From f6e5b015daf2806d67159f91ed92b3dd5e715b3e Mon Sep 17 00:00:00 2001
From: archana-ramalingam <archana.ramalingam@amd.com>
Date: Thu, 18 Apr 2024 14:56:08 -0700
Subject: [PATCH 01/16] Add support for reducesumsquare op

---
 .../TorchOnnxToTorch/DefaultDomainQtoZ.cpp    |  21 ++++
 .../TorchOnnxToTorch/simple_ops_q_to_z.mlir   | 110 ++++++++++++++++++
 2 files changed, 131 insertions(+)

diff --git a/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp b/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
index b4bd102f152f..1633c7e7a8a7 100644
--- a/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
+++ b/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
@@ -914,6 +914,27 @@ void mlir::torch::onnx_c::populateDefaultDomainQtoZ(
                                         /*storeValue=*/data, keepDims,
                                         noop_with_empty_axes, false);
                 });
+  patterns.onOp(
+      "ReduceSumSquare", 1, 
+      [](OpBinder binder, ConversionPatternRewriter &rewriter) {
+        Torch::ValueTensorType resultType;
+        Value data;
+        int64_t keepDims, noop_with_empty_axes;
+        if (binder.tensorOperandAtIndex(operand, 0) ||
+            binder.tensorResultType(resultType) ||
+            binder.s64IntegerAttr(keepDims, "keepdims", 1) ||
+            binder.s64IntegerAttr(noop_with_empty_axes, 
+                                  "noop_with_empty_axes",
+                                  0))
+          return failure();
+
+        Value dataSquare = rewriter.create<Torch::AtenMulTensorOp>(
+            binder.getLoc(), operand.getType(), data, data);
+
+        return reducedSumImpl(binder, rewriter, data, resultType,
+                              /*storeValue=*/data, keepDims,
+                              noop_with_empty_axes, false);
+                });
   patterns.onOp(
       "ReduceMean", 1,
       [](OpBinder binder, ConversionPatternRewriter &rewriter) {
diff --git a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
index 0fdecd68481e..4a2d2bac2a8d 100644
--- a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
+++ b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
@@ -998,6 +998,116 @@ func.func @test_reduce_sum_negative_axes_keepdims_example(%arg0: !torch.vtensor<
 
 // -----
 
+// CHECK-LABEL: func.func @test_reduce_sum_square_default_axes_keepdims_example
+func.func @test_reduce_sum_square_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],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: %[[MULT:.+]] = torch.aten.mul.Tensor %arg0, %arg0 : !torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32> -> !torch.vtensor<[3,2,2],f32>
+  // CHECK: %[[INT0:.+]] = torch.constant.int 0
+  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct  : () -> !torch.list<int>
+  // CHECK: %[[TRUE:.+]] = torch.constant.bool true
+  // CHECK: %[[NONE:.+]] = torch.constant.none
+  // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[MULT]], %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,1,1],f32>
+  // CHECK: return %[[SUM]] : !torch.vtensor<[1,1,1],f32>
+  %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32>
+  return %0 : !torch.vtensor<[1,1,1],f32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_reduce_sum_square_do_not_keepdims_example
+func.func @test_reduce_sum_square_do_not_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],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: %[[MULT:.+]] = torch.aten.mul.Tensor %arg0, %arg0 : !torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32> -> !torch.vtensor<[3,2,2],f32>
+  // CHECK: %[[INT0:.+]] = torch.constant.int 0
+  // CHECK: %[[INT0_0:.+]] = torch.constant.int 0
+  // CHECK: %[[SELECT:.+]] = torch.aten.select.int %arg1, %[[INT0]], %[[INT0_0]] : !torch.vtensor<[1],si64>, !torch.int, !torch.int -> !torch.vtensor<[1],si64>
+  // CHECK: %[[DIM:.+]] = torch.aten.item %[[SELECT]] : !torch.vtensor<[1],si64> -> !torch.int
+  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %1 : (!torch.int) -> !torch.list<int>
+  // CHECK: %[[FALSE:.+]] = torch.constant.bool false
+  // CHECK: %[[NONE:.+]] = torch.constant.none
+  // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[MULT]], %[[DIMS]], %[[FALSE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[3,2],f32>
+  // CHECK: return %[[SUM]] : !torch.vtensor<[3,2],f32>
+  %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32>
+  return %0 : !torch.vtensor<[3,2],f32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_reduce_sum_square_empty_axes_input_noop_example
+func.func @test_reduce_sum_square_empty_axes_input_noop_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[3,2,2],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 = ""} {
+  %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64, torch.onnx.noop_with_empty_axes = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[3,2,2],f32>
+  return %0 : !torch.vtensor<[3,2,2],f32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_reduce_sum_square_empty_set_non_reduced_axis_zero
+func.func @test_reduce_sum_square_empty_set_non_reduced_axis_zero(%arg0: !torch.vtensor<[2,0,4],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,0,1],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: %[[MULT:.+]] = torch.aten.mul.Tensor %arg0, %arg0 : !torch.vtensor<[2,0,4],f32>, !torch.vtensor<[2,0,4],f32> -> !torch.vtensor<[2,0,4],f32>
+  // CHECK: %[[INT2:.+]] = torch.constant.int 2
+  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %[[INT2]] : (!torch.int) -> !torch.list<int>
+  // CHECK: %[[TRUE:.+]] = torch.constant.bool true
+  // CHECK: %[[NONE:.+]] = torch.constant.none
+  // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[MULT]], %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[2,0,4],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[2,0,1],f32>
+  // CHECK: return %[[SUM]] : !torch.vtensor<[2,0,1],f32>
+  %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,0,1],f32>
+  return %0 : !torch.vtensor<[2,0,1],f32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_reduce_sum_square_keepdims_example
+func.func @test_reduce_sum_square_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],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: %[[MULT:.+]] = torch.aten.mul.Tensor %arg0, %arg0 : !torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32> -> !torch.vtensor<[3,2,2],f32>
+  // CHECK: %[[INT0:.+]] = torch.constant.int 0
+  // CHECK: %[[INT0_0:.+]] = torch.constant.int 0
+  // CHECK: %[[SELECT:.+]] = torch.aten.select.int %arg1, %[[INT0]], %[[INT0_0]] : !torch.vtensor<[1],si64>, !torch.int, !torch.int -> !torch.vtensor<[1],si64>
+  // CHECK: %[[DIM:.+]] = torch.aten.item %[[SELECT]] : !torch.vtensor<[1],si64> -> !torch.int
+  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %1 : (!torch.int) -> !torch.list<int>
+  // CHECK: %[[TRUE:.+]] = torch.constant.bool true
+  // CHECK: %[[NONE:.+]] = torch.constant.none
+  // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[MULT]], %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[3,1,2],f32>
+  // CHECK: return %[[SUM]] : !torch.vtensor<[3,1,2],f32>
+  %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32>
+  return %0 : !torch.vtensor<[3,1,2],f32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_reduce_sum_square_keepdims_int_example
+func.func @test_reduce_sum_square_keepdims_int_example(%arg0: !torch.vtensor<[3,2,2],si64>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],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: %[[MULT:.+]] = torch.aten.mul.Tensor %arg0, %arg0 : !torch.vtensor<[3,2,2],si64>, !torch.vtensor<[3,2,2],si64> -> !torch.vtensor<[3,2,2],si64>
+  // CHECK: %[[INT0:.+]] = torch.constant.int 0
+  // CHECK: %[[INT0_0:.+]] = torch.constant.int 0
+  // CHECK: %[[SELECT:.+]] = torch.aten.select.int %arg1, %[[INT0]], %[[INT0_0]] : !torch.vtensor<[1],si64>, !torch.int, !torch.int -> !torch.vtensor<[1],si64>
+  // CHECK: %[[DIM:.+]] = torch.aten.item %[[SELECT]] : !torch.vtensor<[1],si64> -> !torch.int
+  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %1 : (!torch.int) -> !torch.list<int>
+  // CHECK: %[[TRUE:.+]] = torch.constant.bool true
+  // CHECK: %[[NONE:.+]] = torch.constant.none
+  // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[MULT]], %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[3,2,2],si64>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[3,1,2],f32>
+  // CHECK: return %[[SUM]] : !torch.vtensor<[3,1,2],f32>
+  %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32>
+  return %0 : !torch.vtensor<[3,1,2],f32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_reduce_sum_square_negative_axes_keepdims_example
+func.func @test_reduce_sum_square_negative_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],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: %[[MULT:.+]] = torch.aten.mul.Tensor %arg0, %arg0 : !torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32> -> !torch.vtensor<[3,2,2],f32>
+  // CHECK: %[[INT0:.+]] = torch.constant.int 0
+  // CHECK: %[[INT0_0:.+]] = torch.constant.int 0
+  // CHECK: %[[SELECT:.+]] = torch.aten.select.int %arg1, %[[INT0]], %[[INT0_0]] : !torch.vtensor<[1],si64>, !torch.int, !torch.int -> !torch.vtensor<[1],si64>
+  // CHECK: %[[DIM:.+]] = torch.aten.item %[[SELECT]] : !torch.vtensor<[1],si64> -> !torch.int
+  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %1 : (!torch.int) -> !torch.list<int>
+  // CHECK: %[[TRUE:.+]] = torch.constant.bool true
+  // CHECK: %[[NONE:.+]] = torch.constant.none
+  // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[MULT]], %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[3,1,2],f32>
+  // CHECK: return %[[SUM]] : !torch.vtensor<[3,1,2],f32>
+  %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32>
+  return %0 : !torch.vtensor<[3,1,2],f32>
+}
+
+// -----
+
 // CHECK-LABEL: @test_reduce_mean_negative_axes_keepdims_example
 func.func @test_reduce_mean_negative_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64} {
   // CHECK:  %[[TENSOR:.+]] = torch.vtensor.literal(dense<-2> : tensor<1xsi64>) : !torch.vtensor<[1],si64>

