use the rst syntax.

Author: ParagEkbote

beginner_source/basics/autogradqs_tutorial.py

@@ -133,7 +133,8 @@
 #   - To mark some parameters in your neural network as **frozen parameters**.
 #   - To **speed up computations** when you are only doing forward pass, because computations on tensors that do
 #     not track gradients would be more efficient.
-# See this `note<https://docs.pytorch.org/docs/stable/notes/autograd.html#locally-disabling-gradient-computation>` for additional reference. 
+# See this `note <https://docs.pytorch.org/docs/stable/notes/autograd.html#locally-disabling-gradient-computation>`_
+# for additional reference. 
 
 ######################################################################
 
@@ -163,10 +164,10 @@
 # To get a sense of what this computational graph looks like we can use the following tools:  
 #
 # 1. torchviz is a package to visualize computational graphs  
-# `<https://github.com/szagoruyko/pytorchviz>`
+# `pytorchviz <https://github.com/szagoruyko/pytorchviz>`_
 #
 # 2. TORCH_LOGS="+autograd" enables logging for the backward pass. 
-# `<https://dev-discuss.pytorch.org/t/highlighting-a-few-recent-autograd-features-h2-2023/1787>`
+# `<https://dev-discuss.pytorch.org/t/highlighting-a-few-recent-autograd-features-h2-2023/1787>`_
 #
 #
 # .. note::