Revert "Merge branch 'dev-ssl' into master"

This reverts commit f6e9262, reversing
changes made to 68e84a4.

Author: JunguangJiang

docs/dalib/benchmarks/re_identification.rst

@@ -16,7 +16,7 @@ We adopt cross dataset setting (another one is cross camera setting). The model
 
 For a fair comparison, our model is trained with standard cross entropy loss and triplet loss. We adopt modified resnet architecture from `Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification (ICLR 2020) <https://arxiv.org/pdf/2001.01526.pdf>`_.
 
-As we are given unlabelled samples from target domain, we can utilize clustering algorithms to produce pseudo labels on target domain and then use them as supervision signals to perform self-training. This simple method turns out to be a strong baseline. We use ``Baseline_Cluster`` to represent this baseline in our results.
+As we are given unlabeled samples from target domain, we can utilize clustering algorithms to produce pseudo labels on target domain and then use them as supervision signals to perform self-training. This simple method turns out to be a strong baseline. We use ``Baseline_Cluster`` to represent this baseline in our results.
 
 .. note::
 

docs/index.rst

@@ -80,10 +80,7 @@ Transfer Learning
     :caption: Semi Supervised Learning Methods
     :titlesonly:
 
-    ssllib/consistency_regularization.rst
-    ssllib/contrastive_learning.rst
-    ssllib/holistic_methods.rst
-    ssllib/proxy_label.rst
+    ssllib/semi_supervised_learning.rst
 
 
 

docs/ssllib/consistency_regularization.rst

@@ -32,12 +32,13 @@ and prepare them following [Documentation for Retinopathy](/common/vision/datase
 
 Supported methods include:
 
-- [Learning Without Forgetting (LWF, ECCV 2016)](https://arxiv.org/abs/1606.09282)
-- [Explicit inductive bias for transfer learning with convolutional networks (L2-SP, ICML 2018)](https://arxiv.org/abs/1802.01483)
+- [Explicit inductive bias for transfer learning with convolutional networks
+    (L2-SP, ICML 2018)](https://arxiv.org/abs/1802.01483)
 - [Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer Learning (BSS, NIPS 2019)](https://proceedings.neurips.cc/paper/2019/file/c6bff625bdb0393992c9d4db0c6bbe45-Paper.pdf)
 - [DEep Learning Transfer using Fea- ture Map with Attention for convolutional networks (DELTA, ICLR 2019)](https://openreview.net/pdf?id=rkgbwsAcYm)
 - [Co-Tuning for Transfer Learning (Co-Tuning, NIPS 2020)](http://ise.thss.tsinghua.edu.cn/~mlong/doc/co-tuning-for-transfer-learning-nips20.pdf)
 - [Stochastic Normalization (StochNorm, NIPS 2020)](https://papers.nips.cc/paper/2020/file/bc573864331a9e42e4511de6f678aa83-Paper.pdf)
+- [Learning Without Forgetting (LWF, ECCV 2016)](https://arxiv.org/abs/1606.09282)
 - [Bi-tuning of Pre-trained Representations (Bi-Tuning)](https://arxiv.org/abs/2011.06182?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+arxiv%2FQSXk+%28ExcitingAds%21+cs+updates+on+arXiv.org%29)
 
 ## Experiment and Results
@@ -77,52 +78,52 @@ If you use these methods in your research, please consider citing.
 
 ```
 @inproceedings{LWF,
-    author    = {Zhizhong Li and
+  author    = {Zhizhong Li and
                Derek Hoiem},
-    title     = {Learning without Forgetting},
-    booktitle={ECCV},
-    year      = {2016},
+  title     = {Learning without Forgetting},
+  booktitle={ECCV},
+  year      = {2016},
 }
 
 @inproceedings{L2SP,
-    title={Explicit inductive bias for transfer learning with convolutional networks},
-    author={Xuhong, LI and Grandvalet, Yves and Davoine, Franck},
-    booktitle={ICML},
-    year={2018},
+  title={Explicit inductive bias for transfer learning with convolutional networks},
+  author={Xuhong, LI and Grandvalet, Yves and Davoine, Franck},
+  booktitle={ICML},
+  year={2018},
 }
 
 @inproceedings{BSS,
-    title={Catastrophic forgetting meets negative transfer: Batch spectral shrinkage for safe transfer learning},
-    author={Chen, Xinyang and Wang, Sinan and Fu, Bo and Long, Mingsheng and Wang, Jianmin},
-    booktitle={NeurIPS},
-    year={2019}
+  title={Catastrophic forgetting meets negative transfer: Batch spectral shrinkage for safe transfer learning},
+  author={Chen, Xinyang and Wang, Sinan and Fu, Bo and Long, Mingsheng and Wang, Jianmin},
+  booktitle={NeurIPS},
+  year={2019}
 }
 
 @inproceedings{DELTA,
-    title={Delta: Deep learning transfer using feature map with attention for convolutional networks},
-    author={Li, Xingjian and Xiong, Haoyi and Wang, Hanchao and Rao, Yuxuan and Liu, Liping and Chen, Zeyu and Huan, Jun},
-    booktitle={ICLR},
-    year={2019}
+  title={Delta: Deep learning transfer using feature map with attention for convolutional networks},
+  author={Li, Xingjian and Xiong, Haoyi and Wang, Hanchao and Rao, Yuxuan and Liu, Liping and Chen, Zeyu and Huan, Jun},
+  booktitle={ICLR},
+  year={2019}
 }
 
 @inproceedings{StocNorm,
-    title={Stochastic Normalization},
-    author={Kou, Zhi and You, Kaichao and Long, Mingsheng and Wang, Jianmin},
-    booktitle={NeurIPS},
-    year={2020}
+  title={Stochastic Normalization},
+  author={Kou, Zhi and You, Kaichao and Long, Mingsheng and Wang, Jianmin},
+  booktitle={NeurIPS},
+  year={2020}
 }
 
 @inproceedings{CoTuning,
-    title={Co-Tuning for Transfer Learning},
-    author={You, Kaichao and Kou, Zhi and Long, Mingsheng and Wang, Jianmin},
-    booktitle={NeurIPS},
-    year={2020}
+  title={Co-Tuning for Transfer Learning},
+  author={You, Kaichao and Kou, Zhi and Long, Mingsheng and Wang, Jianmin},
+  booktitle={NeurIPS},
+  year={2020}
 }
 
 @article{BiTuning,
-    title={Bi-tuning of Pre-trained Representations},
-    author={Zhong, Jincheng and Wang, Ximei and Kou, Zhi and Wang, Jianmin and Long, Mingsheng},
-    journal={arXiv preprint arXiv:2011.06182},
-    year={2020}
+  title={Bi-tuning of Pre-trained Representations},
+  author={Zhong, Jincheng and Wang, Ximei and Kou, Zhi and Wang, Jianmin and Long, Mingsheng},
+  journal={arXiv preprint arXiv:2011.06182},
+  year={2020}
 }
 ```