From 782c59e3497e15ca04684bb4425b410c1dda6b4d Mon Sep 17 00:00:00 2001
From: archana-ramalingam <archana.ramalingam@amd.com>
Date: Thu, 18 Apr 2024 15:21:57 -0700
Subject: [PATCH 02/16] Adding reducesumsquare op

---
 lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp b/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
index 1633c7e7a8a7..571b9c6c36ec 100644
--- a/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
+++ b/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
@@ -931,7 +931,7 @@ void mlir::torch::onnx_c::populateDefaultDomainQtoZ(
         Value dataSquare = rewriter.create<Torch::AtenMulTensorOp>(
             binder.getLoc(), operand.getType(), data, data);
 
-        return reducedSumImpl(binder, rewriter, data, resultType,
+        return reducedSumImpl(binder, rewriter, dataSquare, resultType,
                               /*storeValue=*/data, keepDims,
                               noop_with_empty_axes, false);
                 });

From 99de15385d9fa4c5e8087597fdd3f4ee28c80bb5 Mon Sep 17 00:00:00 2001
From: archana-ramalingam <archana.ramalingam@amd.com>
Date: Thu, 18 Apr 2024 19:52:24 -0700
Subject: [PATCH 03/16] Replace operand with data

---
 lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp b/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
index 571b9c6c36ec..5ab2da25e6f8 100644
--- a/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
+++ b/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
@@ -920,7 +920,7 @@ void mlir::torch::onnx_c::populateDefaultDomainQtoZ(
         Torch::ValueTensorType resultType;
         Value data;
         int64_t keepDims, noop_with_empty_axes;
-        if (binder.tensorOperandAtIndex(operand, 0) ||
+        if (binder.tensorOperandAtIndex(data, 0) ||
             binder.tensorResultType(resultType) ||
             binder.s64IntegerAttr(keepDims, "keepdims", 1) ||
             binder.s64IntegerAttr(noop_with_empty_axes, 
@@ -929,7 +929,7 @@ void mlir::torch::onnx_c::populateDefaultDomainQtoZ(
           return failure();
 
         Value dataSquare = rewriter.create<Torch::AtenMulTensorOp>(
-            binder.getLoc(), operand.getType(), data, data);
+            binder.getLoc(), data.getType(), data, data);
 
         return reducedSumImpl(binder, rewriter, dataSquare, resultType,
                               /*storeValue=*/data, keepDims,

From f779994db88415900978c03c80eb83592d3e10a5 Mon Sep 17 00:00:00 2001
From: archana-ramalingam <archana.ramalingam@amd.com>
Date: Fri, 19 Apr 2024 13:16:18 -0700
Subject: [PATCH 04/16] Fixing mlir tests

---
 .../TorchOnnxToTorch/simple_ops_q_to_z.mlir      | 16 ++++++++--------
 1 file changed, 8 insertions(+), 8 deletions(-)

diff --git a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
index 4a2d2bac2a8d..47d76cea849b 100644
--- a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
+++ b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
@@ -1019,8 +1019,8 @@ func.func @test_reduce_sum_square_do_not_keepdims_example(%arg0: !torch.vtensor<
   // CHECK: %[[INT0:.+]] = torch.constant.int 0
   // CHECK: %[[INT0_0:.+]] = torch.constant.int 0
   // CHECK: %[[SELECT:.+]] = torch.aten.select.int %arg1, %[[INT0]], %[[INT0_0]] : !torch.vtensor<[1],si64>, !torch.int, !torch.int -> !torch.vtensor<[1],si64>
-  // CHECK: %[[DIM:.+]] = torch.aten.item %[[SELECT]] : !torch.vtensor<[1],si64> -> !torch.int
-  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %1 : (!torch.int) -> !torch.list<int>
+  // CHECK: %[[ITEM:.+]] = torch.aten.item %[[SELECT]] : !torch.vtensor<[1],si64> -> !torch.int
+  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %[[ITEM]] : (!torch.int) -> !torch.list<int>
   // CHECK: %[[FALSE:.+]] = torch.constant.bool false
   // CHECK: %[[NONE:.+]] = torch.constant.none
   // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[MULT]], %[[DIMS]], %[[FALSE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[3,2],f32>
@@ -1060,8 +1060,8 @@ func.func @test_reduce_sum_square_keepdims_example(%arg0: !torch.vtensor<[3,2,2]
   // CHECK: %[[INT0:.+]] = torch.constant.int 0
   // CHECK: %[[INT0_0:.+]] = torch.constant.int 0
   // CHECK: %[[SELECT:.+]] = torch.aten.select.int %arg1, %[[INT0]], %[[INT0_0]] : !torch.vtensor<[1],si64>, !torch.int, !torch.int -> !torch.vtensor<[1],si64>
-  // CHECK: %[[DIM:.+]] = torch.aten.item %[[SELECT]] : !torch.vtensor<[1],si64> -> !torch.int
-  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %1 : (!torch.int) -> !torch.list<int>
+  // CHECK: %[[ITEM:.+]] = torch.aten.item %[[SELECT]] : !torch.vtensor<[1],si64> -> !torch.int
+  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %[[ITEM]] : (!torch.int) -> !torch.list<int>
   // CHECK: %[[TRUE:.+]] = torch.constant.bool true
   // CHECK: %[[NONE:.+]] = torch.constant.none
   // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[MULT]], %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[3,1,2],f32>
@@ -1078,8 +1078,8 @@ func.func @test_reduce_sum_square_keepdims_int_example(%arg0: !torch.vtensor<[3,
   // CHECK: %[[INT0:.+]] = torch.constant.int 0
   // CHECK: %[[INT0_0:.+]] = torch.constant.int 0
   // CHECK: %[[SELECT:.+]] = torch.aten.select.int %arg1, %[[INT0]], %[[INT0_0]] : !torch.vtensor<[1],si64>, !torch.int, !torch.int -> !torch.vtensor<[1],si64>
-  // CHECK: %[[DIM:.+]] = torch.aten.item %[[SELECT]] : !torch.vtensor<[1],si64> -> !torch.int
-  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %1 : (!torch.int) -> !torch.list<int>
+  // CHECK: %[[ITEM:.+]] = torch.aten.item %[[SELECT]] : !torch.vtensor<[1],si64> -> !torch.int
+  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %[[ITEM]] : (!torch.int) -> !torch.list<int>
   // CHECK: %[[TRUE:.+]] = torch.constant.bool true
   // CHECK: %[[NONE:.+]] = torch.constant.none
   // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[MULT]], %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[3,2,2],si64>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[3,1,2],f32>
@@ -1096,8 +1096,8 @@ func.func @test_reduce_sum_square_negative_axes_keepdims_example(%arg0: !torch.v
   // CHECK: %[[INT0:.+]] = torch.constant.int 0
   // CHECK: %[[INT0_0:.+]] = torch.constant.int 0
   // CHECK: %[[SELECT:.+]] = torch.aten.select.int %arg1, %[[INT0]], %[[INT0_0]] : !torch.vtensor<[1],si64>, !torch.int, !torch.int -> !torch.vtensor<[1],si64>
-  // CHECK: %[[DIM:.+]] = torch.aten.item %[[SELECT]] : !torch.vtensor<[1],si64> -> !torch.int
-  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %1 : (!torch.int) -> !torch.list<int>
+  // CHECK: %[[ITEM:.+]] = torch.aten.item %[[SELECT]] : !torch.vtensor<[1],si64> -> !torch.int
+  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %[[ITEM]] : (!torch.int) -> !torch.list<int>
   // CHECK: %[[TRUE:.+]] = torch.constant.bool true
   // CHECK: %[[NONE:.+]] = torch.constant.none
   // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[MULT]], %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[3,1,2],f32>

From 6eb80a826f50bbcf1d2100c5ffe52d8cd3de8bd2 Mon Sep 17 00:00:00 2001
From: archana-ramalingam <archana.ramalingam@amd.com>
Date: Fri, 19 Apr 2024 17:13:31 -0700
Subject: [PATCH 05/16] Fix clang-format issue

---
 lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp b/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
index 5ab2da25e6f8..c9bc13d5a85e 100644
--- a/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
+++ b/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
@@ -923,8 +923,7 @@ void mlir::torch::onnx_c::populateDefaultDomainQtoZ(
         if (binder.tensorOperandAtIndex(data, 0) ||
             binder.tensorResultType(resultType) ||
             binder.s64IntegerAttr(keepDims, "keepdims", 1) ||
-            binder.s64IntegerAttr(noop_with_empty_axes, 
-                                  "noop_with_empty_axes",
+            binder.s64IntegerAttr(noop_with_empty_axes, "noop_with_empty_axes",
                                   0))
           return failure();
 

From ea286baf8148a72caecfb7caf6f7937def8ef71b Mon Sep 17 00:00:00 2001
From: Ubuntu
 <archana@archana-cpu.judsoscro3wupi0qm4bjlj5m3b.bx.internal.cloudapp.net>
Date: Tue, 23 Apr 2024 02:20:44 +0000
Subject: [PATCH 06/16] Fixing reviewed issues

---
 .../TorchOnnxToTorch/DefaultDomainQtoZ.cpp    | 34 +++++++++----------
 .../TorchOnnxToTorch/simple_ops_q_to_z.mlir   | 25 ++++----------
 2 files changed, 24 insertions(+), 35 deletions(-)

diff --git a/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp b/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
index c9bc13d5a85e..57419cc42e4e 100644
--- a/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
+++ b/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
@@ -914,25 +914,25 @@ void mlir::torch::onnx_c::populateDefaultDomainQtoZ(
                                         /*storeValue=*/data, keepDims,
                                         noop_with_empty_axes, false);
                 });
-  patterns.onOp(
-      "ReduceSumSquare", 1, 
-      [](OpBinder binder, ConversionPatternRewriter &rewriter) {
-        Torch::ValueTensorType resultType;
-        Value data;
-        int64_t keepDims, noop_with_empty_axes;
-        if (binder.tensorOperandAtIndex(data, 0) ||
-            binder.tensorResultType(resultType) ||
-            binder.s64IntegerAttr(keepDims, "keepdims", 1) ||
-            binder.s64IntegerAttr(noop_with_empty_axes, "noop_with_empty_axes",
-                                  0))
-          return failure();
+  patterns.onOp("ReduceSumSquare", 1,
+                [](OpBinder binder, ConversionPatternRewriter &rewriter) {
+                  Torch::ValueTensorType resultType;
+                  Value data;
+                  int64_t keepDims, noop_with_empty_axes;
+                  if (binder.tensorOperandAtIndex(data, 0) ||
+                      binder.tensorResultType(resultType) ||
+                      binder.s64IntegerAttr(keepDims, "keepdims", 1) ||
+                      binder.s64IntegerAttr(noop_with_empty_axes,
+                                            "noop_with_empty_axes", 0))
+                    return failure();
 
