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Option to avoid reloading weights at every inference #383

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Kirscher opened this issue Nov 6, 2024 · 2 comments
Open

Option to avoid reloading weights at every inference #383

Kirscher opened this issue Nov 6, 2024 · 2 comments

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@Kirscher
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Kirscher commented Nov 6, 2024

Hello,

I am using TotalSegmentator for multiple inferences and noticed that the weights are reloaded at each inference. This significantly increases the runtime and memory usage.

Would there be an option to keep the weights in memory between inferences to optimize performance?

Thank you for your attention to this request.

Best regards

@wasserth
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Unfortunately supporting this would require a large refactoring of the code base. Therefore, this did not happen so far.

@Kirscher
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Hi @wasserth

Thanks for the update. I understand the challenge with refactoring.

Also, on another note, regarding dropout: would it be possible to introduce it easily into the project to obtain a distribution of segmentations? If so, I'd be happy to work on it and propose a PR.

Thanks for your feedback

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