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Ml Debugging

• Collecting both my ideas and resources from around the web on ML Debugging tools.
• Debugging is
  • Show me what's going on: visibility into the system.
    • Ideally: cheap, always available, very reliable
  • Let me tweak something and tell me if it fixed the problem.
    • Ideally: fast, doesn't waste resources or time and proceeds from where the tweak was applied
• Tactics
  • Overfit a small batch and test that loss is almost negligible: https://twitter.com/rasbt/status/1555286200004534273
• Tools
  • Tensorboard
  • Weights & Biases
  • AIM stack
  • Weight watcher: https://pypi.org/project/weightwatcher/
    • https://calculatedcontent.com/
• Resources
  • ICLR on debugging (2019) [[ICLR]]
  • [[Amazon Sagemaker Debugger]]

— Kunal