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[MLIR][Torch] Add OnnxToTorch and TorchToLinalg support for trig ops (#…
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…2903)

This commit adds the OnnxToTorch lowering for cosh, acosh, asin, asinh,
and atanh op.
This commit also adds the TorchToLinalg lowering for acosh, asin, asinh,
and atanh op.

Signed-Off By: Vivek Khandelwal <vivekkhandelwal1424@gmail.com>
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vivekkhandelwal1 authored Feb 14, 2024
1 parent e9cdd6c commit d6d1a17
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Showing 8 changed files with 746 additions and 161 deletions.
360 changes: 270 additions & 90 deletions include/torch-mlir/Dialect/Torch/IR/GeneratedTorchOps.td
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59 changes: 55 additions & 4 deletions lib/Conversion/TorchOnnxToTorch/DefaultDomainAtoF.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -103,7 +103,6 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(
binder.op, resultType, operand);
return success();
});
// TODO: Acosh unimplemented in torch-mlir
// Add became forward compatible with Torch in version 7.
patterns.onOp("Add", 7,
[](OpBinder binder, ConversionPatternRewriter &rewriter) {
Expand Down Expand Up @@ -203,9 +202,28 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(
binder.op, resultType, operand, constAxis, constKeepDims);
return success();
});
// TODO: Asin unimplemented in torch-mlir
// TODO: Asinh unimplemented in torch-mlir
// TODO: Atanh unimplemented in torch-mlir
patterns.onOp("Asin", 7,
[](OpBinder binder, ConversionPatternRewriter &rewriter) {
Torch::ValueTensorType resultType;
Value operand;
if (binder.tensorOperand(operand) ||
binder.tensorResultType(resultType))
return failure();
rewriter.replaceOpWithNewOp<Torch::AtenAsinOp>(
binder.op, resultType, operand);
return success();
});
patterns.onOp("Asinh", 9,
[](OpBinder binder, ConversionPatternRewriter &rewriter) {
Torch::ValueTensorType resultType;
Value operand;
if (binder.tensorOperand(operand) ||
binder.tensorResultType(resultType))
return failure();
rewriter.replaceOpWithNewOp<Torch::AtenAsinhOp>(
binder.op, resultType, operand);
return success();
});
patterns.onOp("Atan", 7,
[](OpBinder binder, ConversionPatternRewriter &rewriter) {
Torch::ValueTensorType resultType;
Expand All @@ -217,6 +235,17 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(
binder.op, resultType, operand);
return success();
});
patterns.onOp("Atanh", 9,
[](OpBinder binder, ConversionPatternRewriter &rewriter) {
Torch::ValueTensorType resultType;
Value operand;
if (binder.tensorOperand(operand) ||
binder.tensorResultType(resultType))
return failure();
rewriter.replaceOpWithNewOp<Torch::AtenAtanhOp>(
binder.op, resultType, operand);
return success();
});
patterns.onOp("Acos", 7,
[](OpBinder binder, ConversionPatternRewriter &rewriter) {
Torch::ValueTensorType resultType;
Expand All @@ -228,6 +257,17 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(
