Precision: [tensor(0.3927, device='cuda:0'), tensor(0.4070, device='cuda:0'), tensor(0.4042, device='cuda:0'), tensor(0.3979, device='cuda:0'), tensor(0.3945, device='cuda:0'), tensor(0.3920, device='cuda:0'), tensor(0.3975, device='cuda:0'), tensor(0.3958, device='cuda:0'), tensor(0.4057, device='cuda:0'), tensor(0.4019, device='cuda:0')]

Output distance: [tensor(19.6690, device='cuda:0'), tensor(19.5834, device='cuda:0'), tensor(19.6001, device='cuda:0'), tensor(19.6381, device='cuda:0'), tensor(19.6584, device='cuda:0'), tensor(19.6732, device='cuda:0'), tensor(19.6403, device='cuda:0'), tensor(19.6505, device='cuda:0'), tensor(19.5910, device='cuda:0'), tensor(19.6143, device='cuda:0')]

Prediction loss: [tensor(104.0501, device='cuda:0'), tensor(103.8766, device='cuda:0'), tensor(104.5106, device='cuda:0'), tensor(103.7344, device='cuda:0'), tensor(104.6567, device='cuda:0'), tensor(103.9799, device='cuda:0'), tensor(104.6917, device='cuda:0'), tensor(104.4143, device='cuda:0'), tensor(105.1204, device='cuda:0'), tensor(103.4177, 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': 7, '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': 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': 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')}]

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

Training loss: 0

Prediction time: [datetime.timedelta(seconds=2, microseconds=565779), datetime.timedelta(seconds=2, microseconds=550602), datetime.timedelta(seconds=2, microseconds=549592), datetime.timedelta(seconds=2, microseconds=465682), datetime.timedelta(seconds=2, microseconds=717020), datetime.timedelta(seconds=2, microseconds=716123), datetime.timedelta(seconds=2, microseconds=566051), datetime.timedelta(seconds=2, microseconds=565196), datetime.timedelta(seconds=2, microseconds=482400), datetime.timedelta(seconds=2, microseconds=566096)]

Phi time: [datetime.timedelta(seconds=4, microseconds=644397), datetime.timedelta(seconds=4, microseconds=683897), datetime.timedelta(seconds=4, microseconds=771609), datetime.timedelta(seconds=4, microseconds=633017), datetime.timedelta(seconds=4, microseconds=650497), datetime.timedelta(seconds=4, microseconds=684209), datetime.timedelta(seconds=4, microseconds=696650), datetime.timedelta(seconds=4, microseconds=698942), datetime.timedelta(seconds=4, microseconds=633746), datetime.timedelta(seconds=4, microseconds=648305)]

