[CI][Bugfix] Use token-id prefix in batch-invariant decode/prefill consistency test by Evangade · Pull Request #43317 · vllm-project/vllm

Evangade · 2026-05-21T12:47:50Z

Summary

Fixes a long-standing soundness bug in
tests/v1/determinism/test_batch_invariance.py::test_decode_logprobs_match_prefill_logprobs.

The test verifies, for each decoded token at position i, that running
prefill on prompt + decode_tokens[:i] reproduces the same logprob for
decode_tokens[i]. The previous implementation rebuilt the prefill prefix
from text:

Run llm.generate with max_tokens=token_idx to detokenize the partial
output,
Concatenate prompt + partial_text as a Python string,
Pass that string back to llm.generate, which re-encodes it with the
model's tokenizer.

tokenizer.encode(tokenizer.decode(ids)) is not lossless for many BPE
tokenizers. For example with Qwen/Qwen2.5-Coder-0.5B-Instruct, the
adjacent tokens '.' and '#' get merged into a single '.#' token after
detokenization. The reconstructed prefill prefix therefore had a different
token sequence than the decode path, breaking the invariant under test and
producing false mismatches on certain models/inputs. This was reported by
@xRay2016 in #27433.

Fix

Build the prefill prefix directly with token ids:

prompt_token_ids = list(decode_output.prompt_token_ids or [])
prefix_token_ids = prompt_token_ids + list(decode_tokens[:token_idx])
prefill_output = llm.generate(
    [{"prompt_token_ids": prefix_token_ids}],
    prefill_sp,
    use_tqdm=False,
)[0]

This guarantees the prefill request sees the exact same token prefix as the
decode path. As a side effect, it also removes the O(N²) extra
llm.generate call per decoded token (the previous code re-ran a
max_tokens=token_idx generation per position purely to recover the prefix
text).

A tokenizer-only regression test is added in
tests/v1/determinism/test_prefix_token_ids_regression.py that:

Asserts encode(decode(ids)) != ids is reachable on a real
tokenizer/input (Qwen2.5-Coder + '.' + '#'), so a future
"simplification" PR cannot silently reintroduce the text-based round
trip.
Asserts that the new prompt_token_ids + decode_tokens[:i] construction
preserves the sequence by construction.

The regression test only loads a tokenizer (no GPU, no LLM, no
batch-invariant kernels) and runs in a few seconds.

Related: #27433.

Why this is not a duplicate

Searched on 2026-05-21 with gh:

gh pr list --repo vllm-project/vllm --state all --search "test_decode_logprobs_match_prefill_logprobs" → no matching PR
gh pr list --repo vllm-project/vllm --state all --search "test_model_tokenizer batch_invariance" → none
gh pr list --repo vllm-project/vllm --state all --search "decode encode round trip tokenizer determinism" → unrelated only

@xRay2016 reported the issue with a proposed fix on 2026-05-01 and was
acked by @yewentao256, but no PR followed in the ~3 weeks since.

Test plan

CPU regression tests (run on this PR's branch, no GPU required):

.venv/bin/python -m pytest tests/v1/determinism/test_prefix_token_ids_regression.py -v
# 2 passed in 5.42s

GPU smoke for the actual fix (NVIDIA H20, Qwen3-0.6B, 4 prompts × 8 tokens,
batch invariance enabled via conftest.py):

VLLM_TEST_MODEL=Qwen/Qwen3-0.6B \
  VLLM_DECODE_PREFILL_NUM_PROMPTS=4 \
  VLLM_DECODE_PREFILL_MAX_TOKENS=8 \
  .venv/bin/python -m pytest \
    tests/v1/determinism/test_batch_invariance.py::test_decode_logprobs_match_prefill_logprobs -v
# 1 passed in 22.69s
# every position reports "✓ Match (bitwise equal)"

Full default config (Qwen/Qwen3-1.7B, all BACKENDS, larger
VLLM_DECODE_PREFILL_*) was not run locally; happy to have a reviewer
trigger the determinism CI lane.

Lint:

pre-commit run --files \
  tests/v1/determinism/test_batch_invariance.py \
  tests/v1/determinism/test_prefix_token_ids_regression.py
# all hooks pass (ruff, ruff-format, typos, mypy-3.10, SPDX, ...)

