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[ONNX] Change AtenScatterReduce to AtenScatterReduceTwoOp with tm_tensor pass for onnx.ScatterElements #3754

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Oct 6, 2024
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[ONNX] Change AtenScatterReduce to AtenScatterReduceTwoOp with tm_tensor pass for onnx.ScatterElements #3754

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606ed0f
[ONNX] Mapping reduction string from onnx `add` to torch `sum`
AmosLewis Sep 16, 2024
e632755
[Linalg] Add torch.scatter.reduce to linalg lowering
AmosLewis Oct 2, 2024
faec62d
[ONNX] Change AtenScatterReduce to AtenScatterReduceTwoOp for onnx.Sc…
AmosLewis Oct 4, 2024
356ab48
XPASS - "ScatterAddStaticModule_basic"
AmosLewis Oct 5, 2024
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11 changes: 7 additions & 4 deletions lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -635,18 +635,21 @@ void mlir::torch::onnx_c::populateDefaultDomainQtoZ(

// TODO: Implement max and min cases
if (reduction == "mul") {
reduction = "multiply";
reduction = "prod";
} else if (reduction == "max" || reduction == "min") {
return rewriter.notifyMatchFailure(
binder.op, "max/min reduction unsupported for scatter elements");
} else if (reduction == "add") {
reduction = "sum";
}

Value cstStrReduction =
rewriter.create<Torch::ConstantStrOp>(binder.getLoc(), reduction);

rewriter.replaceOpWithNewOp<Torch::AtenScatterReduceOp>(
Value cstTrue =
rewriter.create<Torch::ConstantBoolOp>(binder.getLoc(), true);
rewriter.replaceOpWithNewOp<Torch::AtenScatterReduceTwoOp>(
binder.op, resultType, data, constAxis, indices, updates,
cstStrReduction);
cstStrReduction, cstTrue);
return success();
});
patterns.onOp(
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1 change: 0 additions & 1 deletion projects/pt1/e2e_testing/xfail_sets.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3084,7 +3084,6 @@
"ScatterReduceIntMaxModuleIncludeSelf",
"ScatterReduceIntMinModuleIncludeSelf",
"ScatterValueFloatModule_basic",
"ScatterAddStaticModule_basic",
# Failure - onnx_lowering: onnx.ScatterND
"IndexPut1DFloatAccumulateModule_basic",
"IndexPut1DIntAccumulateModule_basic",
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38 changes: 20 additions & 18 deletions test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
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Expand Up @@ -261,15 +261,16 @@ func.func @test_scatter_elements_with_axis(%arg0: !torch.vtensor<[1,5],f32>, %ar

// CHECK-LABEL: func.func @test_scatter_elements_with_duplicate_indices
func.func @test_scatter_elements_with_duplicate_indices(%arg0: !torch.vtensor<[1,5],f32>, %arg1: !torch.vtensor<[1,2],si64>, %arg2: !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
// CHECK: %[[AXIS:.*]] = torch.constant.int 1
// CHECK: %[[ZERO:.+]] = torch.constant.int 0
// CHECK: %[[ONE:.+]] = torch.constant.int 1
// CHECK: %[[SZ:.+]] = torch.aten.size.int %arg0, %[[AXIS]]
// CHECK: %[[ADD:.+]] = torch.aten.add.Scalar %arg1, %[[SZ]], %[[ONE]]
// CHECK: %[[CMP:.+]] = torch.aten.lt.Scalar %arg1, %[[ZERO]]
// CHECK: %[[WHERE:.+]] = torch.aten.where.self %[[CMP]], %[[ADD]], %arg1
// CHECK: %[[STR:.*]] = torch.constant.str "add"
// CHECK: torch.aten.scatter.reduce %arg0, %[[AXIS]], %[[WHERE]], %arg2, %str : !torch.vtensor<[1,5],f32>, !torch.int, !torch.vtensor<[1,2],si64>, !torch.vtensor<[1,2],f32>, !torch.str -> !torch.vtensor<[1,5],f32>
// CHECK: %[[AXIS:.*]] = torch.constant.int 1
// CHECK: %[[ZERO:.*]] = torch.constant.int 0
// CHECK: %[[FIVE:.*]] = torch.constant.int 1
// CHECK: %[[SZ:.*]] = torch.aten.size.int %arg0, %[[AXIS]] : !torch.vtensor<[1,5],f32>, !torch.int -> !torch.int
// CHECK: %[[ADD:.*]] = torch.aten.add.Scalar %arg1, %[[SZ]], %[[FIVE]] : !torch.vtensor<[1,2],si64>, !torch.int, !torch.int -> !torch.vtensor<[1,2],si64>
// CHECK: %[[CMP:.*]] = torch.aten.lt.Scalar %arg1, %[[ZERO]] : !torch.vtensor<[1,2],si64>, !torch.int -> !torch.vtensor<[1,2],i1>
// CHECK: %[[WHERE:.*]] = torch.aten.where.self %[[CMP]], %[[ADD]], %arg1 : !torch.vtensor<[1,2],i1>, !torch.vtensor<[1,2],si64>, !torch.vtensor<[1,2],si64> -> !torch.vtensor<[1,2],si64>
// CHECK: %[[STR:.*]] = torch.constant.str "sum"
// CHECK: %[[TRUE:.*]] = torch.constant.bool true
// CHECK: torch.aten.scatter_reduce.two %arg0, %[[AXIS]], %[[WHERE]], %arg2, %[[STR]], %[[TRUE]] : !torch.vtensor<[1,5],f32>, !torch.int, !torch.vtensor<[1,2],si64>, !torch.vtensor<[1,2],f32>, !torch.str, !torch.bool -> !torch.vtensor<[1,5],f32>
%0 = torch.operator "onnx.ScatterElements"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64, torch.onnx.reduction = "add"} : (!torch.vtensor<[1,5],f32>, !torch.vtensor<[1,2],si64>, !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32>
return %0 : !torch.vtensor<[1,5],f32>
}
Expand All @@ -294,15 +295,16 @@ func.func @test_scatter_elements_without_axis(%arg0: !torch.vtensor<[3,3],f32>,

