79 lines
4.7 KiB
Markdown
79 lines
4.7 KiB
Markdown
# Docker
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The Docker image currently works on Windows and Linux, optionally supporting NVIDIA GPUs.
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## General Remarks
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- The resulting Docker image is 21 GB in size. Building might require even more disk space temporarily.
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- Another 15 GB is required for building DeepSpeed
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- Build time depends on your hardware and internet connection. Expect at least 20-30min to be normal for a full build.
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- This includes building the conda environment as well as DeepSpeed, which is the basis for the alltalk Docker image.
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- The Docker build for alltalk:
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- Downloads XTTS as default TTS engine
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- Enables RVC by default
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- Downloads all supported RVC models
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- Enables deepspeed by default
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- Starting the Docker image should only a few seconds due to all the steps that were already executed during build.
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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-12-4`
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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](#building-and-running-in-docker)
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## Building and Running in Docker
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1. Open a terminal (or Ubuntu WSL) and go where you cloned the repo
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3. Build the image with `./docker-build.sh`
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4. Start the container with `./docker-start.sh`
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5. Visit `http://localhost:7851/` or remotely with `http://<ip>:7851`
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## Arguments for building and starting docker
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There are various arguments to customize the build and start of the docker image.
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### Arguments for `docker-build.sh`
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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`.
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- Example: `docker-build.sh --tag mytag`
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- `--clean` allows remove existing dependency build like conda environment or DeepSpeed.
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- Example: `docker-build.sh --clean`
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### Arguments for `docker-start.sh`
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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`.
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- Example: `docker-start.sh --tag mytag`
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- Since the above commands only address the most important options, you might pass additional arbitrary docker commands
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to the `docker-start.sh`.
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