* Added cuBlasLtHandle_t to device context.

* Added fused_gemm_epilogue op.

1. Added fused_gemm_epilogue op to leverage cuBlastLt Epilogue.
2. Support fusion Act(X*Y + bias), X'dims >=2 and Y'dims shoule be 2.
2. Act currently only be supported ReLU. (Will add GeLU in the future).

* Added UT to fused_gemm_epilogue op.

* Added LinearAct Pattern

1. Added LinearAct into graph_pattern_detector.* to define (2.)'s
pattern.
2. LinearAct is used to detect act(element_add(matmul_v2(x, w), bias)).
3. act currently only support ReLU (Will support GeLU in the future).

* Added FuseGemmEpiloguePass

1, Added FuseGemmEpiloguePass to handle nn.Linear + Act{ReLU}
fusion (GeLU will be supported in the future).
2. Only support matmul_v2 from nn.Linear.

* Added pybind to BuildStrageter.fuse_gemm_epilogue_.

* Added UT for fuse_gemm_epilogue_pass.

* GeLU support and EpilogueSingleton

1. Added GeLU support to fused_gemm_epilogue op.
2. Added EpilogueSingleton to cache auxiliary pointer.
3. Added related UTs.

* Rename cublaslt_epilogue_opto gemm_epilogue_op.*.

* Added both train and infer pattern to LinearAct.

1. Added support of fwd graph with grap_ops linking to LinearAct.
2. Added related changes to fuse_gemm_epilogue_pass for above
modification.

* Changed CUDA requirement from 11.4 to 11.6 for fuse_gemm_epilogue_pass.

* Added identity activation support to gemm_epilogue_op.

* Added Linear Fusion (matmul_v2 + ele_add)

1. Added matmul_v2 + ele_add pattern to LinearActPattern.
2. Added matmul_v2 + ele_add support to fuse_gemm_epilogue_pass.

* Rename gemm_epilogue_op.* to fused_gemm_epilogue_op.*

* Add fused_gemm_epilogue_grad op.

1. Added fused_gemm_epilogue_grad to support backward epilogue fusion.

* Add UTs to fused_gemm_epilogue_grad_op.

* Change attribute name in fused_gemm_epilogue_grad_op for clearing.

* Allow DX and DBias be dispensable to fused_gemm_epilogue_grad op.

* Added ElementwiseAdd+Matmul+Act graph pattern detection.

* Fuse backward of Linear( Act(x))

1. Added backward fusion pass to Linear( Act(x)).
2. Added backward fusion pass to Linear(x).

* Added UTs to backward fusion of Linear(Act(x)).

* Complete document of arguments to fused_gemm_epilogue_op.

* Made arguments of some functions pass by reference.

* Modify code with review comments.

1. Made arguments of some function pass by reference.
2. Removed redundant code.
3. Followed Google code style to change code.

* Made 'const' code style be consistent

* Fixed random seed of python UTs.

* Set Compiling constrains to cuBlasLt

1. Require CUDA 11.6+
2. Remove fuse_gemm_epilogue related tests when CUDA < 11.6.

* Code Reivew from Paddle

1. Changed arguments name is_first_gemm to without_x_gradient for
clearing.
2. Applied PADDLE_THROW in fused_gemm_epilogue_op.

* Remove EpilogueSingleton

1. Applied ReserveSpace to replace Epilogue for passing auxiliary
pointers between FWD and BWD.

* Fix a logical error and enhance UTs.

1. Added act op count checking in UTs.
2. Fix issue to fuse backward or ReLU(Linear(X)).
3. TODO: solve GELU fusion issues.

* Fix Linear and GeLU fusion issues.

1. Modified graph_detech_pattern to fit with both linear wiht gelu or
relu.
2. Modified data range in Uts to allow negative values.

* Removed fused_gemm_epilogue_op.h.

* Rename namespace pten to phi.

* Rename name of arguments in fused_gemm_epilogue_op

1. bias -> Bias.
2. out -> Out.
3. reserve_space -> ReserveSpace.

* Change EpiloguePassActivationCache as local variable.

