I found the unittest failed due to batch size. Maybe the reason is that our CI machine has limited memory. I decreased the batch size.

As the title

* disable ut test_parallel_executor_fetch_isolated_var,test=document_fix

* test for limiting ut exec time as 15S

* fix an error caused by cannot find ut

* fix some error

* can not find test_transformer

* fix error caused by ut not run in windows

* fix error caused by Compiler Options

* fix error caused by setting timeout value as 15 in python/paddle/tests/CMakeLists.txt

* setting timeout value to 120s for old ut

* add the timeout value setting

* fix error caused by ut only run in coverage_ci

* add analyzer_transformer_profile_tester

* fix some error

* fix some error

* fix error with inference option

* fix error with inference option setting as ON_INFER

* add some ut to set timeout

* modified some option

* fix error

* fix some timeout error

* fix error

* fix error

* fix timeout for test_analyzer_bfloat16_resnet50

* fix error

* setting timeout properity for some ut

* first pr for new ut timeout as 15S

* refine jit.save/load to add support for other method, not only forward

* refine the code based on unit tests

* Add unit test for the code

* Add unit test for the code

* Modify the code according to the unit test

* Delete useless comments, save only one info file, etc.

* remove static_mode_white_list.pyc

* edit the code that generate 'extra_var_info'

* Fix bug in convert_call

* refine unittest

* refine code

* refine code

* fix unittest failed

* add assert

* add multiple exception type

* define all exception & polish compile pystack

* mapping paddle error to python exception

* polish static mode error format

* fix failed unittests

* fix dytostatic test_error

* fix check_nan_inf failed

* add unittest for coverage

* revert some code try to solve compile error

* refactor enforce & error change

* polish code & add unittest

* Join break cond with while cond

* remove usless code

* refine the if code

* Split into BreakTransfromOptimizer

* add BreakTransformOptimizer in ast_transformer

* add more comment

* remove some judgement

* fix len(outputs) == 1

* rename manual_seed to seed

* rename xxx1d-->xxx1D, xxx2d-->xxx2D, xxx3d-->xxx3D

* rename manual_seed --> seed

* do not rename .cc, .cu and .h file

* rename manual_seed --> seed

* rename manual_seed --> seed

* rename manual_seed --> seed

* rename manual_seed --> seed

* disable_static on doc example code

* donot change manual_seed on generator

* add enable_static on sample code

* convert python/paddle/fluid/layers/nn.py to bak

* fix typo

* fix code style

* fix seed to manual_seed when call functions of Generator()

* fix bug

* fix test_lstm unittest failed

* add more unittest

* modify cmakelist

* fix judgement

* disable test_lstm,test=document_fix

* fix some error,test=document_fix

* Fix save in eval mode

* remove assert statement

* fix test_partial_program failed

* add more test

* modify back into _train_program

* change paddle.fluid.layers.reduce_mean to paddle.mean

* change paddle.fluid.layers.reduce_mean to paddle.mean

* modify cond while_loop to paddle.static.nn.cond

* modify crop_tensor to paddle.crop

* modify Variable to paddle.static.Variable

* remove nn.beam_search, nn.beam_search_decode, nn.gather_tree

* remove bpr_loss, center_loss, rank_loss, smooth_l1, teacher_student_sigmoid_loss, edit_distance, sampled_softmax_with_cross_entropy in nn.functional

