Comments (6)
@digantamisra98 I just changed the class_num from 10 to 100 and it runs successfully. Thanks!
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Hi. Can you please tell me the environment in which you're running this code/ GPU on which the code is running. Or you can simply provide me the nvidia-smi
output. I will try to replicate the error you had tomorrow. Regarding Stats.ipynb, you'll have to load in the results of your experiment in npz format to generate the graph. For the results shown, it was generated for the CalTech-256 dataset benchmark.
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@digantamisra98 Hi, thanks for your detailed reply. I was trying to run the notebook cifar-10-senet-18-mish, with a Ubuntu16.04+torch1.13+CUDA10.1+NVIDIA driver430.50, and on a 1080Ti GPU.
I am able to run the code on cifar-10 with its initial form, however when I'm trying to change the code on cifar-100, it raises the above error. I'm not quite sure how to implement on cifar-100, so I just try to change cifar-10 in the code to cifar-100, as it's shown above.
I tried to search for the error, somebody says that it's a category label number problem. However it is hard for me to solve it.
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@SkeletonOne have you changed the num_classes = 10 to 100 ?
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@digantamisra98 A little more confusion... Could you give me a guidance of how to generate the .npz file for Caltech-256 dataset? I'd appreciate it a lot!
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You have to benchmark CalTech-256 dataset which is easily available on Kaggle and save the log files in npz format to use that notebook
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Related Issues (20)
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