[Doc] Update link to correct destination. (#3966)

* Update link to correct destination.

* Update 4_rgcn.py

* Update 4_rgcn.py

* Update tutorials/models/1_gnn/4_rgcn.py

* Update tutorials/models/1_gnn/4_rgcn.py

* Update tutorials/models/1_gnn/4_rgcn.py
Co-authored-by: Rhett Ying <85214957+Rhett-Ying@users.noreply.github.com>

tutorials/models/1_gnn/4_rgcn.py

@@ -60,7 +60,7 @@ multiple edges among any given pair.
 #
 # This tutorial focuses on the first task, entity classification, to show how to generate entity
 # representation. `Complete
-# code <https://github.com/dmlc/dgl/tree/rgcn/examples/pytorch/rgcn>`_
+# code <https://github.com/dmlc/dgl/tree/master/examples/pytorch/rgcn>`_
 # for both tasks is found in the DGL Github repository.
 #
 # Key ideas of R-GCN
@@ -361,5 +361,5 @@ for epoch in range(n_epochs):
 #
 # The implementation is similar to that presented here, but with an extra DistMult layer
 # stacked on top of the R-GCN layers. You can find the complete
-# implementation of link prediction with R-GCN in our `Github Python code example
-#  <https://github.com/dmlc/dgl/blob/master/examples/pytorch/rgcn/link_predict.py>`_.
+# implementation of link prediction with R-GCN in our `Github Python code
+# example <https://github.com/dmlc/dgl/blob/master/examples/pytorch/rgcn/link.py>`_.