Comments (3)
the training process with different learning rate setting is shown below:
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看你有跑通这篇代码,所以想请教你个问题!我是python2.7,pytorch1.0跑的segmentation的代码!
看到有报这个错误,RuntimeError: cuda runtime error (59) : device-side assert triggered at ...
网上说是计算损失的时候label不是从0开始的,pytorch必须是(0,n-1)的label才不会报错,然后这篇论文在设置label的时候,类别个数设置为20,有一个类别作者说是背景。但是我现在想,我的这个报错会不会与作者设置的20个label有关!
请问你在跑这篇代码的时候有遇到这个问题吗?
或者你知道这是哪里出错了吗?多有打扰,期待你的答复!!!
from mcd_da.
看你有跑通这篇代码,所以想请教你个问题!我是python2.7,pytorch1.0跑的segmentation的代码!
看到有报这个错误,RuntimeError: cuda runtime error (59) : device-side assert triggered at ...
网上说是计算损失的时候label不是从0开始的,pytorch必须是(0,n-1)的label才不会报错,然后这篇论文在设置label的时候,类别个数设置为20,有一个类别作者说是背景。但是我现在想,我的这个报错会不会与作者设置的20个label有关!
请问你在跑这篇代码的时候有遇到这个问题吗?或者你知道这是哪里出错了吗?多有打扰,期待你的答复!!!
你好,我对作者关于这两个数据"synthia", "city16"设置的16个类别这里有疑问, 0-15是15个实际的类别,255是背景,那在代码里args.n_class就等于16, 那么这句话: weight[args.n_class - 1] = 0 # Ignore background loss, 其实是将标签为15 的类别的weight设为0了,而不是将背景weight设为0的啊?
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Related Issues (20)
- Loss is becoming negative HOT 3
- About datasets on classification HOT 3
- About the classifiers. HOT 1
- Replicating the results HOT 5
- When do segmentation task, you also need labels for target domain.
- Code for " Strong-Weak Distribution Alignment for Adaptive Object Detection " HOT 1
- Question about the handwritten digit experiment HOT 7
- cityscapes/info.json
- Some problems with building my own datasets on classificaion HOT 1
- question for location HOT 2
- Asking for the visualization code
- sharing svhn2mnist result
- Model Selection
- USPS->Mnist source-only result can't reach 0.634 HOT 2
- The misnt_data.mat dataset
- drn_d_105-12b40979.pth HOT 3
- The link (http://crcv.ucf.edu/data/adaptationseg/ICCV_dataset.zip) is lost.
- The difference between trainer and trainer_one_step
- synth traffic dataset
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