NFC: Fix remaining usages of MulOp as matrix multiplication.

MulOp now represents an element-wise multiplication instead of a matrix multiplication.

PiperOrigin-RevId: 275886774

14 files changed, 149 insertions, 131 deletions

diff --git a/mlir/test/Examples/Toy/Ch1/ast.toy b/mlir/test/Examples/Toy/Ch1/ast.toy
index 72dec050811..df6e1a60ca9 100644
--- a/mlir/test/Examples/Toy/Ch1/ast.toy
+++ b/mlir/test/Examples/Toy/Ch1/ast.toy
@@ -2,7 +2,7 @@
 
 # User defined generic function that operates on unknown shaped arguments.
 def multiply_transpose(a, b) {
-  return a * transpose(b);
+  return transpose(a) * transpose(b);
 }
 
 def main() {
@@ -35,10 +35,12 @@ def main() {
 # CHECK-NEXT:       Params: [a, b]
 # CHECK-NEXT:       Block {
 # CHECK-NEXT:         Return
-# CHECK-NEXT:           BinOp: * @{{.*}}ast.toy:5:14
-# CHECK-NEXT:             var: a @{{.*}}ast.toy:5:10
-# CHECK-NEXT:             Call 'transpose' [ @{{.*}}ast.toy:5:14
-# CHECK-NEXT:               var: b @{{.*}}ast.toy:5:24
+# CHECK-NEXT:           BinOp: * @{{.*}}ast.toy:5:25
+# CHECK-NEXT:             Call 'transpose' [ @{{.*}}ast.toy:5:10
+# CHECK-NEXT:               var: a @{{.*}}ast.toy:5:20
+# CHECK-NEXT:             ]
+# CHECK-NEXT:             Call 'transpose' [ @{{.*}}ast.toy:5:25
+# CHECK-NEXT:               var: b @{{.*}}ast.toy:5:35
 # CHECK-NEXT:             ]
 # CHECK-NEXT:       } // Block
 # CHECK-NEXT:     Function
diff --git a/mlir/test/Examples/Toy/Ch2/ast.toy b/mlir/test/Examples/Toy/Ch2/ast.toy
index 993e2fde6fa..55b9efc7314 100644
--- a/mlir/test/Examples/Toy/Ch2/ast.toy
+++ b/mlir/test/Examples/Toy/Ch2/ast.toy
@@ -2,7 +2,7 @@
 
 # User defined generic function that operates on unknown shaped arguments.
 def multiply_transpose(a, b) {
-  return a * transpose(b);
+  return transpose(a) * transpose(b);
 }
 
 def main() {
@@ -35,10 +35,12 @@ def main() {
 # CHECK-NEXT:       Params: [a, b]
 # CHECK-NEXT:       Block {
 # CHECK-NEXT:         Return
-# CHECK-NEXT:           BinOp: * @{{.*}}ast.toy:5:14
-# CHECK-NEXT:             var: a @{{.*}}ast.toy:5:10
-# CHECK-NEXT:             Call 'transpose' [ @{{.*}}ast.toy:5:14
-# CHECK-NEXT:               var: b @{{.*}}ast.toy:5:24
+# CHECK-NEXT:           BinOp: * @{{.*}}ast.toy:5:25
+# CHECK-NEXT:             Call 'transpose' [ @{{.*}}ast.toy:5:10
+# CHECK-NEXT:               var: a @{{.*}}ast.toy:5:20
+# CHECK-NEXT:             ]
+# CHECK-NEXT:             Call 'transpose' [ @{{.*}}ast.toy:5:25
+# CHECK-NEXT:               var: b @{{.*}}ast.toy:5:35
 # CHECK-NEXT:             ]
 # CHECK-NEXT:       } // Block
 # CHECK-NEXT:     Function
diff --git a/mlir/test/Examples/Toy/Ch2/codegen.toy b/mlir/test/Examples/Toy/Ch2/codegen.toy
index 1eb46fd3425..e4f20aa2a47 100644
--- a/mlir/test/Examples/Toy/Ch2/codegen.toy
+++ b/mlir/test/Examples/Toy/Ch2/codegen.toy
@@ -2,7 +2,7 @@
 
 # User defined generic function that operates on unknown shaped arguments
 def multiply_transpose(a, b) {
-  return a * transpose(b);
+  return transpose(a) * transpose(b);
 }
 
 def main() {
@@ -13,19 +13,19 @@ def main() {
   print(d);
 }
 
-# CHECK-LABEL:   func @multiply_transpose(
-# CHECK-SAME:                             [[VAL_0:%.*]]: tensor<*xf64>, [[VAL_1:%.*]]: tensor<*xf64>)
-# CHECK-NEXT:    attributes  {toy.generic} {
-# CHECK-NEXT:     [[VAL_2:%.*]] = "toy.transpose"([[VAL_1]]) : (tensor<*xf64>) -> tensor<*xf64>
-# CHECK-NEXT:     [[VAL_3:%.*]] = "toy.mul"([[VAL_0]], [[VAL_2]]) : (tensor<*xf64>, tensor<*xf64>) -> tensor<*xf64>
-# CHECK-NEXT:     "toy.return"([[VAL_3]]) : (tensor<*xf64>) -> ()
+# CHECK-LABEL: func @multiply_transpose(
+# CHECK-SAME:                           [[VAL_0:%.*]]: tensor<*xf64>, [[VAL_1:%.*]]: tensor<*xf64>) -> tensor<*xf64>
+# CHECK:         [[VAL_2:%.*]] = "toy.transpose"([[VAL_0]]) : (tensor<*xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    [[VAL_3:%.*]] = "toy.transpose"([[VAL_1]]) : (tensor<*xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    [[VAL_4:%.*]] = "toy.mul"([[VAL_2]], [[VAL_3]]) : (tensor<*xf64>, tensor<*xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    "toy.return"([[VAL_4]]) : (tensor<*xf64>) -> ()
 
