diff --git a/external/anomaly/tasks/openvino.py b/external/anomaly/tasks/openvino.py
index f3f7be473f8..0a453285135 100644
--- a/external/anomaly/tasks/openvino.py
+++ b/external/anomaly/tasks/openvino.py
@@ -274,8 +274,7 @@ def optimize(
         # Training subset does not contain example of anomalous images.
         # Anomalous examples from all dataset used to get statistics for quantization.
         dataset = DatasetEntity(
-            items = [item for item in dataset if item.get_shapes_labels()[0].is_anomalous],
-            purpose = dataset.purpose
+            items=[item for item in dataset if item.get_shapes_labels()[0].is_anomalous], purpose=dataset.purpose
         )
 
         logger.info("Starting POT optimization.")
diff --git a/external/model-preparation-algorithm/mpa_tasks/samples/cls_cls_il_sample.py b/external/model-preparation-algorithm/mpa_tasks/samples/cls_cls_il_sample.py
index 5b576aaf6a1..c4730d4abd7 100644
--- a/external/model-preparation-algorithm/mpa_tasks/samples/cls_cls_il_sample.py
+++ b/external/model-preparation-algorithm/mpa_tasks/samples/cls_cls_il_sample.py
@@ -308,9 +308,7 @@ def main():
             dataset,
             environment.get_model_configuration(),
         )
-        openvino_task.optimize(
-            OptimizationType.POT, dataset, optimized_model, OptimizationParameters()
-        )
+        openvino_task.optimize(OptimizationType.POT, dataset, optimized_model, OptimizationParameters())
 
         logger.info("Get predictions on the validation set")
         predicted_validation_dataset = openvino_task.infer(
diff --git a/external/model-preparation-algorithm/mpa_tasks/samples/det_cls_il_sample.py b/external/model-preparation-algorithm/mpa_tasks/samples/det_cls_il_sample.py
index cebfb718134..d94972c94c8 100644
--- a/external/model-preparation-algorithm/mpa_tasks/samples/det_cls_il_sample.py
+++ b/external/model-preparation-algorithm/mpa_tasks/samples/det_cls_il_sample.py
@@ -252,9 +252,7 @@ def main(args):
             dataset,
             environment.get_model_configuration(),
         )
-        openvino_task.optimize(
-            OptimizationType.POT, dataset, optimized_model, OptimizationParameters()
-        )
+        openvino_task.optimize(OptimizationType.POT, dataset, optimized_model, OptimizationParameters())
 
         logger.info("Get predictions on the validation set")
         predicted_validation_dataset = openvino_task.infer(
diff --git a/external/model-preparation-algorithm/mpa_tasks/samples/inst_seg_cls_il_sample.py b/external/model-preparation-algorithm/mpa_tasks/samples/inst_seg_cls_il_sample.py
index 36aaee672f8..8ad9250d41b 100644
--- a/external/model-preparation-algorithm/mpa_tasks/samples/inst_seg_cls_il_sample.py
+++ b/external/model-preparation-algorithm/mpa_tasks/samples/inst_seg_cls_il_sample.py
@@ -300,9 +300,7 @@ def main(args):
             dataset,
             environment.get_model_configuration(),
         )
-        openvino_task.optimize(
-            OptimizationType.POT, dataset, optimized_model, OptimizationParameters()
-        )
+        openvino_task.optimize(OptimizationType.POT, dataset, optimized_model, OptimizationParameters())
 
         logger.info("Get predictions on the validation set")
         predicted_validation_dataset = openvino_task.infer(
diff --git a/external/model-preparation-algorithm/mpa_tasks/samples/seg_cls_il_sample.py b/external/model-preparation-algorithm/mpa_tasks/samples/seg_cls_il_sample.py
index 019919a554d..9c0f29de2cd 100644
--- a/external/model-preparation-algorithm/mpa_tasks/samples/seg_cls_il_sample.py
+++ b/external/model-preparation-algorithm/mpa_tasks/samples/seg_cls_il_sample.py
@@ -271,9 +271,7 @@ def main(args):
             dataset,
             environment.get_model_configuration(),
         )
-        openvino_task.optimize(
-            OptimizationType.POT, dataset, optimized_model, OptimizationParameters()
-        )
+        openvino_task.optimize(OptimizationType.POT, dataset, optimized_model, OptimizationParameters())
 
         logger.info("Get predictions on the validation set")
         predicted_validation_dataset = openvino_task.infer(