Loopifying conditional kwarg processing in _optimize_acqf_batch (#1923

)

Summary:
Pull Request resolved: #1923

Small code simplification, pattern could be reused elsewhere for `kwarg` processing, particularly where a number of fields have to be check.

Reviewed By: esantorella

Differential Revision: D47297929

fbshipit-source-id: 07574fef862b9e0b06d0f66b1004738e9dcd061f

botorch/optim/optimize.py

@@ -305,14 +305,13 @@ def _optimize_batch_candidates() -> Tuple[Tensor, Tensor, List[Warning]]:
 
         # only add parameter constraints to gen_kwargs if they are specified
         # to avoid unnecessary warnings in _filter_kwargs
-        if opt_inputs.inequality_constraints is not None:
-            gen_kwargs["inequality_constraints"] = opt_inputs.inequality_constraints
-        if opt_inputs.equality_constraints is not None:
-            gen_kwargs["equality_constraints"] = opt_inputs.equality_constraints
-        if opt_inputs.nonlinear_inequality_constraints is not None:
-            gen_kwargs[
-                "nonlinear_inequality_constraints"
-            ] = opt_inputs.nonlinear_inequality_constraints
+        for constraint_name in [
+            "inequality_constraints",
+            "equality_constraints",
+            "nonlinear_inequality_constraints",
+        ]:
+            if (constraint := getattr(opt_inputs, constraint_name)) is not None:
+                gen_kwargs[constraint_name] = constraint
 
         filtered_gen_kwargs = _filter_kwargs(opt_inputs.gen_candidates, **gen_kwargs)