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gradcheck
Manage episode 298153045 series 2921809
Content provided by PyTorch, Edward Yang, and Team PyTorch. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by PyTorch, Edward Yang, and Team PyTorch or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://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 episodes
Share
Manage episode 298153045 series 2921809
Content provided by PyTorch, Edward Yang, and Team PyTorch. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by PyTorch, Edward Yang, and Team PyTorch or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://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 episodes
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Similar to PyTorch Developer Podcast
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continue reading
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