diff --git a/test/Conversion/TorchOnnxToTorch/simple_ops_a_to_f.mlir b/test/Conversion/TorchOnnxToTorch/simple_ops_a_to_f.mlir
index 77cdd5786ea8e..493cdc98312fe 100644
--- a/test/Conversion/TorchOnnxToTorch/simple_ops_a_to_f.mlir
+++ b/test/Conversion/TorchOnnxToTorch/simple_ops_a_to_f.mlir
@@ -1036,7 +1036,7 @@ func.func @test_exp(%arg0: !torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f3
 // -----
 
 // CHECK-LABEL: @test_expand_dim2_shape2
-func.func @test_expand_dim2_shape2(%arg0: !torch.vtensor<[1,4],f32>, %arg1: !torch.vtensor<[2],si32>) 
+func.func @test_expand_dim2_shape2(%arg0: !torch.vtensor<[1,4],f32>, %arg1: !torch.vtensor<[2],si32>)
               -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 9 : 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
@@ -1089,10 +1089,10 @@ func.func @test_expand_dim3_shape4(%arg0: !torch.vtensor<[1,3,1],f32>, %arg1: !t
   // CHECK: torch.aten.select.int %arg1, %int0, %int3 : !torch.vtensor<[4],si64>, !torch.int, !torch.int -> !torch.vtensor<[1],si64>
   // CHECK: torch.aten.item %6 : !torch.vtensor<[1],si64> -> !torch.int
   // CHECK: torch.prim.ListConstruct %1, %3, %5, %7 : (!torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list<int>
-  // CHECK: %9 = torch.aten.broadcast_to %arg0, %8 : !torch.vtensor<[1,3,1],f32>, !torch.list<int> -> !torch.vtensor<[3,3,3,3],f32>   
+  // CHECK: %9 = torch.aten.broadcast_to %arg0, %8 : !torch.vtensor<[1,3,1],f32>, !torch.list<int> -> !torch.vtensor<[3,3,3,3],f32>
   %0 = torch.operator "onnx.Expand"(%arg0, %arg1) : (!torch.vtensor<[1,3,1],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[3,3,3,3],f32>
   return %0 : !torch.vtensor<[3,3,3,3],f32>
-} 
+}
 
 // -----
 
diff --git a/test/Conversion/TorchOnnxToTorch/simple_ops_g_to_p.mlir b/test/Conversion/TorchOnnxToTorch/simple_ops_g_to_p.mlir
index 00d1355c46991..6a420300cdc92 100644
--- a/test/Conversion/TorchOnnxToTorch/simple_ops_g_to_p.mlir
+++ b/test/Conversion/TorchOnnxToTorch/simple_ops_g_to_p.mlir
@@ -160,8 +160,8 @@ func.func @test_gemm_alpha_beta(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.
 // -----
 
 // CHECK-LABEL : func.func @test_layer_norm
-func.func @test_layer_norm(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[3,4],f32>, %arg2: !torch.vtensor<[3,4],f32>) -> (!torch.vtensor<[3,4], f32>, !torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) 
-                           attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { 
+func.func @test_layer_norm(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[3,4],f32>, %arg2: !torch.vtensor<[3,4],f32>) -> (!torch.vtensor<[3,4], f32>, !torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>)
+                           attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
   // CHECK: %int3 = torch.constant.int 3
   // CHECK: %int4 = torch.constant.int 4
   // CHECK: %0 = torch.prim.ListConstruct %int3, %int4 : (!torch.int, !torch.int) -> !torch.list<int>
@@ -173,8 +173,8 @@ func.func @test_layer_norm(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtens
 // -----
 
 // CHECK-LABEL : func.func @test_layer_norm_single_result
-func.func @test_layer_norm_single_result(%arg0: !torch.vtensor<[1,4,768],f32>, %arg1: !torch.vtensor<[768],f32>, %arg2: !torch.vtensor<[768],f32>) -> (!torch.vtensor<[1,4,768], f32>) 
-                           attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { 
+func.func @test_layer_norm_single_result(%arg0: !torch.vtensor<[1,4,768],f32>, %arg1: !torch.vtensor<[768],f32>, %arg2: !torch.vtensor<[768],f32>) -> (!torch.vtensor<[1,4,768], f32>)
+                           attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
   // CHECK: %float9.999990e-06 = torch.constant.float 9.9999997473787516E-6
   // CHECK: %int768 = torch.constant.int 768
   // CHECK: %0 = torch.prim.ListConstruct %int768 : (!torch.int) -> !torch.list<int>
@@ -224,7 +224,7 @@ func.func @test_matmul_4d(%arg0: !torch.vtensor<[1,2,3,4],f32>, %arg1: !torch.vt
 
