[https://nvbugs/6782263][fix] Serialize HF remote-code loading when building tokenizers

[tianyuxbear]

Summary

One of four GEN-side postprocess workers died building its tokenizer on the GB200 5-node disagg perf-sanity lane:

File ".../tensorrt_llm/executor/postproc_worker.py", line 135, in __init__
  self._tokenizer = load_hf_tokenizer(
File ".../tensorrt_llm/tokenizer/tokenizer.py", line 686, in load_hf_tokenizer
  tokenizer = TransformersTokenizer.from_pretrained(
File ".../transformers/models/auto/configuration_auto.py", line 1500, in from_pretrained
  config_class = get_class_from_dynamic_module(
File ".../transformers/dynamic_module_utils.py", line 311, in get_class_in_module
  return getattr(module, class_name)
AttributeError: module 'transformers_modules...configuration_deepseek'
                has no attribute 'DeepseekV3Config'

A checkpoint genuinely missing the class would have failed all four workers identically, so this is a race — the same one as #17708, reached through the one entry point that was still unguarded.

The dead worker was then silently absorbed and the warm-up request hung until teardown. That second defect is not addressed here.

Root cause

DeepSeek-R1 ships no remote tokenizer at all: tokenizer_config.json declares tokenizer_class: LlamaTokenizerFast with no auto_map. The remote code is the config, and a tokenizer load reaches it anyway, because AutoTokenizer.from_pretrained must resolve the tokenizer class through AutoConfig.from_pretrained first:

# transformers/models/auto/tokenization_auto.py:684, abridged
config = AutoConfig.from_pretrained(
    pretrained_model_name_or_path, trust_remote_code=trust_remote_code, **kwargs)
config_model_type = config.model_type

config.json carries auto_map.AutoConfig = configuration_deepseek.DeepseekV3Config, so that call takes the remote branch and publishes the checkpoint's .py files into the shared HF_MODULES_CACHE with the unlocked, non-atomic shutil.copy that hf_remote_code_lock's docstring already describes. transformers 5.5.4 does have a built-in DeepseekV3Config, but trust_remote_code=True makes it prefer the checkpoint's copy (configuration_auto.py:1484-1500), so the cache is written even though a local class exists.

That docstring names three callers that must share the lock — AutoConfig, AutoProcessor and AutoTokenizer. Only the first two were wired up (_torch/model_config.py:1094, inputs/registry.py:1186).

The postprocess pool is the first writer rather than a late one: worker.py submits all num_postprocess_workers jobs at line 359 and only reaches the guarded ModelConfig.from_pretrained through the model construction at line 401. _init_hf_modules() at line 234 looks like a warm-up but only creates the cache directory and its sys.path entry, copying no .py file. In CI, jenkins/scripts/perf/submit.py sets a node-local HF_HOME=/tmp/hf_home for the ctx and gen worker roles, so each fresh container starts cold.

Fix

Take the existing lock around the HF load in TransformersTokenizer.from_pretrained, the single choke point all seven tokenizer loads in the repo funnel through — the two load_hf_tokenizer blocks, tokenizer_factory, and call sites in ad_executor.py, py_executor_creator.py, bench/utils/data.py and serve/router_utils.py. All seven pass trust_remote_code explicitly, so one guard covers them where guarding call sites individually would be three edits with less coverage.

The guard is a no-op when trust_remote_code is false. Most checkpoints carry no auto_map, and serializing their loads would cost startup time for nothing.

Three points a reviewer may want to check:

• The deferred import is required, not stylistic. A module-scope one cycles: _torch/model_config.py:41 imports llmapi.llm_args, which imports this package back at llmapi/llm_args.py:73-77. Adding the top-level import and running import tensorrt_llm fails with cannot import name 'CacheTransceiverConfig' from partially initialized module. inputs/registry.py:1139 defers for the same reason.
• The PreTrainedTokenizerFast fallback stays outside the lock deliberately. It strips trust_remote_code and reads tokenizer.json directly, never touching the module cache. The lock releases in a finally before exceptions propagate, so the fallback never runs while holding it.
• The lock is not reentrant, so a nested acquire would stall the inner waiter for the full timeout. This cannot nest: the input processors guarded at registry.py:1186 call transformers' AutoTokenizer directly rather than this classmethod, and model_config.py:1094 loads only the config.

Test Coverage

No unit test is added, matching the three prior PRs on this lock (#7268, #7656, #17708).

Offline reproduction, 8 processes against one cold HF_MODULES_CACHE, 30 trials each, transformers 5.5.4 — the version in the failing job:

	failed ranks
unlocked	6 / 240
locked	0 / 240

The failures reproduce the reported AttributeError verbatim, plus a sibling SyntaxError: source code string cannot contain null bytes from the same truncation window. A ~2.5% per-rank rate is why no single CI run would settle this, and why a probabilistic test would be flaky as a gate.

Guard placement was checked against tensorrt_llm 1.3.0rc27 with real compiled bindings: that the HF load happens inside the lock, that no lock is taken when trust_remote_code is false, and that load_hf_tokenizer(dir) with no keyword arguments — the call shape in PostprocWorker.__init__ — still reaches the guard. 2 of 3 fail on the unpatched baseline; all 3 pass with this change.

