fix:link syntax.

Author: ParagEkbote

beginner_source/basics/autogradqs_tutorial.py

@@ -133,7 +133,7 @@
 #   - 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>`_
+# See this `note <https://docs.pytorch.org/docs/stable/notes/autograd.html#locally-disabling-gradient-computation>`_ 
 # for additional reference. 
 
 ######################################################################
@@ -163,11 +163,12 @@
 #
 # 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  
-# `pytorchviz <https://github.com/szagoruyko/pytorchviz>`_
+#1. torchviz is a package to visualize computational graphs. 
+#   See the repository here: `https://github.com/szagoruyko/pytorchviz <https://github.com/szagoruyko/pytorchviz>`_
+#
+#2. Setting ``TORCH_LOGS="+autograd"`` enables logging for the backward pass. See details in this 
+#   discussion: `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>`_
 #
-# 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>`_
 #
 #
 # .. note::