[Zx55]

Why

Multimodal vision and audio encoders across the Qwen VLM/Omni model families (qwen2_vl, qwen2_5vl, qwen3_vl, qwen3_vl_moe, qwen3_5, qwen3_5_moe, qwen4_exp, qwen2_5_omni, qwen3_omni_moe) branched on is_flash_attention_requested(self.config) inside each model's attention forward:

• The FlashAttention branch passed cu_seq_lens_q=cu_seqlens, cu_seq_lens_k=cu_seqlens, max_length_q=max_seqlen, max_length_k=max_seqlen directly to self.veomni_attn(...).
• The non-FlashAttention branch (sdpa, veomni_sdpa, eager, flex_attention, veomni_sage_attention) manually split (query_states, key_states, value_states) along the sequence dimension in model code using torch.split(..., lengths.tolist(), dim=2) and invoked self.veomni_attn(...) in a Python loop over chunks.

Splitting along the sequence dimension in model code before calling self.veomni_attn(...) breaks Ulysses sequence parallelism (veomni_sdpa, veomni_sage_attention) whenever multiple variable-length vision/audio windows are packed into a single sequence, because prepare_ulysses_qkv (sequence all-to-all gather) must run on the full sequence shard before per-segment splitting, and restore_ulysses_output must run on the concatenated output after per-segment attention. It also duplicated chunk-splitting boilerplate across 9 model families.

What does this PR do?

• Move packed/varlen cu_seqlens splitting into the veomni.ops attention wrapper:
  • Add extract_packed_varlen_cu_seqlens and packed_split_attention_forward in veomni/ops/kernels/attention/helper.py.
  • When cu_seq_lens_q / cu_seq_lens_k are provided (with batch size 1 and without an already-isolating 3D/4D attention_mask or BlockMask), non-varlen attention wrappers (veomni_sdpa, veomni_sage_attention, and raw sdpa, eager, flex_attention in lookup()) strip the varlen kwargs and split Q/K/V per segment around the inner kernel call.
  • In sdpa_attention_forward (veomni_sdpa) and sage_attention_forward (veomni_sage_attention), per-segment splitting runs after prepare_ulysses_qkv and before restore_ulysses_output, preserving Ulysses SP semantics on packed multi-segment sequences.
• Unify multimodal vision and audio attention forward methods:
  • Simplify Qwen2_5OmniVisionAttention, Qwen2_5OmniAudioAttention, Qwen3OmniMoeVisionAttention, Qwen3OmniMoeAudioAttention, Qwen2VLVisionAttention, Qwen2_5_VLVisionAttention, Qwen3VLVisionAttention (shared by qwen3_vl_moe), and Qwen3_5VisionAttention (shared by qwen3_5_moe and qwen4_exp) to call self.veomni_attn(...) once with cu_seq_lens_q=cu_seqlens, cu_seq_lens_k=cu_seqlens, max_length_q=max_seqlen, max_length_k=max_seqlen.
  • Remove dead Qwen2_5OmniAudioEncoder._prepare_attention_mask override, unused VARLEN_ATTENTION_TYPES in veomni/models/utils/attention_utils.py, and the obsolete ("patched_modeling_qwen3_5_gpu.py", "Qwen3_5VisionAttention.forward") entry in tests/models/transformers/test_model_forward_no_implicit_sync.py.
• Harden Ulysses SP enforcement on attention implementations:
  • Add veomni_sdpa and veomni_sage_attention to _VEOMNI_SP_ATTN in veomni/models/auto.py.
  • Reject raw non-SP attention implementations (eager, sdpa, flex_attention, flash_attention_2, flash_attention_3, flash_attention_4) in lookup(impl) when Ulysses SP is active unless skip_ulysses=True is explicitly passed (or via DeepSeek-V4's dsa_position_ids bridge).

