Random number generators

PyTorch Developer Podcast

Innhold levert av PyTorch, Edward Yang, and Team PyTorch. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av PyTorch, Edward Yang, and Team PyTorch eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

4+ y ago 14:24

MP3•Episoder hjem

Why are RNGs important? What is the generator concept? How do PyTorch's CPU and CUDA RNGs differ? What are some of the reasons why Philox is a good RNG for CUDA? Why doesn't the generator class have virtual methods for getting random numbers? What's with the next normal double and what does it have to do with Box Muller transform? What's up with csprng?

Further reading.

CUDAGeneratorImpl has good notes about CUDA graph interaction and pointers to all of the rest of the stuff https://github.com/pytorch/pytorch/blob/1dee99c973fda55e1e9cac3d50b4d4982b6c6c26/aten/src/ATen/CUDAGeneratorImpl.h
Transform uniformly distributed random numbers to other distributions with https://github.com/pytorch/pytorch/blob/master/aten/src/ATen/core/TransformationHelper.h
torchcsprng https://github.com/pytorch/csprng

83 episoder

#Tech #PyTorch #Edward Yang #Team PyTorch #Deep Learning #Machine Learning