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Anatomy of a domain library

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Manage episode 295783831 series 2921809
Innehåll tillhandahållet av PyTorch, Edward Yang, and Team PyTorch. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av PyTorch, Edward Yang, and Team PyTorch eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.

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.

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
  continue reading

83 episoder

Artwork

Anatomy of a domain library

PyTorch Developer Podcast

34 subscribers

published

iconDela
 
Manage episode 295783831 series 2921809
Innehåll tillhandahållet av PyTorch, Edward Yang, and Team PyTorch. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av PyTorch, Edward Yang, and Team PyTorch eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.

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.

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
  continue reading

83 episoder

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