* 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>

* support control flow

* supoort sync_parameters_buffers

* fix the bug of sparse embedding

* fix doc of MaxPool1D

* fix doc

* fix doc format error

* dbg

* fix doc

* dbg doc format test=document_fix

* fix format test=document_fix

* test doc

* remove - from doc

* fix indent

* remove space before bracket

* dbg format

* fix indent test=document_fix

* remove new line

* fix descrip of Shape test=document_fix

* add description for default value test=document_fix

* fix bug test=document_fix

* add custom init grad for backward function

* add custom init grad for backward function

* handle when the grad_tensor is none

* handle when the grad_tensor is none

* fix the args type error on windows platform

* modify the args order and doc

* format code

* add grad_tensor to xpu

* modify the grad_tensor type check

* add paddle.backward api to support multi tensors gradient compute

* add paddle.backward api to support multi tensors gradient compute

* add paddle.atuograd module and backward api

* change tensor.backward func args

* modify tensor backward api

* remove create_graph intputs args

* add doc and examplex code for backward api

* when have the same tensor, throw error

* modify test Init func args

* modify the execute.Init func args in test files

* add paddle.autograd package in setup.py.in

* modify error msg, remove _run_backward method in class Tensor

* add test cases for backward api

* upgrade vlog

* train from dataset fetch optimize

* add anchor generator op plugin

* add anchor generator unit_test

* remove dbg info

* remove redundant line

* replace assertion with paddle enforce

* dynamic plugin replaces assertion with paddle enforce

* anchor generator support dynamic shape on spatial axis

* anchor generator test with fp16, dynamic shape

* add anchor generator test all

* add back main

* reduce test input size to not exceed the timelimit of ci

* change super to InferencePassTest for python2 compatibility

* reuse paddle operator anchor generator

* move creator construct to header with default

* add cuda ifdef

* reduce line

* change super to InferencePassTest for python2 compatibility

* fix anchor generator fp16 serialize setting

* split unittest from test_all

* restrict anchor generator input format before version 7234

* anchor generator only support greater than trt7.1

* change min_graph_size to 2

* min_graph size to 3 if dynamic shape

* reduce dynamic shape size to avoid trt search tactic too long to exceed time limit

* remove anchor from fetch list

* anchor generator support all trt version

* fix memory not allocated but if serialized

* new group

* ci compatible fix

* assert nccl

* refactor and simplify hook design

* fix reducer add hook error

* add Tensor.register_hook basic impl

* refine prepare data impl

* revert prepare data change

* support register_hook for Tensor

* add hook test in model

* polish tests and doc example

* fix double grad test failed

* remove reduce hook func

* fix set empty error

* polish code by comments

* change reduce_hook to mutable_hook

* remove useless tmp_ins

* fix shape code format error

* fix shape code format error

* fix en doc for emb, test=document_fix;
Change-Id: I4757e67caacd7189f068493ed45a7445f87ffb40

* [Parallel UT]improve Parallel UT level on Windows/Linux

* [Parallel UT]improve Parallel UT level on Windows/Linux

* [Parallel UT]Improve Parallel UT level on Windows/Linux

* [Parallel UT]Improve Parallel UT level on Windows/Linux

* fix CI

* update, test=develop

* polish tensor pipeline. test=develop

* update eigen version to f612df27, test=develop

* fix compilation error, test=develop

* remove patch command in eigen, test=develop

* fix compilation error caused by call Eigen function with float16 and bfloat16, test=develop

* fix unittest error, test=develop

* fix unittest error caused by precision, test=develop

* remove patch files used by old version eigen, test=develop

* fix whl package push pypi

* add rst

* support minus-int idx to LayerList
* update layerlist test

* bugfix for warpctc

* fix warpctc commit id

* fix warpctc commit id

* fix warpctc commit id

* fix warpctc commit id

* fix warpctc commit id

* fix WARPCTC_WITH_HIP invalid

* Add logs to find out why can not dlopen libwarpctc.so

* fix warpctc commit id

* fix unit test test_warpctc_op

* Optime failed log for dlopen

* Optime failed log for dlopen

* Delete extra changes

* fix warpctc commit id

* fix warpctc commit id

* Add is_compiled_with_rocm for test_warpctc_op

* fix warpctc commit id

* Cancel optimize dlopen failed reason, move to next pr, due to it makes windows ci failed

* Cancel optimize dlopen failed reason, move to next pr, due to it makes windows ci failed

* Cancel optimize dlopen failed reason, move to next pr, due to it makes windows ci failed

* fix code style problems

* Remove old custom OP to reduce whl package volume

* [Custom OP]Remove old custom OP to reduce whl package volume

* add deprecated for softmax_with_cross_entropy, test=develop

* test for deprecated in english doc, test=develop

* test deprecated for softmax_with_cross_entropy in english doc, test=develop

* fix readme and English doc for cross_entropy, test=develop

* rm test for softmax_with_cross_entropy deprecated, test=develop

* update readme for CrossEntropyLoss, test=develop

* fix readme format, test=develop

* fix readme format, test=develop

* fix readme format for cross_entropy, test=develop

* add softmax_switch and fix softlabel for cross_entropy, test=develop

* 1)recovery softmax_with_cross_entropy in fluid 2) change softmax_switch to use_softmax 3) add example for softlabel for cross_entropy, test=develop

* fix Example number for cross_entropy, test=develop

* fix code format, test=develop

* fix for CI-Coverage, test=develop

* fix for CI-Coverage, test=develop

* fix ci-coverage for Non-ASCII character '\xe2' in file, test=develop

* fix ci-coverage for Non-ASCII character '\xe2' in nn.layer.loss.py, test=develop

* update description for doc when use_softmax=Fasle, test=develop

* fix some docs and code example for cross_entropy, test=develop

* delete redundant description for soft_label parameter of cross_entropy, test=develop

* fix some comment for test_cross_entropy_loss.py, test=develop

* fix batchnorm when inpu dims < 3

* add unittest for batchnorm dims = 2

* yolobox converter and plugin

* yolobox unittest

* add dynamic shape restriction

* fix git merge log

* Avoid raising warning while import paddle

* fix segment fault of set_value

* fix code style

* modify API nn.Bilinear's doc, test=develop

* modify API nn.Bilinear's doc, test=develop

* give shape related contructor and reshape warning

* change line num to fit ut

* change ut to fit

* remove useless code

* call resize directly in constructor

* add roi_align_plugin

* add roi align unit_test

* add roi align serialization

* remove roi align static plugin because of batch dim issue

* refine roi align unittest and add fp16/serialization

* add trt roi align condition to op_teller

* refine error message

* remove unnecessary reshape layer

* trt affine channel converter

* add trt affine channel base test

* add trt affine channel NHWC

* remove asterisk for python2 compatibility

* trt affine channel converter

* add trt affine channel base test

* add trt affine channel NHWC

* remove asterisk for python2 compatibility

* fix rebase

* move LodTensor to Tensor

* add dbg info

* affine channel converter only support NCHW

* scale,bias are parameters, use create_parameters api

* reduce test input size to not exceed the timelimit of ci

* refine affine channel unittest and add serialization/dynamic test

* change super to InferencePassTest for python2 compatibility

* change super to InferencePassTest for python2 compatibility

* fix affine channel fp16 serialize setting

* Use layer to calculate output scale
* add backward for moving_average_abs_max_scale and save output scales to op's attr