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[OMNIML-5935] Fix hf_ptq overwriting valid pad_token with eos_token - #2597
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ChangesTokenizer pad-token preservation
Priority: ➖ Normal Estimated code review effort: 2 (Simple) | ~8 minutes Change: Bug fix Merge Risk: ⚪ Minimal · up to The change preserves models’ existing padding configuration while retaining the fallback for models without a pad token. No concrete issue blocks merging after normal checks. 🚥 Pre-merge checks | ✅ 5 | ❌ 1❌ Failed checks (1 warning)
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Review comments at @CHANGELOG.rst:
- Line 92: Rewrite the changelog entry as a concise, user-facing description
that exported tokenizers preserve the source model’s valid padding settings.
Remove the internal script path, implementation condition, and internal bug ID.
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CHANGELOG.rstexamples/hf_ptq/example_utils.py
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## main #2597 +/- ##
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The fix stops valid pad tokens from being overwritten, but it also starts replacing <unk> pad tokens with eos_token. The old code deliberately skipped that case, and the PR body wrongly says <unk> models are unaffected.
Needs action:
- Fix the
<unk>regression inexamples/hf_ptq/example_utils.py:379. The simplest option isif tokenizer.pad_token is None:, which matchesget_processorand the other examples. If you do mean to replace<unk>, say why in the PR body and rewrite the code comment (see inline). - Correct the backward-compatibility line in the PR body. Under the current diff,
<unk>pad tokens now becomeeos_token. - Add a unit test for
get_tokenizerthat checks three cases: a valid pad token is kept, a missing pad token falls back toeos_token, and whatever<unk>behavior you settle on. A small stub tokenizer or a tiny HF tokenizer fixture is enough. Today nothing covers this path, so the bug could come back unnoticed.
No action needed:
- The CHANGELOG entry looks right, apart from the wording that depends on the
<unk>decision.
| # can't set attribute 'pad_token' for "<unk>" | ||
| if tokenizer.pad_token != "<unk>" or tokenizer.pad_token is None: | ||
| # can't set attribute 'pad_token' for "<unk>"; leave other valid pad tokens unchanged | ||
| if tokenizer.pad_token is None or tokenizer.pad_token == "<unk>": |
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This does more than fix the inversion. It also changes what happens when the pad token is <unk>. The old condition pad != "<unk>" or pad is None was False for <unk>, so those tokenizers were left alone. The comment above ("can't set attribute 'pad_token' for ''") is the reason it skipped them. With this change, <unk> gets replaced by eos_token. That changes padding for Llama-style tokenizers, and for the tokenizers that comment warns about, it can raise the error it describes.
The minimal fix, which matches get_processor below and the other examples, is:
if tokenizer.pad_token is None:
tokenizer.pad_token = tokenizer.eos_tokenIf you do mean to replace <unk>, please update the comment (it now says the opposite of what the code does) and the backward-compat claim in the PR body.
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Good catch — updated in 6ff9adc. Changed to if tokenizer.pad_token is None: (matching get_processor) so we only set a fallback when none exists, leaving <unk> and any other existing token untouched. Also cleaned up the CHANGELOG entry and the PR body.
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The <unk> regression is fixed, and get_tokenizer now matches get_processor. The regression test I asked for last round is still missing, so the owner should decide whether it's needed before merge.
Needs action:
- 💬 Author replied: switched to
if tokenizer.pad_token is None:in 6ff9adc. Still needs aget_tokenizertest in the existingtests/examples/hf_ptq/test_example_utils.py, using a stub tokenizer. It should check three cases: a valid pad token is kept,<unk>is kept, and a missing pad token falls back toeos_token. - Fix the PR body, which still describes the old fix. Its "After" snippet shows
pad_token is None or pad_token == "<unk>", but the code no longer does that. Replace the snippet with the current condition.
No action needed:
- ✔️ Resolved since the last review: the
<unk>replacement regression, the stale code comment, and the CHANGELOG wording (CodeRabbit's request to remove internal details). - The PR body's claim that models with
Noneor<unk>pad tokens are unaffected is now accurate.