binder.op, resultType, operand);
return success();
});
patterns.onOp("Acosh", 9,
[](OpBinder binder, ConversionPatternRewriter &rewriter) {
Torch::ValueTensorType resultType;
Value operand;
if (binder.tensorOperand(operand) ||
binder.tensorResultType(resultType))
return failure();
rewriter.replaceOpWithNewOp<Torch::AtenAcoshOp>(
binder.op, resultType, operand);
return success();
});
patterns.onOp("BatchNormalization", 15,
[](OpBinder binder, ConversionPatternRewriter &rewriter) {
Torch::ValueTensorType resultType;
Expand Down Expand Up @@ -1041,6 +1081,17 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(
binder.op, resultType, operand);
return success();
});
patterns.onOp("Cosh", 9,
[](OpBinder binder, ConversionPatternRewriter &rewriter) {
Torch::ValueTensorType resultType;
Value operand;
if (binder.tensorOperand(operand) ||
binder.tensorResultType(resultType))
return failure();
rewriter.replaceOpWithNewOp<Torch::AtenCoshOp>(
binder.op, resultType, operand);
return success();
});
patterns.onOp(
"CumSum", 11, [](OpBinder binder, ConversionPatternRewriter &rewriter) {
Location loc = binder.getLoc();
Expand Down
97 changes: 57 additions & 40 deletions lib/Conversion/TorchToLinalg/Uncategorized.cpp
View file
Original file line number Diff line number Diff line change
Expand Up @@ -216,22 +216,6 @@ static Value createLinalgPayloadCalculationForElementwiseOp(
return b.create<math::FloorOp>(loc, payloadArgs[0]);
if (isa<AtenCeilOp>(op))
return b.create<math::CeilOp>(loc, payloadArgs[0]);
if (isa<AtenTanOp>(op)) {
return createCalculationForMathOpWithDtypeConversion<math::TanOp>(
b, converter, payloadArgs[0], op);
}
if (isa<AtenTanhOp>(op)) {
return createCalculationForMathOpWithDtypeConversion<math::TanhOp>(
b, converter, payloadArgs[0], op);
}
if (isa<AtenSinhOp>(op)) {
return createCalculationForMathOpWithDtypeConversion<math::SinhOp>(
b, converter, payloadArgs[0], op);
}
if (isa<AtenCoshOp>(op)) {
return createCalculationForMathOpWithDtypeConversion<math::CoshOp>(
b, converter, payloadArgs[0], op);
}
if (isa<AtenExpOp>(op)) {
return createCalculationForMathOpWithDtypeConversion<math::ExpOp>(
b, converter, payloadArgs[0], op);
Expand Down Expand Up @@ -276,18 +260,50 @@ static Value createLinalgPayloadCalculationForElementwiseOp(
return createCalculationForMathOpWithDtypeConversion<math::SinOp>(
b, converter, payloadArgs[0], op);
}
if (isa<AtenSinhOp>(op)) {
return createCalculationForMathOpWithDtypeConversion<math::SinhOp>(
b, converter, payloadArgs[0], op);
}
if (isa<AtenAsinOp>(op)) {
return createCalculationForMathOpWithDtypeConversion<math::AsinOp>(
b, converter, payloadArgs[0], op);
}
if (isa<AtenAsinhOp>(op)) {
return createCalculationForMathOpWithDtypeConversion<math::AsinhOp>(
b, converter, payloadArgs[0], op);
}
if (isa<AtenCosOp>(op)) {
return createCalculationForMathOpWithDtypeConversion<math::CosOp>(
b, converter, payloadArgs[0], op);
}
if (isa<AtenAtanOp>(op)) {
return createCalculationForMathOpWithDtypeConversion<math::AtanOp>(
