# floydhub/dl-docker

An all-in-one Docker image for deep learning. Contains all the popular DL frameworks (TensorFlow, Theano, Torch, Caffe, etc.)

Repository: https://github.com/floydhub/dl-docker
Canonical: https://ross.abutalabs.com/products/dl-docker
Homepage: https://www.floydhub.com
Language: Python
License Family: other
Last push: 2019-08-21T20:18:27+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": 3742, "days_push": 2569, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3853, forks 802 (observed 2026-08-28T04:08:27.146173+00:00)

## What it is
An all-in-one Docker image bundling popular deep learning frameworks (TensorFlow, Caffe, Theano, Torch, Keras, Lasagne) with CPU and GPU (CUDA/cuDNN) support, plus common scientific Python libraries and Jupyter. It provides Dockerfiles to spin up a fully functional deep learning environment quickly.

## Use cases
- set up a deep learning environment with docker
- run tensorflow with gpu in a container
- all-in-one machine learning docker image
- try multiple deep learning frameworks without installing them
- reproducible deep learning dev environment
- jupyter notebook with cuda and cudnn preinstalled

## When to choose
- you want a prebuilt environment with many DL frameworks and CUDA/cuDNN already configured
- you need a reproducible deep learning setup on Linux with NVIDIA GPUs
- you want to experiment with frameworks like Caffe, Theano, or Torch without manual installation

## When to avoid
- you need current versions of TensorFlow or modern frameworks - the image is frozen on Ubuntu 14.04, CUDA 8, and cuDNN v5
- you only need a single framework - official framework images are better maintained
- you need GPU support on Windows or macOS - the GPU version only works on Linux
- you require an actively maintained project - the last release was in 2019

## Facets
- artifact type: infra-config
- maturity: abandoned
- function: deep-learning, machine-learning, container-runtime, gpu-computing
- domain: deep-learning, machine-learning, gpu-computing
- platform: windows
- tags: docker-image, tensorflow, caffe, theano, torch, keras, cuda, cudnn, jupyter, containers, docker, linux, macos, gpu

## Member repositories
- floydhub/dl-docker (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:27.146173+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 2026-08-29T18:25:56.860594+00:00, confidence not recorded.
  - readme: https://github.com/floydhub/dl-docker (fetched 2026-08-28T04:08:27.146173+00:00, sha da002befebf7)
- Data as of 2026-08-30T08:39:29.467469+00:00.