Precision: [tensor(0.6359, device='cuda:0'), tensor(0.6240, device='cuda:0'), tensor(0.6235, device='cuda:0'), tensor(0.6353, device='cuda:0'), tensor(0.6198, device='cuda:0'), tensor(0.6275, device='cuda:0'), tensor(0.6290, device='cuda:0'), tensor(0.6353, device='cuda:0'), tensor(0.6356, device='cuda:0'), tensor(0.6185, device='cuda:0')]

Output distance: [tensor(5.0344, device='cuda:0'), tensor(5.0580, device='cuda:0'), tensor(5.0591, device='cuda:0'), tensor(5.0354, device='cuda:0'), tensor(5.0664, device='cuda:0'), tensor(5.0512, device='cuda:0'), tensor(5.0480, device='cuda:0'), tensor(5.0354, device='cuda:0'), tensor(5.0349, device='cuda:0'), tensor(5.0690, device='cuda:0')]

Prediction loss: [tensor(19913906., device='cuda:0'), tensor(18553738., device='cuda:0'), tensor(18455170., device='cuda:0'), tensor(17417996., device='cuda:0'), tensor(16768616., device='cuda:0'), tensor(18728626., device='cuda:0'), tensor(18110336., device='cuda:0'), tensor(16477503., device='cuda:0'), tensor(19995514., device='cuda:0'), tensor(19927064., device='cuda:0')]

Others: [{'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]

Compressed training loss: [tensor(40797.1992, device='cuda:0'), tensor(40803.2461, device='cuda:0'), tensor(40942.3086, device='cuda:0'), tensor(40887.2266, device='cuda:0'), tensor(40906.7422, device='cuda:0'), tensor(40881.4336, device='cuda:0'), tensor(40429.9219, device='cuda:0'), tensor(40788.2383, device='cuda:0'), tensor(40883.8281, device='cuda:0'), tensor(40922.7422, device='cuda:0')]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=23, microseconds=177689), datetime.timedelta(seconds=23, microseconds=486180), datetime.timedelta(seconds=23, microseconds=466173), datetime.timedelta(seconds=23, microseconds=422188), datetime.timedelta(seconds=23, microseconds=473243), datetime.timedelta(seconds=23, microseconds=611521), datetime.timedelta(seconds=23, microseconds=397654), datetime.timedelta(seconds=23, microseconds=251386), datetime.timedelta(seconds=23, microseconds=448519), datetime.timedelta(seconds=23, microseconds=303567)]

Phi time: [datetime.timedelta(microseconds=191937), datetime.timedelta(microseconds=392229), datetime.timedelta(microseconds=398382), datetime.timedelta(microseconds=416662), datetime.timedelta(microseconds=272865), datetime.timedelta(microseconds=358953), datetime.timedelta(microseconds=299911), datetime.timedelta(microseconds=296118), datetime.timedelta(microseconds=426252), datetime.timedelta(microseconds=243063)]

