Update aggregator.py

nncf/common/tensor_statistics/aggregator.py

@@ -17,13 +17,13 @@
 from nncf.common import factory
 from nncf.common.graph.graph import NNCFGraph
 from nncf.common.graph.transformations.layout import TransformationLayout
+from nncf.common.logging import nncf_logger
 from nncf.common.logging.track_progress import track
 from nncf.common.tensor import NNCFTensor
 from nncf.common.tensor_statistics.statistic_point import StatisticPointsContainer
 from nncf.data.dataset import DataItem
 from nncf.data.dataset import Dataset
 from nncf.data.dataset import ModelInput
-from nncf.common.logging import nncf_logger
 
 TensorType = TypeVar("TensorType")
 TModel = TypeVar("TModel")
@@ -69,11 +69,8 @@ def collect_statistics(self, model: TModel, graph: NNCFGraph) -> None:
         transformation_layout = self._get_transformation_layout_extra_outputs(merged_statistics)
         model_with_outputs: TModel = model_transformer.transform(transformation_layout)
         engine = factory.EngineFactory.create(model_with_outputs)
-
         iterations_number = self._get_iterations_number()
-
         processed_samples = 0
-
         for input_data in track(  # type: ignore
             islice(self.dataset.get_inference_data(), iterations_number),
             total=iterations_number,
@@ -83,10 +80,8 @@ def collect_statistics(self, model: TModel, graph: NNCFGraph) -> None:
             processed_outputs = self._process_outputs(outputs)
             self._register_statistics(processed_outputs, merged_statistics)
             processed_samples += 1
-
         if processed_samples == 0:
             raise nncf.ValidationError(EMPTY_DATASET_ERROR)
-
         if self.stat_subset_size is not None and self.stat_subset_size > processed_samples:
             nncf_logger.warning(
                 f"Dataset contains only {processed_samples} samples, "