Precision: [tensor(0.2595, device='cuda:0'), tensor(0.2539, device='cuda:0'), tensor(0.2464, device='cuda:0'), tensor(0.2573, device='cuda:0'), tensor(0.2161, device='cuda:0'), tensor(0.2370, device='cuda:0'), tensor(0.2219, device='cuda:0'), tensor(0.2397, device='cuda:0'), tensor(0.2547, device='cuda:0'), tensor(0.2346, device='cuda:0')]

Output distance: [tensor(19.5063, device='cuda:0'), tensor(19.5175, device='cuda:0'), tensor(19.5326, device='cuda:0'), tensor(19.5109, device='cuda:0'), tensor(19.5931, device='cuda:0'), tensor(19.5514, device='cuda:0'), tensor(19.5816, device='cuda:0'), tensor(19.5460, device='cuda:0'), tensor(19.5160, device='cuda:0'), tensor(19.5562, device='cuda:0')]

Prediction loss: [tensor(107.8567, device='cuda:0'), tensor(109.8256, device='cuda:0'), tensor(110.4084, device='cuda:0'), tensor(108.8680, device='cuda:0'), tensor(106.2456, device='cuda:0'), tensor(107.0689, device='cuda:0'), tensor(106.2144, device='cuda:0'), tensor(108.2326, device='cuda:0'), tensor(108.8477, device='cuda:0'), tensor(108.7077, device='cuda:0')]

Others: [{'iter_num': 60, 'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(6616, 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=5, microseconds=291557), datetime.timedelta(seconds=5, microseconds=328351), datetime.timedelta(seconds=5, microseconds=324624), datetime.timedelta(seconds=5, microseconds=319597), datetime.timedelta(seconds=5, microseconds=322631), datetime.timedelta(seconds=5, microseconds=343491), datetime.timedelta(seconds=5, microseconds=313669), datetime.timedelta(seconds=5, microseconds=307744), datetime.timedelta(seconds=5, microseconds=318649), datetime.timedelta(seconds=5, microseconds=322629)]

Phi time: [datetime.timedelta(seconds=4, microseconds=299357), datetime.timedelta(seconds=4, microseconds=342628), datetime.timedelta(seconds=4, microseconds=382454), datetime.timedelta(seconds=4, microseconds=340156), datetime.timedelta(seconds=4, microseconds=357014), datetime.timedelta(seconds=4, microseconds=350207), datetime.timedelta(seconds=4, microseconds=349495), datetime.timedelta(seconds=4, microseconds=359680), datetime.timedelta(seconds=4, microseconds=348207), datetime.timedelta(seconds=4, microseconds=321704)]

