1# RUN: toyc-ch7 %s -emit=mlir 2>&1 | FileCheck %s 2# RUN: toyc-ch7 %s -emit=mlir -opt 2>&1 | FileCheck %s --check-prefix=OPT 3 4struct Struct { 5 var a; 6 var b; 7} 8 9# User defined generic function may operate on struct types as well. 10def multiply_transpose(Struct value) { 11 # We can access the elements of a struct via the '.' operator. 12 return transpose(value.a) * transpose(value.b); 13} 14 15def main() { 16 # We initialize struct values using a composite initializer. 17 Struct value = {[[1, 2, 3], [4, 5, 6]], [[1, 2, 3], [4, 5, 6]]}; 18 19 # We pass these arguments to functions like we do with variables. 20 var c = multiply_transpose(value); 21 print(c); 22} 23 24# CHECK-LABEL: func private @multiply_transpose( 25# CHECK-SAME: [[VAL_0:%.*]]: !toy.struct<tensor<*xf64>, tensor<*xf64>>) -> tensor<*xf64> 26# CHECK-NEXT: [[VAL_1:%.*]] = toy.struct_access [[VAL_0]][0] : !toy.struct<tensor<*xf64>, tensor<*xf64>> -> tensor<*xf64> 27# CHECK-NEXT: [[VAL_2:%.*]] = toy.transpose([[VAL_1]] : tensor<*xf64>) to tensor<*xf64> 28# CHECK-NEXT: [[VAL_3:%.*]] = toy.struct_access [[VAL_0]][1] : !toy.struct<tensor<*xf64>, tensor<*xf64>> -> tensor<*xf64> 29# CHECK-NEXT: [[VAL_4:%.*]] = toy.transpose([[VAL_3]] : tensor<*xf64>) to tensor<*xf64> 30# CHECK-NEXT: [[VAL_5:%.*]] = toy.mul [[VAL_2]], [[VAL_4]] : tensor<*xf64> 31# CHECK-NEXT: toy.return [[VAL_5]] : tensor<*xf64> 32 33# CHECK-LABEL: func @main() 34# CHECK-NEXT: [[VAL_6:%.*]] = toy.struct_constant [dense<{{\[\[}}1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>, dense<{{\[\[}}1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>] : !toy.struct<tensor<*xf64>, tensor<*xf64>> 35# CHECK-NEXT: [[VAL_7:%.*]] = toy.generic_call @multiply_transpose([[VAL_6]]) : (!toy.struct<tensor<*xf64>, tensor<*xf64>>) -> tensor<*xf64> 36# CHECK-NEXT: toy.print [[VAL_7]] : tensor<*xf64> 37# CHECK-NEXT: toy.return 38 39# OPT-LABEL: func @main() 40# OPT-NEXT: [[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> 41# OPT-NEXT: [[VAL_1:%.*]] = toy.transpose([[VAL_0]] : tensor<2x3xf64>) to tensor<3x2xf64> 42# OPT-NEXT: [[VAL_2:%.*]] = toy.mul [[VAL_1]], [[VAL_1]] : tensor<3x2xf64> 43# OPT-NEXT: toy.print [[VAL_2]] : tensor<3x2xf64> 44# OPT-NEXT: toy.return 45