Bot Updating Templated Files

master 1.40.0.7998-c29d4c0c8-ls207
LinuxServer-CI 2 months ago
parent 2b397aa4b5
commit 094a15b4aa

@ -67,10 +67,10 @@ body:
- type: textarea
attributes:
description: |
Provide a full docker log, output of "docker logs linuxserver.io"
Provide a full docker log, output of "docker logs plex"
label: Container logs
placeholder: |
Output of `docker logs linuxserver.io`
Output of `docker logs plex`
render: bash
validations:
required: true

@ -7,7 +7,7 @@ jobs:
external-trigger-master:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3.1.0
- uses: actions/checkout@v4.1.1
- name: External Trigger
if: github.ref == 'refs/heads/master'

@ -9,7 +9,7 @@ jobs:
external-trigger-scheduler:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3.1.0
- uses: actions/checkout@v4.1.1
with:
fetch-depth: '0'

@ -7,7 +7,7 @@ jobs:
package-trigger-master:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3.1.0
- uses: actions/checkout@v4.1.1
- name: Package Trigger
if: github.ref == 'refs/heads/master'

@ -9,7 +9,7 @@ jobs:
package-trigger-scheduler:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3.1.0
- uses: actions/checkout@v4.1.1
with:
fetch-depth: '0'

@ -76,7 +76,7 @@ Valid settings for VERSION are:-
### Hardware Acceleration
Many desktop application will need access to a GPU to function properly and even some Desktop Environments have compisitor effects that will not function without a GPU. This is not a hard requirement and all base images will function without a video device mounted into the container.
Many desktop applications need access to a GPU to function properly and even some Desktop Environments have compositor effects that will not function without a GPU. However this is not a hard requirement and all base images will function without a video device mounted into the container.
#### Intel/ATI/AMD
@ -91,9 +91,9 @@ We will automatically ensure the abc user inside of the container has the proper
#### Nvidia
Hardware acceleration users for Nvidia will need to install the container runtime provided by Nvidia on their host, instructions can be found here:
https://github.com/NVIDIA/nvidia-docker
https://github.com/NVIDIA/nvidia-container-toolkit
We automatically add the necessary environment variable that will utilise all the features available on a GPU on the host. Once nvidia-docker is installed on your host you will need to re/create the docker container with the nvidia container runtime `--runtime=nvidia` and add an environment variable `-e NVIDIA_VISIBLE_DEVICES=all` (can also be set to a specific gpu's UUID, this can be discovered by running `nvidia-smi --query-gpu=gpu_name,gpu_uuid --format=csv` ). NVIDIA automatically mounts the GPU and drivers from your host into the container.
We automatically add the necessary environment variable that will utilise all the features available on a GPU on the host. Once nvidia-container-toolkit is installed on your host you will need to re/create the docker container with the nvidia container runtime `--runtime=nvidia` and add an environment variable `-e NVIDIA_VISIBLE_DEVICES=all` (can also be set to a specific gpu's UUID, this can be discovered by running `nvidia-smi --query-gpu=gpu_name,gpu_uuid --format=csv` ). NVIDIA automatically mounts the GPU and drivers from your host into the container.
#### Arm Devices

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