* qkv

* ci_test

* in NPU environment, use CPUPlace for missing operators.

* in NPU environment, use CPUPlace for missing operators.

* fix TensorCopy bug and add unit test.

* fix code style.

* add more unit tests.

* - fix to #33282

* - Increased threshold for elementwise_mul_bf16 grad

* -disabled faulty UT

* - fix to approval

* add trt LT version helper

* trt8 requires void** to be void* const*

* Modify the search order of dynamic library

* Modify the search order of dynamic library

* add trt LT version helper

* remove deprecated nvinfer1::DimsCHW and replace it to nvinfer1::Dims3

* remove deprecated nvinfer1::DimsNCHW and replace it to nvinfer1::Dims4

* update deserialize engine

* update to createNetworkV2

* update to createNetworkV2

* update buildWithConfig and remove redundent config settings

* replace createNetwork to createNetworkV2

* fix int8

* addMatrixMultiply

* remove unnecessary const cast

* IBuilder->setInt8Calibrator() is deprecated

* auto enable fp16 when using int8

* remove the redundant line

As the title

* tmp

* pass con_element_add2_act

* recover unittests CMakeLists

* init pass enhance

* fix the attr according to review

* repair the attr conv2d

* repair axis of elementwise_add

* CI-coverage test=allcase

* repari some attr

* recover batch_norm_act

* conv_elementwise_add2_act_fuse

* base changes for split op

* 90% of split functionality added

* full fp32 functionality

* added bf16 test

* added submemory caching

* added bf test to static mode whitelist

* minor change

* enabled split op for inference

* minor fix

* minor fix

* optimize attr default value, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* fix bug in AttrReader, test=develop

* fix bug, test=develop

* fix double_grad, test=develop

* refine, test=develop

* refine, test=develop

* fix checker null, test=develop

* for test, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* fix bug about deallocating None, test=develop

* new api diagonal, test=develop

* add new api diagonal, test=develop

* new api diagonal, test=develop

* add new api paddle.diagonal, test=develop

* use framework::stride replace ComputeDimStride

* replace cudaMalloc/cudaMemcpy by TensorFormVector in cudaKernel and cudaGradKernel

* perfect funciton: when attr(offset) is exceed attr(axis1) or attr(axis2), set the diagonal dim is 0

* fix RP-Mac-CI bug: replace framework::stride() by ComputDimStride.

* perfect code-block

* perfect code of python API diagonal

* api supports dtype of float16 and bool

* api supports dtype of float16 and bool

* modify unittest code

* modify unittest code

* perfect dtype describe

* perfect code-block

* using argparse to handle selections

* 2 TODOs

* 先不更改pipeline配置，这里强制改成GPU版本

* sorted the all_names

* exec gpu sample codes tests incrementally

* get all apis from the pr.spec file

* condition with WITH_GPU

WITH_GPU == ON

save

* delete the useless codes

* delete the useless codes.

test=document_fix

* echo the diff result

test=document_fix

* dont reuse the variables

* rename fun to _func not work. put it into the skiplist

https://github.com/PaddlePaddle/Paddle/commit/038ffc795025170e8cda74bcd473b46301b9a1c0
test=document_fix

* skip it in check api approvals

test=document_fix

save

* skip the private _variables

* print signatures wrong. now rename it to _func

test=document_fix

* Add oneDNN AXPY handler.

* Add fallback for small tensors.

* Fix ifdefs

* Remove unnecessary namespace prefixes and add missing headers.

* Guard handler_axpy with proper ifdefs.

* Compilation of this function is possible only when Paddle is not build
with CUDA nor HIP.

* Move AXPY handler code to separate files.

* Use oneDNN AXPY handler in SGD op.

* Use axpy handler only when Paddle is built with oneDNN.

* Add test for SUM BF16 with big rows.

* Fix SFINAE rules for elementwise_add_to.

* Add test case for SGD with big rows.

* update

* update
Co-authored-by: NAdam Osewski <adam.osewski@intel.com>

* use BatchMatMul

* replace TensorCopy with ShareDataWith

* remove check fp16 grad

* fix format

* add grad_check

* fix grad check

* Combine amp and qat
* add unit test