 // CHECK-LABEL: func.func @test_mul
   func.func @test_mul(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
-    // CHECK: torch.aten.mul.Tensor %arg0, %arg1 : !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32> -> !torch.vtensor<[3,4,5],f32> 
+    // CHECK: torch.aten.mul.Tensor %arg0, %arg1 : !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32> -> !torch.vtensor<[3,4,5],f32>
     %0 = torch.operator "onnx.Mul"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32>
     return %0 : !torch.vtensor<[3,4,5],f32>
   }
@@ -399,7 +399,7 @@ func.func @test_pad(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[4],
 // CHECK-LABEL: @test_hardsigmoid_example
 func.func @test_hardsigmoid_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 6 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
   // CHECK: %[[ALPHA_FLOAT:.*]] = torch.constant.float 5.000000e-01
-  // CHECK: %[[BETA_FLOAT:.*]] = torch.constant.float 0.60000002384185791 
+  // CHECK: %[[BETA_FLOAT:.*]] = torch.constant.float 0.60000002384185791
   // CHECK: %[[ALPHA_MULTI_X_PLUS_BETA:.*]] = torch.aten.add.Scalar %arg0, %[[BETA_FLOAT:.*]], %[[ALPHA_FLOAT:.*]] : !torch.vtensor<[3],f32>, !torch.float, !torch.float -> !torch.vtensor<[3],f32>
   // CHECK: %[[INT_1:.*]] = torch.constant.int 1
   // CHECK: %[[TENSOR_DIMENSION_LIST_FOR_ONE:.*]] = torch.prim.ListConstruct  : () -> !torch.list<int>
@@ -414,7 +414,7 @@ func.func @test_hardsigmoid_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vt
   // CHECK: %[[ZERO_TENSOR:.*]] = torch.aten.full %[[TENSOR_DIMENSION_LIST_FOR_ZERO:.*]], %[[INT_0:.*]], %[[INT_TYPE_FOR_TENSOR_ZERO:.*]], %[[NONE_FOR_ZERO:.*]], %none_0, %none_0 : !torch.list<int>, !torch.int, !torch.int, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[],f32>
   // CHECK: %[[RESULT:.*]] = torch.aten.maximum %[[ZERO_TENSOR:.*]], %[[MIN_EXPRESSION:.*]] : !torch.vtensor<[],f32>, !torch.vtensor<[3],f32> -> !torch.vtensor<[3],f32>
   // CHECK: return %[[RESULT:.*]] : !torch.vtensor<[3],f32>
-  
+
   %0 = torch.operator "onnx.HardSigmoid"(%arg0) {torch.onnx.alpha = 5.000000e-01 : f32, torch.onnx.beta = 6.000000e-01 : f32} : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32>
   return %0 : !torch.vtensor<[3],f32>
 }
diff --git a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
index b2128175d9d7e..918141065cc6c 100644
--- a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
+++ b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
@@ -931,7 +931,7 @@ func.func @test_split_2d_uneven_split_opset18(%arg0: !torch.vtensor<[2,8],f32>)
 }
 
