2023-09-28 23:24:54,546 - utils - INFO - Namespace(attack_ratio=0.4, attack_type='None', batch_size=[100, 100], beta=1, data_dir='data', dataset='synthetic', delta_g=0.5, delta_l=0.5, device='cuda', device_id='1', disparity_type='TPSD', drop_last=False, eps=[0.1, 0.01, 0.02], eps_delta=[0.01, 0.01], eps_delta_g=0.01, eps_delta_l=0.01, eps_g=0.1, eps_vg=0.02, eps_vl=0.01, eval_epoch=20, factor_delta=0.1, force_active=True, global_epoch=0, lam=1, local_epochs=5, log_dir='results/EFFL_synthetic', log_name='log', lr_delta=0.1, max_epoch_stage=[750, 750, 500], method='EFFL', n_clients=2, n_feats=2, n_hiddens=20, norm='loss+', num_workers=0, q=6.0, s=1, sampler='None', seed=3, sensitive_attr='race', shuffle=True, step_size=0.03, target_dir_name='results/EFFL_synthetic', test_dir='data/synthetic/test', theta=1, train_dir='data/synthetic/train', weight_fair=1.0)
2023-09-28 23:24:56,008 - utils - INFO - stage1_gradient_single_runtime: 0.009480476379394531
2023-09-28 23:24:56,010 - utils - INFO -  epoch: 0, all client loss: [1.2188140153884888, 1.2611075639724731], all pred client disparities: [0.2953486740589142, 0.1610940843820572], all client disparities: [0.3043324947357178, 0.1635465919971466], all client accs: [0.22760289907455444, 0.2779790163040161],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:56,027 - utils - INFO - valid: True, epoch: 0, loss: [1.1768711805343628, 1.2255388498306274], accuracy: [0.2175999879837036, 0.29600000381469727], mean_accuracy:0.25679999589920044,variance_accuracy:0.039200007915496826, disparity: [0.3081977367401123, 0.1627117544412613], mean_disparity:0.2354547455906868,variance_disparity:0.0727429911494255, pred_disparity: [0.30209848284721375, 0.16060754656791687]
2023-09-28 23:24:56,040 - utils - INFO - global_valid: True, epoch: 0,  global_loss: 1.2103302478790283, global_accuracy: 0.23009803921568628,  global_disparity:0.20039057731628418, global_pred_disparity: 0.1975342333316803,
2023-09-28 23:24:56,090 - utils - INFO - stage1_gradient_single_runtime: 0.0027112960815429688
2023-09-28 23:24:56,091 - utils - INFO -  epoch: 1, all client loss: [1.1885566711425781, 1.2312886714935303], all pred client disparities: [0.2943152189254761, 0.15771019458770752], all client disparities: [0.3026658594608307, 0.16078433394432068], all client accs: [0.22518159449100494, 0.28105759620666504],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:56,144 - utils - INFO - stage1_gradient_single_runtime: 0.0022394657135009766
2023-09-28 23:24:56,144 - utils - INFO -  epoch: 2, all client loss: [1.1592977046966553, 1.2024714946746826], all pred client disparities: [0.2926735281944275, 0.15398021042346954], all client disparities: [0.30139434337615967, 0.15586505830287933], all client accs: [0.22316382825374603, 0.28286853432655334],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:56,198 - utils - INFO - stage1_gradient_single_runtime: 0.003683328628540039
2023-09-28 23:24:56,199 - utils - INFO -  epoch: 3, all client loss: [1.1310540437698364, 1.1746701002120972], all pred client disparities: [0.2903406620025635, 0.14992107450962067], all client disparities: [0.30095618963241577, 0.1505143791437149], all client accs: [0.21791766583919525, 0.2872147858142853],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:56,253 - utils - INFO - stage1_gradient_single_runtime: 0.002637147903442383
2023-09-28 23:24:56,254 - utils - INFO -  epoch: 4, all client loss: [1.1038398742675781, 1.147895336151123], all pred client disparities: [0.2872644364833832, 0.14554986357688904], all client disparities: [0.2988513708114624, 0.14516368508338928], all client accs: [0.2171105593442917, 0.2919232249259949],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:56,305 - utils - INFO - stage1_gradient_single_runtime: 0.0023081302642822266
2023-09-28 23:24:56,306 - utils - INFO -  epoch: 5, all client loss: [1.0776664018630981, 1.1221543550491333], all pred client disparities: [0.2834204435348511, 0.1408640295267105], all client disparities: [0.29503685235977173, 0.14283286035060883], all client accs: [0.21872477233409882, 0.29880478978157043],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:56,353 - utils - INFO - stage1_gradient_single_runtime: 0.002492189407348633
2023-09-28 23:24:56,354 - utils - INFO -  epoch: 6, all client loss: [1.05254065990448, 1.097451090812683], all pred client disparities: [0.27881476283073425, 0.13583704829216003], all client disparities: [0.29157453775405884, 0.13593034446239471], all client accs: [0.22477804124355316, 0.30351322889328003],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:56,401 - utils - INFO - stage1_gradient_single_runtime: 0.0023539066314697266
2023-09-28 23:24:56,402 - utils - INFO -  epoch: 7, all client loss: [1.0284663438796997, 1.0737850666046143], all pred client disparities: [0.2735212743282318, 0.1304391324520111], all client disparities: [0.281926691532135, 0.13144247233867645], all client accs: [0.22921709716320038, 0.3109380602836609],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:56,451 - utils - INFO - stage1_gradient_single_runtime: 0.002279043197631836
2023-09-28 23:24:56,452 - utils - INFO -  epoch: 8, all client loss: [1.00544273853302, 1.051152229309082], all pred client disparities: [0.2676711082458496, 0.1246906965970993], all client disparities: [0.27600738406181335, 0.12410857528448105], all client accs: [0.23527036607265472, 0.31836292147636414],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:56,589 - utils - INFO - stage1_gradient_single_runtime: 0.0022535324096679688
2023-09-28 23:24:56,590 - utils - INFO -  epoch: 9, all client loss: [0.9834654331207275, 1.0295439958572388], all pred client disparities: [0.2613460123538971, 0.1186765804886818], all client disparities: [0.2705262303352356, 0.1154804453253746], all client accs: [0.2384987771511078, 0.3265121579170227],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:56,642 - utils - INFO - stage1_gradient_single_runtime: 0.002359151840209961
2023-09-28 23:24:56,643 - utils - INFO -  epoch: 10, all client loss: [0.9625253677368164, 1.0089482069015503], all pred client disparities: [0.2544953227043152, 0.1124982237815857], all client disparities: [0.26298320293426514, 0.10883554071187973], all client accs: [0.24172718822956085, 0.33502355217933655],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:56,696 - utils - INFO - stage1_gradient_single_runtime: 0.0026047229766845703
2023-09-28 23:24:56,698 - utils - INFO -  epoch: 11, all client loss: [0.9426099061965942, 0.9893484115600586], all pred client disparities: [0.24695543944835663, 0.1062280610203743], all client disparities: [0.2628542184829712, 0.10219063609838486], all client accs: [0.24495559930801392, 0.34281057119369507],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:56,748 - utils - INFO - stage1_gradient_single_runtime: 0.0023517608642578125
2023-09-28 23:24:56,749 - utils - INFO -  epoch: 12, all client loss: [0.9237017631530762, 0.970724880695343], all pred client disparities: [0.23852849006652832, 0.0998498946428299], all client disparities: [0.2614537179470062, 0.09683994948863983], all client accs: [0.2506053149700165, 0.34842449426651],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:56,807 - utils - INFO - stage1_gradient_single_runtime: 0.002239227294921875
2023-09-28 23:24:56,807 - utils - INFO -  epoch: 13, all client loss: [0.9057803153991699, 0.9530541896820068], all pred client disparities: [0.22908329963684082, 0.09324599802494049], all client disparities: [0.250929594039917, 0.09295107424259186], all client accs: [0.2570621371269226, 0.3565737009048462],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:56,858 - utils - INFO - stage1_gradient_single_runtime: 0.0023603439331054688
2023-09-28 23:24:56,859 - utils - INFO -  epoch: 14, all client loss: [0.8888208270072937, 0.9363096356391907], all pred client disparities: [0.21863079071044922, 0.08629609644412994], all client disparities: [0.2341768890619278, 0.08501195162534714], all client accs: [0.26594027876853943, 0.36399856209754944],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:56,912 - utils - INFO - stage1_gradient_single_runtime: 0.002313375473022461
2023-09-28 23:24:56,912 - utils - INFO -  epoch: 15, all client loss: [0.8727956414222717, 0.9204620122909546], all pred client disparities: [0.2072603553533554, 0.07896123081445694], all client disparities: [0.22896191477775574, 0.07836704701185226], all client accs: [0.276432603597641, 0.3725099563598633],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:56,962 - utils - INFO - stage1_gradient_single_runtime: 0.0023374557495117188
2023-09-28 23:24:56,963 - utils - INFO -  epoch: 16, all client loss: [0.8576741814613342, 0.9054793119430542], all pred client disparities: [0.19493094086647034, 0.0712977722287178], all client disparities: [0.2168140858411789, 0.06887611001729965], all client accs: [0.2816787660121918, 0.3804780840873718],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:57,017 - utils - INFO - stage1_gradient_single_runtime: 0.0022864341735839844
2023-09-28 23:24:57,017 - utils - INFO -  epoch: 17, all client loss: [0.8434231877326965, 0.8913283348083496], all pred client disparities: [0.18138298392295837, 0.06342297047376633], all client disparities: [0.20554259419441223, 0.05877995863556862], all client accs: [0.286117821931839, 0.38844621181488037],  alpha_performance: tensor([0., 1.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:57,071 - utils - INFO - stage1_gradient_single_runtime: 0.002607107162475586
2023-09-28 23:24:57,072 - utils - INFO -  epoch: 18, all client loss: [0.8330391049385071, 0.8802724480628967], all pred client disparities: [0.1638507843017578, 0.055568236857652664], all client disparities: [0.1899324357509613, 0.052476443350315094], all client accs: [0.2978208065032959, 0.39605218172073364],  alpha_performance: tensor([0., 1.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:57,123 - utils - INFO - stage1_gradient_single_runtime: 0.002290010452270508
2023-09-28 23:24:57,125 - utils - INFO -  epoch: 19, all client loss: [0.8219877481460571, 0.8683274984359741], all pred client disparities: [0.14168789982795715, 0.046725958585739136], all client disparities: [0.17098894715309143, 0.04315308481454849], all client accs: [0.31033089756965637, 0.4023904502391815],  alpha_performance: tensor([0., 1.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:57,145 - utils - INFO - valid: True, epoch: 19, loss: [0.8156024217605591, 0.8555505871772766], accuracy: [0.3312000036239624, 0.4138181805610657], mean_accuracy:0.37250909209251404,variance_accuracy:0.041309088468551636, disparity: [0.13235291838645935, 0.05192750319838524], mean_disparity:0.0921402107924223,variance_disparity:0.040212707594037056, pred_disparity: [0.11655336618423462, 0.04935947805643082]
2023-09-28 23:24:57,156 - utils - INFO - global_valid: True, epoch: 19,  global_loss: 0.8430668115615845, global_accuracy: 0.33517456982793115,  global_disparity:0.08006783574819565, global_pred_disparity: 0.07366283237934113,
2023-09-28 23:24:57,204 - utils - INFO - stage1_gradient_single_runtime: 0.002322673797607422
2023-09-28 23:24:57,205 - utils - INFO -  epoch: 20, all client loss: [0.8101952075958252, 0.8553874492645264], all pred client disparities: [0.11356064677238464, 0.036630429327487946], all client disparities: [0.14165028929710388, 0.033745937049388885], all client accs: [0.3268764913082123, 0.41017746925354004],  alpha_performance: tensor([0., 1.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:57,329 - utils - INFO - stage1_gradient_single_runtime: 0.005917072296142578
2023-09-28 23:24:57,330 - utils - INFO -  epoch: 21, all client loss: [0.7976966500282288, 0.8414969444274902], all pred client disparities: [0.07868146896362305, 0.02510767988860607], all client disparities: [0.09301596879959106, 0.020372338593006134], all client accs: [0.3551250994205475, 0.41905108094215393],  alpha_performance: tensor([0., 1.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:57,382 - utils - INFO - stage1_gradient_single_runtime: 0.002124786376953125
2023-09-28 23:24:57,384 - utils - INFO -  epoch: 22, all client loss: [0.7847487926483154, 0.8269979357719421], all pred client disparities: [0.03827980160713196, 0.012226620689034462], all client disparities: [0.04933866858482361, 0.009323356673121452], all client accs: [0.3809523582458496, 0.4290112257003784],  alpha_performance: tensor([0., 1.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:57,433 - utils - INFO - stage1_gradient_single_runtime: 0.002102375030517578
2023-09-28 23:24:57,434 - utils - INFO -  epoch: 23, all client loss: [0.7719004154205322, 0.812732994556427], all pred client disparities: [0.0014562904834747314, 0.0018073897808790207], all client disparities: [0.004914015531539917, 0.005996125750243664], all client accs: [0.4075867533683777, 0.4436798393726349],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:57,493 - utils - INFO - stage1_gradient_single_runtime: 0.00225067138671875
2023-09-28 23:24:57,494 - utils - INFO -  epoch: 24, all client loss: [0.7637630701065063, 0.8046049475669861], all pred client disparities: [0.0192297101020813, 0.00897672027349472], all client disparities: [0.022508203983306885, 0.01165086217224598], all client accs: [0.42251813411712646, 0.4496559500694275],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:57,545 - utils - INFO - stage1_gradient_single_runtime: 0.002177715301513672
2023-09-28 23:24:57,546 - utils - INFO -  epoch: 25, all client loss: [0.7561049461364746, 0.796930730342865], all pred client disparities: [0.0355914831161499, 0.016076723113656044], all client disparities: [0.03970721364021301, 0.01962398923933506], all client accs: [0.43462467193603516, 0.457442969083786],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:57,599 - utils - INFO - stage1_gradient_single_runtime: 0.002115011215209961
