From: Sebastian Messmer Date: Mon, 1 Apr 2019 21:53:08 +0000 (-0700) Subject: deprecated function based API (#18444) X-Git-Tag: accepted/tizen/6.5/unified/20211028.231830~501 X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=723ce02a55ab638c1afeb5068e15a8a22e7d5a6e;p=platform%2Fupstream%2Fpytorch.git deprecated function based API (#18444) Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/18444 This adds the deprecated function based API to c10::RegisterOperators(). This is the API currently exposed under jit::RegisterOperators() and we need to support it for backwards compatibility. Reviewed By: dzhulgakov Differential Revision: D14514218 fbshipit-source-id: c77676851cfd431d66f18fd8038cf153a3a7d7cc --- diff --git a/aten/src/ATen/core/op_registration/kernel_function_legacy_test.cpp b/aten/src/ATen/core/op_registration/kernel_function_legacy_test.cpp new file mode 100644 index 0000000..b122aea --- /dev/null +++ b/aten/src/ATen/core/op_registration/kernel_function_legacy_test.cpp @@ -0,0 +1,836 @@ +#include +#include + +#include +#include + +/** + * This file tests the legacy function-based API for registering kernels. + * + * > namespace { Tensor kernel(Tensor a) {...} } + * > static auto registry = c10::RegisterOperators() + * > .op("func(Tensor a) -> Tensor", &kernel); + */ + +using c10::RegisterOperators; +using c10::FunctionSchema; +using c10::Argument; +using c10::IntType; +using c10::FloatType; +using c10::ListType; +using c10::kernel; +using c10::dispatchKey; +using c10::TensorTypeId; +using c10::KernelCache; +using c10::Stack; +using c10::guts::make_unique; +using c10::ivalue::TensorList; +using c10::ivalue::IntList; +using c10::intrusive_ptr; +using c10::ArrayRef; +using std::unique_ptr; +using at::Tensor; + +namespace { + +C10_DECLARE_TENSOR_TYPE(TensorType1); +C10_DEFINE_TENSOR_TYPE(TensorType1); +C10_DECLARE_TENSOR_TYPE(TensorType2); +C10_DEFINE_TENSOR_TYPE(TensorType2); + +int64_t errorKernel(const Tensor& tensor, int64_t input) { + EXPECT_TRUE(false); // this kernel should never be called + return 0; +} + +FunctionSchema errorOpSchema( + "_test::error", + "", + (std::vector{Argument("dummy"), + Argument("input", IntType::get())}), + (std::vector{Argument("output", IntType::get())})); + +int64_t incrementKernel(const Tensor& tensor, int64_t input) { + return input + 1; +} + +int64_t decrementKernel(const Tensor& tensor, int64_t input) { + return input - 1; +} + +FunctionSchema opSchema( + "_test::my_op", + "", + (std::vector{Argument("dummy"), + Argument("input", IntType::get())}), + (std::vector{Argument("output", IntType::get())})); + +void expectCallsIncrement(TensorTypeId type_id) { + // assert that schema and cpu kernel are present + auto op = c10::Dispatcher::singleton().findSchema("_test::my_op", ""); + ASSERT_TRUE(op.has_value()); + auto result = callOp(*op, dummyTensor(type_id), 5); + EXPECT_EQ(1, result.size()); + EXPECT_EQ(6, result[0].toInt()); +} + +void expectCallsDecrement(TensorTypeId type_id) { + // assert that schema and cpu kernel are present + auto op = c10::Dispatcher::singleton().findSchema("_test::my_op", ""); + ASSERT_TRUE(op.has_value()); + auto result = callOp(*op, dummyTensor(type_id), 5); + EXPECT_EQ(1, result.size()); + EXPECT_EQ(4, result[0].toInt()); +} + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenKernel_whenRegistered_thenCanBeCalled) { + auto registrar = RegisterOperators().op(opSchema, &incrementKernel); + expectCallsIncrement(TensorType1()); +} + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenMultipleOperatorsAndKernels_whenRegisteredInOneRegistrar_thenCallsRightKernel) { + auto registrar = RegisterOperators() + .op(opSchema, &incrementKernel) + .op(errorOpSchema, &errorKernel); + expectCallsIncrement(TensorType1()); +} + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenMultipleOperatorsAndKernels_whenRegisteredInMultipleRegistrars_thenCallsRightKernel) { + auto