 // -----
-  
+
 // CHECK-LABEL: func.func @test_tan
 func.func @test_tan(%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 = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
   // CHECK: %[[TAN:.+]] = torch.aten.tan %arg0
@@ -973,7 +973,7 @@ func.func @test_transpose_all_permutations_4(%arg0: !torch.vtensor<[2,3,4],f32>)
 // CHECK-LABEL: func.func @test_slice
 func.func @test_slice(%arg0: !torch.vtensor<[20,10,5],f32>, %arg1: !torch.vtensor<[2],si64>, %arg2: !torch.vtensor<[2],si64>, %arg3: !torch.vtensor<[2],si64>, %arg4: !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,10,5],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: %[[INDEX_TO_GRAB:.*]] = torch.constant.int 0
-  
+
   //CHECK: %[[CONST_0:.*]] = torch.constant.int 0
   //CHECK: %[[ZERO_INDEX_VEC:.*]] = torch.prim.NumToTensor.Scalar %[[CONST_0:.*]] : !torch.int -> !torch.vtensor<[1],si64>
   //CHECK: %[[STARTS_INDEX_VEC_0:.*]] = torch.aten.index_select %arg1, %[[INDEX_TO_GRAB:.*]], %[[ZERO_INDEX_VEC:.*]] : !torch.vtensor<[2],si64>, !torch.int, !torch.vtensor<[1],si64> -> !torch.vtensor<[1],si64>
@@ -985,7 +985,7 @@ func.func @test_slice(%arg0: !torch.vtensor<[20,10,5],f32>, %arg1: !torch.vtenso
   //CHECK: %[[STEPS_INDEX_VEC_0:.*]] = torch.aten.index_select %arg4, %[[INDEX_TO_GRAB:.*]], %[[ZERO_INDEX_VEC:.*]] : !torch.vtensor<[2],si64>, !torch.int, !torch.vtensor<[1],si64> -> !torch.vtensor<[1],si64>
   //CHECK: %[[STEPS_ELEMENT_0:.*]] = torch.aten.item %[[STEPS_INDEX_VEC_0:.*]] : !torch.vtensor<[1],si64> -> !torch.int
   //CHECK: %[[SLICE_0:.*]] = torch.aten.slice.Tensor %arg0, %[[AXES_ELEMENT_0:.*]], %[[STARTS_ELEMENT_0:.*]], %[[ENDS_ELEMENT_0:.*]], %[[STEPS_ELEMENT_0:.*]] : !torch.vtensor<[20,10,5],f32>, !torch.int, !torch.int, !torch.int, !torch.int -> !torch.vtensor<[?,10,5],f32>
-  
+
   //CHECK: %[[CONST_1:.*]] = torch.constant.int 1
   //CHECK: %[[ONE_INDEX_VEC:.*]] = torch.prim.NumToTensor.Scalar %[[CONST_1:.*]] : !torch.int -> !torch.vtensor<[1],si64>
   //CHECK: %[[STARTS_INDEX_VEC_1:.*]] = torch.aten.index_select %arg1, %[[INDEX_TO_GRAB:.*]], %[[ONE_INDEX_VEC:.*]] : !torch.vtensor<[2],si64>, !torch.int, !torch.vtensor<[1],si64> -> !torch.vtensor<[1],si64>
@@ -1013,7 +1013,7 @@ func.func @test_slice_default_axes_and_slices(%arg0: !torch.vtensor<[20,10,5],f3
     //CHECK: %[[DEFAULT_SIZE_INPUT:.*]] = torch.prim.ListConstruct %[[DEFAULT_SIZE_AMOUNT:.*]] : (!torch.int) -> !torch.list<int>
     //CHECK: %[[DEFAULT_SIZES:.*]] = torch.aten.ones %[[DEFAULT_SIZE_INPUT:.*]], %[[NONE_2:.*]], %[[NONE_2:.*]], %[[NONE_2:.*]], %[[NONE_2:.*]] : !torch.list<int>, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[3],si64>
     //CHECK: %[[INDEX_TO_GRAB:.*]] = torch.constant.int 0
-    
+
     //CHECK: %[[CONST_0:.*]] = torch.constant.int 0
     //CHECK: %[[ZERO_INDEX_VEC:.*]] = torch.prim.NumToTensor.Scalar %[[CONST_0:.*]] : !torch.int -> !torch.vtensor<[1],si64>
     //CHECK: %[[STARTS_INDEX_VEC_0:.*]] = torch.aten.index_select %arg1, %[[INDEX_TO_GRAB:.*]], %[[ZERO_INDEX_VEC:.*]] : !torch.vtensor<[3],si64>, !torch.int, !torch.vtensor<[1],si64> -> !torch.vtensor<[1],si64>
@@ -1025,7 +1025,7 @@ func.func @test_slice_default_axes_and_slices(%arg0: !torch.vtensor<[20,10,5],f3
     //CHECK: %[[STEPS_INDEX_VEC_0:.*]] = torch.aten.index_select %[[DEFAULT_SIZES:.*]], %[[INDEX_TO_GRAB:.*]], %[[ZERO_INDEX_VEC:.*]] : !torch.vtensor<[3],si64>, !torch.int, !torch.vtensor<[1],si64> -> !torch.vtensor<[1],si64>
     //CHECK: %[[STEPS_ELEMENT_0:.*]] = torch.aten.item %[[STEPS_INDEX_VEC_0:.*]] : !torch.vtensor<[1],si64> -> !torch.int
     //CHECK: %[[SLICE_0:.*]] = torch.aten.slice.Tensor %arg0, %[[AXES_ELEMENT_0:.*]], %[[STARTS_ELEMENT_0:.*]], %[[ENDS_ELEMENT_0:.*]], %[[STEPS_ELEMENT_0:.*]] : !torch.vtensor<[20,10,5],f32>, !torch.int, !torch.int, !torch.int, !torch.int -> !torch.vtensor<[20,10,?],f32>
-    
+
     //CHECK: %[[CONST_1:.*]] = torch.constant.int 1
     //CHECK: %[[ONE_INDEX_VEC:.*]] = torch.prim.NumToTensor.Scalar %[[CONST_1:.*]] : !torch.int -> !torch.vtensor<[1],si64>
     //CHECK: %[[STARTS_INDEX_VEC_1:.*]] = torch.aten.index_select %arg1, %[[INDEX_TO_GRAB:.*]], %[[ONE_INDEX_VEC:.*]] : !torch.vtensor<[3],si64>, !torch.int, !torch.vtensor<[1],si64> -> !torch.vtensor<[1],si64>
@@ -1037,7 +1037,7 @@ func.func @test_slice_default_axes_and_slices(%arg0: !torch.vtensor<[20,10,5],f3
     //CHECK: %[[STEPS_INDEX_VEC_1:.*]] = torch.aten.index_select %[[DEFAULT_SIZES:.*]], %[[INDEX_TO_GRAB:.*]], %[[ONE_INDEX_VEC:.*]] : !torch.vtensor<[3],si64>, !torch.int, !torch.vtensor<[1],si64> -> !torch.vtensor<[1],si64>
     //CHECK: %[[STEPS_ELEMENT_1:.*]] = torch.aten.item %[[STEPS_INDEX_VEC_1:.*]] : !torch.vtensor<[1],si64> -> !torch.int
     //CHECK: %[[TWO_INDEX_VEC:.*]] = torch.aten.slice.Tensor %[[SLICE_0:.*]], %[[AXES_ELEMENT_1:.*]], %[[STARTS_ELEMENT_1:.*]], %[[ENDS_ELEMENT_1:.*]], %[[STEPS_ELEMENT_1:.*]] : !torch.vtensor<[20,10,?],f32>, !torch.int, !torch.int, !torch.int, !torch.int -> !torch.vtensor<[20,10,?],f32>
-    
+
     //CHECK: %[[CONST_2:.*]] = torch.constant.int 2
     //CHECK: %[[TWO_INDEX_VEC:.*]] = torch.prim.NumToTensor.Scalar %[[CONST_2:.*]] : !torch.int -> !torch.vtensor<[1],si64>
     //CHECK: %[[STARTS_INDEX_VEC_2:.*]] = torch.aten.index_select %arg1, %[[INDEX_TO_GRAB:.*]], %[[TWO_INDEX_VEC:.*]] : !torch.vtensor<[3],si64>, !torch.int, !torch.vtensor<[1],si64> -> !torch.vtensor<[1],si64>
@@ -1062,7 +1062,7 @@ func.func @test_slice_default_steps(%arg0: !torch.vtensor<[20,10,5],f32>, %arg1:
     //CHECK: %[[DEFAULT_SIZE_INPUT:.*]] = torch.prim.ListConstruct %[[DEFAULT_SIZE_AMOUNT:.*]] : (!torch.int) -> !torch.list<int>
     //CHECK: %[[DEFAULT_SIZES:.*]] = torch.aten.ones %[[DEFAULT_SIZE_INPUT:.*]], %[[NONE:.*]], %[[NONE:.*]], %[[NONE:.*]], %[[NONE:.*]] : !torch.list<int>, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[3],si64>
     //CHECK: %[[INDEX_TO_GRAB:.*]] = torch.constant.int 0
-    
+
     //CHECK: %[[CONST_0:.*]] = torch.constant.int 0
     //CHECK: %[[ZERO_INDEX_VEC:.*]] = torch.prim.NumToTensor.Scalar %[[CONST_0:.*]] : !torch.int -> !torch.vtensor<[1],si64>
     //CHECK: %[[STARTS_INDEX_VEC_0:.*]] = torch.aten.index_select %arg1, %[[INDEX_TO_GRAB:.*]], %[[ZERO_INDEX_VEC:.*]] : !torch.vtensor<[3],si64>, !torch.int, !torch.vtensor<[1],si64> -> !torch.vtensor<[1],si64>
@@ -1074,7 +1074,7 @@ func.func @test_slice_default_steps(%arg0: !torch.vtensor<[20,10,5],f32>, %arg1:
     //CHECK: %[[STEPS_INDEX_VEC_0:.*]] = torch.aten.index_select %[[DEFAULT_SIZES:.*]], %[[INDEX_TO_GRAB:.*]], %[[ZERO_INDEX_VEC:.*]] : !torch.vtensor<[3],si64>, !torch.int, !torch.vtensor<[1],si64> -> !torch.vtensor<[1],si64>
     //CHECK: %[[STEPS_ELEMENT_0:.*]] = torch.aten.item %[[STEPS_INDEX_VEC_0:.*]] : !torch.vtensor<[1],si64> -> !torch.int
     //CHECK: %[[SLICE_0:.*]] = torch.aten.slice.Tensor %arg0, %[[AXES_ELEMENT_0:.*]], %[[STARTS_ELEMENT_0:.*]], %[[ENDS_ELEMENT_0:.*]], %[[STEPS_ELEMENT_0:.*]] : !torch.vtensor<[20,10,5],f32>, !torch.int, !torch.int, !torch.int, !torch.int -> !torch.vtensor<[20,10,?],f32>
-    
+
     //CHECK: %[[CONST_1:.*]] = torch.constant.int 1
     //CHECK: %[[ONE_INDEX_VEC:.*]] = torch.prim.NumToTensor.Scalar %[[CONST_1:.*]] : !torch.int -> !torch.vtensor<[1],si64>
     //CHECK: %[[STARTS_INDEX_VEC_1:.*]] = torch.aten.index_select %arg1, %[[INDEX_TO_GRAB:.*]], %[[ONE_INDEX_VEC:.*]] : !torch.vtensor<[3],si64>, !torch.int, !torch.vtensor<[1],si64> -> !torch.vtensor<[1],si64>
@@ -1086,7 +1086,7 @@ func.func @test_slice_default_steps(%arg0: !torch.vtensor<[20,10,5],f32>, %arg1:
     //CHECK: %[[STEPS_INDEX_VEC_1:.*]] = torch.aten.index_select %[[DEFAULT_SIZES:.*]], %[[INDEX_TO_GRAB:.*]], %[[ONE_INDEX_VEC:.*]] : !torch.vtensor<[3],si64>, !torch.int, !torch.vtensor<[1],si64> -> !torch.vtensor<[1],si64>
     //CHECK: %[[STEPS_ELEMENT_1:.*]] = torch.aten.item %[[STEPS_INDEX_VEC_1:.*]] : !torch.vtensor<[1],si64> -> !torch.int
     //CHECK: %[[TWO_INDEX_VEC:.*]] = torch.aten.slice.Tensor %[[SLICE_0:.*]], %[[AXES_ELEMENT_1:.*]], %[[STARTS_ELEMENT_1:.*]], %[[ENDS_ELEMENT_1:.*]], %[[STEPS_ELEMENT_1:.*]] : !torch.vtensor<[20,10,?],f32>, !torch.int, !torch.int, !torch.int, !torch.int -> !torch.vtensor<[20,10,?],f32>
-    
+
     //CHECK: %[[CONST_1:.*]] = torch.constant.int 2
     //CHECK: %[[TWO_INDEX_VEC:.*]] = torch.prim.NumToTensor.Scalar %[[CONST_1:.*]] : !torch.int -> !torch.vtensor<[1],si64>
     //CHECK: %[[STARTS_INDEX_VEC_2:.*]] = torch.aten.index_select %arg1, %[[INDEX_TO_GRAB:.*]], %[[TWO_INDEX_VEC:.*]] : !torch.vtensor<[3],si64>, !torch.int, !torch.vtensor<[1],si64> -> !torch.vtensor<[1],si64>
@@ -1339,7 +1339,7 @@ func.func @test_reshape_zero_and_negative_dim(%arg0: !torch.vtensor<[2,3,4],f32>
     // CHECK: torch.aten.arange.start_step %0, %1, %2, %none, %none, %none, %none : !torch.int, !torch.int, !torch.int, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[2],si64>
     %0 = torch.operator "onnx.Range"(%arg0, %arg1, %arg2) : (!torch.vtensor<[],si64>, !torch.vtensor<[],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[2],si64>
     return %0 : !torch.vtensor<[2],si64>
-  } 
+  }
 
