support qkdim!=vdim

[chang-wenbin]

Motivation

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Modifications

Usage or Command

Accuracy Tests

Checklist

• Add at least a tag in the PR title.
  • Tag list: [[FDConfig],[APIServer],[Engine], [Scheduler], [PD Disaggregation], [Executor], [Graph Optimization], [Speculative Decoding], [RL], [Models], [Quantization], [Loader], [OP], [KVCache], [DataProcessor], [BugFix], [Docs], [CI], [Optimization], [Feature], [Benchmark], [Others], [XPU], [HPU], [GCU], [DCU], [Iluvatar], [Metax]]
  • You can add new tags based on the PR content, but the semantics must be clear.
• Format your code, run pre-commit before commit.
• Add unit tests. Please write the reason in this PR if no unit tests.
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• If the current PR is submitting to the release branch, make sure the PR has been submitted to the develop branch, then cherry-pick it to the release branch with the [Cherry-Pick] PR tag.

[codecov-commenter]

Codecov Report

❌ Patch coverage is 52.77778% with 17 lines in your changes missing coverage. Please review.
⚠️ Please upload report for BASE (develop@edc885d). Learn more about missing BASE report.

Files with missing lines	Patch %	Lines
fastdeploy/model_executor/layers/linear.py	57.69%	10 Missing and 1 partial ⚠️
...l_executor/layers/attention/append_attn_backend.py	50.00%	2 Missing and 2 partials ⚠️
...astdeploy/model_executor/ops/triton_ops/do_rope.py	0.00%	2 Missing ⚠️

Additional details and impacted files

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[PaddlePaddle-bot]

🤖 Paddle-CI-Agent | ci_status_monitor | 2026-06-11 23:16:39 UTC+08:00

CI报告基于以下代码生成（30分钟更新一次）:
PR commit: 94fa1f9 | Merge base: edc885d (branch: develop)

---

1 Required任务 : 8/10 通过

总执行（rerun次数）	总任务	✅ 通过	❌ 失败	⏳ 运行中	⏸️ 等待中	跳过
42(0)	42	37	5	0	0	0

任务	错误类型	置信度	日志
Run FastDeploy Unit Tests and Coverage / run_tests_with_coverage	PR问题	高	Job
Extracted partial CE model tasks to run in CI. / run_ce_cases	未知	低	Job

2 失败详情

🔴 Run FastDeploy Unit Tests and Coverage / run_tests_with_coverage — PR问题（置信度: 高）

分析器: 通用分析(fallback)
失败用例:

用例	错误摘要
layers/test_attention_layer.py::TestAttentionPerformance::test_append_attn_backend_decode_performance_with_prefill	append_attention_gpu 触发 partial_rotary_factor < 1.0 参数约束失败
model_executor/test_paddleformers_base.py::TestPaddleFormersQKVParallelLinearUnit::test_extract_local_shard_with_transpose_and_tp_slice	PaddleFormersQKVParallelLinear 缺少 v_head_dim 属性
model_loader/test_offline_model.py::test_offline_model[offline_quant_Qwen3-30B-A3B-FP8.None.triton]	worker 进程 300s 超时被终止，疑似受同一批 QK/V 维度变更影响

关键日志:

SystemError: (Fatal) partial_rotary_factor < 1.0 only supports use_neox_rotary_style=True, q_norm_weight/k_norm_weight) is None, GQA and is_scale_channel_wise=false.
AttributeError: 'PaddleFormersQKVParallelLinear' object has no attribute 'v_head_dim'
RuntimeError: Worker process hung and was terminated

• 根因摘要: qk/v 维度变更未完整同步
  PR 修改了 fastdeploy/model_executor/layers/attention/append_attn_backend.py、fastdeploy/model_executor/layers/linear.py 和 do_rope.py 以支持 qkdim != vdim，但 attention 路径仍会把 q_norm_weight/k_norm_weight 传给 append attention kernel，触发 partial rotary 场景下的 kernel 参数限制。另一个确定失败来自 PaddleFormersQKVParallelLinear 的测试对象通过 object.__new__ 构造，未设置本 PR 新增的 v_head_dim，而 _get_shard_size_mapping() 已改为读取该属性。

修复建议:

1. 在 fastdeploy/model_executor/layers/attention/append_attn_backend.py 中，当 external_norm_rope=True 且前面已经执行 qk_rmsnorm_fused/do_rope/write_cache 后，避免继续向 append_attention 传入 q_norm_weight/k_norm_weight，确保 partial rotary 的 kernel 参数满足限制。
2. 在 tests/model_executor/test_paddleformers_base.py 的手工构造 layer 中补齐 v_head_dim = head_dim，或在相关 shard size 逻辑中使用 getattr(self, "v_head_dim", self.head_dim) 兜底。
3. 离线模型超时与本 PR 修改的 attention/linear 路径有关联，但还需要补充运行日志确认具体卡点。