if (isa<AtenCoshOp>(op)) {
return createCalculationForMathOpWithDtypeConversion<math::CoshOp>(
b, converter, payloadArgs[0], op);
}
if (isa<AtenAcosOp>(op)) {
return createCalculationForMathOpWithDtypeConversion<math::AcosOp>(
b, converter, payloadArgs[0], op);
}
if (isa<AtenAcoshOp>(op)) {
return createCalculationForMathOpWithDtypeConversion<math::AcoshOp>(
b, converter, payloadArgs[0], op);
}
if (isa<AtenTanOp>(op)) {
return createCalculationForMathOpWithDtypeConversion<math::TanOp>(
b, converter, payloadArgs[0], op);
}
if (isa<AtenTanhOp>(op)) {
return createCalculationForMathOpWithDtypeConversion<math::TanhOp>(
b, converter, payloadArgs[0], op);
}
if (isa<AtenAtanOp>(op)) {
return createCalculationForMathOpWithDtypeConversion<math::AtanOp>(
b, converter, payloadArgs[0], op);
}
if (isa<AtenAtanhOp>(op)) {
return createCalculationForMathOpWithDtypeConversion<math::AtanhOp>(
b, converter, payloadArgs[0], op);
}
if (auto clone = dyn_cast<AtenCloneOp>(op)) {
int64_t memoryFormat;
if (!clone.getMemoryFormat().getType().isa<Torch::NoneType>() &&
Expand Down Expand Up @@ -1505,7 +1521,8 @@ class ConvertElementwiseOp : public ConversionPattern {
AtenMaskedFillTensorOp, AtenLogicalOrOp, AtenLogicalAndOp,
AtenLogicalXorOp, AtenLogicalNotOp, AtenIsinfOp, AtenTriuOp,
AtenTrilOp, AtenBitwiseNotOp, AtenRoundOp, AtenFillScalarOp,
AtenFillTensorOp, AtenAtanOp, AtenAcosOp, AtenRealOp, AtenImagOp,
AtenFillTensorOp, AtenAtanOp, AtenAcosOp, AtenAtanhOp, AtenAcoshOp,
AtenAsinOp, AtenAsinhOp, AtenRealOp, AtenImagOp,
AtenDequantizeSelfOp, AtenDequantizeTensorOp,
AtenQuantizePerTensorOp>(op))
return rewriter.notifyMatchFailure(op, "not a supported elementwise op");
Expand Down Expand Up @@ -2350,27 +2367,27 @@ void mlir::torch::torch_to_linalg::populateUncategorizedPatternsAndLegality(
ConversionTarget &target) {
MLIRContext *context = patterns.getContext();
target.addIllegalOp<
AtenTanOp, AtenTanhOp, AtenSinhOp, AtenCoshOp, AtenReluOp, AtenGeluOp,
AtenGeluBackwardOp, AtenAddTensorOp, AtenMulTensorOp, AtenDivTensorOp,
AtenDivTensorModeOp, AtenSubTensorOp, AtenLerpTensorOp, AtenSigmoidOp,
AtenMinimumOp, AtenAtan2Op, AtenMaximumOp, AtenToDtypeOp, AtenClampOp,
AtenClampTensorOp, AtenRsubScalarOp, AtenLogOp, AtenErfOp, AtenSqrtOp,
AtenFloorOp, AtenCeilOp, AtenPreluOp, AtenPowScalarOp,
AtenPowTensorScalarOp, AtenPowTensorTensorOp, AtenLog2Op, AtenLog10Op,
AtenLog1pOp, AtenRsqrtOp, AtenAbsOp, AtenReciprocalOp,
AtenBitwiseAndTensorOp, AtenBitwiseAndScalarOp, AtenBitwiseOrTensorOp,
AtenBitwiseXorTensorOp, AtenBitwiseLeftShiftTensorOp,
AtenBitwiseRightShiftTensorOp, AtenGtScalarOp, AtenGeScalarOp,
AtenEqScalarOp, AtenLtScalarOp, AtenLeScalarOp, AtenWhereSelfOp,
AtenGtTensorOp, AtenGeTensorOp, AtenEqTensorOp, AtenNeTensorOp,
AtenLtTensorOp, AtenLeTensorOp, AtenThresholdOp, AtenThresholdBackwardOp,
AtenHardtanhBackwardOp, AtenCloneOp, AtenSinOp, AtenCosOp, AtenNeScalarOp,
AtenMaskedFillTensorOp, AtenLogicalOrOp, AtenLogicalAndOp, AtenAtanOp,
AtenAcosOp, AtenLogicalXorOp, AtenLogicalNotOp, AtenIsinfOp, AtenTriuOp,
