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Add info to pull GPU image from Docker Hub

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Aurélien Geron 2021-03-05 17:33:59 +13:00 committed by GitHub
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docker/README.md
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@ -14,7 +14,7 @@ Some general knowledge about `docker` infrastructure might be useful (that's an
### Prepare the image (once)
The first option is to pull the image from Docker Hub (this will download over 6 GB of data):
The first option is to pull the image from Docker Hub (this will download over 2.3 GB of data):
```bash
$ docker pull ageron/handson-ml2
@ -76,14 +76,21 @@ To be precise, the output will tell you *what modifications should be re-played
If you're using Linux, and you have a TensorFlow-compatible GPU card (NVidia card with Compute Capability ≥ 3.5) that you would like TensorFlow to use inside the docker container, then you should download and install the latest driver for your card from [nvidia.com](https://www.nvidia.com/Download/index.aspx?lang=en-us). You will also need to install [NVidia Docker support](https://github.com/NVIDIA/nvidia-docker): if you are using Docker 19.03 or above, you must install the `nvidia-container-toolkit` package, and for earlier versions, you must install `nvidia-docker2`.
To build the image, edit `docker-compose.yml`, replace the line `dockerfile: ./docker/Dockerfile` with `dockerfile: ./docker/Dockerfile.gpu`, and then run:
If you want to pull the prebuilt image from Docker Hub (this will download over 4 GB of data):
```bash
$ docker pull ageron/handson-ml2:latest-gpu
$ docker tag ageron/handson-ml2:latest-gpu handson-ml2
```
If you prefer to build the image yourself, edit `docker-compose.yml`, replace the line `dockerfile: ./docker/Dockerfile` with `dockerfile: ./docker/Dockerfile.gpu`, and then run the following commands (assuming this project is located at `/path/to/project/handson-ml2`):
```bash
$ cd /path/to/project/handson-ml2/docker
$ docker-compose build
```
To run the image, it's depends. If you have `docker-compose` version 1.28 or above, that's great! You can simply uncomment the `deploy` section in `docker-compose.yml`, and then run:
To run the image, it depends. If you have `docker-compose` version 1.28 or above, that's great! You can simply uncomment the `deploy` section in `docker-compose.yml`, and then run:
```bash
$ cd /path/to/project/handson-ml2/docker