Update the dataset cache to factor input parameters #6234
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YosuaMichael
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Jul 4, 2022
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Thanks @datumbox for this PR! This is definitely a pain-point during experimentation and quite often the cache can lead to a weird bug if we are not aware of it.
I only have one small comment of adding step_between_clips, other than that it looks good.
| import hashlib | ||
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| h = hashlib.sha1(filepath.encode()).hexdigest() | ||
| value = f"{filepath}-{args.clip_len}-{args.kinetics_version}-{args.frame_rate}" |
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Should we also add args.step_between_clips here?
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We don't have such as parameter on args. If we introduce it, we should absolutely add it here.
YosuaMichael
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Jul 4, 2022
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Jul 6, 2022
Summary: * Update the dataset cache to factor in parameters from the args. * Fix linter Reviewed By: jdsgomes Differential Revision: D37643907 fbshipit-source-id: e0590c3e3b596dd3e12041c095c4b961941e0d38
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The cache path currently used on video references doesn't factor in parameters that affect the stored data (such as clip length, kinetics version and frame rate). This means that every time we switch to a different model, we must invalidate the cache. This PR avoids this by adding the specific parameters in the
sha1hash used for caching.Proof this works: