* expose and unify the Tensor concepts to the user

* expose tensor to user

* add copy place for Tensor

* add copy place for Tensor

* add note

* add macro PADDLE_WITH_CUDA

* remove RUN_TYPE=DIST

* fix some error

* Upgrade `no_grad` decorator

test=develop

- match torch decorator usage (i.e., with parenthesis)
- handle generator functions
- add `paddle.no_grad` alias

* Switch from `functools` to `decorator`

preserves signature

* Reword decorator usage note

* add auto_cast, test=develop

* add loss scaler, test=develop

* add comments, test=develop

* refine code, test=develop

* refine code, test=develop

* do not set flags automatically, test=develop

* fix custom op bug, test=develop

* add more test, test=develop

* refine enable logic, test=develop

* enable amp test with GPU, test=develop

* add unittest

* add test for found_inf

* follow comments

* follow comments

* remove global variable, use singleton

* add some notes

* update comments

* update comments

* update comments

* add use_dynamic_loss_scaling argument

* refine found_inf

* refine found_inf

* fix loaded var suffix repeat error

* use new dygraph name for loaded param

[Dy2Stat] Removes temporary files created during the transformation of dygraph to static graph.  (#26150)

* Directory migration, test=develop

* Change imperative from paddle init to paddle framework, test=develop

* Fixed jit bug, test=develop

* default static mode, test=develop

* fixed format and create parameter belongs to framework, test=develop

* Fixed import package, test=develop

* fix __init__ format, test=develop

* fixed alias problem

* fixed paddle.enable_imperative problems, test=develop

* Add unittest

* delete install_check comment

* Fixed unittest timeout

* fixed unittest error

* move Program default_xx_program to static package

* optimize unittest method

* fixed framework __init__ format

* fixed jit path

* delete alias

* move jit to paddle

* Fixed unittest format

* fixed paddle.default_main_program

* Fixed save load API in paddle __init__.py

* fixed ci paddle.imperative.to_variable

* fix prelu for compatibility with saved model of old version

* reshape alpha

[Dy2Stat-ErrorMessage]Optimize error value to improve readability when error raised in runtime.  (#25970)

* don't remove op_callstack

* [Dy2Stat-ErrorMessage] Optimize error value to improve readability if error raised in run-time. 
  1. update op_callstack with original information;
  2. simplify error value to improve readability if error raised in run-time.

* Fix error in Python3. 

* add limit support for load_dygraph loading jit.save result

* simplify unittest

* add unittests for coverage

* remove encoding limit of loading extra var info

* [Dy2Stat-ErrorMessage]Enhance original error and create new exception. test=develop

* Delete redundant code and change func name to create_and_update_origin_info_map. 

* optimize loop_transformer. 

* fix bug in print_transformer.

* Modify code according to the comments.

* add paddle.utils.deprecated.

* add docstring. test=develop

* add alias paddle.utils.deprecated. test=develop

* rm deprecated in python/paddle/fluid/annotations.py. test=develop

* 1. check version before warning. 2. bug fix. test=develop

* bug fix. test=develop

* use paddle.fluid.require_version. test=develop

* fix doc

* fix doc. test=develop

* fix doc. test=develop

* bug fix. test=develop

* use packaging.version. test=develop.

* enhance doc. test=develop

* add compare_version function. test=develop

* add version.py. test=develop

* remove packaging. test=develop

* move compare_version to deprecated.py. test=develop

* remove print. test=develop

* fix. test=develop

* fix. test=develop

* fix. test=develop

* fix. test=develop

* inline. test=develop

* fix. test=develop

* add apply for Layer

* fix eval() sync problem

* add unittest

* modify according reviewer

* fix unittest failed

[Dy2Stat-ErrorMessage]  Add interface:create_origin_info_map and attach_origin_info for AST node (#25627)

* Add interface:create_origin_info_map and attach_origin_info for AST node. test=develop

* Fix code according to comments from reviewers. test=develop

* remove ProgramTranslator.save_inference_model

* adapt save_quantized_model

* revert buffer check implemention

* remove useless import function

Enhance TracedLayer Error Message

Note: this PR uses assert to check type somewhere and check_type somewhere, the reason is that the check_type skips checking when it is under dygraph mode.

