[Bugfix][Frontend] Let pooling requests set padding

[Hert4]

Purpose

Pooling endpoints build TokenizeParams from a fixed field list in
_build_pooling_tok_params, not from tokenization_kwargs, and that list had no padding
field. So there was no value a caller could send to /v1/embeddings that pads the prompt —
offline LLM.embed accepts tokenization_kwargs={"padding": "max_length"}, online had no
equivalent.

Models trained with a fixed sequence length and no attention mask are silently wrong
without it. SigLIP is the case that surfaced this: padding tokens are part of the input and
the pooled embedding is read from the last position, so unpadded text embeddings are not
comparable with the image embeddings. The request returns 200 with a correctly shaped
vector; only the values are wrong.

Fix

Add a padding field to the pooling request, taking the Transformers spellings
"max_length" and "do_not_pad", and apply it through the existing
TokenizeParams.with_kwargs — which is already where vLLM translates that vocabulary. No
new mapping logic.

# offline
llm.embed(prompts, tokenization_kwargs={"padding": "max_length", "max_length": 64})
# online
extra_body={"padding": "max_length"}

A closed set rather than a free-form dict, so what a client may send online stays explicit.
Transformers' padding=False is deliberately not accepted: with_kwargs guards the padding
mapping with a truthiness check, so False is popped and silently ignored, while
"do_not_pad" works. A rejected value is better than one that quietly does nothing. Fixing
that guard looks like a separate change.

vision_embedding_offline.py and vision_embedding_online.py both already had a
run_siglip, and both embedded text without padding — demonstrating this bug rather than
the fix. Both now pass it.

Whether a model should be able to declare padding as a default, so callers do not have to
know, is a separate question and not in this PR.

Test plan

test_padding sits next to test_truncate_prompt_tokens in
tests/entrypoints/pooling/embed/test_online.py. Against a real server it asserts that
padding="max_length" raises the prompt token count, that "do_not_pad" matches the
default, and that an unsupported value is rejected.

pytest tests/entrypoints/pooling/embed/test_online.py::test_padding -q

Test result

Run on an NVIDIA GB10 (sm_121, aarch64), together with the existing truncation test as a
control:

tests/entrypoints/pooling/embed/test_online.py::test_padding             PASSED
tests/entrypoints/pooling/embed/test_online.py::test_truncate_prompt_tokens PASSED
2 passed in 33.18s

Separately, serving google/siglip2-base-patch16-224 --runner pooling --max-model-len 64
and comparing /v1/embeddings against a HF reference tokenized with
padding="max_length", max_length=64:

request	cosine vs HF reference
extra_body={"padding": "max_length"}	1.000000
no padding	0.616077, 0.644452

The padded result matches the reference exactly. Without it the embedding is not usable for
retrieval, and before this PR there was no way to ask for it over HTTP.

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[Hert4]

@DarkLight1337 @njhill CODEOWNERS for vllm/renderers. @noooop for the pooling endpoints.

One thing worth a reviewer's eye: @DarkLight1337, you added the padding block in f0a1c84. with_kwargs guards it with if padding := tokenization_kwargs.pop("padding", None), so padding=False is popped and the elif padding in (False, "do_not_pad") branch below never runs. If I read that right it is already a no-op on main for any model with a padded default and it is why this PR cannot tell "explicitly disabled" from "unspecified". Sentinel here, separate PR for that branch, or leave it?

Force-pushed 3ff12dc → a5b4609: .with_kwargs() to match the ten existing overrides, plus two corrections to the description that were mine.

pre-run-check is failing on the label gate rather than on the diff, so pre-commit is skipped, could someone add ready or run /ci run?

[DarkLight1337]

SigLIP is trained with padding="max_length"

The official checkpoint is indeed like this, but this isn't really inherent to the model definition, I don't think it's proper to hardcode this for all SigLIP checkpoints. Instead it would be better to show this inside the example files (e.g. examples/pooling/embed/vision_embedding_offline.py)

[Hert4]

It's not a hardcoded value, text_config.max_position_embeddings comes from the checkpoint config, so a different checkpoint gets its own length.

What isn't checkpoint-specific: SiglipTextTransformer.forward takes no attention mask and get_text_features flips the sequence so CLS pooling reads the last position. The embedding shifts with however many pads trail the text.

