MrBlankness / LightM-UNet

Pytorch implementation of "LightM-UNet: Mamba Assists in Lightweight UNet for Medical Image Segmentation"
https://arxiv.org/abs/2403.05246
Apache License 2.0
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The issue of CUDA memory usage during training #8

Open Li-4 opened 7 months ago

Li-4 commented 7 months ago

Firstly, thank you for your outstanding work and contribution. I found that when training on the 3D dataset of 801Liver, the memory usage was very high, reaching 29140 MiB. May I ask if this is normal?

eclipse0922 commented 7 months ago

I'm not the author, but for reference The current implementation does not match the paper.

6

MrBlankness commented 7 months ago

Firstly, thank you for your outstanding work and contribution. I found that when training on the 3D dataset of 801Liver, the memory usage was very high, reaching 29140 MiB. May I ask if this is normal?

Perhaps this is an inherent issue with nnU-Net. If it's truly impossible to meet the memory requirements, we suggest using only the network model itself that we proposed, rather than employing the associated training pipeline.

xwgit2023 commented 3 months ago

请问有在二维数据集上跑,图片尺寸是多少,我发现256*256特别慢