):
MAKE_FX_TOSA_PASS_SET -= {
# 'tensor.expand_shape' op expected rank expansion, but found source rank 1 >= result rank 1
"ReshapeCollapseModule_basic",

# failed to lower torch.aten.empty.memory_format
"BatchNorm1DModule_basic",
"BatchNorm1DWith2DInputModule_basic",
"BatchNorm2DModule_basic",
"BatchNorm3DModule_basic",
"BatchNorm1DStaticShapeModule_basic",
}
"Conv2dBiasNoPaddingModule_basic",
"Conv2dNoPaddingModule_basic",
"Conv2dWithPaddingDilationStrideModule_basic",
"Conv2dWithPaddingModule_basic",
}

LTC_CRASHING_SET = {
# TODO: update test to move all inputs to the lazy device. Otherwise test fails with:
Expand Down
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