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@@ -38,7 +38,7 @@ You can find some research projects that are built on top of Torchreid `here <ht
 
 What's new
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-- [Apr 2020] Upgraded to `1.2.0`. The engine class has been made more model-agnostic to improve extensibility. See [Engine](torchreid/engine/engine.py) and [ImageSoftmaxEngine](torchreid/engine/image/softmax.py) more details. Credit to [Dassl.pytorch](https://github.com/KaiyangZhou/Dassl.pytorch).
+- [Apr 2020] Upgraded to ``1.2.0``. The engine class has been made more model-agnostic to improve extensibility. See `Engine <torchreid/engine/engine.py)>`_ and `ImageSoftmaxEngine <torchreid/engine/image/softmax.py>`_ more details. Credit to `Dassl.pytorch <https://github.com/KaiyangZhou/Dassl.pytorch>`_.
 - [Dec 2019] Our `OSNet paper <https://arxiv.org/pdf/1905.00953v6.pdf>`_ has been updated, with additional experiments (in section B of the supplementary) showing some useful techniques for improving OSNet's performance in practice.
 - [Nov 2019] ``ImageDataManager`` can load training data from target datasets by setting ``load_train_targets=True``, and the train-loader can be accessed with ``train_loader_t = datamanager.train_loader_t``. This feature is useful for domain adaptation research.