[Fix]: Fix lint (#18)

.github/workflows/publish-to-pypi.yml

@@ -19,4 +19,4 @@ jobs:
       - name: Publish distribution to PyPI
         run: |
           pip install twine
-          twine upload dist/* -u __token__ -p ${{ secrets.pypi_password }}
+          twine upload dist/* -u __token__ -p ${{ secrets.pypi_password }}

README.md

@@ -6,7 +6,7 @@
 [![badge](https://github.com/open-mmlab/mmselfsup/workflows/build/badge.svg)]()
 [![codecov](https://codecov.io/gh/open-mmlab/mmselfsup/branch/master/graph/badge.svg)]()
 [![license](https://img.shields.io/github/license/open-mmlab/mmselfsup.svg)]()
-  
+
 </div>
 
 ## Introduction

docs/tutorials/6_benchmarks.md

@@ -94,7 +94,7 @@ Remarks:
 
 ## Detection
 
-Here we prefer to use MMDetection to do the detection task. First, make sure you have installed [MIM](https://github.com/open-mmlab/mim), which is also a project of OpenMMLab. 
+Here we prefer to use MMDetection to do the detection task. First, make sure you have installed [MIM](https://github.com/open-mmlab/mim), which is also a project of OpenMMLab.
 ```shell
 pip install openmim
 ```
@@ -127,7 +127,7 @@ bash run.sh ${DET_CFG} ${OUTPUT_FILE}
 ```
 ## Segmentation
 
-For semantic segmentation task, we are using MMSegmentation. First, make sure you have installed [MIM](https://github.com/open-mmlab/mim), which is also a project of OpenMMLab. 
+For semantic segmentation task, we are using MMSegmentation. First, make sure you have installed [MIM](https://github.com/open-mmlab/mim), which is also a project of OpenMMLab.
 
 ```shell
 pip install openmim

docs_zh-CN/tutorials/6_benchmarks.md

@@ -94,7 +94,7 @@ Remarks:
 
 ## Detection
 
-Here we prefer to use MMDetection to do the detection task. First, make sure you have installed [MIM](https://github.com/open-mmlab/mim), which is also a project of OpenMMLab. 
+Here we prefer to use MMDetection to do the detection task. First, make sure you have installed [MIM](https://github.com/open-mmlab/mim), which is also a project of OpenMMLab.
 ```shell
 pip install openmim
 ```
@@ -127,7 +127,7 @@ bash run.sh ${DET_CFG} ${OUTPUT_FILE}
 ```
 ## Segmentation
 
-For semantic segmentation task, we are using MMSegmentation. First, make sure you have installed [MIM](https://github.com/open-mmlab/mim), which is also a project of OpenMMLab. 
+For semantic segmentation task, we are using MMSegmentation. First, make sure you have installed [MIM](https://github.com/open-mmlab/mim), which is also a project of OpenMMLab.
 
 ```shell
 pip install openmim

setup.cfg

@@ -8,7 +8,7 @@ line_length = 79
 multi_line_output = 0
 known_standard_library = setuptools
 known_first_party = mmselfsup
-known_third_party = PIL,detectron2,faiss,matplotlib,mmcv,mmdet,numpy,packaging,pytest,scipy,seaborn,six,sklearn,svm_helper,torch,torchvision,tqdm
+known_third_party = PIL,detectron2,faiss,matplotlib,mmcv,mmdet,numpy,packaging,pytest,pytorch_sphinx_theme,scipy,seaborn,six,sklearn,svm_helper,torch,torchvision,tqdm
 no_lines_before = STDLIB,LOCALFOLDER
 default_section = THIRDPARTY