 // -----
 
@@ -1352,7 +1352,7 @@ func.func @test_reshape_zero_and_negative_dim(%arg0: !torch.vtensor<[2,3,4],f32>
     // CHECK: torch.aten.arange.start_step %0, %1, %2, %none, %none, %none, %none : !torch.int, !torch.int, !torch.int, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[2],si32>
     %0 = torch.operator "onnx.Range"(%arg0, %arg1, %arg2) : (!torch.vtensor<[],si32>, !torch.vtensor<[],si32>, !torch.vtensor<[],si32>) -> !torch.vtensor<[2],si32>
     return %0 : !torch.vtensor<[2],si32>
-  } 
+  }
 
 // -----
 
@@ -1375,7 +1375,7 @@ func.func @test_reshape_zero_and_negative_dim(%arg0: !torch.vtensor<[2,3,4],f32>
     // CHECK: return %[[RESULTS]]#0, %[[RESULTS]]#1 : !torch.vtensor<[3,3],f32>, !torch.vtensor<[3,3],si64>
     %0:2 = torch.operator "onnx.TopK"(%arg0, %arg1) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],si64>) -> (!torch.vtensor<[3,3],f32>, !torch.vtensor<[3,3],si64>)
     return %0#0, %0#1 : !torch.vtensor<[3,3],f32>, !torch.vtensor<[3,3],si64>
-  } 
+  }
 
 // -----
 
diff --git a/test/Conversion/TorchOnnxToTorch/unsupported_fb_opt_ops.mlir b/test/Conversion/TorchOnnxToTorch/unsupported_fb_opt_ops.mlir
index 6659935ffa6fc..0a8bbfe1a8e3c 100644
--- a/test/Conversion/TorchOnnxToTorch/unsupported_fb_opt_ops.mlir
+++ b/test/Conversion/TorchOnnxToTorch/unsupported_fb_opt_ops.mlir
@@ -11,8 +11,8 @@ func.func @cast_operation(%arg0: !torch.vtensor<[?,?,?,?],si64>) -> !torch.vtens
 }
 
