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gradcheck
Manage episode 298153045 series 2921809
Contenuto fornito da PyTorch, Edward Yang, and Team PyTorch. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da PyTorch, Edward Yang, and Team PyTorch o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
We talk about gradcheck, the property based testing mechanism that we use to verify the correctness of analytic gradient formulas in PyTorch. I'll talk a bit about testing in general, property based testing and why gradcheck is a particularly useful property based test. There will be some calculus, although I've tried to keep the math mostly to intuitions and pointers on what to read up on elsewhere.
Further reading.
- Gradcheck mechanics, a detailed mathematical explanation of how it works https://pytorch.org/docs/stable/notes/gradcheck.html In particular, it also explains how gradcheck extends to complex numbers
- JAX has a pretty good explanation about vjp and jvp at https://jax.readthedocs.io/en/latest/notebooks/autodiff_cookbook.html
- Fast gradcheck tracking issue https://github.com/pytorch/pytorch/issues/53876
82 episodi
Condividi
Manage episode 298153045 series 2921809
Contenuto fornito da PyTorch, Edward Yang, and Team PyTorch. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da PyTorch, Edward Yang, and Team PyTorch o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
We talk about gradcheck, the property based testing mechanism that we use to verify the correctness of analytic gradient formulas in PyTorch. I'll talk a bit about testing in general, property based testing and why gradcheck is a particularly useful property based test. There will be some calculus, although I've tried to keep the math mostly to intuitions and pointers on what to read up on elsewhere.
Further reading.
- Gradcheck mechanics, a detailed mathematical explanation of how it works https://pytorch.org/docs/stable/notes/gradcheck.html In particular, it also explains how gradcheck extends to complex numbers
- JAX has a pretty good explanation about vjp and jvp at https://jax.readthedocs.io/en/latest/notebooks/autodiff_cookbook.html
- Fast gradcheck tracking issue https://github.com/pytorch/pytorch/issues/53876
82 episodi
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Simile a PyTorch Developer Podcast
Show notes are at https://stevelitchfield.com/sshow/chat.html
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continue reading
The American healthcare system is one of the most innovative in the world. But it’s also riddled with complex challenges, such as access to affordable medications, inefficiency and administrative burdens, and communication barriers between providers. There’s clearly a better way—and at Surescripts, we have a unique sightline into what that may be. In this series, host Melanie Marcus, Chief Marketing Officer of Surescripts, sits down with today’s most inspiring and innovative leaders in healt ...
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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
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…
continue reading
Welcome to Catalyst, the Launch by NTT DATA Podcast. Catalyst is an ongoing discussion for digital leaders dissatisfied with the status quo and optimistic about what’s possible through smart technology and great people. In this studio we believe in shipping software over slideware, that fast will follow smooth, and aiming to create digital experiences that move millions is a worthy pursuit.
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continue reading
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continue reading
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continue reading
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continue reading
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