### What this PR does / why we need it?
Fix the error that reports while initializing qwen3-reranker-0.6b model
with `--enable-lora`.
And add a testcase to verify the fix.
- vLLM version: v0.17.0
- vLLM main:
4034c3d32e
---------
Signed-off-by: paulyu12 <507435917@qq.com>
Co-authored-by: Mengqing Cao <cmq0113@163.com>
### What this PR does / why we need it?
To support prefix cache for Qwen3.5/Next in vLLM-Ascend, this PR mainly
follows the design in
[#30877](https://github.com/vllm-project/vllm/pull/30877) and inherits
changes to functions which are overridden in vLLM-Ascend.
Note:
1. `--mamba-cache-mode align` && PD disaggregation is still not
supported yet in vLLM v0.17.0(see
https://github.com/vllm-project/vllm/blob/main/vllm/v1/core/sched/scheduler.py#L295).
2. The current implementation of hybrid kv cache might result in a very
large block_size when scheduling. For example, if we run Qwen3.5-35B-A3B
with `-tp 2`, the block_size is adjusted to 2048, which means that any
prefix shorter than 2048 will never be cached. Although this behavior is
consistent with vLLM, it still needs improvements in the future.
3. `--mamba-cache-mode align` requires to copy mamba states during
forward steps. vLLM uses a triton kernel to implement it. However, the
original version run into some bugs on Ascend hardwares. Thus we patch a
new triton kernel to avoid this bug.
### Does this PR introduce _any_ user-facing change?
To use mamba prefix cache, set `--enable-prefix-caching` and
`--mamba-cache-mode align`. Note that the mamba state copy function(see
[do_mamba_copy_block](https://github.com/vllm-project/vllm/blob/main/vllm/v1/worker/mamba_utils.py#L132))
does not provide a torch native version, thus it might have trouble if
users can't use triton.
- vLLM version: v0.16.0
- vLLM main:
4034c3d32e
---------
Signed-off-by: Angazenn <supperccell@163.com>
### What this PR does / why we need it?
Reapply the auto-detect quantization format feature (originally in
#6645, reverted in #6873) and extend it to support remote model
identifiers (e.g., `org/model-name`).
Changes:
- Reapply auto-detection of quantization method from model files
(`quant_model_description.json` for ModelSlim, `config.json` for
compressed-tensors)
- Add `get_model_file()` utility to handle file retrieval from both
local paths and remote repos (HuggingFace Hub / ModelScope)
- Update `detect_quantization_method()` to accept remote repo IDs with
optional `revision` parameter
- Update `maybe_update_config()` to work with remote model identifiers
- Add platform-level `auto_detect_quantization` support
- Add unit tests and e2e tests for both local and remote model ID
scenarios
Closes#6836
### Does this PR introduce _any_ user-facing change?
Yes. When `--quantization` is not explicitly specified, vllm-ascend will
now automatically detect the quantization format from the model files
for both local directories and remote model IDs.
- vLLM version: v0.16.0
- vLLM main:
4034c3d32e
---------
Signed-off-by: SlightwindSec <slightwindsec@gmail.com>
### What this PR does / why we need it?
Drop 0.16.0 support in main
- Fix eagle proposer break introduced by
https://github.com/vllm-project/vllm/pull/34552. Mainly change to use
the draft attention group to initialize the attention metadata builder.
- Fix the `ModelRunner` has no attribute `cudagraph_capture_sizes`
error, which is a bug in vLLM v0.17.0, and fixed by a later pr
https://github.com/vllm-project/vllm/pull/30515
- vLLM version: v0.16.0
- vLLM main:
4034c3d32e
---------
Signed-off-by: MengqingCao <cmq0113@163.com>
### What this PR does / why we need it?
This PR supports W8A8C8 in dsv3.2/glm5 with lightning_indexer_quant ops
in pd-mix stage mainly.
Because the code for the current PD-disaggregated scenario is still
under refactoring and cleanup, this PR prioritizes ensuring the C8
functionality in the pd-mix scenario.
The next steps are planned in two parts:
① Once the optimized scatter operator is updated, we will replace the
original operator to improve the performance of storing k_scale.
