[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)

* 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

* enhance check for current block docstring for prim2orig interface

* refine if else syntax

* Updated triple_grad_check func

* add todo for gradient checker and refine some comments

* remove additional code

* add test for warnging in backward.py

* format python code

* support multi input in triple gradient checker

* Add matmul triple grad kernel

* Updated comments of TODO

* Supported some special tests

* Change code-format to follow CI std

* Updated gradient_checker.py

* Fix conflicts

* Removed unnecessary printing log

* Change code style to follow CI std

* merge upstream

* add priops.py

* add_p

* rm useless files

* add sub_p mul_p div_p

* add sqrt_p and tanh_p

* add reshape_p

* add broadcast_p

* Add python primitive wrappers.

* Jvp rules updated.

* JVP rules done for all the 17 primops.

* quick check and fixes.

* add jvp(op, *args)

* add broadcast_p fill_constant_p matmul_p reduce_p reshape_p transpose_p

* add split_p and concat_p

* add gather_p and scatter_add_p

* add slice_select_p and slice_assign_p

* Add transpose rules.

* add multi input check for add_p, sub_p, mul_p, div_p

* update concat_p

* Linearize and transpose in progress..

* refine gather_p and scatter_add_p

* updated.

* update transpose.

* refine slice_assign_p and slice_select_p

* init commit for lower

* Merged with primitive ops.

* small update

* add rules for orig2prim and prim2orig

* add 9 test for prim ops

* add more test and fix some bug

* add more test

* register proto

* Adding primops test.

* add shape valid check for broadcast_p op, and add keepdim attr into reduce_p op proto

* support multi input and multi output for split_p and concat_p

* Test updated.

* update

* fix slice bug for slice_select_p and slice_assign_p

* updated.

* Ops updated.

* Refactor and bug fixes.

* updated.

* finish orig2prim and prim2orig rules

* dtype for axis attr should be long int

* update dtype for axis attr int64_t

* update for iscan CI

* Update primx.

* Refactor vars in primx.

* update for lower transform

* add more shape and dtype check

* update primx.py

* change IndexTensor into int32 dtype

* update

* Fix linearize and transpose.

* Update is_dot

* Update is_dot

* Update is_dot

* add gradient aggregation, fix add_transpose.

* pass first linearize+transpose test.

* update test

* refactor op registration and primx.

* update rule for slice_assign

* try test lower

* update orig2prim and prim2orig

* pass simple lower pass

* update

* Update input types in the unit test.

* orig2prim segfault.

* 50% for adam.minimize

* test updated.

* temp fix erros in removing vars.

* primx updated.

* update for matmul_v2 and reshape2 orig2prim

* update for minimize

* Refine primrules

* Remove some code

* supporting unused and unreachable vars.

* update for use prim2orig in minimize

* fix gather and scatter_add transpose.

* Add rules UT

* update scatter_add

* Refine UT code

* fix nonetype check in topo

* Update gather_p pywrapper.

* remove useless print

* Merge tongxin PR and refine code

* readd some test

* rm useless print

* polish code.

* fix bug in minimize

* add get_input_var_list and get_output_var_list and use it in lower

* Fix scatter_add_p prim2orig

* Update code and fix orig2prim/prim2orig UT

* delete vars after block.desc._remove

* Improve ops and vars clean up logics.

* fix some bug in linearize and lower

* update tanh transpose.

* use set instead of list for var2remove

* test updated.

* polish code.

* fix dot2bar delete.

* merge tx/ad

* add indextensor_dot for gather and scatter_add

* add sorted for set

* Fix scale_orig2prim params

* fix some syntax bug

* add golbal_lower_update list

* Better handling of unused vars.

* update tests.

* Fix elementwise_sub orig2prim

* support none for transpose rule

* Merge and add transform UT

* fix a bug in transpose

* Fix transpose and UT

* a hacky fix for cancat op

* Fix exector place

* Refine variable name

* Add elementwise_mul orig2prim and support p_norm when p=1

* Add sqrt orig2prim rule and UT

* merge wz test

* rename files, add enable_prim, disable_prim, prim_enabled, delete global_lower_update

* fix a bug in test_ad_transform_trans

* revert modify in framework.py

* add paddle.fluid.incubate.ad_transform to  python/setup.py.in

* Fix remove vars error

* Fix p_norm_orig2prim

* merge wz

* Modify the code directory

* Add utils.py and remove get_input/output_vars functions

* Update maolin code

* Rename UT and refine test_ad_transform_primops

* Fix div_p jvp rule

* Add higher derivatives UT

* Remove UT to autograd dir

* Fix comments

* import paddle in primops.py

* Add some error message for assert

* Refine UT class name and refine some comments in primreg.py

* update minimize of paddle/optimizer for supporting new autograd

* resolve cicular importing between backward.py and optimizer.py

* fill gradients and minimize unittest

* Replace `assert isinstance` with `raise TypeError`

* Add some assert message for primx.py

* Polish variable name

* Add some assert message

* add some docstring

* refine some name

* update the format of english documents

* Split test_transform.py to two files to avoid ci error

* fix the document format of enable_prim/disable_prim/prim2orig/prim_enabled

* polish test_gradients_and_minimize

* add default value for prim_enabled api doc

* Remove some UT to avoid windows ci error

* Enlarge test_gradients_and_minimize limit time

* Fix ut limit time
Co-authored-by: Nveyron95 <veyron_wu@163.com>
Co-authored-by: NJiabin Yang <360788950@qq.com>
Co-authored-by: Nlevi131 <limaolin01@baidu.com>
Co-authored-by: NTongxin Bai <waffle.bai@gmail.com>
Co-authored-by: NXiaoxu Chen <chenxx_id@163.com>
Co-authored-by: Nlevi131 <83750468+levi131@users.noreply.github.com>

* update

* add conv yaml

* add backward

* remove useless code

* fix bug

* fix bug

* revert fluid dygraph conv2d

* remove useless infermeta function

* fix meta fn deluplicat error

* conv using custom impl

* remove amp include

* fix bug

* use final op in maskrcnn and hrnet

* refine
Co-authored-by: Nphlrain <phliuhongyu@126.com>

* refactor eager flags

* fix flags error when we switch from eager to dygraph

* fix ci problem

* fix ci

* fix ci

* merge develop and fix code style

* merge develop and fix code style

* fix op test error

* fix op test error

* fix op test error

* fix op test error

* fix op test error

* merge develop