### What this PR does / why we need it?
Fix configuration errors in our documentation.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
NA.
Signed-off-by: linfeng-yuan <1102311262@qq.com>
### What this PR does / why we need it?
Qwen2.5-VL mrope precision problem would been solved once this pr is
merged
### Does this PR introduce _any_ user-facing change? No
### How was this patch tested?
Test on G8600 with textVQA dataset
- vLLM version: v0.11.2
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.2
---------
Signed-off-by: hfadzxy <starmoon_zhang@163.com>
Co-authored-by: shaopeng-666 <lishaopeng21@huawei.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
In cann8.3， npu_moe_gating_top_k operator can support expert nums with
384, so kimi can use the operator to get better preformance.
---------
Signed-off-by: Levi-JQ <yujinqi2@huawei.com>
Co-authored-by: Levi-JQ <yujinqi2@huawei.com>
When retrieving the quantization method for MOE (e.g., the quantization
file of DeepSeek v3.2 exp do not match the model's naming convention in
eager mode), a KeyError is raised: "model.layers.3.mlp.experts.weight
not in self.quant_description". However the quantization file is like :
```bash
"model.layers.3.mlp.experts.255.gate_proj.weight": "W8A8_DYNAMIC",
"model.layers.3.mlp.experts.255.gate_proj.weight_scale": "W8A8_DYNAMIC",
"model.layers.3.mlp.experts.255.gate_proj.weight_offset": "W8A8_DYNAMIC",
"model.layers.3.mlp.experts.255.down_proj.weight": "W8A8_DYNAMIC",
"model.layers.3.mlp.experts.255.down_proj.weight_scale": "W8A8_DYNAMIC",
"model.layers.3.mlp.experts.255.down_proj.weight_offset": "W8A8_DYNAMIC",
"model.layers.3.mlp.experts.255.up_proj.weight": "W8A8_DYNAMIC",
"model.layers.3.mlp.experts.255.up_proj.weight_scale": "W8A8_DYNAMIC",
"model.layers.3.mlp.experts.255.up_proj.weight_offset": "W8A8_DYNAMIC",
```
Co-Authored-By: yangqinghao-cmss <yangqinghao_yewu@cmss.chinamobile.com>
Signed-off-by: hfadzxy <starmoon_zhang@163.com>
Co-authored-by: yangqinghao-cmss <yangqinghao_yewu@cmss.chinamobile.com>
### What this PR does / why we need it?
Earlier we fixed a similar issue for qwen2.5-vl 【
https://github.com/vllm-project/vllm-ascend/issues/4430 】, and then the
multimodal models in vllm v0.11.0 should all have this problem. Here, we
have specifically proposed a fix for qwen3-vl-moe.
---------
Signed-off-by: Levi-JQ <yujinqi2@huawei.com>
Co-authored-by: Levi-JQ <yujinqi2@huawei.com>
### What this PR does / why we need it?
Add a custom op to acclerater the deepseek model. The fusion ops combine
the bmm and transpose together, which is applied to mla module.
Cherry-pick from this commtid c68ddc11ce53334fc9a17bad58342148cbf14e86
### Does this PR introduce _any_ user-facing change?
No
---------
Signed-off-by: hust17yixuan <303660421@qq.com>
### What this PR does / why we need it?
#3985 move stream context initialization before for-loops to improve
performance. However, we find that this might cause potential accuracy
drop when used with pd disaggregation. Thus we partly revert this change
when using pd disaggregation, and we shall fix this bug in th future.
### Does this PR introduce _any_ user-facing change?
No.
---------
Signed-off-by: Angazenn <supperccell@163.com>
### What this PR does / why we need it?
Fix eplb enable when using mtp float weights. It will be remove when
eplb supporting mtp and float weights.
### How was this patch tested?
Deepseek-V3 + MTP + EPLB in A3.
