* 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

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

* add_int_pass

* add_int8_flag_pass

* add_int8_flag_pass

* fix CMakeLists.txt

* fix test_trt_fc_fuse_quant_dequant_pass.py

* fix python/paddle/fluid/tests/unittests/ir/inference/test_trt_fc_fuse_quant_dequant_pass.py

* fix test_trt_fc_fuse_quant_dequant_pass.py

* modify format

* modify format

This reverts commit b3f6eedb.

* [NPU] modify for model deepfm

* [NPU] unit test delete precision control

* [NPU] add more unit test

* revert elementwise_mul related modification

* [NPU] add more unit tests for concat

* change time to remove static tempfile

* delete remove_static_file() function

* autograd.functional passed pylint checker.

* autograd.functional: fix import errors.

* autograd.functional: fixed unit tests.

* autograd.functional minor format change

* [NPU] fix elementwise_mul to support broadcast, test=develop

* remove debug files, test=develop

* add axis support, test=develop

* [NPU] add int64 kernel for scale and slice, test=develop

* remove int64 for scale, test=develop

* fix calling bug of HybridParallelClipGrad

* fix bugs of HybridParallelClipGrad

* add unittest of pp with HybridParallelClipGrad

* fix bugs in mp_layers.py

* update

* fix bugs in pp_layers.py

* update

* Fix stop_gradient in RunProgramOp

* fix reference

* heterps:add fuse_allreduce op; test=develop
* add program_mode in minimize for pslib mode;test=develop

* add FLAGS_allreduce_record_one_event

* add more comments

* fix ut

* improve coverage

* fix ut, improve coverage

Add paddle.nn.functional.sparse_attention API

    本个PR主要将sparse_attention功能在python层进行了一层封装，OP的主体代码见：#PR35676

    此外，对于封装的python 接口，增加了相应的单测。

Sparse tensor core for convolution requires the input channel dimension is 2:4 structed sparse.
So we have to mask the input channel dimension for using sparse tensor core

* add reshard module

* fix conflict

* update reshard module

* update and add unitest

* update reshard module and unitest

* add more unitests

* enhance yolobox plugin

* [NPU] fix matmul_v2 and utils.run_check, test=develop

* remove debug files, test=develop

* fix install_check, test=develop

* fix doc, test=develop

* fix review comments, test=develop

* [NPU] fix set_value, test=develop

* fix typo, test=develop

* fix typo, test=develop

* add mish trt plugin, compile & install success, run error. test=develop
* modify code according to review
* add TRT_NOEXCEPT for mish trt plugin
* add unittest for mish trt plugin
* remove unnecessary check of mish in op_teller.cc
* fix some problem of trt8
* add check and modify unittest while converting mish to trt plugin
Co-authored-by: Ndengkaipeng <dengkaipeng@baidu.com>

* add skip case in trt converter ut

* disable group_norm trt plugin

Add use_cinn flag and use it to control whether we run PaddlePaddle using CINN.

Also add:

Replace PaddlePaddle graph with a CINN graph in a pass
PE Method to feed data and run the graph by CINN

* Add new API tensordot

* Set timeout value 400 for UT; Fix format for EN docs

* Set timeout value 1000 for UT; Fix format for EN docs

* Remove some input check

* Coding style improve: don't compare boolean values to True or False
using ==

* support ClipGradByGlobalNorm in sharding

* support ClipGradByGlobalNorm in sharding

* test=allcase

对于__getattr__重载后不满足条件的参数，全部抛出AttributeError异常，达到与未重载版本一致。

* support CUDA Graph on PE

* add ut, fix CI compile

* reduce memory consumption

* fix CUDA 10 CI

* improve coverage

* improve python coverage

* [NPU] support NCL and NCL for BatchNorm, test=develop

* [NPU] remove debug files, test=develop

* update, test=develop