2023-09-28 23:24:57,600 - utils - INFO -  epoch: 26, all client loss: [0.7488957047462463, 0.7896820306777954], all pred client disparities: [0.05066618323326111, 0.023102855309844017], all client disparities: [0.047868549823760986, 0.02484731748700142], all client accs: [0.45117029547691345, 0.46251359581947327],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:57,650 - utils - INFO - stage1_gradient_single_runtime: 0.0021142959594726562
2023-09-28 23:24:57,651 - utils - INFO -  epoch: 27, all client loss: [0.7421064376831055, 0.7828318476676941], all pred client disparities: [0.06464424729347229, 0.030037129297852516], all client disparities: [0.06462940573692322, 0.030412038788199425], all client accs: [0.4620661735534668, 0.46885186433792114],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:57,704 - utils - INFO - stage1_gradient_single_runtime: 0.002088308334350586
2023-09-28 23:24:57,705 - utils - INFO -  epoch: 28, all client loss: [0.735709547996521, 0.7763546705245972], all pred client disparities: [0.07755336165428162, 0.036862120032310486], all client disparities: [0.08059993386268616, 0.03674955293536186], all client accs: [0.4737691581249237, 0.47537124156951904],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:57,758 - utils - INFO - stage1_gradient_single_runtime: 0.0021975040435791016
2023-09-28 23:24:57,759 - utils - INFO -  epoch: 29, all client loss: [0.7296794652938843, 0.7702264785766602], all pred client disparities: [0.08938339352607727, 0.0435575507581234], all client disparities: [0.08507576584815979, 0.04299706220626831], all client accs: [0.4834543764591217, 0.482252836227417],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:57,811 - utils - INFO - stage1_gradient_single_runtime: 0.0023069381713867188
2023-09-28 23:24:57,812 - utils - INFO -  epoch: 30, all client loss: [0.7239913940429688, 0.7644245624542236], all pred client disparities: [0.10015007853507996, 0.050099533051252365], all client disparities: [0.10144144296646118, 0.053552404046058655], all client accs: [0.4911218583583832, 0.4893154799938202],  alpha_performance: tensor([0.5987, 0.4013], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:57,865 - utils - INFO - stage1_gradient_single_runtime: 0.002295970916748047
2023-09-28 23:24:57,866 - utils - INFO -  epoch: 31, all client loss: [0.7240654826164246, 0.7643534541130066], all pred client disparities: [0.09932029247283936, 0.049418702721595764], all client disparities: [0.100212961435318, 0.05303720384836197], all client accs: [0.4907183051109314, 0.48913437128067017],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:57,922 - utils - INFO - stage1_gradient_single_runtime: 0.002603769302368164
2023-09-28 23:24:57,924 - utils - INFO -  epoch: 32, all client loss: [0.7186678051948547, 0.7588263154029846], all pred client disparities: [0.1092073917388916, 0.055835623294115067], all client disparities: [0.11903563141822815, 0.05775155499577522], all client accs: [0.4975786805152893, 0.49329954385757446],  alpha_performance: tensor([0.5961, 0.4039], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:58,045 - utils - INFO - stage1_gradient_single_runtime: 0.0022857189178466797
2023-09-28 23:24:58,046 - utils - INFO -  epoch: 33, all client loss: [0.7187446355819702, 0.7587522864341736], all pred client disparities: [0.10848599672317505, 0.0552043579518795], all client disparities: [0.11903563141822815, 0.05766776576638222], all client accs: [0.4975786805152893, 0.4927562475204468],  alpha_performance: tensor([0.5977, 0.4023], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:58,099 - utils - INFO - stage1_gradient_single_runtime: 0.0022912025451660156
2023-09-28 23:24:58,099 - utils - INFO -  epoch: 34, all client loss: [0.7188203930854797, 0.7586792707443237], all pred client disparities: [0.10775583982467651, 0.05456860363483429], all client disparities: [0.11903563141822815, 0.058015380054712296], all client accs: [0.4971751272678375, 0.49257516860961914],  alpha_performance: tensor([0.5993, 0.4007], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:58,149 - utils - INFO - stage1_gradient_single_runtime: 0.0022764205932617188
2023-09-28 23:24:58,150 - utils - INFO -  epoch: 35, all client loss: [0.7188951373100281, 0.7586072683334351], all pred client disparities: [0.10701674222946167, 0.05392824485898018], all client disparities: [0.11780712008476257, 0.056469786912202835], all client accs: [0.49677157402038574, 0.49148860573768616],  alpha_performance: tensor([0.6009, 0.3991], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:58,201 - utils - INFO - stage1_gradient_single_runtime: 0.002310037612915039
2023-09-28 23:24:58,203 - utils - INFO -  epoch: 36, all client loss: [0.7189688682556152, 0.7585363388061523], all pred client disparities: [0.10626846551895142, 0.05328323319554329], all client disparities: [0.11657863855361938, 0.05595458671450615], all client accs: [0.49677157402038574, 0.49130749702453613],  alpha_performance: tensor([0.6025, 0.3975], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:58,252 - utils - INFO - stage1_gradient_single_runtime: 0.0022954940795898438
2023-09-28 23:24:58,253 - utils - INFO -  epoch: 37, all client loss: [0.7190415859222412, 0.7584664821624756], all pred client disparities: [0.10551068186759949, 0.05263349413871765], all client disparities: [0.11535012722015381, 0.0555294007062912], all client accs: [0.4951573610305786, 0.4900398552417755],  alpha_performance: tensor([0.6042, 0.3958], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:58,302 - utils - INFO - stage1_gradient_single_runtime: 0.0025577545166015625
2023-09-28 23:24:58,303 - utils - INFO -  epoch: 38, all client loss: [0.7191130518913269, 0.7583978176116943], all pred client disparities: [0.10474318265914917, 0.05197896063327789], all client disparities: [0.11535012722015381, 0.0555294007062912], all client accs: [0.49435025453567505, 0.49022096395492554],  alpha_performance: tensor([0.6058, 0.3942], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:58,353 - utils - INFO - stage1_gradient_single_runtime: 0.0022783279418945312
2023-09-28 23:24:58,355 - utils - INFO -  epoch: 39, all client loss: [0.7191835045814514, 0.758330225944519], all pred client disparities: [0.10396561026573181, 0.051319580525159836], all client disparities: [0.11535012722015381, 0.055703211575746536], all client accs: [0.49394673109054565, 0.4898587465286255],  alpha_performance: tensor([0.6075, 0.3925], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:58,374 - utils - INFO - valid: True, epoch: 39, loss: [0.7262570261955261, 0.7618767619132996], accuracy: [0.48639997839927673, 0.48363634943962097], mean_accuracy:0.48501816391944885,variance_accuracy:0.0013818144798278809, disparity: [0.0726950466632843, 0.05847681686282158], mean_disparity:0.06558593176305294,variance_disparity:0.007109114900231361, pred_disparity: [0.07546263933181763, 0.056192509829998016]
2023-09-28 23:24:58,386 - utils - INFO - global_valid: True, epoch: 39,  global_loss: 0.7507456541061401, global_accuracy: 0.49000300120048024,  global_disparity:0.052414171397686005, global_pred_disparity: 0.05205141007900238,
2023-09-28 23:24:58,434 - utils - INFO - stage1_gradient_single_runtime: 0.0023543834686279297
2023-09-28 23:24:58,435 - utils - INFO -  epoch: 40, all client loss: [0.7192526459693909, 0.7582638263702393], all pred client disparities: [0.10317781567573547, 0.050655268132686615], all client disparities: [0.11043611168861389, 0.05536182224750519], all client accs: [0.4955609142780304, 0.4893154799938202],  alpha_performance: tensor([0.6091, 0.3909], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:58,490 - utils - INFO - stage1_gradient_single_runtime: 0.0023450851440429688
2023-09-28 23:24:58,491 - utils - INFO -  epoch: 41, all client loss: [0.7193207144737244, 0.7581987380981445], all pred client disparities: [0.10237923264503479, 0.049985967576503754], all client disparities: [0.10881245136260986, 0.054331421852111816], all client accs: [0.4955609142780304, 0.48859110474586487],  alpha_performance: tensor([0.6108, 0.3892], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:58,541 - utils - INFO - stage1_gradient_single_runtime: 0.002322673797607422
2023-09-28 23:24:58,542 - utils - INFO -  epoch: 42, all client loss: [0.7193875312805176, 0.7581348419189453], all pred client disparities: [0.1015697717666626, 0.049311600625514984], all client disparities: [0.10758394002914429, 0.053558625280857086], all client accs: [0.49475380778312683, 0.48840999603271484],  alpha_performance: tensor([0.6125, 0.3875], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:58,598 - utils - INFO - stage1_gradient_single_runtime: 0.0023145675659179688
2023-09-28 23:24:58,599 - utils - INFO -  epoch: 43, all client loss: [0.7194529175758362, 0.7580723166465759], all pred client disparities: [0.1007489264011383, 0.048632122576236725], all client disparities: [0.10758394002914429, 0.05227062851190567], all client accs: [0.49475380778312683, 0.48786672949790955],  alpha_performance: tensor([0.6142, 0.3858], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:58,651 - utils - INFO - stage1_gradient_single_runtime: 0.0020411014556884766
2023-09-28 23:24:58,652 - utils - INFO -  epoch: 44, all client loss: [0.7195170521736145, 0.7580111026763916], all pred client disparities: [0.09991636872291565, 0.04794745519757271], all client disparities: [0.10512694716453552, 0.05167163908481598], all client accs: [0.4951573610305786, 0.48732346296310425],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:58,703 - utils - INFO - stage1_gradient_single_runtime: 0.0022993087768554688
2023-09-28 23:24:58,705 - utils - INFO -  epoch: 45, all client loss: [0.7140905261039734, 0.7524274587631226], all pred client disparities: [0.11056101322174072, 0.05481940880417824], all client disparities: [0.12517812848091125, 0.05810539796948433], all client accs: [0.5008071064949036, 0.4916697144508362],  alpha_performance: tensor([0.6112, 0.3888], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:58,822 - utils - INFO - stage1_gradient_single_runtime: 0.003013134002685547
2023-09-28 23:24:58,824 - utils - INFO -  epoch: 46, all client loss: [0.7141578793525696, 0.7523627281188965], all pred client disparities: [0.10985219478607178, 0.05418948829174042], all client disparities: [0.12434479594230652, 0.05681740120053291], all client accs: [0.5, 0.4911264181137085],  alpha_performance: tensor([0.6128, 0.3872], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:58,876 - utils - INFO - stage1_gradient_single_runtime: 0.0021839141845703125
2023-09-28 23:24:58,876 - utils - INFO -  epoch: 47, all client loss: [0.7142241597175598, 0.7522990703582764], all pred client disparities: [0.10913437604904175, 0.05355491861701012], all client disparities: [0.12188780307769775, 0.05578699707984924], all client accs: [0.5004035234451294, 0.4904020428657532],  alpha_performance: tensor([0.6144, 0.3856], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:58,925 - utils - INFO - stage1_gradient_single_runtime: 0.002376556396484375
2023-09-28 23:24:58,926 - utils - INFO -  epoch: 48, all client loss: [0.7142893671989441, 0.7522364854812622], all pred client disparities: [0.10840699076652527, 0.05291562154889107], all client disparities: [0.12311631441116333, 0.0565660260617733], all client accs: [0.49878934025764465, 0.4894965887069702],  alpha_performance: tensor([0.6160, 0.3840], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:58,979 - utils - INFO - stage1_gradient_single_runtime: 0.0022711753845214844
2023-09-28 23:24:58,980 - utils - INFO -  epoch: 49, all client loss: [0.7143533825874329, 0.7521752715110779], all pred client disparities: [0.10766994953155518, 0.0522715300321579], all client disparities: [0.12311631441116333, 0.05630841851234436], all client accs: [0.49838578701019287, 0.48967766761779785],  alpha_performance: tensor([0.6177, 0.3823], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:59,034 - utils - INFO - stage1_gradient_single_runtime: 0.002301454544067383
2023-09-28 23:24:59,034 - utils - INFO -  epoch: 50, all client loss: [0.7144162654876709, 0.7521149516105652], all pred client disparities: [0.10692283511161804, 0.05162256211042404], all client disparities: [0.12188780307769775, 0.05579322576522827], all client accs: [0.49878934025764465, 0.4893154799938202],  alpha_performance: tensor([0.6193, 0.3807], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:59,087 - utils - INFO - stage1_gradient_single_runtime: 0.002229928970336914
2023-09-28 23:24:59,089 - utils - INFO -  epoch: 51, all client loss: [0.7144778966903687, 0.7520560026168823], all pred client disparities: [0.10616537928581238, 0.05096864327788353], all client disparities: [0.11943081021308899, 0.0547628253698349], all client accs: [0.49919289350509644, 0.4887722134590149],  alpha_performance: tensor([0.6210, 0.3790], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:59,141 - utils - INFO - stage1_gradient_single_runtime: 0.003142118453979492
2023-09-28 23:24:59,143 - utils - INFO -  epoch: 52, all client loss: [0.7145383358001709, 0.7519983053207397], all pred client disparities: [0.10539707541465759, 0.05030971020460129], all client disparities: [0.11943081021308899, 0.05424762889742851], all client accs: [0.49878934025764465, 0.48895329236984253],  alpha_performance: tensor([0.6227, 0.3773], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:59,195 - utils - INFO - stage1_gradient_single_runtime: 0.0023322105407714844
2023-09-28 23:24:59,196 - utils - INFO -  epoch: 53, all client loss: [0.7145974040031433, 0.7519419193267822], all pred client disparities: [0.10461768507957458, 0.04964567720890045], all client disparities: [0.11943081021308899, 0.05347483232617378], all client accs: [0.4975786805152893, 0.48859110474586487],  alpha_performance: tensor([0.6244, 0.3756], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:59,250 - utils - INFO - stage1_gradient_single_runtime: 0.0022966861724853516