② Once the code logic for the PD-disaggregated scenario becomes stable,
we will carry out more comprehensive validation and make appropriate
adaptations.
③ Because enabling C8 currently introduces several new operators whose
performance still needs improvement, performance may regress in some
scenarios. Therefore, only after all the operators are fully ready can
we ensure that this feature does not cause any performance degradation.
At that point, we will enable this feature by default and remove the
switch in `additional_config`.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
CI passed with new added/existing test.
- vLLM version: v0.16.0
- vLLM main:
4034c3d32e
---------
Signed-off-by: rjg-lyh <1318825571@qq.com>
### What this PR does / why we need it?
This PR aims to support aclgraph for model runner v2, please see RFC
#5208. The PR contains these modifications:
- adapt to newest commit of vllm main branch.
- supply a unified interface of extra forward context for both model
runner v1 and model runner v2.
- implement graph mode for main model.
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
- vLLM version: v0.16.0
- vLLM main:
4034c3d32e
---------
Signed-off-by: Ronald1995 <ronaldautomobile@163.com>
### What this PR does / why we need it?
1. For all parts of the current test module involving the millisecond
download model, add the `local_file_only` parameter to specify offline
mode; this ensures that CI will not fail due to network instability.
2. Install modelscope from a fixed commit until it next release
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
check if the env or arg `local_files_only` works
1) set the env:
```shell
export HF_HUB_OFFLINE=1
```
2) run the script
```python
from transformers import PretrainedConfig
import huggingface_hub
from modelscope.utils.hf_util import patch_hub
patch_hub()
model="Qwen/Qwen3-0.6B"
kwargs = {}
config_dict, _ = PretrainedConfig.get_config_dict(
model,
trust_remote_code=True,
local_files_only=huggingface_hub.constants.HF_HUB_OFFLINE,
**kwargs,
)
print(config_dict)
```
it works well:
```shell
2026-03-06 06:40:12,546 - modelscope - WARNING - We can not confirm the cached file is for revision: master
The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored.
{'architectures': ['Qwen3ForCausalLM'], 'attention_bias': False, 'attention_dropout': 0.0, 'bos_token_id': 151643, 'eos_token_id': 151645, 'head_dim': 128, 'hidden_act': 'silu', 'hidden_size': 1024, 'initializer_range': 0.02, 'intermediate_size': 3072, 'max_position_embeddings': 40960, 'max_window_layers': 28, 'model_type': 'qwen3', 'num_attention_heads': 16, 'num_hidden_layers': 28, 'num_key_value_heads': 8, 'rms_norm_eps': 1e-06, 'rope_scaling': None, 'rope_theta': 1000000, 'sliding_window': None, 'tie_word_embeddings': True, 'torch_dtype': 'bfloat16', 'transformers_version': '4.51.0', 'use_cache': True, 'use_sliding_window': False, 'vocab_size': 151936, '_commit_hash': None}
```
3) test the model repo does not cached locally when the env
`HF_HUB_OFFLINE`==True
```python
from transformers import PretrainedConfig
import huggingface_hub
from modelscope.utils.hf_util import patch_hub
patch_hub()
model="FireRedTeam/FireRed-OCR"
kwargs = {}
config_dict, _ = PretrainedConfig.get_config_dict(
model,
trust_remote_code=True,
local_files_only=huggingface_hub.constants.HF_HUB_OFFLINE,
**kwargs,
)
print(config_dict)
```
and the result is as expected:
```shell
File "/workspace/demo.py", line 12, in <module>
config_dict, _ = PretrainedConfig.get_config_dict(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/python3.11.14/lib/python3.11/site-packages/modelscope/utils/hf_util/patcher.py", line 189, in patch_get_config_dict
model_dir = get_model_dir(pretrained_model_name_or_path,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/python3.11.14/lib/python3.11/site-packages/modelscope/utils/hf_util/patcher.py", line 164, in get_model_dir
model_dir = snapshot_download(
^^^^^^^^^^^^^^^^^^
File "/usr/local/python3.11.14/lib/python3.11/site-packages/modelscope/hub/snapshot_download.py", line 137, in snapshot_download
return _snapshot_download(
^^^^^^^^^^^^^^^^^^^
File "/usr/local/python3.11.14/lib/python3.11/site-packages/modelscope/hub/snapshot_download.py", line 283, in _snapshot_download
raise ValueError(
ValueError: Cannot find the requested files in the cached path and outgoing traffic has been disabled. To enable look-ups and downloads online, set 'local_files_only' to False
```
- vLLM version: v0.16.0
- vLLM main:
