* replace dropout_is_test with is_test.
* improve atol on a100.

* add fused_bias_dropout_residual_ln op and layer.

* enhance check for current block docstring for prim2orig interface

* refine if else syntax

* Dynamic graph support to Automatic SParsity.

1. Added dynamic support to ASP module (paddle.fluid.contrib.sparsity).
2. Added ASP related unit-tests regards to above changes.
3. Put ASP module under paddle.static for now, waiting for APIs confirmation from Paddle.

* Modified documents of functions to have correct examples.

* Update in_dygraph_mode to paddle.in_dynamic_mode()

* Modified documents of functions and added comments

* Minor changes.

* Fix example errors in asp API.

* Code Change for Review

1. Added more examples in documents.
2. Chaged test_asp_pruning_static.

* Minor changes

* Update ASP function documents.

* Update ASP function documents.

* Reduce test case size of asp pruning due CI time limit.

* Update time limitation to some asp UTs.

* Fix sample code errors.

* Fix sample code errors.

* Fix sample code errors.

* Update time limitation to parts of ASP UTs.

* Update UTs to fit with CI.

* Reduce problem size in python/paddle/fluid/tests/unittests/asp/test_fleet_with_asp_dynamic.py

* Added paddle.asp

* Fixed type casting error of OpRole.Optimize in new dygraph mode.

* Made set_excluded_layers be compatible with 2.2

* Fix example code of calculate_density.

* Update code examples.

* Move paddle.asp to paddle.incubate.asp

* Fixed an example error of calculate_density

* Updated triple_grad_check func

* add todo for gradient checker and refine some comments

* remove additional code

* add test for warnging in backward.py

* format python code

* support multi input in triple gradient checker

* Add matmul triple grad kernel

* Updated comments of TODO

* Supported some special tests

* Change code-format to follow CI std

* Updated gradient_checker.py

* Fix conflicts

* Removed unnecessary printing log

* Change code style to follow CI std

* merge upstream

* add priops.py

* add_p

* rm useless files

* add sub_p mul_p div_p

* add sqrt_p and tanh_p

* add reshape_p

* add broadcast_p

* Add python primitive wrappers.

* Jvp rules updated.

* JVP rules done for all the 17 primops.

* quick check and fixes.

* add jvp(op, *args)

* add broadcast_p fill_constant_p matmul_p reduce_p reshape_p transpose_p

* add split_p and concat_p

* add gather_p and scatter_add_p

* add slice_select_p and slice_assign_p

* Add transpose rules.

* add multi input check for add_p, sub_p, mul_p, div_p

* update concat_p

* Linearize and transpose in progress..

* refine gather_p and scatter_add_p

* updated.

* update transpose.

* refine slice_assign_p and slice_select_p

* init commit for lower

* Merged with primitive ops.

* small update

* add rules for orig2prim and prim2orig

* add 9 test for prim ops

* add more test and fix some bug

* add more test

* register proto

* Adding primops test.

* add shape valid check for broadcast_p op, and add keepdim attr into reduce_p op proto

* support multi input and multi output for split_p and concat_p

* Test updated.

* update

* fix slice bug for slice_select_p and slice_assign_p

* updated.

* Ops updated.

* Refactor and bug fixes.

* updated.

* finish orig2prim and prim2orig rules

* dtype for axis attr should be long int

* update dtype for axis attr int64_t

* update for iscan CI

* Update primx.

* Refactor vars in primx.

* update for lower transform

* add more shape and dtype check

* update primx.py

* change IndexTensor into int32 dtype

* update

* Fix linearize and transpose.

* Update is_dot

* Update is_dot

* Update is_dot

* add gradient aggregation, fix add_transpose.

* pass first linearize+transpose test.

* update test

* refactor op registration and primx.

* update rule for slice_assign

* try test lower

* update orig2prim and prim2orig

* pass simple lower pass

* update

* Update input types in the unit test.

* orig2prim segfault.

* 50% for adam.minimize

* test updated.

* temp fix erros in removing vars.

* primx updated.

* update for matmul_v2 and reshape2 orig2prim

* update for minimize

* Refine primrules

* Remove some code

* supporting unused and unreachable vars.

* update for use prim2orig in minimize

* fix gather and scatter_add transpose.

* Add rules UT

* update scatter_add

* Refine UT code

* fix nonetype check in topo

* Update gather_p pywrapper.

* remove useless print

* Merge tongxin PR and refine code

* readd some test

* rm useless print

* polish code.

* fix bug in minimize

* add get_input_var_list and get_output_var_list and use it in lower

* Fix scatter_add_p prim2orig

* Update code and fix orig2prim/prim2orig UT

* delete vars after block.desc._remove

* Improve ops and vars clean up logics.

* fix some bug in linearize and lower

* update tanh transpose.

* use set instead of list for var2remove

* test updated.

