Comments (4)
@xmy0916
我在我的环境下执行以下命令以模拟您的情况,但是无法复现该报错。考虑可能是触发了 peft 某些奇怪的载入逻辑导致了这个报错。
CUDA_VISIBLE_DEVICES=0,1 xtuner mmbench internlm/internlm2-chat-7b --llava xtuner/llava-internlm2-7b --visual-encoder openai/clip-vit-large-patch14-336 --prompt-template internlm2_chat --data-path ./MMBench_DEV_EN.tsv
目前可以尝试在单卡环境下评测,验证是否有问题。
比如使用2号卡单卡评测:
CUDA_VISIBLE_DEVICES=2 xtuner mmbench XXX
同时,也可以启用 DDP,以加速评测。以使用2号、3号卡为例:
NPROC_PER_NODE=2 CUDA_VISIBLE_DEVICES=2,3 xtuner mmbench XXX
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@LZHgrla project layer我做了点改动,加了个卷积层,不确定是不是这个导致的
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@xmy0916
如果改动不涉及 device,应该不会有问题
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@xmy0916 如果改动不涉及 device,应该不会有问题
好滴,我也感觉挺奇怪的,我加cuda device visalbe=0限制只用一张卡就行了
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