Examples won't cover

/v1/embeddings 

though, there's no padding field on the request and no CLI flag.

If the worry is a finetune trained unpadded, I can add an opt-out instead.

[Hert4]

@DarkLight1337, you're right, max_position_embeddings isn't in any SigLIP config.json, it's the SiglipTextConfig default of 64, so every checkpoint gets 64 anyway.

The tokenizer config does say something useful though: "model_input_names": ["input_ids"] on both siglip1 and siglip2, so no attention mask. Gating on that, a finetune trained with masking would opt out on its own:

if "attention_mask" in self.get_tokenizer().model_input_names:
    return tok_params
return tok_params.with_kwargs(pad_prompt_tokens=self.get_text_max_length())

Length still needs max_position_embeddings though model_max_length is 64 on siglip1 but 1e30 on siglip2.
Does that work?

[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @Hert4.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork

[Hert4]

Rebased — the conflict was from #50907 removing attention_config from this test file. Diff unchanged.

@noooop any preference on renderer vs pooling layer? @DarkLight1337 if noooop is tied up, happy to go with whichever you prefer.

Also, CI has never run on this — pre-run-check is blocked on the label gate. Could someone add ready?

[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @Hert4.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork

[Hert4]

Status check, since this has been open for close to three weeks and I do not want it to stall on something I can resolve myself.

One open question, and it is a placement decision, not a correctness one. @DarkLight1337 asked on Aug 5 why this cannot live in the pooling layer and handed it to @noooop; that thread never got a verdict. My answer, restated against main as it stands today rather than the paths I quoted on Aug 15, since the pooling protocol has been reorganised since then:

build_tok_params now lives in PoolingTokenizeParamsMixin / EmbeddingTokenizeParamsMixin (vllm/entrypoints/pooling/base/protocol.py), and its signature is

def build_tok_params(self, model_config: ModelConfig) -> TokenizeParams:

It takes the request and the model config, and returns one TokenizeParams for the whole batch. There is no prompt parameter, so a per-prompt decision cannot be expressed there. Padding has to be per-prompt: a mixed batch must pad the text prompts and leave the multimodal ones alone. _tokenize_singleton_prompt is the first point that sees an individual prompt, which is why the helper sits in the tokenize path.

If someone would rather it sat in the pooling layer anyway, I am happy to write it, but it needs build_tok_params to become prompt-aware, and that felt like a larger change than this bugfix should be making on its own.

Proposal so this stops waiting on a decision nobody owns: unless there is an objection in the next week, I will take the current placement as settled and leave the code as is. A one-line "keep it" or "move it" from either of you is enough, and I will act on whichever it is.

Separately, the mechanical blocker. CI has never run on this PR. pre-run-check fails in five seconds on the contributor gate:

PR must have the 'ready', 'verified', or 'ready-run-all-tests' label to run
pre-commit, or the author must have at least 4 merged PRs (found 0).

That is a cycle for a first-time contributor: no label, no CI; no CI, no merge; no merge, never four. Could someone add ready? I have asked twice before, so I assume it is falling off the queue rather than being declined, and I would rather ask once more than keep re-requesting review, which evidently does not surface anything.

Worth noting the drift cost: this has already needed two rebases for conflicts (Aug 12, Aug 17), and the pooling refactor above landed since the last review round. The longer it sits without CI, the more of that accumulates.

Review round from my side is done: everything raised by both of you is addressed, and the test is down to 23 lines per @noooop's last comment.

[Hert4]

Rewritten to what you asked for: pad_prompt_tokens on the pooling request, wired through _build_pooling_tok_params, twelve lines. The model-level default and the renderer fallback are gone. Examples for both offline and online are in examples/pooling/embed/; each embeds the same prompts with and without padding and prints the cosine similarity, so the difference shows up rather than being asserted in prose.

Whether a model should be able to declare the default itself is a separate question, and not in this PR.

[noooop]

Thanks for your contribution.

[DarkLight1337]

Thanis, LGTM now

[DarkLight1337]

/ci run

[github-actions]

✅ Triggered Buildkite CI #85794 for commit 0c33bea947b1.