---------
Signed-off-by: offline0806 <3337230449@qq.com>
Signed-off-by: offline893 <158537145+offline893@users.noreply.github.com>
Co-authored-by: offline0806 <3337230449@qq.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
### What this PR does / why we need it?
This pr is cherry-pick from :
https://github.com/vllm-project/vllm-ascend/pull/2958 and
https://github.com/vllm-project/vllm-ascend/pull/4340
Past：
npu_moe_gating_top_k can only support 'group_count=256' pattern
Now：
1、npu_moe_gating_top_k support all size of group_count
2、the functionality of `torch_npu.npu_moe_gating_top_k_softmax` are
included in `torch_npu.npu_moe_gating_top_k`
CANN: depends on 8.3.RC1
Performance：
1. GLM4.5-w8a8, TPS improve 6%
2. Qwen3, the same as before
---------
Signed-off-by: 1092626063 <1092626063@qq.com>
### What this PR does / why we need it?
Redundant experts bugfix
The calculation logic for redundant experts has been fixed, allowing the
correct number of redundant experts to be calculated using the map.
Therefore, there is no longer a need to set the redundant expert
parameter when passing the map.
### Does this PR introduce _any_ user-facing change?
After configuring the path for experts_map, users do not need to
configure iinit_redundancy_expert.
### How was this patch tested?
The accuracy of EPLB was tested with and without the use of redundant
experts.
---------
Signed-off-by: shenchuxiaofugui <1311027364@qq.com>
### What this PR does / why we need it?
Fix ngram lacking of input arg `dummy_compute_logits` error
### How was this patch tested?
CI passed with existing test.
---------
Signed-off-by: MengqingCao <cmq0113@163.com>
### What this PR does / why we need it?
Resolve the interface compatibility issue of get_input_embeddings in MM，
because the get_input_embeddings func of other model does not have the
is_multimodal parameter
---------
Signed-off-by: Levi-JQ <yujinqi2@huawei.com>
Co-authored-by: Levi-JQ <yujinqi2@huawei.com>
### What this PR does / why we need it?
This PR aims to remove env introduced by #3988 and use lock by default.
As described in https://github.com/vllm-project/vllm/issues/27858, we
have tested the writer lock method in various scenarios and the
performance is almost unaffected. Therefore, we believe that it would be
safe to enable the lock by default and remove the redundant env
`SHM_BARRIER` now.
After discussion, we decide to preserve env and set it as true by
default.
### Does this PR introduce _any_ user-facing change?
`SHM_BARRIER` is set as true by default.
### How was this patch tested?
by ci
---------
Signed-off-by: Zetong Li <slippersss@126.com>
### What this PR does / why we need it?
Previously, the dummy run executed compute_logits only once, regardless
of num_speculative_tokens. This caused execute_model to hang on
compute_logits when lm head tensor parallelism exceeded 1. The fix
ensures compute_logits executes correctly during dummy run, matching
num_speculative_tokens.
Signed-off-by: zouyida2052 <zouyida2002@gmail.com>
### What this PR does / why we need it?
The expert mapping table and weights of the dynamic EPLB were not
updated, causing the accuracy to be correct but not effective. This bug
has now been fixed.
If it was tested in a way different from regular unit tests, please
clarify how you tested step by step, ideally copy and paste-able, so
that other reviewers can test and check, and descendants can verify in
the future.
Signed-off-by: shenchuxiaofugui <1311027364@qq.com>
<!-- Thanks for sending a pull request!
BEFORE SUBMITTING, PLEASE READ
https://docs.vllm.ai/en/latest/contributing/overview.html
-->
### What this PR does / why we need it?
disable NZ for float weight case. This is only a quick fix for dev
branch.
For main branch, we'll consider more case to make it more common.
### Does this PR introduce _any_ user-facing change?
<!--
Note that it means *any* user-facing change including all aspects such
as API, interface or other behavior changes.
Documentation-only updates are not considered user-facing changes.
-->
### How was this patch tested?
qwen2.5 32B
<img width="441" height="221" alt="image"
src="https://github.com/user-attachments/assets/7ae18ffd-1ce2-43d9-9960-be45250ad0da"
/>
---------
Signed-off-by: 刘哲续 <liuzhexu1@huawei.com>
Co-authored-by: 刘哲续 <liuzhexu1@huawei.com>
### What this PR does / why we need it?
To fix ops test, where `model_config` has been set to `None` and doesn't
has `hf_config` attribute, we have added a check for `model_config` to
guarantee it is not `None_Type`.
cherry-pick from main:
https://github.com/vllm-project/vllm-ascend/pull/4384.
