PyTorch Hub

Logistics

We accept submission to PyTorch hub through PR in hub repo. Once the PR is merged into master here, it will show up on PyTorch website in 24 hrs.

Add a hubconf.py in your repo, following the instruction in torch.hub doc. Verify it's working correctly by running torch.hub.load(...) locally.
Create a PR in pytorch/hub repo. For each new model you have, create a <repo_owner>_<repo_name>_<title>.md file using this template.

Currently we don't support hosting pretrained weights, users with pretrained weights need to host them properly themselves.
In general we recommend one model per markdown file, models with similar structures like resnet18, resnet50 should be placed in the same file.
If you have images, place them in images/ folder and link them correctly in the [images/featured_image_1/featured_image_2] fields above.
We only support a pre-defined set of tags, currently they are listed in scripts/tags.py. We accept PRs to expand this set as needed.
To test your PR locally, run the tests below.

python scripts/sanity_check.py
./scripts/run_pytorch.sh

Our CI concatenates all python code blocks in one markdown file and runs it agaist the latest PyTorch release.
- Remember to mark your python code using ```python in model markdown file.
- If your dependencies is not installed on our CI machine, add them in install.sh.
- If it fails, you can find a new temp.py file left in the repo to reproduce the failure.
We also provide a way to preview your model webpage through netlify bot. This bot builds your PR with latest pytorch.github.io repo and comment on your PR with preview link. The preview will be updated as you push more commits to the PR.