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标签的一些细节 #12
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@starsky68 标签保持一模一样的即可, 问题的原因可能不在标签,而在你的一些参数设置,具体可以提前打断点debug看下,祝好运,最近有点忙.... |
谢谢回复,我根据计算只修改了cfg中3个yolo的: |
Hello, were you able to solve this issue? I am facing the same "/pytorch/aten/src/THCUNN/ClassNLLCriterion.cu:108: cunn_ClassNLLCriterion_updateOutput_kernel: block: [0,0,0], thread: [1,0,0] Assertion t >= 0 && t < n_classes failed." error. I have checked my labels and they seem to be correct (ie no out of class labels) |
你好先生, |
@CaptainEven
打扰了,可以告知一下标签的格式细节呢,我明明使用的和mcmot一样的标签,但是,似乎一直出现越界的情况。
比如我有54个类,标签是这样的:
0.0 1.0 0.18229166666666666 0.37962962962962965 0.028125 0.10648148148148148
0.0 2.0 0.6484375 0.3731481481481482 0.03333333333333333 0.09351851851851851
0.0 3.0 0.7234375 0.49722222222222223 0.028645833333333332 0.09444444444444444
5.0 1.0 0.18802083333333333 0.7231481481481481 0.28489583333333335 0.3527777777777778
5.0 2.0 0.521875 0.4388888888888889 0.17552083333333332 0.19814814814814816
17.0 1.0 0.190625 0.4064814814814815 0.03802083333333333 0.09722222222222222
17.0 2.0 0.6494791666666667 0.4046296296296296 0.0484375 0.10833333333333334
39.0 1.0 0.4265625 0.18518518518518517 0.2526041666666667 0.2037037037037037
39.0 2.0 0.6135416666666667 0.1 0.0828125 0.11481481481481481
3.0 1.0 0.7208333333333333 0.25833333333333336 0.11927083333333334 0.18611111111111112
38.0 1.0 0.8604166666666667 0.4388888888888889 0.04114583333333333 0.08888888888888889
5.0 3.0 0.8666666666666667 0.6546296296296297 0.26666666666666666 0.19166666666666668
2.0 1.0 0.6552083333333333 0.34074074074074073 0.0109375 0.025
0.0 4.0 0.46510416666666665 0.362962962962963 0.0296875 0.07407407407407407
/pytorch/aten/src/THCUNN/ClassNLLCriterion.cu:108: cunn_ClassNLLCriterion_updateOutput_kernel: block: [0,0,0], thread: [1,0,0] Assertion
t >= 0 && t < n_classes
failed./pytorch/aten/src/THCUNN/ClassNLLCriterion.cu:108: cunn_ClassNLLCriterion_updateOutput_kernel: block: [0,0,0], thread: [2,0,0] Assertion
t >= 0 && t < n_classes
failed./pytorch/aten/src/THCUNN/ClassNLLCriterion.cu:108: cunn_ClassNLLCriterion_updateOutput_kernel: block: [0,0,0], thread: [4,0,0] Assertion
t >= 0 && t < n_classes
failed.RuntimeError: CUDA error: device-side assert triggered
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