1. Removed singleton in EpiloguePassActivationCache.
2. Made EpiloguePassActivationCache as an argument to each pass
functions.

move cpu_vec.h to phi/kernels/funcs.

* clean distribution_helper, index_impl, aligned_vector code in fluid

* fix conflicts

* move reduce gpu impl funcs into pten/kernels/funcs

* change reduce header name and namespace

* fix spell word error

* change mutable_data to dev_ctx.Alloc

* modify place to devcontex

* format code style

* fix build error

* fix build error

* fix conflict

* move conv to pten

* move conv to pten; test=develop

* fix bug;

* add conv cudnn impl; test=develop

* update

* update operator; test=develop

* fix bug; test=develop

* move operator and prepared_operator to develop; test=develop

* resolve conflict; test=develop

* remove useless code;test=develop

* add depency ; test=develop

* fix bug;

* add sig.cc ; test=develop

* fix use_op error; test=develop

* fix bug; test=develop

* fix bug; test=develop

* add conv3d register; test=develop

* fix star gan and conv_nn_grad test failed; test=develop

* add header; test=develop

* manul to recover to develop;

* resolve confilct; test=develop

* remove useless code

* fix bug;

* remove conv2d_cudnn; test=develop

* fix bugs; test=develop

* fix cpu rocm compile bugs; test=develop

* fix blas error; test=develop

* fix compile bug; test=develop

* fix windows compile error; test=develop

* fix windows error; test=develop

* resolve confilct; test=develop

* add pad forward

* fix error

* transfer pad and pass the test_pad_op

* add bn cpu version; test=develop

* move batch norm to pten

* move batch norm to pten; test=develop

* fix bug; test=develop

* fix func::tranpose depend bug; test=develop

* fix compile bugs; test=develop

* fix use_op batch_norm bug; test=develop

* fix cudnn bn add relu test; test=develop

* fix pten context build and double grad bug; test= develop

* remve useless code; test=develop

* add batch norm gpu fp16 support; test=develop

* fix test bn op bug; test=develop

* remove output dtype set; test=develop

* fix bug; test=develop

* fix bug; test=develop

* fix applay pass to program bug; test=develop

* revert to develop; test=develop

* fix rocm bug; test=develop

* revert operator to develop; test=develop

* fix pre_commit; test=develop

* fix statci check error; test=develop

* resolve conflict; test=develop

* ana batch norm bug;

* revert batch norm op

* resolve conlict

* fix nan inf and speed bug; test=develop

* fix bug; test=develop

* fix error; test=develop

* test expand op; test=develop

* fix bug; test=develop

* resolve confilct

* resolve confilct; test=develop

* polish code; test=develop

* polish code; test=develop

* change mutable data to ctx alloc; test=develop

* make format same with ci; test=develop

* fix format error with ci; test=develop

* move sequence2batch

* move lstm and gru

* Add phi/kernels directory into exclusion to stop using hipcc to compile non .cu files in it.

* rename pten_utils to phi_utils

* rename pten_utils target

* rename Pten to Phi

* replace pten with phi

* resolve conflict

* support cudnn kernel moving

* polish cmake rules

* add unittest for coverage

* remove orig kernel

* remove softmax cudnn kernel

* fix softmax test failed

* fix npu func error

* resolve conflict

* rename gpu dnn kernels

* fix name rule error

* fix compile error

* update fp16 namespace

* 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

* move blas related files
* move lapack related files

* move paddle/operators/math/functors.h
* move paddle/operators/math/compound_functors.h

* #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`

* Add fp16 support for scale/bias for fused_layernnorm_residual_dropout_bias op.

* Remove useless code.

* Remove useless code.

* Optimize layer_norm fwd when cols is 1024.

* Remove useless code.

* Minors.

* Minors.

* Modifications accordding to reviews.

* Minors.

* Optimize layer_norm bwd kernel when cols is 1024.

* Polish layer_norm_bwd_1024 kernel.

* Limit ln_bwd_1024_kernel to paddle_with_cuda.

* Fix double type compile error.

* Add optimization of ln bwd for fused_dropout_add_ln op.

