Precision: [tensor(0.9303, device='cuda:0'), tensor(0.9284, device='cuda:0'), tensor(0.9277, device='cuda:0'), tensor(0.9302, device='cuda:0'), tensor(0.9306, device='cuda:0'), tensor(0.9287, device='cuda:0'), tensor(0.9263, device='cuda:0'), tensor(0.9291, device='cuda:0'), tensor(0.9301, device='cuda:0'), tensor(0.9337, device='cuda:0')]
Output distance: [tensor(2573.0093, device='cuda:0'), tensor(2632.0159, device='cuda:0'), tensor(2673.1318, device='cuda:0'), tensor(2571.5630, device='cuda:0'), tensor(2590.8093, device='cuda:0'), tensor(2619.9714, device='cuda:0'), tensor(2758.5486, device='cuda:0'), tensor(2675.7903, device='cuda:0'), tensor(2549.4312, device='cuda:0'), tensor(2399.9429, device='cuda:0')]
Prediction loss: [tensor(6574.3892, device='cuda:0'), tensor(6606.8184, device='cuda:0'), tensor(6628.8921, device='cuda:0'), tensor(6603.5967, device='cuda:0'), tensor(6343.8467, device='cuda:0'), tensor(6434.0459, device='cuda:0'), tensor(6529.5659, device='cuda:0'), tensor(6635.2168, device='cuda:0'), tensor(6647.7754, device='cuda:0'), tensor(6407.9546, device='cuda:0')]
Others: [{'iter_num': 7, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}]
Compressed training loss: [tensor(64927116., device='cuda:0'), tensor(65456308., device='cuda:0'), tensor(65425268., device='cuda:0'), tensor(65381864., device='cuda:0'), tensor(62705240., device='cuda:0'), tensor(63560936., device='cuda:0'), tensor(64639596., device='cuda:0'), tensor(65467480., device='cuda:0'), tensor(65618472., device='cuda:0'), tensor(63182804., device='cuda:0')]
Training loss: Not calculated
Prediction time: [datetime.timedelta(microseconds=613348), datetime.timedelta(microseconds=697988), datetime.timedelta(microseconds=701998), datetime.timedelta(microseconds=610412), datetime.timedelta(microseconds=699036), datetime.timedelta(microseconds=591501), datetime.timedelta(microseconds=603496), datetime.timedelta(microseconds=692064), datetime.timedelta(microseconds=620368), datetime.timedelta(microseconds=691070)]
Phi time: [datetime.timedelta(microseconds=917167), datetime.timedelta(microseconds=868320), datetime.timedelta(microseconds=893264), datetime.timedelta(microseconds=861425), datetime.timedelta(microseconds=899213), datetime.timedelta(microseconds=862055), datetime.timedelta(microseconds=852690), datetime.timedelta(microseconds=860717), datetime.timedelta(microseconds=859870), datetime.timedelta(microseconds=867287)]