-        Value dataSquare = rewriter.create<Torch::AtenMulTensorOp>(
-            binder.getLoc(), data.getType(), data, data);
+                  Value dataSquare = rewriter.create<Torch::AtenMulTensorOp>(
+                      binder.getLoc(), data.getType(), data, data);
 
-        return reducedSumImpl(binder, rewriter, dataSquare, resultType,
-                              /*storeValue=*/data, keepDims,
-                              noop_with_empty_axes, false);
+                  return reducedSumImpl(binder, rewriter, dataSquare,
+                                        resultType,
+                                        /*storeValue=*/dataSquare, keepDims,
+                                        noop_with_empty_axes, false);
                 });
   patterns.onOp(
       "ReduceMean", 1,
diff --git a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
index 47d76cea849b..bd096cb06205 100644
--- a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
+++ b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
@@ -1033,6 +1033,13 @@ func.func @test_reduce_sum_square_do_not_keepdims_example(%arg0: !torch.vtensor<
 
 // CHECK-LABEL: func.func @test_reduce_sum_square_empty_axes_input_noop_example
 func.func @test_reduce_sum_square_empty_axes_input_noop_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[3,2,2],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: %[[MULT:.+]] = torch.aten.mul.Tensor %arg0, %arg0 : !torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32> -> !torch.vtensor<[3,2,2],f32>
+  // CHECK: %[[INT0:.+]] = torch.constant.int 0
+  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct  : () -> !torch.list<int>
+  // CHECK: %[[TRUE:.+]] = torch.constant.bool true
+  // CHECK: %[[NONE:.+]] = torch.constant.none
+  // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[MULT]], %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[3,2,2],f32>
+  // CHECK: return %[[SUM]] : !torch.vtensor<[3,2,2],f32>
   %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64, torch.onnx.noop_with_empty_axes = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[3,2,2],f32>
   return %0 : !torch.vtensor<[3,2,2],f32>
 }
@@ -1090,24 +1097,6 @@ func.func @test_reduce_sum_square_keepdims_int_example(%arg0: !torch.vtensor<[3,
 
 // -----
 
-// CHECK-LABEL: func.func @test_reduce_sum_square_negative_axes_keepdims_example
-func.func @test_reduce_sum_square_negative_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],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: %[[MULT:.+]] = torch.aten.mul.Tensor %arg0, %arg0 : !torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32> -> !torch.vtensor<[3,2,2],f32>
-  // CHECK: %[[INT0:.+]] = torch.constant.int 0
-  // CHECK: %[[INT0_0:.+]] = torch.constant.int 0
-  // CHECK: %[[SELECT:.+]] = torch.aten.select.int %arg1, %[[INT0]], %[[INT0_0]] : !torch.vtensor<[1],si64>, !torch.int, !torch.int -> !torch.vtensor<[1],si64>
-  // CHECK: %[[ITEM:.+]] = torch.aten.item %[[SELECT]] : !torch.vtensor<[1],si64> -> !torch.int
-  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %[[ITEM]] : (!torch.int) -> !torch.list<int>
-  // CHECK: %[[TRUE:.+]] = torch.constant.bool true
-  // CHECK: %[[NONE:.+]] = torch.constant.none
-  // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[MULT]], %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[3,1,2],f32>
-  // CHECK: return %[[SUM]] : !torch.vtensor<[3,1,2],f32>
-  %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32>
-  return %0 : !torch.vtensor<[3,1,2],f32>
-}
-
-// -----
-
 // CHECK-LABEL: @test_reduce_mean_negative_axes_keepdims_example
 func.func @test_reduce_mean_negative_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64} {
   // CHECK:  %[[TENSOR:.+]] = torch.vtensor.literal(dense<-2> : tensor<1xsi64>) : !torch.vtensor<[1],si64>

From 4ff9f0dee89d554fa86fb5ab53aa671826d952b2 Mon Sep 17 00:00:00 2001
From: archana-ramalingam <archana.ramalingam@amd.com>
Date: Tue, 23 Apr 2024 19:20:27 +0000
Subject: [PATCH 07/16] Remove INT0

---
 test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir | 1 -
 1 file changed, 1 deletion(-)

diff --git a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
index bd096cb06205..7dc1bbbc357d 100644
--- a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
+++ b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
@@ -1034,7 +1034,6 @@ func.func @test_reduce_sum_square_do_not_keepdims_example(%arg0: !torch.vtensor<
 // CHECK-LABEL: func.func @test_reduce_sum_square_empty_axes_input_noop_example
 func.func @test_reduce_sum_square_empty_axes_input_noop_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[3,2,2],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: %[[MULT:.+]] = torch.aten.mul.Tensor %arg0, %arg0 : !torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32> -> !torch.vtensor<[3,2,2],f32>
-  // CHECK: %[[INT0:.+]] = torch.constant.int 0
   // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct  : () -> !torch.list<int>
   // CHECK: %[[TRUE:.+]] = torch.constant.bool true
   // CHECK: %[[NONE:.+]] = torch.constant.none

From c03d9b7a710622257fe9e743922c536b6675e34e Mon Sep 17 00:00:00 2001
From: archana-ramalingam <archana.ramalingam@amd.com>
Date: Wed, 24 Apr 2024 03:27:03 +0000
Subject: [PATCH 08/16] Fixing noop test example

---
 test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir | 8 +-------
 1 file changed, 1 insertion(+), 7 deletions(-)

diff --git a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
index 7dc1bbbc357d..d4e020621d79 100644
--- a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
+++ b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
@@ -866,7 +866,7 @@ func.func @test_reduce_max_attr(%arg0: !torch.vtensor<[4,2],i1>) -> !torch.vtens
 // -----
 
 // CHECK-LABEL: func.func @test_reduce_l1_default_axes_keepdims_example
-func.func @test_reduce_l1_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],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 = ""} {
+func.func @test_reduce_l1_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],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_torch.aten.mul.Tensormeta.producer_version = ""} {
   // CHECK: %[[ABS:.+]] = torch.aten.abs %arg0 : !torch.vtensor<[3,2,2],f32> -> !torch.vtensor<[3,2,2],f32>
   // CHECK: %[[INT0:.+]] = torch.constant.int 0
   // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct  : () -> !torch.list<int>
@@ -1033,12 +1033,6 @@ func.func @test_reduce_sum_square_do_not_keepdims_example(%arg0: !torch.vtensor<
 
