* move fluid apis

* fix type error

* remove static exponential_decay

* fix some import error

* remove nn.py

* fix some error

* fix type error

remove the AdamOptimizer、SGDOptimizer、MomentumOptimizer、ModelAverage、LookaheadOptimizer、FtrlOptimizer、DecayedAdagradOptimizer、DpsgdOptimizer in fluid and relocate the ExponentialMovingAverage、PipelineOptimizer、GradientMergeOptimizer and change optimizer base for LarsMomentumOptimizer and RecomputeOptimizer (#55970)

* change the optimizer base for SGDOptimizer

* change the optimizer base for SGDOptimizer

* replace the SGDOptimizer with SGD

* fix bug of sgd

* change the optimizer base for MomentumOptimizer

* fix the remaining tests

* remove the Momentum in fluid/optimizer.py

* fix bug

* fix bug

* fix bug

* fix bug

* Update test_resnet_cinn.py

* Update test_resnet_prim_cinn.py

* fix bug

* fix bug

* fix bug

* remove the ModelAverage in fluid

* remove the LookaheadOptimizer in fluid

* fix bug

* remove AdamOptimizer in fluid

* Update test_image_classification_fp16.py

* fix bug

* relocate the ExponentialMovingAverage in fluid

* restore the static api

* remove the FtrlOptimizer in fluid

* remove the DecayedAdagradOptimizer in fluid

* remove the DpsgdOptimizer in fluid

* fix bug

* fix codestyle

* fix bug

* fix bug

* relocate the PipelineOptimizer

* relocate the GradientMergeOptimizer

* fix bug

* fix bug

* fix bug

* fix doc

* Update __init__.py

* Update test_fleet_qat_meta_optimizer.py

* change optimizer base for LarsMomentumOptimizer

* fix bug

* fix conflict

* fix code-style

* fix sample codes

* fix bug

* fix bug

* fix cinn bug

* fix bug

* fix bug

* Update qat_optimizer.py

* Update __init__.py

* fix bug

* change optimizer base for RecomputeOptimizer

* fix bug

* fix bug

* Update test_imperative_optimizer_v2.py

replace the PolynomialDecay、NoamDecay、LinearLrWarmup、ReduceLROnPlateau in fluid with 2.0 version (#54806)

* remove the ReduceLROnPlateau in fluid

* fix bug

* remove the PolynomialDecay in fluid

* remove the LinearLrWarmup in fluid

* fix bug

* remove the NoamDecay in fluid

* fix bug

* fix bug

* fix bug

* replace PiecewiseDecay(LearningRateDecay) with PiecewiseDecay(LRScheduler)

* fix bug

* fix bug

* replace the StepDecay,MultiStepDecay,LambdaDecay with 2.0 version

* remove the NaturalExpDecay in fluid

* fix bug

* remove the ExponentialDecay in fluid

* remove the InverseTimeDecay in fluid

* remove the InverseTimeDecay class

* fix bug

* mv all unittests test

* fix error

* fix error

* fix

* fix

* del unittests

* fix paddle_build.sh

* fix

* fix test

* fix add test

* fix

* fix

* fix

* merge develop

* fix

* fix

* fix

* fix

* fix

* merge develop

* fix test_async_read_write

* fix test_async_read_write

* merge develop

* fix

* fix import legacy_test

* fix

* fix

* fix

* fix

* fix

* fix

* fix

* fix

* fix bug

* fix

* fix coverage test bug

* fix

* fix

* fix

* fix

* fix

* fix code sstyle

* fix code

* fix code

* fix

* fix

* fix

* del test_sequence_enumerate_op.py

* fix

* 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>

* remove fluid.save_dygraph and fluid.load_dygraph use paddle.save and paddle.load instead