Signed-off-by: shen-shanshan <467638484@qq.com>
### What this PR does / why we need it?
When cudagraph_mode is set to FULL_DECODE_ONLY, if dp > 1, the dummy-run
process will be triggered. When calling the update_attn_params function,
the num_tokens parameter needs to be passed, and this value is obtained
through positions.shape[0]. However, the multimodal model uses mRope
(multi-dimensional rotary positional embeddings), which causes the shape
of positions to be 2. As a result, the value obtained from
positions.shape[0] is incorrect. We solve this problem by replacing
positions.shape[0] with num_tokens.
### Does this PR introduce _any_ user-facing change?
NO
### How was this patch tested?
vLLM version: v0.11.0rc3
vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0
---------
Signed-off-by: wujinyuan1 <wjy9595@qq.com>
Co-authored-by: wujinyuan1 <wjy9595@qq.com>
### What this PR does / why we need it?
Enable force_load_balance in aclgraph, solving OOM issues.
pick from https://github.com/vllm-project/vllm-ascend/pull/4366
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
e2e & ut
Signed-off-by: Pr0Wh1teGivee <calvin_zhu0210@outlook.com>
### What this PR does / why we need it?
add single node PD disaggregation instructions for Qwen 2.5VL model.
### Does this PR introduce _any_ user-facing change?
no
---------
Signed-off-by: mazhixin <mazhixin7@huawei.com>
Signed-off-by: mazhixin000 <mazhixinkorea@163.com>
Co-authored-by: mazhixin <mazhixin7@huawei.com>
### What this PR does / why we need it?
Eplb Verify Fix
---------
Signed-off-by: shenchuxiaofugui <1311027364@qq.com>
Signed-off-by: LI SHENGYONG <49200266+shenchuxiaofugui@users.noreply.github.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
### What this PR does / why we need it?
For better usability, add multimodal audio to vllm compiling in
dockerfile defaultly.
Image size will increase only 2.xM.
Signed-off-by: Ting FU <futing10@huawei.com>
### What this PR does / why we need it?
Remove redundant workflows， just maintain a separate workflow which
setting up on the main branch to control the execution of each branch,
instead of running each branch simultaneously, thus reducing resource
waste.
Signed-off-by: wangli <wangli858794774@gmail.com>
### What this PR does / why we need it?
Add error log for VL models when enabling
`VLLM_ASCEND_ENABLE_FLASHCOMM1=1` or `VLLM_ASCEND_ENABLE_FLASHCOMM=1`
(for backward compatibility).
This is a temporary fix for
https://github.com/vllm-project/vllm-ascend/issues/4132.
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
Signed-off-by: shen-shanshan <467638484@qq.com>
### What this PR does / why we need it?
This dev version of #4199 .
Currently, the default `cudagraph_capture_size` in vLLM is `[1, 2, 4 ,8
,16 ,24 ,... , max_capture_size]`. However, this is not always the best
choice on different situations. This PR aims to change the default
setting when running Qwen3-MoE on full dp (`dp_size > 1` && `tp_size ==
1`) setting, which is usually applied in Large-Scale EP.
old :
`[1, 2, 4 ,8 ,16 ,24 ,... , max_capture_size]`
new:
`[1, 2, 5 ,10 ,15, 16 ,24 ,... , max_capture_size]`
This is mainly because the performance of `_npu_paged_attention` op
degrades dramatically on old settings. We hope to provide better
performance if users do not set specific `cudagraph_capture_size`.
### Does this PR introduce _any_ user-facing change?
The default `cudagraph_capture_size` is modified in above cases.
However, if `cudagraph_capture_size` has already set by users, this PR
won't have any influence on this.
### How was this patch tested?
- vLLM version: v0.11.0
- vLLM main:
2918c1b49c
---------
Signed-off-by: Angazenn <supperccell@163.com>
### What this PR does / why we need it?
avoid mrope fusion op when running qwen25vl on x86 machine
---------
Signed-off-by: 李少鹏 <lishaopeng21@huawei.com>
### What this PR does / why we need it?
pick from : https://github.com/vllm-project/vllm-ascend/pull/2958
Past：
npu_moe_gating_top_k can only support 'group_count=256' pattern
Now：
1、npu_moe_gating_top_k support all size of group_count
2、the functionality of `torch_npu.npu_moe_gating_top_k_softmax` are
included in `torch_npu.npu_moe_gating_top_k`
CANN: depends on 8.3.RC1
Performance：
1. GLM4.5-w8a8, TPS improve 6%
2. Qwen3, the same as before
Signed-off-by: 1092626063 <1092626063@qq.com>
### What this PR does / why we need it?
pd proxy support ipv6, mooncake connector check whether the IPv6 address
is used and notify the user.
