[mlir][NFC] Update textual references of func to func.func in IR/Interface tests

The special case parsing of `func` operations is being removed.

Author: River707

mlir/test/Dialect/traits.mlir

@@ -3,15 +3,15 @@
 // Verify that ops with broadcastable trait verifies operand and result type
 // combinations and emits an error for invalid combinations.
 
-func @broadcast_scalar_scalar_scalar(tensor<i32>, tensor<i32>) -> tensor<i32> {
+func.func @broadcast_scalar_scalar_scalar(tensor<i32>, tensor<i32>) -> tensor<i32> {
 ^bb0(%arg0: tensor<i32>, %arg1: tensor<i32>):
   %0 = "test.broadcastable"(%arg0, %arg1) : (tensor<i32>, tensor<i32>) -> tensor<i32>
   return %0 : tensor<i32>
 }
 
 // -----
 
-func @broadcast_tensor_scalar_tensor(tensor<4xi32>, tensor<i32>) -> tensor<4xi32> {
+func.func @broadcast_tensor_scalar_tensor(tensor<4xi32>, tensor<i32>) -> tensor<4xi32> {
 ^bb0(%arg0: tensor<4xi32>, %arg1: tensor<i32>):
   %0 = "test.broadcastable"(%arg0, %arg1) : (tensor<4xi32>, tensor<i32>) -> tensor<4xi32>
   return %0 : tensor<4xi32>
@@ -20,7 +20,7 @@ func @broadcast_tensor_scalar_tensor(tensor<4xi32>, tensor<i32>) -> tensor<4xi32
 // -----
 
 // Check only one dimension has size 1
-func @broadcast_tensor_tensor_tensor(tensor<4x3x2xi32>, tensor<3x1xi32>) -> tensor<4x3x2xi32> {
+func.func @broadcast_tensor_tensor_tensor(tensor<4x3x2xi32>, tensor<3x1xi32>) -> tensor<4x3x2xi32> {
 ^bb0(%arg0: tensor<4x3x2xi32>, %arg1: tensor<3x1xi32>):
   %0 = "test.broadcastable"(%arg0, %arg1) : (tensor<4x3x2xi32>, tensor<3x1xi32>) -> tensor<4x3x2xi32>
   return %0 : tensor<4x3x2xi32>
@@ -29,7 +29,7 @@ func @broadcast_tensor_tensor_tensor(tensor<4x3x2xi32>, tensor<3x1xi32>) -> tens
 // -----
 
 // Check multiple dimensions have size 1
-func @broadcast_tensor_tensor_tensor(tensor<8x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x6x5xi32> {
+func.func @broadcast_tensor_tensor_tensor(tensor<8x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x6x5xi32> {
 ^bb0(%arg0: tensor<8x1x6x1xi32>, %arg1: tensor<7x1x5xi32>):
   %0 = "test.broadcastable"(%arg0, %arg1) : (tensor<8x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x6x5xi32>
   return %0 : tensor<8x7x6x5xi32>
@@ -38,7 +38,7 @@ func @broadcast_tensor_tensor_tensor(tensor<8x1x6x1xi32>, tensor<7x1x5xi32>) ->
 // -----
 
 // Check leading unknown dimension
-func @broadcast_tensor_tensor_tensor(tensor<?x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<?x7x6x5xi32> {
+func.func @broadcast_tensor_tensor_tensor(tensor<?x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<?x7x6x5xi32> {
 ^bb0(%arg0: tensor<?x1x6x1xi32>, %arg1: tensor<7x1x5xi32>):
   %0 = "test.broadcastable"(%arg0, %arg1) : (tensor<?x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<?x7x6x5xi32>
   return %0 : tensor<?x7x6x5xi32>
@@ -47,7 +47,7 @@ func @broadcast_tensor_tensor_tensor(tensor<?x1x6x1xi32>, tensor<7x1x5xi32>) ->
 // -----
 
 // Check unknown dimension in the middle
-func @broadcast_tensor_tensor_tensor(tensor<8x1x?x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x?x5xi32> {
+func.func @broadcast_tensor_tensor_tensor(tensor<8x1x?x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x?x5xi32> {
 ^bb0(%arg0: tensor<8x1x?x1xi32>, %arg1: tensor<7x1x5xi32>):
   %0 = "test.broadcastable"(%arg0, %arg1) : (tensor<8x1x?x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x?x5xi32>
   return %0 : tensor<8x7x?x5xi32>
@@ -56,7 +56,7 @@ func @broadcast_tensor_tensor_tensor(tensor<8x1x?x1xi32>, tensor<7x1x5xi32>) ->
 // -----
 
