Code review fixes

Author: nicl-nno

examples/advanced/customization/image_classification_with_custom_models.py

@@ -17,7 +17,6 @@
 from fedot.core.pipelines.node import PipelineNode
 from fedot.core.pipelines.pipeline import Pipeline
 from fedot.core.pipelines.pipeline_composer_requirements import PipelineComposerRequirements
-from fedot.core.pipelines.tuning.hyperparams import ParametersChanger
 from fedot.core.pipelines.tuning.search_space import PipelineSearchSpace
 from fedot.core.pipelines.tuning.tuner_builder import TunerBuilder
 from fedot.core.repository.metrics_repository import ClassificationMetricsEnum, ComplexityMetricsEnum
@@ -113,7 +112,7 @@ def run_image_classification_automl(train_dataset: tuple,
     pop_size = 5
 
     # search space for hyper-parametric mutation
-    ParametersChanger.custom_search_space = custom_search_space
+    PipelineSearchSpace.pre_defined_custom_search_space = custom_search_space
 
     params = GPAlgorithmParameters(
         selection_types=[SelectionTypesEnum.spea2],

examples/advanced/customization/implementations/cnn_impls.py

@@ -135,9 +135,9 @@ def fit(self, train_data):
         self.model = cnn_model_dict[self.params.get('architecture_type')](input_shape=train_data.features.shape[1:4],
                                                                           num_classes=len(self.classes))
 
-        # self.model = fit_cnn(train_data=train_data, model=self.model, epochs=self.params.get('epochs'),
-        #                      batch_size=self.params.get('batch_size'),
-        #                      optimizer_params=self.params.get('optimizer_parameters'), logger=self.params.get('log'))
+        self.model = fit_cnn(train_data=train_data, model=self.model, epochs=self.params.get('epochs'),
+                             batch_size=self.params.get('batch_size'),
+                             optimizer_params=self.params.get('optimizer_parameters'), logger=self.params.get('log'))
         return self.model
 
     def predict(self, input_data):

examples/simple/classification/image_classifcation_problem.py renamed to examples/simple/classification/image_classification_problem.py

@@ -45,7 +45,7 @@ def propose_change(self, node: OptNode, possible_operations: List[str]) -> List[
             candidates = set.intersection({'lagged', 'sparse_lagged'}, set(possible_operations))
 
         if 'cnn' in operation_id:
-            candidates = [c for c in candidates if 'cnn' in candidates]
+            candidates = [cand for cand in candidates if 'cnn' in cand]
 
         if operation_id in candidates:
             # the change to the same node is not meaningful

fedot/core/pipelines/pipeline_advisor.py

@@ -11,13 +11,10 @@
 class ParametersChanger:
     """
     Class for the hyperparameters changing in the operation
-
     :param operation_name: name of operation to get hyperparameters for
     :param current_params: current parameters value
     """
 
-    custom_search_space = None
-
     def __init__(self, operation_name, current_params):
         self.operation_name = operation_name
         self.current_params = current_params
@@ -28,7 +25,7 @@ def get_new_operation_params(self):
 
         # Get available parameters for operation
         params_list = \
-            PipelineSearchSpace(ParametersChanger.custom_search_space).get_parameters_for_operation(self.operation_name)
+            PipelineSearchSpace().get_parameters_for_operation(self.operation_name)
 
         if not params_list:
             params_dict = None

fedot/core/pipelines/tuning/hyperparams.py

@@ -9,17 +9,20 @@
 
 class PipelineSearchSpace(SearchSpace):
     """
-    Class for extracting searching space
+    Class for extracting searching space for hyperparameters of pipeline
 
     :param custom_search_space: dictionary of dictionaries of tuples (hyperopt expression (e.g. hp.choice), *params)
      for applying custom hyperparameters search space
     :param replace_default_search_space: whether replace default dictionary (False) or append it (True)
     """
 
+    pre_defined_custom_search_space = None  # workaround to modify search space globally
+
     def __init__(self,
                  custom_search_space: Optional[OperationParametersMapping] = None,
                  replace_default_search_space: bool = False):
-        self.custom_search_space = custom_search_space
+        self.custom_search_space = custom_search_space if PipelineSearchSpace.pre_defined_custom_search_space is None \
+            else PipelineSearchSpace.pre_defined_custom_search_space
         self.replace_default_search_space = replace_default_search_space
         parameters_per_operation = self.get_parameters_dict()
         super().__init__(parameters_per_operation)

fedot/core/pipelines/tuning/search_space.py

@@ -4,7 +4,7 @@
 from sklearn.datasets import load_iris, make_classification
 from sklearn.metrics import roc_auc_score as roc_auc
 
-from examples.simple.classification.image_classifcation_problem import run_image_classification_problem
+from examples.simple.classification.image_classification_problem import run_image_classification_problem
 from fedot.core.data.data import InputData
 from fedot.core.data.data_split import train_test_data_setup
 from fedot.core.data.supplementary_data import SupplementaryData