* 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

* set flag of clip_extra in save_inference_model to true (#46151)

* open the clip_extra flag in paddle.static.save_inference_model, test=allcase (#46456)

* Open the clip_extra flag in TracedLayer.save_inference_model (#46473)

* open the clip_extra flag in paddle.static.save_inference_model, test=allcase

* set the defalut value of clip_extra in TracedLayer from False to True, test=allcase

* update english doc of paddle.static.save_inference_model, test=document_fix (#46484)

* Fix clip_extra logic in remove_training_info (#46534)

* fix clip_extra code in remove_training_info

* revert rnn opmaker clear

* use re replace judge by case

* simplify re

* add scope cache & reuse

* add gc scope for end of each train step

* del scope reuse for jit

* refine code

* test

* [dy2static] support user to use decorator in their program (#45768)

* support deco

* fix deco ast type

* arg_str

* 1

* support callable deco

* code style

* codestyle

* test_error

* fix decos in another file

* recover conflict codes

* [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

* skip forward save

* fix bug

* more ci for jit skip forward

[ Dy2Static ] Fix bugs when select inputs meeting different shape or undefined-var (#45916) (#46020)

* 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

* convert_call support staticmethod for class.

* while support for python container.
It is convenient to convert more dynamic graph codes into static graphs.

* cond support python container

* add unittest for staticmethod convert_call

* fix bugs

* add unittest for item interface

* fix bugs

* change to np.testing.assert_allclose

* code format

* fix comments.

* code format

* 1. fix non-local error while dealing push_pop names
2. escape "'" in push_pop_names to avoid syntax errors.
3. unified the non-local stmt creation processes in getter and setter.
4. split the nonlocal_names and getter/setter names.

* fix bugs

* 1. revert setter and getter, push_pop_names must have non-local

* fix bugs.

* code format

Adapt tensor output_size for conv2d_transpose and depthwise_conv2d_transpose

* [Dy2Stat]Filter UserWarings while @to_static

* only filter DeprecationWarning

* fix unittest

* [Eager] fix pool2d interface under eager mode

* add use_gpudnn for pool2d

* fix pool2d yaml conflicts

* fix pool2d yaml

* 1. make list transformer into jit form.
2. fix some bugs in tensor_array, such as append.
3. enhance the function analysis visitor to recognize push/pop.
4. add setter/getter helper to deal with 2+ name sets.

* fix ci errors:
1. add to_tensor_array logic in convert_cond
2. fix IfExpr error.
3. fix erros while return_names or push_pop_names is None
4. fix slice error in a[i]=1 where a is tensor_array
5. add pop interface in Variable

* [Eager] fix spectral_norm interface under eager mode

* fix spectral_norm yaml config

* add interpretercore

* refine backward program id

* add code

* refine program

* refine code

* create forward/backward_program by prog2graph2prog method

* test, do not care

* refine code

* refine code

* refine code

* test, do not care

* add interpretorcore

* add scope

* refine scope create method

* add jit for new_exe

* solve conflict

* delete unused code

* polish code

* polish code

* refine scope in inplace

* refine for datatransfer

* refine _rebuild_from_desc

* refine control eager deletion attr

* refine used_for_jit

* refine jit for infer

* op size0 use ori program

* polish code

* refine jit

* refine run_program_op ut

* refine inplace

* refine control

* refine graph helper

* refine control

* refine inplace

* refine buffer_share_inplace_pass

* polish code

* polish code

* refine usage for compilerProgram

* refine control

* test

* test core cache

* refine code

* refine io.py

* increase test_seq2seq timeout

* refine convert program

* refine interpretercore_cache release

* delete buildinplace

* refine partial_program && io

* refine code for io

* test

* test

* test

* unify the size and size() by jst

* fix bugs

* bug fix.

* fix bugs

* change all_close -> np.testing.assert_allclose

* while support for python container.
It is convenient to convert more dynamic graph codes into static graphs.

* cond support python container

* 1. make select_input output shape = input[1]
2. add warning in while_loop risky assign

* fix 2 problem in GPT export:
1. a bug in while_op no_need_copy_var, which causes gpu memory leakage
2. a bug in undefined_var where the stop_gradient should be False.

* change name by code review

* format

* while support for python container.
It is convenient to convert more dynamic graph codes into static graphs.

* cond support python container

* optimize python api to speed up eager exec

* optimize python api to speed up eager exec

* optimize python api to speed up eager exec

* Make sure that the output of whilep must exist in the input

* insert assign in block(0)

* add unittest.

* fix_shape

* [Eager]Support Lazy initialization for nn.Lazyer

* fix

* add control flag and input shapes for new dygraph

* fix file mode

* improve code coverage

* fix a bug in statstic

* fix according to review

* optimize performance

* fix

* 1. add prepare_gradient_aggregation in PartialProgramLayer

* 1. draft

* fix ci problem

* Fix abnormal format of message when raise KeyError in Dy2St

* Format code

* Format code

* Add UT

* Rename method