* fix for matmul_v2 broadcasting

* fix for output shape not broadcasted

* c_api support std::string

* update

* update

* add NOTE

* fix delete error.

* Quantize nearest_interp and nearest_interp_v2

* Check if avx_core supported

* Add depthwise_conv2d to supported quantization list

* add huber_loss for kunlun

* update xpu.cmake

* update unitests

* update unitests

* update elementwise_add

* update elementwise_add

* update elementwise_add

* Support EagerTensor init with kwargs

* Updated comments

* Updated unit tests case

* Refactor InitTensor related code to reduce duplicate code

* Updated the error reporting msg

* Updated VLOG msg

* Merge develop and Update EagerTensor init func

* Polish switch case, reduce some code

* Add SyntaxError unit test case

* Refactor the related initialization func of EagerTensor

* Remove ParseStopGradient and ParseZeroCopy and ParsePersistable, construct ParseBooleanArgs instead.

* Updated error msg to pass CI

* Updated PADDLE_ENFORCE error type

* 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

Add OpFunctor and replace cast, scale, clip, bce_loss and abs_grad with elementwise_no_broadcast (#38500)

* Fix memcpyD2H sync behavior with other stream

* add wait

* add wait

* add wait

* change 'math' to 'math_kernel'

* fix compile bugs

* merge develop

* fix compile bugs

* move cpu_impl of elementwise kernel to new directory

[NPU] add pad and pad_grad

[Unify Tensors PR #3]Port framework::Tensor members & interfaces to pten::DenseTensor, test=allcases (#38473)

* Added shared_ptr<Allocation> member & corresponding interfaces to Storage

* Removed original pten::Allocation from Storage and adjusted the interfaces accordingly

* Fixed issues with storage offset

* Used place to malloc allocation for TensorStorage

* [Unify Tensors PR #3]Ported framework::Tensor interfaces to pten::DenseTensor

* Fixed issues with place

* Added comments

* Moved mutable_data with stream argument to DenseTensor

* Added set_offset interface

* Fixed CI issues,test=allcases

* [Unify Tensors PR #4] Port LoDTensor interfaces to DenseTensor

* Reverted changes too pten_layout() interface

* Removed friend classes

* move inner cast api to cast_kernel.h

* resolve conflit

heter context support dynamic mf dim

* [XPU]add split op for kunlun2,*test=kunlun

* [XPU]add split op for kunlun2,*test=kunlun

* [XPU]add split op for kunlun,*test=kunlun
Co-authored-by: NQingshuChen <chenqingshu@baidu.com>

* add new api/op kthvalue

* kthvalue cuda kernel to cub sorting

* fix example code error

* throw errors instead of LOG in cuda sort

* throw errors by Paddle_ENFORCE

* add mul_gru_fuse_pass ut

* update ut

* update ut

* update ut timeout setting

* update ut

* glog fix

* changed approach

* 6 dims fix

* removed limitations of max dims

* change 'math' to 'math_kernel'

* fix compile bugs

* merge develop

* fix compile bugs

* fix compile bugs

* [MLU]support calling mlu op from python interface

* [MLU]fix

* fix

* [mlu]fix mlu_places

* [mlu]fix required mlu

* fix

* [MLU]fix tensor copy

* [mlu] fix MLUPlace call path

* add fold opereators, test=develop

* add fold opereators, test=develop

* add fold opereators, test=develop

* update fold op error test, test=develop

* fix unitext, test=develop

* fix unitext, test=develop

Paddle new APIs: put_along_axis.

Xu Huang is on holiday so we created this PR to work on it. It is based on his PR: https://github.com/PaddlePaddle/Paddle/pull/37921

* unify data layout

* fix test_transfer_layout error

* change 'math' to 'math_kernel'

* fix compile bugs

* merge develop

* fix compile bugs

LGTM

* add sigmoid cross entropy with logits to kl1. test=kunlun

* add sigmoid cross entropy with logits to kl1. test=kunlun

Add exp, abs_grad, reciprocal, reciprocal_grad operator for XPU and update xpu2_op_list.h,test=kunlun (#38570)

This PR adds runtime flags run_kp_kernel, which choose which op to run for xpu2. There are two: dynamic linked and built from kp.