Remove optimistix fixed point finders from API.

These happened to work in the past but not with new JAX, and would be a bad choice in general.

PiperOrigin-RevId: 629744939

bayeux/_src/optimize/optimistix.py

@@ -70,41 +70,11 @@ class BFGS(_OptimistixOptimizer):
   optimizer = "BFGS"
 
 
-class Chord(_OptimistixOptimizer):
-  name = "optimistix_chord"
-  optimizer = "Chord"
-
-
-class Dogleg(_OptimistixOptimizer):
-  name = "optimistix_dogleg"
-  optimizer = "Dogleg"
-
-
-class GaussNewton(_OptimistixOptimizer):
-  name = "optimistix_gauss_newton"
-  optimizer = "GaussNewton"
-
-
-class IndirectLevenbergMarquardt(_OptimistixOptimizer):
-  name = "optimistix_indirect_levenberg_marquardt"
-  optimizer = "IndirectLevenbergMarquardt"
-
-
-class LevenbergMarquardt(_OptimistixOptimizer):
-  name = "optimistix_levenberg_marquardt"
-  optimizer = "LevenbergMarquardt"
-
-
 class NelderMead(_OptimistixOptimizer):
   name = "optimistix_nelder_mead"
   optimizer = "NelderMead"
 
 
-class Newton(_OptimistixOptimizer):
-  name = "optimistix_newton"
-  optimizer = "Newton"
-
-
 class NonlinearCG(_OptimistixOptimizer):
   name = "optimistix_nonlinear_cg"
   optimizer = "NonlinearCG"

bayeux/_src/optimize/shared.py

@@ -51,6 +51,8 @@ def get_optimizer_kwargs(optimizer, kwargs, ignore_required=None):
         f"{','.join(optimizer_required)}. Probably file a bug, but "
         "you can try to manually supply them as keywords."
     )
+  optimizer_kwargs.update(
+      {k: kwargs[k] for k in optimizer_kwargs if k in kwargs})
   return optimizer_kwargs
 
 

bayeux/optimize/__init__.py

@@ -26,28 +26,6 @@
   from bayeux._src.optimize.jaxopt import NonlinearCG
   __all__.extend(["BFGS", "GradientDescent", "LBFGS", "NonlinearCG"])
 
-if importlib.util.find_spec("optimistix") is not None:
-  from bayeux._src.optimize.optimistix import BFGS as optimistix_BFGS
-  from bayeux._src.optimize.optimistix import Chord
-  from bayeux._src.optimize.optimistix import Dogleg
-  from bayeux._src.optimize.optimistix import GaussNewton
-  from bayeux._src.optimize.optimistix import IndirectLevenbergMarquardt
-  from bayeux._src.optimize.optimistix import LevenbergMarquardt
-  from bayeux._src.optimize.optimistix import NelderMead
-  from bayeux._src.optimize.optimistix import Newton
-  from bayeux._src.optimize.optimistix import NonlinearCG as optimistix_NonlinearCG
-
-  __all__.extend([
-      "optimistix_BFGS",
-      "Chord",
-      "Dogleg",
-      "GaussNewton",
-      "IndirectLevenbergMarquardt",
-      "LevenbergMarquardt",
-      "NelderMead",
-      "Newton",
-      "optimistix_NonlinearCG"])
-
 if importlib.util.find_spec("optax") is not None:
   from bayeux._src.optimize.optax import AdaBelief
   from bayeux._src.optimize.optax import Adafactor
@@ -92,3 +70,13 @@
       "Sm3",
       "Yogi",
       ])
+
+if importlib.util.find_spec("optimistix") is not None:
+  from bayeux._src.optimize.optimistix import BFGS as optimistix_BFGS
+  from bayeux._src.optimize.optimistix import NelderMead
+  from bayeux._src.optimize.optimistix import NonlinearCG as optimistix_NonlinearCG
+
+  __all__.extend([
+      "optimistix_BFGS",
+      "NelderMead",
+      "optimistix_NonlinearCG"])