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Bump tokenizers from 0.19.1 to 0.20.0 in /pytorch in the pytorch group #387

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@dependabot dependabot bot commented on behalf of github Sep 16, 2024

Bumps the pytorch group in /pytorch with 1 update: tokenizers.

Updates tokenizers from 0.19.1 to 0.20.0

Release notes

Sourced from tokenizers's releases.

Release v0.20.0: faster encode, better python support

Release v0.20.0

This release is focused on performances and user experience.

Performances:

First off, we did a bit of benchmarking, and found some place for improvement for us! With a few minor changes (mostly #1587) here is what we get on Llama3 running on a g6 instances on AWS https://github.com/huggingface/tokenizers/blob/main/bindings/python/benches/test_tiktoken.py : image

Python API

We shipped better deserialization errors in general, and support for __str__ and __repr__ for all the object. This allows for a lot easier debugging see this:

>>> from tokenizers import Tokenizer;
>>> tokenizer = Tokenizer.from_pretrained("bert-base-uncased");
>>> print(tokenizer)
Tokenizer(version="1.0", truncation=None, padding=None, added_tokens=[{"id":0, "content":"[PAD]", "single_word":False, "lstrip":False, "rstrip":False, ...}, {"id":100, "content":"[UNK]", "single_word":False, "lstrip":False, "rstrip":False, ...}, {"id":101, "content":"[CLS]", "single_word":False, "lstrip":False, "rstrip":False, ...}, {"id":102, "content":"[SEP]", "single_word":False, "lstrip":False, "rstrip":False, ...}, {"id":103, "content":"[MASK]", "single_word":False, "lstrip":False, "rstrip":False, ...}], normalizer=BertNormalizer(clean_text=True, handle_chinese_chars=True, strip_accents=None, lowercase=True), pre_tokenizer=BertPreTokenizer(), post_processor=TemplateProcessing(single=[SpecialToken(id="[CLS]", type_id=0), Sequence(id=A, type_id=0), SpecialToken(id="[SEP]", type_id=0)], pair=[SpecialToken(id="[CLS]", type_id=0), Sequence(id=A, type_id=0), SpecialToken(id="[SEP]", type_id=0), Sequence(id=B, type_id=1), SpecialToken(id="[SEP]", type_id=1)], special_tokens={"[CLS]":SpecialToken(id="[CLS]", ids=[101], tokens=["[CLS]"]), "[SEP]":SpecialToken(id="[SEP]", ids=[102], tokens=["[SEP]"])}), decoder=WordPiece(prefix="##", cleanup=True), model=WordPiece(unk_token="[UNK]", continuing_subword_prefix="##", max_input_chars_per_word=100, vocab={"[PAD]":0, "[unused0]":1, "[unused1]":2, "[unused2]":3, "[unused3]":4, ...}))
>>> tokenizer
Tokenizer(version="1.0", truncation=None, padding=None, added_tokens=[{"id":0, "content":"[PAD]", "single_word":False, "lstrip":False, "rstrip":False, "normalized":False, "special":True}, {"id":100, "content":"[UNK]", "single_word":False, "lstrip":False, "rstrip":False, "normalized":False, "special":True}, {"id":101, "content":"[CLS]", "single_word":False, "lstrip":False, "rstrip":False, "normalized":False, "special":True}, {"id":102, "content":"[SEP]", "single_word":False, "lstrip":False, "rstrip":False, "normalized":False, "special":True}, {"id":103, "content":"[MASK]", "single_word":False, "lstrip":False, "rstrip":False, "normalized":False, "special":True}], normalizer=BertNormalizer(clean_text=True, handle_chinese_chars=True, strip_accents=None, lowercase=True), pre_tokenizer=BertPreTokenizer(), post_processor=TemplateProcessing(single=[SpecialToken(id="[CLS]", type_id=0), Sequence(id=A, type_id=0), SpecialToken(id="[SEP]", type_id=0)], pair=[SpecialToken(id="[CLS]", type_id=0), Sequence(id=A, type_id=0), SpecialToken(id="[SEP]", type_id=0), Sequence(id=B, type_id=1), SpecialToken(id="[SEP]", type_id=1)], special_tokens={"[CLS]":SpecialToken(id="[CLS]", ids=[101], tokens=["[CLS]"]), "[SEP]":SpecialToken(id="[SEP]", ids=[102], tokens=["[SEP]"])}), decoder=WordPiece(prefix="##", cleanup=True), model=WordPiece(unk_token="[UNK]", continuing_subword_prefix="##", max_input_chars_per_word=100, vocab={"[PAD]":0, "[unused0]":1, "[unused1]":2, ...}))

