* [Fluid Clean]Migrate utils files and delete dygraph_to_static dir

* fix setup.py.in

* fix import

* fix unittest

* fix code style

* fix unittest

* [Fluid clean]Migrate base/call/print et.al transformer into paddle.jit

* fix phi kernel

* Revert "fix phi kernel"

This reverts commit eff8891c7efda6e49799edbcaef2ca50379d50ef.

* [Fluid Clean]Migrate if/while/return/break transformer into paddle.jit

* migrate call_transformer

* migrate call_transformer

* [Fluid Clean] Migrate program_translate.py/jit.py into paddle.jit dir

* update config

* re-blacken python code

* temporarily disable date and diff_py_file

* skip a format

* Add TypeHint Transformer

* add unittest for typehint transformer

* [Dy2Static] Remove GradTransformer
1. fix einsum infershape bugs.
2. remove grad_transformer and unify paddle.grad and paddle.static.gradient.
3. add dygraph_and_dy2static_only decorator for dy2static.

* fix bugs

* rename

* [CodeStyle] remove all future import

* revert test_error.py

* restore future import in example code

[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

* 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

* 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. 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

* change NameVisitor to FunctionScopeAnalysis

* polish the logic of undefined var in while_loop. create vars after body execution

* replace old NameVisitor in while and fix all CI

* Togather with CreateVariableTransformer

* add create_variable_transformer

* fix bugs

* merge

* fix some error, TODO: ForNodePreTransform ahead

* merge for unite PR

* fix conflict with base_transformer PR

* fix ci errors, fix [for i in range()] error

* fix according to code review

* add support for control flow block analysis

* move FunctionNameLivenessAnalysis into utils

* pass test_ifelse.py

* remove duplicate data_layer_not_check

* pass the test_ifelse.py

* fix unittest error .

* fix all ci error in first version

* temporay disable CreateVariableTransformer

* fix ci errors

* fix function name liveness analysis bugs

* modifty def cond

* fix

* fix ci error - v2

* fix by code review

* change return_name_ids -> return_name

* Add BaseTransformer for dy2st error message

* Fix return_transformer error

* Polish dy2st error info in runtime

* Fix UT error

* Polish runtime error code

* Refine ifelse early return

[Dy2Stat]Add apply_optimization for @to_static and remove BreakTransformOptimizer by default (#43320)

* [Dy2Stat]Add apply_optimization for @to_static and remove BreakTransformOptimizer by default

* fix unittest

* integrated gast library

* integrated gast library

* fix unittest and remove ast2.py

* remove 'gast' from __all__ in __init__.py

* add copyright in other files

* fix copyright

This PR made these changes to support double grad:

1. Translate `paddle.grad` to `paddle.static.gradients` to support double grad for dy2stat.
2. Fix IfElseTransformer bug which may not change value if "Store before Load" variable is in "Store" statement is in IfElse conditional statement
3. Add `DOut` to support double grad variables in `run_program_op`
4. Add support for renaming for double grads for `jit.save/load`

* Join break cond with while cond

* remove usless code

* refine the if code

* Split into BreakTransfromOptimizer

* add BreakTransformOptimizer in ast_transformer

* add more comment

* refine code of DygraphToStaticAst

* add __init__ function

* Add env value to  log to stdout; 2.Add logger name

* Optimize log messages in dygraph-to-static

* Replace logging.warn and warnings.warn with logging_utils.warn

* [Dy2Stat] Add debugging and logging mechanism for dygraph to static. 

* Remove TransformerError temporarily. 

* import mock in PY2, from unittest import mock in PY3. test=develop

* Expose interfaces set_code_level and set_verbosity in paddle.jit, fix doc of the two interface. 

* polish doc of set_verbosity and set_code_level. 

* add cast transform and its UT for dygraph_to_static. 

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.

* Refine caches of converting func test=develop

* fix if statement test=develop

* refine cache code test=develop

* rm unuse import statement test=develop

* Polish code comment test=develop

* cast var in convert_logical_XX. 

* Add convert_ifelse function in convert_operators.py  

* Add logical_transformer. Remove LogicalTransformer from loop_transformer.py 

* Revert modified tests in PR24799(convert_while_stmt). 

* Comment and modify code that doesn't support `return` statement. 

* Remove unnecessary class: MergeAssignTransformer, NodeTestTransformer and IfConditionVisitor in ifelse_transformer. 

Add assert grammar for ProgramTranslator

* support to train in static

* support to independent decorator

* remove in_dygraph_mode condition in ProgramTranslator

* fix import param_guard and add train/eval test=develop

* Modify into ShareVarsFromScope and rm __all__ in partial_program test=develop

* add print transformer & unify print format, test=develop

* remove using of dygraph_to_static_func, test=develop

* remove python stdout capture, test=develop

* fix compatibility problems for PY2, test=develop

* fix detail error, test=develop

* fix type analysis bug, test=develop

* fix print tuple compatible error in PY2, test=develop

* replace get_func to declarative, test=develop

* fix detail bug, test=develop

* fix some detail problems, test=develop

* change visit_call in print transformer, test=develop

* [Dy2Stat]Support recursive call.

* Remove Redundant decorator to pass the Py35 unittest temporarily.

[Dy2stat] Add Test and Example Code for Different Access to ProgramTranslator and Fix Related Bug (#23958)

To prepare for publishing APIs, I added tests for that we can access dy2stat through:

@fluid.dygraph.declarative
@fluid.dygraph.jit.declarative
fluid.dygraph.ProgramTranslator()
fluid.dygraph.dygraph_to_static.ProgramTranslator()
fluid.dygraph.dygraph_to_static.program_translator.ProgramTranslator()

It surprised me that we had bugs on those different usages. I have fixed them.

I also added example codes for these new APIs

This PR also pulls my current PR https://github.com/PaddlePaddle/Paddle/pull/23880, so the PR history is long. For reviewer information, you could review this PR after https://github.com/PaddlePaddle/Paddle/pull/23880 is merged

1. Rename Dygraph To Static Decorators to declarative
2. dygraph_to_static_func is still using in some training tests, I cannot delete it now.
3. Add some API docs

* Move BasicApiTransformer to a separate file. test=develop

* Fix a bug: A api in module is not a real dygraph api in dygraph_to_static. test=develop

1. Add Decorator 'dygraph_to_static_program'
2. Add corresponding ProgramTranslator.get_program
3. Add ProgramTranslator.save_inference_model
4. Modified some warning information of dy2stat
5. Change program cache to contain startup_program because for users who gets program to run, they may like to initialize startup program

This PR does exact the thing as the title. The reason is that we plan to develop 4 decorators

"dygraph_to_static_code"
"dygraph_to_static_program"
"dygraph_to_static_func"
"dygraph_to_static_output"

 The 4 decorators will emphasize different part when translating dygraph to static graph. Decorator name "dygraph_to_static_graph" is too big for the function it implements.

* Support to use external function test=develop

* refine the parms of ast_to_func test=develop