* Layer.to reutrn self

* add device required

* remove additional warnning in layer.to

* remove additional warnning in layer.to

* remove additional warnning in layer.to

* remove additional warnning in layer.to

* remove additional warnning in layer.to

Add Tokenizer related functionalities for Transformer model in order that the process of training and predicting is consistent.

* support the text string as an input Tensor
* support the "VOCAB"unordered_map<wstring, int> as an input Tensor to lookup tokens
* Tokenizer used for BERT. This tokenizer applies an end-to-end, text string to wordpiece tokenization.
* It first applies basic tokenization, followed by wordpiece tokenization.

* add attr is_distributed

* refine code

* refine black/white list for pure fp16

* add pure fp16 major function in auto_cast & tracer

* support master weight in dygraph for pure fp16

* check mix dtype of fp16&fp32 for check_finite_and_unscale op

* change pure fp16 funtion name

* refine some bug in auto_cast

* refine auto_cast interface logic

* add param _casted_by_pure_fp16 for class Layer

* support state_dict hook for save model by user appointed dtype in pure_fp16_decorator

* refine pure_fp16_decorator as decorator

* add unittest

* add comment

* add comment

* support recompute

* add comment for auto_cast and decorator

* support to_static_state_dict for paddle.jit.save

* unlimite models num and optimizers num

* add lookup_table in black_list

* fix momentum and layer state_dict

* fix bug in layer state_dict

* fix bug in layer state_dict_helper

* refine unittest

* refine test_momentun_op

* refine interface and some code

* refine amp_decorator interface

* refine pure fp16 interface

* refine master weight interface

* Support append customize attributes into op_desc in nn.Layer

* fix code style

* support override

* add unittest

* Add param_guard in ParameterList to support @to_static

* Refactor param_guard of @to_static

* fix unittest failed

* add more unittest

* add varbasecopy func to fix the paraBase type bug in layers.to API

* overload _copy_to func for ParamBase

* add xpuplace

* add waiting varbsecopy completion when not blocking

* fix dst_device bug

* modify varbase to shared_ptr

* fix sublayer error with include_sublayers=False

* add ut

* refactor include_sublayers related api

* fix ut

* fix ut of transformer

* fix ut of transformer

* remove useless code

* change sublayer api

* polish code

* add test for include_self=True

* add layer.to api

* add layer.to api

* add layer.to api

* add the doc for Layer.to

* add input type checking

* modify assert and import bug

* format code style

* format code style

* make place support str type

* add SetGradVarBase method to set the gradient after conversion

* modify argument palce to device

* modify argument palce to device

* modify doc of layers.to API

* add xpuplace to device argument

* support save/load single tensor

* compatibility modification according to unnittest

* Some python2.7 don't have 'copyreg' modules

* Handle a syntax error.

* Dealing with compatibility problems on Mac.

* Dealing with compatibility problems on Mac.

* edit unittest to improve coverage.

* Modify the code according to the review comments

* Reduce redundant code.

* support for static graph loading dygraph state_dict

* edit code according to CI

* edit unittest

* edit unnittest

* delete redundant file

* edit code according to Comments

* edit english doc

* edit english doc

* edit English DOC.

* get/set_tensor->get/set_value; return_numpy=False

* get/set_tensor->get/set_value; return_numpy=False

* edit unnittest

* edit unnittest

* polish code.

* support control flow

* supoort sync_parameters_buffers

* fix the bug of sparse embedding

* delete empty line of pybing.cc, test=develop

* fix layers train eval bug, test=develop

* Polish and Optimize the print/repr message of all layer

* fix some code format

fix the state_dict bug for the xpu

* support deepcopy for Layer/Tensor/Paramerbase

* fix some code

This PR fixes several problems in dy2stat for Deoldify model in PaddleGan.

In model, software engineer wrote if x.shape == y.shape, the Tenser shape is a tuple in dygraph so the == returns True/False, but in static graph the == becomes element-wise comparison, which is a different behavior. In this PR we reduce the element-wise comparison result.

If software engineer write computations which uses parameters in hooks, the static graph can loss the parameter variable because we put param_guard at forward of a Layer. In this PR we made param_guard cover pre-hook and post-hook.

In PaddleGan, software engineer calculated some parameter values in __init__ by running some dygraph code. Those code also run during dy2stat. So some variables may be assign as a VarBase (Tensor) first and then Variable, which raised an error. We fixed the bug in this PR by handling the case.

TODO: We just added testcase for the 1. shape comparison. Should add test case for 2. and 3. But since we are chasing 2.0RC, I will do it in the near future PR

* fix eng doc, test=develop

* add import deprecated for layers, test=develop

* add block line for doc generate, test=develop

* remove todo for create_variable, test=develop

* add blank line for doc generate, test=develop

* add blank line for doc generate, test=develop

* [Dy2stat] Support to modify value of buffer tensor

* remove "defaultTest"

* fix name confliction

* 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

* 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

* 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

* refine error mesg

* update set_dict method name & add aliases

* fix var name error

* fix alias formats

* use set_state_dict in unittest

* add decorator solve compatible problem

* polish decorator

* replace layer set_state_dict by patched method

* remove import monkey path layer

* fix import function error

* add unittest for coverage

* enhance add parameter check for layer

* add unittest for coverage

* remove uninit test case

* enrich unittest ccase

* trigger ci check

* add set/get default dtype

* add children and named_children

* 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

* add apply for Layer

* 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

* 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 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

* test=develop, test=document_fix

* test=develop, test=document_fix
Co-authored-by: Nswtkiwi <1208425345@qq.com>

* 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

* Layer add training attr, add Dropout Layer

* add unit test for Dropout
test=develop

* minor fix
test=develop

* add missing args
test=develop

* support global flag in dropout, add docs
test=develop

* minor fix
test=develop

* minor fix
test=develop

* refine code comments
test=develop

* refine Dropout
test=develop

* fix ut
test=develop

* arg expansion
test=develop

* sample code update
test=develop

* prop -> p
test=develop

* fix ut
test=develop

* minor check fix
test=develop

* support forward hook for dygraph, test=develop

* add optest for forward_hook in dygraph, test=develop

* add optest, test=develop

* polish code, test=develop

* add sample code, test=develop

* rename forwrd_hook to forward_post_hook, test=develop

* fix the api description, test=develop

* fix api description, test=develop

* support reset param with None value

* add unittest
test=develop

* update unittest
test=develop