@@ -1489,22 +1489,22 @@ def test_empty_distance_iou_inputs(self, dtype, device):
14891489 assert_empty_loss (ops .distance_box_iou_loss , dtype , device )
14901490
14911491class TestLastLevelMaxPool2d :
1492- def _generate_fpn_feature_maps (self , ** kwargs ):
1492+ def _generate_fpn_feature_maps (self , ** kwargs ) -> Tuple [ List [ Tensor ], List [ str ]] :
14931493 feature_maps = [torch .rand (16 , 3 , 240 , 320 ),
14941494 torch .rand (16 , 3 , 120 , 160 ),
14951495 torch .rand (16 , 3 , 60 , 80 ),
14961496 torch .rand (16 , 3 , 30 , 40 )]
14971497 names = ['0' , '1' , '2' , '3' ]
1498+
14981499 return feature_maps , names
14991500
1500- def test_lastlevel_maxpool2d (self ):
1501-
1501+ def test_lastlevel_maxpool2d (self ) -> None :
15021502 feature_maps , names = self ._generate_fpn_feature_maps ()
15031503 extra_blocks = ops .feature_pyramid_network .LastLevelMaxPool ()
15041504
15051505 # skip what FPN really dit, simply copy results from feature maps here.
15061506 results = feature_maps
1507-
1507+
15081508 expected_pooled_featuremap = F .max_pool2d (feature_maps [- 1 ], 2 , 2 , 0 )
15091509 results , names = extra_blocks (results , feature_maps , names )
15101510
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