Precision: [tensor(0.5038, device='cuda:0'), tensor(0.4872, device='cuda:0'), tensor(0.4965, device='cuda:0'), tensor(0.4908, device='cuda:0'), tensor(0.4958, device='cuda:0'), tensor(0.4867, device='cuda:0'), tensor(0.4923, device='cuda:0'), tensor(0.4971, device='cuda:0'), tensor(0.4773, device='cuda:0'), tensor(0.4834, device='cuda:0')]

Output distance: [tensor(19.0178, device='cuda:0'), tensor(19.0511, device='cuda:0'), tensor(19.0323, device='cuda:0'), tensor(19.0438, device='cuda:0'), tensor(19.0339, device='cuda:0'), tensor(19.0520, device='cuda:0'), tensor(19.0408, device='cuda:0'), tensor(19.0311, device='cuda:0'), tensor(19.0707, device='cuda:0'), tensor(19.0586, device='cuda:0')]

Prediction loss: [tensor(109.9277, device='cuda:0'), tensor(108.9482, device='cuda:0'), tensor(109.1770, device='cuda:0'), tensor(109.1893, device='cuda:0'), tensor(108.3462, device='cuda:0'), tensor(107.9593, device='cuda:0'), tensor(108.1415, device='cuda:0'), tensor(108.2642, device='cuda:0'), tensor(109.1191, device='cuda:0'), tensor(108.9373, device='cuda:0')]

Others: [{'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'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=334, microseconds=495290), datetime.timedelta(seconds=332, microseconds=991638), datetime.timedelta(seconds=334, microseconds=755280), datetime.timedelta(seconds=333, microseconds=457574), datetime.timedelta(seconds=332, microseconds=416874), datetime.timedelta(seconds=333, microseconds=718644), datetime.timedelta(seconds=333, microseconds=508552), datetime.timedelta(seconds=334, microseconds=623081), datetime.timedelta(seconds=329, microseconds=905382), datetime.timedelta(seconds=315, microseconds=815278)]

Phi time: [datetime.timedelta(seconds=5, microseconds=438982), datetime.timedelta(seconds=5, microseconds=185960), datetime.timedelta(seconds=5, microseconds=307569), datetime.timedelta(seconds=5, microseconds=115758), datetime.timedelta(seconds=5, microseconds=353244), datetime.timedelta(seconds=5, microseconds=207821), datetime.timedelta(seconds=5, microseconds=288548), datetime.timedelta(seconds=5, microseconds=126593), datetime.timedelta(seconds=5, microseconds=79616), datetime.timedelta(seconds=4, microseconds=614116)]