15d76f74e2
---------
Signed-off-by: wangli <wangli858794774@gmail.com>
### What this PR does / why we need it?
The merged graph of draft in `FULL` mode is broken now.
This pr solves it.
Also, `actual_seq_lengths_q` in `model_runner` is found redundant, so,
it is removed.
It depends on https://github.com/vllm-project/vllm-ascend/pull/7144 and
https://github.com/vllm-project/vllm-ascend/pull/7148.
### Does this PR introduce _any_ user-facing change?
N/A
### How was this patch tested?
Test code is shown as below:
```python
prompts = [
"1.Who are you?",
"2. Who are you?",
]
sampling_params = SamplingParams(temperature=0.0, top_p=0.95, top_k=40, max_tokens=200)
llm = LLM(
model="/home/some-model/Meta-Llama-3.1-8B-Instruct",
tensor_parallel_size=1,
max_num_seqs=32,
# enforce_eager=True,
disable_log_stats=False,
distributed_executor_backend="mp",
gpu_memory_utilization=0.7,
async_scheduling=True,
speculative_config={
"enforce_eager": True,
"model": "/home/some-model/EAGLE3-LLaMA3.1-Instruct-8B",
"disable_padded_drafter_batch": False,
"method": "eagle3",
"num_speculative_tokens": 3,
},
compilation_config={
"cudagraph_mode": "FULL",
"cudagraph_num_of_warmups": 1,
},
max_model_len=4096,
enable_prefix_caching=False,
)
outputs = llm.generate(prompts, sampling_params)
```
The result before:
```text
File "/vllm-workspace/vllm-ascend/vllm_ascend/attention/attention_v1.py", line 575, in full_graph_fia
graph_params.events[num_tokens].append(event)
~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^
KeyError: 132
```
The result after:
```text
--------------------------------------------------
total_num_output_tokens: 400
num_drafts: 242
num_draft_tokens: 726
num_accepted_tokens: 156
mean acceptance length: 1.64
--------------------------------------------------
acceptance at token 0: 0.42
acceptance at token 1: 0.16
acceptance at token 2: 0.07
```
We also test `FULL_DECODE_ONLY` mode.
The result is:
```text
--------------------------------------------------
total_num_output_tokens: 400
num_drafts: 244
num_draft_tokens: 732
num_accepted_tokens: 155
mean acceptance length: 1.64
--------------------------------------------------
acceptance at token 0: 0.42
acceptance at token 1: 0.16
acceptance at token 2: 0.06
```
- vLLM version: v0.16.0
- vLLM main:
4034c3d32e
Signed-off-by: drslark <slarksblood@qq.com>
### What this PR does / why we need it?
This patch fix the nightly failure
1. Each case uses a copy of the global kwargs instead of a reference to
prevent parameter pollution between use cases.
2. Add weight initialization in the scenario of `eplb` + `w8a8_dynamic`
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
```python
pytest -sv tests/e2e/nightly/single_node/ops/multicard_ops_a3/test_dispatch_gmm_combine_decode.py
```
```shell
===================================================================== 3 passed, 4 warnings in 194.86s (0:03:14) ======================================================================
```
- vLLM version: v0.16.0
- vLLM main:
4034c3d32e
Signed-off-by: wangli <wangli858794774@gmail.com>
### What this PR does / why we need it?
related to vllm PR #34043 this pr delete func
‘relax_for_mixed_batch_cudagraphs’, num_reqs no longer equals the actual
number of requests, due to fia operator requires that
query_start_loc[-1] equals the total number of computed tokens, so this
func delete cause the ifa error.
