https://github.com/hsm207/docker-harebrain
Dockerfile to get started with fastai's S4TF lessons
https://github.com/hsm207/docker-harebrain
docker s4tf tensorflow
Last synced: 3 months ago
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Dockerfile to get started with fastai's S4TF lessons
- Host: GitHub
- URL: https://github.com/hsm207/docker-harebrain
- Owner: hsm207
- License: gpl-3.0
- Created: 2019-06-11T19:16:49.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2019-06-11T19:16:55.000Z (about 7 years ago)
- Last Synced: 2025-03-04T07:15:03.847Z (over 1 year ago)
- Topics: docker, s4tf, tensorflow
- Language: Dockerfile
- Size: 15.6 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Introduction
This repository contains a Dockerfile that containerizes fastai's [harebrain](https://forums.fast.ai/t/about-the-harebrain-category/36672) project.
It is based on [Jeremy's Harebrained install guide](https://forums.fast.ai/t/jeremys-harebrained-install-guide/43814/9).
# Prerequisites
You will need a machine that has the following software installed in order to build and run the image:
* [docker](https://docs.docker.com/install/)
* [nvidia-docker](https://github.com/NVIDIA/nvidia-docker)
# Usage
1. Clone this repo.
2. Navigate to this project's root directory.
3. Execute:
```bash
docker build -t harebrain . && \
docker run -p 8888:8888 --cap-add SYS_PTRACE --runtime=nvidia --rm harebrain
```
This will build the image which will launch a jupyter server at port 8888. The
working directory of this notebook instance is the root of the [fastai_docs](https://github.com/fastai/fastai_docs) repo.
The `dev_swift` folder contains notebooks about Swift for TensorFlow.
# Contributing
Feel free to raise an issue if you have any questions, feedback, etc.