From c007d0bd5e6a89ad53bd4ab7c8504ed329ffb1a5 Mon Sep 17 00:00:00 2001 From: duiyipan Date: Sat, 14 Sep 2024 23:49:46 +0800 Subject: [PATCH] change import way --- expo/experimenter/autosklearn.py | 22 +++++++++------------- 1 file changed, 9 insertions(+), 13 deletions(-) diff --git a/expo/experimenter/autosklearn.py b/expo/experimenter/autosklearn.py index e8923c6bd..c6aa70920 100644 --- a/expo/experimenter/autosklearn.py +++ b/expo/experimenter/autosklearn.py @@ -15,19 +15,11 @@ class ASRunner: def __init__(self, state=None): self.state = state self.datasets = self.state["datasets_dir"] - try: - import autosklearn.classification - import autosklearn.regression - import autosklearn.metrics - - self.autosklearn = autosklearn - except ImportError: - raise ImportError( - "autosklearn not found or system not supported, please check it first" - ) def create_autosklearn_scorer(self, metric_name): - return self.autosklearn.metrics.make_scorer( + from autosklearn.metrics import make_scorer + + return make_scorer( name=metric_name, score_func=partial(custom_scorer, metric_name=metric_name) ) @@ -45,7 +37,9 @@ class ASRunner: y_train = train_data[target_col] if eval_metric == "rmse": - automl = self.autosklearn.regression.AutoSklearnRegressor( + from autosklearn.regression import AutoSklearnRegressor + + automl = AutoSklearnRegressor( time_left_for_this_task=self.time_limit, metric=self.create_autosklearn_scorer(eval_metric), memory_limit=8192, @@ -55,7 +49,9 @@ class ASRunner: n_jobs=-1, ) elif eval_metric in ["f1", "f1 weighted"]: - automl = self.autosklearn.classification.AutoSklearnClassifier( + from autosklearn.classification import AutoSklearnClassifier + + automl = AutoSklearnClassifier( time_left_for_this_task=self.time_limit, metric=self.create_autosklearn_scorer(eval_metric), memory_limit=8192,