* [Eager]Fix eager no take effect problem

* add element_wise and fix greater_than

* Add graph_reindex API

* add graph_sample_neighbors api

* Add buffer

* delete VLOG

* delete thrust::copy for output

* add ShareDataWith

* delete graph_reindex hashtable output

* add graph_reindex dispensable

* add reindex unittest, move memset to cuda kernel, change api

* fix conflict

* add reindex buffer for gpu version note

* fix conflicts for op_func_generator

* Add fisher_yates sampling, add dispensable, change infermeta

* add dtype for edge_id

* fix rocm ci and static check ci

* add unittest

* fix unittest

* fix unittest

* fix bug

* add yaml for ele_max ele_min

* add yaml for: mish / logexpsum / expm1 / elemenwise_pow / elementwise_floordiv

* paddle inference support new quant_model

* enable new-executor on windows to test it

* add message

* fix ut

* delete function

* fix bug

* update name

* fix bug in strategy

* support test_create_paramter

* support fused_transformer_encoder_layer

* skip program_desc tracer related tests in eager mode

* fix ci tests on eager

* Add UT for full_like after migration YAML

* rename test class

* filter unsupported inputs for elementwise op in op teller

* add unittest for corner case

* 1. add the python api grad 2. add final and intermediate state vlog 3. change the python_api error logic

* add python api or close the check_eager=True

* fix the compatibility

Enhance vjp/jvp/Jacobian/Hessian API for supporting dynamic, static graph and batched, unbatched mode (#40692)

* modify vjp/jvp for both dynamic and static graph

* enforce jacobian class for supporting first/last batch

* add unittest for jvp, jacobian withlast batch, jacobian with first batch

* fix the incorrect shape when multi-index Jacobian

* enforce Hessian class for supporting dynamic graph

* add Hessian class unittest

* bugfix, jvp double_backward_trick zeros_like return stop_gradient=True in static graph

* add API beta warnnings

* add white_list for cuda11.x ci windows.

* optimize some code snippets and documments

* set unittest timeout to 100 seconds

* move vjp,jvp,Jacobian,Hessian to incubate

* fix vjp,vjp import path of sample code

* fix code style error of augtograd/__init__ file

* add nll_loss yaml

* fix nll loss

* fix nll loss bug

* fix bug

* fix bug

* fix infrt problem
Co-authored-by: Nxiongkun <xiongkun03@baidu.com>

* support pinned, test=develop

* support async_write, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine,test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* [ControlFlow] Fix contrib API bug in while_loop

* format code

* change vjp to paddle.grad

* use grad and gradients api

* fix preprocess for x

* fix a bug, val_and_grad should return a Tensor

* detach value and grad to avoid assign error
Co-authored-by: Nlevi131 <limaolin01@baidu.com>

* fix inplace fill_ and zero_ API

* add eager unittest

* change inplace_version checking log

* fix

* support C_ops assign

* open unittest

* fix clone

* [Eager]Enhance eager_trace_op logic to support Optimizer Op

* fix AsDispensable

* add interploate cpu kernel

* fix nullptr bug

* add interpolate gpu kernel

* fix unit test error

* remove raw kernels

* add cuda kernel impl

* add infermeta

* recover accidentally deleted kernels in interpolate op

* fix grad x_grad name error

* remove interpolate_v2_op.h

* rm unused codes

* fix xpu build error

* fix build error

* fix namespace error

* add register header for nup

* fix infermeta error

* modify by review

* add the missing args in test_trt_convert_nearest_interp_v2

* add notes for quantile UT

* Supoort quantile in static-mode and add UT

* support multi_layer of bilstm,*test=kunlun

* support multi_layer of bilstm, *test=kunlun

* support multi_layer of bilstm, *test=kunlun

* support multi_layer of bilstm, *test=kunlun

* add yaml for ele_max ele_min

* fig

* push

* xxx

* [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

* Fixed minor issue

* back fl

* delete ssl cert

* .

* make warning

* .

* unittest paral degree

* solve unittest

* heter & multi cloud commm ready

* .

* .

* correct py36 import error

* correct py36 import error

* correct py36 import error

* correct py36 import error