* remove _in_eager_mode_

* remove _in_eager_mode_

* relocate regularizer.py

* fix bug

* fix bug

* fix bug

* relocate the import

* replace _regularization_coeff with coeff

* remove the L1DecayRegularizer and L2DecayRegularizer

Co-authored-by: Nxiongkun <xiongkun03@baidu.com>

* autofix
Co-authored-by: NLiyulingyue <83450930+Liyulingyue@users.noreply.github.com>

* revert changes in python/paddle/distributed/fleet/utils/hybrid_parallel_util.py

* empty commit, trigger ci

* fix test_slice

---------
Co-authored-by: NSigureMo <sigure.qaq@gmail.com>

* delete old dygraph op test

[CodeStyle][C408][C409][C410] Fix unnecessary <dict/list/tuple> call and unnecessary <list/tuple> passed to <list/tupule>() (#51928)

* autofix

* add select config

* autofix C410

* add C410 select

[Zero-Dim] Support 0D for numel/rank/size/optimizer/create_parameter/create_global_var, fix some usage to adapt 0D (#51566)

* refine _found_inf

* Revert "fixoptminizer _set_auxiliary_var bug (#50335)"

This reverts commit c44005f0.

* Revert "refine optimizer create accumulators (#50188)"

This reverts commit 244e7546.

* Revert "fix found_inf bug for custom optimizer (#50158)"

This reverts commit 64573f9f.

* Revert "refine amp scaler found_inf (#49864)"

This reverts commit 382e9a06.

* fix code format

* fix conflict

* refine optimizer create accumulators

* refine

remove fluid.initializer.UniformInitializer, ConstantInitializer, NormalInitializer, TruncatedNormalInitializer, XavierInitializer, BilinearInitializer, MSRAInitializer, NumpyArrayInitializer and calculate_gain.. (#49498)

* move UniformInitializer and ConstantInitializer

* more modify

* circular import resolved

* another circular import resolved?

* more circular import 2

* circular import 3

* change import paddle in metric.py

* BuildStrategy import from fluid

* modify the framework import path in common.py

* change rnn.py import, from static to original framework

* change import static in the nn folder

* default_main_program should import from common_ops_import

* add import paddle in param_attr.py

* use core not paddle module for using VarDesc

* another old uniform

* mistake that use Uniform instead of UniformInitializer

* modify UniformInitializer doc

* move fluid.NormalInitializer to nn.initializer.NormalInitializer

* remove import of Normal in fluid.layers.nn.py

* remove more import of old Normal

* remove more import of old Normal

* sample code modify and tests modify import

* is_listen_failed passing arg should be log file

* problem solved

* a mistake solved

* comments resoleved and remove paddle.fluid.initializer.TruncatedNormalInitializer

* remove paddle.fluid.initializer.XavierInitializer and paddle.fluid.initializer.MSRAInitializer

* remove paddle.fluid.initializer.BilinearInitializer NumpyArrayInitializer and set_global_initializer

* change fluid to static

* change static to fluid to avoid circular import in distributed_strategy.py

* fix example code and test_initializer

* ValueType

* sample code fix

* change set_global_initializer back to fluid

* put paddle.static.BuildStrategy.ReduceStrategy into the fuction to avoid circular import

* remove calculate_gain, delete BilinearInitializer and revert set_global_initializer

* change the time of using UniformInitializer, ConstantInitializer, NormalInitializer, TruncatedNormalInitializer, XavierInitializer, MSRAInitializer, NumpyArrayInitializer as few as possible

* fix argument incampatible

* fix more arg incompatible

* fix test_prelu_op_xpu.py Constant

* fix inaccurate doc

* more doc fix: default value

* refine _found_inf

* 1219

* temporarily change the num_diff_files limit, test=document_fix

* Revert "temporarily change the num_diff_files limit, test=document_fix"

This reverts commit 8e70f00ef468d2dad0e38b3da06295ed62990d20.

* for codestyle

* remove duplicate license

* `static mode` -> `static graph mode`

* Update hybrid_parallel_inference.py

* Update layer_function_generator.py

* Update manipulation.py

* reset
Co-authored-by: NLigoml <39876205+Ligoml@users.noreply.github.com>
Co-authored-by: NSigureMo <sigure.qaq@gmail.com>

* isort all files

* revert conflicting files

* revert conflicting files

* revert conflicting files

Support bfloat16 for adamw and adam optimizer. Fit the lr for pure bf16 training with tensor fusion. (#48041)

* add bfloat16 for adamw

* set lr not to bfloat16 for pure bf16 training

* update the logic

* update the adamw optimizer

* support bfloat for adam

* Get params and grads in cpp to avoid gpu idel time

* Using python param instead of cpp return param to fix test_asp_optimize_dynamic.py

* Get grads from cpp and construct params_grads on python

* Check meta and remove comments

* [CodeStyle][py2][U004] unecessary explicit `object` inheritance in class definition

* fix an increment

* Remove reduntant numpy input in Example code

* Remove reduntant numpy input in Example code, test=document_fix

* [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

* Update README.md

* Update README.md

* Fix F541 by converting f-string to normal strings

[CodeStyle][F401] remove unused imports in python_paddle/proto_onnx_optimizer_hapi_autograd_framework. (#46754)

* [CodeStyle] remove all future import

* revert test_error.py

* restore future import in example code

* move sum

* fix ci bugs

* fix ci bugs

* fix set_lod bugs

* fix infershape bugs

* fix ci bugs

* fix ci unittest bug

* fix ci bugs

* perfect code

* update code according comment

* add unittest

* fix ci bugs

* trim trailing whitespace

* fix `.cmake-format.py`

* revert npu ut changes, avoid npu ci error

* [Eager] use final_state_fill_constant_

* fill_constant use str_value

* add fill_constant_ to no_amp_list

* use float(value) as input

* support final state full_ same as fill_constant

* [Eager] use final_state_full / *full_ instead fill_constant under eager

* polish code

* fix mistakes

Set the lr var's dtype to fp32 when create a fp16 lr var in optimizer if user not mean to use global fp16. (#44840)