Skip to content

Correct dropout p definition based on test cases #15

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.

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

Open
wants to merge 1 commit into
base: main
Choose a base branch
from
Open
Changes from all commits
Commits
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 hw2.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -491,7 +491,7 @@
"**Important**: If the Dropout module the flag `training=False`, you shouldn't \"dropout\" any weights. That is, dropout applies during training only, not during evaluation. Note that `training` is a flag in `nn.Module`.\n",
"\n",
"##### Parameters\n",
"- `p` - the probability of an element to be zeroed.\n",
"- `p` - the probability of an element to be kept.\n",
"\n",
"___"
]
Expand Down