 // -----
-func.func @div_operation(%arg0: !torch.vtensor<[1,64,768],f32>, 
-                          %arg1: !torch.vtensor<[1,64,1],f32>) 
+func.func @div_operation(%arg0: !torch.vtensor<[1,64,768],f32>,
+                          %arg1: !torch.vtensor<[1,64,1],f32>)
                           -> !torch.vtensor<[1,64,768],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
   %209 = torch.operator "onnx.Div"(%arg0, %arg1) : (!torch.vtensor<[1,64,768],f32>, !torch.vtensor<[1,64,1],f32>) -> !torch.vtensor<[1,64,768],f32>
   return %209 : !torch.vtensor<[1,64,768],f32>
@@ -22,8 +22,8 @@ func.func @div_operation(%arg0: !torch.vtensor<[1,64,768],f32>,
 // Fixed.
 // this is the onnx opset 1 version of Equal, only int types.
 // this used to fail to legalize because the "since" value is set unecessarily high (19)
-func.func @equal_operation(%arg0: !torch.vtensor<[4],si64>, 
-                            %arg1: !torch.vtensor<[4],si64>) 
+func.func @equal_operation(%arg0: !torch.vtensor<[4],si64>,
+                            %arg1: !torch.vtensor<[4],si64>)
                             -> !torch.vtensor<[4],i1> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 1 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
   %205 = torch.operator "onnx.Equal"(%arg0, %arg1) : (!torch.vtensor<[4],si64>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[4],i1>
   return %205 : !torch.vtensor<[4],i1>
@@ -40,8 +40,8 @@ func.func @reduce_mean_operation(%arg0: !torch.vtensor<[1,64,768],f32>)
 
 // -----
 // Fixed.
-func.func @cumsum_operation(%arg0: !torch.vtensor<[2,3],f64>, 
-                            %arg1: !torch.vtensor<[],si32>) 
+func.func @cumsum_operation(%arg0: !torch.vtensor<[2,3],f64>,
+                            %arg1: !torch.vtensor<[],si32>)
                             -> !torch.vtensor<[2,3],f64> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
   %212 = torch.operator "onnx.CumSum"(%arg0, %arg1) : (!torch.vtensor<[2,3],f64>, !torch.vtensor<[],si32>) -> !torch.vtensor<[2,3],f64>
   return %212 : !torch.vtensor<[2,3],f64>
diff --git a/test/Conversion/TorchToLinalg/basic.mlir b/test/Conversion/TorchToLinalg/basic.mlir
index 486b8b641dfd1..cfb252cd104a8 100644
--- a/test/Conversion/TorchToLinalg/basic.mlir
+++ b/test/Conversion/TorchToLinalg/basic.mlir
@@ -45,7 +45,7 @@ func.func @torch.aten.matmul.2d(%arg0: !torch.vtensor<[8,16],f32>, %arg1: !torch
 
 // CHECK-LABEL: func.func @torch.aten.mm$basic_strict(
 // CHECK-NOT: assert
-func.func @torch.aten.mm$basic_strict(%arg0: !torch.vtensor<[?,?],f32>, %arg1: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[?,2],f32> 
+func.func @torch.aten.mm$basic_strict(%arg0: !torch.vtensor<[?,?],f32>, %arg1: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[?,2],f32>
   attributes {torch.assume_strict_symbolic_shapes}
 {
   %0 = torch.aten.mm %arg0, %arg1 : !torch.vtensor<[?,?],f32>, !torch.vtensor<[?,?],f32> -> !torch.vtensor<[?,2],f32>
@@ -56,7 +56,7 @@ func.func @torch.aten.mm$basic_strict(%arg0: !torch.vtensor<[?,?],f32>, %arg1: !
 
 // CHECK-LABEL: func.func @torch.aten.mm$basic_unsigned(
 // CHECK: linalg.matmul_unsigned
-func.func @torch.aten.mm$basic_unsigned(%arg0: !torch.vtensor<[?,?],ui32>, %arg1: !torch.vtensor<[?,?],ui32>) -> !torch.vtensor<[?,2],ui32> 
+func.func @torch.aten.mm$basic_unsigned(%arg0: !torch.vtensor<[?,?],ui32>, %arg1: !torch.vtensor<[?,?],ui32>) -> !torch.vtensor<[?,2],ui32>
   attributes {torch.assume_strict_symbolic_shapes}
 {
   %0 = torch.aten.mm %arg0, %arg1 : !torch.vtensor<[?,?],ui32>, !torch.vtensor<[?,?],ui32> -> !torch.vtensor<[?,2],ui32>
@@ -324,7 +324,7 @@ func.func @torch.aten.cat$convert(%arg0: !torch.vtensor<[?,?],f32>, %arg1: !torc
 // -----
 
