google-research / morph-net
Fast & Simple Resource-Constrained Learning of Deep Network Structure
Why this job: works in the areas we cover, but does not say which job it does
What it does
FiGS, is a probabilistic approach to channel regularization that we introduced in Fine-Grained Stochastic Architecture Search. It outperforms our previous regularizers and can be used as either a pruning algorithm or a full fledged Differentiable Architecture Search method. This is the recommended way to apply MorphNet. In the below documentation it is referred to as the LogisticSigmoid regularizer.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 38 days ago
- Stars
- 1,043
- On GitHub
- Licence
- Apache-2.0
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Python
- 96% of the code
Is it looked after?
- Contributors
- 3
- Last 90 days
- Issues
- 81% closed
- 11 still open
- Pull requests
- 123 merged
- 12 waiting
- Releases
- None
- Never published
- Contributing guide (opens in new tab)
- No security policy
- No code of conduct
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More: languages, topics and project record
Languages
- Python 96%
- Starlark 4%
Topics
- neural-architecture-search
- automl
- tensorflow
- deep-learning
- python
- machine-learning
Project record
- JobOther AI tools
- StatusListed
- Commits144
- Forks151
- Watching29
- Stars in 28 days+1
- CreatedMar 12, 2019
- First seen by usNov 7, 2026
- CheckedNov 8, 2026