2023-09-28 23:24:59,251 - utils - INFO -  epoch: 54, all client loss: [0.7146552801132202, 0.7518868446350098], all pred client disparities: [0.1038268506526947, 0.04897649958729744], all client disparities: [0.11943081021308899, 0.05287584662437439], all client accs: [0.4971751272678375, 0.4882289171218872],  alpha_performance: tensor([0.6261, 0.3739], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:59,305 - utils - INFO - stage1_gradient_single_runtime: 0.0022819042205810547
2023-09-28 23:24:59,306 - utils - INFO -  epoch: 55, all client loss: [0.7147117853164673, 0.7518330812454224], all pred client disparities: [0.10302409529685974, 0.048302069306373596], all client disparities: [0.11697378754615784, 0.05142026022076607], all client accs: [0.4979822337627411, 0.48678016662597656],  alpha_performance: tensor([0.6278, 0.3722], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:59,355 - utils - INFO - stage1_gradient_single_runtime: 0.0022230148315429688
2023-09-28 23:24:59,356 - utils - INFO -  epoch: 56, all client loss: [0.7147668600082397, 0.7517808079719543], all pred client disparities: [0.10220891237258911, 0.047622326761484146], all client disparities: [0.11574530601501465, 0.05047988519072533], all client accs: [0.4971751272678375, 0.4853314161300659],  alpha_performance: tensor([0.6295, 0.3705], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:59,406 - utils - INFO - stage1_gradient_single_runtime: 0.002342700958251953
2023-09-28 23:24:59,408 - utils - INFO -  epoch: 57, all client loss: [0.7148205637931824, 0.7517299652099609], all pred client disparities: [0.10138100385665894, 0.04693719744682312], all client disparities: [0.11574530601501465, 0.04988089203834534], all client accs: [0.4959644675254822, 0.4846070408821106],  alpha_performance: tensor([0.6312, 0.3688], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:59,531 - utils - INFO - stage1_gradient_single_runtime: 0.0022118091583251953
2023-09-28 23:24:59,531 - utils - INFO -  epoch: 58, all client loss: [0.7148728370666504, 0.7516804337501526], all pred client disparities: [0.10053971409797668, 0.04624662548303604], all client disparities: [0.11574530601501465, 0.04859289154410362], all client accs: [0.4955609142780304, 0.4838826656341553],  alpha_performance: tensor([0.6330, 0.3670], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:59,586 - utils - INFO - stage1_gradient_single_runtime: 0.002095937728881836
2023-09-28 23:24:59,587 - utils - INFO -  epoch: 59, all client loss: [0.714923620223999, 0.7516326308250427], all pred client disparities: [0.09968465566635132, 0.04555051401257515], all client disparities: [0.11412161588668823, 0.04644831269979477], all client accs: [0.49636802077293396, 0.482252836227417],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:59,604 - utils - INFO - valid: True, epoch: 59, loss: [0.7155672907829285, 0.7494286298751831], accuracy: [0.5119999647140503, 0.4865454435348511], mean_accuracy:0.4992727041244507,variance_accuracy:0.01272726058959961, disparity: [0.08249896764755249, 0.06268735229969025], mean_disparity:0.07259315997362137,variance_disparity:0.009905807673931122, pred_disparity: [0.08420887589454651, 0.05878927558660507]
2023-09-28 23:24:59,618 - utils - INFO - global_valid: True, epoch: 59,  global_loss: 0.7388469576835632, global_accuracy: 0.49794617847138856,  global_disparity:0.05813617259263992, global_pred_disparity: 0.05642714351415634,
2023-09-28 23:24:59,665 - utils - INFO - stage1_gradient_single_runtime: 0.002323150634765625
2023-09-28 23:24:59,666 - utils - INFO -  epoch: 60, all client loss: [0.7094359993934631, 0.7459561228752136], all pred client disparities: [0.11145702004432678, 0.052999041974544525], all client disparities: [0.12675881385803223, 0.056656040251255035], all client accs: [0.5016142129898071, 0.4893154799938202],  alpha_performance: tensor([0.6295, 0.3705], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:59,719 - utils - INFO - stage1_gradient_single_runtime: 0.002282857894897461
2023-09-28 23:24:59,720 - utils - INFO -  epoch: 61, all client loss: [0.709490954875946, 0.7459036707878113], all pred client disparities: [0.11075034737586975, 0.05236457288265228], all client disparities: [0.12759214639663696, 0.05614084377884865], all client accs: [0.5008071064949036, 0.48913437128067017],  alpha_performance: tensor([0.6311, 0.3689], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:59,774 - utils - INFO - stage1_gradient_single_runtime: 0.0022330284118652344
2023-09-28 23:24:59,775 - utils - INFO -  epoch: 62, all client loss: [0.7095446586608887, 0.7458523511886597], all pred client disparities: [0.11003351211547852, 0.051725178956985474], all client disparities: [0.1284254789352417, 0.056057047098875046], all client accs: [0.501210629940033, 0.48913437128067017],  alpha_performance: tensor([0.6327, 0.3673], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:59,823 - utils - INFO - stage1_gradient_single_runtime: 0.0021810531616210938
2023-09-28 23:24:59,825 - utils - INFO -  epoch: 63, all client loss: [0.7095971703529358, 0.7458023428916931], all pred client disparities: [0.10930618643760681, 0.05108078569173813], all client disparities: [0.12719696760177612, 0.055284250527620316], all client accs: [0.501210629940033, 0.48859110474586487],  alpha_performance: tensor([0.6344, 0.3656], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:59,879 - utils - INFO - stage1_gradient_single_runtime: 0.002301454544067383
2023-09-28 23:24:59,881 - utils - INFO -  epoch: 64, all client loss: [0.7096484303474426, 0.7457537651062012], all pred client disparities: [0.10856780409812927, 0.05043131858110428], all client disparities: [0.12719696760177612, 0.055631861090660095], all client accs: [0.5016142129898071, 0.48804783821105957],  alpha_performance: tensor([0.6361, 0.3639], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:59,931 - utils - INFO - stage1_gradient_single_runtime: 0.0023009777069091797
2023-09-28 23:24:59,932 - utils - INFO -  epoch: 65, all client loss: [0.7096982598304749, 0.7457063794136047], all pred client disparities: [0.10781824588775635, 0.049776677042245865], all client disparities: [0.12719696760177612, 0.05408627167344093], all client accs: [0.5008071064949036, 0.4871423542499542],  alpha_performance: tensor([0.6378, 0.3622], device='cuda:0', dtype=torch.float64)
2023-09-28 23:24:59,988 - utils - INFO - stage1_gradient_single_runtime: 0.002812623977661133
2023-09-28 23:24:59,989 - utils - INFO -  epoch: 66, all client loss: [0.7097468376159668, 0.7456604242324829], all pred client disparities: [0.10705685615539551, 0.049116820096969604], all client disparities: [0.12596848607063293, 0.05228307470679283], all client accs: [0.5008071064949036, 0.48605579137802124],  alpha_performance: tensor([0.6395, 0.3605], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:00,041 - utils - INFO - stage1_gradient_single_runtime: 0.0022423267364501953
2023-09-28 23:25:00,042 - utils - INFO -  epoch: 67, all client loss: [0.7097941040992737, 0.7456157207489014], all pred client disparities: [0.10628324747085571, 0.04845166578888893], all client disparities: [0.12473997473716736, 0.05263069272041321], all client accs: [0.501210629940033, 0.48605579137802124],  alpha_performance: tensor([0.6412, 0.3588], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:00,094 - utils - INFO - stage1_gradient_single_runtime: 0.002716064453125
2023-09-28 23:25:00,095 - utils - INFO -  epoch: 68, all client loss: [0.7098398804664612, 0.7455726265907288], all pred client disparities: [0.10549691319465637, 0.04778113216161728], all client disparities: [0.12473997473716736, 0.05108509212732315], all client accs: [0.5016142129898071, 0.4853314161300659],  alpha_performance: tensor([0.6429, 0.3571], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:00,206 - utils - INFO - stage1_gradient_single_runtime: 0.002670764923095703
2023-09-28 23:25:00,208 - utils - INFO -  epoch: 69, all client loss: [0.7098842859268188, 0.7455308437347412], all pred client disparities: [0.10469725728034973, 0.04710514843463898], all client disparities: [0.12473997473716736, 0.04919810965657234], all client accs: [0.5016142129898071, 0.48370158672332764],  alpha_performance: tensor([0.6447, 0.3553], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:00,262 - utils - INFO - stage1_gradient_single_runtime: 0.0022161006927490234
2023-09-28 23:25:00,263 - utils - INFO -  epoch: 70, all client loss: [0.7099272012710571, 0.7454906105995178], all pred client disparities: [0.10388389229774475, 0.04642366245388985], all client disparities: [0.12473997473716736, 0.047826316207647324], all client accs: [0.501210629940033, 0.48243391513824463],  alpha_performance: tensor([0.6465, 0.3535], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:00,313 - utils - INFO - stage1_gradient_single_runtime: 0.0022950172424316406
2023-09-28 23:25:00,314 - utils - INFO -  epoch: 71, all client loss: [0.709968626499176, 0.7454518675804138], all pred client disparities: [0.10305622220039368, 0.04573656991124153], all client disparities: [0.12473997473716736, 0.04619693011045456], all client accs: [0.4995964467525482, 0.4811662435531616],  alpha_performance: tensor([0.6482, 0.3518], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:00,366 - utils - INFO - stage1_gradient_single_runtime: 0.0022895336151123047
2023-09-28 23:25:00,367 - utils - INFO -  epoch: 72, all client loss: [0.7100085020065308, 0.7454147338867188], all pred client disparities: [0.1022135317325592, 0.045043811202049255], all client disparities: [0.12473997473716736, 0.045945558696985245], all client accs: [0.5, 0.47953641414642334],  alpha_performance: tensor([0.6500, 0.3500], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:00,418 - utils - INFO - stage1_gradient_single_runtime: 0.0023086071014404297
2023-09-28 23:25:00,420 - utils - INFO -  epoch: 73, all client loss: [0.7100467681884766, 0.7453792095184326], all pred client disparities: [0.10135534405708313, 0.04434533417224884], all client disparities: [0.12473997473716736, 0.0456879585981369], all client accs: [0.5, 0.4793553352355957],  alpha_performance: tensor([0.6519, 0.3481], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:00,473 - utils - INFO - stage1_gradient_single_runtime: 0.0022432804107666016
2023-09-28 23:25:00,474 - utils - INFO -  epoch: 74, all client loss: [0.7100834846496582, 0.7453453540802002], all pred client disparities: [0.1004808247089386, 0.043641068041324615], all client disparities: [0.12351146340370178, 0.04500517621636391], all client accs: [0.5008071064949036, 0.4780876636505127],  alpha_performance: tensor([0.6537, 0.3463], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:00,527 - utils - INFO - stage1_gradient_single_runtime: 0.0020089149475097656
2023-09-28 23:25:00,528 - utils - INFO -  epoch: 75, all client loss: [0.7101185321807861, 0.7453129887580872], all pred client disparities: [0.09958931803703308, 0.04293092340230942], all client disparities: [0.12351146340370178, 0.0448375940322876], all client accs: [0.5008071064949036, 0.4773632884025574],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:00,580 - utils - INFO - stage1_gradient_single_runtime: 0.0023622512817382812
2023-09-28 23:25:00,580 - utils - INFO -  epoch: 76, all client loss: [0.7045716047286987, 0.739540696144104], all pred client disparities: [0.11278516054153442, 0.051028210669755936], all client disparities: [0.1369819939136505, 0.053487278521060944], all client accs: [0.509685218334198, 0.4862368702888489],  alpha_performance: tensor([0.6495, 0.3505], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:00,634 - utils - INFO - stage1_gradient_single_runtime: 0.0023696422576904297
2023-09-28 23:25:00,635 - utils - INFO -  epoch: 77, all client loss: [0.7046118974685669, 0.7395026683807373], all pred client disparities: [0.11207658052444458, 0.050387296825647354], all client disparities: [0.1382105052471161, 0.053319696336984634], all client accs: [0.5080710053443909, 0.4853314161300659],  alpha_performance: tensor([0.6511, 0.3489], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:00,690 - utils - INFO - stage1_gradient_single_runtime: 0.0029668807983398438
2023-09-28 23:25:00,691 - utils - INFO -  epoch: 78, all client loss: [0.70465087890625, 0.7394661903381348], all pred client disparities: [0.11135625839233398, 0.04974113404750824], all client disparities: [0.1369819939136505, 0.05289451405405998], all client accs: [0.5092816352844238, 0.48442596197128296],  alpha_performance: tensor([0.6528, 0.3472], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:00,745 - utils - INFO - stage1_gradient_single_runtime: 0.002489328384399414
2023-09-28 23:25:00,747 - utils - INFO -  epoch: 79, all client loss: [0.7046884894371033, 0.7394309043884277], all pred client disparities: [0.11062371730804443, 0.04908967390656471], all client disparities: [0.13575348258018494, 0.05246932804584503], all client accs: [0.5088781118392944, 0.4835204780101776],  alpha_performance: tensor([0.6545, 0.3455], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:00,765 - utils - INFO - valid: True, epoch: 79, loss: [0.7099528908729553, 0.7424744367599487], accuracy: [0.5199999809265137, 0.47781816124916077], mean_accuracy:0.4989090710878372,variance_accuracy:0.021090909838676453, disparity: [0.09230288863182068, 0.05712791904807091], mean_disparity:0.0747154038399458,variance_disparity:0.017587484791874886, pred_disparity: [0.08459421992301941, 0.05359809845685959]
2023-09-28 23:25:00,776 - utils - INFO - global_valid: True, epoch: 79,  global_loss: 0.7323115468025208, global_accuracy: 0.49483693477390955,  global_disparity:0.05620740354061127, global_pred_disparity: 0.05275421589612961,
2023-09-28 23:25:00,824 - utils - INFO - stage1_gradient_single_runtime: 0.002332448959350586
2023-09-28 23:25:00,826 - utils - INFO -  epoch: 80, all client loss: [0.7047247290611267, 0.7393971681594849], all pred client disparities: [0.10987842082977295, 0.04843283072113991], all client disparities: [0.13575348258018494, 0.05238553509116173], all client accs: [0.5080710053443909, 0.48315829038619995],  alpha_performance: tensor([0.6562, 0.3438], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:00,879 - utils - INFO - stage1_gradient_single_runtime: 0.0025849342346191406
