157540c96SRiver Riddle# RUN: toyc-ch7 %s -emit=mlir 2>&1 | FileCheck %s 26b4e30b7SRiver Riddle# RUN: toyc-ch7 %s -emit=mlir -opt 2>&1 | FileCheck %s --check-prefix=OPT 36b4e30b7SRiver Riddle 46b4e30b7SRiver Riddlestruct Struct { 56b4e30b7SRiver Riddle var a; 66b4e30b7SRiver Riddle var b; 76b4e30b7SRiver Riddle} 86b4e30b7SRiver Riddle 96b4e30b7SRiver Riddle# User defined generic function may operate on struct types as well. 106b4e30b7SRiver Riddledef multiply_transpose(Struct value) { 116b4e30b7SRiver Riddle # We can access the elements of a struct via the '.' operator. 126b4e30b7SRiver Riddle return transpose(value.a) * transpose(value.b); 136b4e30b7SRiver Riddle} 146b4e30b7SRiver Riddle 156b4e30b7SRiver Riddledef main() { 166b4e30b7SRiver Riddle # We initialize struct values using a composite initializer. 176b4e30b7SRiver Riddle Struct value = {[[1, 2, 3], [4, 5, 6]], [[1, 2, 3], [4, 5, 6]]}; 186b4e30b7SRiver Riddle 196b4e30b7SRiver Riddle # We pass these arguments to functions like we do with variables. 206b4e30b7SRiver Riddle var c = multiply_transpose(value); 216b4e30b7SRiver Riddle print(c); 226b4e30b7SRiver Riddle} 236b4e30b7SRiver Riddle 24*ee2c6cd9SRiver Riddle# CHECK-LABEL: toy.func private @multiply_transpose( 256b4e30b7SRiver Riddle# CHECK-SAME: [[VAL_0:%.*]]: !toy.struct<tensor<*xf64>, tensor<*xf64>>) -> tensor<*xf64> 260050e8f0SRiver Riddle# CHECK-NEXT: [[VAL_1:%.*]] = toy.struct_access [[VAL_0]][0] : !toy.struct<tensor<*xf64>, tensor<*xf64>> -> tensor<*xf64> 270050e8f0SRiver Riddle# CHECK-NEXT: [[VAL_2:%.*]] = toy.transpose([[VAL_1]] : tensor<*xf64>) to tensor<*xf64> 280050e8f0SRiver Riddle# CHECK-NEXT: [[VAL_3:%.*]] = toy.struct_access [[VAL_0]][1] : !toy.struct<tensor<*xf64>, tensor<*xf64>> -> tensor<*xf64> 290050e8f0SRiver Riddle# CHECK-NEXT: [[VAL_4:%.*]] = toy.transpose([[VAL_3]] : tensor<*xf64>) to tensor<*xf64> 300050e8f0SRiver Riddle# CHECK-NEXT: [[VAL_5:%.*]] = toy.mul [[VAL_2]], [[VAL_4]] : tensor<*xf64> 310050e8f0SRiver Riddle# CHECK-NEXT: toy.return [[VAL_5]] : tensor<*xf64> 326b4e30b7SRiver Riddle 33*ee2c6cd9SRiver Riddle# CHECK-LABEL: toy.func @main() 340050e8f0SRiver Riddle# 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>> 350050e8f0SRiver Riddle# CHECK-NEXT: [[VAL_7:%.*]] = toy.generic_call @multiply_transpose([[VAL_6]]) : (!toy.struct<tensor<*xf64>, tensor<*xf64>>) -> tensor<*xf64> 360050e8f0SRiver Riddle# CHECK-NEXT: toy.print [[VAL_7]] : tensor<*xf64> 370050e8f0SRiver Riddle# CHECK-NEXT: toy.return 386b4e30b7SRiver Riddle 39*ee2c6cd9SRiver Riddle# OPT-LABEL: toy.func @main() 400050e8f0SRiver Riddle# 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> 410050e8f0SRiver Riddle# OPT-NEXT: [[VAL_1:%.*]] = toy.transpose([[VAL_0]] : tensor<2x3xf64>) to tensor<3x2xf64> 420050e8f0SRiver Riddle# OPT-NEXT: [[VAL_2:%.*]] = toy.mul [[VAL_1]], [[VAL_1]] : tensor<3x2xf64> 430050e8f0SRiver Riddle# OPT-NEXT: toy.print [[VAL_2]] : tensor<3x2xf64> 440050e8f0SRiver Riddle# OPT-NEXT: toy.return 45