* fix merged_momentum regular bug

* fix bug

* add multi_tensor for momentum and clear_grads for optimizer

* fix bug for dygraph

* add unittest

* refine comment

* add param_group

* refine regularizaiton logic

* del clear_grads

* add clear_grads

* add dispensable check of None

* refine clear_grad

* fix build bug

* refine code by comment

* refine code

* add multi tensor check

* refine param_group update

* add multi tensor for static mode

* refine comments

* delete useless comma for momentum

* refine comment for momentum

* refine code by commment

* support multi precision update for LAMB

* hide some api

* fix ci uts

* fix lamb output of dygraph

* remove some changes to some PR

* try to fix Py3 CI compile error

* fix test_imperative_optimizer, add lars ut, add layer_norm ut

* fix ut, fix format

* fix ut

* fix windows ci

[XPU AMP] 1. xpu support gradient acc 2. xpu support create tensor in dygraph 3. xpu support update weight params in amp (#36439)

* update func name

* skip cpu

* update unittest

* update unittest

* adam to adamw in AdamW

* add lr_ratio in adamw

* refine logic bug in cpu adamw

* delete fix bug for cpu adamw

* delete fix bug for cpu adamw

* 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

* add layerwise learning rate for adamw

* fix format

* add unitest

* add NotImplementedError

* add gpu unitest

* update gpuplace

* fix warning error , test=document_fix

* fix warning error , test=document_fix

* fix warning error , test=document_fix

* fix warning error , test=document_fix

* fix warning error , test=document_fix

* fix warning error , test=document_fix

* fix warning error , test=document_fix

* adamw support cuda

* adamw support cuda

* fix paddle.optimizer test=document_fix

* fix paddle.optimizer test=document_fix

* fix lr in param group

* add unittest for adamw

* cache core.ops, test=develop

* refine, test=develop

* exclude lr scheduler's state from accumulators_holder

* fix when there is no learning rate scheduler

* make a copy of the loaded state dict to avoid modifying it

* opt dygraph python API, test=develop

* Fix unbind bug in manipulation.py

This reverts commit b2afc8df.

* fix Undefined variables

* fix Undefined variables

* fuse L2Decay and momentum when param.regularizer is set

* add unittest

* refine

* refine _create_regularization_of_grad of momentum

* improve append_optimizer_op

* support params groups, test=develop

* simplify updating opt attr

* update according to review

add __all__=[] to python files not in API public list; import * only support in API public list files (#32643)

* add input EpsilonTensor for adam

* update python api

* add unit test

* add npu test

* add more ut

* fixed docs.

* Fixed docs. test=document_fix

code bak.

fixed docs. test=document_fix

* Revert to previous version of python/paddle/fluid/backward.py

* fixed bugs.

* test=document_fix. Fixed examples.

* add support for optimizer with varbase input

* refine cond

* fix failed unittest

* add test for coverage

* Use correct master weights in AdamW.

* Just modify the master weight.

* Update for CI Coverage.

* Modify the calculation logic of LambOptimizer