* add use_master_acc_grad

* add ut

* refactor the optional tensor

* remove optiona<MetaTensor> in InferMeta

* fix bug

* fix optional<vector<Tensor>>

* fix bug

* fix rmsprop

* fix amp of eager_gen

* polish code

* fix deleted code

* fix merge conflict

* polish code

* remove is_nullopt_

* fix merge conflict

* fix merge conflict

* Add the new XDNN implementation. test=kunlun

* Add the new XDNN implementation. test=kunlun

* Modify the code based on review, test=kunlun

* add gradient merge for DistributedFusedLamb

* use master acc gradient

* fix CI ut

* polish

* remove math_function_impl.h change

* fix test_update_loss_scaling_op.py

* try to fix XPU/NPU CI

* add gm ut

* add sgd yaml

* change python api

* open eager mode in sgd

* fix bug

* add Output(Step) to distributed fused lamb op

* add _set_step

* momentum support l2decay for xpu. test=kunlun

* fix include file. test=kunlun

* fix cmake for device_worker. test=kunlun

* add some infer meta

* fix bug

* fix bugs;

* fix bug and add set data type

* revert infer shape of lookup table

* recover test

* move momentum, rmsprop to phi; test=develop

* update

* update

* update

* update

* udpate; test=develop

* fix xpu npu bugs; test=develop

* fix npu bug; test=develop

* fix windows compile error; test=develop

* fix windows compile error; test=develop

* polish code; test=develop

* fix conflict; test=develop

* add meshgrid;

* update

* polish code

* polish code;

* fix bug

* format; remove useless code

* fix npu bug

* fix bug

* fix lars optitmizer bug

* Update optimizer.py

* [Phi] Migrate Adam and Adamw into Phi

* fix compile error and unittest ok

* fix compile error and unittest ok

* fix undefined reference to fLI::FLAGS

* test depend on operator

* fix cmake

* fix xpu compile

* fix infrt

* fix amp_type_traits

* fix amp_type_traits

* modify according reviewer

* modify according reviewer

* fix dtype float16

* fix typo

* fix Cmake

* fix code style

* [NPU] add merged_momentum

* fix

* fix device

* [Phi]Migrate Adamax into phi

* Add adadelta kernel

* clean distribution_helper, index_impl, aligned_vector code in fluid

* fix conflicts

* move sgd to phi; test=develop

* update

* add sgd kernel; test=develop

* vectorize lamb kernel

* remove flags, add ut

* remove useless codes

* refine code, add param order

* add multi tensor apply l2 norm

* add multi_tensor_apply code

* make sizeof(TensorMeta) smalller

* move code to distributed_fused_lamb_op.cu

* remove useless FLAGS

* change Vector to std::vector and provide MixVector class as a helper wrapper class

* solve the multi-gpu hang problem

* remove the duplicate template instantialize

* Copy vector to cpu

* add CopyToCPU

* xxx

* final version: fix the problem of all reduce

* remove mixvector dependence

* fix

* merge

* fix code

* fix by CI

* rename pten dir to phi

* rename namespace to phi

* rename infrt pten dir to phi

* resolve conflict

* rename pten to phi in cmake

* revert all infrt change

* change needed files

* fix infrt failed

* fix inference failed

* Unify paddle/pten::framework::ddim into pten::ddim

* fix paddle namespace

* compile sucessfully

* fix npu src file

* fix conflict

* fix conflict

* fix tensorrt compiler error

* fix conflict

* fix conflict

* fix tesst file conflict

* fix conflict

* fix mlu file conflict

* fix mlu file conflict

* fix cinn header file conflict

* fix conflict

* fix conflict

* fix conflict

* fix conflict

* 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

Move paddle/fluid/operators/math/algorithm.h to paddle/pten/kernels/funcs and rename all references to symbols in it.

* #1 migrate dist-related type()-> dtype()

* move datatype function from pten -> fluid/framework

* change type() in imperative into convert(dtype())

* modify xx_tensor->type into xx_tensor->dtype

* change the set_type interface and the caller

* modify xx_tensor.type into xx_tensor.dtype

* fix mutable_data(place, dtype())

* change caller of mutable_data in pten and distributed

* change the caller of mutable_data in fluid/framework

* change the caller of mutable_data in imperative directory

* mutable_data: inference

* update the call of mutable_data

* transfer MakePenScalarArray MakePtenScalar ResetHolderWithType

* pass the compile. the next step is remove VarType in Pten

* fix all and remove VarType from pten. success in linux. Next task is other platform

* fix conflict with develop

* fix compiled error

* Fix reset conversion

* fix conflict

* fix compiled problem

* fix typo

* Fix << in tensor_utils.cc

* fix type->dtype

* fix unittest

* fix tensor init constructor

* fix DataTypeSize for BFloat16

* fix code style

* fix npu compiled error

* fix npu

* compile npu sucessfully

* fix conflict

* fix conflict
Co-authored-by: Nxiongkun <xiongkun03@baidu.com>

* move operators/math/math_function_* to pten/kernels/func
* namespace from `paddle::operators::math` to `pten::funcs`

* 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

* Added adam kernel

* CI rerun

* Added selected_rows and rw_lock to pten

* Renamed the unit test target to fix CI

* Removed Class SelectedRows in Fluid, changed include/cmake relationship, use pten::SelectedRows in Fluid

* Remove rw_lock.h,rw_lock_test.cc in fluid

* Use pten::RWLock and pten::AutoRDLock, fix CI

* Use pten::SelectedRows

* Use pten::SelectedRows

* Fix to pass NPU CI

* Use pten::SelectedRows, to pass NPU CI

* To fix NPU CI

* To fix NPU CI again