[Bugfix] Fix computed-token metadata for requests split across DBO microbatches

[forest-david]

[Bugfix] Fix computed-token metadata for requests split across DBO microbatches

Purpose

When DBO splits a prefill request across microbatches, _make_metadata_with_slice() adjusts the continuation slice's query_start_loc, but it only slices the cached _num_computed_tokens_cpu by request. It does not account for query tokens from the same request that were placed in an earlier microbatch.

For example, consider a request with 24 computed tokens and 8 scheduled query tokens, split after the first 4 query tokens:

Metadata	First slice	Continuation slice
seq_lens	28	32
Query length in this slice	4	4
Expected computed tokens	24	28
Cached value before this fix	24	24
Cached value after this fix	24	28

For the continuation slice, the expected value is seq_lens - query_len = 32 - 4 = 28. However, the cached value previously remained 24. When _num_computed_tokens_cpu is populated, the num_computed_tokens_cpu property returns that cache directly instead of recomputing it from the sliced metadata.

This PR updates the continuation slice when a request is split internally:

1. Clone the sliced cache tensor so the parent metadata and sibling slices are not mutated.
2. Add the number of query tokens from the same request that were assigned to the preceding microbatch.

Splits at request boundaries and the path where the CPU cache is absent retain their existing behavior. This is an internal metadata-consistency fix and does not change the public API or attention kernels.

Although this cached field is deprecated, it is still constructed, propagated, and exposed in the current code path. While it remains present, each sliced value should preserve the semantics of the corresponding slice.

I searched the open pull requests for num_computed_tokens_cpu with microbatch/DBO terms and did not find an open PR implementing this correction.

Test plan

Extended the existing parameterized test_prefill_split_across_ubatches test in tests/v1/attention/test_attention_splitting.py. The assertions cover:

• an internal split of the first request;
• an internal split of a later request;
• the first slice retaining its original computed-token count;
• the continuation slice including query tokens from the preceding slice; and
• the parent metadata cache remaining unchanged.

Focused test command:

pytest -q tests/v1/attention/test_attention_splitting.py \
  -k prefill_split_across_ubatches

Test results

Validated on NVIDIA H100 80GB with vLLM 0.25.1, PyTorch 2.11.0+cu130:

Unpatched code with the new assertions: 2 failed, 20 deselected
Patched code with the new assertions:   2 passed, 20 deselected
Patched full test file:                 22 passed

The unpatched failures reported actual=32, expected=36 and actual=24, expected=28. Both failures exercise the continuation-slice computed-token assertion. Community CI should validate the latest-main test matrix.

[claude]

Claude Code Review

This pull request is from a fork — automated review is disabled. A repository maintainer can comment @claude review to run a one-time review.

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[forest-david]

A concrete consumer exists in the DeepSeek-V4 C128 compressor introduced by #48957. Its metadata builder reads _num_computed_tokens_cpu to determine whether a microbatch crosses a 128-token compression boundary. For a fresh 160-token request split into 80 + 80 tokens, the continuation slice incorrectly reports 0 computed tokens instead of 80. Calling the actual metadata-splitting and boundary-checking functions produces False before this patch and True after it for the continuation slice. On the applicable CUDA, non-FULL-CUDA-graph path, this predicate controls whether the compressed-KV write is skipped.

[forest-david]

Additional reproduction: DeepSeek-V4 C128 boundary detection

A concrete consumer of this metadata is DeepSeek-V4’s _get_c128_boundary. For a new request with 160 scheduled tokens split into two 80-token microbatches, the second microbatch starts at token 80 and crosses the first 128-token compression boundary. Before this patch, its _num_computed_tokens_cpu incorrectly remains 0, causing the boundary check to return False. After the patch, it correctly becomes 80, and the check returns True.

The following reproducer uses the actual metadata-splitting and boundary-checking functions. Run it from the repository root in a compatible vLLM development environment whose source includes _get_c128_boundary:

import numpy as np
import torch
import vllm.v1.worker.ubatch_utils as ubatch_utils

from tests.v1.attention.utils import BatchSpec, create_common_attn_metadata

from vllm.models.deepseek_v4.compressor import _get_c128_boundary
common = create_common_attn_metadata(

BatchSpec(seq_lens=[160], query_lens=[160]),

block_size=8,

device=torch.device("cpu"),

)
slices, _ = ubatch_utils.maybe_create_ubatch_slices(

should_ubatch=True,

num_scheduled_tokens=np.array([160], dtype=np.int32),

num_tokens_padded=160,

num_reqs_padded=1,

num_ubatches=2,

)

assert slices is not None and len(slices) == 2
parts = ubatch_utils.split_attn_metadata(slices, common)

computed = [part._num_computed_tokens_cpu.tolist() for part in parts]

boundaries = [_get_c128_boundary(part) for part in parts]
print("Imported source:", ubatch_utils.file)

print("Computed tokens:", computed)

print("C128 boundaries:", boundaries)

print("Parent computed tokens:", common._num_computed_tokens_cpu.tolist())
assert all(

part.query_start_loc_cpu.tolist() == [0, 80]

for part in parts

)

assert common._num_computed_tokens_cpu.tolist() == [0]

assert computed == [[0], [80]]

assert boundaries == [False, True]

The core A/B results previously observed for this scenario were:

Result	Before patch	After patch
Computed tokens	[[0], [0]]	[[0], [80]]
C128 boundaries	[False, False]	[False, True]
Parent computed tokens	[0]	[0]

The existing regression tests can also be run with:

python -m pytest tests/v1/attention/test_attention_splitting.py \
  -k test_prefill_split_across_ubatches -v

[mergify]

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

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

[forest-david]

fixed by #55353 ;close it