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>
 }