* polish code.

* fix dot2bar delete.

* merge tx/ad

* add indextensor_dot for gather and scatter_add

* add sorted for set

* Fix scale_orig2prim params

* fix some syntax bug

* add golbal_lower_update list

* Better handling of unused vars.

* update tests.

* Fix elementwise_sub orig2prim

* support none for transpose rule

* Merge and add transform UT

* fix a bug in transpose

* Fix transpose and UT

* a hacky fix for cancat op

* Fix exector place

* Refine variable name

* Add elementwise_mul orig2prim and support p_norm when p=1

* Add sqrt orig2prim rule and UT

* merge wz test

* rename files, add enable_prim, disable_prim, prim_enabled, delete global_lower_update

* fix a bug in test_ad_transform_trans

* revert modify in framework.py

* add paddle.fluid.incubate.ad_transform to  python/setup.py.in

* Fix remove vars error

* Fix p_norm_orig2prim

* merge wz

* Modify the code directory

* Add utils.py and remove get_input/output_vars functions

* Update maolin code

* Rename UT and refine test_ad_transform_primops

* Fix div_p jvp rule

* Add higher derivatives UT

* Remove UT to autograd dir

* Fix comments

* import paddle in primops.py

* Add some error message for assert

* Refine UT class name and refine some comments in primreg.py

* update minimize of paddle/optimizer for supporting new autograd

* resolve cicular importing between backward.py and optimizer.py

* fill gradients and minimize unittest

* Replace `assert isinstance` with `raise TypeError`

* Add some assert message for primx.py

* Polish variable name

* Add some assert message

* add some docstring

* refine some name

* update the format of english documents

* Split test_transform.py to two files to avoid ci error

* fix the document format of enable_prim/disable_prim/prim2orig/prim_enabled

* polish test_gradients_and_minimize

* add default value for prim_enabled api doc

* Remove some UT to avoid windows ci error

* Enlarge test_gradients_and_minimize limit time

* Fix ut limit time
Co-authored-by: Nveyron95 <veyron_wu@163.com>
Co-authored-by: NJiabin Yang <360788950@qq.com>
Co-authored-by: Nlevi131 <limaolin01@baidu.com>
Co-authored-by: NTongxin Bai <waffle.bai@gmail.com>
Co-authored-by: NXiaoxu Chen <chenxx_id@163.com>
Co-authored-by: Nlevi131 <83750468+levi131@users.noreply.github.com>

* improve introduction of bfgs args; test=document_fix

* modify according to zhouwei's comment; test=document_fix

* add gradient merge for DistributedFusedLamb

* use master acc gradient

* fix CI ut

* polish

* remove math_function_impl.h change

* fix test_update_loss_scaling_op.py

* try to fix XPU/NPU CI

* add gm ut

* expose api

* ref clipgradbynorm

* update

* Update __init__.py

* fix recompute

* modify return

* moe ref

* ref commit; test=document_fix

* update; test=document_fix

* update test=document_fix

* update; test=document_fix

* moe ref

* ref commit; test=document_fix

* update; test=document_fix

* update test=document_fix

* fix bfgs_doc; test=document_fix

* add parameter name; test=document_fix

* modify according to chenlong's comments;test=document_fix

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

* fix kernel register problem

* fix image cv2 import

* fix lamb

* add Output(Step) to distributed fused lamb op

* add _set_step

* add graph_send_recv yaml

* deal with confict

* fix compile bugs

* cut off relation between xk and initial_position's graph

* fix_bug

* add detach to cut off with original graph

* 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

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

* 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>

* [New API]: miminize_bfgs and miminize_lbfgs

* modify for python module call correctly

* add functional package, add error raise in static_graph, change assign to set_value

* unify static_graph and dygraph, fix bug when x or H0 is float64

* now only accept input is tensor, put check args in utils.py, put exception test together

* temp

* add more detailed algorithm illustration and comment, reduce test case to limit test time in 15s

* change in_dygraph_mode to in_dynamic_mode

* fix bug of sample code; reduce test case to reduce test time

* change dir to incubate

* add random routing op

add _random_routing api in utils

add random routing ut

* # This is a combination of 10 commits.
# The first commit's message is:
add expert count op

add ut for expert_count

# This is the 2nd commit message:

update UT only for cuda

# This is the 3rd commit message:

fix for rocm

# This is the 4th commit message:

update ut

# This is the 5th commit message:

add moe module

# This is the 6th commit message:

add expert count op

add ut for expert_count

# This is the 7th commit message:

update UT only for cuda

# This is the 8th commit message:

update ut

# This is the 9th commit message:

add moe module

# This is the 10th commit message:

make expert count private

* add assign pos op

* fix upper num name

* add api _assign pos

* add ut for assign pos op

* update date

* add op about moe gate

update utils

add limit by capacity op

add ut for limit_by_capacity

add ut for prune_gate_by_capacity

add ut for limit_by_capacity

add ut for prune_gate_by_capacity

* fix for win

* fix bugs in test_limit_by_capacity_op

* update ut

* update for test (timeout)

