Update autograd_tutorial.py

asrjy · web-flow · commit 33b5d6d14416 · 2025-06-04T12:58:45.000+05:30
Updated link to momentum article on TDS
diff --git a/beginner_source/blitz/autograd_tutorial.py b/beginner_source/blitz/autograd_tutorial.py
@@ -67,7 +67,7 @@
 loss.backward() # backward pass
 
 ############################################################
-# Next, we load an optimizer, in this case SGD with a learning rate of 0.01 and `momentum <https://towardsdatascience.com/stochastic-gradient-descent-with-momentum-a84097641a5d>`__ of 0.9.
+# Next, we load an optimizer, in this case SGD with a learning rate of 0.01 and `momentum <https://medium.com/data-science/stochastic-gradient-descent-with-momentum-a84097641a5d>`__ of 0.9.
 # We register all the parameters of the model in the optimizer.
 #
 

Original file line number	Diff line number	Diff line change
`@@ -67,7 +67,7 @@`
`67`	`67`	`loss.backward() # backward pass`
`68`	`68`
`69`	`69`	`############################################################`
`70`		-# Next, we load an optimizer, in this case SGD with a learning rate of 0.01 and `momentum <https://towardsdatascience.com/stochastic-gradient-descent-with-momentum-a84097641a5d>`__ of 0.9.
	`70`	+# Next, we load an optimizer, in this case SGD with a learning rate of 0.01 and `momentum <https://medium.com/data-science/stochastic-gradient-descent-with-momentum-a84097641a5d>`__ of 0.9.
`71`	`71`	`# We register all the parameters of the model in the optimizer.`
`72`	`72`	`#`
`73`	`73`