AI-assistance disclosure

This change was prepared with AI assistance (CodeBuddy). I reviewed every
changed line and ran the test/lint commands above myself.

@xRay2016

…nsistency test `test_decode_logprobs_match_prefill_logprobs` previously rebuilt the prefill prefix by running an extra `llm.generate(max_tokens=token_idx)` to detokenize the partial output and then submitting `prompt + partial_text` as a string prompt. vLLM re-encodes that string with the model's tokenizer, which is not lossless for many BPE tokenizers — for example Qwen2.5-Coder merges `'.' + '#'` into `'.#'` after detokenization. This silently changed the token-level prefix the test was supposed to verify, producing sporadic false mismatches on certain models/inputs. Build the prefix directly from token ids using `decode_output.prompt_token_ids` plus `decode_token_ids[:i]` and pass it to `llm.generate` as `{"prompt_token_ids": ...}`. This guarantees the prefill request sees the exact same token prefix as the decode path. As a side effect it also avoids the previous O(N^2) extra `llm.generate` call per decoded token. Add a tokenizer-only regression test (`test_prefix_token_ids_regression.py`) that pins down both properties: `encode(decode(ids)) != ids` is reachable on a real tokenizer/input, and the new token-id construction preserves the sequence by construction. Reported by @xRay2016 in vllm-project#27433 Test plan: # CPU-only regression tests .venv/bin/python -m pytest tests/v1/determinism/test_prefix_token_ids_regression.py -v # 2 passed in 5.42s # GPU smoke (Qwen3-0.6B on H20, 4 prompts x 8 tokens) VLLM_TEST_MODEL=Qwen/Qwen3-0.6B \ VLLM_DECODE_PREFILL_NUM_PROMPTS=4 \ VLLM_DECODE_PREFILL_MAX_TOKENS=8 \ .venv/bin/python -m pytest \ tests/v1/determinism/test_batch_invariance.py::test_decode_logprobs_match_prefill_logprobs -v # 1 passed in 22.69s Lint: pre-commit run --files tests/v1/determinism/test_batch_invariance.py \ tests/v1/determinism/test_prefix_token_ids_regression.py # all hooks pass This change was prepared with AI assistance (CodeBuddy). Every changed line was reviewed and the commands above were run by the human submitter. Co-authored-by: CodeBuddy <noreply@codebuddy.dev> Signed-off-by: Yifan Da <1363818765@qq.com>

github-actions · 2026-05-21T12:48:02Z

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gemini-code-assist

Code Review

This pull request refactors the prefill-prefix construction in test_decode_logprobs_match_prefill_logprobs to use token IDs directly, replacing the previous text-based reconstruction. This change prevents false mismatches caused by non-lossless decode -> encode round trips in BPE tokenizers and improves performance by eliminating O(N^2) extra generation calls. A new regression test suite has been added to ensure token sequence integrity. I have no feedback to provide.

Evangade · 2026-05-21T12:51:11Z

Hi @yewentao256 @bwasti — this is a small fix for the batch-invariance
decode/prefill consistency test you maintain in tests/v1/determinism/.
It's blocked by pre-run-check because I'm a new contributor (no merged
PRs yet); could one of you take a look and apply the ready label if it
looks right?

Context for reviewers:

The existing test rebuilt the prefill prefix via decode → encode of
partial output text. That round trip is not lossless for many BPE
tokenizers (Qwen2.5-Coder merges '.' + '#' into '.#'), so the
prefill prefix silently drifted from the decode prefix and produced
false mismatches.
The fix builds the prefix directly from token ids using
decode_output.prompt_token_ids + decode_tokens[:i], which trivially
preserves the sequence and also removes an O(N²) llm.generate call
per decoded token.
A tokenizer-only regression test pins down both properties so the
text-based round trip can't quietly come back.
Reported by @xRay2016 in [Feature]: Batch Invariant Feature and Performance Optimization #27433.

Locally verified:

pytest tests/v1/determinism/test_prefix_token_ids_regression.py -v →
2 passed (CPU).
GPU smoke on H20 with Qwen3-0.6B, 4 prompts × 8 tokens →
test_decode_logprobs_match_prefill_logprobs[FLASH_ATTN] passes
bitwise on every position.

