Closed CamRW closed 1 year ago
Hi @CamRW, I'm very sorry for the delayed response. Could you please kindly tell me whether your question is still applicable?
Generally speaking, the model is quite memory-intense, i.e., I doubt that you'll be able to fit it on a 4GB GPU. Running it on the CPU is unfortunately not possible due to the utilized base code.
Hi @vniclas,
No worries! I figured as much, I wanted to ask just in case there's a solution I'm not aware of. I'd say this question is no longer applicable. I'll test it on some more appropriate hardware and see if I can get the same results. Thanks for getting back to me! Feel free to close/delete/etc this issue.
Hello, thanks again for all your hard work on building this toolkit.
I apologize if I'm missing something obvious as I'm still pretty new to this :)
I'm trying to get the Efficient_LPS example_usage.py to run on a relatively low memory GPU (4 GB) purely for evaluation/inference with pretrained weights. Is this possible? I know that if I change the config parameter img_scale in singlegpu_semantickitti.py I can get it to fit on the gpu. E.g.
img_scale is normally (4096, 256) and when I try to run the example_usage with the original img_scale, I get the CUDA out of memory error:
I assume this parameter affects performance of the model in some way as I get the following evaluation statistics when running it on semantic kitti eval with img_scale=(1024, 64)
Is it possible to run this model on a relatively low memory gpu? Or, is it possible to run it on the CPU? I'd like to see if I can replicate the statistics from the original paper. Any help is greatly appreciated!
Sincerely, Cameron Weigel