// Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. #include #include #include #include #include #ifndef _WIN32 #include #endif #include "paddle/fluid/framework/op_info.h" #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/framework/operator.h" #include "paddle/fluid/framework/variable.h" #include "paddle/fluid/pybind/pybind.h" #include "paddle/fluid/string/string_helper.h" #ifdef PADDLE_WITH_ASCEND_CL #include "paddle/fluid/framework/fleet/ascend_wrapper.h" #endif #include "paddle/fluid/pybind/op_function_generator.h" // clang-format off const char* OUT_INITIALIZER_TEMPLATE = R"({"%s", {std::shared_ptr(new imperative::VarBase("auto_"+std::to_string(VarBaseUniqueNameID++)+"_"))}})"; const char* OUT_DUPLICABLE_INITIALIZER_TEMPLATE = R"({"%s", ConstructDuplicableOutput(%s)})"; const char* INPUT_INITIALIZER_TEMPLATE = R"({"%s", {%s}})"; const char* INPUT_LIST_INITIALIZER_TEMPLATE = R"({"%s", %s})"; const char* INPUT_INITIALIZER_TEMPLATE_WITH_NULL = R"( if (%s != nullptr) { ins["%s"] = {%s}; } )"; const char* INPUT_INITIALIZER_TEMPLATE_WITH_NULL_LIST = R"( if (%s.size() != 0) { ins["%s"] = %s; } )"; const char* OUTPUT_INITIALIZER_TEMPLATE_WITH_NULL = R"( outs["%s"] = {%s}; )"; const char* OUTPUT_INITIALIZER_TEMPLATE_WITH_NULL_LIST = R"( outs["%s"] = %s; )"; // if inputs is list, no need {} const char* ARG_OUT_NUM = R"(%sNum)"; const char* ARG_OUT_NUM_TYPE = R"(size_t )"; const char* IN_VAR_TYPE = R"(py::handle)"; const char* IN_VAR_LIST_TYPE = R"(py::handle)"; const char* OUT_VAR_TYPE = R"(std::shared_ptr)"; const char* OUT_VAR_LIST_TYPE = R"(std::vector>)"; const char* CAST_VAR_TEMPLATE = R"( auto& %s = GetEagerTensorFromArgs("%s", "%s", args, %d, %s);)"; const char* CAST_VAR_LIST_TEMPLATE = R"( auto %s = GetEagerTensorListFromArgs("%s", "%s", args, %d, %s);)"; const char* CAST_VAR_PTR_TEMPLATE = R"( auto %s = GetEagerTensorPtrFromArgs("%s", "%s", args, %d, %s);)"; const char* CAST_VAR_PTR_LIST_TEMPLATE = R"( auto %s = GetEagerTensorPtrListFromArgs("%s", "%s", args, %d, %s);)"; const char* CAST_SIZE_T_TEMPLATE = R"( auto %s = GetUnsignedLongFromArgs("%s", "%s", args, %d, %s);)"; const char* ARG_TEMPLATE = R"(const %s& %s)"; const char* RETURN_TUPLE_TYPE = R"(std::tuple<%s>)"; const char* RETURN_TUPLE_TEMPLATE = R"(std::make_tuple(%s))"; const char* RETURN_LIST_TEMPLATE = R"(outs["%s"])"; const char* RETURN_TEMPLATE = R"(outs["%s"][0])"; const char* FUNCTION_ARGS = R"(%s, const py::args& args)"; const char* FUNCTION_ARGS_NO_INPUT = R"(const py::args& args)"; const char* HANDLE_VIEW_BETWEEN_INPUT_AND_OUTPUT = R"( if (ins.count("%s") && outs.count("%s")) { HandleViewBetweenInputAndOutput(ins["%s"][0], outs["%s"][0]); })"; const char* OP_FUNCTION_TEMPLATE = R"( static PyObject * %s(PyObject *self, PyObject *args, PyObject *kwargs) { PyThreadState *tstate = nullptr; try { %s framework::AttributeMap attrs; ConstructAttrMapFromPyArgs("%s", args, %d, PyTuple_GET_SIZE(args) , attrs); tstate = PyEval_SaveThread(); %s PyEval_RestoreThread(tstate); tstate = nullptr; %s } catch(...) { if (tstate) { PyEval_RestoreThread(tstate); } ThrowExceptionToPython(std::current_exception()); return nullptr; } })"; const char* PYBIND_ITEM_TEMPLATE = R"( {"%s", (PyCFunction)(void(*)(void))%s, METH_VARARGS | METH_KEYWORDS, "C++ interface function for %s in dygraph."},)"; // clang-format on static inline bool FindInsMap(const std::string& op_type, const std::string& in_name) { return op_ins_map[op_type].count(in_name); } static inline bool FindOutsMap(const std::string& op_type, const std::string& out_name) { return op_outs_map[op_type].count(out_name); } static inline bool FindPassingOutsMap(const std::string& op_type, const std::string& out_name) { return op_passing_outs_map[op_type].count(out_name); } static inline bool FindViewOpMap(const std::string& op_type) { return view_op_map.count(op_type); } static inline std::string TempName(const std::string& name) { return name + '_'; } std::string GenerateOpFunctionsBody( const paddle::framework::proto::OpProto* op_proto, std::string func_name, bool use_inplace_strategy = false, std::map