In full graph mode, set num_reqs_paded = num_reqs to fix the error
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.16.0
- vLLM main:
4034c3d32e
---------
Signed-off-by: wangxiaoxin-sherie <wangxiaoxin7@huawei.com>
Co-authored-by: wangxiaoxin-sherie <wangxiaoxin7@huawei.com>
### What this PR does / why we need it?
fix penality ops for new version, and achieved a 10% performance
improvement
### How was this patch tested?
pytest
tests/e2e/nightly/single_node/ops/singlecard_ops/triton/test_penality.py
- vLLM version: v0.16.0
- vLLM main:
15d76f74e2
Signed-off-by: shiyuan680 <917935075@qq.com>
### What this PR does / why we need it?
Fix the issue #6143 .
### Does this PR introduce _any_ user-facing change?
Allow to start the server with "--enable-lora && --fully-sharded-loras
&& --tensor_parallel_size 2".
### How was this patch tested?
pytest -sv tests/e2e/multicard/2-cards/test_llama32_lora_tp2.py
- vLLM version: v0.15.0
- vLLM main:
d7e17aaacd
---------
Signed-off-by: paulyu12 <507435917@qq.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
1. Increase nightly multi-node test max-parallel from 1 to 2, and fix
resource conflicts that arise when tests run concurrently.
2. Fix parse-trigger job: Add an if condition so it only runs on
schedule, workflow_dispatch, or PRs labeled nightly-test
3. Adjust nightly schedule: Shift trigger time from 24:00 to 23:45
(UTC+8)
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.16.0
- vLLM main:
4034c3d32e
---------
Signed-off-by: hfadzxy <starmoon_zhang@163.com>
### What this PR does / why we need it?
New Quantization Method: Introduced support for the W8A8SC static linear
quantization scheme specifically for 310P hardware, enabling more
efficient model compression.
Refactored the save_sharded_state_310.py to avoid multi-process issue.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
W8A8SC quant E2E test.
- vLLM version: v0.16.0
- vLLM main:
4034c3d32e
---------
Signed-off-by: pu-zhe <zpuaa@outlook.com>
### What this PR does / why we need it?
Fix the LoRA e2e test accuracy issue that introduced by the upstream PR
https://github.com/vllm-project/vllm/pull/32005
### How was this patch tested?
pytest -sv tests/e2e/singlecard/test_llama32_lora.py
- vLLM version: v0.16.0
- vLLM main:
15d76f74e2
---------
Signed-off-by: paulyu12 <507435917@qq.com>
Signed-off-by: yupeng <507435917@qq.com>
### What this PR does / why we need it?
fix skiped test_aclgraph_capture_replay.py when upgrade vllm version
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.15.0
- vLLM main:
13397841ab
Signed-off-by: Meihan-chen <jcccx.cmh@gmail.com>
### What this PR does / why we need it?
Previously implemention of triton rope_siso missing the storage of
second half of rope results, which will result in:
1. accuracy problem in neox-style scenario
2. ub overflow in non neox-style scenario
This PR fixes it and supplement nightly test case for it.
- vLLM version: v0.16.0
- vLLM main:
4034c3d32e
Signed-off-by: whx-sjtu <2952154980@qq.com>
### What this PR does / why we need it?
Support chunked prefill for Qwen3Next with PCP&DCP
- vLLM version: v0.16.0
- vLLM main:
15d76f74e2
---------
Signed-off-by: QiuChunshuo <qiuchunshuo@huawei.com>
### What this PR does / why we need it?
Change recurrent_gated_delta_rule ops from triton to ascend C version
for better performance.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
- vLLM version: v0.15.0
- vLLM main:
9562912cea
---------
Signed-off-by: SunnyLee219 <3294305115@qq.com>
### What this PR does / why we need it?
This pull request addresses a bug related to the fused mc2 functionality
within the EPLB (Expert Parallelism Load Balancing) system, specifically
impacting quantization and MoE communication.