关联变更: fastdeploy/model_executor/layers/attention/append_attn_backend.py, fastdeploy/model_executor/layers/linear.py, fastdeploy/model_executor/ops/triton_ops/do_rope.py, tests/model_executor/test_linear.py

🔴 Extracted partial CE model tasks to run in CI. / run_ce_cases — 未知（置信度: 低）

分析省略/待后续深挖。

当前仅掌握该任务以 exit code 123 失败，尚未读取该 job 的详细日志，无法判断是 PR 问题、环境问题还是不稳定问题。

[PaddlePaddle-bot]

🤖 Paddle-CI-Agent | pr_review | 2026-06-11 02:07:41 Asia/Shanghai

📋 Review 摘要

PR 概述：为 attention/QKV 路径补充 qkdim != vdim 支持。
变更范围：AppendAttention backend、QKV/QKVG linear loader、Triton RoPE、线性层单测。
影响面 Tag：[OP] [KVCache] [Loader]

问题

级别	文件	概述
🔴 Bug	fastdeploy/model_executor/layers/attention/append_attn_backend.py:324	v_head_dim != head_dim 会无条件执行 q/k RMSNorm，未启用 qk norm 的模型会把 None 传进 Triton kernel
🟡 建议	tests/model_executor/test_linear.py:291	新增测试仍使用 v_head_dim == head_dim，没有覆盖本 PR 的核心维度不等分支

📝 PR 规范检查

标题缺少官方 Tag，且 PR 描述的 Motivation / Modifications / Usage or Command / Accuracy Tests 仍未填写。

标题建议（可直接复制）：

• [OP] Support qkdim != vdim in attention and QKV loading

PR 描述建议（点击展开，可直接复制）

## Motivation
Support models whose Q/K head dimension differs from V head dimension (`qkdim != vdim`) in FastDeploy attention and QKV projection paths.

## Modifications
- Add `v_head_dim` to attention backend constructors and use it for value cache shape.
- Pass `model_config.v_head_dim` from GPU model runner to the selected attention backend.
- Update QKV/QKVG parallel linear output sizing and V shard placement to use `v_head_dim`.

## Usage or Command
N/A

## Accuracy Tests
N/A. Current PR does not include accuracy or regression test results.

## Checklist

- [x] Add at least a tag in the PR title.
  - Tag list: [`[FDConfig]`,`[APIServer]`,`[Engine]`, `[Scheduler]`, `[PD Disaggregation]`, `[Executor]`, `[Graph Optimization]`, `[Speculative Decoding]`, `[RL]`, `[Models]`, `[Quantization]`, `[Loader]`, `[OP]`, `[KVCache]`, `[DataProcessor]`, `[BugFix]`, `[Docs]`, `[CI]`, `[Optimization]`, `[Feature]`, `[Benchmark]`, `[Others]`, `[XPU]`, `[HPU]`, `[GCU]`, `[DCU]`, `[Iluvatar]`, `[Metax]`]
  - You can add new tags based on the PR content, but the semantics must be clear.
- [ ] Format your code, run `pre-commit` before commit.
- [ ] Add unit tests. Please write the reason in this PR if no unit tests.
- [ ] Provide accuracy results.
- [x] If the current PR is submitting to the `release` branch, make sure the PR has been submitted to the `develop` branch, then cherry-pick it to the `release` branch with the `[Cherry-Pick]` PR tag.

[PaddlePaddle-bot]

这里把 external_norm_rope 只和 v_head_dim != head_dim 绑定后，会对所有 qk/v 维度不同的层执行 qk_rmsnorm_fused。但 Attention 默认 use_qk_norm=False，只有开启时才会创建 q_norm_weight / k_norm_weight；现有多处 Attention(...) 构造没有传 use_qk_norm。这些模型一旦配置 v_head_dim != head_dim，这里会把 None 作为 Triton 指针传入，qk_rmsnorm_fused_kernel 随后 tl.load(q_weight_ptr + ...) 会直接失败。建议把“需要外部 rope/write_cache”和“需要 q/k norm”拆开：只有权重存在或 layer.use_qk_norm 为真时才跑 fused norm；没有 q/k norm 的模型仍应只做 RoPE/write_cache。

[PaddlePaddle-bot]

这个新增用例仍然设置 v_head_dim=2 且 head_dim=2，因此不会覆盖本 PR 最关键的 qkdim != vdim 分支：V shard size、param offset、shared KV slice 等仍按旧路径通过。建议至少加入 v_head_dim != head_dim（例如 head_dim=2, v_head_dim=3）的 fused/split load 断言，验证 V 段和后续 offset/gate 不重叠。