* first commit

* restruct c++ interface to divide linear from matmulwithcublaslt

* finish building in cublaslt impl

* fix code bugs

* fix host cost

* add some changes

* remove fluid deps in fused_linear_param_grad_add_kernel

* fix compile error

* fix ut error

* follow comments

* optimization for fused linear op

* fix code format

* optimization for linear fused forward

* merge with develop

* fix bugs for gemm_ephilog

* package of cublaslt ephilogue type with enmu

* final fix before code reviewing

* fix missed fusedType typo

* fix code according to review suggestions

* fix windows ci error

* change location of MatmulPlanner

* add some changes for compiler error fix

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* Enable matmul + bias fusion in fused_gat_attention.

* Add a variable to control whether using fused matmul + bias.

* remove needless using tensor

* remove needless using tensor

* resolve conflict

* replace tensor using

* fix format error

* revert needless changing

* fix rocm and npu compile error

* fix cinn compile error

* fix format error

* fix mkldnn format error

* fix mkldnn format error

* fix cinn compile error

* fix cinn compile error

* fix cinn compile error

* resolve conflict

* remove cudaDeviceContext

* remove more template

* fix rocm compile

* remove alias name CUDADeviceContext

* fix compile

* fix tests

* revert changes

* move grad_add

* fix unittest bugs

* fix compile bugs

* 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

* move blas related files
* move lapack related files

* 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 the transformop parameter in TensorReduceFunctorImpl

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。