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diffsinger-docker-envonly's Introduction

在本地使用即开即用的Docker环境训练Diffsinger模型

Docker内环境

python 3.11
cuda 12.1
pytorch 2.1.2
jupyterlab
requirements.txt

准备工作

  • 安装Wsl发行版
  • 安装Docker
  • 安装Cuda
  • 拉取镜像

开始训练

  • 找到一个文件夹，并从github clone Diffsinger仓库
  • 放置训练Diffsinger模型所需的文件
  • 启动容器并将Diffsinger文件夹挂载到镜像中（在您有GPU情况下请直接复制命令，如果没有则将命令中关于gpu的部分删除）
docker run -it --gpus all -p 8888:8888 -e NVIDIA_DRIVER_CAPABILITIES=all -e NVIDIA_VISIBLE_DEVICES=all -v <local path>/Diffsinger:/content/Diffsinger q78kg/diffsinger-env-only:main
  • 从127.0.0.1:8888访问Jupyter Lab，或使用VS Code连接容器，即可按照官方文档操作并开始训练

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