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// Copyright (c) 2019 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 "paddle/fluid/pybind/op_function_generator.h"
#include <algorithm>
#include <fstream>
#include <iostream>
#include <string>
#ifndef _WIN32
#include <unistd.h>
#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
// phi
#include "paddle/phi/kernels/declarations.h"
static std::string LegalizeVarName(const std::string& var_name) {
std::string ret = var_name;
std::replace(ret.begin(), ret.end(), '@', '_'); // replace all '-' to '_'
return ret;
}
// NOTE(pangyoki): Inplace OP with duplicable input.
// The set includes inplace ops that have duplicable input.
// The first Varbase in input needs to be specified for the inplace strategy
// and share Varbase with the output.
std::set<std::string> inplace_op_duplicable_ins_set = {
"sum",
};
// clang-format off
const char* OUT_INITIALIZER_TEMPLATE =
R"({"%s", {std::shared_ptr<imperative::VarBase>(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<imperative::VarBase>)";
const char* OUT_VAR_LIST_TYPE = R"(std::vector<std::shared_ptr<imperative::VarBase>>)";
const char* CAST_VAR_TEMPLATE = R"(
auto %s = GetVarBaseFromArgs(op_type, "%s", args, %d, %s);)";
const char* CAST_VAR_LIST_TEMPLATE = R"(
auto %s = GetVarBaseListFromArgs(op_type, "%s", args, %d, %s);)";
const char* CAST_SIZE_T_TEMPLATE = R"(
auto %s = GetUnsignedLongFromArgs(op_type, "%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* INPLACE_DUPLICABLE_INPUT = R"([0])";
const char* INPLACE_LEAF_ERROR_MESSAGE = R"(Leaf Var (%s) that doesn't stop gradient can't use inplace strategy.)";
const char* INPLACE_STRATEGY_TEMPLATE =
R"(
PADDLE_ENFORCE_EQ(
%s->IsLeaf() && !%s->OverridedStopGradient(), false,
platform::errors::InvalidArgument("%s", %s->Name()));
%s->BumpInplaceVersion();
VLOG(3) << "Var(" << %s->Name() << ") uses Inplace Strategy.";
)";
const char* INPLACE_MAPPING_TEMPLATE = R"({"%s", "%s"})";
const char* OP_FUNCTION_TEMPLATE =
R"(
static PyObject * %s(PyObject *self, PyObject *args, PyObject *kwargs)
{
PyThreadState *tstate = nullptr;
try
{
std::string op_type = "%s";
platform::RecordEvent op_type_record_event("%s pybind_imperative_func");
%s
framework::AttributeMap attrs;
ConstructAttrMapFromPyArgs(op_type, args, %d, PyTuple_GET_SIZE(args) , attrs);
tstate = PyEval_SaveThread();
%s
imperative::NameVarBaseMap outs = %s;
imperative::NameVarBaseMap ins = %s;
%s
imperative::GetCurrentTracer()->TraceOp(op_type, ins, outs, attrs, {%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 FindDuplicableInputInplaceOpSet(const std::string& op_type) {
return inplace_op_duplicable_ins_set.count(op_type);
}
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<std::string, std::string> inplace_map = {}) {
auto& op_type = op_proto->type();
std::string input_args = "";
std::string ins_initializer = "{";
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 = "";
std::string inplace_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, LegalizeVarName(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,
LegalizeVarName(in_name),
in_name,
arg_idx++,
dispensable);
if (input.dispensable()) {
const auto in_template = input.duplicable()
? INPUT_INITIALIZER_TEMPLATE_WITH_NULL_LIST
: INPUT_INITIALIZER_TEMPLATE_WITH_NULL;
ins_initializer_with_null +=
paddle::string::Sprintf(in_template,
LegalizeVarName(in_name),
in_name,
LegalizeVarName(in_name));
} else {
const auto in_template = input.duplicable()
? INPUT_LIST_INITIALIZER_TEMPLATE
: INPUT_INITIALIZER_TEMPLATE;
ins_initializer += paddle::string::Sprintf(
in_template, in_name, LegalizeVarName(in_name));
ins_initializer += ",";
}
}
if (ins_initializer.back() == ',') {
ins_initializer.pop_back();
}
ins_initializer += "}";
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 inplace_mapping_str = "";
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;
const auto return_template =
output.duplicable() ? RETURN_LIST_TEMPLATE : RETURN_TEMPLATE;
if (FindPassingOutsMap(op_type, out_name)) {
if (input_args != "") {
input_args += ",";
}
input_args += out_type;
input_args += LegalizeVarName(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, LegalizeVarName(out_name));
outs_initializer += ",";
}
const auto in_cast_type =
output.duplicable() ? CAST_VAR_LIST_TEMPLATE : CAST_VAR_TEMPLATE;
auto dispensable = output.dispensable() ? "true" : "false";
ins_cast_str += paddle::string::Sprintf(in_cast_type,
LegalizeVarName(out_name),
out_name,
arg_idx++,
dispensable);
} else if (use_inplace_strategy && inplace_map.count(out_name)) {
PADDLE_ENFORCE_NE(
inplace_map[out_name],
"",
paddle::platform::errors::InvalidArgument(
"Inplace op %s has no input corresponding to output %s.",
op_type,
out_name));
// TODO(pangyoki): Inplace op don't have duplicable output in temporary,
// so don't support duplicable output now.