AtenTrilOp, AtenRemainderScalarOp, AtenRemainderTensorOp,
AtenBitwiseNotOp, AtenRoundOp, AtenFillScalarOp, AtenFillTensorOp,
AtenRealOp, AtenImagOp, AtenDequantizeSelfOp, AtenDequantizeTensorOp,
AtenQuantizePerTensorOp>();
AtenTanOp, AtenTanhOp, AtenSinhOp, AtenCoshOp, AtenAtanhOp, AtenAcoshOp,
AtenAsinOp, AtenAsinhOp, AtenReluOp, AtenGeluOp, AtenGeluBackwardOp,
AtenAddTensorOp, AtenMulTensorOp, AtenDivTensorOp, AtenDivTensorModeOp,
AtenSubTensorOp, AtenLerpTensorOp, AtenSigmoidOp, AtenMinimumOp,
AtenAtan2Op, AtenMaximumOp, AtenToDtypeOp, AtenClampOp, AtenClampTensorOp,
AtenRsubScalarOp, AtenLogOp, AtenErfOp, AtenSqrtOp, AtenFloorOp,
AtenCeilOp, AtenPreluOp, AtenPowScalarOp, AtenPowTensorScalarOp,
AtenPowTensorTensorOp, AtenLog2Op, AtenLog10Op, AtenLog1pOp, AtenRsqrtOp,
AtenAbsOp, AtenReciprocalOp, AtenBitwiseAndTensorOp,
AtenBitwiseAndScalarOp, AtenBitwiseOrTensorOp, AtenBitwiseXorTensorOp,
AtenBitwiseLeftShiftTensorOp, AtenBitwiseRightShiftTensorOp,
AtenGtScalarOp, AtenGeScalarOp, AtenEqScalarOp, AtenLtScalarOp,
AtenLeScalarOp, AtenWhereSelfOp, AtenGtTensorOp, AtenGeTensorOp,
AtenEqTensorOp, AtenNeTensorOp, AtenLtTensorOp, AtenLeTensorOp,
AtenThresholdOp, AtenThresholdBackwardOp, AtenHardtanhBackwardOp,
AtenCloneOp, AtenSinOp, AtenCosOp, AtenNeScalarOp, AtenMaskedFillTensorOp,
AtenLogicalOrOp, AtenLogicalAndOp, AtenAtanOp, AtenAcosOp,
AtenLogicalXorOp, AtenLogicalNotOp, AtenIsinfOp, AtenTriuOp, AtenTrilOp,
AtenRemainderScalarOp, AtenRemainderTensorOp, AtenBitwiseNotOp,
AtenRoundOp, AtenFillScalarOp, AtenFillTensorOp, AtenRealOp, AtenImagOp,
AtenDequantizeSelfOp, AtenDequantizeTensorOp, AtenQuantizePerTensorOp>();
patterns.add<ConvertElementwiseOp>(typeConverter, context);
target.addIllegalOp<AtenNllLossForwardOp>();
patterns.add<ConvertAtenDetachOp>(typeConverter, context);
Expand Down
70 changes: 56 additions & 14 deletions lib/Dialect/Torch/Transforms/AbstractInterpLibrary.cpp
View file
Original file line number Diff line number Diff line change
Expand Up @@ -6306,22 +6306,50 @@ StringRef mlir::torch::Torch::getAbstractInterpLibrary() {
" %18 = torch.aten.append.t %7, %17 : !torch.list<int>, !torch.int -> !torch.list<int>\n"
" return %7 : !torch.list<int>\n"
" }\n"
" func.func @\"__torch_mlir_shape_fn.aten.tan\"(%arg0: !torch.list<int>) -> !torch.list<int> {\n"
" func.func @\"__torch_mlir_shape_fn.aten.sin\"(%arg0: !torch.list<int>) -> !torch.list<int> {\n"
" %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>\n"
" return %0 : !torch.list<int>\n"
" }\n"
" func.func @\"__torch_mlir_shape_fn.aten.atan\"(%arg0: !torch.list<int>) -> !torch.list<int> {\n"
" func.func @\"__torch_mlir_shape_fn.aten.asin\"(%arg0: !torch.list<int>) -> !torch.list<int> {\n"
" %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>\n"
" return %0 : !torch.list<int>\n"
" }\n"
" func.func @\"__torch_mlir_shape_fn.aten.asinh\"(%arg0: !torch.list<int>) -> !torch.list<int> {\n"
" %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>\n"
" return %0 : !torch.list<int>\n"