inplace_map = {}) { auto& op_type = op_proto->type(); std::string input_args = ""; std::string call_api_str = "auto out = " + op_type + "_dygraph_function("; std::string ins_initializer_with_null = ""; std::string py_arg = ""; int arg_idx = 0; int input_args_num = 0; std::string ins_cast_str = ""; std::string view_strategy_str = ""; for (auto& input : op_proto->inputs()) { auto& in_name = input.name(); // skip those dispensable inputs, like ResidualData in conv2d if (input.dispensable() && !FindInsMap(op_type, in_name)) { continue; } const auto in_type = input.duplicable() ? IN_VAR_LIST_TYPE : IN_VAR_TYPE; auto input_arg = paddle::string::Sprintf(ARG_TEMPLATE, in_type, TempName(in_name)); input_args += input_arg; input_args += ","; input_args_num++; const auto in_cast_type = input.duplicable() ? CAST_VAR_LIST_TEMPLATE : CAST_VAR_TEMPLATE; auto dispensable = input.dispensable() ? "true" : "false"; ins_cast_str += paddle::string::Sprintf(in_cast_type, in_name, op_type, in_name, arg_idx++, dispensable); call_api_str += in_name + ", "; } if (!input_args.empty() && input_args.back() == ',') { input_args.pop_back(); } // Generate outs initializer std::string outs_initializer = "{"; std::string outs_initializer_with_null = ""; std::string return_str = ""; int outs_num = 0; for (auto& output : op_proto->outputs()) { auto& out_name = output.name(); // skip those dispensable oututs if (output.dispensable() && !FindOutsMap(op_type, out_name)) { continue; } const auto out_type = output.duplicable() ? OUT_VAR_LIST_TYPE : OUT_VAR_TYPE; if (FindPassingOutsMap(op_type, out_name)) { if (input_args != "") { input_args += ","; } input_args += out_type; input_args += out_name; input_args_num++; if (output.dispensable()) { const auto out_template = output.duplicable() ? OUTPUT_INITIALIZER_TEMPLATE_WITH_NULL_LIST : OUTPUT_INITIALIZER_TEMPLATE_WITH_NULL; outs_initializer_with_null += paddle::string::Sprintf(out_template, out_name, out_name); } else { const auto out_template = output.duplicable() ? INPUT_LIST_INITIALIZER_TEMPLATE : INPUT_INITIALIZER_TEMPLATE; outs_initializer += paddle::string::Sprintf(out_template, out_name, out_name); outs_initializer += ","; } const auto in_cast_type = output.duplicable() ? CAST_VAR_PTR_LIST_TEMPLATE : CAST_VAR_PTR_TEMPLATE; auto dispensable = output.dispensable() ? "true" : "false"; ins_cast_str += paddle::string::Sprintf(in_cast_type, out_name, op_type, out_name, arg_idx++, dispensable); call_api_str += out_name + ", "; } else { // There are few Operators that have duplicable output, like `Out` in // split op. We need to specify the number of variables for the // duplicable output, as the argument OutNum; if (output.duplicable()) { if (input_args != "") { input_args += ","; } auto out_num_str = paddle::string::Sprintf(ARG_OUT_NUM, out_name); input_args += ARG_OUT_NUM_TYPE; input_args += out_num_str; input_args_num++; outs_initializer += paddle::string::Sprintf( OUT_DUPLICABLE_INITIALIZER_TEMPLATE, out_name, out_num_str); auto dispensable = output.dispensable() ? "true" : "false"; ins_cast_str += paddle::string::Sprintf(CAST_SIZE_T_TEMPLATE, out_num_str, op_type, out_num_str, arg_idx++, dispensable); call_api_str += out_num_str + ", "; } else { outs_initializer += paddle::string::Sprintf(OUT_INITIALIZER_TEMPLATE, out_name); } outs_initializer += ","; } // return_str += paddle::string::Sprintf(return_template, out_name); // return_str += ","; outs_num += 1; } call_api_str += "attrs);"; if (outs_initializer.back() == ',') { outs_initializer.pop_back(); // return_str.pop_back(); } outs_initializer += "}"; if (FindViewOpMap(op_type)) { std::string viwe_input_name = view_op_map[op_type].first; std::string viwe_output_name = view_op_map[op_type].second; view_strategy_str += paddle::string::Sprintf( HANDLE_VIEW_BETWEEN_INPUT_AND_OUTPUT, viwe_input_name, viwe_output_name, viwe_input_name, viwe_output_name); } return_str = "return ToPyObject(out);"; std::string function_args = ""; if (input_args == "") { function_args = FUNCTION_ARGS_NO_INPUT; } else { function_args = paddle::string::Sprintf(FUNCTION_ARGS, input_args); } // generate