* open eager when WITH_PYTHON, test=develop

* refine, test=develop

* refine, test=develop

* add DWITH_PYTHON for gen_fluid_lib, test=develop

* update;test=cpu-py3

* add processgroup_nccl

* disable some distribute test case when in CPU test env, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* add DistributedFusedLamb op

* polish code

* fix compile error

* compatible with pten changement

* fix rocm compile error

* improve converage

* update upstream/develop

* fix cast_with_ptr.h

* add FLAGS_distributed_lamb_divide_nranks_when_allreduce=1

* fix clip before allreduce

* add use_master_param_norm

* code polish

* fix bug

* fix ROCM ci

* merge legacy to fluid

* Remove legacy code

* Remove legacy code

* Remove DataType test

* Using Tensor directly instead of using EagerTensor

* support gradient_accumulation

* make test_imperative_lod_tensor_to_selected_rows longer

* make test_imperative_lod_tensor_to_selected_rows longer

* implement AllocateFrom

* fix PR-CI-Coverage timeout in 120s
Co-authored-by: Nzkh2016 <zhangkaihuo@baidu.com>

Refactored python-level trace_op to call through _C_ops instead of Tracer::TraceOp, under eager_mode (#38338)

* Replaced core.ops with _C_ops

* Refactored python-level trace_op to call through _C_ops instead of Tracer::TraceOp, under eager_mode

* Modified trace_op interface

* Refactored trace_op logic for eager mode

* Added Eager Dygraph support for OpTest

* Fixed ci issues

* Fixed CI failures

* Fixed Coverage CI Issues

* Fixed XPU CI Issues

* ipu_commit_tests p1

* resolve comments

* resolve comments

* resolve comments

* resolve comments

* resolve comments

* resolve comments

* resolve comments

* update lint and ipustrategy introduction

* update ipu_config

* update __init__ of static

* update doc

* update doc 2

* update doc 3

* update doc 4

* update doc 5

* update doc 5

* update doc 6

* update lint

* update lint 2

* update ipustrategy

* add IpuStrategy to all

* update ipustrategy

* update ipu_shard_guard

* update ipu_shard_guard 2
Co-authored-by: Nyaozhixin <522190855@qq.com>

* [MLU]: add mean and reduce mean op

* [MLU]add mlu pytest dir in CMakeLists.txt

* [MLU]fix tensor data

* [MLU]fix TensorToPyArray and license

* update dist tensor

* add unitest

* update unitest

* refactor dist tensor

* update dist tensor and unitest

* Add the backward support for QR

* Remove unnecessary comments

move distribution.py into distribution package and split into different file for better scalability (#38047)

* add update func of auto search

* update unitest

* [Auto Parallel]  Add the unified cluster representation

* [Auto Parallel] Add the graph class for physical mapping

* [Auto Parallel] Add the simple physical mapper

* Set the timeout of the mapper

* Merge the upstream develop unittests cmake files

* Fix a bug of the process group

* Remove mapper unittest from platforms which is not GPU

* Move the instantiation of process group after resharding

* Add the local id for devices

* Update the rank mapping format

* [Auto Parallel] Relaunch with the rank mapping file

* Remove the unnecessary json file

* Avoid entering get_device_proc_info for auto mapping

* Correct the mapper unit test

* Add some comments

* Remove the related files about mapping

* Update the unittest for auto mapping

* Remove unused rank_mapping unittest

* Improve the unittest coverage

* Improve the unittest coverage

* Improve the unittest of relaunch

* Fix the unittest problem in CI

* Improve the unittest of relaunch

* Remove unnecessary statements

* Update the unittest cmakefile

* Correct the cmakefile of auto parallel unittests

* Modify codes based on the new elastic change

* Use the GPUs exclusively in the unittest

* Correct the cmakefile

* Set the timeout of the unittest

* [Auto Parallel]  Add the unified cluster representation

* [Auto Parallel] Add the graph class for physical mapping

* [Auto Parallel] Add the simple physical mapper

* Set the timeout of the mapper

* Merge the upstream develop unittests cmake files

* Fix a bug of the process group

* Remove mapper unittest from platforms which is not GPU

* Move the instantiation of process group after resharding

* Add the local id for devices

* Update the rank mapping format

* Add some comments

* Remove the related files about mapping

* Update the unittest for auto mapping

* Remove unused rank_mapping unittest

* Improve the unittest coverage

* Improve the unittest coverage

* [Auto Parallel]  Add the unified cluster representation

* [Auto Parallel] Add the graph class for physical mapping

* [Auto Parallel] Add the simple physical mapper

* Set the timeout of the mapper

* Merge the upstream develop unittests cmake files

* Fix a bug of the process group

* Remove mapper unittest from platforms which is not GPU

* Move the instantiation of process group after resharding

* Add the local id for devices

* Update the rank mapping format

* Add some comments

* Remove the related files about mapping

* Remove unused rank_mapping unittest

* Improve the unittest coverage

* fix data parallel when VOCAB var in program

* add split_program

* make ut faster

* increase ut timeout

* make result deterministic

* add fuse_all_reduce pass

* add ut framework, update

* fix ut framework

* remove useless code

* add coverage support

* update

* fix CI

* fix some bugs and fix ci coverage

* fix conflict

* fix bug:
1. atten: set the default value of attn_dropout_rate to None
2. ffn: add activation parameter

* add AutoConvert

* add unitest

* amend merge&slice

* amend default dist_attr

* update doc&improve coverage

* add interface dist_context

* tiny modify

* AutoParallel Save&Load

* tiny modi

* update func name

* tiny fix

* add NotImplementedError

* fix doc

* update func name

* update func param

* update interface

* add unitest & modi make_data_unshard

* update unittest

* update unittest

* fix unittest

* fix cmakelist

* update unittest

功能：本PR的目标是提高attention模块的计算性能。
为了减少框架层对op的调度开销，本PR通过在C++层手动实现attention模块，对外提供attention 大op；
为了减少防存开销，本PR采取了两种优化方法：
（1）在q,k,v计算时通过共享输入X，将该处的gemm，transpose和bias add从三次调用减少为一次；
（2）使用kernel融合优化技术，在不同cuda kernel之间通过寄存器传输数据；

将 #35905 和 #35843 PR中新增的的python api接口移到incubate目录下。

* In cpu parallel using gloo, add various length support for SelectedRows

* fix bug

* fix bugs

* fix by code review

* remove timeout