yolov2-yolov3_PyTorch
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yjh0410
Why is training so slow
Because the workers in dataloader is 0. I denote this in my train code. If I add workers, it will report some errors when I use multiscale training trick. I have no idea how to solve this problems.
---Original--- From: "lilslsls"<[email protected]> Date: Sat, May 23, 2020 13:54 PM To: "yjh0410/yolov2-yolov3_PyTorch"<[email protected]>; Cc: "Subscribed"<[email protected]>; Subject: [yjh0410/yolov2-yolov3_PyTorch] Why is training so slow (#34)
4900 images and batchsize：64 gpu：2080TI
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And if you don't plan to try multi scale training, you'd better set num_workers as 8 or more to accelerate training.
---Original--- From: "lilslsls"<[email protected]> Date: Sat, May 23, 2020 13:54 PM To: "yjh0410/yolov2-yolov3_PyTorch"<[email protected]>; Cc: "Subscribed"<[email protected]>; Subject: [yjh0410/yolov2-yolov3_PyTorch] Why is training so slow (#34)
4900 images and batchsize：64 gpu：2080TI
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I used yolov2 training, not multi-scale, and a batch spent nearly one minute in training. An epoch has many batches. So I feel strange. Is it because the code parses XML.
No multi scale？Aha！You can set num_workers as 8(default=8).
Do you set --cuda to use GPU？ Its default value is False.
---Original--- From: "lilslsls"<[email protected]> Date: Sat, May 23, 2020 14:14 PM To: "yjh0410/yolov2-yolov3_PyTorch"<[email protected]>; Cc: "Comment"<[email protected]>;"Jianhua Yang"<[email protected]>; Subject: Re: [yjh0410/yolov2-yolov3_PyTorch] Why is training so slow (#34)
I used yolov2 training, not multi-scale, and a batch spent nearly one minute in training. An epoch has many batches. So I feel strange. Is it because the code parses XML.
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Sorry, I didn't read the code carefully. Now it's fast to use CUDA. thank you
You're welcome！！！(๑><๑）
---Original--- From: "lilslsls"<[email protected]> Date: Sat, May 23, 2020 14:27 PM To: "yjh0410/yolov2-yolov3_PyTorch"<[email protected]>; Cc: "Comment"<[email protected]>;"Jianhua Yang"<[email protected]>; Subject: Re: [yjh0410/yolov2-yolov3_PyTorch] Why is training so slow (#34)
Sorry, I didn't read the code carefully. Now it's fast to use CUDA. thank you
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SET CUDA TRUE To use GPU!
envs
- 2080ti x 1
- ubuntu 16.04
- python 3.6
- pytorch 1.5.0
- cpu cores :8
- cpu processor num :16
without GPU
when i use cpu to train the model ,the training is sooooooo slow, such as the blow info... [Epoch 1/250][Iter 0/517][lr 0.000000][Loss: obj 210.70 || cls 4.88 || bbox 8.88 || total 224.46 || size 416 || time: 47.35]
use GPU
but when i set cuda True, the training speed up obivous! Epoch 1/250][Iter 10/517][lr 0.000000][Loss: obj 212.88 || cls 7.12 || bbox 9.07 || total 229.07 || size 416 || time: 2.20]
SET CUDA TRUE To use GPU!
envs
- 2080ti x 1
- ubuntu 16.04
- python 3.6
- pytorch 1.5.0
- cpu cores :8
- cpu processor num :16
without GPU
when i use cpu to train the model ,the training is sooooooo slow, such as the blow info... [Epoch 1/250][Iter 0/517][lr 0.000000][Loss: obj 210.70 || cls 4.88 || bbox 8.88 || total 224.46 || size 416 || time: 47.35]
use GPU
but when i set cuda True, the training speed up obivous! Epoch 1/250][Iter 10/517][lr 0.000000][Loss: obj 212.88 || cls 7.12 || bbox 9.07 || total 229.07 || size 416 || time: 2.20]
Thanks for your advice！HAHA！
The reason why I didn't set cuda as True is that I wanna indirectly remind everyone who plans to try this project to use GPU to train the model. If no GPU，it's a little hard to study object detection.