Comments (2)
I found this example which was helpful:
https://ax.dev/tutorials/gpei_hartmann_loop.html
And also this code which defined the parameter constraints:
https://github.com/facebook/Ax/blob/230cdb5f6cec123aebe872b0f1d8f784f9a2f23b/ax/service/utils/instantiation.py
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Hi @dqii,
Take a look at https://ax.dev/api/_modules/ax/service/utils/instantiation.html#constraint_from_str
We can parse order constraints of the form "x1 >= x2" from strings, but for more general constraints we suggest using the classes from your other link.
To constrain a variable to be an int with the Loop API you can define it as follows:
{
"name": "x1",
"type": "range",
"bounds": [0, 10],
"value_type": "int", # Optional, defaults to inference from type of "bounds".
},
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Related Issues (20)
- Comparison of multi-objective acquistion functions HOT 14
- plot_pareto_frontier HOT 6
- attach trials HOT 8
- Multi-task BO with Service API HOT 2
- constrains HOT 17
- Question : Generation 12 trials HOT 8
- Question: Multi-Task Multi Objective HOT 1
- MOO not respecting nonlinear constraints HOT 1
- Problem with Fixed parameters if nonlinear_inequality_constraint is imposed
- Safe optimization in the Service API HOT 4
- The same point is evaluated multiple times during Integer Optimization with BO. HOT 5
- ax_client.generation_strategy.trials_as_df HOT 9
- Managing Objective Function Evaluation Failures in Ax for MOO HOT 6
- [GENERAL SUPPORT]: Managing Objective Function Evaluation Failures in Ax for MOO HOT 3
- [GENERAL SUPPORT]: Using qNegIntegratedPosteriorVariance HOT 3
- [GENERAL SUPPORT]: Reference point for multi-objective bayesian optimization HOT 4
- [GENERAL SUPPORT]: Adjusting search space or accommodating out-of-bounds initial data HOT 19
- [GENERAL SUPPORT]: Manual configuration, HOT 1
- [Bug]: Custom metric issue HOT 4
- [GENERAL SUPPORT]: CI_Level Paretofrontier
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