tensorflow / tensorflow/probability
Support for SeparableConv1DFlipout
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Description
SeparableConv enables a much greater range of low power, low latency models. MobileNet and other low cost high performance networks generally utilizes SeparableConv for it's efficiency. I am building a real probabilistic inference version of a MobileNet which uses SeparableConv. I am using regular tfp convolution ops for now for initial validation but it is much less efficient and will not be fit for production use.
Thanks!
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 locating the existing TFP convolution operations and the SeparableConv API, then compare their interfaces with the requested SeparableConv1DFlipout entry point. Review how MobileNet uses SeparableConv and determine the scope needed for probabilistic inference. Done means the requested operation is supported and suitable for the stated use case.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- tensorflow
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100