 // CHECK-LABEL: func.func @test_reduce_sum_square_empty_axes_input_noop_example
 func.func @test_reduce_sum_square_empty_axes_input_noop_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[3,2,2],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: %[[MULT:.+]] = torch.aten.mul.Tensor %arg0, %arg0 : !torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32> -> !torch.vtensor<[3,2,2],f32>
-  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct  : () -> !torch.list<int>
-  // CHECK: %[[TRUE:.+]] = torch.constant.bool true
-  // CHECK: %[[NONE:.+]] = torch.constant.none
-  // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[MULT]], %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[3,2,2],f32>
-  // CHECK: return %[[SUM]] : !torch.vtensor<[3,2,2],f32>
   %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64, torch.onnx.noop_with_empty_axes = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[3,2,2],f32>
   return %0 : !torch.vtensor<[3,2,2],f32>
 }

From 8ebd3d9078fc92e1582c3066ce2d32a40e47a0bc Mon Sep 17 00:00:00 2001
From: archana-ramalingam <archana.ramalingam@amd.com>
Date: Wed, 24 Apr 2024 11:53:50 -0700
Subject: [PATCH 09/16] Remove failing noop example

---
 test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir | 8 --------
 1 file changed, 8 deletions(-)

diff --git a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
index a1b0165e2946..b5c4c814aac4 100644
--- a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
+++ b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
@@ -975,14 +975,6 @@ func.func @test_reduce_sum_square_do_not_keepdims_example(%arg0: !torch.vtensor<
 
 // -----
 
-// CHECK-LABEL: func.func @test_reduce_sum_square_empty_axes_input_noop_example
-func.func @test_reduce_sum_square_empty_axes_input_noop_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[3,2,2],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 = ""} {
-  %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64, torch.onnx.noop_with_empty_axes = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[3,2,2],f32>
-  return %0 : !torch.vtensor<[3,2,2],f32>
-}
-
-// -----
-
 // CHECK-LABEL: func.func @test_reduce_sum_square_empty_set_non_reduced_axis_zero
 func.func @test_reduce_sum_square_empty_set_non_reduced_axis_zero(%arg0: !torch.vtensor<[2,0,4],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,0,1],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: %[[MULT:.+]] = torch.aten.mul.Tensor %arg0, %arg0 : !torch.vtensor<[2,0,4],f32>, !torch.vtensor<[2,0,4],f32> -> !torch.vtensor<[2,0,4],f32>

From 7ae461077b4dcf426480387dea3e57a617f33e25 Mon Sep 17 00:00:00 2001
From: archana-ramalingam <archana.ramalingam@amd.com>
Date: Fri, 26 Apr 2024 09:47:27 -0700
Subject: [PATCH 10/16] Undo unintended change

---
 test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
index b5c4c814aac4..5d6bb9f213f2 100644
--- a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
+++ b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
@@ -711,7 +711,7 @@ func.func @test_reduce_max_attr(%arg0: !torch.vtensor<[4,2],i1>) -> !torch.vtens
 // -----
 
 // CHECK-LABEL: func.func @test_reduce_l1_default_axes_keepdims_example
-func.func @test_reduce_l1_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],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_torch.aten.mul.Tensormeta.producer_version = ""} {
+func.func @test_reduce_l1_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],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: %[[ABS:.+]] = torch.aten.abs %arg0 : !torch.vtensor<[3,2,2],f32> -> !torch.vtensor<[3,2,2],f32>
   // CHECK: %[[INT0:.+]] = torch.constant.int 0
   // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct  : () -> !torch.list<int>

From dfe642019732d98de2a0995e14f2a232e6238a2c Mon Sep 17 00:00:00 2001
From: archana-ramalingam <archana.ramalingam@amd.com>
Date: Thu, 18 Apr 2024 14:56:08 -0700
Subject: [PATCH 11/16] Rebasing with commit Add support for reducesumsquare op

---
 .../TorchOnnxToTorch/DefaultDomainQtoZ.cpp    | 19 +++++
 .../TorchOnnxToTorch/simple_ops_q_to_z.mlir   | 84 +++++++++++++++++++
 2 files changed, 103 insertions(+)

diff --git a/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp b/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
index 7d34f14b4e70..5d802f429703 100644
--- a/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
+++ b/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
@@ -988,6 +988,25 @@ void mlir::torch::onnx_c::populateDefaultDomainQtoZ(
                       binder.op, resultType, data);
                   return success();
                 });
+  patterns.onOp("ReduceSumSquare", 1,
+                [](OpBinder binder, ConversionPatternRewriter &rewriter) {
+                  Torch::ValueTensorType resultType;
+                  Value data;
+                  int64_t keepDims, noop_with_empty_axes;
+                  if (binder.tensorOperandAtIndex(operand, 0) ||
+                      binder.tensorResultType(resultType) ||
+                      binder.s64IntegerAttr(keepDims, "keepdims", 1) ||
+                      binder.s64IntegerAttr(noop_with_empty_axes,
+                                            "noop_with_empty_axes", 0))
+                    return failure();
+
+                  Value dataSquare = rewriter.create<Torch::AtenMulTensorOp>(
+                      binder.getLoc(), operand.getType(), data, data);
+
+                  return reducedSumImpl(binder, rewriter, data, resultType,
+                                        /*storeValue=*/data, keepDims,
+                                        noop_with_empty_axes, false);
+                });
   patterns.onOp(
       "ReduceMean", 1,
       [](OpBinder binder, ConversionPatternRewriter &rewriter) {
diff --git a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
index e3519a89a73e..648983d777c0 100644
--- a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
+++ b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
@@ -942,6 +942,90 @@ func.func @test_reduce_sum_negative_axes_keepdims_example(%arg0: !torch.vtensor<
 
