D-X-Y/AutoDL-Projects

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1581 stars · 288 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

AutoDL-Projects is a PyTorch library implementing automated deep learning algorithms, including neural architecture search (NAS) methods like DARTS, GDAS, SETN, and TAS, plus hyper-parameter optimization. It unifies multiple AutoDL algorithms in a single lightweight codebase for beginners, engineers, and researchers.

Use cases

• run neural architecture search experiments in pytorch
• try different automl algorithms in one codebase
• implement and benchmark new NAS algorithms for research
• evaluate whether automated deep learning helps my project
• reproduce DARTS or GDAS search results
• learn hyper-parameter optimization and NAS as a beginner

When to choose

• you want multiple NAS/HPO algorithms in one consistent codebase
• you are a researcher prototyping new AutoDL methods
• you want simple dependencies and readable reference implementations of published papers

When to avoid

• you need a production AutoML platform with GUI and pipelines
• you work outside PyTorch (e.g., TensorFlow or JAX)
• you need actively maintained support for the latest models and APIs

Facets

library · maturity maintenance

machine-learning deep-learning machine-learning deep-learning artificial-intelligence python nas neural-architecture-search automl hyperparameter-optimization pytorch research gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="D-X-Y/AutoDL-Projects")