Indhold leveret af PyTorch, Edward Yang, and Team PyTorch. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af PyTorch, Edward Yang, and Team PyTorch eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
Player FM - Podcast-app
Gå offline med appen Player FM !
Gå offline med appen Player FM !
vmap
MP3•Episode hjem
Manage episode 295500885 series 2921809
Indhold leveret af PyTorch, Edward Yang, and Team PyTorch. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af PyTorch, Edward Yang, and Team PyTorch eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
What is vmap? How is it implemented? How does our implementation compare to JAX's? What is a good way of understanding what vmap does? What's up with random numbers? Why are there some issues with the vmap that PyTorch currently ships?
Further reading.
- Tracking issue for vmap support https://github.com/pytorch/pytorch/issues/42368
- BatchedTensor source code https://github.com/pytorch/pytorch/blob/master/aten/src/ATen/BatchedTensorImpl.h , logical-physical transformation helper code https://github.com/pytorch/pytorch/blob/master/aten/src/ATen/VmapTransforms.h (well documented, worth a read)
- functorch, the better, more JAX-y implementation of vmap https://github.com/facebookresearch/functorch
- Autodidax https://jax.readthedocs.io/en/latest/autodidax.html which contains a super simple vmap implementation that is a good model for the internal implementation that PyTorch has
83 episoder
MP3•Episode hjem
Manage episode 295500885 series 2921809
Indhold leveret af PyTorch, Edward Yang, and Team PyTorch. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af PyTorch, Edward Yang, and Team PyTorch eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
What is vmap? How is it implemented? How does our implementation compare to JAX's? What is a good way of understanding what vmap does? What's up with random numbers? Why are there some issues with the vmap that PyTorch currently ships?
Further reading.
- Tracking issue for vmap support https://github.com/pytorch/pytorch/issues/42368
- BatchedTensor source code https://github.com/pytorch/pytorch/blob/master/aten/src/ATen/BatchedTensorImpl.h , logical-physical transformation helper code https://github.com/pytorch/pytorch/blob/master/aten/src/ATen/VmapTransforms.h (well documented, worth a read)
- functorch, the better, more JAX-y implementation of vmap https://github.com/facebookresearch/functorch
- Autodidax https://jax.readthedocs.io/en/latest/autodidax.html which contains a super simple vmap implementation that is a good model for the internal implementation that PyTorch has
83 episoder
همه قسمت ها
×Velkommen til Player FM!
Player FM is scanning the web for high-quality podcasts for you to enjoy right now. It's the best podcast app and works on Android, iPhone, and the web. Signup to sync subscriptions across devices.