* move Sequential to paddle.nn

* modify convert_call_func.py Sequential reference

* remove related unitests

* remove fluid.dynamic.Sequntial

* test remove conver_call_func

* fix conflicts

* fix typro

* fix unitests

* fix sample_code

* fix unitest

* fix __init__

* [remove fluid] under unittesets

* [remove fluid] under unittesets

* [remove fluid] under unittesets

* [remove fluid] under unittesets

* [remove fluid] under unittesets

* [remove fluid] under unittesets

* [remove fluid] under unittesets

* [remove fluid] under unittesets

* [remove fluid] under unittesets

* [remove fluid] under unittesets

* [remove fluid] under unittesets

* [remove fluid] under unittesets

* [remove fluid] under unittesets

* [remove fluid] under unittesets

* [remove fluid] under unittesets

* [remove fluid] under unittesets

* update config

* re-blacken python code

* temporarily disable date and diff_py_file

* skip a format

* [CodeStyle] remove all future import

* revert test_error.py

* restore future import in example code

[CodeStyle][NPU] use np.testing.assert_allclose instead of self.assertTrue(np.allclose(...)) (part 1) (#44988)

* autofix

* try resolve precision issues

* revert some changes

* clean some `err_msg`

* 0.0001 -> 1e-4

* update commented assert code

* try to fix some shape errors

* `numpy` -> `np`

* empty commit, trigger kunlun ci, test=kunlun

* empty commit, retrigger kunlun ci, test=kunlun

* empty commit, trigger kunlun ci, try fix npu memcpy_h2d, test=kunlun

* try fix npu import error, test=kunlun

* 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

* support 2.0 lr_scheduler for 2.0 optimizer

* fix unittest

* fix doc

* fix unittest

* fix sample code, fix unittest

* Reconstruct all API related to lr scheduler, unify dygraph and static

* Reconstruct all API related to lr scheduler, unify dygraph and static

* fix doc

* fix doc

* fix doc of lr_scheduler

* fix unittest and english doc

* fix english doc

* fix confilt

* fix doc

* fix optimizer.state_dict and LRScheduler.state_dict to save/load dygraph,test=develop

* fix optimizer.state_dict and LRScheduler.state_dict to save/load dygraph,test=develop

* Add a judgment that state_dict/set_dict is used incorrectly,test=develop

* fix some doc error,test=develop

* fix current_step_lr for _LearningRateEpochDecay,test=develop

* remove some unsed code to improve coverage,test=develop

* remove some unsed code to improve coverage,test=develop

add new API:LambdaDecay

* add new API: MultiStepDecay, a new learing rate strategy, test=develop

* add new API: MultiStepDecay, a new learing rate strategy,test=develop

* add new API: MultiStepDecay, a new learing rate strategy,test=develop

* add base class of LearningRateEpochDecay, and MultiStepDecay, and StepDecay, test=develop

* fix doc to add coverage,test=develop

添加loss自适应的学习率衰减策略。

* support if logic for Variable in dygraph, test=develop

* fix test_learning_rate_scheduler.py, test=develop

* fix optest, test=develop

* fix error message, test=develop

* fix optest,test=develop

* fix comment, test=develop

* Add parameter(learning_rate) in NoamDecay test=develop

* dygraph mode support linear lr warm up; test=develop

* add unitest for linear warmup; test=develop

* add input type check; test=develop

* fix type check assert error; test=develop

* change type error; test=develop

* deprecate python memory optimize, test=develop

* remove memory_optimize in unittests, test=develop

* add unittests to deprecated interfaces, test=develop

* make it support float/int learning as input.

* Add linear learning warmup method

This warmup lr can be combinated with other learning rate strategies.
For example:
            decayed_lr = fluid.layers.linear_lr_warmup(
                fluid.layers.piecewise_decay(boundaries, lr_steps),
                warmup_steps, start_lr, end_lr)

This reverts commit 3d750f9c.

* wip

* wip

* wip

* wip for test

* add fp16 tests test=develop

* fix cpu build test=develop

* fix test=develop

* fix py3 tests test=develop

* fix lr_scheduler dtype test=develop

* fix test=dvelop

* test fix ci compile test=develop

* fix build and merge test=develop

* fallback momentumop change to general test=develop

* add memopt level

* add opt level for image classification demo

* clean code

* add delete op

* clean code

* test machine translation demo

* clean code

* clean code

* skip fill constant with force cpu

* clean code

* clean code

* refine code

* clean code

* fix bug

* fix mac build error

* override GetExpectedKernelType for cast op

* fix typo

* add cuda unittest

* change learning_rate_decay to learning_rate_scheduler
* optimize code
* change nn.cast to tensor.cast