Fix unstable tokenizer fingerprinting (enables map cache reuse)#7982
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Fix unstable tokenizer fingerprinting (enables map cache reuse)#7982KOKOSde wants to merge 1 commit intohuggingface:mainfrom
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Tokenizers backed by `tokenizers` can mutate truncation/padding state when called, which made dataset transform fingerprints unstable and prevented `.map(load_from_cache_file=True)` from reusing cached results. This change makes tokenizer hashing stable by temporarily clearing backend truncation/padding during serialization for fingerprinting, then restoring it. Add a regression test and a simple benchmark to demonstrate cache-hit speedups. Fixes huggingface#3847
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Hi! It looks like the GitHub Actions check suites for this PR are in Could a maintainer please approve/run the workflows so CI can execute? Happy to address anything CI flags once it runs. |
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Fix unstable dataset fingerprinting when hashing
PreTrainedTokenizerFast.Some tokenizers backed by
tokenizers.Tokenizermutate runtime settings (padding/truncation) when called, which can change the serialized state and make dataset fingerprints unstable. That prevents.map(load_from_cache_file=True)from reusing cache files.Fix: when hashing, temporarily disable backend padding/truncation so runtime settings don’t affect the fingerprint, then restore the original settings.
Includes a regression test showing
Hasher.hash(tokenizer)stays stable after calling the tokenizer.