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Comments (6)

ww0o0 avatar ww0o0 commented on June 12, 2024 1

我也遇到了这个问题,使用vllm对第一个task测完之后就会卡住了

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ww0o0 avatar ww0o0 commented on June 12, 2024 1

目前可以通过运行时把 指定的很大避免对数据集进行切分从而规避这个问题,但是只是一个暂时的解决方案,还是希望开发人员可以看看怎么解决~--max-partition-size

--max-partition-size 对单个数据集可以解决,但是多个数据集进行测评的话还是会分为多个task也会出现这个问题

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Zbaoli avatar Zbaoli commented on June 12, 2024 1

in opencompass/models/vllm.py

import ray
if ray.is_initialized():
    self.logger.info('shutdown ray instance to avoid "Calling ray.init() again" error.')
     ray.shutdown()

add above command before calling vllm LLM class;
in about 52 lines;

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IcyFeather233 avatar IcyFeather233 commented on June 12, 2024

目前可以通过运行时把 --max-partition-size 指定的很大避免对数据集进行切分从而规避这个问题,但是只是一个暂时的解决方案,还是希望开发人员可以看看怎么解决~

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Zbaoli avatar Zbaoli commented on June 12, 2024

same question, get "Calling ray.init() again after it has already been called." error

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IcyFeather233 avatar IcyFeather233 commented on June 12, 2024

in opencompass/models/vllm.py

import ray
if ray.is_initialized():
    self.logger.info('shutdown ray instance to avoid "Calling ray.init() again" error.')
     ray.shutdown()

add above command before calling vllm LLM class; in about 52 lines;

发现使用了这个方法之后,对于单模型多数据集的情况,每次有新数据集,似乎模型也要跟着重新启动一遍ray,即每处理一个数据集都会输出:

2024-04-12 01:59:04,123 INFO worker.py:1743 -- Started a local Ray instance. View the dashboard at 127.0.0.1:8266 
INFO 04-12 01:59:44 llm_engine.py:75] Initializing an LLM engine (v0.4.0) with config: model='xxx', tokenizer='xxx)

(RayWorkerVllm pid=108846) INFO 04-12 02:01:37 selector.py:16] Using FlashAttention backend.

然而我发现这个过程十分耗时,有没有办法能改成启动一遍ray,一口气把数据集都跑完?

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