* modify unittest of lstm forward, *test=kunlun

* modify unittest of lstm forward, *test=kunlun

* [Eager]Fix segment_pool/allclose/isclose/scale API bug

* fix kernel register problem

* [ROCm] fix dcu error in device event base, test=develop

* fix, test=develop

* ad conj flip yaml

* add flip conj pixel shuffle

* afs wrapper

* format

* format

* macro

* add yaml

* perfect converage

* Profile Executors

* update

* fix ut

* fix names

* update

* update

* add Output(Step) to distributed fused lamb op

* add _set_step

* no

* maintain old profiler

* fix old dygraph record event

* ignore some failed test for KL2
*test=kunlun

* minor
*test=kunlun

* minor
*test=kunlun

* 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

* momentum support l2decay for xpu. test=kunlun

* fix include file. test=kunlun

* fix cmake for device_worker. test=kunlun

* modify infer gpu memory strategy

* modify infer gpu memory strategy

* Add GPU memory usage information in the print of profiler.

* Add ifdef.

* support final_state in multiprocess

* fix no place.device

* set device_id in eager_gen

* remove paddle_ipu shared library

* fix unique_name

* [Eager] Support test_layers's test cases switch to eager mode

* Update batch_norm _C_ops action to fix CI

* Use None instead of new EmptyTensor

* Updated var name

* Make sure to switch eager mode, Fix Coverage_CI

* Remove _non_static_mode statement

* Remove batch_norm dispensable input statement

* Polish batch_norm code

* Fix CI issue

* update

* add conv yaml

* add backward

* remove useless code

* fix bug

* fix bug

* revert fluid dygraph conv2d

* remove useless infermeta function

* fix meta fn deluplicat error

* conv using custom impl

* remove amp include

* fix bug

* use cudnn = true

* fix test mkldnn caching bug

* fix bug of data transform in inference executor

* fix bug

* update name

* update name

* fix test

* fix fleet bind

* update name

* update name

* fix test

* fix gpups wrapper

* remove Push/Pull/Load/Save with context in client and wrapper base class

* fix

* fix

* remove some interface

* fix

* remove

* code style

* recover

* fix

* remove code unused

* remove some unused table & accessor & CommonDenseTable => MemoryDenseTable

* fix

* fix

* fix

* recover

* remove unused code
Co-authored-by: Nesythan <esythan@126.com>

* add fake index and unittest for multiclass_nms3 trt

* modify unittest

* [Refactor] refactored eager_gen.py PR #2

* [DoubleGrad PR #1] Decoupled code generation logics for Dygraph ForwardFunctions and GradNodes

* Fixed minor issue

* Adjusted logics of GenerateNodeCreationCodes and GenerateForwardDefinition

* Fixed issues

* Supported higher-order grad node generation

* [DoubleGrad PR #4] Supported higher-order GradNode generation

* [DoubleGrad #4] Bug Fixes to Double Grad Node Generation

* Fixed yaml typo

* Fixed yaml typo

* fixed minor issues

* [DoubleGrad PR #5] Enabled gradient computations for grad_tensors passed to paddle.grad()

* Fixed minor issue

* Fixed CI-Inference issue

* Fixed CI-inference issues

* [DoubleGrad PR #7] paddle.grad() to copy backward graph before backward run

* Fixed minor issues

* Fixed issue with backward graph construction logic

* Fixed implementation issues with backward graph reconstruction

* Fixed unittest issue

* Fixed issues

* [DoubleGrad PR #8] Enabled triple grads for sigmoid and matmul

* Fixed issues with phi kernel

* Added triple grad test case

* Fixed minor issue

* add nms op and batched_nms api

* switch autotune

* implement AutoTuneCache

* implement AutoTuneCache class

* add pybind api

* add dygraph test

* support static mode and eager mode and improve unittests

* rename the SwitchAutoTune Class and improve tests

* improve AutoTuneStatus and reduce the cost of tests

* eager math op, test=develop

* eager support lookahead, test=develop

* refine,test=develop

* refine doc, test=develop

* refine,test =develop

* refie, test=develop

* refie, test=develop

* refie, test=develop

* test_paddle_multiprocessing

* refine, test=develop

* refine, test=develop

* fix bug, test=develop

* refine, test=develop

* dataloader, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* test_datasets timeout, test=develop

* refine, test=develop

* [Eager] Fix empty tensor Initializer bug with shape=[]

* [Eager] Fix empty tensor Initializer bug with shape=[]

* ignore two unittest

* fix unittest

* enable new executor by default

* enable stream safe allocator

* test=document_fix;test=coverage

* do not use scope in op kernel

* fit empty program for new executor

* fix communication depend

* fix test_sync_batch_norm

* skip unsupported place

* refine datatransfer

* fit for dirtributed program

* fix dependencpy

* fix some ut