op-result.td
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// RUN: mlir-tblgen -gen-op-defs -I %S/../../include %s | FileCheck %s
include "mlir/IR/OpBase.td"
include "mlir/Interfaces/InferTypeOpInterface.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_result_op", []> {
let results = (outs I32:$result);
}
// CHECK-LABEL: void OpA::build
// CHECK: ::llvm::ArrayRef<::mlir::Type> resultTypes, ::mlir::ValueRange operands
// CHECK: assert(resultTypes.size() == 1u && "mismatched number of return types");
// CHECK-NEXT: odsState.addTypes(resultTypes);
def OpB : NS_Op<"same_input_output_type_op", [SameOperandsAndResultType]> {
let arguments = (ins I32:$x);
let results = (outs I32:$y);
}
// CHECK-LABEL: OpB definitions
// CHECK: void OpB::build(::mlir::OpBuilder &odsBuilder, ::mlir::OperationState &odsState, ::mlir::Type y, ::mlir::Value x)
// CHECK: odsState.addTypes(y);
// CHECK: void OpB::build(::mlir::OpBuilder &odsBuilder, ::mlir::OperationState &odsState, ::mlir::Value x)
// CHECK: odsState.addTypes({x.getType()});
def OpC : NS_Op<"three_normal_result_op", []> {
let results = (outs I32:$x, /*unnamed*/I32, I32:$z);
}
// CHECK-LABEL: OpC definitions
// CHECK: void OpC::build(::mlir::OpBuilder &odsBuilder, ::mlir::OperationState &odsState, ::mlir::Type x, ::mlir::Type resultType1, ::mlir::Type z)
// CHECK-NEXT: odsState.addTypes(x)
// CHECK-NEXT: odsState.addTypes(resultType1)
// CHECK-NEXT: odsState.addTypes(z)
// CHECK: void OpC::build(::mlir::OpBuilder &odsBuilder, ::mlir::OperationState &odsState, ::llvm::ArrayRef<::mlir::Type> resultTypes) {
// CHECK-NEXT: assert(resultTypes.size() == 3u && "mismatched number of results");
// CHECK-NEXT: odsState.addTypes(resultTypes);
def IntegerTypeAttr : TypeAttrBase<"IntegerType", "Integer type attribute">;
def OpD : NS_Op<"type_attr_as_result_type", [FirstAttrDerivedResultType]> {
let arguments = (ins I32:$x, IntegerTypeAttr:$attr, F32Attr:$f32);
let results = (outs AnyTensor:$y);
}
// CHECK-LABEL: OpD definitions
// CHECK: void OpD::build(::mlir::OpBuilder &odsBuilder, ::mlir::OperationState &odsState, ::mlir::ValueRange operands, ::llvm::ArrayRef<::mlir::NamedAttribute> attributes)
// CHECK: odsState.addTypes({attr.second.cast<::mlir::TypeAttr>().getValue()});
def OpE : NS_Op<"value_attr_as_result_type", [FirstAttrDerivedResultType]> {
let arguments = (ins I32:$x, F32Attr:$attr);
let results = (outs AnyTensor:$y);
}
// CHECK-LABEL: OpE definitions
// CHECK: void OpE::build(::mlir::OpBuilder &odsBuilder, ::mlir::OperationState &odsState, ::mlir::ValueRange operands, ::llvm::ArrayRef<::mlir::NamedAttribute> attributes)
// CHECK: odsState.addTypes({attr.second.getType()});
def OpF : NS_Op<"one_variadic_result_op", []> {
let results = (outs Variadic<I32>:$x);
}
// CHECK-LABEL: void OpF::build
// CHECK-SAME: ::llvm::ArrayRef<::mlir::Type> x
// CHECK-NOT: assert
// CHECK: odsState.addTypes(x);
def OpG : NS_Op<"one_normal_and_one_variadic_result_op", []> {
let results = (outs I32:$x, Variadic<I32>:$y);
}
// CHECK-LABEL: OpG definitions
// CHECK: void OpG::build(::mlir::OpBuilder &odsBuilder, ::mlir::OperationState &odsState, ::mlir::Type x, ::llvm::ArrayRef<::mlir::Type> y)
// CHECK-NEXT: odsState.addTypes(x);
// CHECK-NEXT: odsState.addTypes(y);
// CHECK: void OpG::build
// CHECK: ::llvm::ArrayRef<::mlir::Type> resultTypes
// CHECK: assert(resultTypes.size() >= 1u && "mismatched number of return types");
// CHECK-NEXT: odsState.addTypes(resultTypes);
def OpI : NS_Op<"mix_variadic_and_normal_results_op", [SameVariadicResultSize]> {
let results = (outs Variadic<AnyTensor>:$output1, AnyTensor:$output2, Variadic<AnyTensor>:$output3);
}
// CHECK-LABEL: ::mlir::Operation::result_range OpI::output1
// CHECK-NEXT: return getODSResults(0);
// CHECK-LABEL: ::mlir::Value OpI::output2
// CHECK-NEXT: return *getODSResults(1).begin();
// CHECK-LABEL: OpI::build
// CHECK-NEXT: odsState.addTypes(output1);
// CHECK-NEXT: odsState.addTypes(output2);
// CHECK-NEXT: odsState.addTypes(output3);
// Test that if the only operand is variadic, we access the first value in the
// pack to set result type
// ---
def OpK : NS_Op<"only_input_is_variadic_with_same_value_type_op", [SameOperandsAndResultType]> {
let arguments = (ins Variadic<AnyTensor>:$input);
let results = (outs AnyTensor:$result);
}
// CHECK-LABEL: OpK::build(::mlir::OpBuilder &odsBuilder, ::mlir::OperationState &odsState, ::mlir::ValueRange input)
// CHECK: odsState.addTypes({input.front().getType()});
// Test with inferred shapes and interleaved with operands/attributes.
//
def OpL : NS_Op<"op_with_all_types_constraint",
[AllTypesMatch<["a", "b"]>]> {
let arguments = (ins I32Attr:$attr1, AnyType:$a);
let results = (outs Res<AnyType, "output b", []>:$b);
}
// CHECK-LABEL: LogicalResult OpL::inferReturnTypes
// CHECK-NOT: }
// CHECK: inferredReturnTypes[0] = operands[0].getType();