registrar1 = RegisterOperators().op(opSchema, &incrementKernel); + auto registrar2 = RegisterOperators().op(errorOpSchema, &errorKernel); + expectCallsIncrement(TensorType1()); +} + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenKernel_whenRegistrationRunsOutOfScope_thenCannotBeCalledAnymore) { + { + auto registrar = RegisterOperators().op(opSchema, &incrementKernel); + + expectCallsIncrement(TensorType1()); + } + + // now the registrar is destructed. Assert that the schema is gone. + expectDoesntFindOperator("_test::my_op"); +} + +bool was_called = false; + +void kernelWithoutOutput(const Tensor&) { + was_called = true; +} + +FunctionSchema opWithoutOutputSchema( + "_test::no_return", + "", + (std::vector{Argument("dummy")}), + (std::vector{})); + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenKernelWithoutOutput_whenRegistered_thenCanBeCalled) { + auto registrar = RegisterOperators().op(opWithoutOutputSchema, &kernelWithoutOutput); + + auto op = c10::Dispatcher::singleton().findSchema("_test::no_return", ""); + ASSERT_TRUE(op.has_value()); + was_called = false; + auto result = callOp(*op, dummyTensor(TensorType1())); + EXPECT_TRUE(was_called); + EXPECT_EQ(0, result.size()); +} + +std::tuple<> kernelWithZeroOutputs(const Tensor&) { + was_called = true; + return std::make_tuple(); +} + +FunctionSchema opWithZeroOutputsSchema( + "_test::zero_outputs", + "", + (std::vector{Argument("dummy")}), + (std::vector{})); + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenKernelWithZeroOutputs_whenRegistered_thenCanBeCalled) { + auto registrar = RegisterOperators().op(opWithZeroOutputsSchema, &kernelWithZeroOutputs); + + auto op = c10::Dispatcher::singleton().findSchema("_test::zero_outputs", ""); + ASSERT_TRUE(op.has_value()); + was_called = false; + auto result = callOp(*op, dummyTensor(TensorType1())); + EXPECT_TRUE(was_called); + EXPECT_EQ(0, result.size()); +} + +int64_t kernelWithIntOutput(Tensor, int64_t a, int64_t b) { + return a + b; +} + +FunctionSchema opWithIntOutputSchema( + "_test::int_output", + "", + (std::vector{Argument("dummy"), + Argument("a", IntType::get()), + Argument("b", IntType::get())}), + (std::vector{Argument("sum", IntType::get())})); + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenKernelWithIntOutput_whenRegistered_thenCanBeCalled) { + auto registrar = RegisterOperators() + .op(opWithIntOutputSchema, &kernelWithIntOutput); + + auto op = c10::Dispatcher::singleton().findSchema("_test::int_output", ""); + ASSERT_TRUE(op.has_value()); + + auto result = callOp(*op, dummyTensor(TensorType1()), 3, 6); + EXPECT_EQ(1, result.size()); + EXPECT_EQ(9, result[0].toInt()); +} + +Tensor kernelWithTensorOutput(const Tensor& input) { + return input; +} + +FunctionSchema opWithTensorOutput( + "_test::returning_tensor", + "", + (std::vector{Argument("input")}), + (std::vector{Argument("output")})); + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenKernelWithTensorOutput_whenRegistered_thenCanBeCalled) { + auto registrar = RegisterOperators() + .op(opWithTensorOutput, &kernelWithTensorOutput); + + auto op = c10::Dispatcher::singleton().findSchema("_test::returning_tensor", ""); + ASSERT_TRUE(op.has_value()); + + auto result = callOp(*op, dummyTensor(TensorType1())); + EXPECT_EQ(1, result.size()); + EXPECT_EQ(TensorType1(), result[0].toTensor().type_id()); + + result = callOp(*op, dummyTensor(TensorType2())); + EXPECT_EQ(1, result.size()); + EXPECT_EQ(TensorType2(), result[0].toTensor().type_id()); +} + +std::vector kernelWithTensorListOutput(const Tensor& input1, const Tensor& input2, const Tensor& input3) { + return {input1, input2, input3}; +} + +FunctionSchema opWithTensorListOutputSchema( + "_test::list_output", + "", + (std::vector{Argument("input1"), + Argument("input2"), + Argument("input3")}), + (std::vector{Argument("output", ListType::ofTensors())})); + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenKernelWithTensorListOutput_whenRegistered_thenCanBeCalled) { + auto