87 lines
5.0 KiB
Markdown
87 lines
5.0 KiB
Markdown
# Docker
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The Docker image currently works on Windows and Linux supporting NVIDIA GPUs.
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## System requirements
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- AMD compatible Windows or Linux system
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- CUDA 12.6
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- Nvidia Docker Container Toolkit
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- At least 25GB of free disk space
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## Quickstart
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Use `docker-start.sh` to pull the latest docker image using the XTTS model from Docker Hub and
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visit `http://localhost:7851/`. See instructions below for passing more arguments to the start script.
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## Installing Prerequisites
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### Docker for Linux
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#### Ubuntu Specific Setup for GPUs
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1. Make sure the latest nvidia drivers are installed: `sudo ubuntu-drivers install`
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1. Install Docker your preferred way. One way to do it is to follow the official documentation [here](https://docs.docker.com/engine/install/ubuntu/#uninstall-old-versions).
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- Start by uninstalling the old versions
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- Follow the "apt" repository installation method
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- Check that everything is working with the "hello-world" container
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1. If, when launching the docker contain, you have an error message saying that the GPU cannot be used, you might have to install [Nvidia Docker Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html).
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- Install with the "apt" method
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- Run the docker configuration command
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```sudo nvidia-ctk runtime configure --runtime=docker```
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- Restart docker
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### Docker for Windows (WSL2)
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#### Windows Specific Setup for GPUs
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> Make sure your Nvidia drivers are up to date: https://www.nvidia.com/download/index.aspx
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1. Install WSL2 in PowerShell with `wsl --install` and restart
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2. Open PowerShell, type and enter ```ubuntu```. It should now load you into wsl2
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3. Remove the original nvidia cache key: `sudo apt-key del 7fa2af80`
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4. Download CUDA toolkit keyring: `wget https://developer.download.nvidia.com/compute/cuda/repos/wsl-ubuntu/x86_64/cuda-keyring_1.1-1_all.deb`
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5. Install keyring: `sudo dpkg -i cuda-keyring_1.1-1_all.deb`
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6. Update package list: `sudo apt-get update`
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7. Install CUDA toolkit: `sudo apt-get -y install cuda-toolkit-12-6`
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8. Install Docker Desktop using WSL2 as the backend
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9. Restart
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10. If you wish to monitor the terminal remotely via SSH, follow [this guide](https://www.hanselman.com/blog/how-to-ssh-into-wsl2-on-windows-10-from-an-external-machine).
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11. Open PowerShell, type ```ubuntu```, [then follow below](#quickstart)
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## Arguments for starting the Docker container
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To make it as simple as possible to use Docker, the script `docker-start.sh` can be used. It provides the
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following optional arguments:
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- `--config` lets you choose a config JSON file which can subset of `confignew.json`. This allows you to change only
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few values and leave the rest as defined in the default `confignew.json` file.
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- Example: `docker-start.sh --config /my/config/file.json` with content `{"branding": "My Brand "}` will just change
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the branding in `confignew.json`.
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- `--voices` lets you add voices for the TTS engine in WAV format. You have to specify the folder containing all
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voice files.
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- Example: `docker-start.sh --voices /my/voices/dir`
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- `--rvc_voices` similar to voices, this option lets you pick the folder containing the RVC models.
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- Example: `docker-start.sh --rvc_voices /my/rvc/voices/dir`
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- `--no_ui` allows you to not expose port 7852 for the gradio interface. Note that you still have to set `launch_gradio`
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to `false` via JSON file passed to `--config`.
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- `--tag` allows to choose the docker tag of the image to run. Defaults to `latest-xtts`.
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- Example: `docker-start.sh --tag mytag`
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- `--docker-repository` allows to choose another Docker repository for pulling the image from. Use an empty
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string for the local repo.
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- Since the above commands only address the most important options, you might pass additional arbitrary docker arguments
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to the `docker-start.sh`.
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Of course, like any other Docker image, you can also directly use `docker run` directly and use `docker-start.sh`
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as an inspiration.
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## Building your own images (advanced)
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> Be aware that building the images requires good hardware and bandwidth. Expect this process to require >
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> 40 GB of disk space and > 30min execution time depending on your hardware.
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Under normal circumstances, there should be no need to build the Docker images locally. However, if needed for some
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reason, you may want to use `docker-build.sh` with the following arguments:
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- `--tts_model` allows to choose the TTS model that is used by default. Valid values are `piper`, `vits`, `xtts`. Defaults to `xtts`.
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- Example: `docker-build.sh --tts_model piper`
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- `--tag` allows to choose the docker tag. Defaults to `latest-xtts`.
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- Example: `docker-build.sh --tag mytag`
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- `--docker-repository` allows to choose another Docker repository for tagging the image from. Use an empty
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string for the local repo.
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- `--local-deepspeed-build` should only be used in rare cases where DeepSpeed needs to be rebuilt. Defaults to `false`.
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- `--clean` allows remove existing dependency build like conda environment or DeepSpeed. Defaults to `false`.
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- Example: `docker-build.sh --clean`
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