const auto out_template = INPUT_INITIALIZER_TEMPLATE;
auto inplace_input_name = inplace_map[out_name];
inplace_mapping_str += paddle::string::Sprintf(
INPLACE_MAPPING_TEMPLATE, inplace_input_name, out_name);
inplace_mapping_str += ",";
// If inplace op has duplicable input, the first Varbase in input will
// share Varbase with output.
if (FindDuplicableInputInplaceOpSet(op_type)) {
inplace_input_name += INPLACE_DUPLICABLE_INPUT;
}
// Leaf Var that doesn't stop gradient can't use inplace strategy.
// Increase inplace_version.
inplace_strategy_str +=
paddle::string::Sprintf(INPLACE_STRATEGY_TEMPLATE,
LegalizeVarName(inplace_input_name),
LegalizeVarName(inplace_input_name),
INPLACE_LEAF_ERROR_MESSAGE,
LegalizeVarName(inplace_input_name),
LegalizeVarName(inplace_input_name),
LegalizeVarName(inplace_input_name));
outs_initializer += paddle::string::Sprintf(
out_template, out_name, LegalizeVarName(inplace_input_name));
outs_initializer += ",";
} 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, LegalizeVarName(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,
out_num_str,
arg_idx++,
dispensable);
} 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;
}
if (outs_initializer.back() == ',') {
outs_initializer.pop_back();
return_str.pop_back();
}
outs_initializer += "}";
if (!inplace_mapping_str.empty() && inplace_mapping_str.back() == ',') {
inplace_mapping_str.pop_back();
}
if (!use_inplace_strategy && 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);
}
if (outs_num == 0) {
return_str = "RETURN_PY_NONE";
} else if (outs_num == 1) {
return_str = "return MakeReturnPyObject(" + return_str + ");";
} else {
return_str = "return MakeReturnPyObject(" +
paddle::string::Sprintf(RETURN_TUPLE_TEMPLATE, return_str) +
");";
}
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,
op_type,
op_type,
ins_cast_str,
input_args_num,
inplace_strategy_str,
outs_initializer,
ins_initializer,
ins_initializer_with_null + outs_initializer_with_null +
view_strategy_str,
inplace_mapping_str,
return_str);
return op_function_str;
}
static std::vector<
std::tuple<std::vector<std::string>, std::vector<std::string>>>
GenerateOpFunctions(int split_count) {
auto& op_info_map = paddle::framework::OpInfoMap::Instance().map();
std::vector<std::tuple<std::vector<std::string>, std::vector<std::string>>>
result;
std::vector<std::string> op_function_list, bind_function_list;
auto& all_kernels = paddle::framework::OperatorWithKernel::AllOpKernels();
paddle::flat_hash_map<std::string, paddle::framework::OpInfo>
op_info_map_need_gen;
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 operator which is not inherit form OperatorWithKernel, like while,
// since only OperatorWithKernel can run in dygraph mode.
// if the phi lib contains op kernel, we still generate ops method
if (!all_kernels.count(op_type) &&
!phi::KernelFactory::Instance().HasCompatiblePhiKernel(op_type)) {
continue;
}
// Skip the sparse op
if (op_type.compare(0, 7, "sparse_") == 0 && op_type != "sparse_momentum" &&
op_type != "sparse_attention") {
continue;
}
op_info_map_need_gen.emplace(pair);
}
int cc_file_api_size = op_info_map_need_gen.size() / split_count;
if (op_info_map_need_gen.size() % split_count != 0) {
cc_file_api_size++;
}
int api_index = 0;
int file_index = 0;
for (auto& pair : op_info_map_need_gen) {
auto& op_info = pair.second;
auto op_proto = op_info.proto_;
auto& op_type = op_proto->type();
// NOTE(pangyoki): Inplace Strategy.
