Precision: [tensor(0.3568, device='cuda:0'), tensor(0.3528, device='cuda:0'), tensor(0.3604, device='cuda:0'), tensor(0.3534, device='cuda:0'), tensor(0.3598, device='cuda:0'), tensor(0.3616, device='cuda:0'), tensor(0.3519, device='cuda:0'), tensor(0.3538, device='cuda:0'), tensor(0.3583, device='cuda:0'), tensor(0.3619, device='cuda:0')]

Output distance: [tensor(19.8845, device='cuda:0'), tensor(19.9087, device='cuda:0'), tensor(19.8631, device='cuda:0'), tensor(19.9048, device='cuda:0'), tensor(19.8667, device='cuda:0'), tensor(19.8558, device='cuda:0'), tensor(19.9138, device='cuda:0'), tensor(19.9024, device='cuda:0'), tensor(19.8755, device='cuda:0'), tensor(19.8543, device='cuda:0')]

Prediction loss: [tensor(104.1911, device='cuda:0'), tensor(103.8298, device='cuda:0'), tensor(104.6887, device='cuda:0'), tensor(104.4188, device='cuda:0'), tensor(103.7210, device='cuda:0'), tensor(104.9126, device='cuda:0'), tensor(103.7449, device='cuda:0'), tensor(105.0704, device='cuda:0'), tensor(104.7292, device='cuda:0'), tensor(105.0732, device='cuda:0')]

Others: [{'iter_num': 15, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 15, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 17, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 15, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(19848, 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=733381), datetime.timedelta(seconds=2, microseconds=738502), datetime.timedelta(seconds=2, microseconds=662461), datetime.timedelta(seconds=2, microseconds=619561), datetime.timedelta(seconds=2, microseconds=677888), datetime.timedelta(seconds=2, microseconds=830173), datetime.timedelta(seconds=2, microseconds=652451), datetime.timedelta(seconds=2, microseconds=635793), datetime.timedelta(seconds=2, microseconds=729924), datetime.timedelta(seconds=2, microseconds=643300)]

Phi time: [datetime.timedelta(seconds=4, microseconds=440122), datetime.timedelta(seconds=4, microseconds=422705), datetime.timedelta(seconds=4, microseconds=456344), datetime.timedelta(seconds=4, microseconds=446927), datetime.timedelta(seconds=4, microseconds=458611), datetime.timedelta(seconds=4, microseconds=437578), datetime.timedelta(seconds=4, microseconds=408917), datetime.timedelta(seconds=4, microseconds=449005), datetime.timedelta(seconds=4, microseconds=443369), datetime.timedelta(seconds=4, microseconds=443151)]

