* [CodeStyle][E711] use `is`/`is not` for comparison with `None`

* `self.assertTrue($A is None)` -> `self.assertIsNone($A)`

* `self.assertTrue($A is not None)` -> `self.assertIsNotNone($A)`

* `self.assertFalse($A is None)` -> `self.assertIsNotNone($A)`

* `self.assertEqual($A, None)` -> `self.assertIsNone($A)`

* `self.assertNotEqual($A, None)` -> `self.assertIsNotNone($A)`

* update config

* re-blacken python code

* temporarily disable date and diff_py_file

* skip a format

* add numpy api err msg

* fix bug

* fix unittest

* add set_state_dict err

* rewrite numpy_api_check

* add define

* change err msg

* fix test

* move import statement

* trim trailing whitespace

* fix `.cmake-format.py`

* revert npu ut changes, avoid npu ci error

* fix

* add control flag and input shapes for new dygraph

* fix file mode

* improve code coverage

* fix a bug in statstic

* fix according to review

* optimize performance

* fix

* add name attribute to code-block, test=document_fix

* remove redundant labels, test=document_fix

* remove redundant labels (from upstream), test=document_fix

* more COPY-FROM (try multiple code example), test=document_fix

* empty commit, try to trigger PR-CI-build

* fix some `Examples:` format issues

* fix some ci errors

* refine layer to

* refine code

* add ut

* set_state_dict not use state_dict hook

* add ut

* refine doc

* [Dy2stat]Add RollBack into original dygraph function for @to_static

* fix unittest

* use yapf to format all python file

* yapf exclude two unittests file for they rely on writing and reading file, and format will break them

* disable diff_py_file because too many diff files cause command following failed

* optimize performance

* fix

* improve coverage

* fix

* fix

* make fast through to linear

* make fast through to linear

* add to do for later upgrades

* support build once for now

* full api fix

* when out is None, go old dygraph mode

* fix

* add name for buffer

* fix by code review

* fix

* by static check

* dlpack eager, test=develop

* eager test_base_layer, test=develop

* fix error report, test=develop

* eager _getitem_from_offset, test=develop

* refine, test=develop

* refine offset, test=develop

* add test_inner test_outer, test=develop

* refine, test=develop

* refine, test=develop

* refactor eager flags

* fix flags error when we switch from eager to dygraph

* fix ci problem

* fix ci

* fix ci

* merge develop and fix code style

* merge develop and fix code style

* fix op test error

* fix op test error

* fix op test error

* fix op test error

* fix op test error

* merge develop

* add event record for model profiling

* fix format

* fix format

* fix code example bug

* no

* add profiler statistic

* add profiler feature

* fix bug

* fix bug

* fix bug

* fix bug

* required: gpu

* required: gpu

* fix bug

* required: gpu

* fix ci bug

* fix ci error

* fix ci error

* upgrade document

* fix doc

* fix ci bug

* add doc and fix bug

* nothing

* fix bug

* fix format bug

* modify format

* add deprecated description for old profiler

* fix bug

* fix bug

* fix

* add load_profiler_reuslt doc

* add load_profiler_reuslt doc

* add load_profiler_reuslt doc

* help fix old profiler sample code

* add api doc

* fix format

* fix api doc

* fix api doc format

* fix api doc format

* fix api doc c format

* fix api doc format

* Refine to_tensor for eager mode

* support gpu_pinned

* refine code

* support gpu_pinned copy_to

* fix layer.__setattr__

* support to_tensor for gpu_pinned

* fix unit test

* refine gpu_pinned

* restore the original code

* add is_gup_pinned() and refine eager.Tensor._copy_to()

* for test_mnist.py

* remove comments

* using type() replace isinstance()

* valid vars for run program OP in io.py

* open test_mnist in eager_gurad for coverage

* Update comment

* [Eager] Support test_imperative_hook_for_layer with _test_eager_guard()

* Polish code name style

* Fix a error name

* Polish code, make it clear and simple

* check amp.decorate and DataParallel

* refine coverage

* fix layer dtype

* refine code

* fix error when set buffer in forward

* add unittest

* refine class name

* refine not framework.in_dygraph_mode() in if

* fix UT error

* add comment

* refine code

* remove useless import

* fix bug of dp in pfp16

* fix topo

* fix bug

* refine code

* refine code

* refine code

* fix error when calling sublayer's non-forward func in dy2stat

* fix circular import using an inelegant way

* deal with parameters

* remove param_guard in __call__

* remove comment

* fix error when jit.load

* rename block var

* remove wrong code

* add unit test

* layer.to api support numpy.dtype and paddle.dtype

* skip the layer to eaxmple code executing for env not support

* optimize dygraph probl

* refine code

* fix convert dtype error

* fix import datafeeder error

* optimizer __call__ to make dygraph faster

* fix return type

* remove cpp Layer

* optimizer __call__ to make dygraph faster

* fix return type

* refine layer to

* delete comment

* refine logic

* refine code

* refine pure_fp16_init

* refine comment

* 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