Checklist Before Starting

• Search for relative PRs/issues and link here: follow-up to [BREAKING][ops, model] refactor: replace OpSlot with VeomniOp #1142 (VeomniOp refactor).
• PR title follows [{modules}] {type}: {description} format (enforced by check_pr_title.yml)

Test

Extended existing CI-enumerated unit tests under tests/ops/ and tests/models/ (both directories are collected wholesale by gpu_unit_tests.yml and npu_unit_tests.yml):

• tests/ops/attention/test_sdpa_attention.py: packed varlen cu_seqlens forward/backward parity against manual chunk splitting across veomni_sdpa, sdpa, eager, and flex_attention; asymmetric cu_seq_lens_q / cu_seq_lens_k; BlockMask passthrough without false splitting; invalid metadata rejection (batch > 1, mismatched sequence total, out-of-order cu_seqlens).
• tests/ops/attention/test_sage_attention.py: packed varlen cu_seqlens splitting and Ulysses SP flow in veomni_sage_attention, while keeping indices / s_aux rejected.
• tests/ops/attention/test_attention_op.py: active Ulysses SP rejection for raw non-SP attention implementations (eager, sdpa, flex_attention, flash_attention_2/3/4) and opt-out with skip_ulysses=True.
• tests/models/transformers/qwen/test_qwen2_5_omni.py & tests/models/transformers/qwen/test_qwen3_omni_moe.py: vision and audio attention forward/backward numerical parity against upstream HF reference across veomni_sdpa, sdpa, eager, flex_attention, and veomni_sage_attention.
• tests/models/transformers/test_model_forward_no_implicit_sync.py: removed obsolete Qwen3_5VisionAttention.forward sync allowance on qwen3_5_vl-sdpa.
• Local verification:
  • pytest -q tests/ops/attention/ tests/models/transformers/qwen/test_qwen2_5_omni.py tests/models/transformers/qwen/test_qwen3_omni_moe.py tests/models/test_qwen3_5_shared_prefix.py: passed.
  • make check-patchgen (all 31 patchgen configs OK) and make commit: passed.

API and Usage Example

Vision and audio encoders with packed variable-length sequences now call self.veomni_attn(...) through a single code path across all attention backends (veomni_flash_attention_*, veomni_sdpa, veomni_sage_attention, sdpa, eager, flex_attention):

max_seqlen = kwargs.pop("vision_max_seqlen", None)
if max_seqlen is None:
    max_seqlen = (cu_seqlens[1:] - cu_seqlens[:-1]).max()

attn_output, _ = self.veomni_attn(
    self,
    query_states,
    key_states,
    value_states,
    attention_mask=None,
    scaling=self.scaling,
    dropout=0.0 if not self.training else self.attention_dropout,
    cu_seq_lens_q=cu_seqlens,
    cu_seq_lens_k=cu_seqlens,
    max_length_q=max_seqlen,
    max_length_k=max_seqlen,
    is_causal=False,
    **kwargs,
)

For encoders that intentionally do not participate in Ulysses sequence parallelism (e.g., audio towers with skip_ulysses=True), skip_ulysses=True continues to bypass Ulysses gather/scatter in veomni_* adapters and permits raw attention backends when Ulysses SP is enabled globally.

Design & Code Changes

• veomni/ops/kernels/attention/helper.py: added extract_packed_varlen_cu_seqlens and packed_split_attention_forward.
• veomni/ops/kernels/attention/standard/sdpa.py: integrated packed varlen splitting between prepare_ulysses_qkv and restore_ulysses_output in sdpa_attention_forward.
• veomni/ops/kernels/attention/standard/sage.py: integrated packed varlen splitting between prepare_ulysses_qkv and restore_ulysses_output in sage_attention_forward, narrowing unsupported metadata to ("indices", "s_aux").
• veomni/ops/kernels/attention/__init__.py: wired packed varlen splitting for raw sdpa, eager, and flex_attention in lookup(), and added active-Ulysses guard for _RAW_NON_SP_IMPLS.
• veomni/models/auto.py: added veomni_sdpa and veomni_sage_attention to _VEOMNI_SP_ATTN.
• veomni/models/transformers/{qwen2_5_omni,qwen3_omni_moe,qwen2_vl,qwen2_5vl,qwen3_vl,qwen3_5,qwen4_exp}/ and generated/: simplified vision/audio attention overrides and regenerated GPU/NPU patched modeling files and diffs.
• docs/transformers_v5/veomni_attention_interface.md, docs/transformers_v5/upgrade_5_9_to_5_16.md, veomni/ops/README.md: updated attention contract documentation.