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.15.0
- vLLM main:
83b47f67b1
Signed-off-by: Spicy-Stick <873805887@qq.com>
Signed-off-by: root <root@localhost.localdomain>
### What this PR does / why we need it?
Support FlashComm1 for Qwen3-Next. Fix some padding problems in Sequence
Parallel (SP)
and resolve precision problems in shared_out when both FlashComm1 is
enabled.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
CI
- vLLM version: v0.15.0
- vLLM main:
83b47f67b1
---------
Signed-off-by: zhaojiangjiang <zhaojiangjiang1@h-partners.com>
Co-authored-by: zhaojiangjiang <zhaojiangjiang1@h-partners.com>
### What this PR does / why we need it?
**NOTE: This PR is re-pull of #7016 since ci mistakenly marked
unfinished pr as having passed.**
This PR aims to delete mtp_proposer. By fixing a bug in both dsv32 and
glm5, now it should be ok to remove mtp_proposer. The bug is actually
about unnecessary slicing of `slot_mapping`.
### Does this PR introduce _any_ user-facing change?
N/A
### How was this patch tested?
by ci
- vLLM version: v0.16.0
- vLLM main:
4034c3d32e
---------
Signed-off-by: Zetong Li <slippersss@126.com>
### What this PR does / why we need it?
This PR adds split_qkv_rmsnorm_mrope kernel with interleaved for qwen3.5
and qwen3-vl to improve performance.
### Does this PR introduce _any_ user-facing change?
Does not.
### How to use?
```python
real_q, real_k, real_v, real_gate = torch.ops.vllm.triton_split_qkv_rmsnorm_mrope(
qkv=qkv,
q_weight=q_weight,
k_weight=k_weight,
cos_sin=cos_sin,
num_q_heads=num_q_heads,
num_kv_heads=num_kv_heads,
head_size=head_size,
eps=eps,
mrope_section=mrope_section,
is_interleaved=is_interleaved,
rope_dim=rope_dim,
has_gate=has_gate,
)
```
### How was this patch tested?
- vLLM version: v0.16.0
- Accuracy test script：
```shell
pytest tests/e2e/nightly/single_node/ops/singlecard_ops/triton/test_split_qkv_rmsnorm_mrope.py
```
---------
Signed-off-by: Fager <865071616@qq.com>
Signed-off-by: Fager10086 <77871921+Fager10086@users.noreply.github.com>
Signed-off-by: fager <865071616@qq.com>
### What this PR does / why we need it?
Adapt the graph mode (piecewise and full_decode_only) of PCP and DCP for
DeepSeek v3.2.
### How was this patch tested?
Test output:
{"object":"text_completion","model":"deepeek_v3","choices":[{"index":0,"text":"
the head of state and head of government of the United States,
indirectly elected to a four-year term by the American people through
the Electoral College. The officeholder leads the executive branch of
the federal government and is the commander-in-chief of the United
States","logprobs":null,"finish_reason":"length","stop_reason":null,"token_ids":null,"prompt_logprobs":null,"prompt_token_ids":null},{"index":1,"text":"
Paris. This is the largest city in France and its main political,
cultural and commercial center. The modern location of the city is the
north of the central part of the country, on the banks of the Seine
River Seine River Seine in
3\n\n","logprobs":null,"finish_reason":"length","stop_reason":null,"token_ids":null,"prompt_logprobs":null,"prompt_token_ids":null},{"index":2,"text":"
now\n\n# AI future is now\n\nThe world is changing at a rapid pace, and
artificial intelligence (AI) is at the forefront of this transformation.
From self-driving cars to virtual assistants, AI is already making a
significant impact on our daily
lives","logprobs":null,"finish_reason":"length","stop_reason":null,"token_ids":null,"prompt_logprobs":null,"prompt_token_ids":null},{"index":3,"text":"
a 3rd year student at the University of Lincoln studying Media
Production. This blog is about my work throughout my final year on the
course.\n\n## Tuesday 3 May 2016\n### Final Major Project -
Evaluation\n\nFor my final project
I","logprobs":null,"finish_reason":"length","stop_reason":null,"token_ids":null,"prompt_logprobs":null,"prompt_token_ids":null}],"service_tier":null,"system_fingerprint":null,"usage":{"prompt_tokens":27,"total_tokens":227,"completion_tokens":200,"prompt_tokens_details":null},"kv_transfer_params":null}
- vLLM version: v0.16.0
- vLLM main:
