llvm
/
torch-mlir
mirror of https://github.com/llvm/torch-mlir
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Fix onnx acosh lowering (#3262) 

iree tests `test_acosh` and `test_acosh_example` passed
pull/3269/head
jinchen 2024-04-30 00:49:44 -07:00 committed by GitHub
parent aa471f1d96
commit fb499192df
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
2 changed files with 35 additions and 13 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

20
lib/Conversion/TorchOnnxToTorch/DefaultDomainAtoF.cpp
View File

@ -242,15 +242,27 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(
binder.op, resultType, operand);
return success();
});
patterns.onOp("Acosh", 9,
[](OpBinder binder, ConversionPatternRewriter &rewriter) {
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);
// log(x + sqrt(x**2 - 1))
Value square = rewriter.create<Torch::AtenSquareOp>(
binder.getLoc(), resultType, operand);
Value cstOne = rewriter.create<Torch::ConstantIntOp>(
binder.getLoc(), rewriter.getI64IntegerAttr(1));
Value sub = rewriter.create<Torch::AtenSubScalarOp>(
binder.getLoc(), resultType, square, cstOne, cstOne);
Value sqrt = rewriter.create<Torch::AtenSqrtOp>(binder.getLoc(),
resultType, sub);
Value add = rewriter.create<Torch::AtenAddTensorOp>(
binder.getLoc(), resultType, operand, sqrt, cstOne);
rewriter.replaceOpWithNewOp<Torch::AtenLogOp>(binder.op, resultType,
add);
return success();
});
patterns.onOp("BatchNormalization", 15,

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

@ -695,7 +695,12 @@ func.func @test_cosh(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,
// CHECK-LABEL: @test_acosh_example
func.func @test_acosh_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.acosh %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: %[[SUB:.+]] = torch.aten.sub.Scalar %[[SQUARE]], %[[C1]], %[[C1]] : !torch.vtensor<[3],f32>, !torch.int, !torch.int -> !torch.vtensor<[3],f32>
// CHECK: %[[SQRT:.+]] = torch.aten.sqrt %[[SUB]] : !torch.vtensor<[3],f32> -> !torch.vtensor<[3],f32>
// CHECK: %[[ADD:.+]] = 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]] : !torch.vtensor<[3],f32> -> !torch.vtensor<[3],f32>
%0 = torch.operator "onnx.Acosh"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32>
return %0 : !torch.vtensor<[3],f32>
}
@ -704,7 +709,12 @@ func.func @test_acosh_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<
// CHECK-LABEL: @test_acosh
func.func @test_acosh(%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.acosh %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: %[[SUB:.+]] = torch.aten.sub.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 %[[SUB]] : !torch.vtensor<[3,4,5],f32> -> !torch.vtensor<[3,4,5],f32>
// CHECK: %[[ADD:.+]] = 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]] : !torch.vtensor<[3,4,5],f32> -> !torch.vtensor<[3,4,5],f32>
%0 = torch.operator "onnx.Acosh"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32>
return %0 : !torch.vtensor<[3,4,5],f32>
}