2023-09-28 23:25:00,881 - utils - INFO -  epoch: 81, all client loss: [0.7047594785690308, 0.7393648028373718], all pred client disparities: [0.10911992192268372, 0.04777054488658905], all client disparities: [0.13575348258018494, 0.05178654566407204], all client accs: [0.508474588394165, 0.4829772114753723],  alpha_performance: tensor([0.6580, 0.3420], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:00,933 - utils - INFO - stage1_gradient_single_runtime: 0.0022118091583251953
2023-09-28 23:25:00,934 - utils - INFO -  epoch: 82, all client loss: [0.7047927975654602, 0.739333987236023], all pred client disparities: [0.10834753513336182, 0.04710272699594498], all client disparities: [0.1349201500415802, 0.05049855262041092], all client accs: [0.508474588394165, 0.48207172751426697],  alpha_performance: tensor([0.6597, 0.3403], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:01,052 - utils - INFO - stage1_gradient_single_runtime: 0.002341032028198242
2023-09-28 23:25:01,053 - utils - INFO -  epoch: 83, all client loss: [0.704824686050415, 0.7393046021461487], all pred client disparities: [0.10756060481071472, 0.046429336071014404], all client disparities: [0.1349201500415802, 0.04938436299562454], all client accs: [0.5080710053443909, 0.480985164642334],  alpha_performance: tensor([0.6615, 0.3385], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:01,106 - utils - INFO - stage1_gradient_single_runtime: 0.002325296401977539
2023-09-28 23:25:01,108 - utils - INFO -  epoch: 84, all client loss: [0.7048550248146057, 0.7392768263816833], all pred client disparities: [0.10675859451293945, 0.04575030133128166], all client disparities: [0.13408681750297546, 0.047065965831279755], all client accs: [0.5076674818992615, 0.47953641414642334],  alpha_performance: tensor([0.6633, 0.3367], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:01,163 - utils - INFO - stage1_gradient_single_runtime: 0.0025441646575927734
2023-09-28 23:25:01,164 - utils - INFO -  epoch: 85, all client loss: [0.7048838138580322, 0.7392506003379822], all pred client disparities: [0.10594087839126587, 0.04506558179855347], all client disparities: [0.13285833597183228, 0.045520372688770294], all client accs: [0.5080710053443909, 0.4786309599876404],  alpha_performance: tensor([0.6651, 0.3349], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:01,217 - utils - INFO - stage1_gradient_single_runtime: 0.0025031566619873047
2023-09-28 23:25:01,218 - utils - INFO -  epoch: 86, all client loss: [0.7049111127853394, 0.7392259240150452], all pred client disparities: [0.1051066517829895, 0.04437508061528206], all client disparities: [0.1316298246383667, 0.04509519413113594], all client accs: [0.5076674818992615, 0.4773632884025574],  alpha_performance: tensor([0.6670, 0.3330], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:01,268 - utils - INFO - stage1_gradient_single_runtime: 0.0025675296783447266
2023-09-28 23:25:01,270 - utils - INFO -  epoch: 87, all client loss: [0.7049368023872375, 0.7392028570175171], all pred client disparities: [0.10425511002540588, 0.043678782880306244], all client disparities: [0.1316298246383667, 0.04449619725346565], all client accs: [0.508474588394165, 0.47663891315460205],  alpha_performance: tensor([0.6688, 0.3312], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:01,321 - utils - INFO - stage1_gradient_single_runtime: 0.0022683143615722656
2023-09-28 23:25:01,322 - utils - INFO -  epoch: 88, all client loss: [0.704960823059082, 0.7391814589500427], all pred client disparities: [0.10338565707206726, 0.04297662526369095], all client disparities: [0.13123464584350586, 0.04312441125512123], all client accs: [0.509685218334198, 0.47591453790664673],  alpha_performance: tensor([0.6707, 0.3293], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:01,377 - utils - INFO - stage1_gradient_single_runtime: 0.0029044151306152344
2023-09-28 23:25:01,378 - utils - INFO -  epoch: 89, all client loss: [0.7049832344055176, 0.7391617298126221], all pred client disparities: [0.10249736160039902, 0.04226856306195259], all client disparities: [0.13040131330490112, 0.04072222858667374], all client accs: [0.5088781118392944, 0.4741035997867584],  alpha_performance: tensor([0.6726, 0.3274], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:01,430 - utils - INFO - stage1_gradient_single_runtime: 0.0021696090698242188
2023-09-28 23:25:01,432 - utils - INFO -  epoch: 90, all client loss: [0.7050039768218994, 0.7391436100006104], all pred client disparities: [0.10158941149711609, 0.04155457392334938], all client disparities: [0.13040131330490112, 0.04038083925843239], all client accs: [0.509685218334198, 0.4735603332519531],  alpha_performance: tensor([0.6745, 0.3255], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:01,480 - utils - INFO - stage1_gradient_single_runtime: 0.0022170543670654297
2023-09-28 23:25:01,481 - utils - INFO -  epoch: 91, all client loss: [0.7050229907035828, 0.7391273975372314], all pred client disparities: [0.1006607711315155, 0.04083459824323654], all client disparities: [0.12917283177375793, 0.040123239159584045], all client accs: [0.5100887417793274, 0.4735603332519531],  alpha_performance: tensor([0.6764, 0.3236], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:01,532 - utils - INFO - stage1_gradient_single_runtime: 0.0021665096282958984
2023-09-28 23:25:01,533 - utils - INFO -  epoch: 92, all client loss: [0.7050402760505676, 0.739112913608551], all pred client disparities: [0.09971043467521667, 0.04010865092277527], all client disparities: [0.13040131330490112, 0.03849385306239128], all client accs: [0.5100887417793274, 0.47193047404289246],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:01,584 - utils - INFO - stage1_gradient_single_runtime: 0.002304553985595703
2023-09-28 23:25:01,585 - utils - INFO -  epoch: 93, all client loss: [0.6994404196739197, 0.7332451343536377], all pred client disparities: [0.1147269606590271, 0.0489254966378212], all client disparities: [0.14430999755859375, 0.05144515633583069], all client accs: [0.5197740197181702, 0.48189061880111694],  alpha_performance: tensor([0.6713, 0.3287], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:01,641 - utils - INFO - stage1_gradient_single_runtime: 0.002537250518798828
2023-09-28 23:25:01,642 - utils - INFO -  epoch: 94, all client loss: [0.6994637846946716, 0.7332239747047424], all pred client disparities: [0.1140080988407135, 0.04827573150396347], all client disparities: [0.143476665019989, 0.05041475594043732], all client accs: [0.5197740197181702, 0.4811662435531616],  alpha_performance: tensor([0.6730, 0.3270], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:01,749 - utils - INFO - stage1_gradient_single_runtime: 0.0026917457580566406
2023-09-28 23:25:01,752 - utils - INFO -  epoch: 95, all client loss: [0.6994857788085938, 0.7332043647766113], all pred client disparities: [0.11327499151229858, 0.04762042313814163], all client disparities: [0.143476665019989, 0.049815770238637924], all client accs: [0.5201775431632996, 0.48080408573150635],  alpha_performance: tensor([0.6747, 0.3253], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:01,804 - utils - INFO - stage1_gradient_single_runtime: 0.0022852420806884766
2023-09-28 23:25:01,805 - utils - INFO -  epoch: 96, all client loss: [0.6995062828063965, 0.7331862449645996], all pred client disparities: [0.11252707242965698, 0.04695954918861389], all client disparities: [0.1447051763534546, 0.049216777086257935], all client accs: [0.5205811262130737, 0.48026078939437866],  alpha_performance: tensor([0.6765, 0.3235], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:01,862 - utils - INFO - stage1_gradient_single_runtime: 0.0022377967834472656
2023-09-28 23:25:01,862 - utils - INFO -  epoch: 97, all client loss: [0.6995252370834351, 0.7331695556640625], all pred client disparities: [0.11176368594169617, 0.04629305377602577], all client disparities: [0.1447051763534546, 0.04818638414144516], all client accs: [0.5213881731033325, 0.479898601770401],  alpha_performance: tensor([0.6782, 0.3218], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:01,913 - utils - INFO - stage1_gradient_single_runtime: 0.002167940139770508
2023-09-28 23:25:01,914 - utils - INFO -  epoch: 98, all client loss: [0.699542760848999, 0.7331544756889343], all pred client disparities: [0.1109839677810669, 0.04562089219689369], all client disparities: [0.1447051763534546, 0.04638318717479706], all client accs: [0.5213881731033325, 0.4786309599876404],  alpha_performance: tensor([0.6800, 0.3200], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:01,965 - utils - INFO - stage1_gradient_single_runtime: 0.002302885055541992
2023-09-28 23:25:01,966 - utils - INFO -  epoch: 99, all client loss: [0.6995587944984436, 0.7331408262252808], all pred client disparities: [0.11018729209899902, 0.04494301974773407], all client disparities: [0.1447051763534546, 0.04501140117645264], all client accs: [0.5217917561531067, 0.47718220949172974],  alpha_performance: tensor([0.6818, 0.3182], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:01,985 - utils - INFO - valid: True, epoch: 99, loss: [0.7038605213165283, 0.735876202583313], accuracy: [0.5343999862670898, 0.4698181748390198], mean_accuracy:0.5021090805530548,variance_accuracy:0.032290905714035034, disparity: [0.09230288863182068, 0.06345415860414505], mean_disparity:0.07787852361798286,variance_disparity:0.014424365013837814, pred_disparity: [0.08633768558502197, 0.048845499753952026]
2023-09-28 23:25:01,996 - utils - INFO - global_valid: True, epoch: 99,  global_loss: 0.7258713841438293, global_accuracy: 0.4936284513805522,  global_disparity:0.060812339186668396, global_pred_disparity: 0.04987293481826782,
2023-09-28 23:25:02,047 - utils - INFO - stage1_gradient_single_runtime: 0.0023584365844726562
2023-09-28 23:25:02,048 - utils - INFO -  epoch: 100, all client loss: [0.6995732188224792, 0.7331288456916809], all pred client disparities: [0.10937285423278809, 0.044259414076805115], all client disparities: [0.14593368768692017, 0.04286681115627289], all client accs: [0.5225988626480103, 0.47555235028266907],  alpha_performance: tensor([0.6837, 0.3163], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:02,100 - utils - INFO - stage1_gradient_single_runtime: 0.002742767333984375
2023-09-28 23:25:02,101 - utils - INFO -  epoch: 101, all client loss: [0.6995860934257507, 0.7331184148788452], all pred client disparities: [0.10853984951972961, 0.04357002303004265], all client disparities: [0.14716216921806335, 0.041063617914915085], all client accs: [0.5225988626480103, 0.47482797503471375],  alpha_performance: tensor([0.6855, 0.3145], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:02,150 - utils - INFO - stage1_gradient_single_runtime: 0.0025243759155273438
2023-09-28 23:25:02,151 - utils - INFO -  epoch: 102, all client loss: [0.6995974779129028, 0.7331095933914185], all pred client disparities: [0.10768726468086243, 0.042874861508607864], all client disparities: [0.14716216921806335, 0.03917663171887398], all client accs: [0.5238094925880432, 0.4731981158256531],  alpha_performance: tensor([0.6874, 0.3126], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:02,203 - utils - INFO - stage1_gradient_single_runtime: 0.0024003982543945312
2023-09-28 23:25:02,204 - utils - INFO -  epoch: 103, all client loss: [0.6996071338653564, 0.7331024408340454], all pred client disparities: [0.10681435465812683, 0.04217388108372688], all client disparities: [0.1496191918849945, 0.03909284248948097], all client accs: [0.5225988626480103, 0.47301703691482544],  alpha_performance: tensor([0.6893, 0.3107], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:02,262 - utils - INFO - stage1_gradient_single_runtime: 0.002796649932861328
2023-09-28 23:25:02,264 - utils - INFO -  epoch: 104, all client loss: [0.6996152997016907, 0.7330968379974365], all pred client disparities: [0.10592001676559448, 0.04146710783243179], all client disparities: [0.1496191918849945, 0.03789485991001129], all client accs: [0.5230023860931396, 0.47138720750808716],  alpha_performance: tensor([0.6912, 0.3088], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:02,317 - utils - INFO - stage1_gradient_single_runtime: 0.002420186996459961
2023-09-28 23:25:02,318 - utils - INFO -  epoch: 105, all client loss: [0.6996216773986816, 0.7330929636955261], all pred client disparities: [0.10500329732894897, 0.0407545231282711], all client disparities: [0.1496191918849945, 0.03686446696519852], all client accs: [0.5246165990829468, 0.4710249900817871],  alpha_performance: tensor([0.6931, 0.3069], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:02,428 - utils - INFO - stage1_gradient_single_runtime: 0.0023870468139648438
2023-09-28 23:25:02,429 - utils - INFO -  epoch: 106, all client loss: [0.6996265053749084, 0.7330907583236694], all pred client disparities: [0.10406318306922913, 0.0400361530482769], all client disparities: [0.1496191918849945, 0.03531886637210846], all client accs: [0.5254237055778503, 0.47011953592300415],  alpha_performance: tensor([0.6951, 0.3049], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:02,488 - utils - INFO - stage1_gradient_single_runtime: 0.0033833980560302734
2023-09-28 23:25:02,489 - utils - INFO -  epoch: 107, all client loss: [0.6996297836303711, 0.7330902218818665], all pred client disparities: [0.10309851169586182, 0.03931201621890068], all client disparities: [0.15207618474960327, 0.03394708037376404], all client accs: [0.5254237055778503, 0.46903297305107117],  alpha_performance: tensor([0.6970, 0.3030], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:02,542 - utils - INFO - stage1_gradient_single_runtime: 0.002138853073120117
2023-09-28 23:25:02,542 - utils - INFO -  epoch: 108, all client loss: [0.6996312737464905, 0.733091413974762], all pred client disparities: [0.10210809856653214, 0.03858218342065811], all client disparities: [0.15330469608306885, 0.033006701618433], all client accs: [0.5242130756378174, 0.46776533126831055],  alpha_performance: tensor([0.6990, 0.3010], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:02,592 - utils - INFO - stage1_gradient_single_runtime: 0.002296924591064453
