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I met cuda out of memory when using 2080 with 11G memory.Is there any way to solve this problem?
The text was updated successfully, but these errors were encountered:
Hi, as a reference, we executed our experiments on 4 TitanX GPUs with 12G memory each, and the training costs around 8~10G memory per GPU.
If the out-of-memory error still occurs, you can use a smaller max_instances in configs/qg_rcnn_r50_fpn.py, e.g., from 8 to 6.
max_instances
configs/qg_rcnn_r50_fpn.py
8
6
Alternatively, you can also add a --fp16 flag in your training script, which will however slightly reduce the performance by ~1%.
--fp16
~1%
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I met cuda out of memory when using 2080 with 11G memory.Is there any way to solve this problem?
The text was updated successfully, but these errors were encountered: