* replace matmul with matmul_v2 in fuse passes

* Remove fusion logic from matmul

* removing fusion methods

* add proper name

* adjust namespaces

* clean attrs in python tests

* delete checkpoint and restore matmul version

* remove unused code

* matmul and reshape/transpose fuses migrated

* split MatmulOneDNN headers

* fuse activation and eltwise_add

* add fuse_activation

* matmul_transpose_reshape/reshape_transpose_matmul

* matmul + elementwise_add (fused)

* activation temporary modifciation

* merge newest develop

* remove depedency from other PR

* revert pbtxt

* remove placeholders from matmul_v2

* add description in OPMaker

* remove matmul_v2_op.h and all depedencies

* remove dims changing in base op

* add possibility to fuse already fused_matmul

* restart broken CI

* Empty-Commit

* revert matmul_utils.h

* codestyle

* adjust imports

* add pbtxt file

* 100% matmul unit tests coverage

* trigger CI with minimal changes to develop

* adjust changes to develop

* add fused_matmul op

* inherit base ops

* add "v2"

* move OPMaker

* Gradually add fused_matmul files

* second batch of fused_matmul changes

* split infershapes of matmul_v2 and fused_matmul

* inherit fused_matmul from matmul_v2

* Update paddle/phi/backends/onednn/onednn_reuse.h
Co-authored-by: NTomasz Socha <tomasz.socha@intel.com>

* Update paddle/phi/kernels/fusion/onednn/fused_matmul_kernel.cc
Co-authored-by: NTomasz Socha <tomasz.socha@intel.com>

---------
Co-authored-by: NTomasz Socha <tomasz.socha@intel.com>

* add input check for accuracyOp

* add input check for gpu/accuracyOp

* add unittest

* use rank instead of dimensions in message

* update unittest

* update unittest

* generate some static graph ops

* fix the bug of pow

* add REGISTER_ACTIVATION_OP in operators.cmake

* modify the file operators.cmake

* add stride check for PoolOutputSize

* add unittest

* paddle.nn.functional.softmax
* paddle.nn.functional.log_softmax
* paddle.nn.functional.gumbel_softmax
* paddle.nn.functional.prelu

* fix bugs

* fix ci bugs

* add range check for crop_kernel

* remove shape negative check

* add unittest

* add check for input of slice

* add unittest

* add stride check for MaxPool

* add unittests

* fix 0-d tensor for arg_min_max op.

* fix xpu.

* fix zero dims

* fix

* Update arg_min_max_kernel.cc

* Update arg_min_max_kernel.cc

* Update arg_min_max_kernel.cc

* Update test_zero_dim_tensor.py

* Update test_zero_dim_tensor_xpu.py

* Update test_zero_dim_tensor.py

* Update arg_min_max_kernel.cc

* Update arg_min_max_kernel.cc

* Update arg_min_max_kernel.cc

* [Divide by 0 Error] add lu check

* [Divide by 0 Error] lu check migrate to c++

* [Divide by 0 Error] add eig check

* [Divide by 0 Error] eig check migrate to c++

* [Divide by 0 Error] Fix class name error

* [Divide by 0 Error] add norm check

* [Divide by 0 Error] fix x AttributeError

* [Divide by 0 Error] norm check migrate to c++

* A leap of try for cudaLaunchCooperativeKernel

* fix bugs

* Totally replace the lar cuda kernel

* Fix bugs

* fix code according to comments

* fix codes according to  review comments

* adding some function overload

* relocate the power operation.

* add bf16 support for index select relevant ops

* revert bf16 type change.

* add changes for more op

* fix code writting bugs

* add axis check for unbind

* add axis range check for unbind

* update unittest and axis validation for unbind

* add unittest invalid axis for unbind

* restore axis extract for unbind

* profile reduce kernel for fp16 and reduceHigherdim

* use reinterpret_cast

* fix for CI on ROCm

* add Macro for ROCm

* ROCm CI config

* ROCm CI config

* unit test repair

* pull

* add common_funcs.h

* reduceType

* Update reduce_function.h

* not higher

* rename

* implement of matmul using cublasLt instead of cublas

* cublasLt bugfix

* Update matmul_kernel_impl.h

* Update matmul_kernel_impl_via_blasLt.h

* for-loop-algo

* PR comments changes

* add macro

* ci unused variable isCublasLt

* ci unused variable isCublasLt macro

* split matmul to autotune

* rewrite the split kernel with segmented_array

* rewrite the split kernel with segmented_array

* rewrite the split kernel with segmented_array

* add some method for cuda_graph

* fix bugs for rocm

* change for ci-error

* i dont know why ci-model-benchmark gives a shit error, so i recover codes with original one to see if original codes work.

* add some changes for passing mode_benchmark and coverage ci

* fix ci error

* fix ci-rocm error

* add some changes for header

---------
Co-authored-by: Nzhangbopd <1299246947@qq.com>
Co-authored-by: NBo Zhang <105368690+zhangbopd@users.noreply.github.com>

* [CustomDevice] add custom device api

* update

* update

* test=document_fix

* update

* update

* add  examples

* fix incorrect output shape of broadcast

* add unittest

* fix mod 0 error

* fix div 0 error in floormod

* support 0d tensor for interpolate

* support 0d tensor for interpolate

* add xpu unittest for interp

* update unittest for interpolate

* fix coverage

* fix code style

* fix for coverage

* fix coverage

* decouple phi custom_op

* decouple phi custom_op, remove codes

* delete custom symbol of inference

* add axis check in UniqueRawInferMeta

* add unittest for negative axis

* simplify check for unique

* add elements count check in atan2

* add unittest and pre-check in inferMeta

* add dimension check

* add zero size check in matrix_power_kernel_impl.h

* add zero size check in matrix_power_kernel_impl.h

* add zero size check in unittest

* bug_fix

* bug_fix

* bug_fix

* bug_fix

* bug_fix

* bug fix

* bug_fix

* bug_fix

* add static check

* delete the dy codes

* support negative index in repeat_interleave

* add unittest

* Unify the gpu implementation of stack and unstack to reuse the optimization.

* Optimize the cuda implementation of unstack.

* Use GpuMemcpyAsync instead of memory::Copy.

* Fix error of calculating the index.

* Use FastDivMod to further imporve the performance of unstack.

* add pivots type check and fix batchsize error

* add unittest for batchsize = 0

* fix nullptr in lu_unpack

fix batchsize error in LU_Unpack
add nullptr check in OneFunctor

* remove exception in device code