registrar = RegisterOperators() + .op(opWithTensorListOutputSchema, &kernelWithTensorListOutput); + + auto op = c10::Dispatcher::singleton().findSchema("_test::list_output", ""); + ASSERT_TRUE(op.has_value()); + + auto result = callOp(*op, dummyTensor(TensorType1()), dummyTensor(TensorType2()), dummyTensor(TensorType1())); + EXPECT_EQ(1, result.size()); + EXPECT_EQ(3, result[0].toTensorListRef().size()); + EXPECT_EQ(TensorType1(), result[0].toTensorListRef()[0].type_id()); + EXPECT_EQ(TensorType2(), result[0].toTensorListRef()[1].type_id()); + EXPECT_EQ(TensorType1(), result[0].toTensorListRef()[2].type_id()); +} + +std::vector kernelWithIntListOutput(const Tensor&, int64_t input1, int64_t input2, int64_t input3) { + return {input1, input2, input3}; +} + +FunctionSchema opWithIntListOutputSchema( + "_test::list_output", + "", + (std::vector{Argument("dummy"), + Argument("input1", IntType::get()), + Argument("input2", IntType::get()), + Argument("input3", IntType::get())}), + (std::vector{Argument("output", ListType::ofInts())})); + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenKernelWithIntListOutput_whenRegistered_thenCanBeCalled) { + auto registrar = RegisterOperators() + .op(opWithIntListOutputSchema, &kernelWithIntListOutput); + + auto op = c10::Dispatcher::singleton().findSchema("_test::list_output", ""); + ASSERT_TRUE(op.has_value()); + + auto result = callOp(*op, dummyTensor(TensorType1()), 2, 4, 6); + EXPECT_EQ(1, result.size()); + EXPECT_EQ(3, result[0].toIntListRef().size()); + EXPECT_EQ(2, result[0].toIntListRef()[0]); + EXPECT_EQ(4, result[0].toIntListRef()[1]); + EXPECT_EQ(6, result[0].toIntListRef()[2]); +} + +std::tuple> kernelWithMultipleOutputs(Tensor) { + return std::tuple>( + dummyTensor(TensorType2()), 5, {dummyTensor(TensorType1()), dummyTensor(TensorType2())} + ); +} + +FunctionSchema opWithMultipleOutputsSchema( + "_test::multiple_outputs", + "", + (std::vector{Argument("dummy")}), + (std::vector{Argument("output1"), + Argument("output2", IntType::get()), + Argument("output3", ListType::ofTensors())})); + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenKernelWithMultipleOutputs_whenRegistered_thenCanBeCalled) { + auto registrar = RegisterOperators() + .op(opWithMultipleOutputsSchema, &kernelWithMultipleOutputs); + + auto op = c10::Dispatcher::singleton().findSchema("_test::multiple_outputs", ""); + ASSERT_TRUE(op.has_value()); + + auto result = callOp(*op, dummyTensor(TensorType1())); + EXPECT_EQ(3, result.size()); + EXPECT_EQ(TensorType2(), result[0].toTensor().type_id()); + EXPECT_EQ(5, result[1].toInt()); + EXPECT_EQ(2, result[2].toTensorListRef().size()); + EXPECT_EQ(TensorType1(), result[2].toTensorListRef()[0].type_id()); + EXPECT_EQ(TensorType2(), result[2].toTensorListRef()[1].type_id()); +} + +Tensor kernelWithTensorInputByReferenceWithOutput(const Tensor& input1) { + return input1; +} + +Tensor kernelWithTensorInputByValueWithOutput(Tensor input1) { + return input1; +} + +FunctionSchema opWithTensorInputWithOutput( + "_test::tensor_input", + "", + (std::vector{Argument("input")}), + (std::vector{Argument("output")})); + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenKernelWithTensorInputByReference_withOutput_whenRegistered_thenCanBeCalled) { + auto registrar = RegisterOperators() + .op(opWithTensorInputWithOutput, &kernelWithTensorInputByReferenceWithOutput); + + auto op = c10::Dispatcher::singleton().findSchema("_test::tensor_input", ""); + ASSERT_TRUE(op.has_value()); + + auto result = callOp(*op, dummyTensor(TensorType1())); + EXPECT_EQ(1, result.size()); + EXPECT_EQ(TensorType1(), result[0].toTensor().type_id()); + + result = callOp(*op, dummyTensor(TensorType2())); + EXPECT_EQ(1, result.size()); + EXPECT_EQ(TensorType2(), result[0].toTensor().type_id()); +} + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenKernelWithTensorInputByValue_withOutput_whenRegistered_thenCanBeCalled) { + auto registrar = RegisterOperators() + .op(opWithTensorInputWithOutput, &kernelWithTensorInputByValueWithOutput); + + auto op = c10::Dispatcher::singleton().findSchema("_test::tensor_input", ""); + ASSERT_TRUE(op.has_value()); + + auto result = callOp(*op, dummyTensor(TensorType1())); + EXPECT_EQ(1, result.size()); + EXPECT_EQ(TensorType1(), result[0].toTensor().type_id()); + + result = callOp(*op, dummyTensor(TensorType2())); + EXPECT_EQ(1, result.size()); + EXPECT_EQ(TensorType2(), result[0].toTensor().type_id()); +} + +Tensor captured_input; + +void kernelWithTensorInputByReferenceWithoutOutput(const Tensor& input1) { + captured_input = input1; +} + +void kernelWithTensorInputByValueWithoutOutput(Tensor input1) { + captured_input = input1; +} + +FunctionSchema opWithTensorInputWithoutOutput( + "_test::tensor_input", + "", + (std::vector{Argument("input")}), + (std::vector{})); + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenKernelWithTensorInputByReference_withoutOutput_whenRegistered_thenCanBeCalled) { + auto registrar = RegisterOperators() + .op(opWithTensorInputWithoutOutput, &kernelWithTensorInputByReferenceWithoutOutput); + + auto op = c10::Dispatcher::singleton().findSchema("_test::tensor_input", ""); + ASSERT_TRUE(op.has_value()); + + auto outputs = callOp(*op, dummyTensor(TensorType1())); + EXPECT_EQ(0, outputs.size()); + EXPECT_EQ(TensorType1(), captured_input.type_id()); + + outputs = callOp(*op, dummyTensor(TensorType2())); + EXPECT_EQ(0, outputs.size()); + EXPECT_EQ(TensorType2(), captured_input.type_id()); +} + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenKernelWithTensorInputByValue_withoutOutput_whenRegistered_thenCanBeCalled) { + auto registrar = RegisterOperators() + .op(opWithTensorInputWithoutOutput, &kernelWithTensorInputByValueWithoutOutput); + + auto op = c10::Dispatcher::singleton().findSchema("_test::tensor_input", ""); + ASSERT_TRUE(op.has_value()); + + auto outputs = callOp(*op, dummyTensor(TensorType1())); + EXPECT_EQ(0, outputs.size()); + EXPECT_EQ(TensorType1(), captured_input.type_id()); + + outputs = callOp(*op, dummyTensor(TensorType2())); + EXPECT_EQ(0, outputs.size()); + EXPECT_EQ(TensorType2(), captured_input.type_id()); +} + +int64_t captured_int_input = 0; + +void kernelWithIntInputWithoutOutput(Tensor, int64_t input1) { + captured_int_input = input1; +} + +FunctionSchema opWithIntInputWithoutOutput( + "_test::int_input", + "", + (std::vector{Argument("dummy"), + Argument("input", IntType::get())}), + (std::vector{})); + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenKernelWithIntInput_withoutOutput_whenRegistered_thenCanBeCalled) { + auto registrar = RegisterOperators() + .op(opWithIntInputWithoutOutput, &kernelWithIntInputWithoutOutput); + + auto op = c10::Dispatcher::singleton().findSchema("_test::int_input", ""); + ASSERT_TRUE(op.has_value()); + + captured_int_input = 0; + auto outputs = callOp(*op, dummyTensor(TensorType1()), 3); + EXPECT_EQ(0, outputs.size()); + EXPECT_EQ(3, captured_int_input); +} + +int64_t kernelWithIntInputWithOutput(Tensor, int64_t input1) { + return input1 + 1; +} + +FunctionSchema opWithIntInputWithOutput( + "_test::int_input", + "", + (std::vector{Argument("dummy"), + Argument("input", IntType::get())}), + (std::vector{Argument("output", IntType::get())})); + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenKernelWithIntInput_withOutput_whenRegistered_thenCanBeCalled) { + auto registrar = RegisterOperators() + .op(opWithIntInputWithOutput, &kernelWithIntInputWithOutput); + + auto op = c10::Dispatcher::singleton().findSchema("_test::int_input", ""); + ASSERT_TRUE(op.has_value()); + + auto outputs = callOp(*op, dummyTensor(TensorType1()), 