* add master gradients on static graph

* add unit test for bf16 master grad static graph

* use float16 as v100 test dtype

* only skip GPU which do not support bf16

* use linear layer to test master grad

* 1.push master grad creation before all optimizer ops; 2.remove useless unittest; 3.use a function to create master grad states

* 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

* updata Adamw.py

out.backward()  -> loss.backward()

* Update adamw.py

* modify numel in lbfgs and add a new test case. test=develop

* change param 'lr' to 'learning_rate' in lbfgs and its test

* add opt LBFGS and change test

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

* Fix some typos.
Signed-off-by: Yulv-git <yulvchi@qq.com>

* pre-commit
Signed-off-by: Yulv-git <yulvchi@qq.com>

---------
Signed-off-by: Yulv-git <yulvchi@qq.com>

* 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

* fix div 0 error of NoamDecay

* add unittest

* Update lr.py

* refine _found_inf