### What this PR does / why we need it?
This PR is to replace addRmsNorm and Add With addRmsNormBias. This way
can lead to a more effecient result.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Full Test Pass
- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef
Signed-off-by: Chen_HaoWen <chenhaowen12@huawei.com>
Co-authored-by: Chen_HaoWen <chenhaowen12@huawei.com>
### What this PR does / why we need it?
This PR enables FLASHCOMM1 communication optimization with layer
sharding for DeepSeek-V3.2 W8A8 model testing to
validate PR #5702. The changes include:
1. Enable FLASHCOMM1: Set VLLM_ASCEND_ENABLE_FLASHCOMM1=1
improves performance for distributed inference
2. Add layer sharding: Configure layer_sharding: ["q_b_proj", "o_proj"]
4. Update baselines: Adjust performance baselines to reflect the
improvements from FLASHCOMM1 and layer sharding
### Does this PR introduce _any_ user-facing change?
No. This is a CI/test-only change that enables new communication
optimization features for testing purposes.
### How was this patch tested?
- vLLM version: v0.13.0
- vLLM main:
d68209402d
Signed-off-by: guozr <guozr1997@hotmail.com>
Co-authored-by: guozr <guozr1997@hotmail.com>
### What this PR does / why we need it?
This PR adds mooncake common method to conftest, we need it to add more
test cases later
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
by running a test
- vLLM version: v0.14.0
- vLLM main:
d68209402d
Signed-off-by: jiangyunfan1 <jiangyunfan1@h-partners.com>
### What this PR does / why we need it?
The test case
`tests/e2e/singlecard/spec_decode/test_v1_spec_decode.py::test_llama_qwen_eagle_acceptance`
fails occasionally, such result seems not stable with method `eagle`,
for example:
[tests/e2e/singlecard/spec_decode/test_v1_spec_decode.py::test_llama_qwen_eagle_acceptance](https://github.com/vllm-project/vllm-ascend/actions/runs/21249578476/job/61147453980?pr=6151)
This PR skips the `eagle` tests to keep CI success
- vLLM version: v0.14.0
- vLLM main:
d68209402d
Signed-off-by: wjunLu <wjunlu217@gmail.com>
### What this PR does / why we need it?
Add nightly ci test for deepseek v3.1
- vLLM version: release/v0.13.0
- vLLM main:
bc0a5a0c08
Signed-off-by: hfadzxy <starmoon_zhang@163.com>
### What this PR does / why we need it?
PCP/DCP splits the kv-cache onto different cards. After introducing the
parameter cp-kv-cache-interleave-size, the first size tokens will be
cached at Card 0, and so on.
However, if there are too few tokens, some cards will not store the
key-value pairs, resulting in values of 0, corrupted values, and
precision issues. Currently, additional operations are introduced to
avoid this precision problem.
After we integrate FIA operator in mla_cp._forward_decode and CANN
updates to 8.5.0, we now can remove these additional operations.
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
passed all CI by CANN 8.5.0
- vLLM version: v0.13.0
- vLLM main:
2c24bc6996
Signed-off-by: dsxsteven <dsxsteven@sina.com>
Signed-off-by: dsxsteven <36877507+dsxsteven@users.noreply.github.com>
### What this PR does / why we need it?
Re-open `tests/e2e/singlecard/test_aclgraph_accuracy.py` and update its
golden results to match PTA 2.9.0
- vLLM version: v0.13.0
- vLLM main:
d68209402d
Signed-off-by: wjunLu <wjunlu217@gmail.com>
### What this PR does / why we need it?
Drop vLLM 0.13.0 support, upgrade to 0.14.0
- vLLM version: v0.13.0
- vLLM main:
d68209402d
---------
Signed-off-by: hfadzxy <starmoon_zhang@163.com>
### What this PR does / why we need it?
Install clang in dokerfile for triton ascend
- vLLM version: v0.13.0
- vLLM main:
d68209402d
Signed-off-by: Meihan-chen <jcccx.cmh@gmail.com>
### What this PR does / why we need it?
Upgrade PTA to 2.9.0
- vLLM version: v0.13.0
- vLLM main:
d68209402d
---------
Signed-off-by: wjunLu <wjunlu217@gmail.com>
### What this PR does / why we need it?
This patch purpose to optimize the lint check term. The main idea is to
reduce unnecessary installation time.