 // -----
 
+// CHECK-LABEL: func.func @test_reduce_sum_square_default_axes_keepdims_example
+func.func @test_reduce_sum_square_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],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: %[[MULT:.+]] = torch.aten.mul.Tensor %arg0, %arg0 : !torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32> -> !torch.vtensor<[3,2,2],f32>
+  // CHECK: %[[INT0:.+]] = torch.constant.int 0
+  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct  : () -> !torch.list<int>
+  // CHECK: %[[TRUE:.+]] = torch.constant.bool true
+  // CHECK: %[[NONE:.+]] = torch.constant.none
+  // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[MULT]], %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,1,1],f32>
+  // CHECK: return %[[SUM]] : !torch.vtensor<[1,1,1],f32>
+  %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32>
+  return %0 : !torch.vtensor<[1,1,1],f32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_reduce_sum_square_do_not_keepdims_example
+func.func @test_reduce_sum_square_do_not_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],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: %[[MULT:.+]] = torch.aten.mul.Tensor %arg0, %arg0 : !torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32> -> !torch.vtensor<[3,2,2],f32>
+  // CHECK: %[[INT0:.+]] = torch.constant.int 0
+  // CHECK: %[[INT0_0:.+]] = torch.constant.int 0
+  // CHECK: %[[SELECT:.+]] = torch.aten.select.int %arg1, %[[INT0]], %[[INT0_0]] : !torch.vtensor<[1],si64>, !torch.int, !torch.int -> !torch.vtensor<[1],si64>
+  // CHECK: %[[ITEM:.+]] = torch.aten.item %[[SELECT]] : !torch.vtensor<[1],si64> -> !torch.int
+  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %[[ITEM]] : (!torch.int) -> !torch.list<int>
+  // CHECK: %[[FALSE:.+]] = torch.constant.bool false
+  // CHECK: %[[NONE:.+]] = torch.constant.none
+  // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[MULT]], %[[DIMS]], %[[FALSE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[3,2],f32>
+  // CHECK: return %[[SUM]] : !torch.vtensor<[3,2],f32>
+  %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32>
+  return %0 : !torch.vtensor<[3,2],f32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_reduce_sum_square_empty_set_non_reduced_axis_zero
+func.func @test_reduce_sum_square_empty_set_non_reduced_axis_zero(%arg0: !torch.vtensor<[2,0,4],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,0,1],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: %[[MULT:.+]] = torch.aten.mul.Tensor %arg0, %arg0 : !torch.vtensor<[2,0,4],f32>, !torch.vtensor<[2,0,4],f32> -> !torch.vtensor<[2,0,4],f32>
+  // CHECK: %[[INT2:.+]] = torch.constant.int 2
+  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %[[INT2]] : (!torch.int) -> !torch.list<int>
+  // CHECK: %[[TRUE:.+]] = torch.constant.bool true
+  // CHECK: %[[NONE:.+]] = torch.constant.none
+  // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[MULT]], %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[2,0,4],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[2,0,1],f32>
+  // CHECK: return %[[SUM]] : !torch.vtensor<[2,0,1],f32>
+  %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,0,1],f32>
+  return %0 : !torch.vtensor<[2,0,1],f32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_reduce_sum_square_keepdims_example
+func.func @test_reduce_sum_square_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],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: %[[MULT:.+]] = torch.aten.mul.Tensor %arg0, %arg0 : !torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32> -> !torch.vtensor<[3,2,2],f32>
+  // CHECK: %[[INT0:.+]] = torch.constant.int 0
+  // CHECK: %[[INT0_0:.+]] = torch.constant.int 0
+  // CHECK: %[[SELECT:.+]] = torch.aten.select.int %arg1, %[[INT0]], %[[INT0_0]] : !torch.vtensor<[1],si64>, !torch.int, !torch.int -> !torch.vtensor<[1],si64>
+  // CHECK: %[[ITEM:.+]] = torch.aten.item %[[SELECT]] : !torch.vtensor<[1],si64> -> !torch.int
+  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %[[ITEM]] : (!torch.int) -> !torch.list<int>
+  // CHECK: %[[TRUE:.+]] = torch.constant.bool true
+  // CHECK: %[[NONE:.+]] = torch.constant.none
+  // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[MULT]], %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[3,1,2],f32>
+  // CHECK: return %[[SUM]] : !torch.vtensor<[3,1,2],f32>
+  %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32>
+  return %0 : !torch.vtensor<[3,1,2],f32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_reduce_sum_square_keepdims_int_example
+func.func @test_reduce_sum_square_keepdims_int_example(%arg0: !torch.vtensor<[3,2,2],si64>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],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: %[[MULT:.+]] = torch.aten.mul.Tensor %arg0, %arg0 : !torch.vtensor<[3,2,2],si64>, !torch.vtensor<[3,2,2],si64> -> !torch.vtensor<[3,2,2],si64>
+  // CHECK: %[[INT0:.+]] = torch.constant.int 0
+  // CHECK: %[[INT0_0:.+]] = torch.constant.int 0
+  // CHECK: %[[SELECT:.+]] = torch.aten.select.int %arg1, %[[INT0]], %[[INT0_0]] : !torch.vtensor<[1],si64>, !torch.int, !torch.int -> !torch.vtensor<[1],si64>
+  // CHECK: %[[ITEM:.+]] = torch.aten.item %[[SELECT]] : !torch.vtensor<[1],si64> -> !torch.int
+  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %[[ITEM]] : (!torch.int) -> !torch.list<int>
+  // CHECK: %[[TRUE:.+]] = torch.constant.bool true
+  // CHECK: %[[NONE:.+]] = torch.constant.none
+  // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[MULT]], %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[3,2,2],si64>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[3,1,2],f32>
+  // CHECK: return %[[SUM]] : !torch.vtensor<[3,1,2],f32>
+  %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32>
+  return %0 : !torch.vtensor<[3,1,2],f32>
+}
+
+// -----
+
 // CHECK-LABEL: func.func @test_reduce_log_sum_default_axes_keepdims_example
 func.func @test_reduce_log_sum_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],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: %[[INT0:.+]] = torch.constant.int 0

From 3dc34e3d2ee93ec0b1ced10953ea577c6d79389f Mon Sep 17 00:00:00 2001
From: archana-ramalingam <archana.ramalingam@amd.com>
Date: Thu, 18 Apr 2024 15:21:57 -0700
Subject: [PATCH 12/16] Rebasing to commit Adding reducesumsquare op

---
 .../TorchOnnxToTorch/DefaultDomainQtoZ.cpp    | 41 ++++++++++---------
 1 file changed, 21 insertions(+), 20 deletions(-)

diff --git a/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp b/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
index 5d802f429703..ef48179a1114 100644
--- a/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
+++ b/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
@@ -946,22 +946,6 @@ void mlir::torch::onnx_c::populateDefaultDomainQtoZ(
             /*memory_format=*/noneVal);
         return success();
       });
-  patterns.onOp("ReduceSum", 1,
-                [](OpBinder binder, ConversionPatternRewriter &rewriter) {
-                  Torch::ValueTensorType resultType;
-                  Value data;
-                  int64_t keepDims, noop_with_empty_axes;
-                  if (binder.tensorOperandAtIndex(data, 0) ||
-                      binder.tensorResultType(resultType) ||
-                      binder.s64IntegerAttr(keepDims, "keepdims", 1) ||
-                      binder.s64IntegerAttr(noop_with_empty_axes,
-                                            "noop_with_empty_axes", 0))
-                    return failure();
-
-                  return reducedSumImpl(binder, rewriter, data, resultType,
-                                        /*storeValue=*/data, keepDims,
-                                        noop_with_empty_axes, false);
-                });
   patterns.onOp("ReduceLogSum", 1,
                 [](OpBinder binder, ConversionPatternRewriter &rewriter) {
                   Torch::ValueTensorType resultType;
@@ -988,12 +972,28 @@ void mlir::torch::onnx_c::populateDefaultDomainQtoZ(
                       binder.op, resultType, data);
                   return success();
                 });
+  patterns.onOp("ReduceSum", 1,
+                [](OpBinder binder, ConversionPatternRewriter &rewriter) {
+                  Torch::ValueTensorType resultType;
+                  Value data;
+                  int64_t keepDims, noop_with_empty_axes;
+                  if (binder.tensorOperandAtIndex(data, 0) ||
+                      binder.tensorResultType(resultType) ||
+                      binder.s64IntegerAttr(keepDims, "keepdims", 1) ||
+                      binder.s64IntegerAttr(noop_with_empty_axes,
+                                            "noop_with_empty_axes", 0))
+                    return failure();
+
+                  return reducedSumImpl(binder, rewriter, data, resultType,
+                                        /*storeValue=*/data, keepDims,
+                                        noop_with_empty_axes, false);
+                });
   patterns.onOp("ReduceSumSquare", 1,
                 [](OpBinder binder, ConversionPatternRewriter &rewriter) {
                   Torch::ValueTensorType resultType;
                   Value data;
                   int64_t keepDims, noop_with_empty_axes;
-                  if (binder.tensorOperandAtIndex(operand, 0) ||
+                  if (binder.tensorOperandAtIndex(data, 0) ||
                       binder.tensorResultType(resultType) ||
                       binder.s64IntegerAttr(keepDims, "keepdims", 1) ||
                       binder.s64IntegerAttr(noop_with_empty_axes,
@@ -1001,10 +1001,11 @@ void mlir::torch::onnx_c::populateDefaultDomainQtoZ(
                     return failure();
 
