op-operand.td
1.82 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
// RUN: mlir-tblgen -gen-op-defs -I %S/../../include %s | FileCheck %s
include "mlir/IR/OpBase.td"
def Test_Dialect : Dialect {
let name = "test";
}
class NS_Op<string mnemonic, list<OpTrait> traits> :
Op<Test_Dialect, mnemonic, traits>;
def OpA : NS_Op<"one_normal_operand_op", []> {
let arguments = (ins I32:$input);
}
// CHECK-LABEL: OpA definitions
// CHECK: OpAOperandAdaptor::OpAOperandAdaptor
// CHECK-NEXT: tblgen_operands = values
// CHECK: void OpA::build
// CHECK: Value input
// CHECK: tblgen_state.addOperands(input);
// CHECK: void OpA::build
// CHECK: ValueRange operands
// CHECK: assert(operands.size() == 1u && "mismatched number of parameters");
// CHECK: tblgen_state.addOperands(operands);
def OpB : NS_Op<"one_variadic_operand_op", []> {
let arguments = (ins Variadic<I32>:$input);
}
// CHECK-LABEL: OpB::build
// CHECK: ValueRange input
// CHECK-NOT: assert
// CHECK: tblgen_state.addOperands(input);
def OpD : NS_Op<"mix_variadic_and_normal_inputs_op", [SameVariadicOperandSize]> {
let arguments = (ins Variadic<AnyTensor>:$input1, AnyTensor:$input2, Variadic<AnyTensor>:$input3);
}
// CHECK-LABEL: ArrayRef<Value> OpDOperandAdaptor::input1
// CHECK-NEXT: return getODSOperands(0);
// CHECK-LABEL: Value OpDOperandAdaptor::input2
// CHECK-NEXT: return *getODSOperands(1).begin();
// CHECK-LABEL: ArrayRef<Value> OpDOperandAdaptor::input3
// CHECK-NEXT: return getODSOperands(2);
// CHECK-LABEL: Operation::operand_range OpD::input1
// CHECK-NEXT: return getODSOperands(0);
// CHECK-LABEL: Value OpD::input2
// CHECK-NEXT: return *getODSOperands(1).begin();
// CHECK-LABEL: OpD::build
// CHECK-NEXT: tblgen_state.addOperands(input1);
// CHECK-NEXT: tblgen_state.addOperands(input2);
// CHECK-NEXT: tblgen_state.addOperands(input3);