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natbukowski avatar natbukowski commented on July 17, 2024 2

Thank you for mentioning this, as you can see in the documentation of AEFCNClusterer, and any deep learner in aeon, you have to use the save_best_model flag parameter to True, and you can choose the name using best_file_name . Best means the model that has the lowest training loss during training

Same thing goes if you wish the last model, use the save_last_model flag and the last_file_name string parameter

Deep Learners cannot be pickled, thats why you get this error, and thats why we have these parameters i described above.

Thanks for the mention @MatthewMiddlehurst , we should think of adding a warning or something about this somewhere so that users dont try to save it like that.

Let us know if this answers to your issue @natbukowski !

Yes this answered my question, thank you!

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TonyBagnall avatar TonyBagnall commented on July 17, 2024 1

I think we can close this now, feel free to reopen or raise a new issue

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hadifawaz1999 avatar hadifawaz1999 commented on July 17, 2024

Thank you for mentioning this, as you can see in the documentation of AEFCNClusterer, and any deep learner in aeon, you have to use the save_best_model flag parameter to True, and you can choose the name using best_file_name . Best means the model that has the lowest training loss during training

Same thing goes if you wish the last model, use the save_last_model flag and the last_file_name string parameter

Deep Learners cannot be pickled, thats why you get this error, and thats why we have these parameters i described above.

Thanks for the mention @MatthewMiddlehurst , we should think of adding a warning or something about this somewhere so that users dont try to save it like that.

Let us know if this answers to your issue @natbukowski !

from aeon.

TonyBagnall avatar TonyBagnall commented on July 17, 2024

as I understand it you just cant pickle tensorflow models?

from aeon.

hadifawaz1999 avatar hadifawaz1999 commented on July 17, 2024

as I understand it you just cant pickle tensorflow models?

yes

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