Skip to content

fix case of torch.nn.Module #1791

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 2 commits into from
Jan 18, 2022
Merged

fix case of torch.nn.Module #1791

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
3e4c2a6
fix case of torch.nn.Module
decoherencer Jan 12, 2022
6aa2c48
Merge branch 'master' into patch-2
holly1238 Jan 15, 2022
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion beginner_source/introyt/autogradyt_tutorial.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -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
Expand Down