2023-09-28 23:25:02,594 - utils - INFO -  epoch: 109, all client loss: [0.6996310353279114, 0.7330942749977112], all pred client disparities: [0.10109078884124756, 0.03784665837883949], all client disparities: [0.15286648273468018, 0.03266531229019165], all client accs: [0.5238094925880432, 0.46722203493118286],  alpha_performance: tensor([0.7010, 0.2990], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:02,645 - utils - INFO - stage1_gradient_single_runtime: 0.002353668212890625
2023-09-28 23:25:02,645 - utils - INFO -  epoch: 110, all client loss: [0.6996291875839233, 0.7330989241600037], all pred client disparities: [0.10004538297653198, 0.03710555657744408], all client disparities: [0.15286648273468018, 0.0308621134608984], all client accs: [0.5258272886276245, 0.46649765968322754],  alpha_performance: tensor([0.7030, 0.2970], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:02,699 - utils - INFO - stage1_gradient_single_runtime: 0.0025396347045898438
2023-09-28 23:25:02,700 - utils - INFO -  epoch: 111, all client loss: [0.6996256113052368, 0.7331053018569946], all pred client disparities: [0.09897038340568542, 0.03635892644524574], all client disparities: [0.15080466866493225, 0.029232727363705635], all client accs: [0.5258272886276245, 0.46522998809814453],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:02,757 - utils - INFO - stage1_gradient_single_runtime: 0.002193450927734375
2023-09-28 23:25:02,758 - utils - INFO -  epoch: 112, all client loss: [0.6939606070518494, 0.7271192669868469], all pred client disparities: [0.11667463183403015, 0.046001192182302475], all client disparities: [0.1598423421382904, 0.04467000812292099], all client accs: [0.5427764058113098, 0.47663891315460205],  alpha_performance: tensor([0.6968, 0.3032], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:02,807 - utils - INFO - stage1_gradient_single_runtime: 0.002273082733154297
2023-09-28 23:25:02,808 - utils - INFO -  epoch: 113, all client loss: [0.6939632296562195, 0.7271189093589783], all pred client disparities: [0.11590844392776489, 0.045333679765462875], all client disparities: [0.1598423421382904, 0.04355581849813461], all client accs: [0.5427764058113098, 0.47591453790664673],  alpha_performance: tensor([0.6986, 0.3014], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:02,860 - utils - INFO - stage1_gradient_single_runtime: 0.0022068023681640625
2023-09-28 23:25:02,861 - utils - INFO -  epoch: 114, all client loss: [0.6939643025398254, 0.727120041847229], all pred client disparities: [0.1151232123374939, 0.0446605384349823], all client disparities: [0.16146600246429443, 0.042441632598638535], all client accs: [0.5419692993164062, 0.4751901626586914],  alpha_performance: tensor([0.7004, 0.2996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:02,911 - utils - INFO - stage1_gradient_single_runtime: 0.0022499561309814453
2023-09-28 23:25:02,912 - utils - INFO -  epoch: 115, all client loss: [0.6939639449119568, 0.7271226644515991], all pred client disparities: [0.11431819200515747, 0.04398173838853836], all client disparities: [0.16146600246429443, 0.04063843563199043], all client accs: [0.5435835123062134, 0.4744657874107361],  alpha_performance: tensor([0.7022, 0.2978], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:02,970 - utils - INFO - stage1_gradient_single_runtime: 0.002500772476196289
2023-09-28 23:25:02,972 - utils - INFO -  epoch: 116, all client loss: [0.6939620971679688, 0.7271268963813782], all pred client disparities: [0.11349239945411682, 0.043297309428453445], all client disparities: [0.1606326699256897, 0.038751453161239624], all client accs: [0.543179988861084, 0.4728359580039978],  alpha_performance: tensor([0.7040, 0.2960], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:03,027 - utils - INFO - stage1_gradient_single_runtime: 0.002565622329711914
2023-09-28 23:25:03,029 - utils - INFO -  epoch: 117, all client loss: [0.6939586997032166, 0.7271326184272766], all pred client disparities: [0.11264479160308838, 0.04260728135704994], all client disparities: [0.16186115145683289, 0.036606866866350174], all client accs: [0.5443906188011169, 0.4710249900817871],  alpha_performance: tensor([0.7059, 0.2941], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:03,177 - utils - INFO - stage1_gradient_single_runtime: 0.002572774887084961
2023-09-28 23:25:03,179 - utils - INFO -  epoch: 118, all client loss: [0.6939538717269897, 0.7271398305892944], all pred client disparities: [0.11177444458007812, 0.041911665350198746], all client disparities: [0.16102781891822815, 0.0355764664709568], all client accs: [0.5443906188011169, 0.47066283226013184],  alpha_performance: tensor([0.7077, 0.2923], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:03,237 - utils - INFO - stage1_gradient_single_runtime: 0.002207040786743164
2023-09-28 23:25:03,238 - utils - INFO -  epoch: 119, all client loss: [0.693947434425354, 0.727148711681366], all pred client disparities: [0.11088022589683533, 0.04121050983667374], all client disparities: [0.16225633025169373, 0.03420468047261238], all client accs: [0.5456012487411499, 0.4697573482990265],  alpha_performance: tensor([0.7096, 0.2904], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:03,254 - utils - INFO - valid: True, epoch: 119, loss: [0.6972435116767883, 0.7296414971351624], accuracy: [0.5503999590873718, 0.46109089255332947], mean_accuracy:0.5057454258203506,variance_accuracy:0.04465453326702118, disparity: [0.11462244391441345, 0.043454162776470184], mean_disparity:0.07903830334544182,variance_disparity:0.035584140568971634, pred_disparity: [0.0898655354976654, 0.04460684955120087]
2023-09-28 23:25:03,265 - utils - INFO - global_valid: True, epoch: 119,  global_loss: 0.7195171117782593, global_accuracy: 0.49511304521808724,  global_disparity:0.05119261145591736, global_pred_disparity: 0.04799190163612366,
2023-09-28 23:25:03,315 - utils - INFO - stage1_gradient_single_runtime: 0.002569913864135742
2023-09-28 23:25:03,316 - utils - INFO -  epoch: 120, all client loss: [0.6939394474029541, 0.7271590828895569], all pred client disparities: [0.10996103286743164, 0.04050388187170029], all client disparities: [0.16304665803909302, 0.03223390504717827], all client accs: [0.5451977252960205, 0.4675842225551605],  alpha_performance: tensor([0.7115, 0.2885], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:03,365 - utils - INFO - stage1_gradient_single_runtime: 0.0033888816833496094
2023-09-28 23:25:03,366 - utils - INFO -  epoch: 121, all client loss: [0.6939300298690796, 0.7271709442138672], all pred client disparities: [0.10901570320129395, 0.03979184105992317], all client disparities: [0.1638370156288147, 0.03206631913781166], all client accs: [0.5447942018508911, 0.4668598473072052],  alpha_performance: tensor([0.7134, 0.2866], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:03,417 - utils - INFO - stage1_gradient_single_runtime: 0.0027141571044921875
2023-09-28 23:25:03,418 - utils - INFO -  epoch: 122, all client loss: [0.6939190626144409, 0.7271844744682312], all pred client disparities: [0.10804304480552673, 0.039074480533599854], all client disparities: [0.1638370156288147, 0.031125934794545174], all client accs: [0.5460048317909241, 0.4657732844352722],  alpha_performance: tensor([0.7153, 0.2847], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:03,479 - utils - INFO - stage1_gradient_single_runtime: 0.002183675765991211
2023-09-28 23:25:03,480 - utils - INFO -  epoch: 123, all client loss: [0.6939066648483276, 0.7271994352340698], all pred client disparities: [0.10704183578491211, 0.03835189715027809], all client disparities: [0.16256549954414368, 0.030269348993897438], all client accs: [0.5456012487411499, 0.46486783027648926],  alpha_performance: tensor([0.7173, 0.2827], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:03,528 - utils - INFO - stage1_gradient_single_runtime: 0.0023102760314941406
2023-09-28 23:25:03,529 - utils - INFO -  epoch: 124, all client loss: [0.6938926577568054, 0.7272160053253174], all pred client disparities: [0.10601061582565308, 0.037624210119247437], all client disparities: [0.16252252459526062, 0.028124762699007988], all client accs: [0.5443906188011169, 0.4628757834434509],  alpha_performance: tensor([0.7193, 0.2807], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:03,576 - utils - INFO - stage1_gradient_single_runtime: 0.002204418182373047
2023-09-28 23:25:03,578 - utils - INFO -  epoch: 125, all client loss: [0.6938772201538086, 0.7272341251373291], all pred client disparities: [0.10494834184646606, 0.036891575902700424], all client disparities: [0.16208434104919434, 0.027094366028904915], all client accs: [0.5443906188011169, 0.4628757834434509],  alpha_performance: tensor([0.7212, 0.2788], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:03,631 - utils - INFO - stage1_gradient_single_runtime: 0.002604961395263672
2023-09-28 23:25:03,633 - utils - INFO -  epoch: 126, all client loss: [0.6938602924346924, 0.7272536754608154], all pred client disparities: [0.10385337471961975, 0.0361541248857975], all client disparities: [0.16164618730545044, 0.02701057493686676], all client accs: [0.5460048317909241, 0.46233248710632324],  alpha_performance: tensor([0.7232, 0.2768], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:03,690 - utils - INFO - stage1_gradient_single_runtime: 0.002633810043334961
2023-09-28 23:25:03,692 - utils - INFO -  epoch: 127, all client loss: [0.6938419342041016, 0.7272747755050659], all pred client disparities: [0.10272449254989624, 0.03541204333305359], all client disparities: [0.16326984763145447, 0.026070190593600273], all client accs: [0.5476190447807312, 0.4608837366104126],  alpha_performance: tensor([0.7252, 0.2748], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:03,741 - utils - INFO - stage1_gradient_single_runtime: 0.0022814273834228516
2023-09-28 23:25:03,742 - utils - INFO -  epoch: 128, all client loss: [0.6938220858573914, 0.7272973656654358], all pred client disparities: [0.1015600860118866, 0.034665513783693314], all client disparities: [0.161603182554245, 0.02487221173942089], all client accs: [0.5480225682258606, 0.45943498611450195],  alpha_performance: tensor([0.7272, 0.2728], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:03,791 - utils - INFO - stage1_gradient_single_runtime: 0.002227306365966797
2023-09-28 23:25:03,792 - utils - INFO -  epoch: 129, all client loss: [0.6938008069992065, 0.7273213863372803], all pred client disparities: [0.10035884380340576, 0.03391478210687637], all client disparities: [0.1611650288105011, 0.023584214970469475], all client accs: [0.5480225682258606, 0.458529531955719],  alpha_performance: tensor([0.7293, 0.2707], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:03,893 - utils - INFO - stage1_gradient_single_runtime: 0.0022726058959960938
2023-09-28 23:25:03,894 - utils - INFO -  epoch: 130, all client loss: [0.6937781572341919, 0.7273468971252441], all pred client disparities: [0.09911912679672241, 0.03316008299589157], all client disparities: [0.1607268750667572, 0.02272762358188629], all client accs: [0.5500403642654419, 0.45762407779693604],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:03,954 - utils - INFO - stage1_gradient_single_runtime: 0.0024950504302978516
2023-09-28 23:25:03,955 - utils - INFO -  epoch: 131, all client loss: [0.68808913230896, 0.7212774753570557], all pred client disparities: [0.11998459696769714, 0.043609242886304855], all client disparities: [0.17064085602760315, 0.036960702389478683], all client accs: [0.5682001709938049, 0.4703006148338318],  alpha_performance: tensor([0.7222, 0.2778], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:04,007 - utils - INFO - stage1_gradient_single_runtime: 0.0021927356719970703
2023-09-28 23:25:04,008 - utils - INFO -  epoch: 132, all client loss: [0.6880704164505005, 0.7212983965873718], all pred client disparities: [0.11914229393005371, 0.042925965040922165], all client disparities: [0.17020270228385925, 0.034642308950424194], all client accs: [0.5682001709938049, 0.46903297305107117],  alpha_performance: tensor([0.7240, 0.2760], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:04,060 - utils - INFO - stage1_gradient_single_runtime: 0.002245664596557617
2023-09-28 23:25:04,061 - utils - INFO -  epoch: 133, all client loss: [0.6880503296852112, 0.7213208079338074], all pred client disparities: [0.11827456951141357, 0.04223741963505745], all client disparities: [0.17143121361732483, 0.0322401262819767], all client accs: [0.5702179074287415, 0.4668598473072052],  alpha_performance: tensor([0.7258, 0.2742], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:04,117 - utils - INFO - stage1_gradient_single_runtime: 0.003282785415649414
2023-09-28 23:25:04,118 - utils - INFO -  epoch: 134, all client loss: [0.6880288124084473, 0.7213446497917175], all pred client disparities: [0.11738026142120361, 0.04154369607567787], all client disparities: [0.17222154140472412, 0.029664132744073868], all client accs: [0.5690072178840637, 0.46541109681129456],  alpha_performance: tensor([0.7276, 0.2724], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:04,174 - utils - INFO - stage1_gradient_single_runtime: 0.002178668975830078
2023-09-28 23:25:04,175 - utils - INFO -  epoch: 135, all client loss: [0.6880059242248535, 0.7213698029518127], all pred client disparities: [0.11645811796188354, 0.04084492474794388], all client disparities: [0.17138820886611938, 0.029065143316984177], all client accs: [0.5694108009338379, 0.4645056128501892],  alpha_performance: tensor([0.7294, 0.2706], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:04,226 - utils - INFO - stage1_gradient_single_runtime: 0.0031359195709228516