-# CHECK-LABEL:   func @main() {
-# CHECK-NEXT:     [[VAL_4:%.*]] = "toy.constant"() {value = dense<{{\[\[}}1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64>
-# CHECK-NEXT:     [[VAL_5:%.*]] = "toy.reshape"([[VAL_4]]) : (tensor<2x3xf64>) -> tensor<2x3xf64>
-# CHECK-NEXT:     [[VAL_6:%.*]] = "toy.constant"() {value = dense<[1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00, 5.000000e+00, 6.000000e+00]> : tensor<6xf64>} : () -> tensor<6xf64>
-# CHECK-NEXT:     [[VAL_7:%.*]] = "toy.reshape"([[VAL_6]]) : (tensor<6xf64>) -> tensor<2x3xf64>
-# CHECK-NEXT:     [[VAL_8:%.*]] = "toy.generic_call"([[VAL_5]], [[VAL_7]]) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
-# CHECK-NEXT:     [[VAL_9:%.*]] = "toy.generic_call"([[VAL_7]], [[VAL_5]]) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
-# CHECK-NEXT:     "toy.print"([[VAL_9]]) : (tensor<*xf64>) -> ()
-# CHECK-NEXT:     "toy.return"() : () -> ()
+# CHECK-LABEL: func @main()
+# CHECK-NEXT:    [[VAL_5:%.*]] = "toy.constant"() {value = dense<{{\[\[}}1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64>
+# CHECK-NEXT:    [[VAL_6:%.*]] = "toy.reshape"([[VAL_5]]) : (tensor<2x3xf64>) -> tensor<2x3xf64>
+# CHECK-NEXT:    [[VAL_7:%.*]] = "toy.constant"() {value = dense<[1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00, 5.000000e+00, 6.000000e+00]> : tensor<6xf64>} : () -> tensor<6xf64>
+# CHECK-NEXT:    [[VAL_8:%.*]] = "toy.reshape"([[VAL_7]]) : (tensor<6xf64>) -> tensor<2x3xf64>
+# CHECK-NEXT:    [[VAL_9:%.*]] = "toy.generic_call"([[VAL_6]], [[VAL_8]]) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    [[VAL_10:%.*]] = "toy.generic_call"([[VAL_8]], [[VAL_6]]) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    "toy.print"([[VAL_10]]) : (tensor<*xf64>) -> ()
+# CHECK-NEXT:    "toy.return"() : () -> ()
diff --git a/mlir/test/Examples/Toy/Ch3/ast.toy b/mlir/test/Examples/Toy/Ch3/ast.toy
index 89bc279f844..e1f5bee8126 100644
--- a/mlir/test/Examples/Toy/Ch3/ast.toy
+++ b/mlir/test/Examples/Toy/Ch3/ast.toy
@@ -2,7 +2,7 @@
 
 # User defined generic function that operates on unknown shaped arguments.
 def multiply_transpose(a, b) {
-  return a * transpose(b);
+  return transpose(a) * transpose(b);
 }
 
 def main() {
@@ -35,10 +35,12 @@ def main() {
 # CHECK-NEXT:       Params: [a, b]
 # CHECK-NEXT:       Block {
 # CHECK-NEXT:         Return
-# CHECK-NEXT:           BinOp: * @{{.*}}ast.toy:5:14
-# CHECK-NEXT:             var: a @{{.*}}ast.toy:5:10
-# CHECK-NEXT:             Call 'transpose' [ @{{.*}}ast.toy:5:14
-# CHECK-NEXT:               var: b @{{.*}}ast.toy:5:24
+# CHECK-NEXT:           BinOp: * @{{.*}}ast.toy:5:25
+# CHECK-NEXT:             Call 'transpose' [ @{{.*}}ast.toy:5:10
+# CHECK-NEXT:               var: a @{{.*}}ast.toy:5:20
+# CHECK-NEXT:             ]
+# CHECK-NEXT:             Call 'transpose' [ @{{.*}}ast.toy:5:25
+# CHECK-NEXT:               var: b @{{.*}}ast.toy:5:35
 # CHECK-NEXT:             ]
 # CHECK-NEXT:       } // Block
 # CHECK-NEXT:     Function
diff --git a/mlir/test/Examples/Toy/Ch3/codegen.toy b/mlir/test/Examples/Toy/Ch3/codegen.toy
index 7103e549ca3..cc9fdd4798a 100644
--- a/mlir/test/Examples/Toy/Ch3/codegen.toy
+++ b/mlir/test/Examples/Toy/Ch3/codegen.toy
@@ -2,7 +2,7 @@
 
