1# RUN: toyc-ch7 %s -emit=mlir 2>&1 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 @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]]) {index = 0 : i64} : (!toy.struct<tensor<*xf64>, tensor<*xf64>>) -> tensor<*xf64> 27# CHECK-NEXT: [[VAL_2:%.*]] = "toy.transpose"([[VAL_1]]) : (tensor<*xf64>) -> tensor<*xf64> 28# CHECK-NEXT: [[VAL_3:%.*]] = "toy.struct_access"([[VAL_0]]) {index = 1 : i64} : (!toy.struct<tensor<*xf64>, tensor<*xf64>>) -> tensor<*xf64> 29# CHECK-NEXT: [[VAL_4:%.*]] = "toy.transpose"([[VAL_3]]) : (tensor<*xf64>) -> tensor<*xf64> 30# CHECK-NEXT: [[VAL_5:%.*]] = "toy.mul"([[VAL_2]], [[VAL_4]]) : (tensor<*xf64>, tensor<*xf64>) -> 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"() {value = [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"([[VAL_6]]) {callee = @multiply_transpose} : (!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"() {value = dense<{{\[\[}}1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64> 41# OPT-NEXT: [[VAL_1:%.*]] = "toy.transpose"([[VAL_0]]) : (tensor<2x3xf64>) -> tensor<3x2xf64> 42# OPT-NEXT: [[VAL_2:%.*]] = "toy.mul"([[VAL_1]], [[VAL_1]]) : (tensor<3x2xf64>, tensor<3x2xf64>) -> tensor<3x2xf64> 43# OPT-NEXT: "toy.print"([[VAL_2]]) : (tensor<3x2xf64>) -> () 44# OPT-NEXT: "toy.return"() : () -> () 45