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Approving: everything from earlier reviews is fixed. The fix is a one-line change to match get_processor, and the new tests cover all three pad-token cases.
No action needed.
No action needed:
- ✔️ Resolved since the last review: the
<unk>replacement regression, the missingget_tokenizerregression test (now intests/examples/hf_ptq/test_example_utils.py), the stale "After" snippet in the PR body, and the CHANGELOG wording CodeRabbit flagged. - The test monkeypatches
example_utils.AutoTokenizer.from_pretrainedwith a stub, and monkeypatch restores it afterwards. The three cases are: a valid pad token is kept,<unk>is kept, and a missing pad token falls back toeos_token. I read the tests but didn't run them. - No existing tests were changed. No licensing changes.
get_tokenizer() had an inverted condition: it replaced pad_token whenever it was NOT "<unk>" or was None, which overwrote any valid existing token. For Qwen3-0.6B the pad_token <|endoftext|> (151643) was silently replaced with eos_token <|im_end|> (151645) in the exported tokenizer while generation_config.json retained the original ID, creating a mismatch. Fix the condition to only replace when pad_token is None (missing) or is "<unk>" (unusable as a pad token), preserving all other existing tokens. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> Signed-off-by: Zhiyu Cheng <zhiyuc@nvidia.com>
Per review feedback: replace pad_token with eos_token only when the tokenizer has no pad_token at all. This matches get_processor() and avoids silently replacing any existing pad token, including <unk>. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> Signed-off-by: Zhiyu Cheng <zhiyuc@nvidia.com>
Tests three cases: valid pad token preserved, <unk> preserved, and None falls back to eos_token. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> Signed-off-by: Zhiyu Cheng <zhiyuc@nvidia.com>
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> Signed-off-by: Zhiyu Cheng <zhiyuc@nvidia.com>
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… needed (#2609) ### What does this PR do? Type of change: bug fix ### Summary of the series Every pipeline that quantizes, prunes, sparsifies or distills a Hugging Face model now starts the same way: **make the checkpoint local, then load from it**. `ensure_local_checkpoint` returns a local directory as-is and downloads a Hub model ID in full if it is not cached yet -- once, on rank 0 -- and the model, tokenizer and processor are then loaded from that local directory. Before, a Hub ID went straight to `from_pretrained`, which fetched only the files loading needed, so every later step that needed the source as files found its own way back to it: `hf_ptq` through a hand-rolled cache lookup (`_resolve_model_path`, whose `TRANSFORMERS_CACHE` glob picked the lexicographically largest commit hash rather than `refs/main`) and a hardcoded download allowlist, regenerating tokenizer files along the way; the Megatron export by fetching only `*.py` for a Hub ID; other callers of `export_hf_checkpoint` not at all. With the source on local disk, exports follow one rule: an export writes the **model files** -- weights in any format and the metadata describing them -- and carries every other source file (**non-model files**: tokenizer, processor, remote code, chat templates, README, ...) over verbatim, from **local disk only**. Merge in order: 1. #2607 — Add `ensure_local_checkpoint` to load models from local disk, and `copy_non_model_files` 2. #2608 — HF exporters write off-index safetensors and non-model files 3. #2609 — `hf_ptq`: load the model from local disk, downloading it first if needed ← **this PR** 4. #2610 — `megatron_bridge`: load the HF model from local disk; Megatron export copies its non-model files 5. #2611 — `llm_sparsity`: load the model from local disk, downloading it first if needed ### This PR [3/5] **Loading.** `main()` now makes the model local before anything else: `ensure_local_checkpoint(--pyt_ckpt_path)` returns a local directory as-is or downloads a Hub ID once, and every later step -- loading the model, tokenizer and processor, the MXFP4 cast, and the export's copy of the source's files -- reads that local copy. `--pyt_ckpt_path` stays as given; the local directory is `args.local_checkpoint_path`, and `args.hub_model_id` (the Hub ID, or `None`) still names the layerwise resume directory. This replaces the per-step ways back to the source -- `_resolve_model_path`, a hardcoded sidecar allowlist, `_resolved_local_dir`, `hf_hub_download` fallbacks. **Exporting.