15d76f74e2
---------
Signed-off-by: xiaocongtou6 <2066962956@qq.com>
Signed-off-by: xiaocongtou6 <105542647+xiaocongtou6@users.noreply.github.com>
### What this PR does / why we need it?
Add e2e test cases for the Qwen-VL model adaptation to Ascend 310p
- vLLM version: v0.16.0
- vLLM main:
15d76f74e2
Signed-off-by: gcw_61wqY8cy <wanghengkang1@huawei.com>
### What this PR does / why we need it?
This PR optimizes the `split_qkv_rmsnorm_rope` operator by introducing a
new Triton kernel, `split_qkv_rmsnorm_rope_prefill_kernel`, for the
prefill stage (i.e., large batch sizes). The implementation now
dynamically selects between the existing decode kernel and the new
prefill kernel based on the batch size, which improves performance for
large batch scenarios.
Additionally, the RoPE implementation is updated to support partial
rotation dimensions (`rope_dim`), making the operator more flexible.
### Does this PR introduce _any_ user-facing change?
No. This is a performance optimization and is not expected to introduce
any user-facing changes.
### How was this patch tested?
CI should pass with existing tests. The new prefill path is triggered
when the batch size is larger than the number of available vector cores.
The partial RoPE feature can be tested by passing the `rope_dim`
argument.
- vLLM version: v0.15.0
- vLLM main:
83b47f67b1
---------
Signed-off-by: guzhiyong <guzhiyong5@h-partners.com>
Signed-off-by: frank <2547457096@qq.com>
Co-authored-by: guzhiyong <guzhiyong5@h-partners.com>
### What this PR does / why we need it?
This PR aims to delete mtp_proposer. By fixing a bug in both dsv32 and
glm5, now it should be ok to remove mtp_proposer. The bug is actually
about unnecessary slicing of `slot_mapping`.
### Does this PR introduce _any_ user-facing change?
N/A
### How was this patch tested?
by ci
- vLLM version: v0.16.0
- vLLM main:
15d76f74e2
---------
Signed-off-by: Zetong Li <slippersss@126.com>
## Problem
When MTP is enabled, prefill requests with `prompt_tokens ==
num_spec_tokens + 1` are incorrectly classified as decode requests,
causing accuracy issues.
## Root Cause
The `uniform_decode` condition only checked:
- `max_num_scheduled_tokens == uniform_decode_query_len`
- `num_tokens == max_num_scheduled_tokens * num_reqs`
This is insufficient because a prefill request with specific prompt
length satisfies these conditions as well.
## Fix
Add `is_all_decode` check to ensure all requests have
`num_computed_tokens > 0` before classifying as uniform decode, since
decode requests must have computed at least one token.
- vLLM version: v0.15.0
- vLLM main:
83b47f67b1
---------
Signed-off-by: SlightwindSec <slightwindsec@gmail.com>
### What this PR does / why we need it?
This PR refactors the nightly CI workflows (A2 and A3) to support
running tests against a specific PR's code, in addition to the existing
scheduled/dispatch runs using pre-built images.
#### Motivation:
Previously, nightly tests could only be triggered by schedule or
workflow_dispatch, always using the pre-built nightly image. This change
allows developers to trigger nightly tests against their own PR's source
code, enabling early validation without waiting for a nightly build.
#### Changes
Trigger logic (parse-trigger job)
A new parse-trigger job is introduced in both
schedule_nightly_test_a2.yaml and schedule_nightly_test_a3.yaml to
centralize trigger evaluation:
`schedule / workflow_dispatch`: runs all tests with the pre-built image
(existing behavior preserved)
`pull_request (labeled + synchronize)`: runs only when:The PR has the
nightly-test label, and /nightly [test-names] comment exists (latest one
wins)
1. /nightly or /nightly all — runs all tests
2. /nightly test1 test2 — runs only named tests (comma-wrapped for exact
matching)
#### How to trigger
1. Add the nightly-test label to your PR
2. Comment /nightly (all tests) or /nightly test1 test2 (specific tests)
4. Re-triggering: add another /nightly comment and push a new commit
(synchronize event)
