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Reference counting
Manage episode 297915922 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.
Reference counting is a common memory management technique in C++ but PyTorch does its reference counting in a slightly idiosyncratic way using intrusive_ptr. We'll talk about why intrusive_ptr exists, the reason why refcount bumps are slow in C++ (but not in Python), what's up with const Tensor& everywhere, why the const is a lie and how TensorRef lets you create a const Tensor& from a TensorImpl* without needing to bump your reference count.
Further reading.
- Why you shouldn't feel bad about passing tensor by reference https://dev-discuss.pytorch.org/t/we-shouldnt-feel-bad-about-passing-tensor-by-reference/85
- Const correctness in PyTorch https://github.com/zdevito/ATen/issues/27
- TensorRef RFC https://github.com/pytorch/rfcs/pull/16
82 episodes
Share
Manage episode 297915922 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.
Reference counting is a common memory management technique in C++ but PyTorch does its reference counting in a slightly idiosyncratic way using intrusive_ptr. We'll talk about why intrusive_ptr exists, the reason why refcount bumps are slow in C++ (but not in Python), what's up with const Tensor& everywhere, why the const is a lie and how TensorRef lets you create a const Tensor& from a TensorImpl* without needing to bump your reference count.
Further reading.
- Why you shouldn't feel bad about passing tensor by reference https://dev-discuss.pytorch.org/t/we-shouldnt-feel-bad-about-passing-tensor-by-reference/85
- Const correctness in PyTorch https://github.com/zdevito/ATen/issues/27
- TensorRef RFC https://github.com/pytorch/rfcs/pull/16
82 episodes
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Similar to PyTorch Developer Podcast
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continue reading
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