* Polish codes.

* update cmake file to remove fluid kernel

* add pten declaration.h to where pybind.h used

* fix sync_bn and tensorrt_engine

* refine detection_library

* fix interpreter_core

* support eager legacy

* fit eager legacy for pten

* fall back to cpu if not found kernel

* fix compile problem

* fix compile problem

* refine fallback logic

* fit operator.run()

* fix xpu compile

* fit for new_exec

* add REGISTER_OP_WITHOUT_GRADIENT

* un-cache pt_kernel_context

* fix compile

* fix cudnn

* fix compiling with on_infer

* fix mkldnn

* fix isfinite_v2

* fix xpu problem

* fix op_device

* refine fallback for xpu

* fix xpu compile

* merge develop

* refine code format

* fix compile

* fix compile

* add data_transfer

* fix PreparePtenData

* fix cpu context

* merge develop

* fix compile

* fix error device context

* fix xpu

* fix dev_ctx

* Optimize layer_norm fwd when cols is 1024.

* 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

* - more unlikely

* - compilation fix

* - removed redundant definition

* - fix

* - Fixes

* - compilation fix for windows

* Merged LoDTensor with Tensor,test=allcases

* Patched python level LoDTensor

* Patched python level LoDTensor

* Merge Tensor into DenseTensor

* Fixed namespace issues,test=allcases

* Fixed merge issues

* Fixed inference issues

* Fixed NPU test issues

* Fixed merge issues

* add pten::Place data structure.

* update ci problem

* fix ci problem

* update

* using platform::Place=pten::Place

* remove BOOST_GET_CONST for CPUPlace and GPUPlace

* compile pass 25%.

* compile pass 45%

* compile pass 60%

* remove boost_get for xpu npu mlu and ipu

* compile pass on cpu and gpu.

* fix compile problem

* fix compile error.

* update

* fix ci problem

* update

* ci approve

* fix ci problem

* fix ci eager test problem

* remove BOOST_GET_CONST

* fix npu compile

* first commit

* fix wrong filename

* fix the wrong spell name

* fix gpu config warper

* modify according to pr advices

* fix GpuLauchConfig1D api bugs

* change the config for dropout grad

* fix bugs

* modification according to pr advices

* modification according to pr advices

* Add fp16 support for scale/bias for fused_layernnorm_residual_dropout_bias op.

* combine reduce_cuda codes

* support float16 in pten redcue_mean

* replace ReduceCudaKernel impl with pten reduce impl

* mv reduce funcs into reduce_cuda_impl

* rm unsed codes and headers

* mv GetReduceDim into reduce_cuda_impl

* recover GetReduceDim in reduce_op.h

* add new dispatch macro

* fix pool op output not inited and cause transform to pten::denseTensor error

* fix output tensor not initialized error

* rename new dispatch macro and format code style

* rm reduce_functor_op.h file

* Add the transformop parameter in TensorReduceFunctorImpl

* refine structure for cuda and rocm

* update

* update

* update

* update

Add support for bias is none for fused_attention op.

* GeneratePass support attr condition and mapping, test=develop

* fix coverage, test=develop

* Add fuse_resnet_unit pass, test=develop

* fix CI errors, test=develop

* fix CI errors, test=develop

* fix unittest error when compiling without CUDA, test=develop

* fix static ci error, test=develop

* limit kernel size must equal 1, test=develop

* Change first batch of mkldnn headers and namespace names to dnnl

* Revert changes to tensor.h, which require approval

* Format changes with pre-commit

* Add int32 tests

* Fix int32 tests and call GetDataFromTensor for int32

* Fix test

fused_attention_op的实现中，使用了bias_add，且其实现是通过使用kernel primitive来实现的，之后kernel primitive的WriteData api接口及函数内部实现发生了更改，将判断越界的逻辑移到了template的参数中，使得调用的分支有错误，产生了越界赋值操作，污染了别的显存空间的内容。具体表现为：test_fused_attention_op_api.py 单次执行基本上不会报错，多次循环执行不同shape的输入，结果计算不对，具有偶发性，bug不易察觉。

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