The pre_tokenizer.Sequence and normalizer.Sequence are also more accessible now:

from tokenizers import normalizers
norm = normalizers.Sequence([normalizers.Strip(), normalizers.BertNormalizer()])
norm[0]
norm[1].lowercase=False

What's Changed

... (truncated)

Commits
  • a5adaac version 0.20.0
  • a8def07 Merge branch 'fix_release' of github.com:huggingface/tokenizers into branch_v...
  • fe50673 Fix CI
  • b253835 push cargo
  • fc3bb76 update dependencies
  • bfd9cde Perf improvement 16% by removing offsets. (#1587)
  • bd27fa5 add deserialize for pre tokenizers (#1603)
  • 56c9c70 Tests + Deserialization improvement for normalizers. (#1604)
  • 49dafd7 Fix strip python type (#1602)
  • bded212 Support None to reset pre_tokenizers and normalizers, and index sequences (...
  • Additional commits viewable in compare view

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Bumps the pytorch group in /pytorch with 1 update: [tokenizers](https://github.com/huggingface/tokenizers).


Updates `tokenizers` from 0.19.1 to 0.20.0
- [Release notes](https://github.com/huggingface/tokenizers/releases)
- [Changelog](https://github.com/huggingface/tokenizers/blob/main/RELEASE.md)
- [Commits](huggingface/tokenizers@v0.19.1...v0.20.0)

---
updated-dependencies:
- dependency-name: tokenizers
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: pytorch
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot bot added dependencies Pull requests that update a dependency file python Pull requests that update Python code labels Sep 16, 2024
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Dependency Review

✅ No vulnerabilities or license issues or OpenSSF Scorecard issues found.

OpenSSF Scorecard

PackageVersionScoreDetails
pip/tokenizers 0.20.0 🟢 5
Details
CheckScoreReason
Code-Review🟢 8Found 24/27 approved changesets -- score normalized to 8
Maintained🟢 1030 commit(s) and 19 issue activity found in the last 90 days -- score normalized to 10
CII-Best-Practices⚠️ 0no effort to earn an OpenSSF best practices badge detected
License🟢 10license file detected
Signed-Releases⚠️ -1no releases found
Branch-Protection⚠️ -1internal error: error during branchesHandler.setup: internal error: githubv4.Query: Resource not accessible by integration
Binary-Artifacts🟢 10no binaries found in the repo
Dangerous-Workflow🟢 10no dangerous workflow patterns detected
Token-Permissions⚠️ 0detected GitHub workflow tokens with excessive permissions
Security-Policy⚠️ 0security policy file not detected
Fuzzing⚠️ 0project is not fuzzed
Pinned-Dependencies⚠️ 0dependency not pinned by hash detected -- score normalized to 0
Packaging🟢 10packaging workflow detected
SAST⚠️ 0SAST tool is not run on all commits -- score normalized to 0
Vulnerabilities⚠️ 012 existing vulnerabilities detected

Scanned Manifest Files

pytorch/hf-genai-requirements.txt
  • tokenizers@0.20.0
  • tokenizers@0.19.1

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dependabot bot commented on behalf of github Sep 23, 2024

Looks like tokenizers is updatable in another way, so this is no longer needed.

@dependabot dependabot bot closed this Sep 23, 2024
@dependabot dependabot bot deleted the dependabot/pip/pytorch/pytorch-3b2d776fe8 branch September 23, 2024 13:36
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