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lena-kashtelyan avatar lena-kashtelyan commented on March 29, 2024 2

@Irynei, this is intentional behavior –– the evaluation function is strictly typed, and it's return type is a union of a float, a tuple of two floats, and a dictionary of a string to such tuples, as documented in SimpleExperiment. We use python builtins for primitive types and convert from numpy primitives where necessary. However, you're right that for the evaluation function, we should allow numpy types –– will add that support shortly.

Is it much trouble to convert back from numpy to python primitive in the evaluation function, for now? You could use our utility ax.utils.common.typeutils.numpy_type_to_python_type, if you'd like.

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Irynei avatar Irynei commented on March 29, 2024 2

@lena-kashtelyan, thanks for your explanation. I was expecting the evaluation function to work with numpy types, so for me, that was a surprising behavior.
No, It's not hard to convert them for now, but thanks for the suggestion.

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lena-kashtelyan avatar lena-kashtelyan commented on March 29, 2024 1

Great! I'll let you know once the fix for this is on master.

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ldworkin avatar ldworkin commented on March 29, 2024 1

Fix is in the latest version!

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dkatz23238 avatar dkatz23238 commented on March 29, 2024

Interesting. Have you tried with torch.Tensor data types?

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Irynei avatar Irynei commented on March 29, 2024

Cool, thank you!

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