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A tartalmat a PyTorch, Edward Yang, and Team PyTorch biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a PyTorch, Edward Yang, and Team PyTorch vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.
Hasonló a(z) PyTorch Developer Podcast sorozathoz
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Random number generators
Manage episode 295591508 series 2921809
A tartalmat a PyTorch, Edward Yang, and Team PyTorch biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a PyTorch, Edward Yang, and Team PyTorch vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.
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 epizódok
Megosztás
Manage episode 295591508 series 2921809
A tartalmat a PyTorch, Edward Yang, and Team PyTorch biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a PyTorch, Edward Yang, and Team PyTorch vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.
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 epizódok
All episodes
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Hasonló a(z) PyTorch Developer Podcast sorozathoz
We already have many of the climate solutions we need. But scaling them is hard. The Green Blueprint is a show about the people who are architecting the clean economy. Every other week, host Lara Pierpoint profiles the founders, investors, and organizational leaders who are solving complex challenges in the quest to build climate technologies fast.
…
continue reading
Thanks for visiting The Cell Phone Junkie! I will be taking the time each week to discuss my favorite topic, cell phones. Any feedback is appreciated and welcome. You can email me at: questions (AT) thecellphonejunkie (DOT) com or call: 206-203-3734 Thanks and welcome!
…
continue reading
Show notes are at https://stevelitchfield.com/sshow/chat.html
…
continue reading
The director’s commentary track for Daring Fireball. Long digressions on Apple, technology, design, movies, and more.
…
continue reading
Embedded is the show for people who love gadgets. Making them, breaking them, and everything in between. Weekly interviews with engineers, educators, and enthusiasts. Find the show, blog, and more at embedded.fm.
…
continue reading
A podcast for developers interested in building great software products. Every episode, Adam Wathan is joined by a guest to talk about everything from product design and user experience to unit testing and system administration.
…
continue reading
Making artificial intelligence practical, productive & accessible to everyone. Practical AI is a show in which technology professionals, business people, students, enthusiasts, and expert guests engage in lively discussions about Artificial Intelligence and related topics (Machine Learning, Deep Learning, Neural Networks, GANs, MLOps, AIOps, LLMs & more). The focus is on productive implementations and real-world scenarios that are accessible to everyone. If you want to keep up with the lates ...
…
continue reading
Download This Show is your weekly guide to the world of media, culture, and technology. From social media to gadgets, streaming services to privacy issues. Each week Rae Johnston and guests take a fun, deep dive into how technology is reshaping our lives.
…
continue reading
WSJ’s Bold Names brings you conversations with the leaders of the bold-named companies featured in the pages of The Wall Street Journal. Hosts Tim Higgins and Christopher Mims speak to CEOs and business leaders in interviews that challenge conventional wisdom and take you inside the decisions being made in the C-suite and beyond.
…
continue reading
The power of Data is undeniable. And unharnessed - it’s nothing but chaos. Making data your ally. Using it to lead with confidence and clarity. Host Jess Carter is solving problems in real-time to reveal what’s possible. Helping communities and people thrive. This is Data Driven Leadership, a show brought to you by Resultant.
…
continue reading
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