* add self-hosted repo:
* add extra requirements for different field and reduce necessary requirements
* update docker file with so required by audio
* add requirements checker which will be used later when implement lazy import
* remove repeated requirements and replace opencv-python-headless with opencv-python

example usage:
```shell
pip install model_scope[all] -f https://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/release/maas/repo.html
pip install model_scope[cv] -f https://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/release/maas/repo.html
pip install model_scope[nlp] -f https://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/release/maas/repo.html
pip install model_scope[audio] -f https://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/release/maas/repo.html
pip install model_scope[multi-modal] -f https://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/release/maas/repo.html

```
Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9211383

1.  refactor maaslib to modelscope
2.  fix UT error
3.  support pipeline which does not register default model

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/8988388

1. add build_doc linter script
2. add sphinx-docs support
3. add development doc and api doc
4. change version to 0.1.0 for the first internal release version

Link: https://code.aone.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/8775307

* add preprocessor module
 * add model base and builder
 * update task constant
 * add load image preprocessor and its dependency
 * add pipeline interface and UT covered
 * support default pipeline for task
 * add image matting pipeline
 * refine nlp tokenize interface
 * add nlp pipeline 
 * fix UT failed
 * add test for Compose

Link: https://code.aone.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/8769235

* add preprocessor module

* add test for Compose

* fix citest error

* fix abs class error

* add model base and builder

* update task constant

* add load image preprocessor and its dependency

* add pipeline interface and UT covered

* support default pipeline for task

* refine models and pipeline interface

* add pipeline folder structure

* add image matting pipeline

* refine nlp tokenize interface

* add nlp pipeline 

1.add preprossor model pipeline for nlp text classification
2. add corresponding test

Link: https://code.aone.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/8757371

* new nlp pipeline

* format pre-commit code

* update easynlp pipeline

* update model_name for easynlp pipeline; add test for maas_lib/utils/typeassert.py

* update test_typeassert.py

* refactor code

1. rename typeassert to type_assert
2. use lazy import to make easynlp dependency optional
3. refine image matting UT

* fix linter test failed

* update requirements.txt

* fix UT failed

* fix citest script to update requirements

* add constant
 * add logger module
 * add registry and builder module
 * add fileio module
 * add requirements and setup.cfg
 * add config module and tests
 * add citest script

Link: https://code.aone.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/8718998