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Fix onnx asinh lowering (#3263) 

iree tests `test_asinh` and `test_asinh_example` passed
pull/3269/head
jinchen 2024-04-30 00:49:57 -07:00 committed by GitHub
parent fb499192df
commit bf04b53b07
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GPG Key ID: B5690EEEBB952194
2 changed files with 35 additions and 13 deletions
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34
lib/Conversion/TorchOnnxToTorch/DefaultDomainAtoF.cpp
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@ -198,17 +198,29 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(
binder.op, resultType, operand); binder.op, resultType, operand);
return success(); return success();
}); });
patterns.onOp("Asinh", 9, patterns.onOp(
[](OpBinder binder, ConversionPatternRewriter &rewriter) { "Asinh", 9, [](OpBinder binder, ConversionPatternRewriter &rewriter) {
Torch::ValueTensorType resultType; Torch::ValueTensorType resultType;
Value operand; Value operand;
if (binder.tensorOperand(operand) || if (binder.tensorOperand(operand) ||
binder.tensorResultType(resultType)) binder.tensorResultType(resultType))
return failure(); return failure();
rewriter.replaceOpWithNewOp<Torch::AtenAsinhOp>(
binder.op, resultType, operand); // log(x + sqrt(x**2 + 1))
return success(); Value square = rewriter.create<Torch::AtenSquareOp>(
}); binder.getLoc(), resultType, operand);
Value cstOne = rewriter.create<Torch::ConstantIntOp>(
binder.getLoc(), rewriter.getI64IntegerAttr(1));
Value add0 = rewriter.create<Torch::AtenAddScalarOp>(
binder.getLoc(), resultType, square, cstOne, cstOne);
Value sqrt = rewriter.create<Torch::AtenSqrtOp>(binder.getLoc(),
resultType, add0);
Value add1 = rewriter.create<Torch::AtenAddTensorOp>(
binder.getLoc(), resultType, operand, sqrt, cstOne);
rewriter.replaceOpWithNewOp<Torch::AtenLogOp>(binder.op, resultType,
add1);
return success();
});
patterns.onOp("Atan", 7, patterns.onOp("Atan", 7,
[](OpBinder binder, ConversionPatternRewriter &rewriter) { [](OpBinder binder, ConversionPatternRewriter &rewriter) {
Torch::ValueTensorType resultType; Torch::ValueTensorType resultType;

14
test/Conversion/TorchOnnxToTorch/simple_ops_a_to_f.mlir
View File

@ -741,7 +741,12 @@ func.func @test_asin(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,
// CHECK-LABEL: @test_asinh_example // CHECK-LABEL: @test_asinh_example
func.func @test_asinh_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { func.func @test_asinh_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
// CHECK: torch.aten.asinh %arg0 : !torch.vtensor<[3],f32> -> !torch.vtensor<[3],f32> // CHECK: %[[SQUARE:.+]] = torch.aten.square %arg0 : !torch.vtensor<[3],f32> -> !torch.vtensor<[3],f32>
// CHECK: %[[C1:.+]] = torch.constant.int 1
// CHECK: %[[ADD:.+]] = torch.aten.add.Scalar %[[SQUARE]], %[[C1]], %[[C1]] : !torch.vtensor<[3],f32>, !torch.int, !torch.int -> !torch.vtensor<[3],f32>
// CHECK: %[[SQRT:.+]] = torch.aten.sqrt %[[ADD]] : !torch.vtensor<[3],f32> -> !torch.vtensor<[3],f32>
// CHECK: %[[ADD_0:.+]] = torch.aten.add.Tensor %arg0, %[[SQRT]], %[[C1]] : !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.int -> !torch.vtensor<[3],f32>
// CHECK: torch.aten.log %[[ADD_0]] : !torch.vtensor<[3],f32> -> !torch.vtensor<[3],f32>
%0 = torch.operator "onnx.Asinh"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> %0 = torch.operator "onnx.Asinh"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32>
return %0 : !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32>
} }
@ -750,7 +755,12 @@ func.func @test_asinh_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<
// CHECK-LABEL: @test_asinh // CHECK-LABEL: @test_asinh
func.func @test_asinh(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { func.func @test_asinh(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
// CHECK: torch.aten.asinh %arg0 : !torch.vtensor<[3,4,5],f32> -> !torch.vtensor<[3,4,5],f32> // CHECK: %[[SQUARE:.+]] = torch.aten.square %arg0 : !torch.vtensor<[3,4,5],f32> -> !torch.vtensor<[3,4,5],f32>
// CHECK: %[[C1:.+]] = torch.constant.int 1
// CHECK: %[[ADD:.+]] = torch.aten.add.Scalar %[[SQUARE]], %[[C1]], %[[C1]] : !torch.vtensor<[3,4,5],f32>, !torch.int, !torch.int -> !torch.vtensor<[3,4,5],f32>
// CHECK: %[[SQRT:.+]] = torch.aten.sqrt %[[ADD]] : !torch.vtensor<[3,4,5],f32> -> !torch.vtensor<[3,4,5],f32>
// CHECK: %[[ADD_0:.+]] = torch.aten.add.Tensor %arg0, %[[SQRT]], %[[C1]] : !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>, !torch.int -> !torch.vtensor<[3,4,5],f32>
// CHECK: torch.aten.log %[[ADD_0]] : !torch.vtensor<[3,4,5],f32> -> !torch.vtensor<[3,4,5],f32>
%0 = torch.operator "onnx.Asinh"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> %0 = torch.operator "onnx.Asinh"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32>
return %0 : !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32>
} }