2023-09-28 23:25:04,227 - utils - INFO -  epoch: 136, all client loss: [0.6879817843437195, 0.7213963866233826], all pred client disparities: [0.11550694704055786, 0.04014121741056442], all client disparities: [0.17217853665351868, 0.028639962896704674], all client accs: [0.5702179074287415, 0.46360015869140625],  alpha_performance: tensor([0.7312, 0.2688], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:04,277 - utils - INFO - stage1_gradient_single_runtime: 0.0022325515747070312
2023-09-28 23:25:04,277 - utils - INFO -  epoch: 137, all client loss: [0.6879561543464661, 0.7214243412017822], all pred client disparities: [0.11452552676200867, 0.03943272680044174], all client disparities: [0.17498773336410522, 0.027268171310424805], all client accs: [0.5694108009338379, 0.46251359581947327],  alpha_performance: tensor([0.7330, 0.2670], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:04,327 - utils - INFO - stage1_gradient_single_runtime: 0.0022144317626953125
2023-09-28 23:25:04,328 - utils - INFO -  epoch: 138, all client loss: [0.6879292726516724, 0.7214536666870117], all pred client disparities: [0.11351242661476135, 0.03871961683034897], all client disparities: [0.17332106828689575, 0.026926781982183456], all client accs: [0.5702179074287415, 0.46233248710632324],  alpha_performance: tensor([0.7349, 0.2651], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:04,383 - utils - INFO - stage1_gradient_single_runtime: 0.0021758079528808594
2023-09-28 23:25:04,385 - utils - INFO -  epoch: 139, all client loss: [0.6879011392593384, 0.7214843034744263], all pred client disparities: [0.11246639490127563, 0.03800206258893013], all client disparities: [0.17288288474082947, 0.026334013789892197], all client accs: [0.5698143243789673, 0.45997828245162964],  alpha_performance: tensor([0.7367, 0.2633], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:04,403 - utils - INFO - valid: True, epoch: 139, loss: [0.6901542544364929, 0.723801851272583], accuracy: [0.585599958896637, 0.45236361026763916], mean_accuracy:0.5189817845821381,variance_accuracy:0.0666181743144989, disparity: [0.12546932697296143, 0.03202857822179794], mean_disparity:0.07874895259737968,variance_disparity:0.04672037437558174, pred_disparity: [0.09567070007324219, 0.04105263575911522]
2023-09-28 23:25:04,416 - utils - INFO - global_valid: True, epoch: 139,  global_loss: 0.7132869958877563, global_accuracy: 0.5006462585034014,  global_disparity:0.04571171849966049, global_pred_disparity: 0.04742145538330078,
2023-09-28 23:25:04,463 - utils - INFO - stage1_gradient_single_runtime: 0.00225067138671875
2023-09-28 23:25:04,464 - utils - INFO -  epoch: 140, all client loss: [0.6878716945648193, 0.7215161919593811], all pred client disparities: [0.11138612031936646, 0.03728029504418373], all client disparities: [0.17200657725334167, 0.025477424263954163], all client accs: [0.5714285373687744, 0.45889171957969666],  alpha_performance: tensor([0.7386, 0.2614], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:04,515 - utils - INFO - stage1_gradient_single_runtime: 0.0022149085998535156
2023-09-28 23:25:04,516 - utils - INFO -  epoch: 141, all client loss: [0.6878410577774048, 0.721549391746521], all pred client disparities: [0.11027020215988159, 0.03655451908707619], all client disparities: [0.1769205629825592, 0.02521982602775097], all client accs: [0.5734463334083557, 0.45871061086654663],  alpha_performance: tensor([0.7405, 0.2595], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:04,641 - utils - INFO - stage1_gradient_single_runtime: 0.002485513687133789
2023-09-28 23:25:04,642 - utils - INFO -  epoch: 142, all client loss: [0.6878092288970947, 0.7215837836265564], all pred client disparities: [0.10911726951599121, 0.035825006663799286], all client disparities: [0.17525386810302734, 0.0238480381667614], all client accs: [0.5754640698432922, 0.457442969083786],  alpha_performance: tensor([0.7423, 0.2577], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:04,695 - utils - INFO - stage1_gradient_single_runtime: 0.0022542476654052734
2023-09-28 23:25:04,696 - utils - INFO -  epoch: 143, all client loss: [0.6877762079238892, 0.7216194868087769], all pred client disparities: [0.10792586207389832, 0.03509201481938362], all client disparities: [0.17766788601875305, 0.022302445024251938], all client accs: [0.5746569633483887, 0.456356406211853],  alpha_performance: tensor([0.7442, 0.2558], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:04,746 - utils - INFO - stage1_gradient_single_runtime: 0.0022423267364501953
2023-09-28 23:25:04,747 - utils - INFO -  epoch: 144, all client loss: [0.6877421140670776, 0.7216562032699585], all pred client disparities: [0.10669466853141785, 0.03435584157705307], all client disparities: [0.17679154872894287, 0.020241649821400642], all client accs: [0.5754640698432922, 0.4549076557159424],  alpha_performance: tensor([0.7461, 0.2539], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:04,798 - utils - INFO - stage1_gradient_single_runtime: 0.002260923385620117
2023-09-28 23:25:04,798 - utils - INFO -  epoch: 145, all client loss: [0.6877068877220154, 0.7216941714286804], all pred client disparities: [0.10542222857475281, 0.033616803586483], all client disparities: [0.1746867299079895, 0.018953653052449226], all client accs: [0.5758675932884216, 0.45418328046798706],  alpha_performance: tensor([0.7480, 0.2520], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:04,854 - utils - INFO - stage1_gradient_single_runtime: 0.0024955272674560547
2023-09-28 23:25:04,856 - utils - INFO -  epoch: 146, all client loss: [0.6876706480979919, 0.7217330932617188], all pred client disparities: [0.10410717129707336, 0.03287525475025177], all client disparities: [0.1692485809326172, 0.017755672335624695], all client accs: [0.5742534399032593, 0.4527345299720764],  alpha_performance: tensor([0.7498, 0.2502], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:04,910 - utils - INFO - stage1_gradient_single_runtime: 0.0023517608642578125
2023-09-28 23:25:04,911 - utils - INFO -  epoch: 147, all client loss: [0.6876334547996521, 0.7217731475830078], all pred client disparities: [0.10274818539619446, 0.032131556421518326], all client disparities: [0.17332923412322998, 0.016383884474635124], all client accs: [0.5746569633483887, 0.4514668583869934],  alpha_performance: tensor([0.7517, 0.2483], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:04,962 - utils - INFO - stage1_gradient_single_runtime: 0.0022249221801757812
2023-09-28 23:25:04,963 - utils - INFO -  epoch: 148, all client loss: [0.6875953078269958, 0.7218140363693237], all pred client disparities: [0.10134398937225342, 0.031386107206344604], all client disparities: [0.16832923889160156, 0.014496898278594017], all client accs: [0.5750604867935181, 0.4498370289802551],  alpha_performance: tensor([0.7536, 0.2464], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:05,013 - utils - INFO - stage1_gradient_single_runtime: 0.002003192901611328
2023-09-28 23:25:05,014 - utils - INFO -  epoch: 149, all client loss: [0.6875563263893127, 0.721855878829956], all pred client disparities: [0.09989327192306519, 0.03063933178782463], all client disparities: [0.16490989923477173, 0.012867513112723827], all client accs: [0.5714285373687744, 0.44820719957351685],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:05,065 - utils - INFO - stage1_gradient_single_runtime: 0.0029456615447998047
2023-09-28 23:25:05,066 - utils - INFO -  epoch: 150, all client loss: [0.6818854808807373, 0.7157400250434875], all pred client disparities: [0.12422993779182434, 0.041857849806547165], all client disparities: [0.19271907210350037, 0.027100587263703346], all client accs: [0.6029055714607239, 0.4616081118583679],  alpha_performance: tensor([0.7460, 0.2540], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:05,119 - utils - INFO - stage1_gradient_single_runtime: 0.002159595489501953
2023-09-28 23:25:05,121 - utils - INFO -  epoch: 151, all client loss: [0.6818447709083557, 0.7157831192016602], all pred client disparities: [0.12325003743171692, 0.04115688055753708], all client disparities: [0.19307124614715576, 0.026675406843423843], all client accs: [0.6025019884109497, 0.4605215787887573],  alpha_performance: tensor([0.7477, 0.2523], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:05,172 - utils - INFO - stage1_gradient_single_runtime: 0.0025920867919921875
2023-09-28 23:25:05,174 - utils - INFO -  epoch: 152, all client loss: [0.6818027496337891, 0.7158273458480835], all pred client disparities: [0.12223532795906067, 0.040451548993587494], all client disparities: [0.19219492375850677, 0.02504601888358593], all client accs: [0.6025019884109497, 0.45889171957969666],  alpha_performance: tensor([0.7494, 0.2506], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:05,280 - utils - INFO - stage1_gradient_single_runtime: 0.0022420883178710938
2023-09-28 23:25:05,280 - utils - INFO -  epoch: 153, all client loss: [0.6817597150802612, 0.7158728241920471], all pred client disparities: [0.12118436396121979, 0.03974206745624542], all client disparities: [0.18842342495918274, 0.024704627692699432], all client accs: [0.6004842519760132, 0.45834845304489136],  alpha_performance: tensor([0.7511, 0.2489], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:05,334 - utils - INFO - stage1_gradient_single_runtime: 0.002155303955078125
2023-09-28 23:25:05,334 - utils - INFO -  epoch: 154, all client loss: [0.6817156076431274, 0.7159193754196167], all pred client disparities: [0.12009577453136444, 0.039028704166412354], all client disparities: [0.1879422664642334, 0.023332839831709862], all client accs: [0.6012913584709167, 0.4568997025489807],  alpha_performance: tensor([0.7527, 0.2473], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:05,389 - utils - INFO - stage1_gradient_single_runtime: 0.003083467483520508
2023-09-28 23:25:05,391 - utils - INFO -  epoch: 155, all client loss: [0.6816703677177429, 0.715967059135437], all pred client disparities: [0.1189681738615036, 0.03831173852086067], all client disparities: [0.19202294945716858, 0.02152964472770691], all client accs: [0.6033090949058533, 0.45599421858787537],  alpha_performance: tensor([0.7544, 0.2456], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:05,448 - utils - INFO - stage1_gradient_single_runtime: 0.0025682449340820312
2023-09-28 23:25:05,449 - utils - INFO -  epoch: 156, all client loss: [0.681624174118042, 0.7160156965255737], all pred client disparities: [0.11780017614364624, 0.03759147226810455], all client disparities: [0.18947991728782654, 0.020157858729362488], all client accs: [0.6037126779556274, 0.45472657680511475],  alpha_performance: tensor([0.7561, 0.2439], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:05,501 - utils - INFO - stage1_gradient_single_runtime: 0.0022573471069335938
2023-09-28 23:25:05,504 - utils - INFO -  epoch: 157, all client loss: [0.6815770268440247, 0.7160653471946716], all pred client disparities: [0.11659039556980133, 0.036868222057819366], all client disparities: [0.18364658951759338, 0.018354663625359535], all client accs: [0.6029055714607239, 0.4536399841308594],  alpha_performance: tensor([0.7578, 0.2422], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:05,559 - utils - INFO - stage1_gradient_single_runtime: 0.0023691654205322266
2023-09-28 23:25:05,559 - utils - INFO -  epoch: 158, all client loss: [0.6815289855003357, 0.7161160111427307], all pred client disparities: [0.11533749103546143, 0.03614233434200287], all client disparities: [0.18154177069664001, 0.016036272048950195], all client accs: [0.6037126779556274, 0.45219123363494873],  alpha_performance: tensor([0.7594, 0.2406], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:05,613 - utils - INFO - stage1_gradient_single_runtime: 0.0022993087768554688
2023-09-28 23:25:05,613 - utils - INFO -  epoch: 159, all client loss: [0.6814801692962646, 0.7161675095558167], all pred client disparities: [0.11404018104076385, 0.035414207726716995], all client disparities: [0.18022724986076355, 0.014149283990263939], all client accs: [0.6037126779556274, 0.45056140422821045],  alpha_performance: tensor([0.7611, 0.2389], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:05,631 - utils - INFO - valid: True, epoch: 159, loss: [0.6826499104499817, 0.7183805704116821], accuracy: [0.6064000129699707, 0.445818156003952], mean_accuracy:0.5261090844869614,variance_accuracy:0.08029092848300934, disparity: [0.2027534395456314, 0.021052632480859756], mean_disparity:0.11190303601324558,variance_disparity:0.09085040353238583, pred_disparity: [0.10369881987571716, 0.038329724222421646]
2023-09-28 23:25:05,642 - utils - INFO - global_valid: True, epoch: 159,  global_loss: 0.7072147727012634, global_accuracy: 0.5125825330132052,  global_disparity:0.057557545602321625, global_pred_disparity: 0.04833226650953293,
2023-09-28 23:25:05,691 - utils - INFO - stage1_gradient_single_runtime: 0.002696990966796875
2023-09-28 23:25:05,691 - utils - INFO -  epoch: 160, all client loss: [0.681430459022522, 0.7162198424339294], all pred client disparities: [0.11269716918468475, 0.03468422591686249], all client disparities: [0.18097461760044098, 0.014413106255233288], all client accs: [0.6033090949058533, 0.44929373264312744],  alpha_performance: tensor([0.7627, 0.2373], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:05,747 - utils - INFO - stage1_gradient_single_runtime: 0.0025196075439453125
2023-09-28 23:25:05,748 - utils - INFO -  epoch: 161, all client loss: [0.681380033493042, 0.7162728905677795], all pred client disparities: [0.11130724847316742, 0.03395281359553337], all client disparities: [0.18088862299919128, 0.014586914330720901], all client accs: [0.6061339378356934, 0.44893157482147217],  alpha_performance: tensor([0.7643, 0.2357], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:05,804 - utils - INFO - stage1_gradient_single_runtime: 0.0024704933166503906