 // Check incompatible vector and tensor result type
-func @broadcast_scalar_vector_vector(tensor<4xf32>, tensor<4xf32>) -> vector<4xf32> {
+func.func @broadcast_scalar_vector_vector(tensor<4xf32>, tensor<4xf32>) -> vector<4xf32> {
 ^bb0(%arg0: tensor<4xf32>, %arg1: tensor<4xf32>):
   // expected-error @+1 {{op result #0 must be tensor of any type values, but got 'vector<4xf32>'}}
   %0 = "test.broadcastable"(%arg0, %arg1) : (tensor<4xf32>, tensor<4xf32>) -> vector<4xf32>
@@ -66,7 +66,7 @@ func @broadcast_scalar_vector_vector(tensor<4xf32>, tensor<4xf32>) -> vector<4xf
 // -----
 
 // Check incompatible operand types with known dimension
-func @broadcast_tensor_tensor_tensor(tensor<4x3x2xi32>, tensor<3x3xi32>) -> tensor<4x3x2xi32> {
+func.func @broadcast_tensor_tensor_tensor(tensor<4x3x2xi32>, tensor<3x3xi32>) -> tensor<4x3x2xi32> {
 ^bb0(%arg0: tensor<4x3x2xi32>, %arg1: tensor<3x3xi32>):
   // expected-error @+1 {{operands don't have broadcast-compatible shapes}}
   %0 = "test.broadcastable"(%arg0, %arg1) : (tensor<4x3x2xi32>, tensor<3x3xi32>) -> tensor<4x3x2xi32>
@@ -76,7 +76,7 @@ func @broadcast_tensor_tensor_tensor(tensor<4x3x2xi32>, tensor<3x3xi32>) -> tens
 // -----
 
 // Check incompatible result type with known dimension
-func @broadcast_tensor_tensor_tensor(tensor<4x3x2xi32>, tensor<3x1xi32>) -> tensor<4x3x3xi32> {
+func.func @broadcast_tensor_tensor_tensor(tensor<4x3x2xi32>, tensor<3x1xi32>) -> tensor<4x3x3xi32> {
 ^bb0(%arg0: tensor<4x3x2xi32>, %arg1: tensor<3x1xi32>):
   // expected-error @+1 {{op result type '4x3x3' not broadcast compatible with broadcasted operands's shapes '4x3x2'}}
   %0 = "test.broadcastable"(%arg0, %arg1) : (tensor<4x3x2xi32>, tensor<3x1xi32>) -> tensor<4x3x3xi32>
@@ -86,7 +86,7 @@ func @broadcast_tensor_tensor_tensor(tensor<4x3x2xi32>, tensor<3x1xi32>) -> tens
 // -----
 
 // Check incompatible result type with known dimension
-func @broadcast_tensor_tensor_tensor(tensor<8x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x6x1xi32> {
+func.func @broadcast_tensor_tensor_tensor(tensor<8x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x6x1xi32> {
 ^bb0(%arg0: tensor<8x1x6x1xi32>, %arg1: tensor<7x1x5xi32>):
   // expected-error @+1 {{op result type '8x7x6x1' not broadcast compatible with broadcasted operands's shapes '8x7x6x5'}}
   %0 = "test.broadcastable"(%arg0, %arg1) : (tensor<8x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x6x1xi32>
@@ -95,31 +95,31 @@ func @broadcast_tensor_tensor_tensor(tensor<8x1x6x1xi32>, tensor<7x1x5xi32>) ->
 
 // -----
 
-func @broadcast_tensor_tensor_tensor(tensor<2xi32>, tensor<2xi32>) -> tensor<*xi32> {
+func.func @broadcast_tensor_tensor_tensor(tensor<2xi32>, tensor<2xi32>) -> tensor<*xi32> {
 ^bb0(%arg0: tensor<2xi32>, %arg1: tensor<2xi32>):
   %0 = "test.broadcastable"(%arg0, %arg1) : (tensor<2xi32>, tensor<2xi32>) -> tensor<*xi32>
   return %0 : tensor<*xi32>
 }
 
