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