Precision: [tensor(0.5367, device='cuda:0'), tensor(0.5240, device='cuda:0'), tensor(0.5116, device='cuda:0'), tensor(0.5240, device='cuda:0'), tensor(0.5130, device='cuda:0'), tensor(0.5160, device='cuda:0'), tensor(0.5228, device='cuda:0'), tensor(0.5487, device='cuda:0'), tensor(0.5289, device='cuda:0'), tensor(0.5343, device='cuda:0')]

Output distance: [tensor(18.9519, device='cuda:0'), tensor(18.9773, device='cuda:0'), tensor(19.0021, device='cuda:0'), tensor(18.9773, device='cuda:0'), tensor(18.9994, device='cuda:0'), tensor(18.9933, device='cuda:0'), tensor(18.9797, device='cuda:0'), tensor(18.9281, device='cuda:0'), tensor(18.9677, device='cuda:0'), tensor(18.9568, device='cuda:0')]

Prediction loss: [tensor(108.1237, device='cuda:0'), tensor(108.9605, device='cuda:0'), tensor(108.9033, device='cuda:0'), tensor(109.0601, device='cuda:0'), tensor(109.1196, device='cuda:0'), tensor(109.2281, device='cuda:0'), tensor(107.9273, device='cuda:0'), tensor(109.4001, device='cuda:0'), tensor(108.9484, device='cuda:0'), tensor(108.0587, device='cuda:0')]

Others: [{'iter_num': 11, 'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}]

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

Training loss: 0

Prediction time: [datetime.timedelta(seconds=2, microseconds=573133), datetime.timedelta(seconds=2, microseconds=619046), datetime.timedelta(seconds=2, microseconds=649985), datetime.timedelta(seconds=2, microseconds=576640), datetime.timedelta(seconds=2, microseconds=594996), datetime.timedelta(seconds=2, microseconds=600038), datetime.timedelta(seconds=2, microseconds=604916), datetime.timedelta(seconds=2, microseconds=599961), datetime.timedelta(seconds=2, microseconds=599988), datetime.timedelta(seconds=2, microseconds=626215)]

Phi time: [datetime.timedelta(seconds=4, microseconds=657877), datetime.timedelta(seconds=4, microseconds=654547), datetime.timedelta(seconds=4, microseconds=618734), datetime.timedelta(seconds=4, microseconds=647072), datetime.timedelta(seconds=4, microseconds=717914), datetime.timedelta(seconds=4, microseconds=650548), datetime.timedelta(seconds=4, microseconds=649229), datetime.timedelta(seconds=4, microseconds=649806), datetime.timedelta(seconds=4, microseconds=631793), datetime.timedelta(seconds=4, microseconds=646903)]