---------
Signed-off-by: liziyu <liziyu16@huawei.com>
### What this PR does / why we need it?
Quick fix for missing log2phy conversion in MC2 token_dispatcher, which
has been already fixed in main branch
https://github.com/vllm-project/vllm-ascend/pull/3512.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
e2e & ut
Signed-off-by: Pr0Wh1teGivee <calvin_zhu0210@outlook.com>
<!-- Thanks for sending a pull request!
BEFORE SUBMITTING, PLEASE READ
https://docs.vllm.ai/en/latest/contributing/overview.html
-->
### What this PR does / why we need it?
This is cherry-pick from #4097 .
Currently, we set `seq_lens` in dummy attn_metadata to be
`max_model_len` to get max workspace for attention during capturing.
However, setting it consistently to be `max_model_len` causing dummy_run
to execute a long attention when running actual inference. For example,
if there is a single req with `seqs_lens` as [8] but `max_model_len` is
131072, the whole process will be slow down by dummy_run as it execute a
fake long-seq attention. Therefore, we instead set it to max_query_len,
which is also consistent with vLLM gpu implementation.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
<!--
CI passed with new added/existing test.
If it was tested in a way different from regular unit tests, please
clarify how you tested step by step, ideally copy and paste-able, so
that other reviewers can test and check, and descendants can verify in
the future.
If tests were not added, please describe why they were not added and/or
why it was difficult to add.
-->
---------
Signed-off-by: Angazenn <supperccell@163.com>
### What this PR does / why we need it?
This pr fixes a bug introduced in #3985, which set wrong npu_stream
(possibly by mistakes in cherry-pick). I correct it and make
`update_attn_params` consistent to main branch.
### Does this PR introduce _any_ user-facing change?
No.
Signed-off-by: Angazenn <supperccell@163.com>
### What this PR does / why we need it?
- Fixes Qwen3-Next enable nz accuracy problem
---------
Signed-off-by: wxsIcey <1790571317@qq.com>
Signed-off-by: Icey <1790571317@qq.com>
### What this PR does / why we need it?
Cherry-pick #3967 from main branch. This PR reverts the changes
introduced in PR #2894 Initially, due to performance issues with the
older version of the chunked prefill ops, the default behavior was to
use the Ascend scheduler to disable the chunked prefill feature.
However, with the improvements in the performance of the new chunked
prefill ops, this interception strategy has been removed. This change
also aligns with the community's default configuration behavior.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
CI passed with new added/existing test.
Signed-off-by: rjg-lyh <1318825571@qq.com>
### What this PR does / why we need it?
In the `update_*attn_params` functions, the
`torch.npu.stream(update_stream)` context manager was previously located
inside the for-loop that updates parameters for each layer. This
resulted in redundant stream initiations for every layer, adding
unnecessary overhead.
This commit refactors the code by moving the stream context manager to
wrap the entire for-loop. This ensures that the update stream is
initiated only once per function call, rather than for each layer. This
change reduces 90us in each decode model.
update stream in every layer:
<img width="1720" height="383" alt="image"
src="https://github.com/user-attachments/assets/70e4cb69-5bc1-4180-a67d-c99132134be6"
/>
remove update stream in every layer:
<img width="1269" height="175" alt="image"
src="https://github.com/user-attachments/assets/0e290edb-b0ce-48fe-b032-1b924ade6ae5"
/>
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
Signed-off-by: wangxiaoxin-sherie <wangxiaoxin7@huawei.com>
Co-authored-by: wangxiaoxin-sherie <wangxiaoxin7@huawei.com>
### What this PR does / why we need it?
cherry-pick from https://github.com/vllm-project/vllm-ascend/pull/4022
The code bug caused an empty bubble. When the npu_paged_cache_load
operator was called, it forcibly transferred seq_len2 to the device,
which triggered synchronization and interrupted the CPU operator's
launch stream.
---------
Signed-off-by: underfituu <hzhucong@163.com>
