Skip to content
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

Jump to bottom

Use conda environment yaml's for training-tuning-scripts #1256

Merged
merged 7 commits into from
Oct 13, 2023
Merged

Use conda environment yaml's for training-tuning-scripts #1256

Show file tree
Hide file tree
Changes from 1 commit
Commits
Show all changes
7 commits
Select commit Hold shift + click to select a range
efead5c
use conda env yaml's for training-tuning-scripts
efajardo-nv Oct 10, 2023
004d353
remove unused import from sid training notebook
efajardo-nv Oct 11, 2023
b8a982c
Merge branch 'branch-23.11' into training-tuning-req-yamls
efajardo-nv Oct 11, 2023
e0decad
Merge branch 'branch-23.11' of https://github.com/nv-morpheus/Morpheu…
efajardo-nv Oct 13, 2023
895de1c
fix copyright year and indents
efajardo-nv Oct 13, 2023
c780249
autoencoder updates in dfp script/notebook
efajardo-nv Oct 13, 2023
a3676e4
Merge branch 'training-tuning-req-yamls' of https://github.com/efajar…
efajardo-nv Oct 13, 2023
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
Prev Previous commit
Next Next commit
autoencoder updates in dfp script/notebook
  • Loading branch information
@efajardo-nv
efajardo-nv committed Oct 13, 2023
commit c7802496d67a6635f05937528f8ba1f2dd65cd3a
2 changes: 1 addition & 1 deletion models/training-tuning-scripts/dfp-models/hammah-20211017-script.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -102,7 +102,7 @@ def main():
min_cats=1 # cut off for minority categories
)

model.fit(x_train, epochs=25, validation_data=x_val)
model.fit(x_train, epochs=25, validation_data=x_val, run_validation=True)

torch.save(model.state_dict(), args.trainingdata[:-4] + ".pkl")
with open(args.trainingdata[:-4] + 'dill' + '.pkl', 'wb') as f:
Expand Down
Loading