[Master Issue] Add more models to torchvision
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@fmassa is already working on this.
Since Oct 30, 2018.
enhancement
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- Python
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Description
This is a master issue to track requests for adding new pre-trained models to torchvision.
Here is the (potentially incomplete) list I compiled:
- ResNext https://github.com/pytorch/vision/issues/154 https://github.com/pytorch/vision/issues/543 https://github.com/pytorch/vision/issues/154
- ResNet / ResNext with Group Norm https://github.com/pytorch/vision/issues/631
- mobilenet https://github.com/pytorch/vision/issues/625
- Inception family https://github.com/pytorch/vision/issues/490 https://github.com/pytorch/vision/issues/537
-
NasNet https://github.com/pytorch/vision/issues/321Implemented as MNasNet - SENet https://github.com/pytorch/vision/issues/260
- ShuffleNet
@Cadene has already implemented a number of those models in his fantastic https://github.com/Cadene/pretrained-models.pytorch . I'll start from there and try to get models trained using pytorch/examples/imagenet, so that the models are reproducible.
Requirements
- python implementation to live in
vision/models - pre-trained weights using the same mean / std normalization as in the imagenet example
- the script used to train the models, or the command-line arguments used if the script was exactly the one from
examples/imagenet.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Assessment
This issue has not been assessed yet.