* update doc

* update doc

* fix optimizer sample code

* add default value for adamw weight_decay

* fix adamw

* change LearningRateDecay to _LRScheduler

* fix adamw;notest

* fix load;notest

* remove file

* bug fix

* fix code style

* bug fix

* add ut

* adamw support weight_decay=0

* fix ut

* fix set_lr doc

* fix doc

* change parameters place

* add doc; notest

* fix doc; notest

* update doc; notest

* refine optimizer && adam

* refine optimizer; notest

* add adam

* fix doc

* fix doc && add adamw; notest

* add error message

* bug fix

* refine rmsprop && adamax

* fix ci

* buf fix

* update comment

* unify arguments place; notest

* fix ut, test=develop

* bug fix

* fix conflicts, test=develop

* add examples code

* bug fix

* fix comments

* fix sample code

* add sample code for Optimizer

* add adamax ut, test=develop

* fix rmsprop ut, test=develop

* add ut for optimizer.py and adamw.py

* first commit of adadelta optimizer

* fix learning rate

* fix adadelta doc and add sgd momentum

* remove unused fluid

* fix codestyle

* Update test_adam_op.py

* Update test_adam_op.py

* fix SGD in 2 unittests

* fix SGD in 2 unittests

* fix ci

* fix ut
Co-authored-by: NMRXLT <xlt2024@gmail.com>
Co-authored-by: Nmapingshuo <mps2012@yeah.net>

* refine manual seed

* fix ci problem

* fix unittests

* fix unittest

* set is_init_py=false in manual_seed

* fix unittest

* fix bernoulli_op

* fix(unittest): change random_seed to manual_seed

* 🐞fix(unittest): fix manual_seed

* trigger ci

* fix test_sentiment

* fix test_imperative_save_load

* fix test_uniform_random_op

* fix test_uniform_random_op

* fix test_jit_save_load

* merge develop

* fix manual_seed

* fix manual_seed

* use global engine

* use shared_ptr

* fix double free

* fix bug

* fix bug

* fix bug

* fix test bug

* fix test bug

* fix test bug

* fix ci

* support 2.0 lr_scheduler for 2.0 optimizer

* fix unittest

* fix doc

* fix unittest

* fix sample code, fix unittest

refine Optimizer/Adam/Admax/RMSProp && add Admw

* buf fix

* update comment

* unify arguments place; notest

* fix ut, test=develop

* bug fix

* fix conflicts, test=develop

* add examples code

* bug fix

* fix comments

* fix sample code

* add sample code for Optimizer

* add adamax ut, test=develop

* fix rmsprop ut, test=develop

* add ut for optimizer.py and adamw.py

* remove TestAdamOptimizerBetaVariable

* update api && add ut

* update doc && fix ut

* add ut
Co-authored-by: Nmapingshuo <mps2012@yeah.net>

* fix optimizer parameter is a iterator; test=develop

* fix parameter list None bug; test=develop

* use is not None; test=develop

* change list to iterable; test=develop

* add new api: optimizer.set_lr, test=develop

* add API doc and example code for optimizer.set_lr,test=develop

* add API doc and example code for optimizer.set_lr,test=develop

* Modified doc to :api_attr: imperative,test=develop

* Linear use mul op
test=develop

* fix unittest
test=develop

* add learning rate api; test=develop

* fix uni test converage; test=develop

* fix travis ci error; test=develop

* fix comment; test=develop

* fix example error; test=develop

* polish the api description, test=develop
Co-authored-by: Nzhongpu <2013000149@qq.com>

* test Optimizer in dygraph, test=develop

* add optest for Optimizer in dygraph, test=develop

* fix adagrad optimizer, test=develop

* fix dpsgd optimizer, test=develop

* fix test_optimizer.py, test=develop

* fix dpsgd optimizer, this op only support cpu, test=develop

* add optest for optimizer, test=develop

* add description for dpsgd, test=develop

* add rmsprop to white_list in unused_var_check.cc, test=develop

* polish code style, test=develop

* polish code style, test=develop

* delete seed attribute for DpsgdOptimizer, test=develop

* change testing to debugging, test=develop

* remove params in Tracer object, test=develop

* Repair failed optest, test=develop

* remove build_once & name_scope (Conv2D)
test=develop

* fix unittest
test=develop

* Conv2DTranspose

* Conv3D & Conv3DTranspose
test=develop

* Pool2D & BatchNorm

* Embedding

* LayerNorm

* GRUUnit & NCE

* PRelu

* BilinearTensorProduct

* GroupNorm & SpectralNorm

* TreeConv
test=develop

* fix LayerNorm in transformer unnittest
test=develop

* disable LayerNorm or BatchNorm in multicard
test=develop

* refine Layer.create_parameter api
test=develop

* refine LayerNorm, remove begin_norm_axis param, add normed shape check
test=develop

* LayerNorm bug fix
test=develop

* fix optest,test=develop

* fix optest, test=develop

* fix optest for pass parameter_list when constructing an Optimizer class instance, test=develop

* polish code for better code style, test=develop

* fix se_resnext optest, test=develop

* polish code for better code style, test=develop
Co-authored-by: Nsongyouwei <youwei0314@gmail.com>

* test=develop, fix docker with paddle nccl problem

* don't expose numerous Tensor.set(), test=develop

* fix condition, test=develop

* fix float16 bug, test=develop

* feed should be Tensor or np.array, not Variable or number, test=develop

* use forcecast to copy numpy slice to new array, test=develop

* remove float16-uint16 hacking, test=develop

* add variable method to varbase and refactor to_variable to support return varbase

* support kwargs in varbase constructor

* add VarBase constructor to support default python args

* refine varbase initial method

* reset branch

* fix ut for change VarBase error info to PaddleEnforce

* cherry is parameter change before

* overload isinstance to replace too many change of is_variable

* rm useless files

* rm useless code merged by git

* test=develop, fix some ut failed error

* test=develop, fix test_graph_wrapper

* add some tests, test=develop

* refine __getitem__, test=develop

* add tests, test=develop

* fix err_msg, test=develop

* use pyreader to read data

* add return_list to PyReader to support return value represented as list

test=develop

test=develop

* test=develop, reconstruct layer helper to fit imperative usage

* test=develop, fix import error on py35

* test=develop, fix rnn gradient error

* test=develop, delete test use code

* test=develop, remove helper from imperative usage

* test=develop, fix test_base_layer using new helper

* test=develop, reconstruct layerhelper for imperative mode

* test=develop, reconstruct layerhelper for imperative mode

* test=develop, fix bug

* test=develop, fix test failed bug

* test=develop, fix test failed bug

* test=develop, fix test failed bug

* test=develop, fix bug

* test=develop, polish code

* test=develop, reconstruct layer helper to fit imperative usage

* test=develop, fix import error on py35

* test=develop, fix rnn gradient error

* test=develop, delete test use code

* test=develop, remove helper from imperative usage

* test=develop, fix test_base_layer using new helper

* test=develop, reconstruct layerhelper for imperative mode

* test=develop, reconstruct layerhelper for imperative mode

* test=develop, fix bug

* test=develop, fix test failed bug

* test=develop, fix test failed bug

* test=develop, fix test failed bug

* test=develop, fix bug

* test=develop, polish code

test=develop

test=develop

test=develop

test=develop

test=develop

test=develop

test=develop

parameters within a Layer instance should be unique.

test=develop

test=develop

test=develop

test=develop