2023-09-28 23:25:05,806 - utils - INFO -  epoch: 162, all client loss: [0.681329071521759, 0.7163266539573669], all pred client disparities: [0.10986939817667007, 0.033220428973436356], all client disparities: [0.17711712419986725, 0.013556517660617828], all client accs: [0.6093623638153076, 0.4483882784843445],  alpha_performance: tensor([0.7659, 0.2341], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:05,858 - utils - INFO - stage1_gradient_single_runtime: 0.002263307571411133
2023-09-28 23:25:05,859 - utils - INFO -  epoch: 163, all client loss: [0.6812774538993835, 0.7163810133934021], all pred client disparities: [0.10838255286216736, 0.03248755633831024], all client disparities: [0.17036445438861847, 0.012526120990514755], all client accs: [0.605730414390564, 0.4478449821472168],  alpha_performance: tensor([0.7675, 0.2325], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:05,912 - utils - INFO - stage1_gradient_single_runtime: 0.002405405044555664
2023-09-28 23:25:05,913 - utils - INFO -  epoch: 164, all client loss: [0.6812253594398499, 0.716435968875885], all pred client disparities: [0.10684581100940704, 0.031754665076732635], all client disparities: [0.1756306290626526, 0.01175332348793745], all client accs: [0.605730414390564, 0.44766390323638916],  alpha_performance: tensor([0.7690, 0.2310], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:06,037 - utils - INFO - stage1_gradient_single_runtime: 0.002204418182373047
2023-09-28 23:25:06,038 - utils - INFO -  epoch: 165, all client loss: [0.6811729073524475, 0.7164912819862366], all pred client disparities: [0.10525847226381302, 0.03102230653166771], all client disparities: [0.17427314817905426, 0.010980525985360146], all client accs: [0.604519784450531, 0.4474828243255615],  alpha_performance: tensor([0.7706, 0.2294], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:06,092 - utils - INFO - stage1_gradient_single_runtime: 0.0023047924041748047
2023-09-28 23:25:06,093 - utils - INFO -  epoch: 166, all client loss: [0.6811200976371765, 0.7165470123291016], all pred client disparities: [0.10361990332603455, 0.030290987342596054], all client disparities: [0.17331081628799438, 0.010207727551460266], all client accs: [0.6012913584709167, 0.44693952798843384],  alpha_performance: tensor([0.7720, 0.2280], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:06,145 - utils - INFO - stage1_gradient_single_runtime: 0.0022618770599365234
2023-09-28 23:25:06,145 - utils - INFO -  epoch: 167, all client loss: [0.6810671091079712, 0.7166029810905457], all pred client disparities: [0.10192972421646118, 0.029561303555965424], all client disparities: [0.17116296291351318, 0.00969252921640873], all client accs: [0.6016948819160461, 0.4467584490776062],  alpha_performance: tensor([0.7735, 0.2265], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:06,198 - utils - INFO - stage1_gradient_single_runtime: 0.002581357955932617
2023-09-28 23:25:06,199 - utils - INFO -  epoch: 168, all client loss: [0.6810138821601868, 0.7166590690612793], all pred client disparities: [0.10018777847290039, 0.028833802789449692], all client disparities: [0.1648484766483307, 0.008404534310102463], all client accs: [0.6008877754211426, 0.44585296511650085],  alpha_performance: tensor([0.7749, 0.2251], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:06,257 - utils - INFO - stage1_gradient_single_runtime: 0.0022728443145751953
2023-09-28 23:25:06,258 - utils - INFO -  epoch: 169, all client loss: [0.6809607744216919, 0.7167152762413025], all pred client disparities: [0.09839402139186859, 0.028109095990657806], all client disparities: [0.1643243283033371, 0.008236950263381004], all client accs: [0.5992735624313354, 0.4449474811553955],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:06,307 - utils - INFO - stage1_gradient_single_runtime: 0.0022153854370117188
2023-09-28 23:25:06,308 - utils - INFO -  epoch: 170, all client loss: [0.6753294467926025, 0.7105665802955627], all pred client disparities: [0.12643392384052277, 0.040042243897914886], all client disparities: [0.19278664886951447, 0.01672527566552162], all client accs: [0.6311541199684143, 0.45237234234809875],  alpha_performance: tensor([0.7677, 0.2323], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:06,359 - utils - INFO - stage1_gradient_single_runtime: 0.0022428035736083984
2023-09-28 23:25:06,359 - utils - INFO -  epoch: 171, all client loss: [0.6752637028694153, 0.7106349468231201], all pred client disparities: [0.12510177493095398, 0.03930541127920151], all client disparities: [0.19349099695682526, 0.01612628437578678], all client accs: [0.6311541199684143, 0.4514668583869934],  alpha_performance: tensor([0.7691, 0.2309], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:06,412 - utils - INFO - stage1_gradient_single_runtime: 0.002211332321166992
2023-09-28 23:25:06,412 - utils - INFO -  epoch: 172, all client loss: [0.6751972436904907, 0.7107041478157043], all pred client disparities: [0.12371698021888733, 0.03856616094708443], all client disparities: [0.1946765035390854, 0.014323092065751553], all client accs: [0.632364809513092, 0.4501992166042328],  alpha_performance: tensor([0.7705, 0.2295], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:06,464 - utils - INFO - stage1_gradient_single_runtime: 0.002325296401977539
2023-09-28 23:25:06,466 - utils - INFO -  epoch: 173, all client loss: [0.6751300692558289, 0.7107739448547363], all pred client disparities: [0.12227815389633179, 0.03782496601343155], all client disparities: [0.19086198508739471, 0.01398169994354248], all client accs: [0.6347861289978027, 0.4496559500694275],  alpha_performance: tensor([0.7718, 0.2282], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:06,523 - utils - INFO - stage1_gradient_single_runtime: 0.002159595489501953
2023-09-28 23:25:06,524 - utils - INFO -  epoch: 174, all client loss: [0.6750624775886536, 0.7108443975448608], all pred client disparities: [0.12078404426574707, 0.037082333117723465], all client disparities: [0.19117116928100586, 0.013556517660617828], all client accs: [0.633575439453125, 0.4483882784843445],  alpha_performance: tensor([0.7732, 0.2268], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:06,573 - utils - INFO - stage1_gradient_single_runtime: 0.0023081302642822266
2023-09-28 23:25:06,574 - utils - INFO -  epoch: 175, all client loss: [0.6749943494796753, 0.7109153866767883], all pred client disparities: [0.11923350393772125, 0.036338817328214645], all client disparities: [0.18981367349624634, 0.012783720158040524], all client accs: [0.633575439453125, 0.44820719957351685],  alpha_performance: tensor([0.7745, 0.2255], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:06,624 - utils - INFO - stage1_gradient_single_runtime: 0.0024874210357666016
2023-09-28 23:25:06,624 - utils - INFO -  epoch: 176, all client loss: [0.6749257445335388, 0.7109867930412292], all pred client disparities: [0.11762557923793793, 0.035594966262578964], all client disparities: [0.19095619022846222, 0.01175332348793745], all client accs: [0.6355931758880615, 0.4474828243255615],  alpha_performance: tensor([0.7757, 0.2243], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:06,674 - utils - INFO - stage1_gradient_single_runtime: 0.002209901809692383
2023-09-28 23:25:06,675 - utils - INFO -  epoch: 177, all client loss: [0.674856960773468, 0.711058497428894], all pred client disparities: [0.11595956981182098, 0.03485136106610298], all client disparities: [0.19122236967086792, 0.01175332348793745], all client accs: [0.6339790225028992, 0.4478449821472168],  alpha_performance: tensor([0.7769, 0.2231], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:06,779 - utils - INFO - stage1_gradient_single_runtime: 0.002226591110229492
2023-09-28 23:25:06,780 - utils - INFO -  epoch: 178, all client loss: [0.6747879385948181, 0.7111304998397827], all pred client disparities: [0.1142348051071167, 0.034108635038137436], all client disparities: [0.18696968257427216, 0.010980525985360146], all client accs: [0.6347861289978027, 0.44766390323638916],  alpha_performance: tensor([0.7781, 0.2219], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:06,833 - utils - INFO - stage1_gradient_single_runtime: 0.002589702606201172
2023-09-28 23:25:06,834 - utils - INFO -  epoch: 179, all client loss: [0.6747188568115234, 0.7112026810646057], all pred client disparities: [0.11245106160640717, 0.03336745873093605], all client disparities: [0.18894553184509277, 0.010896733030676842], all client accs: [0.6364002823829651, 0.4471206068992615],  alpha_performance: tensor([0.7792, 0.2208], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:06,853 - utils - INFO - valid: True, epoch: 179, loss: [0.6747288703918457, 0.7133829593658447], accuracy: [0.6319999694824219, 0.44072726368904114], mean_accuracy:0.5363636165857315,variance_accuracy:0.09563635289669037, disparity: [0.20421360433101654, 0.00947368424385786], mean_disparity:0.1068436442874372,variance_disparity:0.09736996004357934, pred_disparity: [0.11033362150192261, 0.03638697415590286]
2023-09-28 23:25:06,866 - utils - INFO - global_valid: True, epoch: 179,  global_loss: 0.7013036012649536, global_accuracy: 0.5359793917567026,  global_disparity:0.05150604248046875, global_pred_disparity: 0.04988449811935425,
2023-09-28 23:25:06,916 - utils - INFO - stage1_gradient_single_runtime: 0.002775907516479492
2023-09-28 23:25:06,916 - utils - INFO -  epoch: 180, all client loss: [0.6746497750282288, 0.7112748622894287], all pred client disparities: [0.1106082946062088, 0.03262845426797867], all client disparities: [0.18227887153625488, 0.010123935528099537], all client accs: [0.6380144953727722, 0.4465773403644562],  alpha_performance: tensor([0.7803, 0.2197], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:06,977 - utils - INFO - stage1_gradient_single_runtime: 0.0022525787353515625
2023-09-28 23:25:06,980 - utils - INFO -  epoch: 181, all client loss: [0.6745807528495789, 0.7113469243049622], all pred client disparities: [0.10870672762393951, 0.031892333179712296], all client disparities: [0.17385955154895782, 0.008752148598432541], all client accs: [0.6355931758880615, 0.4454907774925232],  alpha_performance: tensor([0.7813, 0.2187], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:07,027 - utils - INFO - stage1_gradient_single_runtime: 0.0026252269744873047
2023-09-28 23:25:07,030 - utils - INFO -  epoch: 182, all client loss: [0.6745120286941528, 0.711418867111206], all pred client disparities: [0.10674692690372467, 0.031159795820713043], all client disparities: [0.17333537340164185, 0.007721751928329468], all client accs: [0.6364002823829651, 0.44476640224456787],  alpha_performance: tensor([0.7822, 0.2178], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:07,085 - utils - INFO - stage1_gradient_single_runtime: 0.002622365951538086
2023-09-28 23:25:07,086 - utils - INFO -  epoch: 183, all client loss: [0.6744436621665955, 0.7114904522895813], all pred client disparities: [0.10472987592220306, 0.030431527644395828], all client disparities: [0.16285422444343567, 0.007895559072494507], all client accs: [0.6376109719276428, 0.4444042146205902],  alpha_performance: tensor([0.7830, 0.2170], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:07,140 - utils - INFO - stage1_gradient_single_runtime: 0.002710103988647461
2023-09-28 23:25:07,141 - utils - INFO -  epoch: 184, all client loss: [0.6743757724761963, 0.7115616202354431], all pred client disparities: [0.10265688598155975, 0.02970828488469124], all client disparities: [0.15689188241958618, 0.007296569179743528], all client accs: [0.6351896524429321, 0.4436798393726349],  alpha_performance: tensor([0.7838, 0.2162], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:07,199 - utils - INFO - stage1_gradient_single_runtime: 0.0026094913482666016
2023-09-28 23:25:07,200 - utils - INFO -  epoch: 185, all client loss: [0.6743084788322449, 0.711632251739502], all pred client disparities: [0.10052968561649323, 0.02899077907204628], all client disparities: [0.1535155475139618, 0.006266172043979168], all client accs: [0.6384180784225464, 0.44295546412467957],  alpha_performance: tensor([0.7845, 0.2155], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:07,252 - utils - INFO - stage1_gradient_single_runtime: 0.0021271705627441406
2023-09-28 23:25:07,253 - utils - INFO -  epoch: 186, all client loss: [0.6742419004440308, 0.7117021083831787], all pred client disparities: [0.098350390791893, 0.02827974036335945], all client disparities: [0.1537817269563675, 0.005235775373876095], all client accs: [0.6380144953727722, 0.44223108887672424],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:07,303 - utils - INFO - stage1_gradient_single_runtime: 0.0022783279418945312
2023-09-28 23:25:07,305 - utils - INFO -  epoch: 187, all client loss: [0.6687377095222473, 0.7056164741516113], all pred client disparities: [0.1275326907634735, 0.04089219123125076], all client disparities: [0.20220108330249786, 0.01398169994354248], all client accs: [0.6626311540603638, 0.4496559500694275],  alpha_performance: tensor([0.7797, 0.2203], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:07,354 - utils - INFO - stage1_gradient_single_runtime: 0.002285003662109375
2023-09-28 23:25:07,355 - utils - INFO -  epoch: 188, all client loss: [0.6686499714851379, 0.7057074904441833], all pred client disparities: [0.12563002109527588, 0.04010854288935661], all client disparities: [0.19755323231220245, 0.013897907920181751], all client accs: [0.6638417840003967, 0.4496559500694275],  alpha_performance: tensor([0.7807, 0.2193], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:07,483 - utils - INFO - stage1_gradient_single_runtime: 0.0022687911987304688
2023-09-28 23:25:07,484 - utils - INFO -  epoch: 189, all client loss: [0.6685622930526733, 0.7057984471321106], all pred client disparities: [0.12365280091762543, 0.03932557627558708], all client disparities: [0.19001023471355438, 0.012268520891666412], all client accs: [0.6646488904953003, 0.44820719957351685],  alpha_performance: tensor([0.7816, 0.2184], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:07,535 - utils - INFO - stage1_gradient_single_runtime: 0.0022687911987304688
