Api fixes

aimclub · Jan 26, 2024 · 66ee030 · 66ee030
1 parent af707e1
commit 66ee030
Showing 1 changed file with 9 additions and 16 deletions.
diff --git a/fedot_ind/api/main.py b/fedot_ind/api/main.py
@@ -67,6 +67,7 @@ def __init__(self, **kwargs):
         self.preprocessing = kwargs.get('industrial_preprocessing', False)
         self.backend_method = kwargs.get('backend', 'cpu')
         self.RAF_workers = kwargs.get('RAF_workers', None)
+
         if self.output_folder is None:
             self.output_folder = default_path_to_save_results
             Path(self.output_folder).mkdir(parents=True, exist_ok=True)
@@ -89,9 +90,11 @@ def __init__(self, **kwargs):
         self.predicted_labels = None
         self.predicted_probs = None
         self.predict_data = None
-        self.config_dict = None
-        self.ensemble_solver = None
         self.config_dict = kwargs
+        self.config_dict['available_operations'] = kwargs.get('available_operations',
+                                                              default_industrial_availiable_operation(
+                                                                  self.config_dict['problem']))
+        self.config_dict['optimizer'] = kwargs.get('optimizer', IndustrialEvoOptimizer)
         self.__init_experiment_setup()
 
     def __init_experiment_setup(self):
@@ -101,9 +104,6 @@ def __init_experiment_setup(self):
         backend_method_current, backend_scipy_current = BackendMethods(self.backend_method).backend
         globals()['backend_methods'] = backend_method_current
         globals()['backend_scipy'] = backend_scipy_current
-        self.config_dict['available_operations'] = default_industrial_availiable_operation(self.config_dict['problem'])
-
-        self.config_dict['optimizer'] = IndustrialEvoOptimizer
 
     def __init_solver(self):
         self.logger.info('Initialising Industrial Repository')
@@ -132,13 +132,9 @@ def _preprocessing_strategy(self, input_data):
             batch_timeout = round(self.config_dict['timeout'] / FEDOT_WORKER_TIMEOUT_PARTITION)
             self.config_dict['timeout'] = batch_timeout
             self.logger.info(f'Batch_size - {batch_size}. Number of batches - {self.RAF_workers}')
-            self.ensemble_solver = RAFensembler(composing_params=self.config_dict, n_splits=self.RAF_workers,
-                                                batch_size=batch_size)
-            self.logger.info(f'Number of AutoMl models in ensemble - {self.ensemble_solver.n_splits}')
-            self.ensemble_solver.fit(input_data)
-            self.solver = self.ensemble_solver
-        else:
-            self.preprocessing = False
+            self.solver = RAFensembler(composing_params=self.config_dict, n_splits=self.RAF_workers,
+                                       batch_size=batch_size)
+            self.logger.info(f'Number of AutoMl models in ensemble - {self.solver.n_splits}')
 
     def fit(self,
             input_data,
@@ -161,10 +157,7 @@ def fit(self,
         self.solver = self.__init_solver()
         if self.preprocessing:
             self._preprocessing_strategy(input_data)
-            fitted_pipeline = self.ensemble_solver
-        else:
-            fitted_pipeline = self.solver.fit(input_data)
-        return fitted_pipeline
+        return self.solver.fit(input_data)
 
     def predict(self,
                 predict_data,