 # User defined generic function that operates on unknown shaped arguments
 def multiply_transpose(a, b) {
-  return a * transpose(b);
+  return transpose(a) * transpose(b);
 }
 
 def main() {
@@ -13,19 +13,19 @@ def main() {
   print(d);
 }
 
-# CHECK-LABEL:   func @multiply_transpose(
-# CHECK-SAME:                             [[VAL_0:%.*]]: tensor<*xf64>, [[VAL_1:%.*]]: tensor<*xf64>)
-# CHECK-NEXT:    attributes  {toy.generic} {
-# CHECK-NEXT:     [[VAL_2:%.*]] = "toy.transpose"([[VAL_1]]) : (tensor<*xf64>) -> tensor<*xf64>
-# CHECK-NEXT:     [[VAL_3:%.*]] = "toy.mul"([[VAL_0]], [[VAL_2]]) : (tensor<*xf64>, tensor<*xf64>) -> tensor<*xf64>
-# CHECK-NEXT:     "toy.return"([[VAL_3]]) : (tensor<*xf64>) -> ()
+# CHECK-LABEL: func @multiply_transpose(
+# CHECK-SAME:                           [[VAL_0:%.*]]: tensor<*xf64>, [[VAL_1:%.*]]: tensor<*xf64>) -> tensor<*xf64>
+# CHECK:         [[VAL_2:%.*]] = "toy.transpose"([[VAL_0]]) : (tensor<*xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    [[VAL_3:%.*]] = "toy.transpose"([[VAL_1]]) : (tensor<*xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    [[VAL_4:%.*]] = "toy.mul"([[VAL_2]], [[VAL_3]]) : (tensor<*xf64>, tensor<*xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    "toy.return"([[VAL_4]]) : (tensor<*xf64>) -> ()
 
-# CHECK-LABEL:   func @main() {
-# CHECK-NEXT:     [[VAL_4:%.*]] = "toy.constant"() {value = dense<{{\[\[}}1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64>
-# CHECK-NEXT:     [[VAL_5:%.*]] = "toy.reshape"([[VAL_4]]) : (tensor<2x3xf64>) -> tensor<2x3xf64>
-# CHECK-NEXT:     [[VAL_6:%.*]] = "toy.constant"() {value = dense<[1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00, 5.000000e+00, 6.000000e+00]> : tensor<6xf64>} : () -> tensor<6xf64>
-# CHECK-NEXT:     [[VAL_7:%.*]] = "toy.reshape"([[VAL_6]]) : (tensor<6xf64>) -> tensor<2x3xf64>
-# CHECK-NEXT:     [[VAL_8:%.*]] = "toy.generic_call"([[VAL_5]], [[VAL_7]]) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
-# CHECK-NEXT:     [[VAL_9:%.*]] = "toy.generic_call"([[VAL_7]], [[VAL_5]]) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
-# CHECK-NEXT:     "toy.print"([[VAL_9]]) : (tensor<*xf64>) -> ()
-# CHECK-NEXT:     "toy.return"() : () -> ()
+# CHECK-LABEL: func @main()
+# CHECK-NEXT:    [[VAL_5:%.*]] = "toy.constant"() {value = dense<{{\[\[}}1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64>
+# CHECK-NEXT:    [[VAL_6:%.*]] = "toy.reshape"([[VAL_5]]) : (tensor<2x3xf64>) -> tensor<2x3xf64>
+# CHECK-NEXT:    [[VAL_7:%.*]] = "toy.constant"() {value = dense<[1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00, 5.000000e+00, 6.000000e+00]> : tensor<6xf64>} : () -> tensor<6xf64>
+# CHECK-NEXT:    [[VAL_8:%.*]] = "toy.reshape"([[VAL_7]]) : (tensor<6xf64>) -> tensor<2x3xf64>
+# CHECK-NEXT:    [[VAL_9:%.*]] = "toy.generic_call"([[VAL_6]], [[VAL_8]]) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    [[VAL_10:%.*]] = "toy.generic_call"([[VAL_8]], [[VAL_6]]) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    "toy.print"([[VAL_10]]) : (tensor<*xf64>) -> ()
+# CHECK-NEXT:    "toy.return"() : () -> ()
diff --git a/mlir/test/Examples/Toy/Ch4/ast.toy b/mlir/test/Examples/Toy/Ch4/ast.toy
index aae8da78095..18a88e5e6bb 100644
--- a/mlir/test/Examples/Toy/Ch4/ast.toy
+++ b/mlir/test/Examples/Toy/Ch4/ast.toy
@@ -2,7 +2,7 @@
 
 # User defined generic function that operates on unknown shaped arguments.
 def multiply_transpose(a, b) {
-  return a * transpose(b);
+  return transpose(a) * transpose(b);
 }
 
 def main() {
@@ -35,10 +35,12 @@ def main() {
 # CHECK-NEXT:       Params: [a, b]
 # CHECK-NEXT:       Block {
 # CHECK-NEXT:         Return
-# CHECK-NEXT:           BinOp: * @{{.*}}ast.toy:5:14
-# CHECK-NEXT:             var: a @{{.*}}ast.toy:5:10
-# CHECK-NEXT:             Call 'transpose' [ @{{.*}}ast.toy:5:14
-# CHECK-NEXT:               var: b @{{.*}}ast.toy:5:24
+# CHECK-NEXT:           BinOp: * @{{.*}}ast.toy:5:25
+# CHECK-NEXT:             Call 'transpose' [ @{{.*}}ast.toy:5:10
+# CHECK-NEXT:               var: a @{{.*}}ast.toy:5:20
+# CHECK-NEXT:             ]
+# CHECK-NEXT:             Call 'transpose' [ @{{.*}}ast.toy:5:25
+# CHECK-NEXT:               var: b @{{.*}}ast.toy:5:35
 # CHECK-NEXT:             ]
 # CHECK-NEXT:       } // Block
 # CHECK-NEXT:     Function
diff --git a/mlir/test/Examples/Toy/Ch4/codegen.toy b/mlir/test/Examples/Toy/Ch4/codegen.toy
index 722ff4a2587..94ecbae38e8 100644
--- a/mlir/test/Examples/Toy/Ch4/codegen.toy
+++ b/mlir/test/Examples/Toy/Ch4/codegen.toy
@@ -2,7 +2,7 @@
 
