#ifndef MNN_Train_Module_hpp
#define MNN_Train_Module_hpp
#include <vector>
#include <MNN/expr/Expr.hpp>
#include <MNN/expr/Executor.hpp>
#include <MNN/MNNForwardType.h>
namespace MNN {
class Session;
namespace Express {
struct SubGraph;
class MNN_PUBLIC Module {
public:
Module() = default;
virtual ~Module() = default;
virtual std::vector<Express::VARP> onForward(const std::vector<Express::VARP>& inputs) = 0;
Express::VARP forward(Express::VARP input);
std::vector<Express::VARP> parameters() const;
bool loadParameters(const std::vector<Express::VARP>& parameters);
void setIsTraining(const bool isTraining);
bool getIsTraining();
void clearCache();
const std::string& name() const {
return mName;
};
void setName(std::string name) {
mName = std::move(name);
}
const std::string type() const {
return mType;
}
void setType(std::string type) {
mType = std::move(type);
}
int addParameter(Express::VARP parameter);
void setParameter(Express::VARP parameter, int index);
static Module* createEmpty(const std::vector<Express::VARP>& parameters);
struct BackendInfo {
MNNForwardType type = MNN_FORWARD_CPU;
BackendConfig* config = nullptr;
};
struct Config {
bool dynamic = false;
bool shapeMutable = true;
bool rearrange = false;
BackendInfo* backend = nullptr;
const Module* base = nullptr;
};
static Module* load(const std::vector<std::string>& inputs, const std::vector<std::string>& outputs, const uint8_t* buffer, size_t length, const Config* config = nullptr);
static Module* load(const std::vector<std::string>& inputs, const std::vector<std::string>& outputs, const char* fileName, const Config* config = nullptr);
static Module* load(const std::vector<std::string>& inputs, const std::vector<std::string>& outputs, const char* fileName, const std::shared_ptr<MNN::Express::Executor::RuntimeManager> rtMgr, const Config* config = nullptr);
static Module* load(const std::vector<std::string>& inputs, const std::vector<std::string>& outputs, const uint8_t* buffer, size_t length, const std::shared_ptr<MNN::Express::Executor::RuntimeManager> rtMgr, const Config* config = nullptr);
static Module* extract(std::vector<Express::VARP> inputs, std::vector<Express::VARP> outputs, bool fortrain, const std::map<std::string, SubGraph>& subGraph = {});
static Module* clone(const Module* module, const bool shareParams = false);
struct Info {
std::vector<Variable::Info> inputs;
Dimensionformat defaultFormat;
std::shared_ptr<MNN::Express::Executor::RuntimeManager> runTimeManager;
std::vector<std::string> inputNames;
std::vector<std::string> outputNames;
std::string version;
std::string bizCode;
std::map<std::string, std::string> metaData;
std::string uuid;
};
const Info* getInfo() const;
class CloneContext;
virtual Module* clone(CloneContext* ctx) const {
return nullptr;
}
void registerModel(const std::vector<std::shared_ptr<Module>>& children);
static void destroy(Module* m);
int traceOrOptimize(Interpreter::SessionMode stage);
std::vector<std::shared_ptr<Module>> getChildren() const { return mChildren; }
protected:
virtual int onOptimize(Interpreter::SessionMode stage) {
return 0;
}
virtual void onClearCache() {
}
Module* cloneBaseTo(CloneContext* ctx, Module* module) const;
std::vector<std::shared_ptr<Module>> mChildren;
std::vector<Express::VARP> mParameters;
private:
void _collectParameters(std::vector<Express::VARP>& result) const;
bool mIsTraining = true;
std::string mName;
std::string mType;
};
struct SubGraph {
std::vector<std::string> inputs;
std::vector<std::string> outputs;
std::shared_ptr<Module> m;
};
} }
#endif