Precision: [tensor(0.3471, device='cuda:0'), tensor(0.3333, device='cuda:0'), tensor(0.3454, device='cuda:0'), tensor(0.3501, device='cuda:0'), tensor(0.3546, device='cuda:0'), tensor(0.3448, device='cuda:0'), tensor(0.3440, device='cuda:0'), tensor(0.3446, device='cuda:0'), tensor(0.3537, device='cuda:0'), tensor(0.3462, device='cuda:0')]

Output distance: [tensor(19.9426, device='cuda:0'), tensor(20.0257, device='cuda:0'), tensor(19.9531, device='cuda:0'), tensor(19.9247, device='cuda:0'), tensor(19.8978, device='cuda:0'), tensor(19.9565, device='cuda:0'), tensor(19.9613, device='cuda:0'), tensor(19.9577, device='cuda:0'), tensor(19.9030, device='cuda:0'), tensor(19.9480, device='cuda:0')]

Prediction loss: [tensor(103.8818, device='cuda:0'), tensor(103.1100, device='cuda:0'), tensor(104.0146, device='cuda:0'), tensor(103.9961, device='cuda:0'), tensor(104.0387, device='cuda:0'), tensor(104.3450, device='cuda:0'), tensor(103.4489, device='cuda:0'), tensor(104.1992, device='cuda:0'), tensor(103.9871, device='cuda:0'), tensor(104.2968, device='cuda:0')]

Others: [{'iter_num': 7, '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')}, {'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=696566), datetime.timedelta(seconds=2, microseconds=791162), datetime.timedelta(seconds=2, microseconds=795145), datetime.timedelta(seconds=2, microseconds=826014), datetime.timedelta(seconds=2, microseconds=792162), datetime.timedelta(seconds=2, microseconds=793153), datetime.timedelta(seconds=2, microseconds=780205), datetime.timedelta(seconds=2, microseconds=768254), datetime.timedelta(seconds=2, microseconds=804112), datetime.timedelta(seconds=2, microseconds=793198)]

Phi time: [datetime.timedelta(seconds=5, microseconds=28234), datetime.timedelta(seconds=5, microseconds=22415), datetime.timedelta(seconds=5, microseconds=17900), datetime.timedelta(seconds=5, microseconds=27770), datetime.timedelta(seconds=5, microseconds=9282), datetime.timedelta(seconds=4, microseconds=995242), datetime.timedelta(seconds=5, microseconds=6177), datetime.timedelta(seconds=4, microseconds=992092), datetime.timedelta(seconds=5, microseconds=5592), datetime.timedelta(seconds=5, microseconds=32651)]