The perf-sanity case that caught this is no longer enrolled, so this PR touches no test list: #19349 trimmed disagg_upload-e2e-gb200_deepseek-r1-fp4_8k1k_con4096_ctx1_dep4_gen1_dep16_eplb0_mtp1_ccb-NIXL from l0_gb200_multi_nodes_perf_sanity_ctx1_node1_gpu4_gen1_node4_gpu16.yml, which now holds only the gen_only variant. /bot run is issued without --extra-stage. CI instead shows no regression on the shared load path, which it does cover — TransformersTokenizer.from_pretrained is reached by essentially every test that builds a tokenizer.

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Walkthrough

The tokenizer adds a deferred guard for Hugging Face remote-code loading. Trusted remote-code loads use the shared lock. Other loads use a no-op context. AutoTokenizer.from_pretrained now runs inside this guard.

Changes

Tokenizer remote-code loading

Layer / File(s)	Summary
Guard and tokenizer integration tensorrt_llm/tokenizer/tokenizer.py	Adds _hf_remote_code_guard and wraps AutoTokenizer.from_pretrained with the guard based on trust_remote_code.

Priority: ➖ Normal

Estimated code review effort: 2 (Simple) | ~10 minutes

Change: Bug fix

Suggested reviewers: bowenfu

Merge Risk: 🔵 Low · up to da942

The locking fix appears targeted, but its missing regression test leaves a bounded risk of future tokenizer cache races.

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 66.67% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 3 functions across 1 files.	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Title check	✅ Passed	The title clearly identifies the NVBugs issue, fix type, and primary change: serializing Hugging Face remote-code loading during tokenizer construction.
Description check	✅ Passed	The description clearly explains the failure, root cause, fix, scope, lock behavior, and test coverage. It does not include the template's PR Checklist section, but the required technical information …

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Actionable comments posted: 1

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Inline comments:
In `@tensorrt_llm/tokenizer/tokenizer.py`:
- Around line 321-323: Add tokenizer regression coverage for
_hf_remote_code_guard and AutoTokenizer.from_pretrained: mock the shared
hf_remote_code_lock and verify it is held during loading when
trust_remote_code=True, while confirming it is not invoked when
trust_remote_code=False. Place the test under the existing tokenizer tests and
preserve the current load behavior.

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• tensorrt_llm/tokenizer/tokenizer.py

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[JunyiXu-nv]

Overall LGTM. Better to have tests.

[github-actions]

Automatically added "ci: full pre-merge approved" because this PR has satisfied the required GitHub review approvals. Unresolved review conversations and other required checks remain independent merge requirements.

[github-actions]

Semantic conflict review

The verdict of record is the Semantic conflict with target branch / PR #19553 commit status on the requested head commit. This summary updates on reply events and may lag between a new request and its reply.

Latest recorded state: No semantic conflict found (best effort) for head da942eac3057d88d27c4a324bbb07e5bb1c5ea4f, target a81da8a5a8380c4ec8c2d3eafabb8cfc55d7ad56, merge base 945513ae169d78ce3037e1cf198476c0387766dc (request 291aaeae-36b4-4e63-80a6-f771e2586819). CodeRabbit analysis.

Best-effort AI judgment for the recorded revisions. PASS, FAIL and INCONCLUSIVE may be incomplete or incorrect. PR authors and reviewers should independently verify the evidence and relevant behavior. This semantic review and its status/workflow are advisory, not required merge checks under current repository rules; other merge requirements still apply. Advisory status does not make a confirmed defect safe to ignore.

Requested (UTC)	Head	Target	Verdict	Comment
2026-10-02T10:37:10Z	da942eac3057	a81da8a5a838	PASS	reply
2026-10-02T02:49:40Z	da942eac3057	5ce4cb57cb8e	PASS	reply
2026-10-01T20:43:08Z	da942eac3057	80509acfc073	PASS	reply
2026-10-01T12:51:10Z	da942eac3057	ee510fc85d39	PASS	reply
2026-10-01T06:55:21Z	da942eac3057	0d3bbd257d35	PASS	reply
2026-09-30T22:36:48Z	da942eac3057	fc2f8543e039	PASS	reply
2026-09-30T14:44:42Z	da942eac3057	50f85bfe3e94	PASS	reply
2026-09-30T08:45:32Z	da942eac3057	7fe1dd2ba608	PASS	reply
2026-09-30T01:15:27Z	da942eac3057	bdd012579f89	PASS	reply
2026-09-29T16:42:23Z	da942eac3057	ae3531adf3ed	PASS	reply
2026-09-29T10:38:10Z	da942eac3057	d949656a4f87	PASS	reply
2026-09-29T02:47:11Z	da942eac3057	f08592ada02b	PASS	reply
2026-09-28T20:36:11Z	da942eac3057	7dfacfb583e2	PASS	reply
2026-09-28T12:57:56Z	da942eac3057	0c58480ca680	FAIL	reply
2026-09-28T07:07:16Z	da942eac3057	f00e9627fa98	PASS	reply

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[tianyuxbear]

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PR_Github #76640 [ run ] completed with state SUCCESS. Commit: da942ea
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[tianyuxbear]

/bot run --disable-fail-fast

[tensorrt-cicd]

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[QiJune]

@tianyuxbear Please cherry pick this PR to release/1.3 branch as well.

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