 # User defined generic function that operates on unknown shaped arguments
 def multiply_transpose(a, b) {
-  return a * transpose(b);
+  return transpose(a) * transpose(b);
 }
 
 def main() {
@@ -13,19 +13,19 @@ def main() {
   print(d);
 }
 
-# CHECK-LABEL:   func @multiply_transpose(
-# CHECK-SAME:                             [[VAL_0:%.*]]: tensor<*xf64>, [[VAL_1:%.*]]: tensor<*xf64>)
-# CHECK-NEXT:    attributes  {toy.generic} {
-# CHECK-NEXT:     [[VAL_2:%.*]] = "toy.transpose"([[VAL_1]]) : (tensor<*xf64>) -> tensor<*xf64>
-# CHECK-NEXT:     [[VAL_3:%.*]] = "toy.mul"([[VAL_0]], [[VAL_2]]) : (tensor<*xf64>, tensor<*xf64>) -> tensor<*xf64>
-# CHECK-NEXT:     "toy.return"([[VAL_3]]) : (tensor<*xf64>) -> ()
+# CHECK-LABEL: func @multiply_transpose(
+# CHECK-SAME:                           [[VAL_0:%.*]]: tensor<*xf64>, [[VAL_1:%.*]]: tensor<*xf64>) -> tensor<*xf64>
+# CHECK:         [[VAL_2:%.*]] = "toy.transpose"([[VAL_0]]) : (tensor<*xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    [[VAL_3:%.*]] = "toy.transpose"([[VAL_1]]) : (tensor<*xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    [[VAL_4:%.*]] = "toy.mul"([[VAL_2]], [[VAL_3]]) : (tensor<*xf64>, tensor<*xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    "toy.return"([[VAL_4]]) : (tensor<*xf64>) -> ()
 
-# CHECK-LABEL:   func @main() {
-# CHECK-NEXT:     [[VAL_4:%.*]] = "toy.constant"() {value = dense<{{\[\[}}1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64>
-# CHECK-NEXT:     [[VAL_5:%.*]] = "toy.reshape"([[VAL_4]]) : (tensor<2x3xf64>) -> tensor<2x3xf64>
-# CHECK-NEXT:     [[VAL_6:%.*]] = "toy.constant"() {value = dense<[1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00, 5.000000e+00, 6.000000e+00]> : tensor<6xf64>} : () -> tensor<6xf64>
-# CHECK-NEXT:     [[VAL_7:%.*]] = "toy.reshape"([[VAL_6]]) : (tensor<6xf64>) -> tensor<2x3xf64>
-# CHECK-NEXT:     [[VAL_8:%.*]] = "toy.generic_call"([[VAL_5]], [[VAL_7]]) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
-# CHECK-NEXT:     [[VAL_9:%.*]] = "toy.generic_call"([[VAL_7]], [[VAL_5]]) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
-# CHECK-NEXT:     "toy.print"([[VAL_9]]) : (tensor<*xf64>) -> ()
-# CHECK-NEXT:     "toy.return"() : () -> ()
+# CHECK-LABEL: func @main()
+# CHECK-NEXT:    [[VAL_5:%.*]] = "toy.constant"() {value = dense<{{\[\[}}1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64>
+# CHECK-NEXT:    [[VAL_6:%.*]] = "toy.reshape"([[VAL_5]]) : (tensor<2x3xf64>) -> tensor<2x3xf64>
+# CHECK-NEXT:    [[VAL_7:%.*]] = "toy.constant"() {value = dense<[1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00, 5.000000e+00, 6.000000e+00]> : tensor<6xf64>} : () -> tensor<6xf64>
+# CHECK-NEXT:    [[VAL_8:%.*]] = "toy.reshape"([[VAL_7]]) : (tensor<6xf64>) -> tensor<2x3xf64>
+# CHECK-NEXT:    [[VAL_9:%.*]] = "toy.generic_call"([[VAL_6]], [[VAL_8]]) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    [[VAL_10:%.*]] = "toy.generic_call"([[VAL_8]], [[VAL_6]]) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    "toy.print"([[VAL_10]]) : (tensor<*xf64>) -> ()
+# CHECK-NEXT:    "toy.return"() : () -> ()
diff --git a/mlir/test/Examples/Toy/Ch4/shape_inference.mlir b/mlir/test/Examples/Toy/Ch4/shape_inference.mlir
index e783300c5cf..799ce45751a 100644
--- a/mlir/test/Examples/Toy/Ch4/shape_inference.mlir
+++ b/mlir/test/Examples/Toy/Ch4/shape_inference.mlir
@@ -3,9 +3,10 @@
 // Check the result of inlining+shape inference on an input module.
 