3); + EXPECT_EQ(1, outputs.size()); + EXPECT_EQ(4, outputs[0].toInt()); +} + +int64_t captured_input_list_size = 0; + +void kernelWithIntListInputWithoutOutput(Tensor, ArrayRef input1) { + captured_input_list_size = input1.size(); +} + +FunctionSchema opWithIntListInputWithoutOutput( + "_test::int_list_input", + "", + (std::vector{Argument("dummy"), + Argument("input", ListType::ofInts())}), + (std::vector{})); + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenKernelWithIntListInput_withoutOutput_whenRegistered_thenCanBeCalled) { + auto registrar = RegisterOperators() + .op(opWithIntListInputWithoutOutput, &kernelWithIntListInputWithoutOutput); + + auto op = c10::Dispatcher::singleton().findSchema("_test::int_list_input", ""); + ASSERT_TRUE(op.has_value()); + + captured_input_list_size = 0; + auto outputs = callOp(*op, dummyTensor(TensorType1()), IntList::create({2, 4, 6})); + EXPECT_EQ(0, outputs.size()); + EXPECT_EQ(3, captured_input_list_size); +} + +int64_t kernelWithIntListInputWithOutput(Tensor, ArrayRef input1) { + return input1.size(); +} + +FunctionSchema opWithIntListInputWithOutput( + "_test::int_list_input", + "", + (std::vector{Argument("dummy"), + Argument("input", ListType::ofInts())}), + (std::vector{Argument("output", IntType::get())})); + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenKernelWithIntListInput_withOutput_whenRegistered_thenCanBeCalled) { + auto registrar = RegisterOperators() + .op(opWithIntListInputWithOutput, &kernelWithIntListInputWithOutput); + + auto op = c10::Dispatcher::singleton().findSchema("_test::int_list_input", ""); + ASSERT_TRUE(op.has_value()); + + auto outputs = callOp(*op, dummyTensor(TensorType1()), IntList::create({2, 4, 6})); + EXPECT_EQ(1, outputs.size()); + EXPECT_EQ(3, outputs[0].toInt()); +} + +void kernelWithTensorListInputWithoutOutput(ArrayRef input1) { + captured_input_list_size = input1.size(); +} + +FunctionSchema opWithTensorListInputWithoutOutput( + "_test::tensor_list_input", + "", + (std::vector{Argument("input", ListType::ofTensors())}), + (std::vector{})); + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenKernelWithTensorListInput_withoutOutput_whenRegistered_thenCanBeCalled) { + auto registrar = RegisterOperators() + .op(opWithTensorListInputWithoutOutput, &kernelWithTensorListInputWithoutOutput); + + auto op = c10::Dispatcher::singleton().findSchema("_test::tensor_list_input", ""); + ASSERT_TRUE(op.has_value()); + + captured_input_list_size = 0; + auto outputs = callOp(*op, TensorList::create({dummyTensor(TensorType1()), dummyTensor(TensorType1())})); + EXPECT_EQ(0, outputs.size()); + EXPECT_EQ(2, captured_input_list_size); +} + +int64_t kernelWithTensorListInputWithOutput(ArrayRef input1) { + return input1.size(); +} + +FunctionSchema opWithTensorListInputWithOutput( + "_test::tensor_list_input", + "", + (std::vector{Argument("input", ListType::ofTensors())}), + (std::vector{Argument("output", IntType::get())})); + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenKernelWithTensorListInput_withOutput_whenRegistered_thenCanBeCalled) { + auto registrar = RegisterOperators() + .op(opWithTensorListInputWithOutput, &kernelWithTensorListInputWithOutput); + + auto op = c10::Dispatcher::singleton().findSchema("_test::tensor_list_input", ""); + ASSERT_TRUE(op.has_value()); + + auto outputs = callOp(*op, TensorList::create({dummyTensor(TensorType1()), dummyTensor(TensorType1())})); + EXPECT_EQ(1, outputs.size()); + EXPECT_EQ(2, outputs[0].toInt()); +} + +template struct kernel_func final { + static Return func(Args...) { return {}; } +}; +template struct kernel_func final { + static void func(Args...) {} +}; + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenMismatchedKernel_withDifferentNumArguments_whenRegistering_thenFails) { + // assert this does not fail because it matches + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg")}), + (std::vector{Argument("ret", IntType::get())}) + ), &kernel_func::func); + + // and