op funtcion body auto op_function_str = paddle::string::Sprintf( OP_FUNCTION_TEMPLATE, func_name, ins_cast_str, op_type, input_args_num, call_api_str, return_str); return op_function_str; } static std::string GenerateCoreOpsInfoMap() { std::string result = "static PyObject * eager_get_core_ops_args_info(PyObject *self) {\n" " PyThreadState *tstate = nullptr;\n" " try\n" " {\n" " return ToPyObject(core_ops_args_info);\n" " }\n" " catch(...) {\n" " if (tstate) {\n" " PyEval_RestoreThread(tstate);\n" " }\n" " ThrowExceptionToPython(std::current_exception());\n" " return nullptr;\n" " }\n" "}\n" "\n" "static PyObject * eager_get_core_ops_returns_info(PyObject *self) {\n" " PyThreadState *tstate = nullptr;\n" " try\n" " {\n" " return ToPyObject(core_ops_returns_info);\n" " }\n" " catch(...) {\n" " if (tstate) {\n" " PyEval_RestoreThread(tstate);\n" " }\n" " ThrowExceptionToPython(std::current_exception());\n" " return nullptr;\n" " }\n" "}\n"; return result; } static std::tuple, std::vector> GenerateOpFunctions() { auto& op_info_map = paddle::framework::OpInfoMap::Instance().map(); std::vector op_function_list, bind_function_list; auto& all_kernels = paddle::framework::OperatorWithKernel::AllOpKernels(); for (auto& pair : op_info_map) { auto& op_info = pair.second; auto op_proto = op_info.proto_; if (op_proto == nullptr) { continue; } auto& op_type = op_proto->type(); // Skip ooerator which is not inherit form OperatorWithKernel, like while, // since only OperatorWithKernel can run in dygraph mode. // if the pten lib contains op kernel, we still generate ops method if (!all_kernels.count(op_type) && !pten::KernelFactory::Instance().HasCompatiblePtenKernel(op_type)) { continue; } std::string func_name = "eager_api_" + op_type; std::string op_function_str = GenerateOpFunctionsBody(op_proto, func_name); // generate pybind item auto bind_function_str = paddle::string::Sprintf( PYBIND_ITEM_TEMPLATE, op_type, func_name, op_type); op_function_list.emplace_back(std::move(op_function_str)); bind_function_list.emplace_back(std::move(bind_function_str)); } return std::make_tuple(op_function_list, bind_function_list); } int main(int argc, char* argv[]) { if (argc != 2) { std::cerr << "argc must be 2" << std::endl; return -1; } #ifdef PADDLE_WITH_ASCEND_CL auto ascend_ptr = paddle::framework::AscendInstance::GetInstance(); ascend_ptr->InitGEForUT(); #endif std::vector headers{ "\"pybind11/detail/common.h\"", "\"paddle/fluid/pybind/op_function_common.h\"", "\"paddle/fluid/eager/api/generated/fluid_generated/" "dygraph_forward_api.h\"", "\"paddle/fluid/pybind/exception.h\"", ""}; std::ofstream out(argv[1], std::ios::out); out << "#pragma once\n\n"; for (auto& header : headers) { out << "#include " + header + "\n"; } out << "\n\n"; auto op_funcs = GenerateOpFunctions(); auto core_ops_infos = GenerateCoreOpsInfoMap(); std::string core_ops_infos_registry = "{\"get_core_ops_args_info\", " "(PyCFunction)(void(*)(void))eager_get_core_ops_args_info, METH_NOARGS, " "\"C++ interface function for eager_get_core_ops_args_info.\"},\n" " {\"get_core_ops_returns_info\", " "(PyCFunction)(void(*)(void))eager_get_core_ops_returns_info, " "METH_NOARGS, \"C++ interface function for " "eager_get_core_ops_returns_info.\"},\n"; out << "namespace paddle {\n" << "namespace pybind {\n\n"; out << core_ops_infos; out << paddle::string::join_strings(std::get<0>(op_funcs), '\n'); out << "\n\n"; out << "static PyMethodDef ExtestMethods[] = {\n" << paddle::string::join_strings(std::get<1>(op_funcs), '\n') << "\n" << core_ops_infos_registry << "\n {nullptr,nullptr,0,nullptr}" << "};\n\n"; out << "inline void BindEagerOpFunctions(pybind11::module *module) {\n" << " InitOpsAttrTypeMap();\n" << " auto m = module->def_submodule(\"ops\");\n" << " if (PyModule_AddFunctions(m.ptr(), ExtestMethods) < 0) {\n" << " PADDLE_THROW(platform::errors::Fatal (\"Add functions to " "core.eager.ops failed!\"));\n" << " }\n\n" << "}\n\n" << "} // namespace pybind\n" << "} // namespace paddle\n"; out.close(); #ifdef PADDLE_WITH_ASCEND_CL ge::GEFinalize(); #endif return 0; }