 func @multiply_transpose(%arg0: tensor<*xf64>, %arg1: tensor<*xf64>) -> tensor<*xf64> {
-  %0 = "toy.transpose"(%arg1) : (tensor<*xf64>) -> tensor<*xf64>
-  %1 = "toy.mul"(%arg0, %0) : (tensor<*xf64>, tensor<*xf64>) -> tensor<*xf64>
-  "toy.return"(%1) : (tensor<*xf64>) -> ()
+  %0 = "toy.transpose"(%arg0) : (tensor<*xf64>) -> tensor<*xf64>
+  %1 = "toy.transpose"(%arg1) : (tensor<*xf64>) -> tensor<*xf64>
+  %2 = "toy.mul"(%0, %1) : (tensor<*xf64>, tensor<*xf64>) -> tensor<*xf64>
+  "toy.return"(%2) : (tensor<*xf64>) -> ()
 }
 func @main() {
   %0 = "toy.constant"() {value = dense<[[1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64>
@@ -21,10 +22,11 @@ func @main() {
 // CHECK-NOT: func @multiply_transpose
 // CHECK-NOT: tensor<*xf64>
 
-// CHECK-LABEL: func @main() {
+// CHECK-LABEL: func @main()
 // CHECK:         [[VAL_0:%.*]] = "toy.constant"() {value = dense<{{\[\[}}1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64>
 // CHECK:         [[VAL_1:%.*]] = "toy.constant"() {value = dense<{{\[\[}}1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64>
-// CHECK:         [[VAL_2:%.*]] = "toy.transpose"([[VAL_0]]) : (tensor<2x3xf64>) -> tensor<3x2xf64>
-// CHECK:         [[VAL_3:%.*]] = "toy.mul"([[VAL_1]], [[VAL_2]]) : (tensor<2x3xf64>, tensor<3x2xf64>) -> tensor<2x2xf64>
-// CHECK:         "toy.print"([[VAL_3]]) : (tensor<2x2xf64>) -> ()
+// CHECK:         [[VAL_2:%.*]] = "toy.transpose"([[VAL_1]]) : (tensor<2x3xf64>) -> tensor<3x2xf64>
+// CHECK:         [[VAL_3:%.*]] = "toy.transpose"([[VAL_0]]) : (tensor<2x3xf64>) -> tensor<3x2xf64>
+// CHECK:         [[VAL_4:%.*]] = "toy.mul"([[VAL_2]], [[VAL_3]]) : (tensor<3x2xf64>, tensor<3x2xf64>) -> tensor<3x2xf64>
+// CHECK:         "toy.print"([[VAL_4]]) : (tensor<3x2xf64>) -> ()
 // CHECK:         "toy.return"() : () -> ()
diff --git a/mlir/test/Examples/Toy/Ch5/ast.toy b/mlir/test/Examples/Toy/Ch5/ast.toy
index 8850a50fa9e..ba7456d27a3 100644
--- a/mlir/test/Examples/Toy/Ch5/ast.toy
+++ b/mlir/test/Examples/Toy/Ch5/ast.toy
@@ -2,7 +2,7 @@
 
 # User defined generic function that operates on unknown shaped arguments.
 def multiply_transpose(a, b) {
-  return a * transpose(b);
+  return transpose(a) * transpose(b);
 }
 
 def main() {
@@ -35,10 +35,12 @@ def main() {
 # CHECK-NEXT:       Params: [a, b]
 # CHECK-NEXT:       Block {
 # CHECK-NEXT:         Return
-# CHECK-NEXT:           BinOp: * @{{.*}}ast.toy:5:14
-# CHECK-NEXT:             var: a @{{.*}}ast.toy:5:10
-# CHECK-NEXT:             Call 'transpose' [ @{{.*}}ast.toy:5:14
-# CHECK-NEXT:               var: b @{{.*}}ast.toy:5:24
+# CHECK-NEXT:           BinOp: * @{{.*}}ast.toy:5:25
+# CHECK-NEXT:             Call 'transpose' [ @{{.*}}ast.toy:5:10
+# CHECK-NEXT:               var: a @{{.*}}ast.toy:5:20
+# CHECK-NEXT:             ]
+# CHECK-NEXT:             Call 'transpose' [ @{{.*}}ast.toy:5:25
+# CHECK-NEXT:               var: b @{{.*}}ast.toy:5:35
 # CHECK-NEXT:             ]
 # CHECK-NEXT:       } // Block
 # CHECK-NEXT:     Function
diff --git a/mlir/test/Examples/Toy/Ch5/codegen.toy b/mlir/test/Examples/Toy/Ch5/codegen.toy
index 50a1d8ff089..8719ce4f430 100644
--- a/mlir/test/Examples/Toy/Ch5/codegen.toy
+++ b/mlir/test/Examples/Toy/Ch5/codegen.toy
@@ -2,7 +2,7 @@
 
