* [CodeStyle][py2] remove `compat` module (to_bytes)

* remove some unused imports

* clean up to_bytes definition and unittests

* Revert "clean up to_bytes definition and unittests"

This reverts commit e726539e1768172a411ff60e63fab82f164343cf.

* use `b` prefix instead of `encode()`

* [Zero-Dim] support input 0D Tensor for unary api

* fix CI

[Eager, Performance optimization] support mod / matmul ( % and @ operator) to sink to Cpp layer (#46565)

* [Eager, Performance optimization] support mod ( % operator) to sink to Cpp layer

* fix mod logic

* support matmul math operator

* rm LOG(warning), use VLOG(6)

* fix conflicts mistake

[Eager, Performance optimization] support less_than & less_equal( < & <= operator) to sink to Cpp layer (#46542)

* [Eager] math op sink to Cpp level

* fix ci errors

* draft version

* support + and - operator under cpp directly

* add static test

* polish code

* promote types or unify right type to left

* recover static test case

* polish code and fix some ci errors

* support complex and polish code

* fix conflicts

* fix windows ci errors

* fix windows-inference-ci errors

* polish and fix tests

* fix test case

* polish code

* [Eager, Performance optimization] support multiply( * operator) to sink to Cpp layer

* rm useless glog

* [Eager, Performance optimization] support divide( / and // operator) to sink to Cpp layer

* polish code

* polish code and fix code-format

* polish code

* fix CI

* polish code

* update test

* support div operator under cpp

* fix scalar as input

* Polish div logic, fix ci test

* fix errors

* [CodeStyle] remove all future import

* revert test_error.py

* restore future import in example code

* [Eager] math op sink to Cpp level

* fix ci errors

* draft version


* support + and - operator under cpp directly

* add static test

* polish code

* promote types or unify right type to left

* recover static test case

* polish code and fix some ci errors

* support complex and polish code

* fix conflicts

* fix windows ci errors

* fix windows-inference-ci errors

* polish and fix tests

* fix test case

* polish code

* [Eager, Performance optimization] support multiply( * operator) to sink to Cpp layer

* rm useless glog

* polish code

* polish code and fix code-format

* polish code

* fix CI

* polish code

[Eager, Performance optimization] math op sink to Cpp level ( + and - operator as an example ) (#45811)

* [Eager] math op sink to Cpp level

* fix ci errors

* draft version

* draft version

* draft version

* support + and - operator under cpp directly

* add static test

* polish code

* promote types or unify right type to left

* recover static test case

* polish code and fix some ci errors

* support complex and polish code

* fix conflicts

* fix windows ci errors

* fix windows-inference-ci errors

* polish and fix tests

* fix test case

* polish code

* polish code

* polish code and fix code-format

* polish code

* polish code

* polish code

* polish code

* 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

* add numpy api err msg

* fix bug

* fix unittest

* add set_state_dict err

* rewrite numpy_api_check

* add define

* change err msg

* fix test

* move import statement

* use re replace judge by case

* simplify re

* [Eager] polish clone interface

* rm clone in python, add clone in eager_method.cc

* 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

[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

* trim trailing whitespace

* fix `.cmake-format.py`

* revert npu ut changes, avoid npu ci error

* 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

* 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

* add scope cache & reuse

* add gc scope for end of each train step

* del scope reuse for jit

* refine code

* test

* 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