fix case of torch.nn.Module (#1791)

decoherencer · holly1238 · web-flow · commit f2579c6f4502 · 2022-01-18T10:52:45.000-08:00
Co-authored-by: Holly Sweeney &lt;77758406+holly1238@users.noreply.github.com&gt;
diff --git a/beginner_source/introyt/autogradyt_tutorial.py b/beginner_source/introyt/autogradyt_tutorial.py
@@ -269,7 +269,7 @@ def forward(self, x):
 ##########################################################################
 # One thing you might notice is that we never specify
 # ``requires_grad=True`` for the model’s layers. Within a subclass of
-# ``torch.nn.module``, it’s assumed that we want to track gradients on the
+# ``torch.nn.Module``, it’s assumed that we want to track gradients on the
 # layers’ weights for learning.
 # 
 # If we look at the layers of the model, we can examine the values of the

Original file line number	Diff line number	Diff line change
`@@ -269,7 +269,7 @@ def forward(self, x):`
`269`	`269`	`##########################################################################`
`270`	`270`	`# One thing you might notice is that we never specify`
`271`	`271`	# ``requires_grad=True`` for the model’s layers. Within a subclass of
`272`		-# ``torch.nn.module``, it’s assumed that we want to track gradients on the
	`272`	+# ``torch.nn.Module``, it’s assumed that we want to track gradients on the
`273`	`273`	`# layers’ weights for learning.`
`274`	`274`	`#`
`275`	`275`	`# If we look at the layers of the model, we can examine the values of the`