 # User defined generic function that operates on unknown shaped arguments
 def multiply_transpose(a, b) {
-  return a * transpose(b);
+  return transpose(a) * transpose(b);
 }
 
 def main() {
@@ -13,19 +13,19 @@ def main() {
   print(d);
 }
 
-# CHECK-LABEL:   func @multiply_transpose(
-# CHECK-SAME:                             [[VAL_0:%.*]]: tensor<*xf64>, [[VAL_1:%.*]]: tensor<*xf64>)
-# CHECK-NEXT:    attributes  {toy.generic} {
-# CHECK-NEXT:     [[VAL_2:%.*]] = "toy.transpose"([[VAL_1]]) : (tensor<*xf64>) -> tensor<*xf64>
-# CHECK-NEXT:     [[VAL_3:%.*]] = "toy.mul"([[VAL_0]], [[VAL_2]]) : (tensor<*xf64>, tensor<*xf64>) -> tensor<*xf64>
-# CHECK-NEXT:     "toy.return"([[VAL_3]]) : (tensor<*xf64>) -> ()
+# CHECK-LABEL: func @multiply_transpose(
+# CHECK-SAME:                           [[VAL_0:%.*]]: tensor<*xf64>, [[VAL_1:%.*]]: tensor<*xf64>) -> tensor<*xf64>
+# CHECK:         [[VAL_2:%.*]] = "toy.transpose"([[VAL_0]]) : (tensor<*xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    [[VAL_3:%.*]] = "toy.transpose"([[VAL_1]]) : (tensor<*xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    [[VAL_4:%.*]] = "toy.mul"([[VAL_2]], [[VAL_3]]) : (tensor<*xf64>, tensor<*xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    "toy.return"([[VAL_4]]) : (tensor<*xf64>) -> ()
 
-# CHECK-LABEL:   func @main() {
-# CHECK-NEXT:     [[VAL_4:%.*]] = "toy.constant"() {value = dense<{{\[\[}}1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64>
-# CHECK-NEXT:     [[VAL_5:%.*]] = "toy.reshape"([[VAL_4]]) : (tensor<2x3xf64>) -> tensor<2x3xf64>
-# CHECK-NEXT:     [[VAL_6:%.*]] = "toy.constant"() {value = dense<[1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00, 5.000000e+00, 6.000000e+00]> : tensor<6xf64>} : () -> tensor<6xf64>
-# CHECK-NEXT:     [[VAL_7:%.*]] = "toy.reshape"([[VAL_6]]) : (tensor<6xf64>) -> tensor<2x3xf64>
-# CHECK-NEXT:     [[VAL_8:%.*]] = "toy.generic_call"([[VAL_5]], [[VAL_7]]) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
-# CHECK-NEXT:     [[VAL_9:%.*]] = "toy.generic_call"([[VAL_7]], [[VAL_5]]) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
-# CHECK-NEXT:     "toy.print"([[VAL_9]]) : (tensor<*xf64>) -> ()
-# CHECK-NEXT:     "toy.return"() : () -> ()
+# CHECK-LABEL: func @main()
+# CHECK-NEXT:    [[VAL_5:%.*]] = "toy.constant"() {value = dense<{{\[\[}}1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64>
+# CHECK-NEXT:    [[VAL_6:%.*]] = "toy.reshape"([[VAL_5]]) : (tensor<2x3xf64>) -> tensor<2x3xf64>
+# CHECK-NEXT:    [[VAL_7:%.*]] = "toy.constant"() {value = dense<[1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00, 5.000000e+00, 6.000000e+00]> : tensor<6xf64>} : () -> tensor<6xf64>
+# CHECK-NEXT:    [[VAL_8:%.*]] = "toy.reshape"([[VAL_7]]) : (tensor<6xf64>) -> tensor<2x3xf64>
+# CHECK-NEXT:    [[VAL_9:%.*]] = "toy.generic_call"([[VAL_6]], [[VAL_8]]) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    [[VAL_10:%.*]] = "toy.generic_call"([[VAL_8]], [[VAL_6]]) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    "toy.print"([[VAL_10]]) : (tensor<*xf64>) -> ()
+# CHECK-NEXT:    "toy.return"() : () -> ()
diff --git a/mlir/test/Examples/Toy/Ch5/shape_inference.mlir b/mlir/test/Examples/Toy/Ch5/shape_inference.mlir
index 7be7eda7782..962a641d657 100644
--- a/mlir/test/Examples/Toy/Ch5/shape_inference.mlir
+++ b/mlir/test/Examples/Toy/Ch5/shape_inference.mlir
@@ -3,9 +3,10 @@
 // Check the result of inlining+shape inference on an input module.
 
 func @multiply_transpose(%arg0: tensor<*xf64>, %arg1: tensor<*xf64>) -> tensor<*xf64> {
-  %0 = "toy.transpose"(%arg1) : (tensor<*xf64>) -> tensor<*xf64>
-  %1 = "toy.mul"(%arg0, %0) : (tensor<*xf64>, tensor<*xf64>) -> tensor<*xf64>
-  "toy.return"(%1) : (tensor<*xf64>) -> ()
+  %0 = "toy.transpose"(%arg0) : (tensor<*xf64>) -> tensor<*xf64>
+  %1 = "toy.transpose"(%arg1) : (tensor<*xf64>) -> tensor<*xf64>
+  %2 = "toy.mul"(%0, %1) : (tensor<*xf64>, tensor<*xf64>) -> tensor<*xf64>
+  "toy.return"(%2) : (tensor<*xf64>) -> ()
 }
 func @main() {
   %0 = "toy.constant"() {value = dense<[[1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64>
@@ -21,10 +22,11 @@ func @main() {
 // CHECK-NOT: func @multiply_transpose
 // CHECK-NOT: tensor<*xf64>
 