1. The installation of vllm is not must, only append the path of vllm
src to the `PATHONPATH` is effective
2. This installation of `requirements-dev.txt` is not must, we have a
pre-built image `quay.io/ascend-ci/vllm-ascend:lint` with all the
requirements installed in advance.
**NOTE**: the conditions for triggering image builds are: 1).Daily
scheduled build; 2) Build when requirements are modified; 3) Manual
build. This ensures that the dependencies in our image are up-to-date to
the greatest extent possible.
3. The `mypy` was separated from the `pre-commit` hook for performance
reasons; we found that integrating `mypy` into the `pre-commit` hook
resulted in poor performance.
4. Reduce the CPU core consumption from 16 -> 8
### Does this PR introduce _any_ user-facing change?
The end-to-end lint time was optimized from 20min/per PR to 8min/per PR
### How was this patch tested?
- vLLM version: v0.13.0
- vLLM main:
2c24bc6996
---------
Signed-off-by: wangli <wangli858794774@gmail.com>
According to the official documentation, the parameter
"draft_tensor_parallel_size": 1 is supposed to be applied to the Eagle3
model. However, based on actual debugging, it was found that the number
of tensor parallelisms (tp) of the Eagle model is consistent with that
of the target model. The setting of tp for the draft model did not take
effect as expected.
**Note:** This feature has not been superimposed and tested with `sp`
and `dp`. It will be adapted later
No
```python
from vllm import LLM, SamplingParams
def main():
prompts = [
"The future of AI is",
]
sampling_params = SamplingParams(temperature=0.8, top_p=0.95)
llm = LLM(
model="meta-llama/Llama-3.1-8B-Instruct",
tensor_parallel_size=4,
gpu_memory_utilization=0.9,
enforce_eager=True,
speculative_config={
"method": "eagle3",
"model": "yuhuili/EAGLE3-LLaMA3.1-Instruct-8B"
"draft_tensor_parallel_size": 1,
"num_speculative_tokens": 3,
},
)
outputs = llm.generate(prompts, sampling_params)
print(f"Outputs: {outputs}")
for output in outputs:
prompt = output.prompt
generated_text = output.outputs[0].text
print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
```
Fixesvllm-project/vllm#31345
### What this PR does / why we need it?
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.13.0
- vLLM main:
d68209402d
Signed-off-by: zhaomingyu <zhaomingyu13@h-partners.com>
Co-authored-by: drslark <slarksblood@qq.com>
### What this PR does / why we need it?
1) Default enable MLAPO for deepseek MLA Attention W8A8 models on PD
disagregation D Instance, for example: DeepSeekV3-W8A8,
DeepSeek-R1-W8A8.
2) Default enable MLAPO for DeepSeek SFA Attention W8A8 models,
currently is DeepSeek-V3.2-W8A8.
### Does this PR introduce _any_ user-facing change?
Don't need use manully to VLLM_ASCEND_ENABLE_MLAPO=1, to enable MLAPO
feature for deepseek w8a8 model
The effect of enabling MLAPO SFA model deployed on a single A3 Node:
Test
with:tests/e2e/nightly/single_node/models/test_deepseek_v3_2_exp_w8a8.py
dataset: gsm8k-lite，without set MTP, FULL GRAPH, has 19% promote：
未默认开启 MLAPO 时：
├─────────────────────────┤
│ TTFT │ 14055.8836 ms │
├─────────────────────────┤
│ ITL │ 66.8171 ms. │
├─────────────────────────┤
│ Output Token Throughput │ 104.9105 token/s │
├─────────────────────────┤
默认开启 MLAPO 时：
├─────────────────────────┤
│ TTFT │ 3753.1547 ms │
├─────────────────────────┤
│ ITL. │ 61.4236 ms. │
├─────────────────────────┤
│ Output Token Throughput │ 125.2075 token/s│
├─────────────────────────┤
- vLLM version: v0.13.0
- vLLM main:
2c24bc6996
---------
Signed-off-by: leo-pony <nengjunma@outlook.com>
### What this PR does / why we need it?
update triton ascend version in 3.2.0
- vLLM version: v0.13.0
- vLLM main:
d68209402d
Signed-off-by: Meihan-chen <jcccx.cmh@gmail.com>
### What this PR does / why we need it?
In long-sequence scenarios, the chunked-prefill component may encounter
dimension misalignment issues, which previously occurred during
precision testing on the code_generate_lite dataset. This PR removes
redundant computations and instead derives the value using existing
results and straightforward calculations.