 // CHECK-LABEL:   func.func @torch.aten.cat(
-// CHECK-SAME:                              %[[ARG_0:.*]]: !torch.vtensor<[?,?],f32>, 
+// CHECK-SAME:                              %[[ARG_0:.*]]: !torch.vtensor<[?,?],f32>,
 // CHECK-SAME:                              %[[ARG_1:.*]]: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[?,?],f32> {
 // CHECK:           %int0 = torch.constant.int 0
 // CHECK:           %[[VAL_0:.*]] = torch.prim.ListConstruct %[[ARG_0]], %[[ARG_1]] : (!torch.vtensor<[?,?],f32>, !torch.vtensor<[?,?],f32>) -> !torch.list<vtensor>
diff --git a/test/Conversion/TorchToLinalg/pooling.mlir b/test/Conversion/TorchToLinalg/pooling.mlir
index 70f543ad4f74c..8ed75f648f5ef 100644
--- a/test/Conversion/TorchToLinalg/pooling.mlir
+++ b/test/Conversion/TorchToLinalg/pooling.mlir
@@ -50,13 +50,13 @@ func.func @forward_max_pool3d(%arg0: !torch.vtensor<[?,?,?,?,?],f32>) -> !torch.
   %dilation1 = torch.constant.int 3
   %dilation2 = torch.constant.int 3
   %dilation3 = torch.constant.int 3
-  
+
   %false = torch.constant.bool false
   %kernel_size = torch.prim.ListConstruct %kernel_size1, %kernel_size2, %kernel_size3 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int>
   %stride = torch.prim.ListConstruct %stride1, %stride2, %stride3 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int>
   %padding = torch.prim.ListConstruct %padding1, %padding2, %padding3 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int>
   %dilation = torch.prim.ListConstruct %dilation1, %dilation2, %dilation3 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int>
-  
+
   %4 = torch.aten.max_pool3d %arg0, %kernel_size, %stride, %padding, %dilation, %false : !torch.vtensor<[?,?,?,?,?],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool -> !torch.vtensor<[?,?,?,?,?],f32>
 
   // CHECK: %[[MIN_VALUE:.*]] = arith.constant 0xFF800000 : f32
@@ -64,13 +64,13 @@ func.func @forward_max_pool3d(%arg0: !torch.vtensor<[?,?,?,?,?],f32>) -> !torch.
   // CHECK-NEXT: ^bb0(%{{.*}}: index, %{{.*}}: index, %{{.*}}: index, %{{.*}}: index, %{{.*}}: index):
   // CHECK-NEXT:  tensor.yield %[[MIN_VALUE:.*]] : f32
   // CHECK: } : tensor<?x?x?x?x?xf32> to tensor<?x?x?x?x?xf32>
-  
+
   // CHECK: %[[OUTPUT_TENSOR:.*]] = linalg.fill ins(%[[MIN_VALUE:.*]] : f32) outs(%{{.*}} : tensor<?x?x?x?x?xf32>) -> tensor<?x?x?x?x?xf32>
   // CHECK: %[[MAX_3D_POOL:.*]] = linalg.generic {indexing_maps = [#map, #map1, #map2], iterator_types = ["parallel", "parallel", "parallel", "parallel", "parallel", "reduction", "reduction", "reduction"]} ins(%[[PADDED_INPUT_TENSOR:.*]], %{{.*}} : tensor<?x?x?x?x?xf32>, tensor<?x?x?xf32>) outs(%[[OUTPUT_TENSOR:.*]] : tensor<?x?x?x?x?xf32>) {
   // CHECK-NEXT:  ^bb0(%[[CURRENT_VALUE:.*]]: f32, %[[KERNEL:.*]]: f32, %[[ACC_OUT:.*]]: f32):
   // CHECK-NEXT:    %[[MAXF:.*]] = arith.maximumf %[[CURRENT_VALUE:.*]], %[[ACC_OUT:.*]] : f32
   // CHECK-NEXT:    linalg.yield %[[MAXF:.*]] : f32
   // CHECK:  } -> tensor<?x?x?x?x?xf32>
-  
+
   return %4 : !torch.vtensor<[?,?,?,?,?],f32>
 }
diff --git a/test/Conversion/TorchToLinalg/view.mlir b/test/Conversion/TorchToLinalg/view.mlir
index 83424a17d8435..4f9c1f867ee40 100644
--- a/test/Conversion/TorchToLinalg/view.mlir
+++ b/test/Conversion/TorchToLinalg/view.mlir
@@ -148,8 +148,8 @@ func.func @torch.aten.view$expandInferredDim(%arg0: !torch.vtensor<[2,6],f32>) -
 // CHECK: return %[[BUILTIN_TENSOR_CAST]] : !torch.vtensor<[2,3,5,?,6],f32>
 
 // [10,3,?,2,3] -> [30,?,6] -> [2,3,5,?,6]
-// Associations are, 
-//  -- for collapse, [0,1], [2], [3,4] and 
+// Associations are,
+//  -- for collapse, [0,1], [2], [3,4] and
 //  -- for expand [0,1,2], [3], [4].
 func.func @torch.aten.view$singleUnknownMatches0(%arg0: !torch.vtensor<[10,3,?,2,3],f32>) -> !torch.vtensor<[2,3,5,?,6],f32> {
     %int3 = torch.constant.int 3
diff --git a/test/Conversion/TorchToStablehlo/basic.mlir b/test/Conversion/TorchToStablehlo/basic.mlir
index 51e3e6f9bdbb3..e0ab6bf1502bf 100644
--- a/test/Conversion/TorchToStablehlo/basic.mlir
+++ b/test/Conversion/TorchToStablehlo/basic.mlir
@@ -281,7 +281,7 @@ func.func @torch.aten.cat$convert(%arg0: !torch.vtensor<[?,?],f32>, %arg1: !torc
 // -----
 
 // CHECK-LABEL:   func.func @torch.aten.cat(
-// CHECK-SAME:                              %[[ARG_0:.*]]: !torch.vtensor<[?,?],f32>, 
+// CHECK-SAME:                              %[[ARG_0:.*]]: !torch.vtensor<[?,?],f32>,
 // CHECK-SAME:                              %[[ARG_1:.*]]: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[?,?],f32> {
 // CHECK:           %int0 = torch.constant.int 0
 // CHECK:           %[[VAL_0:.*]] = torch.prim.ListConstruct %[[ARG_0]], %[[ARG_1]] : (!torch.vtensor<[?,?],f32>, !torch.vtensor<[?,?],f32>) -> !torch.list<vtensor>
diff --git a/test/Conversion/TorchToStablehlo/linear.mlir b/test/Conversion/TorchToStablehlo/linear.mlir
index b9bac97ca6c95..7f253a98df045 100644
--- a/test/Conversion/TorchToStablehlo/linear.mlir
+++ b/test/Conversion/TorchToStablehlo/linear.mlir
@@ -269,7 +269,7 @@ func.func @torch.aten.mm$proj(%arg0: !torch.vtensor<[?,256],f32>) -> !torch.vten
 // -----
 