 // -----
 
-func @broadcast_tensor_tensor_tensor(tensor<4x3x2xi32>, tensor<?xi32>) -> tensor<4x3x2xi32> {
+func.func @broadcast_tensor_tensor_tensor(tensor<4x3x2xi32>, tensor<?xi32>) -> tensor<4x3x2xi32> {
 ^bb0(%arg0: tensor<4x3x2xi32>, %arg1: tensor<?xi32>):
   %0 = "test.broadcastable"(%arg0, %arg1) : (tensor<4x3x2xi32>, tensor<?xi32>) -> tensor<4x3x2xi32>
   return %0 : tensor<4x3x2xi32>
 }
 
 // -----
 
-func @broadcast_tensor_tensor_tensor(%arg0: tensor<?x6x1xi32>, %arg1: tensor<*xi32>) -> tensor<?x6x6xi32> {
+func.func @broadcast_tensor_tensor_tensor(%arg0: tensor<?x6x1xi32>, %arg1: tensor<*xi32>) -> tensor<?x6x6xi32> {
   %0 = "test.broadcastable"(%arg0, %arg1) : (tensor<?x6x1xi32>, tensor<*xi32>) -> tensor<?x6x6xi32>
   return %0 : tensor<?x6x6xi32>
 }
 
 // -----
 
 // Unranked operands but ranked result
-func @broadcast_tensor_tensor_tensor(tensor<*xi32>, tensor<*xi32>) -> tensor<2xi32> {
+func.func @broadcast_tensor_tensor_tensor(tensor<*xi32>, tensor<*xi32>) -> tensor<2xi32> {
 ^bb0(%arg0: tensor<*xi32>, %arg1: tensor<*xi32>):
   %0 = "test.broadcastable"(%arg0, %arg1) : (tensor<*xi32>, tensor<*xi32>) -> tensor<2xi32>
   return %0 : tensor<2xi32>
@@ -128,15 +128,15 @@ func @broadcast_tensor_tensor_tensor(tensor<*xi32>, tensor<*xi32>) -> tensor<2xi
 // -----
 
 // Unranked operand and compatible ranked result
-func @broadcast_tensor_tensor_tensor(tensor<3x2xi32>, tensor<*xi32>) -> tensor<4x3x2xi32> {
+func.func @broadcast_tensor_tensor_tensor(tensor<3x2xi32>, tensor<*xi32>) -> tensor<4x3x2xi32> {
 ^bb0(%arg0: tensor<3x2xi32>, %arg1: tensor<*xi32>):
   %0 = "test.broadcastable"(%arg0, %arg0, %arg1) : (tensor<3x2xi32>, tensor<3x2xi32>, tensor<*xi32>) -> tensor<4x3x2xi32>
   return %0 : tensor<4x3x2xi32>
 }
 
 // -----
 
-func @broadcast_tensor_tensor_tensor(tensor<3x2xi32>, tensor<*xi32>) -> tensor<2xi32> {
+func.func @broadcast_tensor_tensor_tensor(tensor<3x2xi32>, tensor<*xi32>) -> tensor<2xi32> {
 ^bb0(%arg0: tensor<3x2xi32>, %arg1: tensor<*xi32>):
   // expected-error @+1 {{op result type '2' not broadcast compatible with broadcasted operands's shapes '3x2'}}
   %0 = "test.broadcastable"(%arg0, %arg1) : (tensor<3x2xi32>, tensor<*xi32>) -> tensor<2xi32>
@@ -145,15 +145,15 @@ func @broadcast_tensor_tensor_tensor(tensor<3x2xi32>, tensor<*xi32>) -> tensor<2
 
 // -----
 
-func @broadcast_tensor_tensor_tensor(tensor<?x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x6x5xi32> {
+func.func @broadcast_tensor_tensor_tensor(tensor<?x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x6x5xi32> {
 ^bb0(%arg0: tensor<?x1x6x1xi32>, %arg1: tensor<7x1x5xi32>):
   %0 = "test.broadcastable"(%arg0, %arg1) : (tensor<?x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x6x5xi32>
   return %0 : tensor<8x7x6x5xi32>
 }
 
 // -----
 
-func @broadcastDifferentResultType(tensor<4xi32>, tensor<4xi32>) -> tensor<4xi1> {
+func.func @broadcastDifferentResultType(tensor<4xi32>, tensor<4xi32>) -> tensor<4xi1> {
 ^bb0(%arg0: tensor<4xi32>, %arg1: tensor<4xi32>):
   %0 = "test.broadcastable"(%arg0, %arg1) : (tensor<4xi32>, tensor<4xi32>) -> tensor<4xi1>
   return %0 : tensor<4xi1>