Raise specific Error type when duplicate point is registered, make log loading idempotent

Author: till-m

bayes_opt/target_space.py

@@ -1,6 +1,5 @@
 import numpy as np
-from .util import ensure_rng
-from .constraint import ConstraintModel
+from .util import ensure_rng, NotUniqueError
 
 
 def _hashable(x):
@@ -177,7 +176,7 @@ def register(self, params, target, constraint_value=None):
         """
         x = self._as_array(params)
         if x in self:
-            raise KeyError('Data point {} is not unique'.format(x))
+            raise NotUniqueError('Data point {} is not unique'.format(x))
 
 
         self._params = np.concatenate([self._params, x.reshape(1, -1)])

bayes_opt/util.py

@@ -158,6 +158,11 @@ def _poi(x, gp, y_max, xi):
         return norm.cdf(z)
 
 
+class NotUniqueError(Exception):
+    """A point is non-unique."""
+    pass
+
+
 def load_logs(optimizer, logs):
     """Load previous ...
 
@@ -176,11 +181,14 @@ def load_logs(optimizer, logs):
                     break
 
                 iteration = json.loads(iteration)
-                optimizer.register(
-                    params=iteration["params"],
-                    target=iteration["target"],
-                    constraint_value=iteration["constraint"] if optimizer.is_constrained else None
-                )
+                try:
+                    optimizer.register(
+                        params=iteration["params"],
+                        target=iteration["target"],
+                        constraint_value=iteration["constraint"] if optimizer.is_constrained else None
+                    )
+                except NotUniqueError:
+                    continue
 
     return optimizer
 

tests/test_bayesian_optimization.py

@@ -4,6 +4,7 @@
 from bayes_opt import BayesianOptimization
 from bayes_opt.logger import ScreenLogger
 from bayes_opt.event import Events, DEFAULT_EVENTS
+from bayes_opt.util import NotUniqueError
 
 
 def target_func(**kwargs):
@@ -26,9 +27,9 @@ def test_register():
     assert len(optimizer.res) == 2
     assert len(optimizer.space) == 2
 
-    with pytest.raises(KeyError):
+    with pytest.raises(NotUniqueError):
         optimizer.register(params={"p1": 1, "p2": 2}, target=3)
-    with pytest.raises(KeyError):
+    with pytest.raises(NotUniqueError):
         optimizer.register(params={"p1": 5, "p2": 4}, target=9)
 
 

tests/test_target_space.py

@@ -1,6 +1,7 @@
 import pytest
 import numpy as np
 from bayes_opt.target_space import TargetSpace
+from bayes_opt.util import NotUniqueError
 
 
 def target_func(**kwargs):
@@ -87,9 +88,9 @@ def test_register():
     assert all(space.params[1] == np.array([5, 4]))
     assert all(space.target == np.array([3, 9]))
 
-    with pytest.raises(KeyError):
+    with pytest.raises(NotUniqueError):
         space.register(params={"p1": 1, "p2": 2}, target=3)
-    with pytest.raises(KeyError):
+    with pytest.raises(NotUniqueError):
         space.register(params={"p1": 5, "p2": 4}, target=9)