                   Value dataSquare = rewriter.create<Torch::AtenMulTensorOp>(
-                      binder.getLoc(), operand.getType(), data, data);
+                      binder.getLoc(), data.getType(), data, data);
 
-                  return reducedSumImpl(binder, rewriter, data, resultType,
-                                        /*storeValue=*/data, keepDims,
+                  return reducedSumImpl(binder, rewriter, dataSquare,
+                                        resultType,
+                                        /*storeValue=*/dataSquare, keepDims,
                                         noop_with_empty_axes, false);
                 });
   patterns.onOp(

From dd90ca87d10f8f7db656d0eb09cf3eb68a6686b8 Mon Sep 17 00:00:00 2001
From: archana-ramalingam <archana.ramalingam@amd.com>
Date: Thu, 18 Apr 2024 19:52:24 -0700
Subject: [PATCH 13/16] Rebasing to commit Replace operand with data

---
 lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp b/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
index ef48179a1114..68e6d00c0323 100644
--- a/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
+++ b/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
@@ -1005,7 +1005,7 @@ void mlir::torch::onnx_c::populateDefaultDomainQtoZ(
 
                   return reducedSumImpl(binder, rewriter, dataSquare,
                                         resultType,
-                                        /*storeValue=*/dataSquare, keepDims,
+                                        /*storeValue=*/data, keepDims,
                                         noop_with_empty_axes, false);
                 });
   patterns.onOp(

From d43b16512d65701babd0d86c08b954fc7470494f Mon Sep 17 00:00:00 2001
From: Ubuntu
 <archana@archana-cpu.judsoscro3wupi0qm4bjlj5m3b.bx.internal.cloudapp.net>
Date: Tue, 23 Apr 2024 02:20:44 +0000
Subject: [PATCH 14/16] Rebase to commit Fixing reviewed issues

---
 .../TorchOnnxToTorch/simple_ops_q_to_z.mlir   | 102 +++++++++---------
 1 file changed, 51 insertions(+), 51 deletions(-)

diff --git a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
index 648983d777c0..830a8523b212 100644
--- a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
+++ b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
@@ -860,6 +860,57 @@ func.func @test_reduce_l2_keep_dims_int_input_example(%arg0: !torch.vtensor<[3,2
 
 // -----
 
+// CHECK-LABEL: func.func @test_reduce_log_sum_default_axes_keepdims_example
+func.func @test_reduce_log_sum_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],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: %[[INT0:.+]] = torch.constant.int 0
+  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct  : () -> !torch.list<int>
+  // CHECK: %[[TRUE:.+]] = torch.constant.bool true
+  // CHECK: %[[NONE:.+]] = torch.constant.none
+  // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %arg0, %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,1,1],f32>
+  // CHECK: %[[LOG:.+]] = torch.aten.log %[[SUM]] : !torch.vtensor<[1,1,1],f32> -> !torch.vtensor<[1,1,1],f32>
+  // CHECK: return %[[LOG]] : !torch.vtensor<[1,1,1],f32>
+  %0 = torch.operator "onnx.ReduceLogSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32>
+  return %0 : !torch.vtensor<[1,1,1],f32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_reduce_log_sum_keep_dims_example
+func.func @test_reduce_log_sum_keep_dims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],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: %[[INT0:.+]] = torch.constant.int 0
+  // CHECK: %[[INT0_0:.+]] = torch.constant.int 0
+  // CHECK: %[[SELECT:.+]] = torch.aten.select.int %arg1, %[[INT0]], %[[INT0_0]] : !torch.vtensor<[1],si64>, !torch.int, !torch.int -> !torch.vtensor<[1],si64>
+  // CHECK: %[[ITEM:.+]] = torch.aten.item %[[SELECT]] : !torch.vtensor<[1],si64> -> !torch.int
+  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %[[ITEM]] : (!torch.int) -> !torch.list<int>
+  // CHECK: %[[TRUE:.+]] = torch.constant.bool true
+  // CHECK: %[[NONE:.+]] = torch.constant.none
+  // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %arg0, %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[3,2,1],f32>
+  // CHECK: %[[LOG:.+]] = torch.aten.log %[[SUM]] : !torch.vtensor<[3,2,1],f32> -> !torch.vtensor<[3,2,1],f32>
+  // CHECK: return %[[LOG]] : !torch.vtensor<[3,2,1],f32>
+  %0 = torch.operator "onnx.ReduceLogSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32>
+  return %0 : !torch.vtensor<[3,2,1],f32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_reduce_log_sum_do_not_keepdims_example
+func.func @test_reduce_log_sum_do_not_keepdims_example(%arg0:!torch.vtensor<[3,2,2],f32>, %arg1:!torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],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: %[[INT0:.+]] = torch.constant.int 0
+  // CHECK: %[[INT0_0:.+]] = torch.constant.int 0
+  // CHECK: %[[SELECT:.+]] = torch.aten.select.int %arg1, %[[INT0]], %[[INT0_0]] : !torch.vtensor<[1],si64>, !torch.int, !torch.int -> !torch.vtensor<[1],si64>
+  // CHECK: %[[ITEM:.+]] = torch.aten.item %[[SELECT]] : !torch.vtensor<[1],si64> -> !torch.int
+  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %[[ITEM]] : (!torch.int) -> !torch.list<int>
+  // CHECK: %[[FALSE:.+]] = torch.constant.bool false
+  // CHECK: %[[NONE:.+]] = torch.constant.none
+  // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %arg0, %[[DIMS]], %[[FALSE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[3,2],f32>
+  // CHECK: %[[LOG:.+]] = torch.aten.log %[[SUM]] : !torch.vtensor<[3,2],f32> -> !torch.vtensor<[3,2],f32>
+  // CHECK: return %[[LOG]] : !torch.vtensor<[3,2],f32>
+  %0 = torch.operator "onnx.ReduceLogSum"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32>
+  return %0 : !torch.vtensor<[3,2],f32>
+}
+
+// -----
+
 // CHECK-LABEL: func.func @test_reduce_sum_default_axes_keepdims_example
 func.func @test_reduce_sum_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> 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 = ""} {
   // CHECK: %[[INT0:.+]] = torch.constant.int 0
@@ -1026,57 +1077,6 @@ func.func @test_reduce_sum_square_keepdims_int_example(%arg0: !torch.vtensor<[3,
 