* fix the double grad bug for the star gan. test=develop

* update the retain_graph parameter doc. test=develop

* add the unit test for the retain_graph parameter. test=develop

* fix jit.save input type change error

* add unittes

* Refine Model

1. Take the network (instance of Layer) as the input of Model.
2. Refine set_dict/load_dict of Layer.
3. Refine Input interface, so update code sample about Input

Modify the print in Dy2stat for dynamic type. Unit test is covered in old test_print.py

windows CI scripts for xly

* remove op call stack test=develop

* fix typo test=develop

* experimental refactoring, test=develop

* add TranslatedLayer & remove StaticModelRunner, test=develop

* revert tracedlayer change, test=develop

* fix test_mnist unittest error, test=develop

* add doc & examples, test=develop

* polish doc details, test=develop

* add imperative.jit module, test=develop

* change TranslatedLayer pos, test=develop

* adjust jit module import path, test=develop

* polish doc based review result

* add SaveLoadConfig.separate_params to save paraams separately

* add Layer.buffer support, test=develop

* polish doc details based review result, test=develop

* polish details baesd review comments, test=develop

* add empty str check for param, test=develop

* add unittests, test=develop

* polish details based review comment, test=develop

* remove blanks in comment, test=develop

* polish doc details, test=develop

* update imperative doc link, test=develop

* add api attr for load, test=develop

* fix optimizer.state_dict and LRScheduler.state_dict to save/load dygraph,test=develop

* fix optimizer.state_dict and LRScheduler.state_dict to save/load dygraph,test=develop

* Add a judgment that state_dict/set_dict is used incorrectly,test=develop

* fix some doc error,test=develop

* fix current_step_lr for _LearningRateEpochDecay,test=develop

* remove some unsed code to improve coverage,test=develop

* remove some unsed code to improve coverage,test=develop

add new API:LambdaDecay

* clean __str__ of VarBase and ParamBase, test=develop

* clean to_string, test=develop

* update unittest, test=develop

* fix bn & in in dy, test=develop

* update instance_norm,test=develop

* fix bugs,test=develop

* add more case in unittest,test=develop

* fix,test=develop

* fix,test=develop

* add cast transform and its UT for dygraph_to_static. 

* show the attr and functions of the Layer,test=develop

* add buffer for dir,test=develop

* fix __dir__,test=develop

* fix doc of Layer.__dir__, test=develop

* support tuple/list init for VarBase,test=develop

* fix doc of fluid.dygraph.to_variable,test=develop

* fix doc of fluid.dygraph.to_variable,test=develop

* add new API: MultiStepDecay, a new learing rate strategy, test=develop

* add new API: MultiStepDecay, a new learing rate strategy,test=develop

* add new API: MultiStepDecay, a new learing rate strategy,test=develop

* add base class of LearningRateEpochDecay, and MultiStepDecay, and StepDecay, test=develop

* fix doc to add coverage,test=develop

Support Various-Length Return Grammar in Dy2stat. This PR is a follow-up of https://github.com/PaddlePaddle/Paddle/pull/25176 .

The basic idea is putting no-value placeholder variables at `return` statement to make all `return` statement have same length, after that the static graph can have fixed fetch output (code at return_transformer.py). Then remove those no-value placeholder when we finally return dygraph result (code at partial_program.py).

However, various length return in Bert model is still not supported. The dy2stat can change the code as I wish but some ops which check shape at compile time (e.g. Reshape, MatMul) will throw error because of the no-value-placeholder may not have the required shape. Is this a matter? To me, those no-value placeholder will be replaced as really values meeting shape requirements at run time, so I think the solution should be some way to do the compile-time checking. By the way, every time when we have dynamic shape, it often causes problem in dy2stat. We should find a way to handle it in the future.

Fixing various return in Bert is my TODO thing and I will also find some other existing models for verification.

* support to save varBase created in __init__ test=develop

* polish code test=develop

* refine to_static_var test=develop

* refine warning test=develop

* add unitteset for to_static_var test=develop

* fix logger test=develop

* polish buffers en doc test=develop

* fix param_guard test=develop

* refine en doc test=develop

This PR added basic support for 'return' grammar in dy2stat. It supports the control flow of 'return'.

The basics idea is using a return value variable to store the early return statements and boolean state variables with if-else to skip the statements after the return statements.

**This PR is very basic support. There are some corner cases I didn't develop/test**. For example, 'return None', 'return different length of variables', 'return non-tensor and tensor together', 'no return statement'. **These corner cases will be done in my next PRs**. Target date is this week.

**Note**: 
1. for the unit test, I changed test_program_translator.py because the StaticCode of `dyfunc_with_if_else` will change. To guarantee the correctness of `dyfunc_with_if_else`, I also run it in `TestRecursiveReturn` in test_return.py.

2. I commented the early return code in bert_dygraph_model.py because 'return different length of variables' is unsupported now. I also know that there are some other models used early return and we didn't enable it in the unit test. I will add support for it in next PRs and then re-enable those tests.

* add cycle_gan_model

* align train test=develop

* modify image_size into 64 to avoid TimeOut test=develop

* TODO in GPU test=develop

fix sample code error of fluid.dygraph.NaturalExpDecay