2019-04-17 10:49:11 +08:00
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//
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// Session.hpp
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// MNN
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//
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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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//
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#ifndef Session_hpp
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#define Session_hpp
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#include <map>
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#include <memory>
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#include <vector>
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#include "Backend.hpp"
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#include "Macro.h"
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#include "Pipeline.hpp"
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#include "Schedule.hpp"
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#include "SizeComputer.hpp"
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#include "Tensor.hpp"
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namespace MNN {
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2019-06-17 20:10:35 +08:00
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struct Net;
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2019-04-17 10:49:11 +08:00
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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;
2019-10-29 13:37:26 +08:00
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class MNN_PUBLIC Session {
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2019-04-17 10:49:11 +08:00
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public:
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/**
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* @breif initializ with schedule info.
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* @param info given schedule info.
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*/
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Session(const Schedule::ScheduleInfo& info);
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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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/**
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* @brief infer with loops. used for profiling only.
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* @param loops run times.
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* @return result code.
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*/
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ErrorCode runWithProfiler(int loops) const;
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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();
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/**
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* @brief check if needs resize.
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* @return needs resize or not.
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*/
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bool getNeedResize() const {
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return mNeedResize;
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}
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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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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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2019-06-17 20:10:35 +08:00
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2019-04-17 10:49:11 +08:00
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/**
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* @brief the session will not be resized any more, release all cache used for resize.
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* @return errorcode
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*/
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ErrorCode releaseCache();
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2019-06-17 20:10:35 +08:00
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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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2019-04-17 10:49:11 +08:00
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protected:
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const std::vector<std::unique_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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Backend* _getDefaultBackend();
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private:
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std::map<MNNForwardType, std::unique_ptr<Backend>> mBackends;
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std::vector<std::unique_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 = false;
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bool mValid = true;
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Backend* mFirstBackend = nullptr;
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};
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} // namespace MNN
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#endif /* Session_hpp */
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