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Home Page: https://nextorch.readthedocs.io/en/latest/
License: MIT License
Experimental design and Bayesian optimization library in Python/PyTorch
Home Page: https://nextorch.readthedocs.io/en/latest/
License: MIT License
Thank you for a great tool and this is probably something that is non-urgent as the core code still seems to work.
When trying to produce heat map and surface plots using the template I end up with a uniform value across all values:
I initially thought that there was a problem with my code, but when running one of your notebooks (10_PFR_mixed_type_inputs.ipynb) I see the exact same behaviour:
My assumption is that this is probably just a dependency issue. The optimal values still seem to be correct and so it doesn't seem to be a problem that affects the underlying data processing.
Nice work on NEXTorch! Seems like a compelling idea, and some difficulty with implementing human-in-the-loop optimization via Ax is what led me here.
Something very important for my use-case is inequality constraints for composition-based Bayesian optimization (also prevalence-based, fractional-based, etc., i.e. everything needs to sum to 1
). For example:
A + B + C <= 1
where A
, B
, and C
are parameters to be optimized.
For me, there would technically also be D
, the final parameter is determined automatically outside of the optimization loop via:
D = 1 - sum([A, B, C])
In other words, safe to ignore D
, but relevant for the context of a composition-based optimization.
Is it possible to specify an inequality constraint within the current implementation of NEXTorch?
I tried to create a conda environment where Ax and nextorch could play together, but I am not so lucky.
I installed ax-platform first.
nextorch 0.4.0 requires botorch<=0.4.0, but you have botorch 0.9.5 which is incompatible.
nextorch 0.4.0 requires gpytorch<=1.4, but you have gpytorch 1.11 which is incompatible.
Please update nextorch to make that possible.
Once I want to run your example in the supporting information of your paper, I cannot import PFR_yield. I also cannot install this package.
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