# lucidrains/mlp-mixer-pytorch

An All-MLP solution for Vision, from Google AI

Repository: https://github.com/lucidrains/mlp-mixer-pytorch
Canonical: https://ross.abutalabs.com/products/mlp-mixer-pytorch
Language: Python
License: MIT
License Family: permissive
Topics: deep-learning, vision
Last push: 2025-07-07T15:59:57+00:00

## Health v2 (maintenance only)
Score: 48/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 30, release rhythm 40, longevity 100
- inputs: {"age_days": 1946, "days_push": 422, "days_rel": 422, "gap_med": 0.5, "n_releases_24m": 5}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1064, forks 107 (observed 2026-08-28T04:03:26.497158+00:00)

## What it is
A PyTorch implementation of Google AI's MLP-Mixer, an all-MLP architecture for image classification that uses neither convolutions nor attention. It also includes a 3D variant (MLPMixer3D) for video inputs.

## Use cases
- implement mlp-mixer architecture in pytorch
- image classification without convolutions or attention
- experiment with all-mlp vision models
- classify video with an mlp-based model
- reproduce the mlp-mixer paper results

## When to choose
- you want a simple, dependency-light PyTorch implementation of MLP-Mixer for research or experimentation
- you need image or video classification models based purely on MLP layers
- you want to benchmark MLP-only architectures against CNNs and vision transformers

## When to avoid
- you need pretrained production-ready vision models with state-of-the-art accuracy
- you require architectures with attention or convolutions
- you work outside PyTorch, e.g. TensorFlow or JAX

## Facets
- artifact type: library
- maturity: active
- function: machine-learning, deep-learning, image-processing
- domain: deep-learning, computer-vision, machine-learning
- platform: python
- tags: pytorch, mlp-mixer, vision-transformer-alternative, image-classification, research-code

## Member repositories
- lucidrains/mlp-mixer-pytorch (main) score 48

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:26.497158+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 2026-08-30T06:56:05.193250+00:00, confidence not recorded.
  - readme: https://github.com/lucidrains/mlp-mixer-pytorch (fetched 2026-08-28T04:03:26.497158+00:00, sha 21d3d6a04cd3)
  - registry_pypi: https://pypi.org/pypi/mlp-mixer-pytorch/json (fetched 2026-08-29T12:58:08.780872+00:00, sha 46617d4e96fe)
- Data as of 2026-08-30T08:39:29.467469+00:00.