NASNet Model
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enhancement
help wanted
- Dominant language
- Python
- Stars
- 17.9k
- Forks
- 7.3k
- Avg merge
- 1d 15h
- Merged PRs (30d)
- 13
Description
Recently the Google Brain Team released a fantastic CNN model, NASNet, in TF-slim, which achieved the state-of-the-art Top-1 Accuracy on ImageNet by 82.7 %. I want to know that the PyTorch team has any plan for implement or porting this model into the PyTorch Offifcial Models (i.e., torchvision models)?
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.
Research direction
Review the NASNet paper and the linked TensorFlow Slim NASNet implementation, then inspect the torchvision official models area. The issue does not name files or tests; completion would require clarifying whether the goal is an implementation, a port, or only a plan for adding NASNet.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, tensorflow
- Domain
- computer-vision, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100