-// CHECK-LABEL: func @main() {
+// CHECK-LABEL: func @main()
 // CHECK:         [[VAL_0:%.*]] = "toy.constant"() {value = dense<{{\[\[}}1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64>
 // CHECK:         [[VAL_1:%.*]] = "toy.constant"() {value = dense<{{\[\[}}1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64>
-// CHECK:         [[VAL_2:%.*]] = "toy.transpose"([[VAL_0]]) : (tensor<2x3xf64>) -> tensor<3x2xf64>
-// CHECK:         [[VAL_3:%.*]] = "toy.mul"([[VAL_1]], [[VAL_2]]) : (tensor<2x3xf64>, tensor<3x2xf64>) -> tensor<2x2xf64>
-// CHECK:         "toy.print"([[VAL_3]]) : (tensor<2x2xf64>) -> ()
+// CHECK:         [[VAL_2:%.*]] = "toy.transpose"([[VAL_1]]) : (tensor<2x3xf64>) -> tensor<3x2xf64>
+// CHECK:         [[VAL_3:%.*]] = "toy.transpose"([[VAL_0]]) : (tensor<2x3xf64>) -> tensor<3x2xf64>
+// CHECK:         [[VAL_4:%.*]] = "toy.mul"([[VAL_2]], [[VAL_3]]) : (tensor<3x2xf64>, tensor<3x2xf64>) -> tensor<3x2xf64>
+// CHECK:         "toy.print"([[VAL_4]]) : (tensor<3x2xf64>) -> ()
 // CHECK:         "toy.return"() : () -> ()
diff --git a/mlir/test/Examples/Toy/Ch6/ast.toy b/mlir/test/Examples/Toy/Ch6/ast.toy
index d7d6ae5200d..cc7e5698fe6 100644
--- a/mlir/test/Examples/Toy/Ch6/ast.toy
+++ b/mlir/test/Examples/Toy/Ch6/ast.toy
@@ -2,7 +2,7 @@
 
 # User defined generic function that operates on unknown shaped arguments.
 def multiply_transpose(a, b) {
-  return a * transpose(b);
+  return transpose(a) * transpose(b);
 }
 
 def main() {
@@ -35,10 +35,12 @@ def main() {
 # CHECK-NEXT:       Params: [a, b]
 # CHECK-NEXT:       Block {
 # CHECK-NEXT:         Return
-# CHECK-NEXT:           BinOp: * @{{.*}}ast.toy:5:14
-# CHECK-NEXT:             var: a @{{.*}}ast.toy:5:10
-# CHECK-NEXT:             Call 'transpose' [ @{{.*}}ast.toy:5:14
-# CHECK-NEXT:               var: b @{{.*}}ast.toy:5:24
+# CHECK-NEXT:           BinOp: * @{{.*}}ast.toy:5:25
+# CHECK-NEXT:             Call 'transpose' [ @{{.*}}ast.toy:5:10
+# CHECK-NEXT:               var: a @{{.*}}ast.toy:5:20
+# CHECK-NEXT:             ]
+# CHECK-NEXT:             Call 'transpose' [ @{{.*}}ast.toy:5:25
+# CHECK-NEXT:               var: b @{{.*}}ast.toy:5:35
 # CHECK-NEXT:             ]
 # CHECK-NEXT:       } // Block
 # CHECK-NEXT:     Function
diff --git a/mlir/test/Examples/Toy/Ch6/codegen.toy b/mlir/test/Examples/Toy/Ch6/codegen.toy
index 0420a55004c..7056880eae9 100644
--- a/mlir/test/Examples/Toy/Ch6/codegen.toy
+++ b/mlir/test/Examples/Toy/Ch6/codegen.toy
@@ -2,7 +2,7 @@
 
 # User defined generic function that operates on unknown shaped arguments
 def multiply_transpose(a, b) {
-  return a * transpose(b);
+  return transpose(a) * transpose(b);
 }
 
 def main() {
@@ -13,19 +13,19 @@ def main() {
   print(d);
 }
 
-# CHECK-LABEL:   func @multiply_transpose(
-# CHECK-SAME:                             [[VAL_0:%.*]]: tensor<*xf64>, [[VAL_1:%.*]]: tensor<*xf64>)
-# CHECK-NEXT:    attributes  {toy.generic} {
-# CHECK-NEXT:     [[VAL_2:%.*]] = "toy.transpose"([[VAL_1]]) : (tensor<*xf64>) -> tensor<*xf64>
-# CHECK-NEXT:     [[VAL_3:%.*]] = "toy.mul"([[VAL_0]], [[VAL_2]]) : (tensor<*xf64>, tensor<*xf64>) -> tensor<*xf64>
-# CHECK-NEXT:     "toy.return"([[VAL_3]]) : (tensor<*xf64>) -> ()
+# CHECK-LABEL: func @multiply_transpose(
+# CHECK-SAME:                           [[VAL_0:%.*]]: tensor<*xf64>, [[VAL_1:%.*]]: tensor<*xf64>) -> tensor<*xf64>
+# CHECK:         [[VAL_2:%.*]] = "toy.transpose"([[VAL_0]]) : (tensor<*xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    [[VAL_3:%.*]] = "toy.transpose"([[VAL_1]]) : (tensor<*xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    [[VAL_4:%.*]] = "toy.mul"([[VAL_2]], [[VAL_3]]) : (tensor<*xf64>, tensor<*xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    "toy.return"([[VAL_4]]) : (tensor<*xf64>) -> ()
 