** The unified exporters copy the source's non-model files themselves (#2608), so the example no longer does -- except after the deprecated TensorRT-LLM export, which does not. It also stops regenerating tokenizer and processor files: the source's are carried over verbatim. So a `pad_token` that `get_tokenizer` sets for calibration (the EOS token, for a model without one) no longer leaks into the exported tokenizer; #2597 already stopped it overwriting an existing pad token. It also removes the default padding side and pad token threaded through six functions only to undo that before saving. The three notebooks do the same: make the model local first, load from it, and leave the tokenizer files to the export. Mostly deletions (+84 / −466). ### Usage No flag change. `--pyt_ckpt_path org/model` downloads the whole repo once before loading; to skip files, download it yourself (e.g. `hf download org/model --exclude 'original/*'`) and pass the local path. ### Testing Same suite as #2607: 685 passed (the `hf_ptq` tests moved to the library in #2607 or were dropped with the code they covered). Notebooks validated as JSON. CPU only (torch 2.12, transformers 5.9, huggingface_hub 1.19); `transformer_engine` cannot be imported in this environment, so GPU and Megatron tests are left to CI. ### Before your PR is "*Ready for review*" Make sure you read and follow [Contributor guidelines](https://github.com/NVIDIA/Model-Optimizer/blob/main/CONTRIBUTING.md) and your commits are signed (`git commit -s -S`). Make sure you read and follow the [Security Best Practices](https://github.com/NVIDIA/Model-Optimizer/blob/main/SECURITY.md#security-coding-practices-for-contributors) (e.g. avoiding hardcoded `trust_remote_code=True`, `torch.load(..., weights_only=False)`, `pickle`, etc.). - Is this change backward compatible?: ✅ (`--pyt_ckpt_path` unchanged; exports carry the source's files as-is) - If you copied code from any other sources or added a new PIP dependency, did you follow guidance in `CONTRIBUTING.md`: N/A - Did you write any new necessary tests?: N/A (removes code; the new helpers are tested in #2607/#2608) - Did you update [Changelog](https://github.com/NVIDIA/Model-Optimizer/blob/main/CHANGELOG.rst)?: N/A (the `pad_token` fix is #2597's entry; the verbatim copy is #2608's) - Did you get Claude approval on this PR?: ❌ ### Additional Information Stacked on #2608. <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **Updates** * Models and tokenizers are loaded from a locally resolved checkpoint, which is reused across quantization and export steps. * TensorRT-LLM exports include non-model files from the local checkpoint, and multimodal exports save the source configuration. * Quantized exports no longer separately save tokenizer files or restore tokenizer padding settings. Local checkpoint paths are also used when restoring compressed weights and resolving source configurations. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Signed-off-by: Shengliang Xu <shengliangx@nvidia.com>
2 participants
What does this PR do?
Type of change: Bug fix
get_tokenizer()inexamples/hf_ptq/example_utils.pyhad an inverted guard condition that replaced a model's existingpad_tokenwitheos_tokenwhenever the token was not"<unk>". For Qwen3-0.6B (and any model whose pad_token is a valid non-<unk>token), this silently overwrote<|endoftext|>(151643) with<|im_end|>(151645) in the exported tokenizer, whilegeneration_config.jsonretained the original ID — creating a mismatch.Root cause — the condition:
evaluates to
Truefor any valid non-<unk>token (e.g.<|endoftext|>), overwriting it.Fix — only set a fallback when no pad token exists at all, matching
get_processor()in the same file:Usage
Testing
tests/examples/hf_ptq/test_example_utils.pycovering three cases: valid pad token is preserved,<unk>pad token is preserved, andNonefalls back toeos_token.Before your PR is "Ready for review"
eos_tokenas a fallback)CONTRIBUTING.md: N/AAdditional Information
🤖 Generated with Claude Code
Summary by CodeRabbit
<unk>and other valid values. The EOS token is now used as the padding token only when no padding token is set. Exported tokenizers retain the source padding configuration, while still receiving a fallback when one is needed.