Happy to address feedback. Thanks!

yewentao256

Thanks for the work! This test is very tricky and we don't really rely on it to test batch invariance, we can merge your PR now but the additional specific unit test is not needed

yewentao256 · 2026-05-21T18:46:20Z

+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+"""Regression tests for the prefill-prefix construction used by
+``test_decode_logprobs_match_prefill_logprobs`` in ``test_batch_invariance.py``.
+
+The decode/prefill consistency test verifies, for each decoded token at
+position ``i``, that running prefill on ``prompt + decode_tokens[:i]``
+reproduces the same logprob for ``decode_tokens[i]`` that decode produced.
+
+A previous implementation reconstructed the prefill prefix from text by
+running ``llm.generate`` to detokenize the partial output and then passing
+``prompt + partial_text`` back as a string prompt. vLLM internally re-encoded
+that string through the model's tokenizer, which silently changes the token
+sequence for many BPE tokenizers because ``tokenizer.encode(tokenizer.decode(ids))``
+is not lossless. That broke the underlying invariant of the test (the
+prefill prefix was no longer the same token sequence as the decode prefix)
+and produced sporadic false mismatches.
+
+These tests pin down two properties so the issue does not silently regress:
+
+1. There exist real-world inputs/tokenizers where ``encode(decode(ids)) != ids``.
+   Future "simplification" PRs that reintroduce the text-based round trip must
+   contend with this evidence.
+2. Building the prefix directly with ``prompt_token_ids + decode_tokens[:i]``
+   trivially preserves the token sequence and is the implementation that
+   ``test_decode_logprobs_match_prefill_logprobs`` relies on.
+
+The tests are intentionally tokenizer-only so they run quickly on CPU in CI
+and do not require a GPU, model weights, or batch-invariant kernels.
+"""
+
+from __future__ import annotations
+
+import pytest
+
+pytestmark = pytest.mark.cpu_test
+
+
+@pytest.fixture(scope="module")
+def qwen_coder_tokenizer():
+    """A tokenizer that exhibits BPE merges across the decode/encode boundary.
+
+    Skips if ``transformers`` (or the cached tokenizer files) are unavailable
+    in the current environment.
+    """
+    transformers = pytest.importorskip("transformers")
+    try:
+        return transformers.AutoTokenizer.from_pretrained(
+            "Qwen/Qwen2.5-Coder-0.5B-Instruct",
+        )
+    except Exception as exc:  # pragma: no cover - depends on local cache/network
+        pytest.skip(f"Tokenizer not available offline: {exc}")
+
+
+def _encode(tok, text: str) -> list[int]:
+    return tok.encode(text, add_special_tokens=False)
+
+
+def test_decode_then_encode_can_change_token_ids(qwen_coder_tokenizer):
+    """The decode -> encode round trip is not lossless for some BPE tokenizers.
+
+    With Qwen2.5-Coder, the adjacent tokens ``'.'`` and ``'#'`` get merged into
+    a single ``'.#'`` token after detokenization. Reconstructing a prefill
+    prefix via text therefore produces a *different* token sequence than the
+    decode path used.
+    """
+    tok = qwen_coder_tokenizer
+
+    prompt = "Yesterday I went to the store and bought a new toy."
+    continuation = "#1."
+
+    prompt_ids = _encode(tok, prompt)
+    continuation_ids = _encode(tok, continuation)
+    original_ids = prompt_ids + continuation_ids
+
+    text = tok.decode(original_ids)
+    re_ids = _encode(tok, text)
+
+    # The round trip must change the token sequence on this input; otherwise
+    # the regression scenario this test is guarding against would not exist.
+    assert original_ids != re_ids, (
+        "Expected `encode(decode(ids)) != ids` for this BPE tokenizer/input. "
+        f"original={original_ids}, round_trip={re_ids}"
+    )
+
+
+def test_token_id_prefix_is_preserved_without_round_trip(qwen_coder_tokenizer):
+    """Building a prefix directly from token ids preserves the sequence.
+
+    This mirrors the construction used by
+    ``test_decode_logprobs_match_prefill_logprobs``:
+    ``prefix_token_ids = prompt_token_ids + decode_tokens[:i]``.
+    """
+    tok = qwen_coder_tokenizer
+
+    prompt = "Yesterday I went to the store and bought a new toy."
+    continuation = "#1."
+
+    prompt_ids = _encode(tok, prompt)
+    decode_tokens = _encode(tok, continuation)
+
+    for i in range(len(decode_tokens) + 1):
+        prefix_token_ids = prompt_ids + decode_tokens[:i]
+
+        # The first ``len(prompt_ids)`` ids are exactly the original prompt.
+        assert prefix_token_ids[: len(prompt_ids)] == prompt_ids
+        # The remaining ids are the first ``i`` decode tokens, unchanged.
+        assert prefix_token_ids[len(prompt_ids) :] == decode_tokens[:i]