 // CHECK-LABEL:   func.func @torch.aten.convolution(
-// CHECK-SAME:                                 %[[ARG_0:.*]]: !torch.vtensor<[?,?,?,?],f32>, 
+// CHECK-SAME:                                 %[[ARG_0:.*]]: !torch.vtensor<[?,?,?,?],f32>,
 // CHECK-SAME:                                 %[[ARG_1:.*]]: !torch.vtensor<[?,?,3,3],f32>) -> !torch.vtensor<[?,?,?,?],f32> {
 // CHECK:           %[[T_0:.*]] = torch_c.to_builtin_tensor %[[ARG_0]] : !torch.vtensor<[?,?,?,?],f32> -> tensor<?x?x?x?xf32>
 // CHECK:           %[[T_1:.*]] = torch_c.to_builtin_tensor %[[ARG_1]] : !torch.vtensor<[?,?,3,3],f32> -> tensor<?x?x3x3xf32>
@@ -306,7 +306,7 @@ func.func @torch.aten.convolution(%arg0: !torch.vtensor<[?,?,?,?],f32>, %arg1: !
 // -----
 
 // CHECK-LABEL:   func.func @torch.aten.convolution$bias(
-// CHECK-SAME:                                           %[[ARG_0:.*]]: !torch.vtensor<[?,?,?,?],f32>, %[[ARG_1:.*]]: !torch.vtensor<[?,?,3,3],f32>, 
+// CHECK-SAME:                                           %[[ARG_0:.*]]: !torch.vtensor<[?,?,?,?],f32>, %[[ARG_1:.*]]: !torch.vtensor<[?,?,3,3],f32>,
 // CHECK-SAME:                                           %[[ARG_2:.*]]: !torch.vtensor<[?],f32>) -> !torch.vtensor<[?,?,?,?],f32> {
 // CHECK:           %[[T_0:.*]] = torch_c.to_builtin_tensor %[[ARG_0]] : !torch.vtensor<[?,?,?,?],f32> -> tensor<?x?x?x?xf32>
 // CHECK:           %[[T_1:.*]] = torch_c.to_builtin_tensor %[[ARG_1]] : !torch.vtensor<[?,?,3,3],f32> -> tensor<?x?x3x3xf32>
@@ -349,7 +349,7 @@ func.func @torch.aten.convolution$bias(%arg0: !torch.vtensor<[?,?,?,?],f32>, %ar
 // -----
 
 // CHECK-LABEL:   func.func @torch.aten.convolution$transposed_basic(
-// CHECK-SAME:                                                       %[[ARG_0:.*]]: !torch.vtensor<[1,2,7,7],f32>, 
+// CHECK-SAME:                                                       %[[ARG_0:.*]]: !torch.vtensor<[1,2,7,7],f32>,
 // CHECK-SAME:                                                       %[[ARG_1:.*]]: !torch.vtensor<[2,4,3,3],f32>) -> !torch.vtensor<[1,4,9,9],f32> {
 // CHECK:           %[[T_0:.*]] = torch_c.to_builtin_tensor %[[ARG_0]] : !torch.vtensor<[1,2,7,7],f32> -> tensor<1x2x7x7xf32>
 // CHECK:           %[[T_1:.*]] = torch_c.to_builtin_tensor %[[ARG_1]] : !torch.vtensor<[2,4,3,3],f32> -> tensor<2x4x3x3xf32>
@@ -380,7 +380,7 @@ func.func @torch.aten.convolution$transposed_basic(%arg0: !torch.vtensor<[1,2,7,
 // -----
 
 // CHECK-LABEL:   func.func @torch.aten.convolution$transposed_stride(
-// CHECK-SAME:                                                        %[[ARG_0:.*]]: !torch.vtensor<[1,2,7,7],f32>, 
+// CHECK-SAME:                                                        %[[ARG_0:.*]]: !torch.vtensor<[1,2,7,7],f32>,
 // CHECK-SAME:                                                        %[[ARG_1:.*]]: !torch.vtensor<[2,4,3,3],f32>) -> !torch.vtensor<[1,4,15,15],f32> {
 // CHECK:           %[[T_0:.*]] = torch_c.to_builtin_tensor %[[ARG_0]] : !torch.vtensor<[1,2,7,7],f32> -> tensor<1x2x7x7xf32>
 // CHECK:           %[[T_1:.*]] = torch_c.to_builtin_tensor %[[ARG_1]] : !torch.vtensor<[2,4,3,3],f32> -> tensor<2x4x3x3xf32>
@@ -415,7 +415,7 @@ func.func @torch.aten.convolution$transposed_stride(%arg0: !torch.vtensor<[1,2,7
 // -----
 
 // CHECK-LABEL:   func.func @torch.aten.convolution$transposed_outputpadding(
-// CHECK-SAME:                                                               %[[ARG_0:.*]]: !torch.vtensor<[1,2,7,7],f32>, 
+// CHECK-SAME:                                                               %[[ARG_0:.*]]: !torch.vtensor<[1,2,7,7],f32>,
 // CHECK-SAME:                                                               %[[ARG_1:.*]]: !torch.vtensor<[2,4,3,3],f32>) -> !torch.vtensor<[1,4,16,16],f32> {
 // CHECK:           %[[T_0:.*]] = torch_c.to_builtin_tensor %[[ARG_0]] : !torch.vtensor<[1,2,7,7],f32> -> tensor<1x2x7x7xf32>
 // CHECK:           %[[T_1:.*]] = torch_c.to_builtin_tensor %[[ARG_1]] : !torch.vtensor<[2,4,3,3],f32> -> tensor<2x4x3x3xf32>
@@ -450,7 +450,7 @@ func.func @torch.aten.convolution$transposed_outputpadding(%arg0: !torch.vtensor
 // -----
 