* remove apis in nn.functional.learn_rate.py

* remove pool2d, pool3d, adaptive_pool2d, adaptive_pool3d in nn.functional

* remove apis in nn.functional.vision

* remove erf, soft_relu in nn.functional.activation

* remove apis in nn.functional.extension

* remove nn.functional.rnn

* remove hash from nn.functional.lod

* remove row_conv from nn.functional.extension

* remove one_hot, pad2d, pad_constant_like from nn.functional.common

* remove nn.gather_tree, nn.BilinearTensorProduct, nn.Pool2D, nn.Pad2D

* remove apis from optimizer.__init

* remove tensor.creation.fill_constant

* remove elementwise_mul in nn.functional.common and  modify to paddle.multiply

* remove  tensor.stat.reduce_mean

* remove reduce_all, reduce_any in tensor.logic

* remove apis in tensor.math

* remove apis in tensor.__init__

* remove has_inf, has_nan in tensor.search

* remove apis in framework.__init__

* remove apis in paddle.__init__

* remove apis in nn.functional.__init__

* modify removed alias apis to raw api in doc and unittests

* fix remove grid_sample bug

* modify removed alias apis to raw api in doc and unittests

* modify removed alias apis to raw api in doc and unittests

* modify removed alias apis to raw api in doc and unittests

* modify removed alias apis to raw api in doc and unittests

* modify removed alias apis to raw api in doc and unittests

* modify removed alias apis to raw api in doc and unittests

* delete alias api relastions in doc

* reserve paddle.compat, paddle.sysconfig

* remove unittest for paddle.reduce_all, paddle.reduce_any

* modify removed alias apis to raw api in doc and unittests

* recover paddle.save and paddle.load

* resolve conflicts

* fix sample code missing paddle.enable_static() bug

* fix sample code missing paddle.enable_static() bug

* fix to_string sample code error

* fix adam

* fix gpu adam

* fix code style

* fix ut

* update ut add cuda code

add paddle.nn.initializer API, including: Normal, TruncatedNormal, Uniform, XavierNormal, XavierUniform, Assign (#27769)

* remove test_lac predictor run case

* replace config by kwargs

* change save path form dir to prefix

* fix failed unittests

* revert unittest name change

* polish en docs

* add more tests for coverage

Add Simnet Test for V2 APIs.

We used tool from https://www.paddlepaddle.org.cn/documentation/docs/zh/2.0-beta/guides/migration_cn.html#paddle1-xpaddle2-0beta to do v1.x to v2 transformation.

This PR pulled changes from #27430, please DO NOT merge before #27430 is merged

* Add test_resnet_v2.py test=develop

* fix test_se_resnet unittest

* fix test_se_resnet unittest

* add comments for decresing test_se_resnet precision

As the title

Refine Dy2stat APIs to 2.0rc

After discussion, we accepted 3 key points from reviewers:

1. In 2.0rc we changed dygraph_to_static folder to dy2static
2. Keep the three files: convert_call_func.py, convert_operators.py, variable_trans_func.py
3. Remove convert_operators path when users import convert_xxx. 

After this PR, users can import convert_xxx APIs by:

`import paddle.jit.dy2static.convert_xxx`

The file structure will be:

```
jit
    dy2static
          convert_operators.py
          convert_func_call.py
          variable_trans_func.py
```

Detail changed API in files:

In python/paddle/jit/dygraph_to_static/convert_call_func.py:
from ...fluid.dygraph.dygraph_to_static.convert_call_func import convert_call  #DEFINE_ALIAS

In python/paddle/jit/dygraph_to_static/convert_operators.py:
from ...fluid.dygraph.dygraph_to_static.convert_operators import cast_bool_if_necessary  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.convert_operators import convert_assert  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.convert_operators import convert_ifelse  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.convert_operators import convert_len  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.convert_operators import convert_logical_and  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.convert_operators import convert_logical_not  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.convert_operators import convert_logical_or  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.convert_operators import convert_print  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.convert_operators import convert_var_dtype  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.convert_operators import convert_var_shape  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.convert_operators import convert_while_loop  #DEFINE_ALIAS

In python/paddle/jit/dygraph_to_static/variable_trans_func.py:
from ...fluid.dygraph.dygraph_to_static.variable_trans_func import create_fill_constant_node  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.variable_trans_func import create_static_variable_gast_node  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.variable_trans_func import data_layer_not_check  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.variable_trans_func import to_static_variable  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.variable_trans_func import to_static_variable_gast_node  #DEFINE_ALIAS

This PR fixed two bugs when converting LSTM in dy2stat:

is_unsupported has a condition can trigger Python syntax error
LSTM API's implementation in _rnn_static_graph doesn't include parameter initialization, which can cause dy2stat error.

We decreased the batch size on CPU so that it can run correctly on Win/Mac machine, this may cause the delta to be larger. So I set larger delta value.

* rename StaticLayer

* rename

* default open dygraph mode

* fix CI-Mac

* fix Mac-CI other unittest file

* fix CI-Py3

* fix test_communicator_geo and test_buffer_shared_memory_reuse_pass

* add enable_static to fix CI-Py3

* add enable_static to fix CI-coverage

* delete try except

* refine error mesg

* 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

* fix calcu_gradients

* fix code place

* fix embedding interface usage

* support to_static(model)

* add warning and unittest

* Add naming rule if not specific InputSpec.name

* fix function name typo

* refine comment

* remove print statement

* add descriptor cache

* fix self arugments

* deal case if instance is None

* clean code

* fix usage

Raise RuntimeError if run the callable object decorated by '@paddle.jit.to_static' not in dynamic mode.  (#26750)

[Dy2Stat-debugging] Fix bug: Returns True if the verbosity level set by the user is greater than or equal to the log level (#26858)