" }\n"
" func.func @\"__torch_mlir_shape_fn.aten.cos\"(%arg0: !torch.list<int>) -> !torch.list<int> {\n"
" %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>\n"
" return %0 : !torch.list<int>\n"
" }\n"
" func.func @\"__torch_mlir_shape_fn.aten.cosh\"(%arg0: !torch.list<int>) -> !torch.list<int> {\n"
" %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>\n"
" return %0 : !torch.list<int>\n"
" }\n"
" func.func @\"__torch_mlir_shape_fn.aten.acos\"(%arg0: !torch.list<int>) -> !torch.list<int> {\n"
" %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>\n"
" return %0 : !torch.list<int>\n"
" }\n"
" func.func @\"__torch_mlir_shape_fn.aten.acosh\"(%arg0: !torch.list<int>) -> !torch.list<int> {\n"
" %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>\n"
" return %0 : !torch.list<int>\n"
" }\n"
" func.func @\"__torch_mlir_shape_fn.aten.tan\"(%arg0: !torch.list<int>) -> !torch.list<int> {\n"
" %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>\n"
" return %0 : !torch.list<int>\n"
" }\n"
" func.func @\"__torch_mlir_shape_fn.aten.tanh\"(%arg0: !torch.list<int>) -> !torch.list<int> {\n"
" %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>\n"
" return %0 : !torch.list<int>\n"
" }\n"
" func.func @\"__torch_mlir_shape_fn.aten.atan\"(%arg0: !torch.list<int>) -> !torch.list<int> {\n"
" %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>\n"
" return %0 : !torch.list<int>\n"
" }\n"
" func.func @\"__torch_mlir_shape_fn.aten.atanh\"(%arg0: !torch.list<int>) -> !torch.list<int> {\n"
" %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>\n"
" return %0 : !torch.list<int>\n"
" }\n"
" func.func @\"__torch_mlir_shape_fn.aten.erf\"(%arg0: !torch.list<int>) -> !torch.list<int> {\n"
" %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>\n"
" return %0 : !torch.list<int>\n"
Expand Down Expand Up @@ -6358,18 +6386,6 @@ StringRef mlir::torch::Torch::getAbstractInterpLibrary() {
" %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>\n"
" return %0 : !torch.list<int>\n"
" }\n"
" func.func @\"__torch_mlir_shape_fn.aten.sin\"(%arg0: !torch.list<int>) -> !torch.list<int> {\n"
" %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>\n"
" return %0 : !torch.list<int>\n"
" }\n"
" func.func @\"__torch_mlir_shape_fn.aten.cos\"(%arg0: !torch.list<int>) -> !torch.list<int> {\n"
" %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>\n"
" return %0 : !torch.list<int>\n"
" }\n"
" func.func @\"__torch_mlir_shape_fn.aten.acos\"(%arg0: !torch.list<int>) -> !torch.list<int> {\n"
" %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>\n"
" return %0 : !torch.list<int>\n"
" }\n"
" func.func @\"__torch_mlir_shape_fn.aten.cosine_similarity\"(%arg0: !torch.list<int>, %arg1: !torch.list<int>, %arg2: !torch.int, %arg3: !torch.float) -> !torch.list<int> {\n"
" %none = torch.constant.none\n"
" %int1 = torch.constant.int 1\n"
Expand Down Expand Up @@ -9371,6 +9387,11 @@ StringRef mlir::torch::Torch::getAbstractInterpLibrary() {
