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Deterministic order of classes and images for the Omniglot dataset #8678

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V0XNIHILI
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PR for #8677

By sorting the output of the list_files() and list_dir() helper functions, the order of samples in the Omniglot dataset can be made deterministic across OSes which helps reproducibility across machines for few-shot learning tasks where the accuracy can change significantly when different classes are used at a certain instant.

… classes and images in the Omniglot torchvision dataset
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pytorch-bot bot commented Oct 9, 2024

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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/vision/8678

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@NicolasHug
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Sorry @V0XNIHILI , if we were to sort the input we'd be running the risk of outputting the dataset in a different order than how it was originally packaged.
Ensuring that the order is reproducible within an arch seems reasonable , but across OSs it may not be in scope

@V0XNIHILI
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V0XNIHILI commented Oct 11, 2024

I understand! What would be the best way to go about it then? For example, other torchvision datasets do not have this issue as they retrieve the filenames (and as such, also the order) from a separate file instead of listing files and dirs.

For example: would it make sense to store a copy of the original order in file and then load this?

That guarantees:

  • Same order across OSes
  • Same ordering as original dataset

Let me know, happy to work on this!

@NicolasHug
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I think storing a copy of the original order would have to be part of the original dataset, but that's not somethin torchvision can control, only the dataset authors can do something about that.

I'm not sure there's an easy way to enforce what you need unfortunately, sorry :/

BTW, according to SO this seems to be more of a file-system dependent issue rather than OS-dependent:
https://stackoverflow.com/questions/31534583/is-os-listdir-deterministic

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3 participants