Row 3808

Row ID: 3808 | Dataset Entry | Axioma AXP Content Repository

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Hi everyone!

*Full disclaimer, this is shameless self-promotion, but one that I hope can be useful to many users here*

I've just released a library that implements sketched SVD and Hermitian eigendecompositions. It can be e.g. used to approximate full Hessians (or any other matrix-free linops) in the millions of parameters up to 90%+ accuracy. But it works in general with any finite-dimensional linear operator (including matrix-free).

It is built on top of PyTorch, with distributed and GPU capabilities, but it also works on CPU and interfaces nicely with e.g. SciPy LinearOperators. It is also thoroughly tested and documented, plus CI and a bunch of bells and whistles.

I'd really appreciate if you can give it a try, and hope you can do some cool stuff with it!

[https://github.com/andres-fr/skerch](https://github.com/andres-fr/skerch)

FieldValue
text Hi everyone! *Full disclaimer, this is shameless self-promotion, but one that I hope can be useful to many users here* I've just released a library that implements sketched SVD and Hermitian eigendecompositions. It can be e.g. used to approximate full Hessians (or any other matrix-free linops) in the millions of parameters up to 90%+ accuracy. But it works in general with any finite-dimensional linear operator (including matrix-free). It is built on top of PyTorch, with distributed and GPU c…
label r/pytorch
dataType post
communityName r/pytorch
datetime 2024-03-24
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Raw Record

{
  "text": "Hi everyone!\n\n*Full disclaimer, this is shameless self-promotion, but one that I hope can be useful to many users here*\n\nI've just released a library that implements sketched SVD  and Hermitian eigendecompositions. It can be e.g. used to approximate full Hessians (or any other matrix-free linops) in the millions of parameters up to 90%+ accuracy. But it works in general with any finite-dimensional linear operator (including matrix-free).\n\nIt is built on top of PyTorch, with distributed and GPU capabilities,  but it also works on CPU and interfaces nicely with e.g. SciPy LinearOperators. It is also thoroughly tested and documented, plus CI and a bunch of bells and whistles.\n\nI'd really appreciate if you can give it a try, and hope you can do some cool stuff with it!\n\n[https://github.com/andres-fr/skerch](https://github.com/andres-fr/skerch)",
  "label": "r/pytorch",
  "dataType": "post",
  "communityName": "r/pytorch",
  "datetime": "2024-03-24",
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}
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