PyTorch Developer Podcast

Anatomy of a domain library

Episode Summary

What's a domain library? Why do they exist? What do they do for you? What should you know about developing in PyTorch main library versus in a domain library? What's cool about working on domain libraries?

Episode Notes

What's a domain library? Why do they exist? What do they do for you? What should you know about developing in PyTorch main library versus in a domain library? How coupled are they with PyTorch as a whole? What's cool about working on domain libraries?

Further reading.

• The classic trio of domain libraries is https://pytorch.org/audio/stable/index.html https://pytorch.org/text/stable/index.html and https://pytorch.org/vision/stable/index.html

Line notes.

• why do domain libraries exist? lots of domains specific gadgets,
  inappropriate for PyTorch
• what does a domain library do
  • operator implementations (old days: pure python, not anymore)
    • with autograd support and cuda acceleration
    • esp encoding/decoding, e.g., for domain file formats
      • torchbind for custom objects
      • takes care of getting the dependencies for you
    • esp transformations, e.g., for data augmentation
  • models, esp pretrained weights
  • datasets
  • reference scripts
  • full wheel/conda packaging like pytorch
  • mobile compatibility
• separate repos: external contributors with direct access
  • manual sync to fbcode; a lot easier to land code! less
    motion so lower risk
• coupling with pytorch? CI typically runs on nightlies
  • pytorch itself tests against torchvision, canary against
    extensibility mechanisms
  • mostly not using internal tools (e.g., TensorIterator),
    too unstable (this would be good to fix)
• closer to research side of pytorch; francesco also part of papers