* bug fix for  DeserializeSelectedRows. test=develop

* fix bug for SerializeSelectedRows. test=develop

* update. test=develop

Add CINN compile option in CMake.

Now you can use CINN in Paddle by `-DWITH_CINN=ON` when `cmake`

To test it, you can run `make cinn_lib_test -j` and `ctest -R cinn_lib_test`. 

Note:
1. You should set
```
export runtime_include_dir=${CINN_SOURCE_DIR}/cinn/runtime/cuda 
```
When run test, the `${CINN_SOURCE_DIR}` should be set based on your CINN directory.

2. CINN is under developing now, you may have to change `CINN_GIT_TAG` to the git commit you need.

* fix

* remove const

* Support elementwise_add triple grad Kernel

* Change code-format to follow CI std

* [NPU] Add iou_similarity op

* [NPU] Add iou_similarity op

* [NPU] Add iou_similarity op

* [NPU] update inference cmake, test=develop

* address review comments, test=develop

* fix compile error when WITH_ASCEND_CXX11 ON, test=develop

* update

* fix ut error

* update ut

* add feed op and new var for the generated subgraph

* perfect the test script of build_cinn_pass 

* remove useless clear and perfect some annotation

* add nearest_interp_v2 trt plugin

* fix replicate pad when input size is 0
* add unit test

* Add QR decomposition op

* Change codes to adapt to new svd_helper

* Update linalg.py

Restore the deleted comma

* Restore the deleted line

* Update linalg.py

* Update linalg.py

* Improve the qr code by reviews

* Update QR based on CI results

* Update qr doc, test=document_fix

* Change unsafe and ill-formed codes

* add pow2_warmup op

* remove contrib __all__

* add AttrT

* rename

* follow comments

* fix duplicate PADDLE_RESTRICT

* added softplus

* refactored softplus op

* deleted unnecessary file

* added missing file

* added formatting

* disabled tests if GPU is used

* added reviewer suggestion

* unified softplus kernel

* add_quant_axis

* add_quant_axis

* --amend

* Update quant_conv2d_dequant_fuse_pass.cc

* fix async_read bug

* change index place to cpu

* add tensor size judge

* add async_read & async_write test

* fix bug in async_write

* fix mac py3 ci

* fix bug for cpu version paddle

* fix windows ci bug

* change input argument error type

* change const_cast to mutable_data

* add async_write out-of-bound check and consumate error hint

* fix a small bug for dst_tensor

* add docs and refine codes

* refine docs

* notest,test=windows_ci

* fix windows ci

* fix require

* fix code-block

* add core.is_compiled_with_cuda()

[XPU AMP] 1. xpu support gradient acc 2. xpu support create tensor in dygraph 3. xpu support update weight params in amp (#36439)

* remove wrong restrict

* remove master_param_out __restrict__

* update

* Add CinnSubgraphSearchPass

* solve CI problem of subgraph order not same

* fix some bug by review advices

* ensure the independently of subgraph, that mean the subgraph should not have link to out-graph

* rename cinn_subgraph_search_pass to build_cinn_pass and delete paddle_to_cinn_pass

* add flag to control wheter append build cinn pass

* remove AppendPass at ParallelExecutorPassBuilder

* rename paddle_to_cinn_pass to build_cinn_pass in build_strategy and close test_run_from_cinn

* native commit for triple grad of sigmod

* Updated unittests files

* init functional jacobian api

* Updated trible_test func

* Updated gradient_checker & test_script

* finish test with dtype float32

* add float64 test case

* polish code

* use atol=1e-5 with dtype float64

* fix for ci

* set timeout for test_jacobian

* fix dygraph grad to support high differential

* polish API docstring

* Updated gradient checker and some related files

* fix double grad strip error for high differential

* fix double grad strip error for high differential

* Add Sigmoid triple grad tests

* fix dygraph double grad dtype error when calling for high differential senario

* Updated triple grad teses func

* Use np.random to initialize ddx

* Updated triple_grad_check func

* add todo for gradient checker and refine some comments

* remove additional code

* add test for warnging in backward.py

* add tanh triple grad

* format python code

* refine code
Co-authored-by: Nveyron95 <veyron_wu@163.com>
Co-authored-by: Nlevi131 <limaolin01@baidu.com>

* support bert when exists matmul_v2

* update