Checklist Before Submitting

• Read the Contribute Guide
• Applied pre-commit checks
• Added/updated documentation
• If tasks/ training scripts were moved or renamed: updated docs/ examples and verified python3 scripts/ci/check_doc_task_paths.py passes (also enforced by the Check doc task paths CI workflow)
• Tests: extended an existing CI-enumerated test, or added a new test and wired it into gpu_unit_tests.yml (and npu_unit_tests.yml where applicable), or explained in Test why none is needed.

Summary by CodeRabbit

• New Features

  • Improved packed-sequence attention for supported vision and audio models.
  • Single-batch, multi-segment inputs are processed independently and recombined across SDPA, eager, VeOmni SDPA, and SageAttention.
  • Expanded support for sequence-parallel attention workflows.

• Bug Fixes

  • Improved output consistency between VeOmni and Hugging Face attention implementations.
  • Added validation for unsupported masks, batch sizes, sequence metadata, and parallel configurations.

• Documentation

  • Updated migration and attention guidance for packed sequences, masks, and sequence-length metadata.

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📒 Files selected for processing: 3

• tests/distributed/test_torch_compile.py
• tests/ops/attention/test_fa4_sm90_compat.py
• veomni/models/transformers/qwen4_exp/qwen4_exp_gpu_patch_gen_config.py

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📝 Walkthrough

Attention wrappers now validate and split supported packed multi-segment inputs. Qwen vision and audio patches route packed attention through local VeOmni operations. Tests and documentation cover routing, isolation, distributed execution, and validation.

Changes: Packed Attention

Layer / File(s)	Summary
Packed metadata validation and splitting veomni/ops/kernels/attention/helper.py	Helpers detect isolating masks, extract and validate packed sequence lengths, split tensors by segment, and concatenate outputs.
Attention dispatch and backend integration veomni/ops/kernels/attention/__init__.py, veomni/ops/kernels/attention/standard/*, tests/ops/attention/*, veomni/ops/README.md	Raw dispatch, SDPA, and SageAttention support packed splitting under defined batch, mask, and metadata conditions. Tests cover Ulysses handling, gradients, isolation, and invalid metadata.
Model attention routing and parity veomni/models/transformers/*, veomni/models/auto.py, veomni/models/utils/attention_utils.py, tests/models/transformers/qwen/*	Qwen vision and audio patches pass packed sequence metadata to local VeOmni attention operations. Tests compare outputs with Hugging Face implementations and verify segment isolation.
Documentation and integration validation docs/transformers_v5/*, tests/models/transformers/test_model_forward_no_implicit_sync.py, tests/distributed/test_torch_compile.py, tests/ops/attention/test_fa4_sm90_compat.py	Documentation, sync allowlists, compile fixtures, and FA4 guards reflect the updated attention paths.

Priority: ➖ Normal

Estimated code review effort: 4 (Complex) | ~60 minutes

Change: Refactor

Sequence Diagram(s)

sequenceDiagram
  participant QwenVisionAttention
  participant veomni_attn
  participant Ulysses
  participant AttentionWrapper
  participant PackedSplit
  participant AttentionBackend
  QwenVisionAttention->>veomni_attn: Pass packed Q/K/V and sequence lengths
  veomni_attn->>Ulysses: Gather Q/K/V when sequence parallelism is active
  Ulysses->>AttentionWrapper: Pass gathered tensors and packed metadata
  AttentionWrapper->>PackedSplit: Pass validated segment boundaries
  loop Each sequence segment
    PackedSplit->>AttentionBackend: Run attention for segment Q/K/V
  end
  PackedSplit->>Ulysses: Return concatenated output for restoration

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Suggested reviewers: coach257

Merge Risk: 🔵 Low · up to def5f

The standard test workflow is unaffected, but running these compile tests under an initialized multi-rank process group fails before compilation. This is a bounded risk rather than a merge blocker.

Security architecture risk: 🔵 Low · up to def5f

The change centralizes a data-isolation responsibility used by several callers. Inspected safeguards remain in place, but coverage of all input paths and deployment exposure is incomplete.

Retained concerns
No architecture-level concerns identified.