Suggested change

# SPDX-License-Identifier: Apache-2.0

# SPDX-FileCopyrightText: Copyright contributors to the vLLM project

"""Regression tests for the prefill-prefix construction used by

``test_decode_logprobs_match_prefill_logprobs`` in ``test_batch_invariance.py``.

The decode/prefill consistency test verifies, for each decoded token at

position ``i``, that running prefill on ``prompt + decode_tokens[:i]``

reproduces the same logprob for ``decode_tokens[i]`` that decode produced.

A previous implementation reconstructed the prefill prefix from text by

running ``llm.generate`` to detokenize the partial output and then passing

``prompt + partial_text`` back as a string prompt. vLLM internally re-encoded

that string through the model's tokenizer, which silently changes the token

sequence for many BPE tokenizers because ``tokenizer.encode(tokenizer.decode(ids))``

is not lossless. That broke the underlying invariant of the test (the

prefill prefix was no longer the same token sequence as the decode prefix)

and produced sporadic false mismatches.

These tests pin down two properties so the issue does not silently regress:

1. There exist real-world inputs/tokenizers where ``encode(decode(ids)) != ids``.

Future "simplification" PRs that reintroduce the text-based round trip must

contend with this evidence.

2. Building the prefix directly with ``prompt_token_ids + decode_tokens[:i]``

trivially preserves the token sequence and is the implementation that

``test_decode_logprobs_match_prefill_logprobs`` relies on.

The tests are intentionally tokenizer-only so they run quickly on CPU in CI

and do not require a GPU, model weights, or batch-invariant kernels.

"""

from __future__ import annotations

import pytest

pytestmark = pytest.mark.cpu_test

@pytest.fixture(scope="module")

def qwen_coder_tokenizer():

"""A tokenizer that exhibits BPE merges across the decode/encode boundary.

Skips if ``transformers`` (or the cached tokenizer files) are unavailable

in the current environment.

"""

transformers = pytest.importorskip("transformers")

try:

return transformers.AutoTokenizer.from_pretrained(

"Qwen/Qwen2.5-Coder-0.5B-Instruct",

)

except Exception as exc: # pragma: no cover - depends on local cache/network

pytest.skip(f"Tokenizer not available offline: {exc}")

def _encode(tok, text: str) -> list[int]:

return tok.encode(text, add_special_tokens=False)

def test_decode_then_encode_can_change_token_ids(qwen_coder_tokenizer):

"""The decode -> encode round trip is not lossless for some BPE tokenizers.

With Qwen2.5-Coder, the adjacent tokens ``'.'`` and ``'#'`` get merged into

a single ``'.#'`` token after detokenization. Reconstructing a prefill

prefix via text therefore produces a *different* token sequence than the

decode path used.

"""

tok = qwen_coder_tokenizer

prompt = "Yesterday I went to the store and bought a new toy."

continuation = "#1."

prompt_ids = _encode(tok, prompt)

continuation_ids = _encode(tok, continuation)

original_ids = prompt_ids + continuation_ids

text = tok.decode(original_ids)

re_ids = _encode(tok, text)

# The round trip must change the token sequence on this input; otherwise

# the regression scenario this test is guarding against would not exist.

assert original_ids != re_ids, (

"Expected `encode(decode(ids)) != ids` for this BPE tokenizer/input. "

f"original={original_ids}, round_trip={re_ids}"

)

def test_token_id_prefix_is_preserved_without_round_trip(qwen_coder_tokenizer):

"""Building a prefix directly from token ids preserves the sequence.

This mirrors the construction used by

``test_decode_logprobs_match_prefill_logprobs``:

``prefix_token_ids = prompt_token_ids + decode_tokens[:i]``.

