Precision: [tensor(0.9084, device='cuda:0'), tensor(0.9100, device='cuda:0'), tensor(0.9101, device='cuda:0'), tensor(0.9102, device='cuda:0'), tensor(0.9104, device='cuda:0'), tensor(0.9101, device='cuda:0'), tensor(0.9103, device='cuda:0'), tensor(0.9097, device='cuda:0'), tensor(0.9090, device='cuda:0'), tensor(0.9101, device='cuda:0')]

Output distance: [tensor(565.6839, device='cuda:0'), tensor(549.4049, device='cuda:0'), tensor(550.8518, device='cuda:0'), tensor(558.9231, device='cuda:0'), tensor(550.0652, device='cuda:0'), tensor(558.2589, device='cuda:0'), tensor(555.1060, device='cuda:0'), tensor(553.8168, device='cuda:0'), tensor(563.0328, device='cuda:0'), tensor(552.3129, device='cuda:0')]

Prediction loss: [tensor(644.6710, device='cuda:0'), tensor(623.4180, device='cuda:0'), tensor(635.2769, device='cuda:0'), tensor(654.6124, device='cuda:0'), tensor(652.4075, device='cuda:0'), tensor(650.0716, device='cuda:0'), tensor(650.1829, device='cuda:0'), tensor(639.9193, device='cuda:0'), tensor(665.1421, device='cuda:0'), tensor(637.4201, device='cuda:0')]

Others: [{'num_positive': tensor(16574, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16619, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16621, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16562, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16593, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16568, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16573, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16587, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16580, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16594, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}]

Compressed training loss: [tensor(8853079., device='cuda:0'), tensor(8595268., device='cuda:0'), tensor(8741478., device='cuda:0'), tensor(8959272., device='cuda:0'), tensor(8930557., device='cuda:0'), tensor(8881698., device='cuda:0'), tensor(8910409., device='cuda:0'), tensor(8784771., device='cuda:0'), tensor(9093173., device='cuda:0'), tensor(8750782., device='cuda:0')]

Training loss: 8794926.0

Prediction time: [datetime.timedelta(seconds=320, microseconds=162117), datetime.timedelta(seconds=317, microseconds=282309), datetime.timedelta(seconds=309, microseconds=622904), datetime.timedelta(seconds=301, microseconds=106399), datetime.timedelta(seconds=300, microseconds=284104), datetime.timedelta(seconds=300, microseconds=87040), datetime.timedelta(seconds=301, microseconds=643131), datetime.timedelta(seconds=301, microseconds=467015), datetime.timedelta(seconds=301, microseconds=512738), datetime.timedelta(seconds=301, microseconds=281326)]

Phi time: [datetime.timedelta(seconds=1, microseconds=385143), datetime.timedelta(microseconds=836673), datetime.timedelta(microseconds=850649), datetime.timedelta(microseconds=818532), datetime.timedelta(microseconds=834941), datetime.timedelta(microseconds=822304), datetime.timedelta(microseconds=823762), datetime.timedelta(microseconds=815717), datetime.timedelta(microseconds=833810), datetime.timedelta(microseconds=830807)]

