Precision: [tensor(0.4348, device='cuda:0'), tensor(0.4285, device='cuda:0'), tensor(0.4245, device='cuda:0'), tensor(0.4320, device='cuda:0'), tensor(0.4319, device='cuda:0'), tensor(0.4294, device='cuda:0'), tensor(0.4295, device='cuda:0'), tensor(0.4264, device='cuda:0'), tensor(0.4339, device='cuda:0'), tensor(0.4273, device='cuda:0')]

Output distance: [tensor(5.6976, device='cuda:0'), tensor(5.7348, device='cuda:0'), tensor(5.7590, device='cuda:0'), tensor(5.7138, device='cuda:0'), tensor(5.7149, device='cuda:0'), tensor(5.7296, device='cuda:0'), tensor(5.7291, device='cuda:0'), tensor(5.7480, device='cuda:0'), tensor(5.7028, device='cuda:0'), tensor(5.7422, device='cuda:0')]

Prediction loss: [tensor(17789174., device='cuda:0'), tensor(16636684., device='cuda:0'), tensor(17948114., device='cuda:0'), tensor(16924968., device='cuda:0'), tensor(18671470., device='cuda:0'), tensor(17817130., device='cuda:0'), tensor(22407432., device='cuda:0'), tensor(19438010., device='cuda:0'), tensor(21482024., device='cuda:0'), tensor(18845910., device='cuda:0')]

Others: [{'iter_num': 11, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]

Compressed training loss: [tensor(41218.4102, device='cuda:0'), tensor(40966.5898, device='cuda:0'), tensor(40578.3086, device='cuda:0'), tensor(40813.8086, device='cuda:0'), tensor(40756.0586, device='cuda:0'), tensor(40802.6211, device='cuda:0'), tensor(40538.5508, device='cuda:0'), tensor(41111.8398, device='cuda:0'), tensor(40870.3516, device='cuda:0'), tensor(40836.3281, device='cuda:0')]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=1, microseconds=161076), datetime.timedelta(seconds=1, microseconds=216839), datetime.timedelta(seconds=1, microseconds=179995), datetime.timedelta(seconds=1, microseconds=228790), datetime.timedelta(seconds=1, microseconds=216839), datetime.timedelta(seconds=1, microseconds=144147), datetime.timedelta(seconds=1, microseconds=88384), datetime.timedelta(seconds=1, microseconds=158089), datetime.timedelta(seconds=1, microseconds=122241), datetime.timedelta(seconds=1, microseconds=100334)]

Phi time: [datetime.timedelta(microseconds=216083), datetime.timedelta(microseconds=226041), datetime.timedelta(microseconds=225046), datetime.timedelta(microseconds=228032), datetime.timedelta(microseconds=216083), datetime.timedelta(microseconds=226041), datetime.timedelta(microseconds=204133), datetime.timedelta(microseconds=190194), datetime.timedelta(microseconds=220067), datetime.timedelta(microseconds=211104)]

