Precision: [tensor(0.3438, device='cuda:0'), tensor(0.3409, device='cuda:0'), tensor(0.3495, device='cuda:0'), tensor(0.3471, device='cuda:0'), tensor(0.3573, device='cuda:0'), tensor(0.3395, device='cuda:0'), tensor(0.3456, device='cuda:0'), tensor(0.3610, device='cuda:0'), tensor(0.3524, device='cuda:0'), tensor(0.3479, device='cuda:0')]

Output distance: [tensor(19.9628, device='cuda:0'), tensor(19.9797, device='cuda:0'), tensor(19.9287, device='cuda:0'), tensor(19.9429, device='cuda:0'), tensor(19.8818, device='cuda:0'), tensor(19.9885, device='cuda:0'), tensor(19.9519, device='cuda:0'), tensor(19.8594, device='cuda:0'), tensor(19.9108, device='cuda:0'), tensor(19.9380, device='cuda:0')]

Prediction loss: [tensor(103.8722, device='cuda:0'), tensor(103.5312, device='cuda:0'), tensor(104.5137, device='cuda:0'), tensor(103.8587, device='cuda:0'), tensor(105.3077, device='cuda:0'), tensor(102.9861, device='cuda:0'), tensor(104.0241, device='cuda:0'), tensor(105.2277, device='cuda:0'), tensor(104.2031, device='cuda:0'), tensor(104.1388, device='cuda:0')]

Others: [{'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, '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=459305), datetime.timedelta(seconds=2, microseconds=467735), datetime.timedelta(seconds=2, microseconds=450054), datetime.timedelta(seconds=2, microseconds=534552), datetime.timedelta(seconds=2, microseconds=440592), datetime.timedelta(seconds=2, microseconds=443237), datetime.timedelta(seconds=2, microseconds=429119), datetime.timedelta(seconds=2, microseconds=447776), datetime.timedelta(seconds=2, microseconds=453536), datetime.timedelta(seconds=2, microseconds=457798)]

Phi time: [datetime.timedelta(seconds=4, microseconds=474108), datetime.timedelta(seconds=4, microseconds=459981), datetime.timedelta(seconds=4, microseconds=427090), datetime.timedelta(seconds=4, microseconds=450645), datetime.timedelta(seconds=4, microseconds=477837), datetime.timedelta(seconds=4, microseconds=409178), datetime.timedelta(seconds=4, microseconds=412064), datetime.timedelta(seconds=4, microseconds=462523), datetime.timedelta(seconds=4, microseconds=503792), datetime.timedelta(seconds=4, microseconds=442251)]

