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train the net #7
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Hi, thanks for your interest.
Best regards. |
Thanks for such a quick answer! |
Hello, when I evaluate and visualize, the process is killed when it reaches 14%. It may be a memory overflow problem. Is there any good solution?my graphics card is titan |
Hello, What's your GPU memory size ? I didn't record the runtime memory size before, but GTX 1080Ti is enough for me. One way your can try is to use Best. |
Hi, sorry to trouble you again! Because I just started learning this aspect, so I don't understand a lot of things. I still can't solve the problem of killing the process. I don't know how to add this code. torch.cuda.empty_cache() ;
I executed this command. Is this not using CUDA?
python eval_3dmatch.py --benchmark 3DMatch --data_root your_path/indoor --checkpoint your_path/3dmatch.pth --saved_path work_dirs/3dmatch [--vis] [--no_cuda]
If I want to use CUDA for evaluation and visualization, how do I need to modify the code?
Hope to get your help, thank you very much!!!
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发件人: "zhulf0804/NgeNet" ***@***.***>;
发送时间: 2022年6月26日(星期天) 中午12:19
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主题: Re: [zhulf0804/NgeNet] train the net (Issue #7)
Hello,
What's your GPU memory size ? I didn't record the runtime memory size before, but GTX 1080Ti is enough for me.
One way your can try is to use torch.cuda.empty_cache() after each iteration.
Best.
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Hi,
Besides, you may add Best. |
Hi!Thank you so much for sharing!
1:How many epochs has this been trained for? I didn't find any instructions on the source code,
for epoch in range(config.max_epoch):
print('=' * 20, epoch, '=' * 20)
train_step, val_step = 0, 0
for inputs in tqdm(train_dataloader):
for k, v in inputs.items():
if isinstance(v, list):
for i in range(len(v)):
inputs[k][i] = inputs[k][i].cuda()
else:
inputs[k] = inputs[k].cuda()
2: Why is training so slow? my graphics card is titan
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