// In this case, output will reuse input varbase.
// Dygraph mode needs to be aligned with the in-place strategy in static
// mode, and the mapping relationships between output and input that have
// been defined in static graph mode should be used in dygraph mode.
// Find which ops need to use Inplace strategy in static graph mode, and get
// the mapping relationship between Inplace output and input.
auto& infer_inplace =
paddle::framework::OpInfoMap::Instance().Get(op_type).infer_inplace_;
std::map<std::string, std::string> inplace_map;
if (infer_inplace) {
auto in_to_outs = infer_inplace(true);
for (auto& inplace_pair : in_to_outs) {
inplace_map[inplace_pair.second] = inplace_pair.first;
}
}
std::string func_name = "imperative_" + 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));
if (infer_inplace) {
// Reuse Varbase Inplace OP: op_type_.
// The inplace OP needs a new implementation method.
std::string inplace_op_type = op_type + "_";
std::string inplace_func_name = "imperative_" + inplace_op_type;
std::string inplace_op_function_str = GenerateOpFunctionsBody(
op_proto, inplace_func_name, true, inplace_map);
// generate pybind item
auto inplace_bind_function_str =
paddle::string::Sprintf(PYBIND_ITEM_TEMPLATE,
inplace_op_type,
inplace_func_name,
inplace_op_type);
op_function_list.emplace_back(std::move(inplace_op_function_str));
bind_function_list.emplace_back(std::move(inplace_bind_function_str));
}
api_index++;
if (api_index / cc_file_api_size > file_index) {
file_index++;
result.push_back(std::make_tuple(op_function_list, bind_function_list));
op_function_list.clear();
bind_function_list.clear();
}
}
result.push_back(std::make_tuple(op_function_list, bind_function_list));
return result;
}
int main(int argc, char* argv[]) {
if (argc != 3) {
std::cerr << "argc must be 3" << std::endl;
return -1;
}
#ifdef PADDLE_WITH_ASCEND_CL
auto ascend_ptr = paddle::framework::AscendInstance::GetInstance();
ascend_ptr->InitGEForUT();
#endif
std::vector<std::string> headers{"\"paddle/fluid/imperative/tracer.h\"",
"\"paddle/fluid/platform/profiler.h\"",
"\"pybind11/numpy.h\"",
"\"pybind11/pybind11.h\"",
"\"pybind11/detail/common.h\"",
"\"paddle/fluid/pybind/eager_utils.h\"",
"\"paddle/fluid/pybind/op_function.h\"",
"<Python.h>"};
std::string path = argv[1];
int split_count = atoi(argv[2]);
auto op_funcs = GenerateOpFunctions(split_count);
for (size_t i = 0; i < op_funcs.size(); i++) {
std::ofstream out(path + "op_function" + std::to_string(i + 1) + ".cc.tmp",
std::ios::out);
out << "#if defined(_MSC_VER)\n"
<< "#include <BaseTsd.h>\n"
<< "typedef SSIZE_T ssize_t;\n"
<< "#endif\n";
for (auto& header : headers) {
out << "#include " + header + "\n";
}
out << "\n\n";
out << "namespace paddle {\n"
<< "namespace pybind {\n\n";
out << "extern std::atomic<int> VarBaseUniqueNameID;\n";
out << paddle::string::join_strings(std::get<0>(op_funcs[i]), '\n');
out << "\n\n";
out << "static PyMethodDef ExtestMethods[] = {\n"
<< paddle::string::join_strings(std::get<1>(op_funcs[i]), '\n')
<< "\n {nullptr,nullptr,0,nullptr}"
<< "};\n\n";
out << "void BindOpFunctions" << i + 1 << "(pybind11::module *module) {\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.ops failed!\"));\n"
<< " }\n\n"
<< " InitOpsAttrTypeMap();"
<< "}\n\n"
<< "} // namespace pybind\n"
<< "} // namespace paddle\n";
out.close();
}
#ifdef PADDLE_WITH_ASCEND_CL
ge::GEFinalize();
#endif
return 0;
}