Precision: [tensor(0.2361, device='cuda:0'), tensor(0.2446, device='cuda:0'), tensor(0.2432, device='cuda:0'), tensor(0.2442, device='cuda:0'), tensor(0.2213, device='cuda:0'), tensor(0.2327, device='cuda:0'), tensor(0.2646, device='cuda:0'), tensor(0.2647, device='cuda:0'), tensor(0.2476, device='cuda:0'), tensor(0.2570, device='cuda:0')]

Output distance: [tensor(20.6085, device='cuda:0'), tensor(20.5577, device='cuda:0'), tensor(20.5659, device='cuda:0'), tensor(20.5602, device='cuda:0'), tensor(20.6974, device='cuda:0'), tensor(20.6291, device='cuda:0'), tensor(20.4380, device='cuda:0'), tensor(20.4374, device='cuda:0'), tensor(20.5396, device='cuda:0'), tensor(20.4834, device='cuda:0')]

Prediction loss: [tensor(103.4220, device='cuda:0'), tensor(102.5506, device='cuda:0'), tensor(102.5745, device='cuda:0'), tensor(101.0693, device='cuda:0'), tensor(101.1418, device='cuda:0'), tensor(102.2243, device='cuda:0'), tensor(104.3518, device='cuda:0'), tensor(102.4533, device='cuda:0'), tensor(102.7690, device='cuda:0'), tensor(102.8176, device='cuda:0')]

Others: [{'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': 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': 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')}]

Compressed training loss: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=2, microseconds=632833), datetime.timedelta(seconds=2, microseconds=520310), datetime.timedelta(seconds=2, microseconds=528277), datetime.timedelta(seconds=2, microseconds=595940), datetime.timedelta(seconds=2, microseconds=497409), datetime.timedelta(seconds=2, microseconds=629847), datetime.timedelta(seconds=2, microseconds=524296), datetime.timedelta(seconds=2, microseconds=531265), datetime.timedelta(seconds=2, microseconds=528224), datetime.timedelta(seconds=2, microseconds=499400)]

Phi time: [datetime.timedelta(seconds=4, microseconds=471363), datetime.timedelta(seconds=4, microseconds=436869), datetime.timedelta(seconds=4, microseconds=490063), datetime.timedelta(seconds=4, microseconds=444939), datetime.timedelta(seconds=4, microseconds=452683), datetime.timedelta(seconds=4, microseconds=452669), datetime.timedelta(seconds=4, microseconds=451599), datetime.timedelta(seconds=4, microseconds=442386), datetime.timedelta(seconds=4, microseconds=434143), datetime.timedelta(seconds=4, microseconds=464765)]

