From 5231898894d334ef88922cec1f76da181d6c0256 Mon Sep 17 00:00:00 2001 From: =?utf8?q?J=C3=A9r=C3=B4me=20Benoit?= Date: Sun, 25 May 2025 17:19:09 +0200 Subject: [PATCH] refactor(qav3): error message cleanups MIME-Version: 1.0 Content-Type: text/plain; charset=utf8 Content-Transfer-Encoding: 8bit Signed-off-by: Jérôme Benoit --- ReforceXY/user_data/freqaimodels/ReforceXY.py | 2 +- .../user_data/freqaimodels/QuickAdapterRegressorV3.py | 10 +++++----- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/ReforceXY/user_data/freqaimodels/ReforceXY.py b/ReforceXY/user_data/freqaimodels/ReforceXY.py index ebc3b9d..0cbf427 100644 --- a/ReforceXY/user_data/freqaimodels/ReforceXY.py +++ b/ReforceXY/user_data/freqaimodels/ReforceXY.py @@ -503,7 +503,7 @@ class ReforceXY(BaseReinforcementLearningModel): ) else: raise ValueError( - f"Unsupported storage backend: {storage_backend}. Supported backends are: 'sqlite' and 'file'." + f"Unsupported storage backend: {storage_backend}. Supported backends are: 'sqlite' and 'file'" ) return storage diff --git a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py index 981f717..19fbb75 100644 --- a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py +++ b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py @@ -398,7 +398,7 @@ class QuickAdapterRegressorV3(BaseRegressionModel): self, namespace: str, study: optuna.study.Study ) -> Optional[optuna.trial.FrozenTrial]: if namespace != "label": - raise ValueError(f"Unsupported namespace: {namespace}") + raise ValueError(f"Invalid namespace: {namespace}") if not QuickAdapterRegressorV3.optuna_study_has_best_trials(study): return None @@ -414,7 +414,7 @@ class QuickAdapterRegressorV3(BaseRegressionModel): ) if label_trials_selection not in ["quantile", "chebyshev"]: raise ValueError( - f"Unsupported label trials selection method: {label_trials_selection}. Supported methods are 'quantile' and 'chebyshev'." + f"Unsupported label trials selection method: {label_trials_selection}. Supported methods are 'quantile' and 'chebyshev'" ) best_trials = [ @@ -611,7 +611,7 @@ class QuickAdapterRegressorV3(BaseRegressionModel): ) else: raise ValueError( - f"Unsupported optuna storage backend: {storage_backend}. Supported backends are 'sqlite' and 'file'." + f"Unsupported optuna storage backend: {storage_backend}. Supported backends are 'sqlite' and 'file'" ) return storage @@ -1283,7 +1283,7 @@ def smoothed_max(series: pd.Series, temperature=1.0) -> float: if data_array.size == 0: return np.nan if temperature < 0: - raise ValueError("temperature must be non-negative.") + raise ValueError("temperature must be non-negative") if np.isclose(temperature, 0): return data_array.max() return sp.special.logsumexp(temperature * data_array) / temperature @@ -1294,7 +1294,7 @@ def smoothed_min(series: pd.Series, temperature=1.0) -> float: if data_array.size == 0: return np.nan if temperature < 0: - raise ValueError("temperature must be non-negative.") + raise ValueError("temperature must be non-negative") if np.isclose(temperature, 0): return data_array.min() return -sp.special.logsumexp(-temperature * data_array) / temperature -- 2.43.0