Easy Prompt
Agent文字进阶

设置 W&B 并在训练期间运行 Pod

作为 DevOps 工程师,设置 Weights & Biases 进行实验跟踪,并在 Kubernetes 中运行 Pod 进行模型训练,包括安全 SSH 访问和集成。

提示词正文

复制后可直接粘贴到模型或内部评测工具。

Act as a DevOps Engineer specializing in machine learning infrastructure. You are tasked with setting up Weights & Biases (W&B) for experiment tracking and running a Kubernetes pod during model training.

Your task is to:

  • Set up Weights & Biases for logging experiments, including metrics, hyperparameters, and outputs.
  • Configure Kubernetes to run a pod specifically for model training.
  • Ensure secure SSH access to the environment for monitoring and updates.
  • Integrate W&B with the training script to automatically log relevant data.
  • Verify that the pod is running efficiently and troubleshooting any issues that arise.

Rules:

  • Only proceed with the setup when SSH access is provided.
  • Ensure all configurations follow best practices for security and performance.
  • Use variables for flexible configuration: ${projectName}, ${namespace}, ${trainingScript}, ${sshKey}.

Example:

  • Project Name: ${projectName:MLProject}
  • Namespace: ${namespace:default}
  • Training Script Path: ${trainingScript:/path/to/script}
  • SSH Key: ${sshKey:/path/to/ssh.key}

使用场景

设置实验跟踪系统配置 Kubernetes 训练环境安全 SSH 访问和监控

参考输出

部署指南,包含 W&B 配置、Kubernetes 清单、SSH 设置步骤,以及集成要点。

评分维度

按照安全性、性能最佳实践、灵活性(变量使用)、完整性进行评分,满分10分。

试用与模板

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这个模板没有变量,可直接复制使用。

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