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learnware.learnware_model not found. #2

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Fay-why opened this issue Feb 28, 2024 · 5 comments
Open

learnware.learnware_model not found. #2

Fay-why opened this issue Feb 28, 2024 · 5 comments

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@Fay-why
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Fay-why commented Feb 28, 2024

Dear author,
Thansk for your work!
I try to run the command line you provided. However, it fails to execute successfully (many module not found error in train.py), appearing that you haven't uploaded the complete files. Would you be able to upload the entire project so that we can utilize it?

@MoeinSorkhei
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MoeinSorkhei commented Feb 28, 2024

Hello @zhangyikaii, I have the same problem. It would be awesome if you could share share the code.

@zhangyikaii
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Dear @Fay-why and @MoeinSorkhei,
Thank you for bringing this to our attention, and we sincerely apologize for any inconvenience caused by the oversight. We greatly appreciate your continued support and understanding.
Rest assured, we are committed to rectifying the situation promptly and ensuring all necessary code is uploaded accordingly. Should you have any further questions or concerns, please don't hesitate to reach out to us.

@Fay-why
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Fay-why commented Mar 12, 2024

Thanks for your reply. It looks like the requirement.txt is still missing.
Actually, I just want to use your trained model to test my datasets. Is there a easy way to just do testing on new task(maybe input is features, labels of dataset)?

Also, I wonder if I take some new pre-trained models as candidate models, whether or not I have to retrain?
If so, could you please provide the training dataset and Rankagg module( I understand rankagg is to generate ground truth for training pairs) ?

@Fay-why
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Fay-why commented Mar 12, 2024

File "trainer.py", line 79, in
args.prototype_maxnum = max([DATASET2NUM_CLASSES[i] for i in (args.train_dataset + args.test_dataset)])
KeyError: 'c86'

@zhangyikaii
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I apologize for any inconvenience caused, and thank you for your continued follow-up. We have re-reviewed and updated the code, and the dataset has been uploaded here. I would appreciate if you could attempt to replicate the experiment again with the provided dataset. Thank you for your understanding and patience.

If you would like to engage in a more detailed discussion, please feel free to contact me via email or WeChat. My WeChat ID is cifar10.

Thank you once again! We will continue to strive to produce better work.

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3 participants