Precision: [tensor(0.2314, device='cuda:0'), tensor(0.2453, device='cuda:0'), tensor(0.2292, device='cuda:0'), tensor(0.2634, device='cuda:0'), tensor(0.2493, device='cuda:0'), tensor(0.2450, device='cuda:0'), tensor(0.2463, device='cuda:0'), tensor(0.2478, device='cuda:0'), tensor(0.2437, device='cuda:0'), tensor(0.2444, device='cuda:0')]

Output distance: [tensor(20.6372, device='cuda:0'), tensor(20.5535, device='cuda:0'), tensor(20.6499, device='cuda:0'), tensor(20.4450, device='cuda:0'), tensor(20.5296, device='cuda:0'), tensor(20.5553, device='cuda:0'), tensor(20.5475, device='cuda:0'), tensor(20.5387, device='cuda:0'), tensor(20.5632, device='cuda:0'), tensor(20.5593, device='cuda:0')]

Prediction loss: [tensor(102.9602, device='cuda:0'), tensor(103.5465, device='cuda:0'), tensor(102.2399, device='cuda:0'), tensor(103.8769, device='cuda:0'), tensor(103.1648, device='cuda:0'), tensor(103.9947, device='cuda:0'), tensor(103.3621, device='cuda:0'), tensor(102.9189, device='cuda:0'), tensor(101.9253, device='cuda:0'), tensor(102.6067, device='cuda:0')]

Others: [{'iter_num': 15, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 15, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 17, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 17, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 19, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 15, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 17, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 17, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 19, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 17, '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=796141), datetime.timedelta(seconds=2, microseconds=758301), datetime.timedelta(seconds=2, microseconds=918621), datetime.timedelta(seconds=2, microseconds=893727), datetime.timedelta(seconds=2, microseconds=982351), datetime.timedelta(seconds=2, microseconds=777221), datetime.timedelta(seconds=2, microseconds=871820), datetime.timedelta(seconds=2, microseconds=860864), datetime.timedelta(seconds=2, microseconds=992310), datetime.timedelta(seconds=2, microseconds=869826)]

Phi time: [datetime.timedelta(seconds=4, microseconds=470016), datetime.timedelta(seconds=4, microseconds=474122), datetime.timedelta(seconds=4, microseconds=501909), datetime.timedelta(seconds=4, microseconds=428487), datetime.timedelta(seconds=4, microseconds=437424), datetime.timedelta(seconds=4, microseconds=470879), datetime.timedelta(seconds=4, microseconds=513956), datetime.timedelta(seconds=4, microseconds=420875), datetime.timedelta(seconds=4, microseconds=453004), datetime.timedelta(seconds=4, microseconds=426740)]

