mirror of https://github.com/llvm/torch-mlir
[onnx] Support of onnx.Greater, onnx.Less, onnx.GreaterOrEqual to Torch (#2649)
The three remaining compare operations onnx.Greater onnx.Less onnx.GreaterOrEqual Are also added with this push request. This concludes a set of basic tensor compare functions.pull/2667/head
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61888690bb
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@ -38,7 +38,43 @@ void mlir::torch::onnx_c::populateDefaultDomainGtoP(
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binder.op, resultType, lhs, rhs);
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return success();
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});
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patterns.onOp("LessOrEqual", 1,
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patterns.onOp("Greater", 16,
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[](OpBinder binder, ConversionPatternRewriter &rewriter) {
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Torch::ValueTensorType resultType;
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Value lhs, rhs;
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std::string direction;
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if (binder.tensorOperands(lhs, rhs) ||
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binder.tensorResultType(resultType))
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return failure();
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rewriter.replaceOpWithNewOp<Torch::AtenGtTensorOp>(
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binder.op, resultType, lhs, rhs);
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return success();
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});
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patterns.onOp("GreaterOrEqual", 16,
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[](OpBinder binder, ConversionPatternRewriter &rewriter) {
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Torch::ValueTensorType resultType;
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Value lhs, rhs;
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std::string direction;
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if (binder.tensorOperands(lhs, rhs) ||
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binder.tensorResultType(resultType))
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return failure();
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rewriter.replaceOpWithNewOp<Torch::AtenGeTensorOp>(
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binder.op, resultType, lhs, rhs);
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return success();
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});
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patterns.onOp("Less", 13,
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[](OpBinder binder, ConversionPatternRewriter &rewriter) {
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Torch::ValueTensorType resultType;
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Value lhs, rhs;
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if (binder.tensorOperands(lhs, rhs) ||
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binder.tensorResultType(resultType)) {
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return failure();
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}
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rewriter.replaceOpWithNewOp<Torch::AtenLtTensorOp>(
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binder.op, resultType, lhs, rhs);
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return success();
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});
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patterns.onOp("LessOrEqual", 16,
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[](OpBinder binder, ConversionPatternRewriter &rewriter) {
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Torch::ValueTensorType resultType;
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Value lhs, rhs;
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@ -4,6 +4,33 @@
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// level constants. This is a pragmatic choice which lets us have a lot
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// of tests in this file, whereas the others tend to be more bespoke.
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// CHECK-LABEL: func.func @test_greater
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func.func @test_greater(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
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// CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]]: !torch.vtensor<[3,4,5],f32>
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// CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: !torch.vtensor<[3,4,5],f32>
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// CHECK: torch.aten.gt.Tensor %[[ARG0]], %[[ARG1]] : !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32> -> !torch.vtensor<[3,4,5],i1>
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%0 = torch.operator "onnx.Greater"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1>
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return %0 : !torch.vtensor<[3,4,5],i1>
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}
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// CHECK-LABEL: func.func @test_greater_or_equal
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func.func @test_greater_or_equal(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
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// CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]]: !torch.vtensor<[3,4,5],f32>
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// CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: !torch.vtensor<[3,4,5],f32>
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// CHECK: torch.aten.ge.Tensor %[[ARG0]], %[[ARG1]] : !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32> -> !torch.vtensor<[3,4,5],i1>
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%0 = torch.operator "onnx.GreaterOrEqual"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1>
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return %0 : !torch.vtensor<[3,4,5],i1>
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}
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// CHECK-LABEL: func.func @test_less
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func.func @test_less(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
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// CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]]: !torch.vtensor<[3,4,5],f32>
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// CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: !torch.vtensor<[3,4,5],f32>
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// CHECK: torch.aten.lt.Tensor %[[ARG0]], %[[ARG1]] : !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32> -> !torch.vtensor<[3,4,5],i1>
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%0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1>
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return %0 : !torch.vtensor<[3,4,5],i1>
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}
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// CHECK-LABEL: func.func @test_gather_elements
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func.func @test_gather_elements(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5], si64>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.opset_version = 13 : si64} {
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// CHECK-DAG: %[[INT0:.+]] = torch.constant.int 0
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@ -43,7 +70,7 @@ func.func @test_matmul_4d(%arg0: !torch.vtensor<[1,2,3,4],f32>, %arg1: !torch.vt
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}
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// CHECK-LABEL: func.func @test_less_or_equal
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func.func @test_less_or_equal(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
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func.func @test_less_or_equal(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
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// CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]]: !torch.vtensor<[3,4,5],f32>
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// CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: !torch.vtensor<[3,4,5],f32>
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// CHECK: torch.aten.le.Tensor %[[ARG0]], %[[ARG1]] : !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32> -> !torch.vtensor<[3,4,5],i1>
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