hotfix: go for FeaturesType instead of InputData in a pipeline tuning (…

…#1311)
aimclub · Jul 24, 2024 · d33ca9e · d33ca9e
1 parent a7e4243
commit d33ca9e
Showing 1 changed file with 8 additions and 3 deletions.
diff --git a/fedot/api/main.py b/fedot/api/main.py
@@ -202,7 +202,8 @@ def fit(self,
         return self.current_pipeline
 
     def tune(self,
-             input_data: Optional[InputData] = None,
+             input_data: Optional[FeaturesType] = None,
+             target: TargetType = 'target',
              metric_name: Optional[Union[str, MetricCallable]] = None,
              iterations: int = DEFAULT_TUNING_ITERATIONS_NUMBER,
              timeout: Optional[float] = None,
@@ -212,7 +213,8 @@ def tune(self,
         """Method for hyperparameters tuning of current pipeline
 
         Args:
-            input_data: data for tuning pipeline.
+            input_data: data for tuning pipeline in one of the supported formats.
+            target: data target values in one of the supported target formats.
             metric_name: name of metric for quality tuning.
             iterations: numbers of tuning iterations.
             timeout: time for tuning (in minutes). If ``None`` or ``-1`` means tuning until max iteration reach.
@@ -227,7 +229,10 @@ def tune(self,
             raise ValueError(NOT_FITTED_ERR_MSG)
 
         with fedot_composer_timer.launch_tuning('post'):
-            input_data = input_data or self.train_data
+            if input_data is None:
+                input_data = self.train_data
+            else:
+                input_data = self.data_processor.define_data(features=input_data, target=target, is_predict=False)
             cv_folds = cv_folds or self.params.get('cv_folds')
             n_jobs = n_jobs or self.params.n_jobs