Feature/complete sentencepiece tokenizer

[Arpitsh7]

Summary

Completes the SentencePieceTokenizer implementation introduced in #17 by adding encode(), decode(), and load() — making SentencePieceTokenizer fully usable in the pipeline.

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Background

PR #17 introduced a modular tokenizer architecture with SentencePieceTokenizer as one of the implementations. However the current SentencePieceTokenizer only supports training and lacks encode(), decode(), and load().

Since these methods are absent, the tokenizer cannot process text despite being trained, which prevents it from being used in downstream pipeline tasks.

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Changes

openverifiablellm/tokenizer/sentencepiece_tokenizer.py

• Implemented encode(text) -> list[int]
• Implemented decode(ids) -> str
• Implemented load(tokenizer_dir) — reloads from vocab.json + merges.txt
• Added text_file.is_file() validation in train()
• Added _check_loaded() guard for encode/decode

tests/test_sentencepiece.py ← new file

• 18 tests covering training, encode/decode roundtrip, load, artifact paths, special tokens, determinism, and constructor validation

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Testing

pytest tests/test_sentencepiece.py -v

All 18 tests pass.

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Scope

Self-contained change. Touches only sentencepiece_tokenizer.py and tests/test_sentencepiece.py. No overlap with any open PR.

Related

• PR feat: deterministic tokenizer training and config hashing #17 — feat: deterministic tokenizer training and config hashing
• Issue [FEATURE]: Complete SentencePiece tokenizer — encode, decode, load and input validation #51

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Reviewing files that changed from the base of the PR and between a2dfd7a and 0b54e19.

📒 Files selected for processing (4)

• .gitignore
• openverifiablellm/tokenizer/sentencepiece_tokenizer.py
• openverifiablellm/verify.py
• tests/test_sentencepiece.py

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