- vLLM version: v0.13.0
- vLLM main:
2c24bc6996
Signed-off-by: QiuChunshuo <qiuchunshuo@huawei.com>
### What this PR does / why we need it?
add dispath_ffn_combine_bf16
- vLLM version: v0.13.0
- vLLM main:
bde38c11df
---------
Signed-off-by: guanguan0308 <1546542263@qq.com>
### What this PR does / why we need it?
This is a part of
https://github.com/vllm-project/vllm-ascend/issues/4715#issue-3694310762
1. refactor the npugraph_ex config，modified the default configuration of
the static kernel, new default value of static kernel is false
2. support online-infer with static kernel
3. fixed the issue where manually modifying FX graphs caused an abnormal
model return type, and removed the related redundant code.
### Does this PR introduce _any_ user-facing change?
yes，the new config of npugraph_ex is as follow:
```
additional_config={
"npugraph_ex_config": {
"enable": True,
"enable_static_kernel": False
}
}
```
### How was this patch tested?
```
vllm serve /data/DeepSeek-V3.1-Terminus-w4a8 \
--host 0.0.0.0 \
--port 8004 \
--data-parallel-size 4 \
--tensor-parallel-size 4 \
--quantization ascend \
--seed 1024 \
--served-model-name deepseek_v3 \
--enable-expert-parallel \
--max-num-seqs 48 \
--max-model-len 40000 \
--async-scheduling \
--max-num-batched-tokens 9000 \
--trust-remote-code \
--no-enable-prefix-caching \
--speculative-config '{"num_speculative_tokens": 3, "method":"deepseek_mtp","disable_padded_drafter_batch": false}' \
--gpu-memory-utilization 0.9 \
--compilation-config '{"cudagraph_capture_sizes":[4,32,64,112,160,176,192], "cudagraph_mode": "FULL_DECODE_ONLY"}' \
--additional-config \
'{"enable_shared_expert_dp": true,"multistream_overlap_shared_expert": true,"npugraph_ex_config":{"enable":true}}'
```
- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef
---------
Signed-off-by: chencangtao <chencangtao@huawei.com>
Signed-off-by: ChenCangtao <50493711+ChenCangtao@users.noreply.github.com>
Co-authored-by: chencangtao <chencangtao@huawei.com>
### What this PR does / why we need it?
Wait until the NPU memory is clean
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.13.0
- vLLM main:
2c24bc6996
---------
Signed-off-by: wangli <wangli858794774@gmail.com>
Signed-off-by: leo-pony <nengjunma@outlook.com>
Co-authored-by: leo-pony <nengjunma@outlook.com>
### What this PR does / why we need it?
Add DeepSeek-V3.2-W8A8 nightly ci test：
DeepSeek-V3.2-W8A8 1node DP2+TP8
:tests/e2e/nightly/models/test_deepseek_v3_2_w8a8.py
### Does this PR introduce _any_ user-facing change
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
Signed-off-by: hfadzxy <starmoon_zhang@163.com>
### What this PR does / why we need it?
Optimized operator performance and add ut test
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
test in qwen2.5 7b vl, ops time approved 90%
- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef
this pr is for
# https://github.com/vllm-project/vllm-ascend/issues/5208
Signed-off-by: shiyuan680 <917935075@qq.com>
### What this PR does / why we need it?
Move the qwen3 performance test from nightly to e2e to intercept
performance degradation.
- vLLM version: v0.13.0
- vLLM main:
2c24bc6996
---------
Signed-off-by: wxsIcey <1790571317@qq.com>
### What this PR does / why we need it?
Fixed the issue where the PCP and MTP services could not be started due
to asynchronous scheduling.
After the pcp, mtp, and asynchronous scheduling functions are enabled,
the service is suspended because of a shape mismatch after a curl
request is sent. This PR resolves this issue.
