* fix or backend many inputs bug

* fix or backend many inputs bug

* fix or backend many inputs bug

* fix or backend many inputs bug

* code format

* code format

* cmake-lint

* update

* run all demo ci before exit;test=document_fix;test=windows_ci_inference

* fix bug;test=document_fix;test=windows_ci_inference

* improve log

* commetn test code

* modify according to zhouwei's comments

* change inference demo_test build method to ninja to choose visual studio version automaticly

* notest;test=windows_ci_inference

* set cuda of demo_ci by arg,fix bug of ninja compile,test=document_fix;test=windows_ci;test=windows_ci_inference

* fix bug;test=document_fix;test=windows_ci;test=windows_ci_inference

* fix bug;test=document_fix;test=windows_ci_inference"

* set lib_path according to generator

* add onnxruntime predictor

* Add code comments

* support link paddle2onnx onnxruntime

* support onnxruntime with python

* support onnxruntime with python

* support onnxruntime with windows

* paddle2onnx compile with windows

* supoort windows compile

* supoort windows compile with onnxruntime

* supoort windows compile with paddle2onnx

* supoort mac compile

* compile with mac

* compile with mac

* add code comments

* fix remind word

* code optimization

* add test case

* add test case

* add inference demo_ci test case

* fix compile paddle2onnx with no python

* add inference demo_ci test case

* add inference demo_ci test case

* add inference infer_ut test case

* support c go api and test cases

* add converage test case

* add converage test case

* add capi test case

* add capi test case

* block warning when build demo_ci and infer_ut

* use build pipe line clone to test

* add trt_mobilenet demo test

* only deliver trt_root in run.sh

Add Tokenizer related functionalities for Transformer model in order that the process of training and predicting is consistent.

* support the text string as an input Tensor
* support the "VOCAB"unordered_map<wstring, int> as an input Tensor to lookup tokens
* Tokenizer used for BERT. This tokenizer applies an end-to-end, text string to wordpiece tokenization.
* It first applies basic tokenization, followed by wordpiece tokenization.

* graph engine demo

* upload unsaved changes

* fix dependency error

* fix shard_num problem

* py client

* remove lock and graph-type

* add load direct graph

* add load direct graph

* add load direct graph

* batch random_sample

* batch_sample_k

* fix num_nodes size

* batch brpc

* batch brpc

* add test

* add test

* add load_nodes; change add_node function

* change sample return type to pair

* resolve conflict

* resolved conflict

* resolved conflict

* separate server and client

* merge pair type

* fix

* resolved conflict

* fixed segment fault; high-level VLOG for load edges and load nodes

* random_sample return 0

* rm useless loop

* test:load edge

* fix ret -1

* test: rm sample

* rm sample

* random_sample return future

* random_sample return int

* test fake node

* fixed here

* memory leak

* remove test code

* fix return problem

* add common_graph_table

* random sample node &test & change data-structure from linkedList to vector

* add common_graph_table

* sample with srand

* add node_types

* optimize nodes sample

* recover test

* random sample

* destruct weighted sampler

* GraphEdgeBlob

* WeightedGraphEdgeBlob to GraphEdgeBlob

* WeightedGraphEdgeBlob to GraphEdgeBlob

* pybind sample nodes api

* pull nodes with step

* fixed pull_graph_list bug; add test for pull_graph_list by step

* add graph table;name

* add graph table;name

* add pybind

* add pybind

* add FeatureNode

* add FeatureNode

* add FeatureNode Serialize

* add FeatureNode Serialize

* get_feat_node

* avoid local rpc

* fix get_node_feat

* fix get_node_feat

* remove log

* get_node_feat return  py:bytes

* merge develop with graph_engine

* fix threadpool.h head

* fix

* fix typo

* resolve conflict

* fix conflict

* recover lost content

* fix pybind of FeatureNode

* recover cmake

* recover tools

* resolve conflict

* resolve linking problem

* code style

* change test_server port

* fix code problems

* remove shard_num config

* remove redundent threads

* optimize start server

* remove logs

* fix code problems by reviewers' suggestions
Co-authored-by: NHuang Zhengjie <270018958@qq.com>
Co-authored-by: NWeiyue Su <weiyue.su@gmail.com>
Co-authored-by: Nsuweiyue <suweiyue@baidu.com>
Co-authored-by: Nluobin06 <luobin06@baidu.com>
Co-authored-by: Nliweibin02 <liweibin02@baidu.com>

* modify windows CI to VS2017

* modify windows CI to VS2017

* modify windows CI to VS2017

* update paddle_fluid.so to paddle_inference.so

* 01:Modify the shell script according to the specification

* 01:Modify the shell script according to the specification

* fix windows ci
test=develop

* fix ci error

* add SetCommandLineOption

* add the print_FLAGS function

* remove the test demo

* modify the location of macro

* add the 'WITH_STATIC_LIB' option on windows

* modify the macro of PD_INFER_DECL

* modify the the fuction name

* modify the unittest

* modify the code style

* solve mklml memory leak on windows

test=develop

* remove unused msvcr120.dll

test=develop

* update the analysis predictor, test=develop

* update the unit test, test=develop

* no priority set before the inferface determined, test=develop

* interface name generalization, test=develop

* Remove the NGraph engine from PDPD repository
1. Each operator was removed from the operator's directory
2. Each test was removed from the unittest directory
3. The parallel executor support was removed from the PDPD
4. The CMake file was removed from the PDPD
5. The NG flags were removed from the repository
test=develop

* Remove ngraph from:
1. Cmake file
2. Python file
test=develop

* remove the useless third_party library from C++ inference library

* revert removing the install directory