我可以在COLAB PRO中使用GPU
大约4个月前，我对TensorFlow模型的学习缓慢。学习速度是如此慢，由于今天自己检查一下，我能够确认GPU是正常检测到的，但是GPU功率已经关闭。挥发性的GPU UTIT也分配为0，但看起来GPU并未用于训练。当我寻找原因时，有一个说法是数据I/O瓶颈是，所以我还修改了数据载体加载程序，当我在其他COLAB帐户中运行相同的代码和数据集时，我可以看到GPU是GPU分配效果很好，时间也缩短了。如果操作系统设置有问题，或者我需要修复一些问题，请告诉我。祝你有美好的一天
I am using colab pro. About 4 months ago, I experienced slow learning of the tensorflow model. The learning speed is so slow, and as a result of checking it myself today, I was able to confirm that the gpu was detected normally, but the GPU POWER was off. The volatile GPU Util is also allocated as 0 , but it looks like the GPU is not being utilized for training. When I looked for the cause, there was a saying that the data I/O bottleneck was, so I also modified the DATALOADER, and when I ran the same code and dataset in a different COLAB account, I was able to see that the GPU allocation worked well and the time was also shortened. If there is a problem with the os settings or if there is something I need to fix, please let me know. have a good day
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我发现问题只是一个路径问题。正如我们之前获得的反馈一样，似乎已经通过文件夹加载图像的瓶颈了。
通过将数据集的路径指定为内容/来解决。
I figured out that the problem was simply a path problem. As we've gotten feedback before, it seems like there's been a bottleneck in loading images through folders.
It was solved by specifying the path of the dataset as content/ .