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.13.0
- vLLM main:
2c24bc6996
---------
Signed-off-by: weiguihua2 <weiguihua2@huawei.com>
### What this PR does / why we need it?
#### Documentation Improvements
New Configuration: Added the layer_sharding parameter to the
DeepSeek-V3.2-W8A8 deployment tutorial. This guides users to include
`["q_b_proj", "o_proj"]` in their prefill node setup for better resource
utilization.
#### CI and Testing Updates
Test Config Update: Updated the multi-node E2E test configuration file:
tests/e2e/nightly/multi_node/config/DeepSeek-V3_2-W8A8-A3-dual-nodes.yaml.
including disable `FLASHCOMM` and enable `FULL_DECODE_ONLY` and update
performance baseline.
### Does this PR introduce any user-facing change?
Yes. The documentation now recommends a more optimized startup command
for DeepSeek-V3.2-W8A8. Users following the updated tutorial will see
improved performance in multi-node PD disaggregation environments.
### How was this patch tested?
CI Validation: The updated E2E test configuration has been verified
through the nightly CI pipeline.
Environment: * vLLM version: v0.13.0
Base Commit:
[11b6af5](11b6af5280)
Hardware: Ascend A3/A2 multi-node cluster.
---------
Signed-off-by: guozr <guozr1997@hotmail.com>
Co-authored-by: guozr <guozr1997@hotmail.com>
### What this PR does / why we need it?
[Feature] Adapt DispathGmmCombineDecode opertor to align with weight
scale dtype of small operators.
- **Before**: weight scale must be float32
- **After**: weight scale can be float32/float16 when x is float16,
float32/bfloat16 when x is float32/bfloat16. And w1 scale can use
different dtype with w2 scale.
More info about this operator, please refer to RFC: issue
https://github.com/vllm-project/vllm-ascend/issues/5476
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
#### Perf
> When scale is of type fp16 or bf16, it will be cast to fp32 internally
within the operator, while the subsequent computations remain unchanged.
Therefore, this PR will introduce an additional cast operation but halve
the memory copy operations for scale . Furthermore, since the scale data
is only a few KB in size and participates in relatively few
computations, its impact is almost negligible compared to major
operations like matrix multiplication. Thus, the theoretical performance
change should be minimal.
test single operator cases from qwen3-235b,
- single A3 node(ep16), 64 moe experts, 4 experts / die (like qwen3-235b
ep32)
- batch=18/32, token_hidden_size 4096, moe_intermediate_size 1536
The test was conducted for 100 rounds, and the average of the last 95
rounds was taken.
| | bs18(us)| bs32(us)|
| -----| -----| -----|
|Without this PR|96.28|108.83|
|With this PR|96.06|107.90|
Note: Single-operator benchmarks represent an ideal scenario. They are
usually only useful for referencing relative changes and may not fully
align with performance data observed within the full model.
#### Acc
test qwen3-235b eplb on a single A3 node(ep16),
with dispatch_gmm_combine_decode
| dataset | version | metric | mode | vllm-api-stream-chat |
|----- | ----- | ----- | ----- | -----|
| aime2024 | 604a78 | accuracy | gen | 83.33 |
- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef
Signed-off-by: wangqiankun <wangqiankun13@huawei.com>
### What this PR does / why we need it?
Add basic 310p support. Only dense models work with eager mode now.
- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef
---------
Signed-off-by: Tflowers-0129 <2906339855@qq.com>
Signed-off-by: Shaoxu Cheng <2906339855@qq.com>
### What this PR does / why we need it?
1. Fix DeepSeek-V3.2-W8A8-Pruning mtp
2. Add DeepSeek-V3.2-W8A8-Pruning e2e test
### How was this patch tested?
- vLLM version: v0.13.0
- vLLM main:
11b6af5280
Signed-off-by: hfadzxy <starmoon_zhang@163.com>
### What this PR does / why we need it?
Upgrade vllm commit to releases/v0.14.0
- Re-open cases in `tests/e2e/singlecard/pooling/test_scoring.py`, since
the errors before have been fixed by
https://github.com/vllm-project/vllm/pull/32243
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.13.0
- vLLM main:
11b6af5280
Signed-off-by: wjunLu <wjunlu217@gmail.com>
### What this PR does / why we need it?
Add DeepSeek R1 W8A8 HMB nightly ci
- vLLM version: v0.13.0
- vLLM main:
bde38c11df
Signed-off-by: hfadzxy <starmoon_zhang@163.com>
Skip bad UT test_models_chunked_prefill_with_empty_kvcache temporarily,
which is inadaptable with main2main 20260114.
