[Bugfix] Retrieve num_redundant_experts from eplb_config in torchair qwen3_moe.py (#2857)
### What this PR does / why we need it?
This PR addresses a configuration retrieval issue related to EPLB
(Expert Parallel Load Balancing) settings in qwen3_moe.py.
The key change is adjusting the source of num_redundant_experts to
correctly fetch from the eplb_config sub-structure within
parallel_config, rather than directly from parallel_config. This aligns
with the updated configuration hierarchy for EPLB-related parameters.
This change references `vllm_ascend/models/qwen3_moe.py`
https://github.com/vllm-project/vllm-ascend/blob/main/vllm_ascend/models/qwen3_moe.py#L255-L257
### Does this PR introduce _any_ user-facing change?
NA
### How was this patch tested?
run bash as follows and test pass
```
source /sfs_turbo/humpy/B080/cann_b080/ascend-toolkit/set_env.sh
source /sfs_turbo/humpy/B080/cann_b080/nnal/atb/set_env.sh
#export HCCL_BUFFSIZE=300
# export HCCL_SOCKET_IFNAME="eth0"
# export TP_SOCKET_IFNAME="eth0"
# export GLOO_SOCKET_IFNAME="eth0"
# export HCCL_IF_IP=33.215.118.231
export VLLM_USE_V1=1
export VLLM_ASCEND_ENABLE_MOE_ALL2ALL_SEQ=1
export TASK_QUEUE_ENABLE=1
# export VLLM_VERSION=0.9.1
export PYTORCH_NPU_ALLOC_CONF=expandable_segments:True
export HCCL_OP_EXPANSION_MODE="AIV"
export HCCL_INTRA_PCIE_ENABLE=1
export HCCL_INTRA_ROCE_ENABLE=0
rm -rf ./.torchair_cache/
rm -rf ./dynamo_*
rm -rf /root/ascend/log/debug/plog/*
python -m vllm.entrypoints.openai.api_server \
--model=/sfs_turbo/tzq/model/Qwen/Qwen3-235B-A22B/ \
--served-model-name auto \
--port 8006 \
-tp 1 \
-dp 16 \
--enable_expert_parallel \
--max-num-seqs 48 \
--max-model-len 32768 \
--gpu-memory-utilization 0.95 \
--additional-config '{"torchair_graph_config":{"enabled":true,"use_cached_graph":true,"graph_batch_sizes_init":false,"graph_batch_sizes":[1, 8, 16, 24, 48]}, "ascend_scheduler_config":{"enabled":false}, "refresh":true}' \
--kv-transfer-config \
'{
"kv_connector": "SharedStorageConnector",
"kv_buffer_device": "npu",
"kv_role": "kv_consumer",
"kv_parallel_size": 2,
"kv_port": "20002",
"engine_id": "decode-'${NODE_RANK}'",
"kv_rank": 1,
"kv_connector_extra_config": {
"prefill": {
"dp_size": 1,
"tp_size": 16
},
"decode": {
"dp_size": 16,
"tp_size": 1
}
}
}' \
2>&1 disown
```
- vLLM version: main
- vLLM main:
0ae43dbf8c
Signed-off-by: wyu0-0 <woshilynn@163.com>
eab3635850