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								//
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								//  Session.hpp
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								//  MNN
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								//  Created by MNN on 2018/07/30.
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								//  Copyright © 2018, Alibaba Group Holding Limited
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								#ifndef Session_hpp
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								#define Session_hpp
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								#include <MNN/Tensor.hpp>
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								#include <map>
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								#include <memory>
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								#include <vector>
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								#include "Pipeline.hpp"
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								#include "Schedule.hpp"
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								#include "core/Backend.hpp"
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								#include "core/Macro.h"
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								#include "shape/SizeComputer.hpp"
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								namespace MNN {
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								struct Net;
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								/** infer unit. multiple sessions could share one net. */
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												- build:
	- unify schema building in core and converter;
	- add more build script for android;
	- add linux build script for python;
- ops impl:
	- add floor mod support in binary;
	- use eltwise impl in add/max/sub/mul binary for optimization;
	- remove fake double support in cast;
	- fix 5d support for concat;
	- add adjX and adjY support for batch matmul;
	- optimize conv2d back prop filter;
	- add pad mode support for conv3d;
	- fix bug in conv2d & conv depthwise with very small feature map;
	- optimize binary without broacast;
	- add data types support for gather;
	- add gather ND support;
	- use uint8 data type in gather v2;
	- add transpose support for matmul;
	- add matrix band part;
	- add dim != 4 support for padding, reshape & tensor convert;
	- add pad type support for pool3d;
	- make ops based on TensorFlow Lite quantization optional;
	- add all & any support for reduction;
	- use type in parameter as output type in reduction;
	- add int support for unary;
	- add variable weight support for conv2d;
	- fix conv2d depthwise weights initialization;
	- fix type support for transpose;
	- fix grad outputs count for  reduce grad and reshape grad;
	- fix priorbox & detection output;
	- fix metal softmax error;
- python:
	- add runSessionWithCallBackInfo interface;
	- add max nodes limit (1400) for visualization tool;
	- fix save error in python3;
	- align default dim;
- convert:
	- add extra design for optimization;
	- add more post converting optimizers;
	- add caffe v1 weights blob support;
	- add cast, unary, conv transpose support for onnx model;
	- optimize batchnorm, conv with variable weights, prelu, reshape, slice, upsample for onnx model;
	- add cos/sin/atan/tan support for unary for tensorflow model;
	- add any/all support for reduction for tensorflow model;
	- add elu, conv3d, pool3d support for tensorflow model;
	- optimize argmax, batchnorm, concat, batch to space, conv with variable weights, prelu, slice for tensorflow model;
- others:
	- fix size computer lock;
	- fix thread pool deadlock;
	- add express & parameters in express;
	- rewrite blitter chooser without static map;
	- add tests for expr;
											
										 
										
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								class MNN_PUBLIC Session {
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								public:
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								    Session(Schedule::ScheduleInfo&& info, Interpreter::SessionMode callBackMode, Interpreter::SessionMode inputMode,
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								            RuntimeInfo&& runtime);
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								    ~Session();
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								public:
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								    /**
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								     * @brief infer.
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								     * @return result code.
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								     */
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								    ErrorCode run() const;
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								    /**
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								     * @brief infer with callbacks and sync option.
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								     * @param enterCallback callback before each op.
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								     * @param exitCallback  callback after each op.
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								     * @param sync          wait until all ops done before return or not.
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								     * @return result code.
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								     */
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								    ErrorCode runWithCallBack(const TensorCallBackWithInfo& enterCallback, const TensorCallBackWithInfo& exitCallback,
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								                              bool sync = false) const;
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								    bool getInfo(Interpreter::SessionInfoCode code, void* ptr) const;
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								    void cloneExecution(const std::map<const Op*, std::shared_ptr<Execution>>& cache, int pipelineIndex);
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								    const std::map<const Op*, std::shared_ptr<Execution>>& getExecution(int pipelineIndex);
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								public:
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								    /**
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								     * @brief resize tensors and buffers responding to input changes.
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								     * @return result code.
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								     */
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								    ErrorCode resize(bool isStatic = false);
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								    /**
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								     * @brief set if needs resize.
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								     * @param flag  needs resize or not.
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								     */
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								    void setNeedResize(bool flag = true) {
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								        mNeedResize = flag;
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								    }
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								    void setNeedMalloc(bool flag = true) {
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								        mNeedMalloc = flag;
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								    }
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								public:
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								    /**
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								     * @brief get backend that create the tensor.
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								     * @param tensor    given tensor.
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								     * @return backend that create the tensor, NULL if the tensor is created by default backend (CPU backend).
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								     */
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								    const Backend* getBackEnd(const Tensor* tensor) const;
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								    /**
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								     * @brief get input tensor for given op name.
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								     * @param name given op name. if NULL, return first input tensor.
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								     * @return input tensor if found, NULL otherwise.
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								     */
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								    Tensor* getInput(const char* name) const;
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								    /**
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								     * @brief get output tensor for given op name.
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								     * @param name given op name. if NULL, return first output tensor.
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								     * @return output tensor if found, NULL otherwise.
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								     */
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								    Tensor* getOutput(const char* name) const;
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								    /**
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								     * @brief get output tensors map.
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								     * @return get output tensors map.
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								     */
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								    const std::map<std::string, Tensor*>& getOutputAll() const;
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								    const std::map<std::string, Tensor*>& getInputAll() const;
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								    /**
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								     * @brief check session is valid or not.
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								     * @return session is valid or not.
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								     */
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								    inline bool valid() const {
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								        return mValid;
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								    }
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								    /**
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								     * @brief update the session's const value to origin model's const blob.
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								     * @return errorcode
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								     */
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								    ErrorCode updateToModel(Net* net) const;
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								    bool loadCache(const void* buffer, size_t size);
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								    std::pair<const void*, size_t> getCache();
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								protected:
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								    const std::vector<std::shared_ptr<Pipeline>>& getPipelines() const {
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								        return this->mPipelines;
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								    }
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								private:
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								    void _clearCache();
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								    void _setUpTensorInfo(const Schedule::ScheduleInfo& info);
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								private:
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								    RuntimeInfo mRuntime;
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								    std::vector<std::shared_ptr<Pipeline>> mPipelines;
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								    std::vector<std::pair<int, std::shared_ptr<Tensor>>> mTensors;
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								    std::map<std::string, Tensor*> mInputs;
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								    std::map<std::string, Tensor*> mOutputs;
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								    bool mNeedResize = true;
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								    bool mValid      = true;
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											2021-04-08 15:34:23 +08:00
										 
									 
								 
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								    bool mNeedMalloc = true;
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											2020-11-05 16:41:56 +08:00
										 
									 
								 
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								    Interpreter::SessionMode mCallBackMode;
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											2019-04-17 10:49:11 +08:00
										 
									 
								 
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								};
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								} // namespace MNN
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								#endif /* Session_hpp */
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