Fix unstable tokenizer fingerprinting (enables map cache reuse) #7982
+133
−3
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
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 Co-authored-by: Cursor <[email protected]>
KOKOSde
force-pushed
the
perf/stable-tokenizer-fingerprint
branch
from
fac0934 to
8c1891b
Compare
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
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.