Precision: [tensor(0.4944, device='cuda:0'), tensor(0.4875, device='cuda:0'), tensor(0.4825, device='cuda:0'), tensor(0.4875, device='cuda:0'), tensor(0.4873, device='cuda:0'), tensor(0.4815, device='cuda:0'), tensor(0.4986, device='cuda:0'), tensor(0.4741, device='cuda:0'), tensor(0.4810, device='cuda:0'), tensor(0.4818, device='cuda:0')]

Output distance: [tensor(5.3174, device='cuda:0'), tensor(5.3311, device='cuda:0'), tensor(5.3410, device='cuda:0'), tensor(5.3311, device='cuda:0'), tensor(5.3316, device='cuda:0'), tensor(5.3431, device='cuda:0'), tensor(5.3090, device='cuda:0'), tensor(5.3578, device='cuda:0'), tensor(5.3442, device='cuda:0'), tensor(5.3426, device='cuda:0')]

Prediction loss: [tensor(15455805., device='cuda:0'), tensor(16975762., device='cuda:0'), tensor(17216280., device='cuda:0'), tensor(23396364., device='cuda:0'), tensor(9649217., device='cuda:0'), tensor(22168728., device='cuda:0'), tensor(18701128., device='cuda:0'), tensor(18072878., device='cuda:0'), tensor(13200698., device='cuda:0'), tensor(17260674., device='cuda:0')]

Others: [{'iter_num': 9, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]

Compressed training loss: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=1, microseconds=75488), datetime.timedelta(seconds=1, microseconds=64535), datetime.timedelta(seconds=1, microseconds=49597), datetime.timedelta(seconds=1, microseconds=78477), datetime.timedelta(seconds=1, microseconds=52584), datetime.timedelta(seconds=1, microseconds=27690), datetime.timedelta(seconds=1, microseconds=52584), datetime.timedelta(seconds=1, microseconds=41631), datetime.timedelta(seconds=1, microseconds=119305), datetime.timedelta(seconds=1, microseconds=59555)]

Phi time: [datetime.timedelta(microseconds=203147), datetime.timedelta(microseconds=219079), datetime.timedelta(microseconds=211114), datetime.timedelta(microseconds=195178), datetime.timedelta(microseconds=209121), datetime.timedelta(microseconds=216092), datetime.timedelta(microseconds=192194), datetime.timedelta(microseconds=201157), datetime.timedelta(microseconds=208124), datetime.timedelta(microseconds=207131)]

