# carpedm20/ENAS-pytorch

PyTorch implementation of "Efficient Neural Architecture Search via Parameters Sharing"

Repository: https://github.com/carpedm20/ENAS-pytorch
Canonical: https://ross.abutalabs.com/products/enas-pytorch
Language: Python
License: Apache-2.0
License Family: permissive
Topics: pytorch, neural-architecture-search, google-brain
Last push: 2023-07-06T21:33:33+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3121, "days_push": 1154, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2719, forks 486 (observed 2026-08-28T04:07:12.246185+00:00)

## What it is
A PyTorch implementation of Efficient Neural Architecture Search (ENAS), which reduces NAS GPU-hours by 1000x via parameter sharing between subgraph models. It supports discovering recurrent cells for language modeling and CNN architectures, though the README recommends the authors' official code.

## Use cases
- search for novel RNN cells for language modeling
- discover CNN architectures on CIFAR
- reproduce the ENAS paper in PyTorch
- run neural architecture search with limited GPU budget
- visualize discovered architectures as gifs

## When to choose
- you want a PyTorch-based ENAS reference implementation
- you're studying or extending neural architecture search with parameter sharing

## When to avoid
- you need production-grade or officially supported NAS code (use the authors' official implementation)
- you need modern PyTorch versions (it targets PyTorch 0.3.1)
- you need complete CNN search support (marked in progress)

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning
- domain: machine-learning, deep-learning
- platform: python
- tags: neural-architecture-search, pytorch, enas, research-code, parameter-sharing

## Member repositories
- carpedm20/ENAS-pytorch (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:12.246185+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:15:17.640183+00:00, confidence not recorded.
  - readme: https://github.com/carpedm20/ENAS-pytorch (fetched 2026-08-28T04:07:12.246185+00:00, sha 9c65f5ac9b73)
- Data as of 2026-08-30T08:39:29.467469+00:00.