now a set of mismatching schemas + EXPECT_THROW( + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg"), Argument("arg2")}), + (std::vector{Argument("ret", IntType::get())}) + ), &kernel_func::func), + c10::Error + ); + + // assert this does not fail because it matches + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg"), Argument("arg2")}), + (std::vector{}) + ), &kernel_func::func); + + // and now a set of mismatching schemas + EXPECT_THROW( + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{}), + (std::vector{}) + ), &kernel_func::func), + c10::Error + ); + + EXPECT_THROW( + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg")}), + (std::vector{}) + ), &kernel_func::func), + c10::Error + ); + + EXPECT_THROW( + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg"), Argument("arg2"), Argument("arg3")}), + (std::vector{}) + ), &kernel_func::func), + c10::Error + ); +} + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenMismatchedKernel_withDifferentArgumentType_whenRegistering_thenFails) { + // assert this does not fail because it matches + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg1"), Argument("arg2", IntType::get())}), + (std::vector{Argument("ret", IntType::get())}) + ), &kernel_func::func); + + // and now a set of mismatching schemas + EXPECT_THROW( + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg1"), Argument("arg2", FloatType::get())}), + (std::vector{Argument("ret", IntType::get())}) + ), &kernel_func::func), + c10::Error + ); + + EXPECT_THROW( + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg1", IntType::get()), Argument("arg2", IntType::get())}), + (std::vector{Argument("ret", IntType::get())}) + ), &kernel_func::func), + c10::Error + ); +} + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenMismatchedKernel_withDifferentNumReturns_whenRegistering_thenFails) { + // assert this does not fail because it matches + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg")}), + (std::vector{Argument("ret", IntType::get())}) + ), &kernel_func::func); + + // and now a set of mismatching schemas + EXPECT_THROW( + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg")}), + (std::vector{}) + ), &kernel_func::func), + c10::Error + ); + + EXPECT_THROW( + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg")}), + (std::vector{Argument("ret1", IntType::get()), + Argument("ret2", IntType::get())}) + ), &kernel_func::func), + c10::Error + ); + + // assert this does not fail because it matches + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg")}), + (std::vector{}) + ), &kernel_func::func); + + // and now a set of mismatching schemas + EXPECT_THROW( + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg")}), + (std::vector{Argument("ret")}) + ), &kernel_func::func), + c10::Error + ); + + EXPECT_THROW( + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg")}), + (std::vector{Argument("ret"), Argument("ret2")}) + ), &kernel_func::func), + c10::Error + ); + + // assert this does not fail because it matches + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg")}), + (std::vector{Argument("ret1"), Argument("ret2")}) + ), &kernel_func, Tensor>::func); + + // and now a set of mismatching schemas + EXPECT_THROW( + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg")}), + (std::vector{}) + ), &kernel_func, Tensor>::func), + c10::Error + ); + + EXPECT_THROW( + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg")}), + (std::vector{Argument("ret1")}) + ), &kernel_func, Tensor>::func), + c10::Error + ); + + EXPECT_THROW( + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg")}), + (std::vector{Argument("ret1"), Argument("ret2"), Argument("ret3")}) + ), &kernel_func, Tensor>::func), + c10::Error + ); +} + +TEST(OperatorRegistrationTest_LegacyFunctionBasedKernel, givenMismatchedKernel_withDifferentReturnTypes_whenRegistering_thenFails) { + // assert