Upgrade Optuna (#1321)

flaml/tune/searcher/suggestion.py

@@ -561,7 +561,15 @@ def __init__(
  self._space = space
 
  self._points_to_evaluate = points_to_evaluate or []
- self._evaluated_rewards = evaluated_rewards
+ # rewards should be a list of floats, not a dict
+ # After Optuna > 3.5.0, there is a check for NaN in the list "any(math.isnan(x) for x in self._values)"
+ # which will raise an error when encountering a dict
+ if evaluated_rewards is not None:
+ self._evaluated_rewards = [
+ list(item.values())[0] if isinstance(item, dict) else item for item in evaluated_rewards
+ ]
+ else:
+ self._evaluated_rewards = evaluated_rewards
 
  self._study_name = "optuna" # Fixed study name for in-memory storage
 

setup.py

@@ -65,7 +65,7 @@
  "catboost>=0.26,<1.2; python_version<'3.11'",
  "catboost>=0.26; python_version>='3.11'",
  "rgf-python",
- "optuna==2.8.0",
+ "optuna>=2.8.0,<=3.6.1",
  "openml",
  "statsmodels>=0.12.2",
  "psutil==5.8.0",
@@ -94,7 +94,7 @@
  ],
  "catboost": ["catboost>=0.26"],
  "blendsearch": [
- "optuna==2.8.0",
+ "optuna>=2.8.0,<=3.6.1",
  "packaging",
  ],
  "ray": [
@@ -153,7 +153,7 @@
  ],
  "synapse": [
  "joblibspark>=0.5.0",
- "optuna==2.8.0",
+ "optuna>=2.8.0,<=3.6.1",
  "pyspark>=3.2.0",
  ],
  "autozero": ["scikit-learn", "pandas", "packaging"],