### Does this PR introduce _any_ user-facing change?
None
### How was this patch tested?
- vLLM version: v0.14.1
- vLLM main:
dc917cceb8
---------
Signed-off-by: hfadzxy <starmoon_zhang@163.com>
### What this PR does / why we need it?
fix test_qwen3_moe_external_launcher_ep_tp2 by
wait_until_npu_memory_free
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.16.0
- vLLM main:
15d76f74e2
Signed-off-by: hfadzxy <starmoon_zhang@163.com>
## What this PR does / why we need it?
Implements [RFC
#6954](https://github.com/vllm-project/vllm-ascend/issues/6954):
NPUWorker Profiler profile_prefix full adaptation for API parity with
upstream vLLM.
### Changes
- **Lazy profiler init**: Defer profiler creation until first
`profile(is_start=True)` call
- **profile_prefix param**: Add `profile_prefix` to `profile()`; compute
`trace_name` from prefix + `get_worker_rank_suffix()`
- **Refactor `_init_profiler` → `_create_profiler(trace_name)`**: Pass
`worker_name` to `tensorboard_trace_handler` for unique trace files per
worker
- Unique trace files per worker; no collision in multi-worker setups
### Testing
- Unit tests updated/added in `tests/ut/worker/test_worker_v1.py`
- `pytest tests/ut/worker/test_worker_v1.py::TestNPUWorker` passed
## Does this PR introduce _any_ user-facing change?
Yes. Trace file naming may differ (more descriptive with worker rank
suffix). `profile(is_start=True, profile_prefix="warmup")` now
supported.
## How was this patch tested?
- Unit tests:`pytest tests/ut/worker/test_worker_v1.py::TestNPUWorker`
- Manual: vLLM serve with profiler config, start/stop profile, verified
trace files
- vLLM version: v0.16.0
- vLLM main:
15d76f74e2
---------
Signed-off-by: realliujiaxu <realliujiaxu@163.com>
This pull request refactors the speculative decoding proposer interface
to align with upstream vLLM, removing the local `Proposer` interface and
renaming methods to `propose`.
This is the first step. In the future we should remove the class
register and just add few Ascend specified method once the arch in vLLM
is ready.
- vLLM version: v0.16.0
- vLLM main:
15d76f74e2
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
This PR add docs of batch invariance and make some extra operators
according to validation result.
please see https://github.com/vllm-project/vllm-ascend/issues/5487 to
track progress.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
- vLLM version: v0.16.0
- vLLM main:
15d76f74e2
---------
Signed-off-by: Ronald1995 <ronaldautomobile@163.com>
### What this PR does / why we need it?
Add DeepSeek-V3.2 nightly ci
Fix PD routing to exclude headless nodes when collecting
prefiller/decoder IPs
- vLLM version: v0.14.1
- vLLM main:
dc917cceb8
Signed-off-by: hfadzxy <starmoon_zhang@163.com>
### What this PR does / why we need it?
This PR introduces global CPU slicing for Ascend NPUs to ensure
non-overlapping CPU partitions, addresses IRQ binding logical errors on
A3, and enhances the logic for determining total NPUs in CPU allocation.
These changes are necessary to optimize CPU resource management and
improve system stability.
- **Global CPU Slicing**: Introduced a global CPU slicing mechanism for
Ascend NPUs to ensure non-overlapping CPU partitions across multiple
processes or data parallel groups, preventing resource contention.
- **Improved IRQ Binding for A3 Devices**: Refined the IRQ binding logic
specifically for Ascend A3 devices, correctly mapping logical NPU IDs to
physical card and chip IDs for accurate npu-smi queries and preventing
multi-process overwrite of IRQ settings.
- **Enhanced NPU Count Determination**: Improved the logic for
determining the total number of logical NPUs, prioritizing NPU mapping
information to ensure more accurate CPU allocation.
- **Minimum CPU Requirement**: Established a minimum requirement of 5
CPUs per NPU for binding, reserving specific cores for IRQ, main, ACL,
and release operations to ensure stable operation.