"""

tok = qwen_coder_tokenizer

prompt = "Yesterday I went to the store and bought a new toy."

continuation = "#1."

prompt_ids = _encode(tok, prompt)

decode_tokens = _encode(tok, continuation)

for i in range(len(decode_tokens) + 1):

prefix_token_ids = prompt_ids + decode_tokens[:i]

# The first ``len(prompt_ids)`` ids are exactly the original prompt.

assert prefix_token_ids[: len(prompt_ids)] == prompt_ids

# The remaining ids are the first ``i`` decode tokens, unchanged.

assert prefix_token_ids[len(prompt_ids) :] == decode_tokens[:i]

mergify · 2026-05-21T18:54:10Z

Hi @Evangade, the pre-commit checks have failed. Please run:

uv pip install pre-commit>=4.5.1
pre-commit install
pre-commit run --all-files

Then, commit the changes and push to your branch.

For future commits, pre-commit will run automatically on changed files before each commit.

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github-actions · 2026-08-21T02:40:07Z

This pull request has been automatically marked as stale because it has not had any activity within 90 days. It will be automatically closed if no further activity occurs within 30 days. Leave a comment if you feel this pull request should remain open. Thank you!

@xRay2016

…nsistency test `test_decode_logprobs_match_prefill_logprobs` previously rebuilt the prefill prefix by running an extra `llm.generate(max_tokens=token_idx)` to detokenize the partial output and then submitting `prompt + partial_text` as a string prompt. vLLM re-encodes that string with the model's tokenizer, which is not lossless for many BPE tokenizers — for example Qwen2.5-Coder merges `'.' + '#'` into `'.#'` after detokenization. This silently changed the token-level prefix the test was supposed to verify, producing sporadic false mismatches on certain models/inputs. Build the prefix directly from token ids using `decode_output.prompt_token_ids` plus `decode_token_ids[:i]` and pass it to `llm.generate` as `{"prompt_token_ids": ...}`. This guarantees the prefill request sees the exact same token prefix as the decode path. As a side effect it also avoids the previous O(N^2) extra `llm.generate` call per decoded token. Carried from vllm-project#43317 into vllm-project#53692 at the maintainer's request; the standalone tokenizer regression test from vllm-project#43317 is dropped per review. Concrete instance that motivated carrying it: `zai-org/glm-4-9b-chat` generates `'.' + 'Here'` as `[13, 8419]`, which re-encodes to the single token `89329` (`'.Here'`), making the text-based prefix diverge from position 11 onward. Reported by @xRay2016 in vllm-project#27433 Co-authored-by: CodeBuddy <noreply@codebuddy.dev> Signed-off-by: Yifan Da <1363818765@qq.com> Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01GRuZZBfpWK2Gxo6d9PTPYw Signed-off-by: LioEinaudi <zhao3024667639@gmail.com>

Evangade requested a review from yewentao256 as a code owner May 21, 2026 12:47

mergify Bot added v1 bug Something isn't working labels May 21, 2026

gemini-code-assist Bot reviewed May 21, 2026

View reviewed changes

yewentao256 reviewed May 21, 2026

View reviewed changes

yewentao256 added the ready ONLY add when PR is ready to merge/full CI is needed label May 21, 2026

github-actions Bot added the stale Over 90 days of inactivity label Aug 21, 2026

machero mentioned this pull request Aug 22, 2026

[Test] Fix _random_prompt length handling and exercise chunked prefill #53386

Closed

LioEinaudi mentioned this pull request Sep 1, 2026

[CI][Docs] Fix decode/prefill consistency test prefix construction; add GLM-4-9B and Phi-4 to batch-invariant tested models #53692

Open

This was referenced Sep 1, 2026

gdn: make batch-invariant decode path CUDA-graph-capturable yuvalluria/vllm#1

Open

[Feature] Add batch invariance support to GDN_ATTN backend #45819

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[CI][Bugfix] Use token-id prefix in batch-invariant decode/prefill consistency test - #43317

[CI][Bugfix] Use token-id prefix in batch-invariant decode/prefill consistency test#43317
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Evangade:fix/batch-invariance-prefill-test-prefix-token-ids

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Evangade commented May 21, 2026

Summary

Fix

Why this is not a duplicate

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