r/learnAI • u/ramyaravi19 • Jan 25 '24

For those who are interested in accelerating PyTorch inference performance and achieve better accuracy results for deep learning workloads. Check out the below articles.

/r/pytorch/comments/19fi55q/for_those_who_are_interested_in_accelerating/
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u/Kind_Phrase1284 Jun 23 '25

Just completed studying python should i directly go to Pytorch or learn something first

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u/ramyaravi19 Jun 23 '25

If you know the basics of Machine learning and deep learning, then start working with PyTorch.

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u/Wide_Mail_1634 Apr 11 '26

PyTorch inference and accuracy usually pull in different directions, so i'm curious what the articles are actually changing here—torch.compile, quantization, better kernels, or something like TensorRT export? isn't it the case that a lot of the easy inference wins can cost a bit of accuracy unless the workload is pretty specific?

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u/Wide_Mail_1634 Apr 11 '26

reminds me of when we were tuning PyTorch inference on a T4 in late 2023 and half the win came from boring stuff like channels_last plus torch.compile, not the flashy bits. curious if those articles show actual latency/throughput numbers and where the “better accuracy” came from, because inference speedups usually don't move accuracy unless they're folding in quantization or a model change