Envnet model and related transforms
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Description
Hey,
I'm implementing EnvNet with ESC50 dataset with pytorch, it works great, but I would like to pull it into torchaudio.
So far I'm using the utils from bc_learning , what would be the best way to put this utils in torch audio ? should I rewrite the utils to be full pytorch or leave it in numpy (as in torchvision, the PIL Image in transforms.py)
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
Start by reading the referenced bc_learning utils.py and comparing its EnvNet and ESC50 data transforms with torchaudio's existing transform conventions. The issue does not identify torchaudio files, tests, an accepted NumPy-versus-PyTorch design, or a clear completion criterion, so the scope needs maintainer clarification before implementation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- numpy, python, pytorch
- Domain
- audio-video-rtc, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100