modify link

Author: thucbx99

dalib/adaptation/adda.py

@@ -14,7 +14,8 @@ class DomainAdversarialLoss(nn.Module):
     <https://arxiv.org/pdf/1702.05464.pdf>`_.
     Similar to the original `GAN <https://arxiv.org/pdf/1406.2661.pdf>`_ paper, ADDA argues that replacing
     :math:`\text{log}(1-p)` with :math:`-\text{log}(p)` in the adversarial loss provides better gradient qualities. Detailed
-    optimization process can be found at `examples/domain_adaptation/image_classification/adda.py`.
+    optimization process can be found `here
+    <https://github.com/thuml/Transfer-Learning-Library/blob/master/examples/domain_adaptation/image_classification/adda.py>`_.
 
     Inputs:
         - domain_pred (tensor): predictions of domain discriminator

docs/dalib/adaptation/domain_adversarial.rst

@@ -34,8 +34,8 @@ ADDA: Adversarial Discriminative Domain Adaptation
 .. autoclass:: dalib.adaptation.adda.DomainAdversarialLoss
 
 .. note::
-    ADDAgrl is also implemented and benchmarked. You can find code at
-    `examples/domain_adaptation/image_classification/addagrl.py`.
+    ADDAgrl is also implemented and benchmarked. You can find code
+    `here <https://github.com/thuml/Transfer-Learning-Library/blob/master/examples/domain_adaptation/image_classification/addagrl.py>`_.
 
 
 .. _BSP: