新增sparse.is_same_shape、sparse.reshape、sparse.transpose 三个API

* [dygraph sharding] Overlap the reduce and the caculation for sharding stage 2. (#46495)

* [dygraph sharding stage 2] sharding broadcast overlap (#46656)

* Multi groups for broadcast of sharding stage 2 (#46894)

* Support both use_calc_stream and sync_op in send recv APIs (#46023)

* Support both use_calc_stream and sync_op in allgather API (#46295)

* Support both use_calc_stream and sync_op in collective communication API (#46761)

* Move group and all reduce from collective to communication (#45848)

* Completes bfloat16 dtype for collective api in eager mode (#45844)

* Fix collective APIs cannot be recognized when building docs (#46962)
Co-authored-by: NLiYuRio <63526175+LiYuRio@users.noreply.github.com>

cherry-pick : #46322, #46245
Sparse API 支持静态图

* [BUG]Fix expand_as_v2 bug while X and Y with different dtype

* fix commit

* fix reshape2 opteller;
add elementwise min/max register for tensorrt

Fix set_value failure when source tensor is fp16 Dtype and destiny value is a number
(dev PR link:#46801)

* Revert pool+grad oneDNN kernel conversion (#45989)

* [PHI] transpose2_grad op migration (#46139)

* op migrated, Copy(OneDNNContext, ...) added

* mutable_data & op registration in fluid removed

* refactoring

* OneDNNGetDataType to uppercase

* missing cpu check added, handler moved to .h file

* name changed to transpose_grad

* Copy changed back to TensorCopy

* Resizing corrected, Copy(OneDNNContext) removed
Co-authored-by: NPiotr Paturej <48731682+piotrekobi@users.noreply.github.com>
Co-authored-by: NPaulina Gacek <paulina.gacek@intel.com>

Cherry-pick 46541
保证Reset50 TSM deeplabv3模型零修改下实现Layout自动调优

cherry pick pr46536 

* fix gather op convert to only support int32 index as input.
* add ut

* 1. refactor the return transformer.
2. fix some bugs in return transformer.

* support raise error while return stmt's father is For or while

* fix ci error.

* fix ci error and add some unittest

* code format

* fix ci error

Add FP16 support for uniform in dygraph mode on Nvidia GPU
Dev PR link PR46212

* Clear extra attrs of elementwise op in OpMaker (#45845)

* clear extra attrs of elementwise op in opmaker

* fix op_debug_string_test

* fix bug of grad_add

* fix sort of runtime attrs

* Clear extra attrs of scale in OpMaker (#45984)

* clear extra attr of scale in opmaker

* fix sum bug

* fix merge conflict

* fix minus

* Clear extra attributes of some Op in OpMaker (Part4) (#46060)

* clear extra attr of some ops in opmaker

* revert clear use_cudnn for pool

* fix test_operator_desc

* fix Attr interface of OperatorBase

* fix code stype

* fix sub sign reverse for mkldnn

* refactor code as comment

* remove useless

* [BugFix]Fix reduce_mean/min/sum/prod, cumsum grad_op infershape bug

* fix typo

* fix typo

uniform logger manager in FleetAPI.
hidde API under distributed/utils which users don't need.

* [Check]Enhance pooling output_size type check

* add unittest

* fix cast bug

* polish code comments

* polish data_device_transform.cc

* [Auto Parallel] Change the import way of Auto Parallel (#46115)

* fix strategy (#46256)

* [Auto Parallel] performance improvement for Sharding-DP hybrid parallelism (#46180)

* remove no need grad allreduce communication when sharding-dp

* remove no need grad allreduce communication when sharding-dp

* bugfix

* bugfix

* bugfix
Co-authored-by: NYulong Ao <aoyulong@baidu.com>
Co-authored-by: NJZ-LIANG <jianzhongliang10@gmail.com>

* Support matmul_v2 in Paddle-TensorRT converter.

* Fix TransDataBackend Error when call unsqueeze using MKL Tensor

* Add UT

* Refine UT

cherry-pick : #46016, #46021, #45974

* [Sparse]Sparse add support gpu (#45974)

* [Sparse]Remove unused code (#46021)

* [Sparse] Add infer meta (#46016)

* support cast op backward refuse forward and fix some bugs (#46173)

* support cast op backward refuse forward

* Fix the bug of high order unit test framework

* support sign op backward refuse forward (#46002)

cherry-pick from #45826
LayoutAutotune 支持 inplace 类型的OP
 根据 Add eager layout autotune #45409 修改意见调整UseAutotune
将LayoutAutotune判断放到controller中，与AMP 判断保持一致