diff --git a/tests/unit_tests/test_on_gpu.py b/tests/unit_tests/test_on_gpu.py
index 2aecb5e8..ea2001ae 100644
--- a/tests/unit_tests/test_on_gpu.py
+++ b/tests/unit_tests/test_on_gpu.py
@@ -1,7 +1,6 @@
 import os
 
 import cv2
-import pandas as pd
 from dedocutils.data_structures import BBox
 
 from dedoc.data_structures.line_metadata import LineMetadata
@@ -24,11 +23,11 @@ def test_line_type_classifier(self) -> None:
         Loads AbstractPickledLineTypeClassifier
         """
         law_extractor = LawStructureExtractor(config=self.config)
-
-        lines = [LineWithMeta("     З А К О Н", metadata=LineMetadata(page_id=0, line_id=0)),
-                 LineWithMeta("\n", metadata=LineMetadata(page_id=0, line_id=1)),
-                 LineWithMeta("     ГОРОДА МОСКВЫ", metadata=LineMetadata(page_id=0, line_id=2))]
-        features = law_extractor.classifier.feature_extractor.transform([lines])
+        lines = [
+            LineWithMeta("     З А К О Н", metadata=LineMetadata(page_id=0, line_id=0)),
+            LineWithMeta("\n", metadata=LineMetadata(page_id=0, line_id=1)),
+            LineWithMeta("     ГОРОДА МОСКВЫ", metadata=LineMetadata(page_id=0, line_id=2))
+        ]
         predictions = law_extractor.classifier.predict(lines)
         self.assertListEqual(predictions, ["header", "header", "cellar"])
 
@@ -56,8 +55,10 @@ def test_scan_paragraph_classifier_extractor(self) -> None:
         bbox2 = BBox(x_top_left=50, y_top_left=50, width=100, height=20)
         location = Location(page_number=1, bbox=bbox)
         location2 = Location(page_number=1, bbox=bbox2)
-        lines = [LineWithLocation(line="Example line", metadata=metadata, annotations=[], location=location),
-                 LineWithLocation(line="Example line 2", metadata=metadata2, annotations=[], location=location2)]
+        lines = [
+            LineWithLocation(line="Example line", metadata=metadata, annotations=[], location=location),
+            LineWithLocation(line="Example line 2", metadata=metadata2, annotations=[], location=location2)
+        ]
         data = classify_lines_with_location.feature_extractor.transform([lines])
 
         if any((data[col].isna().all() for col in data.columns)):
@@ -67,6 +68,3 @@ def test_scan_paragraph_classifier_extractor(self) -> None:
 
         self.assertEqual(labels[0], "paragraph")
         self.assertEqual(labels[1], "paragraph")
-
-
-