- vLLM version: v0.13.0
- vLLM main:
11b6af5280
Signed-off-by: QiuChunshuo <qiuchunshuo@huawei.com>
This PR add 310 e2e test back to ensure the related PR will be tested on
310.
1. for light e2e, we'll run 310p test if the changed files are located
in `vllm_ascend/_310p`
2. for full e2e, we'll always run 310p test
3. for main2main test, we'll stop run 310p test
- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
Add tutorials for `Qwen3-VL-30B-A3B-Instruct`.
- vLLM version: release/v0.13.0
- vLLM main:
bc0a5a0c08
---------
Signed-off-by: shen-shanshan <467638484@qq.com>
### What this PR does / why we need it?
1. Rename num_iterations_eplb_update to expert_heat_collection_interval.
2. Rename num_wait_worker_iterations to algorithm_execution_interval.
3. Rename init_redundancy_expert to num_redundant_experts because the
variable with the same meaning in vLLM is named this way.
4. Delete gate_eplb because we don't need this feature.
5. Move eplb config into a dict in additional config.
6. Depend on pr5817
### Does this PR introduce _any_ user-facing change?
before this pr：
`--additional-config '{"dynamic_eplb":true,
"num_iterations_eplb_update": 4000, "num_wait_worker_iterations": 150,
"init_redundancy_expert": 16, "expert_map_path": "xxx.json"}'`
after this pr:
`--additional-config
'{"eplb_config":{"dynamic_eplb":true,"expert_heat_collection_interval":4000,
"algorithm_execution_interval":150,"num_redundant_experts": 16,
"expert_map_path": "xxx.json"}}'`
### How was this patch tested?
#### test qwen3-235b eplb num_redundant_experts=16
without pr5817
| dataset | version | metric | mode | vllm-api-general-chat |
|----- | ----- | ----- | ----- | -----|
| aime2024 | 604a78 | accuracy | gen | 83.33 |
with pr5817
| dataset | version | metric | mode | vllm-api-general-chat |
|----- | ----- | ----- | ----- | -----|
| aime2024 | 604a78 | accuracy | gen | 86.67 |
- vLLM version: v0.13.0
- vLLM main:
45c1ca1ca1
Signed-off-by: shenchuxiaofugui <1311027364@qq.com>
### What this PR does / why we need it?
Based on the RFC:https://github.com/vllm-project/vllm-ascend/issues/5604
This PR is a refactoring of vllm_ascend/distributed, moving all
kv_transfer realtaed codes into a dedicated folder, which has already
been done in vLLM
### Does this PR introduce _any_ user-facing change?
NA
### How was this patch tested?
- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef
---------
Signed-off-by: lty <linhebiwen@gmail.com>
### What this PR does / why we need it?
Since we have upgrade all the nodes' `cann` HDK version to `25.3rc1`, we
should not limit nightly schedule to the specific nodes
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.13.0
- vLLM main:
bde38c11df
Signed-off-by: wangli <wangli858794774@gmail.com>
### What this PR does / why we need it?
fix bug : https://github.com/vllm-project/vllm-ascend/issues/5634
Intermittent CI failure due to a compilation error in the triton
operator
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef
---------
Signed-off-by: Meihan-chen <jcccx.cmh@gmail.com>
### What this PR does / why we need it?
When there is no kv cache in some devices, the `_compute_prefill_context
func` will return `None`, which is unexecpted. This PR replaces None
with full zeros/-inf tensors to avoid TypeError.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
```bash
pytest tests/e2e/multicard/4-cards/long_sequence/test_chunked_prefill.py -k test_models_chunked_prefill_with_empty_kvcache
```
- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef
---------
Signed-off-by: QiuChunshuo <qiuchunshuo@huawei.com>
### What this PR does / why we need it?
this pr implement eagle spec decoding for model runner v2, please see
RFC https://github.com/vllm-project/vllm-ascend/issues/5208
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
vLLM version: v0.13.0
---------
Signed-off-by: Ronald1995 <ronaldautomobile@163.com>
### What this PR does / why we need it?
While using the LLM Compressor quantization tool from the VLLM community
to generate quantized weights, the VLLM Ascend engine needs to be
adapted to support the compressed tensors quantization format.
