finish pylint

research/object_detection/matchers/hungarian_matcher.py

@@ -58,6 +58,6 @@ class HungarianBipartiteMatcher(matcher.Matcher):
       return tf.numpy_function(numpy_matching, inputs, Tout=[tf.int32])
 
     matching_result = tf.autograph.experimental.do_not_convert(
-                        numpy_wrapper)([distance_matrix])
-    
+        numpy_wrapper)([distance_matrix])
+
     return tf.reshape(matching_result, [-1])

research/object_detection/matchers/hungarian_matcher_tf2_test.py

@@ -26,7 +26,7 @@ if tf_version.is_tf2():
 
 
 @unittest.skipIf(tf_version.is_tf1(), 'Skipping TF2.X only test.')
-class GreedyBipartiteMatcherTest(test_case.TestCase):
+class HungarianBipartiteMatcherTest(test_case.TestCase):
 
   def test_get_expected_matches_when_all_rows_are_valid(self):
     similarity_matrix = np.array([[0.50, 0.1, 0.8], [0.15, 0.2, 0.3]],
@@ -37,9 +37,9 @@ class GreedyBipartiteMatcherTest(test_case.TestCase):
     matcher = hungarian_matcher.HungarianBipartiteMatcher()
     match_results_out = matcher.match(similarity_matrix, valid_rows=valid_rows)
 
-    self.assertAllEqual(match_results_out._match_results.numpy(), expected_match_results)
+    self.assertAllEqual(match_results_out._match_results.numpy(),
+                        expected_match_results)
 
-  
   def test_get_expected_matches_with_all_rows_be_default(self):
     similarity_matrix = np.array([[0.50, 0.1, 0.8], [0.15, 0.2, 0.3]],
                                  dtype=np.float32)
@@ -47,41 +47,45 @@ class GreedyBipartiteMatcherTest(test_case.TestCase):
 
     matcher = hungarian_matcher.HungarianBipartiteMatcher()
     match_results_out = matcher.match(similarity_matrix)
-    
-    self.assertAllEqual(match_results_out._match_results.numpy(), expected_match_results)
+
+    self.assertAllEqual(match_results_out._match_results.numpy(),
+                        expected_match_results)
 
   def test_get_no_matches_with_zero_valid_rows(self):
     similarity_matrix = np.array([[0.50, 0.1, 0.8], [0.15, 0.2, 0.3]],
                                  dtype=np.float32)
     valid_rows = np.zeros([2], dtype=np.bool)
     expected_match_results = [-1, -1, -1]
-    
+
     matcher = hungarian_matcher.HungarianBipartiteMatcher()
     match_results_out = matcher.match(similarity_matrix, valid_rows=valid_rows)
-    
-    self.assertAllEqual(match_results_out._match_results.numpy(), expected_match_results)
+
+    self.assertAllEqual(match_results_out._match_results.numpy(),
+                        expected_match_results)
 
   def test_get_expected_matches_with_only_one_valid_row(self):
     similarity_matrix = np.array([[0.50, 0.1, 0.8], [0.15, 0.2, 0.3]],
                                  dtype=np.float32)
     valid_rows = np.array([True, False], dtype=np.bool)
     expected_match_results = [-1, -1, 0]
-    
+
     matcher = hungarian_matcher.HungarianBipartiteMatcher()
     match_results_out = matcher.match(similarity_matrix, valid_rows=valid_rows)
-    
-    self.assertAllEqual(match_results_out._match_results.numpy(), expected_match_results)
+
+    self.assertAllEqual(match_results_out._match_results.numpy(),
+                        expected_match_results)
 
   def test_get_expected_matches_with_only_one_valid_row_at_bottom(self):
     similarity_matrix = np.array([[0.15, 0.2, 0.3], [0.50, 0.1, 0.8]],
                                  dtype=np.float32)
     valid_rows = np.array([False, True], dtype=np.bool)
     expected_match_results = [-1, -1, 0]
-    
+
     matcher = hungarian_matcher.HungarianBipartiteMatcher()
     match_results_out = matcher.match(similarity_matrix, valid_rows=valid_rows)
-    
-    self.assertAllEqual(match_results_out._match_results.numpy(), expected_match_results)
+
+    self.assertAllEqual(match_results_out._match_results.numpy(),
+                        expected_match_results)
 
 if __name__ == '__main__':
   tf.test.main()