* [CodeStyle][py2] remove unnecessary u-prefix in string literal

* `"{}".format(x)` -> `x`

* remove duplicated dtype literals

* revert changes in data_feeder.py

* remove u-prefix in data_feeder

* revert remove duplicated dtype literals in data_feeder

* remove unnecessary convert to str

* for test

* add some comments

* refine comment

* restore a removed str conversion

* re-trigger all ci, empty commit

* fix scale kernel configuration error where input numel is 0

* fix code stype

* add unit test case for scale op when numel of input x is zero

* fix ci codestyle check

* add cpu and gpu unit test case for scale op when numel of input x is zero

* add uninitialized judgment for input of scale

* upgrade scale and slice op convert for Paddle-TensorRT

[Auto Parallel] Sharding Optimization：Partition Algorithm & Stage2 Parameter Bucket communication  (#47180)

* partition param by order

* add logging

* reorder opt

* config

* stage2 bucket

* update unitest

* [Zero-Dim] support input 0D Tensor for sundary api

* fix comment

* softplus+activation

* fc + elementwise_add test refactored

* rename MKLDNN to OneDNN

* fc+activation tests refactored

* remove softplus ut

* whitespace

* whitespace

* codestyle

* codestyle

* add more cases to fc+act

* remove softplus+hard_sigmoid pass

* remove softplus + hard_sigmoid UT

* add approximate for gelu

* swish beta range

* new codestyle

* reduce number of tests

* [Zero-Dim] support input 0D Tensor for distribution api

* fix comment

* fix tensor_array slice bugs in _getitem_impl_

* fix when var is a paddle.Tensor

* code format

* allow fold fill_constant && allow nms3 into trt in int8 model
* use unordered_map
* fix CI failing

* [CodeStyle][py2][U004] unecessary explicit `object` inheritance in class definition

* fix an increment

* Split kernel registered, tests for uint/int added

* Split quantized

* Split output scales calculated only once

* NearestInterp test fix reversed

* DequantizeOutputs corrected

* disable distributed xpu tests

* test=kunlun

* test=document_fix;test=kunlun

* test=document_fix;test=kunlun

* test=document_fix;test=kunlun

* test=document_fix;test=kunlun

* support pow_double_grad op

* add unit test for pow double grad

* fix pow double grad

* optimize pow double grad kernel

* fix pow double grad kernel

* fix cast bug

*test=kunlun

* fp16 pass support assign op

* choose assign op exec mode

* add unittest

* add cmakelist

add roll and roll_grad kernels and strided_slice and strided_slice_grad kernels, test=kunlun (#47368)

* add stat tool

* add roll and roll_grad kernels and strided_slice and strided_slice_grad kernels, test=kunlun

* test_paddle_multiprocessing support eager tensor pickler

* Get three grad lists in CPP to avoid gpu idle time

* Support legacy mode

* remove paddle.fluid.dygraph.nn.conv2D

* fix ut

* fix conv fp16 UT

* [CodeStyle][E262][E265] make comments start with `# `

* flake8 config

* add sin double grad operator

* add sin double grad test example

* move sindoublegradopmaker to backward.yaml

* fix sindoublegrad code

* simplify sindoublegrad functor

* [XPU] add cumsum op. test=kunlun

* try to fix linker. test=kunlun

* try to fix linker. test=kunlun

* try to fix linker. test=kunlun

* debug. test=kunlun

* update xpu.cmake. remove unnecessary codes. test=kunlun.

* move fluid.layers.deformable_conv to static.nn

* modify example code

* fix doc

* Update common.py
Co-authored-by: NLigoml <39876205+Ligoml@users.noreply.github.com>

* Fix dnnl errors in elementwise_sub tests

* Fix model accuracy attempt

* Add new fix

* Add proper fix

* Refactor by removing code repetition

* [CodeStyle][py2][U008] remove unnecessary args in `super()`

* remove remained args

* revert changes in test_pylayer_op

* Revert "revert changes in test_pylayer_op"

This reverts commit ff185a9ae738afac3b0264f61bde6c6b7f72e7c4.

* revert some changes in example code

* Add six for @to_static and add CI approval

* add six

* refine logic

* delete approve

* fix return

* add ImportError

* typo `moduels` -> `modules`
Co-authored-by: NNyakku Shigure <sigure.qaq@gmail.com>