// CHECK-LABEL: func.func @test_scatter_elements_with_reduction_mul
func.func @test_scatter_elements_with_reduction_mul(%arg0: !torch.vtensor<[1,5],f32>, %arg1: !torch.vtensor<[1,2],si64>, %arg2: !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
// CHECK: %[[AXIS:.*]] = torch.constant.int 1
// CHECK: %[[ZERO:.+]] = torch.constant.int 0
// CHECK: %[[ONE:.+]] = torch.constant.int 1
// CHECK: %[[SZ:.+]] = torch.aten.size.int %arg0, %[[AXIS]]
// CHECK: %[[ADD:.+]] = torch.aten.add.Scalar %arg1, %[[SZ]], %[[ONE]]
// CHECK: %[[CMP:.+]] = torch.aten.lt.Scalar %arg1, %[[ZERO]]
// CHECK: %[[WHERE:.+]] = torch.aten.where.self %[[CMP]], %[[ADD]], %arg1
// CHECK: %[[STR:.*]] = torch.constant.str "multiply"
// CHECK: torch.aten.scatter.reduce %arg0, %[[AXIS]], %[[WHERE]], %arg2, %str : !torch.vtensor<[1,5],f32>, !torch.int, !torch.vtensor<[1,2],si64>, !torch.vtensor<[1,2],f32>, !torch.str -> !torch.vtensor<[1,5],f32>
// CHECK: %[[AXIS:.*]] = torch.constant.int 1
// CHECK: %[[ZERO:.*]] = torch.constant.int 0
// CHECK: %[[FIVE:.*]] = torch.constant.int 1
// CHECK: %[[SZ:.*]] = torch.aten.size.int %arg0, %[[AXIS]] : !torch.vtensor<[1,5],f32>, !torch.int -> !torch.int
// CHECK: %[[ADD:.*]] = torch.aten.add.Scalar %arg1, %[[SZ]], %[[FIVE]] : !torch.vtensor<[1,2],si64>, !torch.int, !torch.int -> !torch.vtensor<[1,2],si64>
// CHECK: %[[CMP:.*]] = torch.aten.lt.Scalar %arg1, %[[ZERO]] : !torch.vtensor<[1,2],si64>, !torch.int -> !torch.vtensor<[1,2],i1>
// CHECK: %[[WHERE:.*]] = torch.aten.where.self %[[CMP]], %[[ADD]], %arg1 : !torch.vtensor<[1,2],i1>, !torch.vtensor<[1,2],si64>, !torch.vtensor<[1,2],si64> -> !torch.vtensor<[1,2],si64>
// CHECK: %[[STR:.*]] = torch.constant.str "prod"
// CHECK: %[[TRUE:.*]] = torch.constant.bool true
// CHECK: torch.aten.scatter_reduce.two %arg0, %[[AXIS]], %[[WHERE]], %arg2, %[[STR]], %[[TRUE]] : !torch.vtensor<[1,5],f32>, !torch.int, !torch.vtensor<[1,2],si64>, !torch.vtensor<[1,2],f32>, !torch.str, !torch.bool -> !torch.vtensor<[1,5],f32>
%0 = torch.operator "onnx.ScatterElements"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64, torch.onnx.reduction = "mul"} : (!torch.vtensor<[1,5],f32>, !torch.vtensor<[1,2],si64>, !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32>
return %0 : !torch.vtensor<[1,5],f32>
}
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