Comments (6)
@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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@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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Great! I'll let you know once the fix for this is on master.
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Fix is in the latest version!
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Interesting. Have you tried with torch.Tensor data types?
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Cool, thank you!
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Related Issues (20)
- [Bug]: Custom metric issue HOT 4
- [GENERAL SUPPORT]: CI_Level Paretofrontier
- [Bug]: Large sample time increase in ax-platform >= version 0.3.5 HOT 6
- [GENERAL SUPPORT]: Reference Point for Multi-Objective Bayesian Optimization HOT 5
- [GENERAL SUPPORT]: Plotting Pareto fronts / Posterior mean model HOT 6
- [GENERAL SUPPORT]: Getting best predicted point of a botorch model HOT 10
- [GENERAL SUPPORT]: Logical-or in outcome constraints HOT 4
- [GENERAL SUPPORT]: Parallelism and arbitrary parameter type support. HOT 5
- [GENERAL SUPPORT]: How to Standardize and Normalize Data for Service API HOT 6
- [FEATURE REQUEST]: Implement ImprovementGlobalStoppingStrategy for batch trials HOT 2
- [GENERAL SUPPORT]: Plot observed pareto frontier alongside remaining Arms HOT 2
- [GENERAL SUPPORT]: Why `qLogNEI` by default? HOT 2
- [Bug]: No module named 'ax.analysis' HOT 2
- Performance issue HOT 11
- [GENERAL SUPPORT]: Multi-Objective, scale about the objectives HOT 3
- Multi-Objective, scale about the objectives HOT 2
- [GENERAL SUPPORT]: MultiTask with Choice Parameter using Ax Service API HOT 2
- [GENERAL SUPPORT]: Seeking Guidance on Surrogate Model and Acquisition Function for High-Dimensional Optimization Problem HOT 10
- [FEATURE REQUEST]: Issues with Customizing Data Classes HOT 3
- [FEATURE REQUEST]: RangeParameter handling periodic variables (such as angles) HOT 2
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