this does not fail because it matches + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg")}), + (std::vector{Argument("ret", IntType::get())}) + ), &kernel_func::func); + + // and now a set of mismatching schemas + EXPECT_THROW( + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg")}), + (std::vector{Argument("ret")}) + ), &kernel_func::func), + c10::Error + ); + + EXPECT_THROW( + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg")}), + (std::vector{Argument("ret", FloatType::get())}) + ), &kernel_func::func), + c10::Error + ); + + // assert this does not fail because it matches + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg")}), + (std::vector{Argument("ret")}) + ), &kernel_func::func); + + // and now a set of mismatching schemas + EXPECT_THROW( + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg")}), + (std::vector{Argument("ret", FloatType::get())}) + ), &kernel_func::func), + c10::Error + ); + + // assert this does not fail because it matches + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg")}), + (std::vector{Argument("ret1"), Argument("ret2", IntType::get())}) + ), &kernel_func, Tensor>::func); + + // and now a set of mismatching schemas + EXPECT_THROW( + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg")}), + (std::vector{Argument("ret1"), Argument("ret2", FloatType::get())}) + ), &kernel_func, Tensor>::func), + c10::Error + ); + + EXPECT_THROW( + RegisterOperators() + .op(FunctionSchema( + "_test::mismatch", + "", + (std::vector{Argument("arg")}), + (std::vector{Argument("ret1", IntType::get()), Argument("ret2", IntType::get())}) + ), &kernel_func, Tensor>::func), + c10::Error + ); +} + +} diff --git a/aten/src/ATen/core/op_registration/op_registration.h b/aten/src/ATen/core/op_registration/op_registration.h index 29b4895..15d03e3 100644 --- a/aten/src/ATen/core/op_registration/op_registration.h +++ b/aten/src/ATen/core/op_registration/op_registration.h @@ -70,7 +70,51 @@ public: return std::move(*this); } - // TODO Add deprecated function and lambda based kernel APIs + // TODO allow input schema to be just the operator name + overload name, in that case use schema generated from kernel function + + /** + * Deprecated. For backwards compatibility only. + * Don't use this, it introduces a performance overhead on each kernel call + * due to the kernel being stored in the wrapper as a runtime function pointer. + * + * Given a kernel + * + * > namespace { Tensor my_kernel_cpu(Tensor a, Tensor b) {...} } + * + * This deprecated API looks like: + * + * > static auto registry = c10::RegisterOperators() + * > .op("my_op", &my_kernel_cpu); + * + * But you should use the new API instead: + * + * > static auto registry = c10::RegisterOperators() + * > .op("my_op", kernel()); + * + * Or, alternatively, write your kernel as a functor: + * + * > namespace { + * > class my_kernel_cpu final : public c10::OperatorKernel { + * > public: + * > Tensor operator()(Tensor a, Tensor b) {...} + * > }; + * > } + * > + * > static auto registry = c10::RegisterOperators() + * > .op("my_op", c10::kernel()); + */ + template + C10_DEPRECATED_MESSAGE("Registering kernels via passing function pointers to op() directly is deprecated. " \ + "Please use the new c10::kernel() based API instead.") + // enable_if: only enable it if FuncType is actually a function, but not a stack based KernelFunction. + guts::enable_if_t::value && !std::is_same::value, RegisterOperators> + op(FunctionSchema schema, FuncType* func) && { + // We intentionally don't extend this deprecated API to support dispatch keys + // and the like to push people towards using the new API. + return std::move(*this).op(std::move(schema), kernel>(func)); + } + + // TODO Add deprecated lambda-based API private: void registerOp_(FunctionSchema&& schema, detail::KernelRegistrationConfig&& config);