 // CHECK-LABEL:   func.func @torch.aten.convolution$transposed_groups(
-// CHECK-SAME:                                                        %[[ARG_0:.*]]: !torch.vtensor<[1,2,7,7],f32>, 
+// CHECK-SAME:                                                        %[[ARG_0:.*]]: !torch.vtensor<[1,2,7,7],f32>,
 // CHECK-SAME:                                                        %[[ARG_1:.*]]: !torch.vtensor<[2,2,3,3],f32>) -> !torch.vtensor<[1,4,15,15],f32> {
 // CHECK:           %[[T_0:.*]] = torch_c.to_builtin_tensor %[[ARG_0]] : !torch.vtensor<[1,2,7,7],f32> -> tensor<1x2x7x7xf32>
 // CHECK:           %[[T_1:.*]] = torch_c.to_builtin_tensor %[[ARG_1]] : !torch.vtensor<[2,2,3,3],f32> -> tensor<2x2x3x3xf32>
@@ -485,7 +485,7 @@ func.func @torch.aten.convolution$transposed_outputpadding(%arg0: !torch.vtensor
 // CHECK:           %[[T_15:.*]] = stablehlo.transpose %[[T_14]], dims = [0, 1, 3, 2, 4] : (tensor<3x3x2x2x1xf32>) -> tensor<3x3x2x2x1xf32>
 // CHECK:           %from_elements_3 = tensor.from_elements %[[T_8]], %[[T_9]], %[[T_13]], %[[T_12]] : tensor<4xi64>
 // CHECK:           %[[T_16:.*]] = stablehlo.dynamic_reshape %[[T_15]], %from_elements_3 : (tensor<3x3x2x2x1xf32>, tensor<4xi64>) -> tensor<3x3x4x1xf32>
-// CHECK:           %[[T_17:.*]] = stablehlo.convolution(%[[T_0]], %[[T_16]]) 
+// CHECK:           %[[T_17:.*]] = stablehlo.convolution(%[[T_0]], %[[T_16]])
 // CHECK{LITERAL}:          dim_numbers = [b, f, 0, 1]x[0, 1, o, i]->[b, f, 0, 1], window = {stride = [1, 1], pad = [[2, 2], [2, 2]], lhs_dilate = [2, 2], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 2 : i64} : (tensor<1x2x7x7xf32>, tensor<3x3x4x1xf32>) -> tensor<1x4x15x15xf32>
 // CHECK:           %[[T_18:.*]] = torch_c.from_builtin_tensor %[[T_17]] : tensor<1x4x15x15xf32> -> !torch.vtensor<[1,4,15,15],f32>
 // CHECK:           return %[[T_18]] : !torch.vtensor<[1,4,15,15],f32>
diff --git a/test/Conversion/TorchToStablehlo/pooling.mlir b/test/Conversion/TorchToStablehlo/pooling.mlir
index 426a435424779..fd531006d614f 100644
--- a/test/Conversion/TorchToStablehlo/pooling.mlir
+++ b/test/Conversion/TorchToStablehlo/pooling.mlir
@@ -50,7 +50,7 @@ func.func @torch.aten.max_pool2d(%arg0: !torch.vtensor<[?,?,?,?],f32>) -> !torch
 // CHECK:           ^bb0(%[[VAL_8:.*]]: tensor<f32>, %[[VAL_9:.*]]: tensor<f32>):
 // CHECK:             %[[VAL_10:.*]] = stablehlo.maximum %[[VAL_8]], %[[VAL_9]] : tensor<f32>
 // CHECK:             stablehlo.return %[[VAL_10]] : tensor<f32>
-// CHECK:           }) 
+// CHECK:           })
 // CHECK-SAME{LITERAL}:  {padding = dense<[[0, 0], [0, 0], [2, 2], [1, 1]]> : tensor<4x2xi64>, window_dilations = dense<[1, 1, 2, 1]> : tensor<4xi64>, window_dimensions = dense<[1, 1, 2, 2]> : tensor<4xi64>, window_strides = dense<1> : tensor<4xi64>} : (tensor<?x?x?x?xf32>, tensor<f32>) -> tensor<?x?x?x?xf32>
 // CHECK:           %[[VAL_7:.*]] = torch_c.from_builtin_tensor %[[VAL_6]] : tensor<?x?x?x?xf32> -> !torch.vtensor<[?,?,?,?],f32>
 // CHECK:           return %[[VAL_7]] : !torch.vtensor<[?,?,?,?],f32>
diff --git a/test/Conversion/TorchToTosa/conv2d_transpose.mlir b/test/Conversion/TorchToTosa/conv2d_transpose.mlir
index 678034cb8405d..7f0d5e2ab25bf 100644
--- a/test/Conversion/TorchToTosa/conv2d_transpose.mlir
+++ b/test/Conversion/TorchToTosa/conv2d_transpose.mlir
@@ -12,7 +12,7 @@ func.func @forward(%input: !torch.vtensor<[1,64,1,100],f32>) -> !torch.vtensor<[
   %stride = torch.prim.ListConstruct %int2, %int2 : (!torch.int, !torch.int) -> !torch.list<int>
   %int1x1 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<int>
   // expected-error@+1 {{failed to legalize operation 'torch.aten.convolution' that was explicitly marked illegal}}
-  %output = torch.aten.convolution %input, %weight, %bias, %stride, %int1x1, %int1x1, %true, %int1x1, %int1 : !torch.vtensor<[1,64,1,100],f32>, !torch.vtensor<[64,64,3,3],f32>, !torch.vtensor<[64],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[1,64,2,200],f32> 
+  %output = torch.aten.convolution %input, %weight, %bias, %stride, %int1x1, %int1x1, %true, %int1x1, %int1 : !torch.vtensor<[1,64,1,100],f32>, !torch.vtensor<[64,64,3,3],f32>, !torch.vtensor<[64],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[1,64,2,200],f32>
   return %output : !torch.vtensor<[1,64,2,200],f32>
 }