[Bug]: vllm.engine.async_llm_engine.AsyncEngineDeadError: Background loop has errored already. · Issue #5060 · vllm-project/vllm (github.com) 以及添加参数 ENGINE_ITERATION_TIMEOUT_S ## 设置为 180 timeout=configuration.request_timeout or 180.0...
VLLM_ENGINE_ITERATION_TIMEOUT_S=180 \ GLOO_SOCKET_IFNAME=enp5s0 \TP_SOCKET_IFNAME=enp5s0 \ NCCL_SOCKET_IFNAME=enp5s0 \ NCCL_DEBUG=info \ NCCL_NET=Socket \ NCCL_IB_DISABLE=0 WORKDIR /server COPY . . RUN apt-get update && apt -y install \ dos2unix tzdata vim tree curl wget \...
设置环境变量VLLM_ENGINE_ITERATION_TIMEOUT_S为更大的值(如180秒),以延长引擎每次迭代的超时时间。 在请求端配置中延长请求时间。 禁用自定义AllReduce:在启动参数中添加--disable-custom-all-reduce,可能有助于解决某些并发请求导致的错误。 4. 应用解决方案 根据具体情况选择上述解决方案中的一种或多种进行尝试...
return_value = task.result() File "/usr/local/lib/python3.10/dist-packages/vllm-0.5.3.post1+cpu-py3.10-linux-x86_64.egg/vllm/engine/async_llm_engine.py", line 630, in run_engine_loop async with asyncio_timeout(ENGINE_ITERATION_TIMEOUT_S): File "/usr/local/lib/python3.10/dist-...
Setting the environment variable ENGINE_ITERATION_TIMEOUT_S to >60 increases the async io timeout which may be causing the issue because inference on CPU is very slow. 👍 1 github-actions bot commented Jan 10, 2025 This issue has been automatically marked as stale because it has not ha...
FROMvllm/vllm-openai:v0.6.2ENVTZ=Asia/Shanghai\DEBIAN_FRONTEND=noninteractive\VLLM_ENGINE_ITERATION_TIMEOUT_S=180\GLOO_SOCKET_IFNAME=eth0\TP_SOCKET_IFNAME=eth0\NCCL_SOCKET_IFNAME=eth0\NCCL_DEBUG=info\NCCL_NET=Socket\NCCL_IB_DISABLE=0WORKDIR/serverCOPY. .RUNapt-get update && apt -y in...
VLLM_ENGINE_ITERATION_TIMEOUT_S=180 \ GLOO_SOCKET_IFNAME=ens18 \ TP_SOCKET_IFNAME=ens18 \ NCCL_SOCKET_IFNAME=ens18 \ NCCL_DEBUG=info \ NCCL_NET=Socket \ NCCL_IB_DISABLE=0 \ NODE_TYPE=worker \ HEAD_NODE_ADDRESS=127.0.0.1
要设置档位1(DeepSeek V2 236B W8A8 模型建议最大设置4个档位) export VLLM_ENGINE_ITERATION_TIMEOUT_S=1500 # 设置vllm请求超时时间(DeepSeek V2 236B W8A8 模型建议调大为6000) export 来自:帮助中心 查看更多 → 附录:基于vLLM不同模型推理支持最小卡数和最大序列说明 qwen2-57b-a14b - - ...
我添加了额外的环境变量：VLLM_CPU_KVCACHE_SPACE=4和额外的启动参数：python3 -m vllm.entrypoints....
当有请求时,会按照PP配置数量,创建requests_in_progress,持有PP_size个engine.step(ve)的消息。 后续会通过: async with asyncio_timeout(ENGINE_ITERATION_TIMEOUT_S): done, _ = await asyncio.wait( requests_in_progress, return_when=asyncio.FIRST_COMPLETED) ...