[torch-mlir][conversion-test] cleanup trailing whitespace in mlir fil…

…es (#2807)
llvm · Jan 25, 2024 · 0aed231 · 0aed231
1 parent fe836ce
commit 0aed231
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Showing 11 changed files with 47 additions and 47 deletions.
diff --git 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
@@ -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
@@ -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
@@ -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>