* [NPU] add index_select_grad kernel and unit tests

* dim=0 not need transpose

* fix DataLoader exit with SIGABRT/SIGSEGV. test=develop

* Support new API linalg.cond in paddle

* check code style

* check code style

* modify codes

* add docs_eng of linalg.cond

* add svd_norm for linalg.cond

* modify docs_en of cond

* add support for empty input in dynamic mode

* modify set_time of unittest

* update

* modify unittest of cond

* update

* remove cond in paddle.__all__

* pull latest codes

* merge latest codes

* update

* remove autograd/grad api

* import grad, no_grad set_grad_enable from autograd module

* modify import no_grad_ as no_grad

* fix gather

* fix

* fix no_grad context error in dy2stat

* remove useless comments

* fix error by drop_kids in python

* add test and fix review

* support fp16 dtype

* update

PR主要功能：针对fusion等子图替换场景，支持Python侧开发并注册Pass。

背景
Pass是指输入一个深度学习计算图Graph，依照一定条件进行修改，输出修改后的Graph的过程；
当前PaddlePadle框架编写Pass代码存在以下问题：
用户需要手写Graph的条件匹配、在Graph上的修改代码；
对Graph操作需要深入底层框架代码，了解Graph的结构，并且知道相关Pass写法；
我们提出了针对fusion等子图替换类Pass的优化方案以支持用户在Python侧开发注册Pass，提升二次开发体验：
用户只需要输入匹配和替换的子图描述，由深度学习框架编写的代码来生成匹配和替换的逻辑，不需要用户对Graph进行匹配和替换操作；
API级别的替换，用户可以通过Paddle的Python API构造子图，从而不需要知道Graph的结构，也能写Paddle的Graph Pass代码

Fix docs in stream_guard API 

* fixed slice error

* added handling of StartsTensor+List and EndsTensor+List

* fix for ppyolo model

* add inplace logic into new_executor, test=develop

* check shape and add inplace FLAGS, test=develop

* refine, test=develop

* refine, test=develop

* clip op extra information when export model,test=ocr

* rename clip_extra parameter to kwargs in save_inference_model, test=ocr

* Change the invoking method of settiem from numpy to set_value op when value is not tensor

* fix the check logic for inplace in setitem

* fix the unittest problem caused by setitem doesn't support fp16

* modify some code format in setitem

* add dist_attr for dist op

* add unitest

* update inputname

* update function name

* add unitest

* update CMakeLists.txt for CI

* fix dis_matmul

* fix compile error

* update matmul to matmul_v2

Put Nvidia's cusparse library into paddle.

* add beam_search npu op

* fix CMakeList and add unittest

* fix bug of beam search npu op

* fix unittest

* let input ids become int64

* set output ids to int64_t

* delete check_dygraph

* fix beam_width=1

* support numpy.ndarray index.

* polish code.

* [NPU] fix depthwise_conv2d_grad, test=develop

* remove debug files, test=develop