" %0 = torch.prim.ListConstruct %int5, %int15, %int6, %int7 : (!torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list<int>\n"
" return %0 : !torch.list<int>\n"
" }\n"
" func.func @\"__torch_mlir_dtype_fn.aten.acosh\"(%arg0: !torch.tuple<int, int>) -> !torch.int {\n"
" %0:2 = torch.prim.TupleUnpack %arg0 : !torch.tuple<int, int> -> !torch.int, !torch.int\n"
" %1 = call @__torch__._get_dtype_of_floating_point_op(%0#1) : (!torch.int) -> !torch.int\n"
" return %1 : !torch.int\n"
" }\n"
" func.func @\"__torch_mlir_dtype_fn.aten.tanh\"(%arg0: !torch.tuple<int, int>) -> !torch.int {\n"
" %0:2 = torch.prim.TupleUnpack %arg0 : !torch.tuple<int, int> -> !torch.int, !torch.int\n"
" %1 = call @__torch__._get_dtype_of_floating_point_op(%0#1) : (!torch.int) -> !torch.int\n"
Expand All @@ -9391,6 +9412,16 @@ StringRef mlir::torch::Torch::getAbstractInterpLibrary() {
" %1 = call @__torch__._get_dtype_of_floating_point_op(%0#1) : (!torch.int) -> !torch.int\n"
" return %1 : !torch.int\n"
" }\n"
" func.func @\"__torch_mlir_dtype_fn.aten.asin\"(%arg0: !torch.tuple<int, int>) -> !torch.int {\n"
" %0:2 = torch.prim.TupleUnpack %arg0 : !torch.tuple<int, int> -> !torch.int, !torch.int\n"
" %1 = call @__torch__._get_dtype_of_floating_point_op(%0#1) : (!torch.int) -> !torch.int\n"
" return %1 : !torch.int\n"
" }\n"
" func.func @\"__torch_mlir_dtype_fn.aten.asinh\"(%arg0: !torch.tuple<int, int>) -> !torch.int {\n"
" %0:2 = torch.prim.TupleUnpack %arg0 : !torch.tuple<int, int> -> !torch.int, !torch.int\n"
" %1 = call @__torch__._get_dtype_of_floating_point_op(%0#1) : (!torch.int) -> !torch.int\n"
" return %1 : !torch.int\n"
" }\n"
" func.func @\"__torch_mlir_dtype_fn.aten.cos\"(%arg0: !torch.tuple<int, int>) -> !torch.int {\n"
" %0:2 = torch.prim.TupleUnpack %arg0 : !torch.tuple<int, int> -> !torch.int, !torch.int\n"
" %1 = call @__torch__._get_dtype_of_floating_point_op(%0#1) : (!torch.int) -> !torch.int\n"
Expand Down Expand Up @@ -12473,6 +12504,17 @@ StringRef mlir::torch::Torch::getAbstractInterpLibrary() {
" }\n"
" return %2 : !torch.int\n"
" }\n"
" func.func @\"__torch_mlir_dtype_fn.aten.atanh\"(%arg0: !torch.tuple<int, int>) -> !torch.int {\n"
" %int6 = torch.constant.int 6\n"
" %0:2 = torch.prim.TupleUnpack %arg0 : !torch.tuple<int, int> -> !torch.int, !torch.int\n"
" %1 = call @__torch__.torch_mlir.jit_ir_importer.build_tools.library_generator.is_integer_dtype(%0#1) : (!torch.int) -> !torch.bool\n"
" %2 = torch.prim.If %1 -> (!torch.int) {\n"
" torch.prim.If.yield %int6 : !torch.int\n"
" } else {\n"
" torch.prim.If.yield %0#1 : !torch.int\n"
" }\n"
" return %2 : !torch.int\n"
" }\n"
" func.func @\"__torch_mlir_dtype_fn.aten.linear\"(%arg0: !torch.tuple<int, int>, %arg1: !torch.tuple<int, int>, %arg2: !torch.optional<tuple<int, int>>) -> !torch.int {\n"
" %0:2 = torch.prim.TupleUnpack %arg0 : !torch.tuple<int, int> -> !torch.int, !torch.int\n"
" %1:2 = torch.prim.TupleUnpack %arg1 : !torch.tuple<int, int> -> !torch.int, !torch.int\n"
Expand Down
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