1. Support Moe model W8A8 Int8 dynamic weight.
2. Specify W4A16 quantization configuration.
Co-authored-by: menogrey 1299267905@qq.com
Co-authored-by: kunpengW-code 1289706727@qq.com
### Does this PR introduce _any_ user-facing change?
No
- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef
---------
Signed-off-by: LHXuuu <scut_xlh@163.com>
Signed-off-by: menogrey <1299267905@qq.com>
Signed-off-by: Wang Kunpeng <1289706727@qq.com>
Co-authored-by: menogrey <1299267905@qq.com>
Co-authored-by: Wang Kunpeng <1289706727@qq.com>
### What this PR does / why we need it?
Fixed an accuracy problem when using eagle3 with sp.
The problem is described in
https://github.com/vllm-project/vllm-ascend/issues/5825.
It also adds a much more precise way to determine whether drafter should
use `sp` or not.
Also, it changes the `eager` of drafter to be a real `eager` in frontend
to avoid a `fx-graph` problem.
### Does this PR introduce _any_ user-facing change?
N/A
### How was this patch tested?
For simpilicity, we test it as in
https://github.com/vllm-project/vllm-ascend/issues/5825.
And we get the same result of `eagle3` with `sp` disabled.
```text
--------------------------------------------------
total_num_output_tokens: 1000
num_drafts: 437
num_draft_tokens: 1311
num_accepted_tokens: 564
mean acceptance length: 2.29
--------------------------------------------------
acceptance at token 0: 0.62
acceptance at token 1: 0.40
acceptance at token 2: 0.27
acceptance at token 3: 0.00
acceptance at token 4: 0.00
acceptance at token 5: 0.00
```
* vLLM version: v0.13.0
* vLLM main:
2f4e6548ef
Signed-off-by: drslark <slarksblood@qq.com>
### What this PR does / why we need it?
This PR depends on PR
https://github.com/vllm-project/vllm-ascend/pull/4046. And only if the
latter merged, it will work.
This PR aims to solve the issue
https://github.com/vllm-project/vllm-ascend/issues/3240.
The new-added Llama-2-7b-hf and Qwen3-0.6B testcases will cover the
senarios that the LoRA weights are added to q_proj, v_proj, k_proj,
o_proj, gate_proj, up_proj, down_proj, embed_tokens and lm_head modules.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
pytest -sv tests/e2e/singlecard/test_llama2_lora.py
pytest -sv tests/e2e/singlecard/test_qwen3_multi_loras.py
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
---------
Signed-off-by: paulyu12 <507435917@qq.com>
### What this PR does / why we need it?
According to the official documentation, the parameter
"draft_tensor_parallel_size": 1 is supposed to be applied to the Eagle3
model. However, based on actual debugging, it was found that the number
of tensor parallelisms (tp) of the Eagle model is consistent with that
of the target model. The setting of tp for the draft model did not take
effect as expected.
**Note:** This feature has not been superimposed and tested with `sp`
and `dp`. It will be adapted later
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
```python
from vllm import LLM, SamplingParams
def main():
prompts = [
"The future of AI is",
]
# Create a sampling params object.
sampling_params = SamplingParams(temperature=0.8, top_p=0.95)
# Create an LLM.
llm = LLM(
model="meta-llama/Llama-3.1-8B-Instruct",
tensor_parallel_size=4,
gpu_memory_utilization=0.9,
enforce_eager=True,
speculative_config={
"method": "eagle3",
"model": "yuhuili/EAGLE3-LLaMA3.1-Instruct-8B"
"draft_tensor_parallel_size": 1,
"num_speculative_tokens": 3,
},
)
# Generate texts from the prompts.
outputs = llm.generate(prompts, sampling_params)
print(f"Outputs: {outputs}")
for output in outputs:
prompt = output.prompt
generated_text = output.outputs[0].text
print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
```
- vLLM version: v0.13.0
- vLLM main:
45c1ca1ca1Fixesvllm-project/vllm#31345
Signed-off-by: zhaomingyu <zhaomingyu13@h-partners.com>
Co-authored-by: drslark <slarksblood@qq.com>
