* 1. refactor the return transformer.
2. fix some bugs in return transformer.

* support raise error while return stmt's father is For or while

* fix ci error.

* fix ci error and add some unittest

* code format

* fix ci error

* clear extra attr of some ops in opmaker

* revert clear use_cudnn for pool

* fix test_operator_desc

* fix Attr interface of OperatorBase

* [CodeStyle] trim trailing whitespace in yaml and hook

* python incremental whitespace and yml files

* support cast op backward refuse forward

* Fix the bug of high order unit test framework

* fix return order error and duplicate results with specific inputs

* Fix TransDataBackend Error when call unsqueeze using MKL Tensor

* Add UT

* Refine UT

[BugFix] fixed a bug in decorator transformer, it can not analyze decorator with params correctly (#46055)

* fix deco call

* add raise

* add test

* add warn, fix paddle api

* fix error type

* fix coverage

* add reduce_mean,reduce_sum primitive ops
* add ne_p gt_p primitive operators
* add ge_p abs_p primitive oparators
* add cast primitive operators
* add pow,square prim2oirg rules
* add elementwise_div orig2prim rule

* unify  core_avx and core_noavx

* fix except error

* revert mac compile logic

* revert dylib to so

* add core_noavx branch

* remove core_noavx

* replace paddle_core by lib paddle

* polish var name

* replace paddle_core by libpaddle

* update custom device commit

* polish code by comments

* skip forward save

* fix bug

* more ci for jit skip forward

* [Auto Parallel] Use c++ dist attr in the completion process

* [Auto Parallel] Add minor changes

* [Auto Parallel] Use c++ dist attr in the completion process

* [Auto Parallel] Add minor changes

* [Auto Parallel] Add the serialization process for dist attrs

* [Auto Parallel] Remove unnecessary comments

* [Auto Parallel] Fix some bugs

* [Auto Parallel] Fix the code style

* [Auto Parallel] Remove unnecessary impls

* [Auto Parallel] Fix the importing error

* [Auto Parallel] Fix the copy from bugs of op dist attr

* [Auto Parallel] Replace the use of constexpr if

* [Auto Parallel] Redesign the shard_tensor, shard_op and ProcessMesh

* [Auto Parallel] Change API of the completion unittest

* [Auto Parallel] Fix the bug when set_attr an int

* [Auto Parallel] Add the unittest for the serialization

* [Auto Parallel] Add some unit tests

* [Auto Paralle] Unify the strategy

* [Auto Parallel] Improve the engine api

* [Auto Parallel] Reset the changes made to the framework

* [Auto Parallel] Change the engine unittest

* [Auto Parallel] Update API of the completion and partitioner

* [Auto Parallel] Update unit tests using engine api

* update shard annotation

* [Auto Parallel] Remove the modifications of other modules

* [Auto Parallel] Add docs for APIs

* add new strategy

* [Auto Parallel] Replace the logger

* [Auto Parallel] Restore the test_program.py

* [Auto Parallel] Change the import rules

* [Auto Parallel] Add the examples for Engine

* [Auto Parallel] Do some minor changes

* [Auto Parallel] Remove yaml dependency

* [Auto Parallel] Fix the unittests

* add valid after train

* bug fix
Co-authored-by: Nzhaoyingli <zhaoyingli@baidu.com>
Co-authored-by: Ncaozhou <caozhou@radi.ac.cn>
Co-authored-by: Ncaozhou <48191911+Caozhou1995@users.noreply.github.com>

Support 0 shapes input Tensor for MKL slice kernel

* saved_tensors_hooks

* trim trailing whitespace

* fix `.cmake-format.py`

* revert npu ut changes, avoid npu ci error

* merge python lib
* Update third_party.cmake
* Update CMakeLists.txt

* add convert rules for fill_any_like op in paddle science

* add unit test for fill_any_like op in paddle science

* modify fill_any_like convert rule

* modify fill_any_like convert rule dtype

* [CodeStyle] trim trailing whitespace in .md and .rst

* empty commit, test=document_fix

* update

* update

* update

* support bfloat16 for amp_decorate

* add check_finite for bf16

* fix bug

* add ut

* add ut

* refine code

* fix select_input with different shape errors:
1. select_input_with_buildin_type directly return non-undefinedvar branch when meeting undefined var
2. the output shape of select_input is inferred from inputs.

* reverse the logic in select_input

* add reduce_mean,reduce_sum primitive ops

* add ne_p gt_p primitive operators

* add ge_p abs_p primitive oparators