Precision: [tensor(0.4670, device='cuda:0'), tensor(0.4627, device='cuda:0'), tensor(0.4637, device='cuda:0'), tensor(0.4653, device='cuda:0'), tensor(0.4635, device='cuda:0'), tensor(0.4631, device='cuda:0'), tensor(0.4621, device='cuda:0'), tensor(0.4668, device='cuda:0'), tensor(0.4584, device='cuda:0'), tensor(0.4649, device='cuda:0')]

Output distance: [tensor(19.2231, device='cuda:0'), tensor(19.2494, device='cuda:0'), tensor(19.2434, device='cuda:0'), tensor(19.2337, device='cuda:0'), tensor(19.2443, device='cuda:0'), tensor(19.2467, device='cuda:0'), tensor(19.2527, device='cuda:0'), tensor(19.2243, device='cuda:0'), tensor(19.2751, device='cuda:0'), tensor(19.2358, device='cuda:0')]

Prediction loss: [tensor(105.2657, device='cuda:0'), tensor(105.2122, device='cuda:0'), tensor(105.1254, device='cuda:0'), tensor(105.2495, device='cuda:0'), tensor(104.8156, device='cuda:0'), tensor(104.7444, device='cuda:0'), tensor(104.3802, device='cuda:0'), tensor(105.3082, device='cuda:0'), tensor(105.2669, device='cuda:0'), tensor(104.8216, device='cuda:0')]

Others: [{'iter_num': 5, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 5, '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=744361), datetime.timedelta(seconds=2, microseconds=830994), datetime.timedelta(seconds=2, microseconds=795145), datetime.timedelta(seconds=2, microseconds=699547), datetime.timedelta(seconds=2, microseconds=936546), datetime.timedelta(seconds=2, microseconds=721456), datetime.timedelta(seconds=2, microseconds=726428), datetime.timedelta(seconds=2, microseconds=773291), datetime.timedelta(seconds=2, microseconds=724443), datetime.timedelta(seconds=2, microseconds=739387)]

Phi time: [datetime.timedelta(seconds=6, microseconds=209966), datetime.timedelta(seconds=6, microseconds=85531), datetime.timedelta(seconds=6, microseconds=158739), datetime.timedelta(seconds=6, microseconds=194875), datetime.timedelta(seconds=6, microseconds=121885), datetime.timedelta(seconds=6, microseconds=91425), datetime.timedelta(seconds=6, microseconds=97613), datetime.timedelta(seconds=6, microseconds=129976), datetime.timedelta(seconds=6, microseconds=96150), datetime.timedelta(seconds=6, microseconds=217458)]

