* add deformable_conv op on xpu (#29234)

* rebase develop

* update deformable_conv op on xpu

* update deformable_conv op on xpu

* update kunlun conv2d/softmax/elementwise implemetation (#29229)

* update conv2d & softmax to new xpu api
* test=kunlun

* remove useless comments
* test=kunlun

* remote softmax xpu op
* test=kunlun

* update kunlun softmax
* test=kunlun

* update xpu unitest
* test=kunlun

* fix elementwise_grad bug for kunlun
*test=kunlun

* support global pooling for kunlun (#29293)

* test=kunlun

* update reduce_sum op on xpu (#29367)

* update reduce_sum op on xpu

* update reduce_sum op on xpu

* support running on xpu

* fix expand/uniform_random && concat/transpose to new api on xpu (#29280)

* fix expand && concat/transpose to new api

* update uniform_random_op

* update xpu_header

* 1. fix elementwise ops'bug 2. fix softmax_with_cross_entropy_op 3. add biliner_interp_op (#29448)
Co-authored-by: Nroot <root@bjhw-sys-rpm0223.bjhw.baidu.com>
Co-authored-by: N卖鱼的哲学 <tangzhiyi11@users.noreply.github.com>
Co-authored-by: NQingshuChen <qingshu.chen714@gmail.com>
Co-authored-by: Ntaixiurong <taixiurong@126.com>
Co-authored-by: Nroot <root@bjhw-sys-rpm0223.bjhw.baidu.com>

* fix random failed of complex matmul

* Make transpose, trace, kron, reshape, sum op support complex type (#29321)

* add complex64 and complex128 type; add +-*/@ and slice opreator for complex types

* add test cases for complex elementwise, matmul and getitem unittest

* add test cases for complex types

* add test cases for complex matmul unittest

* kron, reshape, transpose support complex types

* sum and trace op support complex types

* add test case of sum and trace op

* fix the bug of imag part of complex not initialized

* format file

* format code style

* kron support type promotion; modify test cases

* basic impl of type promote

* add comment & another testcase

* fix complex bugs & support python op promote type

* fix failed unittests & polish code

* add unittest for coverage

* change to only promote complex type

* polish code details

* polish several comments

* add complex64 and complex128 type; add +-*/@ and slice opreator for complex types

* add test cases for complex elementwise, matmul and getitem unittest

* add test cases for complex types

* add test cases for complex matmul unittest

* add reducer

* refine envent for memorycopy

* add concat&split for allreduce

* apply concat & split for fuse tensor

* fix nccl dep

* fix the untest, compile problem and ddp initialize problem

* fix untest for mac & add some comments & solve the repeated param in sublayers

* fix untest for windows & fix document

* remove -DSUPPORTS_CUDA_FP16 in cuda.cmake

* comile with cuda9

* add some unittest

* notest;test=coverage

* add unittest for trt plugin swish && split

* update ernie unittest

* fix some error message

* remove repeated judgement of CUDA version in mbEltwiseLayerNormOpConverter

* fix comile errror when CUDA_ARCH_NAME < Pascal"

* fix comile error

* update unittest timeout

* compile with cuda9

* update error msg

* fix code style

* add some comments

* add define IF_CUDA_ARCH_SUPPORT_FP16

* rename IF_CUDA_ARCH_SUPPORT_FP16 to CUDA_ARCH_FP16_SUPPORTED

* default not show cpp statck & add hint

* fix failed unittest

* fix failed unittests

remove eigen threadpool for the speed up

* change avg pooling and global pooling to trt layer

* add support for static shape global pooling

* modify trt errmsg

* adjust kunlun header file
*test=kunlun

* update kunlun unittest
*test=kunlun

* update xpu unitest
* test = kunlun

* update xpu unittest
* test=kunlun

* update xpu unitest
* test=kunlun

* fp16 result ok

* change -DWITH_NVINFER_PLUGIN toconfig.EnableTensorRtOSS

* auto detect special slice op converter for ernie with trt oss

* ernie oss only support fp16

* fix special_slice_plugin serialize bug

* matmul in tensorrt ok

* ernie unittest ok

* add matmul tensorrt unittest

* remove demo code

* Add rnn_op.
test=develop

* Fix rnn_op grad maker's drop_empty_grad.
test=develop

This PR is follow up of #28213. On that PR we tried to decrease GPU usage, however the CI still randomly failed. So I added retry logic for the initialization of nccl and cusolver. If the initialization failed, we can retry to avoid the random failure.

* add multiple exception type

* define all exception & polish compile pystack

* mapping paddle error to python exception

* polish static mode error format

* fix failed unittests

* fix dytostatic test_error

* fix check_nan_inf failed

* add unittest for coverage

* revert some code try to solve compile error

* refactor enforce & error change

* polish code & add unittest

* add compile limit for paddle enforce

* polish elementwise_op_function.cu.h

* fix failed unittest

* fix windows compile failed

* detail polish

* revert no type constructor

* conv dilated mkldnn support: forward and backward pass

* add mkldnn conv_transpose dilation UT
test=develop

* remove unnecessary PADDLE_ENFORCE

* add int8 and bf16 dilated conv UT

* update according to reviews

* use exhaustive_search for float16

* tune algo only when dtype is float16

* - condidate fix to issue #25537

test=develop

* - UT for transpose NHWC

test=develop

* Add avx instructions check

* Small fix

* Change function name

* Change uint to unsigned int