* 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

* move dot_dev api into dot_kernel.h

* add infermate header

* modify to dotkerel in dot_op.h

* mvoe conj dev api into complex_kernel.h

* move sign dev api into  sign_kernel.h

* move scale dev api into kernel.h and remove infermete.h

* rm paddle/pten/include/math.h

* rm paddle/pten/include/math.h

* rm include dir

* rm paddle/pten/include/math.h

* fix conflict with develop branch

* rm devContext in conj_op.h

* add the missing complex_kernel header

* refactor the impl of elementwise grad kernel

* refactor impl of elementwise grad kernel(cuda)

* fix compile bugs

* fix bug when inplace strategy

* fix

* fix

* fix

* fix

* fix

* move gpu_impl of elementwise kernel

* change copyright to 2022

* add elementwise div

* move mul and div grad functor

* Combine multiple CUDA kernels

* Update the reduce interface call

* add multi-output

* add multi-output div

* add branch judge

* Package branch

* Combine the x and y functions into one

* change 'math' to 'math_kernel'

* fix compile bugs

* merge develop

* fix compile bugs

* move cpu_impl of elementwise kernel to new directory

* add complex op and `paddle.complex`.

test=document_fix

* refine structure for cuda and rocm

* update

* update

* update

* update

* 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

* 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

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)

* enhance error message when x or y is empty in elementwise_op

* format code

* format code

* [ROCM] fix test_gru_rnn_op

* [ROCM] fix test_expand_op

* [ROCM] fix test_cross_entropy_loss

* [ROCM] fix test_conv_nn_grad

* [ROCM] fix test_bilinear_tensor_product_op

* [ROCM] fix elementwise_op_function

* [ROCM] fix test_lstm_cudnn_op

* [ROCM] fix test_gpu_package_without_gpu_device

* [ROCM] fix test_gru_unit_op

* [ROCM] fix test_imperative_optimizer

* [ROCM] fix rnn

* [ROCM] fix group_norm_op

* [ROCM] fix test_pool3d_api

* [ROCM] fix test_pool3d_op

* [ROCM] update fluid elementwise op for rocm (part10), test=develop

* update, test=develop

* address review comments, test=develop

fix the broadcast for the large second input 

reduce the  occupied size  of memory for the fused pattern of elementwise_add Op and activation Op(relu Op for example) (#29885)

test=develop

* Remove the error in the elementwise op, use the backup mode to calculate

* add new macro BOOST_GET_SAFELY & unittests, test=develop

* add different macro type, test=develop

* fix get macro type in executor, test=develop

* four macro part change backup

* using one macro for all case, test=develop

* revert attribute change, test=develop

* change to three func to solve gcc4.8 bug, test=develop

* polish some details, test=develop

Those ops add the kernel message enhancement, as follows
paddle.fluid.layers.elementwise_add	
paddle.fluid.layers.elementwise_div
paddle.fluid.layers.elementwise_floordiv
paddle.fluid.layers.elementwise_max	
paddle.fluid.layers.elementwise_min	
paddle.fluid.layers.elementwise_mod	
paddle.fluid.layers.elementwise_mul	
paddle.fluid.layers.elementwise_pow	
paddle.fluid.layers.elementwise_sub

elementwise function used before definition then failed in cuda 8, move it ahead.

* improve elementwise performance.

* Add contiguous check, test=develop

* Improve elementwise performance.

Elementwise performace is poor as walk into CommonGradBroadcastCUDA, add some new kernels for different data pattern.

* Add some cuda kernel to speedup common broadcast cases. test=develop

* Add more test cases and fix cuda kernel bug. test=develop

* Remove tests as cpu percision fails.test=develop

* Refine SplitDims, test=develop

* Change file mode, test=develop