 // -----
 
-// CHECK-LABEL: func.func @test_reduce_log_sum_default_axes_keepdims_example
-func.func @test_reduce_log_sum_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],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: %[[INT0:.+]] = torch.constant.int 0
-  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct  : () -> !torch.list<int>
-  // CHECK: %[[TRUE:.+]] = torch.constant.bool true
-  // CHECK: %[[NONE:.+]] = torch.constant.none
-  // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %arg0, %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,1,1],f32>
-  // CHECK: %[[LOG:.+]] = torch.aten.log %[[SUM]] : !torch.vtensor<[1,1,1],f32> -> !torch.vtensor<[1,1,1],f32>
-  // CHECK: return %[[LOG]] : !torch.vtensor<[1,1,1],f32>
-  %0 = torch.operator "onnx.ReduceLogSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32>
-  return %0 : !torch.vtensor<[1,1,1],f32>
-}
-
-// -----
-
-// CHECK-LABEL: func.func @test_reduce_log_sum_keep_dims_example
-func.func @test_reduce_log_sum_keep_dims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],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: %[[INT0:.+]] = torch.constant.int 0
-  // CHECK: %[[INT0_0:.+]] = torch.constant.int 0
-  // CHECK: %[[SELECT:.+]] = torch.aten.select.int %arg1, %[[INT0]], %[[INT0_0]] : !torch.vtensor<[1],si64>, !torch.int, !torch.int -> !torch.vtensor<[1],si64>
-  // CHECK: %[[ITEM:.+]] = torch.aten.item %[[SELECT]] : !torch.vtensor<[1],si64> -> !torch.int
-  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %[[ITEM]] : (!torch.int) -> !torch.list<int>
-  // CHECK: %[[TRUE:.+]] = torch.constant.bool true
-  // CHECK: %[[NONE:.+]] = torch.constant.none
-  // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %arg0, %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[3,2,1],f32>
-  // CHECK: %[[LOG:.+]] = torch.aten.log %[[SUM]] : !torch.vtensor<[3,2,1],f32> -> !torch.vtensor<[3,2,1],f32>
-  // CHECK: return %[[LOG]] : !torch.vtensor<[3,2,1],f32>
-  %0 = torch.operator "onnx.ReduceLogSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32>
-  return %0 : !torch.vtensor<[3,2,1],f32>
-}
-
-// -----
-
-// CHECK-LABEL: func.func @test_reduce_log_sum_do_not_keepdims_example
-func.func @test_reduce_log_sum_do_not_keepdims_example(%arg0:!torch.vtensor<[3,2,2],f32>, %arg1:!torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],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: %[[INT0:.+]] = torch.constant.int 0
-  // CHECK: %[[INT0_0:.+]] = torch.constant.int 0
-  // CHECK: %[[SELECT:.+]] = torch.aten.select.int %arg1, %[[INT0]], %[[INT0_0]] : !torch.vtensor<[1],si64>, !torch.int, !torch.int -> !torch.vtensor<[1],si64>
-  // CHECK: %[[ITEM:.+]] = torch.aten.item %[[SELECT]] : !torch.vtensor<[1],si64> -> !torch.int
-  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %[[ITEM]] : (!torch.int) -> !torch.list<int>
-  // CHECK: %[[FALSE:.+]] = torch.constant.bool false
-  // CHECK: %[[NONE:.+]] = torch.constant.none
-  // CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %arg0, %[[DIMS]], %[[FALSE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[3,2],f32>
-  // CHECK: %[[LOG:.+]] = torch.aten.log %[[SUM]] : !torch.vtensor<[3,2],f32> -> !torch.vtensor<[3,2],f32>
-  // CHECK: return %[[LOG]] : !torch.vtensor<[3,2],f32>
-  %0 = torch.operator "onnx.ReduceLogSum"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32>
-  return %0 : !torch.vtensor<[3,2],f32>
-}
-
-// -----
-
 // CHECK-LABEL: @test_reduce_mean_negative_axes_keepdims_example
 func.func @test_reduce_mean_negative_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64} {
   // CHECK:  %[[TENSOR:.+]] = torch.vtensor.literal(dense<-2> : tensor<1xsi64>) : !torch.vtensor<[1],si64>

From 8e491c0dca89804d68c8d964db849e5ca3da28e1 Mon Sep 17 00:00:00 2001
From: archana-ramalingam <archana.ramalingam@amd.com>
Date: Wed, 24 Apr 2024 03:27:03 +0000
Subject: [PATCH 15/16] Rebase to commit Fixing noop test example

---
 test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
index 830a8523b212..63dfc04c7f44 100644
--- a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
+++ b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
@@ -711,7 +711,7 @@ func.func @test_reduce_max_attr(%arg0: !torch.vtensor<[4,2],i1>) -> !torch.vtens
 // -----
 
 // CHECK-LABEL: func.func @test_reduce_l1_default_axes_keepdims_example
-func.func @test_reduce_l1_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],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 = ""} {
+func.func @test_reduce_l1_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],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_torch.aten.mul.Tensormeta.producer_version = ""} {
   // CHECK: %[[ABS:.+]] = torch.aten.abs %arg0 : !torch.vtensor<[3,2,2],f32> -> !torch.vtensor<[3,2,2],f32>
   // CHECK: %[[INT0:.+]] = torch.constant.int 0
   // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct  : () -> !torch.list<int>

From 35acbb0fcb73a0bcb0c21bba57bb1e6e295d5db3 Mon Sep 17 00:00:00 2001
From: archana-ramalingam <archana.ramalingam@amd.com>
Date: Fri, 26 Apr 2024 09:47:27 -0700
Subject: [PATCH 16/16] Undo unintended change

---
 test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
index 63dfc04c7f44..830a8523b212 100644
--- a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
+++ b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
@@ -711,7 +711,7 @@ func.func @test_reduce_max_attr(%arg0: !torch.vtensor<[4,2],i1>) -> !torch.vtens
 // -----
 
 // CHECK-LABEL: func.func @test_reduce_l1_default_axes_keepdims_example
-func.func @test_reduce_l1_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],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_torch.aten.mul.Tensormeta.producer_version = ""} {
+func.func @test_reduce_l1_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],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: %[[ABS:.+]] = torch.aten.abs %arg0 : !torch.vtensor<[3,2,2],f32> -> !torch.vtensor<[3,2,2],f32>
   // CHECK: %[[INT0:.+]] = torch.constant.int 0
   // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct  : () -> !torch.list<int>