// 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.

int run_generator(int argc, char* argv[]);

#pragma once

#include <map>
#include <set>
#include <string>

// NOTE(zhiqiu): Commonly, the inputs in auto-generated OP function are
// determined by the OP`s proto automatically, i.e., all the inputs registered
// in OpMaker.
// However, some OPs have dispensable inputs, which means the input can
// be none for some conditions. It is discovered that most dispensable inputs
// is not used in imperative mode, so we drop those inputs when generating OP
// functions. While, for very few OPs, the dispensable inputs are used, we
// need to manually specify them in this map.
extern std::map<std::string, std::set<std::string>> op_ins_map;

// NOTE(zhiqiu): Like op_ins_map.
// Commonly, the outputs in auto-generated OP function are determined by the
// OP`s proto automatically, i.e., all the outputs registered in OpMaker.
// However, some OPs have dispensable outputs, which means the output can
// be none for some conditions. It is discovered that most dispensable outputs
// is not used in imperative mode, so we drop those outputs when generating OP
// functions. While, for very few OPs, the dispensable outputs are used, we
// need to manually specify them in this map.
extern std::map<std::string, std::set<std::string>> op_outs_map;

// NOTE(zhiqiu): Commonly, the outputs in auto-generated OP function are
// generated in C++ automatically.
// However, some OPs need to pass the outputs from Python instead of generating
// them in C++. There are mainly 2 reasons for that,
// (1) Optimizer OPs need to update the input param in-place, like sgd.
//     So they need to pass the output which is same as input param.
// (2) Very few python APIs has out in their arguments, like fill_constant.
//     So they need to pass the python output to C++.
//     Actually, this is not a good design, since it may break the SSA graph,
//     especially in declarative mode.
// For those OPs, we need to manually specify the outs need to pass in this map.
extern std::map<std::string, std::set<std::string>> op_passing_outs_map;

// NOTE(pangyoki): Tensor View Strategy.
// In this case, a new output varbase will be created, and this varbase will
// reuse the input varbase's allocation.
// It's a map. The key of outer map is the view op name, the value is
// a pair which implies the mapping relationship between the input and
// output varbase.
extern std::map<std::string, std::pair<std::string, std::string>> view_op_map;

// NOTE(pangyoki): Special inplace ops that are not supported in temporary.
// The input and output of some inplace ops are special, such as
// duplicate input. These inplace ops have no usage scenarios and
// are not supported in temporary.
extern std::set<std::string> special_inplace_op_set;

// NOTE(pangyoki): Special no_need_buffer ops that are not supported in
// temporary.
// sequence_conv op will raise error to get no_need_buffer info during
// compiling.
extern std::set<std::string> special_no_need_buffer_op_set;