diff --git a/nncf/quantization/algorithms/min_max/onnx_backend.py b/nncf/quantization/algorithms/min_max/onnx_backend.py
index 276defe2b0f..4e0d659f849 100644
--- a/nncf/quantization/algorithms/min_max/onnx_backend.py
+++ b/nncf/quantization/algorithms/min_max/onnx_backend.py
@@ -42,7 +42,8 @@
 from nncf.quantization.algorithms.min_max.backend import MinMaxAlgoBackend
 from nncf.quantization.fake_quantize import FakeConvertParameters
 from nncf.quantization.fake_quantize import FakeQuantizeParameters
-from nncf.quantization.range_estimator import RangeEstimatorParameters, AggregatorType
+from nncf.quantization.range_estimator import AggregatorType
+from nncf.quantization.range_estimator import RangeEstimatorParameters
 
 
 class ONNXMinMaxAlgoBackend(MinMaxAlgoBackend):
@@ -214,7 +215,7 @@ def get_statistic_collector(
             kwargs = {
                 "num_samples": num_samples,
                 "aggregation_axes": aggregation_axes,
-                "tensor_processor": ONNXNNCFCollectorTensorProcessor
+                "tensor_processor": ONNXNNCFCollectorTensorProcessor,
             }
             if params.aggregator_type == AggregatorType.MEAN_NO_OUTLIERS:
                 kwargs.update({"quantile": params.quantile_outlier_prob})
diff --git a/nncf/quantization/algorithms/min_max/openvino_backend.py b/nncf/quantization/algorithms/min_max/openvino_backend.py
index dfed19632a6..8407462dfb3 100644
--- a/nncf/quantization/algorithms/min_max/openvino_backend.py
+++ b/nncf/quantization/algorithms/min_max/openvino_backend.py
@@ -199,7 +199,7 @@ def get_statistic_collector(
             kwargs = {
                 "num_samples": num_samples,
                 "aggregation_axes": aggregation_axes,
-                "tensor_processor": OVNNCFCollectorTensorProcessor
+                "tensor_processor": OVNNCFCollectorTensorProcessor,
             }
             if params.aggregator_type == AggregatorType.MEAN_NO_OUTLIERS:
                 kwargs.update({"quantile": params.quantile_outlier_prob})
diff --git a/nncf/quantization/algorithms/min_max/torch_backend.py b/nncf/quantization/algorithms/min_max/torch_backend.py
index 60dd7ee311b..8e8367af62c 100644
--- a/nncf/quantization/algorithms/min_max/torch_backend.py
+++ b/nncf/quantization/algorithms/min_max/torch_backend.py
@@ -33,7 +33,8 @@
 from nncf.quantization.algorithms.min_max.backend import MinMaxAlgoBackend
 from nncf.quantization.fake_quantize import FakeConvertParameters
 from nncf.quantization.fake_quantize import FakeQuantizeParameters
-from nncf.quantization.range_estimator import RangeEstimatorParameters, AggregatorType
+from nncf.quantization.range_estimator import AggregatorType
+from nncf.quantization.range_estimator import RangeEstimatorParameters
 from nncf.torch.graph.graph import PTNNCFGraph
 from nncf.torch.graph.graph import PTTargetPoint
 from nncf.torch.graph.transformations.command_creation import create_quantizer_insertion_command
@@ -198,7 +199,7 @@ def get_statistic_collector(
             kwargs = {
                 "num_samples": num_samples,
                 "aggregation_axes": aggregation_axes,
-                "tensor_processor": PTNNCFCollectorTensorProcessor
+                "tensor_processor": PTNNCFCollectorTensorProcessor,
             }
             if params.aggregator_type == AggregatorType.MEAN_NO_OUTLIERS:
                 kwargs.update({"quantile": params.quantile_outlier_prob})