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In paper, It is written that VRAM consumption is way lower than others, 256mb or somethin.
But when I train bicycle dataset with command below, I checked nvidia-smi and it was consuming vram about 1~2GB, and its getting more and more when it goes to next step. It was over 7 GB at the end. Is that other way to check VRAM consumption? or just me having such issue?
In paper, It is written that VRAM consumption is way lower than others, 256mb or somethin.
But when I train bicycle dataset with command below, I checked nvidia-smi and it was consuming vram about 1~2GB, and its getting more and more when it goes to next step. It was over 7 GB at the end. Is that other way to check VRAM consumption? or just me having such issue?
~/YBS/torch_merf/torch-merf$ python main.py /data_ssd/YBS/merf_data/bicycle/ --workspace trial_bicycle --enable_cam_center --downscale 4
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