Security review details

Trust Boundaries and Controls

• observed — For the supported split path, query, key, and value chunks are paired by segment and passed separately to the attention callable. The routed public-entrypoint evidence identifies test setup and capability guards; it does not establish new attacker-facing production ingress.

Resilience and Maintainability Implications

• inferred — The split helper validates segment lengths before invoking segment attention and returns a concatenated result only after all segment calls complete. A raised segment call therefore does not return a partial packed output through this helper. Distributed interruption and recovery behavior were not exercised.

Hardening Proposals

• proposed — Bind the sparse-metadata exemption to an explicitly verified sparse execution capability, rather than relying solely on the presence of dsa_position_ids. This would make segment-isolation ownership clearer when metadata passes through shared dense wrappers; it is a hardening proposal, not a verified externally reachable vulnerability.

Pre-merge checks: 4 · 1

Failed checks: 1 warning

Check name	Status	Explanation	Resolution
Docstring Coverage		Docstring coverage is 32.69% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 52 functions across 21 files.	Write docstrings for the functions missing them to satisfy the coverage threshold.

Passed checks: 4 passed

Check name	Status	Explanation
Description Check		Check skipped - CodeRabbit’s high-level summary is enabled.
Title check		The title clearly and concisely describes the main change: adding packed variable-length cu_seqlens splitting to the attention wrapper across operations and models.
Linked Issues check		Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check		Check skipped because no linked issues were found for this pull request.

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Inline comments:
Review comments at @docs/transformers_v5/upgrade_5_9_to_5_16.md:
- Around line 95-97: Update the migration note’s backend list to include raw
flex_attention and veomni_sage_attention alongside sdpa, veomni_sdpa, and eager;
state that these backends split unmasked batch-size-1 multi-segment cu_seqlens
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📒 Files selected for processing: 23

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• docs/transformers_v5/veomni_attention_interface.md
• tests/models/transformers/qwen/test_qwen2_5_omni.py
• tests/models/transformers/qwen/test_qwen3_omni_moe.py
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• tests/ops/attention/test_sdpa_attention.py
• veomni/models/auto.py
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• veomni/models/transformers/qwen2_5vl/qwen2_5_vl_gpu_patch_gen_config.py
• veomni/models/transformers/qwen2_vl/qwen2_vl_gpu_patch_gen_config.py
• veomni/models/transformers/qwen3_5/qwen3_5_gpu_patch_gen_config.py
• veomni/models/transformers/qwen3_5/qwen3_5_npu_patch_gen_config.py
• veomni/models/transformers/qwen3_omni_moe/qwen3_omni_moe_gpu_patch_gen_config.py
• veomni/models/transformers/qwen3_vl/qwen3_vl_gpu_patch_gen_config.py
• veomni/models/transformers/qwen4_exp/qwen4_exp_gpu_patch_gen_config.py
• veomni/models/utils/attention_utils.py
• veomni/ops/README.md
• veomni/ops/kernels/attention/__init__.py
• veomni/ops/kernels/attention/helper.py
• veomni/ops/kernels/attention/standard/sage.py
• veomni/ops/kernels/attention/standard/sdpa.py

💤 Files with no reviewable changes: 2

• veomni/models/transformers/qwen4_exp/qwen4_exp_gpu_patch_gen_config.py
• veomni/models/utils/attention_utils.py

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Review comments at @tests/distributed/test_torch_compile.py:
- Line 258: Update the tests around use_parallel_state(ParallelState()) so they
remain single-process under the existing plain pytest command, or construct
ParallelState with sizes matching the active distributed world size before
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• tests/distributed/test_torch_compile.py

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• 🪄 Fix comments: Fix CodeRabbit comments on this PR

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Review comments at
@veomni/models/transformers/qwen4_exp/qwen4_exp_gpu_patch_gen_config.py:
- Line 1768: Restore the is_flash_attention_requested import from
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⛔ Files ignored due to path filters: 30

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📒 Files selected for processing: 9

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🚧 Files skipped from review as they are similar to previous changes: 2

• docs/transformers_v5/upgrade_5_9_to_5_16.md
• docs/transformers_v5/veomni_attention_interface.md

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