* 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

* add sumary feature

* refine printting tensor

* add sci_mode

* add sample code

* fix indent error

* fix _format_item

* polish code

* support item indent

* add ut

* set place for ut

* fix py2 issue

* fix ut

As the title

* polish save load en doc details, test=document_fix

* polish details, test=document_fix

* remove blank, test=document_fix

* fix ascii error, test=document_fix

* update fc's input to x, test=document_fix

* update fc argument activation, test=document_fix

* fix doc and unittest of 2.0 lr_scheduler

* fix doc of 2.0 lr_scheduler

* fix unittest

* fix english doc of lr_scheduler

* fix api name of lr scheduler

* fix api name of lr scheduler

* 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

Polish the english documentation and example of paddle.nn.Linear and paddle.nn.functional.linear (#27759)

* modify doc for ParameterList and LayerList, test=develop

* add empty line after code-block, test=develop

* modify doc for Layer, test=develop

* modify doc for Layer2, test=develop

* set dtype default value to float32, test=develop

* add example code for paddle.nn.Layer, test=develop

* set create_parameter and create_variable dtype default value to None, test=develop

* modify some example code, tet=develop

* refine, test=develop

* del no ues code, test=develop

* modify doc, example code, args, test=develop

* modify doc, test=develop

* remove data parallel scale loss & apply collective_grads

* move apply in minimize

* fix failed unittests

* polish Program api doc & example

* polish CompiledProgram api doc & example

* polish ParallelEnv api doc & examples

* polish details, test=document_fix

* polish program doc details, test=document_fix

* polish details, test=document_fix

* fix note format error, test=document_fix

* add lost example, test=document_fix

* fix lost example, test=document_fix

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.

* remove inplace argument

* fix sample code

* fix sample code

* rename StaticLayer

* rename

* init commit of new save/load

* fix failed unittests

* fix save_load_v2 unittest failed

* fix failed unittest & polish doc

* add tests for coverage

* add more tests & move static apis

* fix example code error

* polish emample code

* fix detail example code problem

* Makes the Bind Method more intelligent

* Makes the Bind Method more intelligent

* fix unittest

* fix unittest

* fix conflict

* 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

Change ProgramTranslator.enable_declarative to ProgramTranslator.enable_to_static to meet API 2.0

* remove objgraph

* remove graphviz

* fix ut

* support load state_dict from save_params/persistables

* remove failed unittest

* add load eof check & unittest

* remove eof check

* add input_spec & output_spec for translated_layer

* update error message

Update amp_check_finite_and_scale_op and add an updating_loss_scaling op for static graph amp training. (#26240)

* update amp_check_finite_and_scale_op for static_amp.

* use amp_check_finite_and_scale in static graph amp.

* update grads to zero when grads own infinite values(as for amp_checkout_finite_and_scale op).

* add update_loss_scaling op in cpp.

* add update_loss_scaling_op unit test.

* update the doc of the check_finite_and_unscale op

* Update the process of gradients updating skipping if the gradients have infinite values.

* update the way to zero grads.

* update test_update_loss_scaling_op.py

* add log info when find infinite grads.

* add the unit test for UpdateLossScaling Layer.

* temporally disable zero_copy

* add test

* follow comments

* support to_static(model)

* add warning and unittest

* add some unittest cases ot verify jit.save, no_test

* add more unittests

* add test with example inputs

* polish implement details

* remove useless blank

* fix fetch random error