Nonlinear parameter constraints

[yiyinying]

How to define nonlinear constraints

[lena-kashtelyan]

@yiyinying, I don't think it's currently supported, but may I learn what kind of a constraint you are looking to define, as well as whether it is a parameter constraint or an outcome metric constraint?

[yiyinying]

Should be a parameter constraint。
For example：
x1^2+x2^2=9

[Balandat]

We currently don't support general non-linear parameter constraints.

Is there a way you can reparameterize the constraint? E.g. in your example you'd have a single parameter x' in [0, 2pi] and parameterize x1 = 3 cos(x'), x2 = 3 sin(x').

May I ask what your use case is? In principle it's possible to support nonlinear parameter constraints, but it would require a significant amount of work (and it would slow down candidate generation significantly as well).

[lena-kashtelyan]

@yiyinying, does @Balandat's solution with parameterizing the constraint work for your use case? If not, could you tell us a bit more about your use case, so that we can consider supporting it?

[jkterry1]

@lena-kashtelyan @Balandat I have a practical constraint that I don't believe can be sensibly supported without nonlinear constraints: (20*n_envs*n_steps) % nminibatches == 0. That's a fairly common constraint in reinforcement learning. While work arounds exist, they're super hacky and make the search space much less smooth.

I can also explain where that constraint comes from if you'd like.

[lena-kashtelyan]

I'd be curious to hear @Balandat's thoughts on this one.