* fix ut

* update

* update(fix) ut for win

* moe apis in incubate

* # This is a combination of 10 commits.
# The first commit's message is:
add expert count op

add ut for expert_count

# This is the 2nd commit message:

update UT only for cuda

# This is the 3rd commit message:

fix for rocm

# This is the 4th commit message:

update ut

# This is the 5th commit message:

add moe module

# This is the 6th commit message:

add expert count op

add ut for expert_count

# This is the 7th commit message:

update UT only for cuda

# This is the 8th commit message:

update ut

# This is the 9th commit message:

add moe module

# This is the 10th commit message:

make expert count private

* add assign pos op

* fix upper num name

* add api _assign pos

* add ut for assign pos op

* update date

* fix for win

* update for test (timeout)

* fix ut

* update

* fix ut for number count

* add apis and utils

* add gate apis

* add moe and grad clip apis

* update moe apis

* add ops for moe gate

* fix

* update for base moe layer api

* add random routing op

add _random_routing api in utils

add random routing ut

* fix for dygraph

* update with ranodm routing

* update

* fix ut for limit by capacity

* update

* update limit by capacity for easily to switch to single thread mode

* update api docs
Co-authored-by: Nhlygit66666 <2570058140@qq.com>

* add random routing op

add _random_routing api in utils

add random routing ut

* # This is a combination of 10 commits.
# The first commit's message is:
add expert count op

add ut for expert_count

# This is the 2nd commit message:

update UT only for cuda

# This is the 3rd commit message:

fix for rocm

# This is the 4th commit message:

update ut

# This is the 5th commit message:

add moe module

# This is the 6th commit message:

add expert count op

add ut for expert_count

# This is the 7th commit message:

update UT only for cuda

# This is the 8th commit message:

update ut

# This is the 9th commit message:

add moe module

# This is the 10th commit message:

make expert count private

* add assign pos op

* fix upper num name

* add api _assign pos

* add ut for assign pos op

* update date

* add op about moe gate

update utils

add limit by capacity op

add ut for limit_by_capacity

add ut for prune_gate_by_capacity

add ut for limit_by_capacity

add ut for prune_gate_by_capacity

* fix for win

* fix bugs in test_limit_by_capacity_op

* update ut

* update for test (timeout)

* fix ut

* update

* update(fix) ut for win

* moe apis in incubate

* # This is a combination of 10 commits.
# The first commit's message is:
add expert count op

add ut for expert_count

# This is the 2nd commit message:

update UT only for cuda

# This is the 3rd commit message:

fix for rocm

# This is the 4th commit message:

update ut

# This is the 5th commit message:

add moe module

# This is the 6th commit message:

add expert count op

add ut for expert_count

# This is the 7th commit message:

update UT only for cuda

# This is the 8th commit message:

update ut

# This is the 9th commit message:

add moe module

# This is the 10th commit message:

make expert count private

* add assign pos op

* fix upper num name

* add api _assign pos

* add ut for assign pos op

* update date

* fix for win

* update for test (timeout)

* fix ut

* update

* fix ut for number count

* add apis and utils

* add gate apis

* add moe and grad clip apis

* update moe apis

* add ops for moe gate

* fix

* update for base moe layer api

* add random routing op

add _random_routing api in utils

add random routing ut

* fix for dygraph

* update with ranodm routing

* update

* fix ut for limit by capacity

* update
Co-authored-by: Nhlygit66666 <2570058140@qq.com>

* refactor eager flags

* fix flags error when we switch from eager to dygraph

* fix ci problem

* fix ci

* fix ci

* merge develop and fix code style

* merge develop and fix code style

* fix op test error

* fix op test error

* fix op test error

* fix op test error

* fix op test error

* merge develop

* add out_size shape for graph_send_recv

* fix bug in register kernel: no const int& support

* add out_size in infermeta

* change unittest

* fix unittest

* fix out_size default value

* fix doc

* delete arg mapping

* add sig

* move -1 to 0

* move -1 to 0

* segment pool support for int int64 kernel.

* add support in python api

[multiprocessing] Add paddle.incubate.multiprocessing for sharing tensors  between python processes. (#37302)

* Add support for paddle.multiprocessing
* move multiprocessing to incubate.

* vectorize lamb kernel

* remove flags, add ut

* remove useless codes

* refine code, add param order

* add multi tensor apply l2 norm

* add multi_tensor_apply code

* make sizeof(TensorMeta) smalller

* move code to distributed_fused_lamb_op.cu

* remove useless FLAGS

* fix 'invalid escape sequence'

* fix assert error