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Add new argument num_classes to eval scripts #21

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@fabito fabito commented May 4, 2021

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@fabito fabito changed the title Add new argument num_classes to eval_knn script Add new argument num_classes to eval scripts May 4, 2021
Add num_labels to eval_linear, change max_accuracy to best_acc
@mathildecaron31
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Hi @fabito
I have just merged another PR dealing with the same issue in eval_linear.py. Can you update your PR accordingly :) ?
Thanks a lot for contributing

@fabito
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fabito commented May 11, 2021

Done @mathildecaron31

@mathildecaron31 mathildecaron31 force-pushed the main branch 2 times, most recently from ce8632f to 82d28b4 Compare May 13, 2021 17:33
@mathildecaron31
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Please rebase

@ketil-malde
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Good... but shouldn't this rather be automatically calculated from the number of directories in data_path/val and /train? What happens if I have more directories than num_labels? Or if val and train subdirectories don't match? (I can write the code for this, but would like to know if I misunderstand something here)

@woctezuma
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The pull request is just there to allow to specify the value of the function argument, which is otherwise used with its default value:

def knn_classifier(train_features, train_labels, test_features, test_labels, k, T, num_classes=1000):

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