-# CHECK-LABEL:   func @main() {
-# CHECK-NEXT:     [[VAL_4:%.*]] = "toy.constant"() {value = dense<{{\[\[}}1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64>
-# CHECK-NEXT:     [[VAL_5:%.*]] = "toy.reshape"([[VAL_4]]) : (tensor<2x3xf64>) -> tensor<2x3xf64>
-# CHECK-NEXT:     [[VAL_6:%.*]] = "toy.constant"() {value = dense<[1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00, 5.000000e+00, 6.000000e+00]> : tensor<6xf64>} : () -> tensor<6xf64>
-# CHECK-NEXT:     [[VAL_7:%.*]] = "toy.reshape"([[VAL_6]]) : (tensor<6xf64>) -> tensor<2x3xf64>
-# CHECK-NEXT:     [[VAL_8:%.*]] = "toy.generic_call"([[VAL_5]], [[VAL_7]]) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
-# CHECK-NEXT:     [[VAL_9:%.*]] = "toy.generic_call"([[VAL_7]], [[VAL_5]]) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
-# CHECK-NEXT:     "toy.print"([[VAL_9]]) : (tensor<*xf64>) -> ()
-# CHECK-NEXT:     "toy.return"() : () -> ()
+# CHECK-LABEL: func @main()
+# CHECK-NEXT:    [[VAL_5:%.*]] = "toy.constant"() {value = dense<{{\[\[}}1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64>
+# CHECK-NEXT:    [[VAL_6:%.*]] = "toy.reshape"([[VAL_5]]) : (tensor<2x3xf64>) -> tensor<2x3xf64>
+# CHECK-NEXT:    [[VAL_7:%.*]] = "toy.constant"() {value = dense<[1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00, 5.000000e+00, 6.000000e+00]> : tensor<6xf64>} : () -> tensor<6xf64>
+# CHECK-NEXT:    [[VAL_8:%.*]] = "toy.reshape"([[VAL_7]]) : (tensor<6xf64>) -> tensor<2x3xf64>
+# CHECK-NEXT:    [[VAL_9:%.*]] = "toy.generic_call"([[VAL_6]], [[VAL_8]]) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    [[VAL_10:%.*]] = "toy.generic_call"([[VAL_8]], [[VAL_6]]) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
+# CHECK-NEXT:    "toy.print"([[VAL_10]]) : (tensor<*xf64>) -> ()
+# CHECK-NEXT:    "toy.return"() : () -> ()
diff --git a/mlir/test/Examples/Toy/Ch6/shape_inference.mlir b/mlir/test/Examples/Toy/Ch6/shape_inference.mlir
index 3ccf70db89f..5788d869e42 100644
--- a/mlir/test/Examples/Toy/Ch6/shape_inference.mlir
+++ b/mlir/test/Examples/Toy/Ch6/shape_inference.mlir
@@ -3,9 +3,10 @@
 // Check the result of inlining+shape inference on an input module.
 
 func @multiply_transpose(%arg0: tensor<*xf64>, %arg1: tensor<*xf64>) -> tensor<*xf64> {
-  %0 = "toy.transpose"(%arg1) : (tensor<*xf64>) -> tensor<*xf64>
-  %1 = "toy.mul"(%arg0, %0) : (tensor<*xf64>, tensor<*xf64>) -> tensor<*xf64>
-  "toy.return"(%1) : (tensor<*xf64>) -> ()
+  %0 = "toy.transpose"(%arg0) : (tensor<*xf64>) -> tensor<*xf64>
+  %1 = "toy.transpose"(%arg1) : (tensor<*xf64>) -> tensor<*xf64>
+  %2 = "toy.mul"(%0, %1) : (tensor<*xf64>, tensor<*xf64>) -> tensor<*xf64>
+  "toy.return"(%2) : (tensor<*xf64>) -> ()
 }
 func @main() {
   %0 = "toy.constant"() {value = dense<[[1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64>
@@ -21,10 +22,11 @@ func @main() {
 // CHECK-NOT: func @multiply_transpose
 // CHECK-NOT: tensor<*xf64>
 
-// CHECK-LABEL: func @main() {
+// CHECK-LABEL: func @main()
 // CHECK:         [[VAL_0:%.*]] = "toy.constant"() {value = dense<{{\[\[}}1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64>
 // CHECK:         [[VAL_1:%.*]] = "toy.constant"() {value = dense<{{\[\[}}1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64>
-// CHECK:         [[VAL_2:%.*]] = "toy.transpose"([[VAL_0]]) : (tensor<2x3xf64>) -> tensor<3x2xf64>
-// CHECK:         [[VAL_3:%.*]] = "toy.mul"([[VAL_1]], [[VAL_2]]) : (tensor<2x3xf64>, tensor<3x2xf64>) -> tensor<2x2xf64>
-// CHECK:         "toy.print"([[VAL_3]]) : (tensor<2x2xf64>) -> ()
+// CHECK:         [[VAL_2:%.*]] = "toy.transpose"([[VAL_1]]) : (tensor<2x3xf64>) -> tensor<3x2xf64>
+// CHECK:         [[VAL_3:%.*]] = "toy.transpose"([[VAL_0]]) : (tensor<2x3xf64>) -> tensor<3x2xf64>
+// CHECK:         [[VAL_4:%.*]] = "toy.mul"([[VAL_2]], [[VAL_3]]) : (tensor<3x2xf64>, tensor<3x2xf64>) -> tensor<3x2xf64>
+// CHECK:         "toy.print"([[VAL_4]]) : (tensor<3x2xf64>) -> ()
 // CHECK:         "toy.return"() : () -> ()