Mercurial > hg > CbC > CbC_llvm

diff mlir/test/Examples/Toy/Ch7/shape_inference.mlir @ 173:0572611fdcc8 llvm10 llvm12

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reorgnization done
author Shinji KONO <kono@ie.u-ryukyu.ac.jp>
date Mon, 25 May 2020 11:55:54 +0900
parents 1d019706d866
children 2e18cbf3894f
line wrap: on
line diff
--- a/mlir/test/Examples/Toy/Ch7/shape_inference.mlir	Mon May 25 11:50:15 2020 +0900
+++ b/mlir/test/Examples/Toy/Ch7/shape_inference.mlir	Mon May 25 11:55:54 2020 +0900
@@ -4,28 +4,28 @@
 
 func @multiply_transpose(%arg0: tensor<*xf64>, %arg1: tensor<*xf64>) -> tensor<*xf64>
     attributes { sym_visibility = "private" } {
-  %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>) -> ()
+  %0 = toy.transpose(%arg0 : tensor<*xf64>) to tensor<*xf64>
+  %1 = toy.transpose(%arg1 : tensor<*xf64>) to tensor<*xf64>
+  %2 = toy.mul %0, %1 : 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>
-  %1 = "toy.reshape"(%0) : (tensor<2x3xf64>) -> tensor<2x3xf64>
-  %2 = "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>
-  %3 = "toy.reshape"(%2) : (tensor<6xf64>) -> tensor<2x3xf64>
-  %4 = "toy.generic_call"(%1, %3) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
-  %5 = "toy.generic_call"(%3, %1) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
-  "toy.print"(%5) : (tensor<*xf64>) -> ()
-  "toy.return"() : () -> ()
+  %0 = toy.constant dense<[[1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>
+  %1 = toy.reshape(%0 : tensor<2x3xf64>) to tensor<2x3xf64>
+  %2 = toy.constant dense<[1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00, 5.000000e+00, 6.000000e+00]> : tensor<6xf64>
+  %3 = toy.reshape(%2 : tensor<6xf64>) to tensor<2x3xf64>
+  %4 = toy.generic_call @multiply_transpose(%1, %3) : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
+  %5 = toy.generic_call @multiply_transpose(%3, %1) : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
+  toy.print %5 : tensor<*xf64>
+  toy.return
 }
 
 // CHECK-NOT: func @multiply_transpose
 // CHECK-NOT: tensor<*xf64>
 
 // 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.transpose"([[VAL_0]]) : (tensor<2x3xf64>) -> tensor<3x2xf64>
-// CHECK:         [[VAL_2:%.*]] = "toy.mul"([[VAL_1]], [[VAL_1]]) : (tensor<3x2xf64>, tensor<3x2xf64>) -> tensor<3x2xf64>
-// CHECK:         "toy.print"([[VAL_2]]) : (tensor<3x2xf64>) -> ()
-// CHECK:         "toy.return"() : () -> ()
+// CHECK:         [[VAL_0:%.*]] = toy.constant dense<{{\[\[}}1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>
+// CHECK:         [[VAL_1:%.*]] = toy.transpose([[VAL_0]] : tensor<2x3xf64>) to tensor<3x2xf64>
+// CHECK:         [[VAL_2:%.*]] = toy.mul [[VAL_1]], [[VAL_1]] : tensor<3x2xf64>
+// CHECK:         toy.print [[VAL_2]] : tensor<3x2xf64>
+// CHECK:         toy.return