### Does this PR introduce _any_ user-facing change?
No user-facing changes are introduced.
### How was this patch tested?
CI passed with new added/existing tests.
- vLLM version: v0.16.0
- vLLM main:
15d76f74e2
---------
Signed-off-by: c00818886 <chenchuwei@huawei.com>
### What this PR does / why we need it?
- This PR fixes an issue with weight format conversion for unquantized
models running on Ascend 310P devices.
- The changes refactor the logic for converting weights to the
FRACTAL_NZ format. Previously, this was handled in a 310P-specific
linear layer implementation (`AscendUnquantizedLinearMethod310`). This
implementation has been removed, and the logic is now centralized in the
`maybe_trans_nz` utility function. This function now checks if the
device is a 310P and applies the NZ format cast accordingly for
`float16`/`bfloat16` weights.
- This refactoring simplifies the code by removing platform-specific
duplication and ensures correct weight handling for unquantized models
on 310P.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
ut and local test
- vLLM version: v0.15.0
- vLLM main:
83b47f67b1
---------
Signed-off-by: Tflowers-0129 <2906339855@qq.com>
### What this PR does / why we need it?
[CI] Upgrade CANN to 8.5.1
### Does this PR introduce _any_ user-facing change?
N/A
### How was this patch tested?
CI passed with existing test.
- vLLM version: v0.16.0
- vLLM main:
15d76f74e2
Signed-off-by: wxsIcey <1790571317@qq.com>
### What this PR does / why we need it?
This pull request introduces significant enhancements for 310P device
support, primarily by enabling W8A8S quantization and facilitating the
saving of models with W8A8SC state outputs. It provides an example
script for saving sharded and compressed model states, implements the
core W8A8S quantization method, and integrates metadata generation
within the 310P worker to accurately describe the quantization types of
saved parameters. These changes aim to improve efficiency and
compatibility for quantized models on 310P hardware.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
W8A8S accuarcy test and W8A8SC states save.
<img width="886" height="184" alt="image"
src="https://github.com/user-attachments/assets/e9bcac54-1f69-4d3a-a5b8-221a147ef99d"
/>
- vLLM version: v0.16.0
- vLLM main:
15d76f74e2
---------
Signed-off-by: pu-zhe <zpuaa@outlook.com>
### What this PR does / why we need it?
Add muls_add triton kernel with related fusion pass. What's more, this
PR refactors `AscendCompilationConfig` and delete `NpugraphExConfig`.
### Does this PR introduce _any_ user-facing change?
None
### How was this patch tested?
CI passed with new added test.
- vLLM version: v0.13.0
- vLLM main:
45c1ca1ca1
---------
Signed-off-by: whx-sjtu <2952154980@qq.com>
### What this PR does / why we need it?
Support platform.get_device_uuid function.
currently, the pytorch.npu.get_device_properties return uuid as full
zero, vllm-ascend implement the interface at first, once the
pytorch.npu.get_device_properties return the real uuid, vllm-ascend will
support without modification.
more details see
https://github.com/vllm-project/vllm-ascend/issues/6669
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
- vLLM version: v0.15.0
- vLLM main:
9562912cea
root@localhost:/workspace/l00614971/vllm_test# python vllm_test.py
INFO 02-24 09:43:48 [__init__.py:43] Available plugins for group
vllm.platform_plugins:
INFO 02-24 09:43:48 [__init__.py:45] - ascend -> vllm_ascend:register
INFO 02-24 09:43:48 [__init__.py:48] All plugins in this group will be
loaded. Set `VLLM_PLUGINS` to control which plugins to load.
INFO 02-24 09:43:48 [__init__.py:217] Platform plugin ascend is
activated
device_uuid = 00000000-0000-0000-0000-000000000000
---------
Signed-off-by: liziyu <liziyu16@huawei.com>
Signed-off-by: wangxiaoteng <wangxiaoteng@huawei.com>
Signed-off-by: luomin2005 <luomin2005@huawei.com>
Co-authored-by: liziyu <56102866+liziyu179@users.noreply.github.com>
Co-authored-by: wangxiaoteng <wangxiaoteng@huawei.com>
