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fixed indention and enumeration for nvct (#518)

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Daniel Kleine 2025-02-06 15:17:12 +01:00 committed by GitHub
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setup/03_optional-docker-environment/README.md
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@ -37,38 +37,38 @@ mv setup/03_optional-docker-environment/.devcontainer ./
4. If you have a [CUDA-supported GPU](https://developer.nvidia.com/cuda-gpus), you can speed up the training and inference:
3.1 Install **NVIDIA Container Toolkit** as described [here](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html#installing-with-apt). NVIDIA Container Toolkit is supported as written [here](https://docs.nvidia.com/cuda/wsl-user-guide/index.html#nvidia-compute-software-support-on-wsl-2).
4.1 Install **NVIDIA Container Toolkit** as described [here](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html#installing-with-apt). NVIDIA Container Toolkit is supported as written [here](https://docs.nvidia.com/cuda/wsl-user-guide/index.html#nvidia-compute-software-support-on-wsl-2).
3.2 Add _nvidia_ as runtime in Docker Engine daemon config (see _Docker Desktop_ -> _Change settings_ -> _Docker Engine_). Add these lines to your config:
4.2 Add _nvidia_ as runtime in Docker Engine daemon config (see _Docker Desktop_ -> _Change settings_ -> _Docker Engine_). Add these lines to your config:
```json
"runtimes": {
"nvidia": {
"path": "nvidia-container-runtime",
"runtimeArgs": []
```
```json
"runtimes": {
"nvidia": {
"path": "nvidia-container-runtime",
"runtimeArgs": []
```
For example, the full Docker Engine daemon config json code should look like that:
For example, the full Docker Engine daemon config json code should look like that:
```json
{
"builder": {
"gc": {
"defaultKeepStorage": "20GB",
"enabled": true
}
},
"experimental": false,
"runtimes": {
"nvidia": {
"path": "nvidia-container-runtime",
"runtimeArgs": []
}
}
}
```
```json
{
"builder": {
"gc": {
"defaultKeepStorage": "20GB",
"enabled": true
}
},
"experimental": false,
"runtimes": {
"nvidia": {
"path": "nvidia-container-runtime",
"runtimeArgs": []
}
}
}
```
and restart Docker Desktop.
and restart Docker Desktop.
5. Type `code .` in the terminal to open the project in VS Code. Alternatively, you can launch VS Code and select the project to open from the UI.