* elementwise_add kernel refactor

* fix compile bugs in elementwise_add refactor

* fix compile bugs when run in npu/xpu

* fix bugs when run unit test

* fix bugs when run ci-windows

* modify code as recommended

* code format adjust

* fix bugs when run ci

* fix compile bug when run in ci-windwos

* fix several bugs

* fix elementwith override error

* add TypeAdapter method for npu_op_runner

* add int64 supporting for elementwise_mul and reduce_sum

* add int64 supporting and UT for expand_v2, scale and reduce_max

* fix bug

* Add WIP version of elementwise_div_mkldnn without working dy grad

* Add dy gradient calculation implementation, disable broadcast tests

* Readd removed tests from static_mode_white_list

* Add bfloat16 gradient tests, remove int8 and uint8 support

* - Change the way dy grad is calculated to improve performance
- Refactor BinaryMKLDNNHandler to use a default parameter

* Change copyright year

* Refactor as suggested

* Attempt to bypass CI Approval
not accepting max_relative_error

* Fix formatting issue

* [NPU] modifications for model ernie-1.0

* rollback 503003 and change cast to dtype

* Support elementwise_add triple grad Kernel

* Change code-format to follow CI std

* Removed unreasonable code, and fixed an input uninitialized issue

* Support elementwise_add triple grad Kernel

* Change code-format to follow CI std

* Removed unreasonable code, and fixed an input uninitialized issue

* add viterbi decode cpu kernel

* add viterbi decoder api in paddle.text

* add a data buffer once to avoid create many small pieces of data buffer frequently

* fix viterbi max_seq_length bug

* fix seq_len=1 bug

* fix device context

* move split out of for loop

* remove INVERSE_SUB

* remove 2 GET_CAST_MASK

* remove 1 loop

* remove Functor

* add to_static deploy code

* use MAX_FUNC instead of ELE_MAX

* add MaxFunctor

* impl max_func

* remove MaxFunctor

* remove cast op

* use REGISTER_OP_WITHOUT_GRADIENT

* add viterbi cuda kernel

* add FIX_BLOCKDIM_CASE macro

* add MKL add, mul; add get data mask

* add arange mkl impl

* add CPU Argmax

* add cpu gather

* use EXECUTE_MKL_ELEMENT_BINARY_OP instead of some ADD, MUL

* use SameDimsBinaryOP instead of EXECUTE_MKL_ELEMENT_BINARY_OP

* use SAME_DIMS_ELEMENT_BINARY_OP

* add SimpleBroadcastBinaryOP

* use int instead of int64_t to accelerate

* optimize SimpleBroadcastBinaryOP

* optimize SimpleBroadcastBinaryOP

* optimize performance in both single thread and multithread situation

* remove useless line

* remove useless code

* add CREATE_TENSOR_BUFFER macro

* add INIT_REQUIRED_TENSOR macro

* add comment

* fix windows ci

* add viterbi unittest

* remove cuda add functor

* remove cuda equal

* remove a template function

* fix windows ci

* fix windows dtype

* remove some template instance

* remove useless header file

* remove some blockdim

* remove transpose impl

* accelerate cpu performance on single thread situation

* viterbi_decode->crf_decode

* rename crf params name

* add viterbi api test

* remove useless import

* add enable_static

* use viterbi decoder

* fix viterbi len=1

* fix  viterbi unittest

* remove useless comments

* reconstruct viterbi decode

* remove ADD,SUB,MUL structure

* fix coverage

* remove CREATE_TENSOR

* add name args

* crf.py->ops.py; with_start_stop_tag->include_start_end_tag

* update crf_decode en docs

* fix viterbi decode en docs

* fix some review comments

* add FIXED_BLOCK_DIM_CASE in cuda

* push_back->emplace_back

* crf_decode->viterbi_decode; include_start_end_tag->include_bos_eos_tag

* paddle.text.ops.viterbi_decode->paddle.text.viterbi_decode

* fix viterbi_decode en docs

* Update the implement of reduceAnyKernel according to kernel primitive api
* Fix a bug in ReadData, ReadDataBc and ReadDataReduce when NX != 1

* Support elementwise_add triple grad Kernel

* Change code-format to follow CI std

* [NPU] fix elementwise_mul to support broadcast, test=develop

* remove debug files, test=develop

* add axis support, test=develop

* merge conflict of paddle_gtest_main.cc

* modify FLAGS_npu_precision_mode and default not to call aclSetCompileopt

* Add elementwise_sub_mkldnn_op without grad

* Add test to static_mode_white_list

* Refactor code, change license years

* Remove invalid grad implementation

* Fix element_wise_sub_op test

* Fix CI Approval error

* Remove unnecessary EltwiseSubMKLDNNGradKernel class

* Fix CI Approval 2

* Fix CI Approval 3

* Fix CI Approval Attempt #4

* Fix CI Approve Attempt #5

* Fix CI Approval Attempt #6

* Fix CI Approval Attemt #7

* Change test names containing add to sub

* Fix old tests testing add instead of sub

* Copy grad implementation from elementwise_add_mkldnn

* CI test fix attempt

* Revert "CI test fix attempt"

This reverts commit c647cacf41e6a87c715385a185de5cbf65fc8900.

* Fix CI attempt 2

* Fix elementwise_sub tests, temporary mkldnn broadcast test disable

* Add working implementation of elementwise_sub grad

* Fix build errors caused by pull

* Fix format error

* Fix format error 2

* Disable elementwise_sub_mkldnn test on GPU

* Apply fix for paddle.fluid import

* Revert changes of test_elementwise_sub and Fix mkldnn test

* Revert "Apply fix for paddle.fluid import"

This reverts commit fc3b122fec8e12f2bcb32928a2685ba4d20fd742.

* fix bug of module 'paddle' has no attribute 'fluid' for python3.6 (#35862)

* Add changes suggested by reviewers

* Change @unittest.skipIf... to @OpTestTool.skip_if_not_cpu_bf16() to satisfy Approval CI

* Remove check_dygraph=False to satisify CI Approval
Co-authored-by: Nzhangbo9674 <82555433+zhangbo9674@users.noreply.github.com>

* - REorder disabling caching

* - compilation fix

* - another compilation fix

* - another compilation fix

* - compilation fix

* - Fix

* - yet another compilation fix

* - suppresingly another compilation fix

* - lint

* - fix after review

* - fix

Implement FunctionTraits to support two kinds of elementwise functor and remove some old codes for broadcast. (#35688)

Revert "Implement FunctionTraits to support two kinds of elementwise functor and remove some old codes for broadcast. (#35487)" (#35686)

Implement FunctionTraits to support two kinds of elementwise functor and remove some old codes for broadcast. (#35487)

multiply supports bool  

* Add the extra flag for the some ops

* fix the compile problem in matmul extra

* add elementwise_pow_grad_npu

* fixed bug for CI

* deal with comments

* fixed bug for CI

* deal with comments

add axis check for elementwise op while the dimension of x is equal to the dimension of tensor (#35340)

* add elementwise max grad op for npu

* add elementwise max grad op for npu

* add elementwise max grad op for npu

* add elementwise max grad op for npu

* add elementwise max grad op for npu

[oneDNN] disable caching oneDNN primitives in  matmul v2, Reduce grad and elementwise_add grad, expand_v2 (#35132)

* - grad caching disabled of matmul_v1

- compilation fix

- compilation fix

* - reduction removed

* - Matmul v2 disabled caching

* Draft of further changes

* - workaround for reducegrad

* - fixes to UT

* - fix to compilation

* - another fix

* - fix

* - Added softmax without caching

* - Binary is no longer manually cached

* - Activation onednn caching removed

* - Removed manual caching of activation

* - modified UT

* - fix

* - fix

* - fixes to building

* - fix

* - fix

* - fix to UT

* - Faulty UT workaround

* - approval workaround

* - Fixes after review

* - compilation fixes

* - more lint fixes

* - more fixes after review

* - fixes after another round of review

* - hopefully compilation fix

- compilation fix

This reverts commit 0a5c99e8.

* - Added softmax without caching

* - Binary is no longer manually cached

* - Activation onednn caching removed

* - Removed manual caching of activation

* - modified UT

* - fix

* - fix

* - fixes to building

* - fix

* - fix

* - fix to UT

* - Faulty UT workaround

* - approval workaround

* - Fixes after review

* - compilation fixes

* - more lint fixes

* - more fixes after review

* - fixes after another round of review

* add broadcast supporting for elementwise_add

* add broadcast supporting for elementwise_add

* add more tests

* remove the redundant code

* update

* fix place error in unittest

* remove skip.If