[https://nvbugs/6507080][fix] Override TokenizerBase.__repr__ to return f"{self.__class__.__name__}()"…#16839
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[https://nvbugs/6507080][fix] Override TokenizerBase.__repr__ to return f"{self.__class__.__name__}()"…#16839trtllm-agent wants to merge 2 commits into
TokenizerBase.__repr__ to return f"{self.__class__.__name__}()"…#16839trtllm-agent wants to merge 2 commits into
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WalkthroughAdds a fallback ChangesTokenizer representation and test enablement
Estimated code review effort: 1 (Trivial) | ~2 minutes 🚥 Pre-merge checks | ✅ 5✅ Passed checks (5 passed)
✨ Finishing Touches🧪 Generate unit tests (beta)
Comment |
PreTrainedTokenizerBase.__repr__ reads properties (e.g.
added_tokens_decoder) that TokenizerBase subclasses are not required
to implement. When a user-supplied custom tokenizer becomes a field of
the pydantic llm_args model, logging f"LLM Args:\n{llm_args}" in
py_executor_creator triggers pydantic's __repr__, which recursively
calls repr() on the tokenizer and blows up with NotImplementedError.
Override __repr__ on TokenizerBase to return a class-name-only string
so pydantic reprs and startup logging never crash on custom tokenizers.
Signed-off-by: handongl <handongl@nvidia.com>
Signed-off-by: handongl <handongl@nvidia.com>
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Summary
__repr__, which reads the abstractadded_tokens_decoderproperty and raisesNotImplementedErroron user protocol subclassesTokenizerBase.__repr__to returnf"{self.__class__.__name__}()"so pydantic/logging never touches transformers-internal state on custom tokenizersTest plan
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Dev Engineer Review
TokenizerBaseintensorrt_llm/tokenizer/tokenizer.pyto override__repr__, returningf"{self.__class__.__name__}()".PreTrainedTokenizerBase.__repr__from touching tokenizer properties (e.g.,added_tokens_decoder) thatTokenizerBasesubclasses may not implement, avoidingNotImplementedErrorduring pydantic representation and startup/logging.QA Engineer Review
tests/integration/test_lists/waives.txtunittest/llmapi/test_llm.py::test_llm_with_customized_tokenizer(no entries added).