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| author | River Riddle <riverriddle@google.com> | 2019-10-21 11:30:58 -0700 |
|---|---|---|
| committer | A. Unique TensorFlower <gardener@tensorflow.org> | 2019-10-21 11:31:32 -0700 |
| commit | 941a1c43320afed13bc964452cef3eeafa93a48c (patch) | |
| tree | dc3d4ce3ceb48bf8c116cc3c05f3b4fff0983131 /mlir/test/Examples/Toy/Ch2 | |
| parent | b74af4aa5c314f596ad5ed26c00e4b9033dee78f (diff) | |
| download | bcm5719-llvm-941a1c43320afed13bc964452cef3eeafa93a48c.tar.gz bcm5719-llvm-941a1c43320afed13bc964452cef3eeafa93a48c.zip | |
NFC: Fix remaining usages of MulOp as matrix multiplication.
MulOp now represents an element-wise multiplication instead of a matrix multiplication.
PiperOrigin-RevId: 275886774
Diffstat (limited to 'mlir/test/Examples/Toy/Ch2')
| -rw-r--r-- | mlir/test/Examples/Toy/Ch2/ast.toy | 12 | ||||
| -rw-r--r-- | mlir/test/Examples/Toy/Ch2/codegen.toy | 32 |
2 files changed, 23 insertions, 21 deletions
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"() : () -> () |