2023-09-28 23:25:07,537 - utils - INFO -  epoch: 190, all client loss: [0.6684747338294983, 0.7058893442153931], all pred client disparities: [0.1216009110212326, 0.038544103503227234], all client disparities: [0.18821458518505096, 0.011495724320411682], all client accs: [0.6622275710105896, 0.4478449821472168],  alpha_performance: tensor([0.7825, 0.2175], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:07,588 - utils - INFO - stage1_gradient_single_runtime: 0.0025467872619628906
2023-09-28 23:25:07,589 - utils - INFO -  epoch: 191, all client loss: [0.6683876514434814, 0.7059799432754517], all pred client disparities: [0.11947469413280487, 0.037765022367239], all client disparities: [0.18598076701164246, 0.01115433219820261], all client accs: [0.658595621585846, 0.4473017156124115],  alpha_performance: tensor([0.7832, 0.2168], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:07,645 - utils - INFO - stage1_gradient_single_runtime: 0.002270936965942383
2023-09-28 23:25:07,647 - utils - INFO -  epoch: 192, all client loss: [0.668300986289978, 0.706070065498352], all pred client disparities: [0.11727496981620789, 0.03698919340968132], all client disparities: [0.17966625094413757, 0.009782545268535614], all client accs: [0.6577885150909424, 0.4462151527404785],  alpha_performance: tensor([0.7839, 0.2161], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:07,699 - utils - INFO - stage1_gradient_single_runtime: 0.0021696090698242188
2023-09-28 23:25:07,700 - utils - INFO -  epoch: 193, all client loss: [0.6682149767875671, 0.7061597108840942], all pred client disparities: [0.11500295996665955, 0.03621756285429001], all client disparities: [0.17370393872261047, 0.009267346933484077], all client accs: [0.6565778851509094, 0.44585296511650085],  alpha_performance: tensor([0.7845, 0.2155], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:07,750 - utils - INFO - stage1_gradient_single_runtime: 0.002321004867553711
2023-09-28 23:25:07,752 - utils - INFO -  epoch: 194, all client loss: [0.6681297421455383, 0.7062485814094543], all pred client disparities: [0.11266057193279266, 0.035451047122478485], all client disparities: [0.1702416092157364, 0.009009746834635735], all client accs: [0.6569814085960388, 0.44567185640335083],  alpha_performance: tensor([0.7850, 0.2150], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:07,803 - utils - INFO - stage1_gradient_single_runtime: 0.0022361278533935547
2023-09-28 23:25:07,804 - utils - INFO -  epoch: 195, all client loss: [0.6680454015731812, 0.7063366174697876], all pred client disparities: [0.11025020480155945, 0.034690629690885544], all client disparities: [0.16353192925453186, 0.009183554910123348], all client accs: [0.6577885150909424, 0.44530969858169556],  alpha_performance: tensor([0.7854, 0.2146], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:07,858 - utils - INFO - stage1_gradient_single_runtime: 0.0026962757110595703
2023-09-28 23:25:07,859 - utils - INFO -  epoch: 196, all client loss: [0.6679622530937195, 0.7064235806465149], all pred client disparities: [0.10777485370635986, 0.03393721953034401], all client disparities: [0.1468222737312317, 0.008326965384185314], all client accs: [0.6533494591712952, 0.4442231059074402],  alpha_performance: tensor([0.7856, 0.2144], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:07,914 - utils - INFO - stage1_gradient_single_runtime: 0.002557516098022461
2023-09-28 23:25:07,915 - utils - INFO -  epoch: 197, all client loss: [0.6678801774978638, 0.7065094113349915], all pred client disparities: [0.1052381843328476, 0.033191803842782974], all client disparities: [0.13923628628253937, 0.00703897001221776], all client accs: [0.6493139266967773, 0.4433176517486572],  alpha_performance: tensor([0.7858, 0.2142], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:07,965 - utils - INFO - stage1_gradient_single_runtime: 0.002633810043334961
2023-09-28 23:25:07,967 - utils - INFO -  epoch: 198, all client loss: [0.6677995920181274, 0.7065938711166382], all pred client disparities: [0.1026444137096405, 0.03245534747838974], all client disparities: [0.12708845734596252, 0.005493374541401863], all client accs: [0.6456819772720337, 0.44241219758987427],  alpha_performance: tensor([0.7858, 0.2142], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:08,015 - utils - INFO - stage1_gradient_single_runtime: 0.0020470619201660156
2023-09-28 23:25:08,016 - utils - INFO -  epoch: 199, all client loss: [0.6677204370498657, 0.7066768407821655], all pred client disparities: [0.09999842196702957, 0.03172874450683594], all client disparities: [0.12362613528966904, 0.00446297787129879], all client accs: [0.6436642408370972, 0.44168782234191895],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:08,035 - utils - INFO - valid: True, epoch: 199, loss: [0.6616157293319702, 0.7032836079597473], accuracy: [0.6687999963760376, 0.44363635778427124], mean_accuracy:0.5562181770801544,variance_accuracy:0.11258181929588318, disparity: [0.1833541989326477, 0.019999999552965164], mean_disparity:0.10167709924280643,variance_disparity:0.08167709968984127, pred_disparity: [0.1372762769460678, 0.05188918858766556]
2023-09-28 23:25:08,048 - utils - INFO - global_valid: True, epoch: 199,  global_loss: 0.690262496471405, global_accuracy: 0.6165716286514606,  global_disparity:0.05669763684272766, global_pred_disparity: 0.06973108649253845,
2023-09-28 23:25:08,102 - utils - INFO - stage1_gradient_single_runtime: 0.002565622329711914
2023-09-28 23:25:08,104 - utils - INFO -  epoch: 200, all client loss: [0.6624246835708618, 0.7007516026496887], all pred client disparities: [0.1277761310338974, 0.04512014240026474], all client disparities: [0.17761261761188507, 0.015868686139583588], all client accs: [0.6731234788894653, 0.4520101547241211],  alpha_performance: tensor([0.7847, 0.2153], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:08,151 - utils - INFO - stage1_gradient_single_runtime: 0.0021855831146240234
2023-09-28 23:25:08,152 - utils - INFO -  epoch: 201, all client loss: [0.6623246073722839, 0.7008556723594666], all pred client disparities: [0.1251983344554901, 0.04429970681667328], all client disparities: [0.16546478867530823, 0.015269696712493896], all client accs: [0.667070209980011, 0.45110470056533813],  alpha_performance: tensor([0.7853, 0.2147], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:08,203 - utils - INFO - stage1_gradient_single_runtime: 0.0026082992553710938
2023-09-28 23:25:08,204 - utils - INFO -  epoch: 202, all client loss: [0.6622260212898254, 0.7009583711624146], all pred client disparities: [0.12253595143556595, 0.04348495230078697], all client disparities: [0.15248361229896545, 0.013897907920181751], all client accs: [0.6634382605552673, 0.45001810789108276],  alpha_performance: tensor([0.7858, 0.2142], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:08,301 - utils - INFO - stage1_gradient_single_runtime: 0.002713441848754883
2023-09-28 23:25:08,303 - utils - INFO -  epoch: 203, all client loss: [0.6621288657188416, 0.7010596394538879], all pred client disparities: [0.11979304999113083, 0.04267716780304909], all client disparities: [0.14279280602931976, 0.012352313846349716], all client accs: [0.6602098345756531, 0.4491126537322998],  alpha_performance: tensor([0.7862, 0.2138], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:08,353 - utils - INFO - stage1_gradient_single_runtime: 0.002233743667602539
2023-09-28 23:25:08,354 - utils - INFO -  epoch: 204, all client loss: [0.6620334982872009, 0.7011591792106628], all pred client disparities: [0.11697455495595932, 0.04187764972448349], all client disparities: [0.13564497232437134, 0.0110643170773983], all client accs: [0.6577885150909424, 0.4483882784843445],  alpha_performance: tensor([0.7864, 0.2136], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:08,403 - utils - INFO - stage1_gradient_single_runtime: 0.002191781997680664
2023-09-28 23:25:08,406 - utils - INFO -  epoch: 205, all client loss: [0.6619400382041931, 0.7012569308280945], all pred client disparities: [0.11408629268407822, 0.04108772054314613], all client disparities: [0.1322256475687027, 0.011411932297050953], all client accs: [0.6553671956062317, 0.44766390323638916],  alpha_performance: tensor([0.7866, 0.2134], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:08,455 - utils - INFO - stage1_gradient_single_runtime: 0.002567291259765625
2023-09-28 23:25:08,456 - utils - INFO -  epoch: 206, all client loss: [0.6618487238883972, 0.7013525366783142], all pred client disparities: [0.11113499104976654, 0.040308691561222076], all client disparities: [0.12380631268024445, 0.011070541106164455], all client accs: [0.6509281396865845, 0.44693952798843384],  alpha_performance: tensor([0.7866, 0.2134], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:08,503 - utils - INFO - stage1_gradient_single_runtime: 0.002180814743041992
2023-09-28 23:25:08,504 - utils - INFO -  epoch: 207, all client loss: [0.661759614944458, 0.701445996761322], all pred client disparities: [0.10812830924987793, 0.03954183682799339], all client disparities: [0.1120966449379921, 0.009524945169687271], all client accs: [0.6464890837669373, 0.44585296511650085],  alpha_performance: tensor([0.7864, 0.2136], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:08,550 - utils - INFO - stage1_gradient_single_runtime: 0.002354145050048828
2023-09-28 23:25:08,552 - utils - INFO -  epoch: 208, all client loss: [0.6616730093955994, 0.701537013053894], all pred client disparities: [0.10507465898990631, 0.03878841549158096], all client disparities: [0.10788697004318237, 0.008494548499584198], all client accs: [0.6464890837669373, 0.44530969858169556],  alpha_performance: tensor([0.7861, 0.2139], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:08,599 - utils - INFO - stage1_gradient_single_runtime: 0.0021910667419433594
2023-09-28 23:25:08,600 - utils - INFO -  epoch: 209, all client loss: [0.6615889668464661, 0.701625406742096], all pred client disparities: [0.10198327153921127, 0.03804964944720268], all client disparities: [0.0970536395907402, 0.0076379599049687386], all client accs: [0.6440677642822266, 0.4442231059074402],  alpha_performance: tensor([0.7857, 0.2143], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:08,655 - utils - INFO - stage1_gradient_single_runtime: 0.002784252166748047
2023-09-28 23:25:08,656 - utils - INFO -  epoch: 210, all client loss: [0.6615076065063477, 0.701711118221283], all pred client disparities: [0.09886401146650314, 0.037326667457818985], all client disparities: [0.08451064676046371, 0.00634996360167861], all client accs: [0.6376109719276428, 0.4433176517486572],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:08,703 - utils - INFO - stage1_gradient_single_runtime: 0.0022509098052978516
2023-09-28 23:25:08,705 - utils - INFO -  epoch: 211, all client loss: [0.6564531326293945, 0.6959914565086365], all pred client disparities: [0.12456708401441574, 0.05152755230665207], all client disparities: [0.12968263030052185, 0.02136206068098545], all client accs: [0.6610169410705566, 0.45599421858787537],  alpha_performance: tensor([0.7882, 0.2118], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:08,753 - utils - INFO - stage1_gradient_single_runtime: 0.002332925796508789
2023-09-28 23:25:08,754 - utils - INFO -  epoch: 212, all client loss: [0.6563565135002136, 0.6960926055908203], all pred client disparities: [0.12141511589288712, 0.050730735063552856], all client disparities: [0.1262633204460144, 0.019732672721147537], all client accs: [0.6565778851509094, 0.4545454680919647],  alpha_performance: tensor([0.7885, 0.2115], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:08,803 - utils - INFO - stage1_gradient_single_runtime: 0.0023729801177978516
2023-09-28 23:25:08,804 - utils - INFO -  epoch: 213, all client loss: [0.6562628149986267, 0.6961909532546997], all pred client disparities: [0.11821123957633972, 0.04994808882474899], all client disparities: [0.1183251440525055, 0.01767188124358654], all client accs: [0.6537529826164246, 0.4532778263092041],  alpha_performance: tensor([0.7887, 0.2113], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:08,854 - utils - INFO - stage1_gradient_single_runtime: 0.0024824142456054688
2023-09-28 23:25:08,856 - utils - INFO -  epoch: 214, all client loss: [0.6561721563339233, 0.6962860822677612], all pred client disparities: [0.11496566236019135, 0.049181003123521805], all client disparities: [0.1095106452703476, 0.016557691618800163], all client accs: [0.6493139266967773, 0.4525534510612488],  alpha_performance: tensor([0.7888, 0.2112], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:08,907 - utils - INFO - stage1_gradient_single_runtime: 0.002360820770263672
2023-09-28 23:25:08,908 - utils - INFO -  epoch: 215, all client loss: [0.6560848355293274, 0.6963779330253601], all pred client disparities: [0.11168913543224335, 0.04843082278966904], all client disparities: [0.103634312748909, 0.015784895047545433], all client accs: [0.6456819772720337, 0.45219123363494873],  alpha_performance: tensor([0.7887, 0.2113], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:09,027 - utils - INFO - stage1_gradient_single_runtime: 0.0022292137145996094
2023-09-28 23:25:09,028 - utils - INFO -  epoch: 216, all client loss: [0.6560009121894836, 0.6964664459228516], all pred client disparities: [0.10839293152093887, 0.047698795795440674], all client disparities: [0.0940294861793518, 0.015185904689133167], all client accs: [0.6428571343421936, 0.45128577947616577],  alpha_performance: tensor([0.7885, 0.2115], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:09,079 - utils - INFO - stage1_gradient_single_runtime: 0.0022034645080566406
2023-09-28 23:25:09,080 - utils - INFO -  epoch: 217, all client loss: [0.6559204459190369, 0.6965514421463013], all pred client disparities: [0.10508862882852554, 0.046986084431409836], all client disparities: [0.0889434888958931, 0.01467070635408163], all client accs: [0.6384180784225464, 0.4509235918521881],  alpha_performance: tensor([0.7881, 0.2119], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:09,130 - utils - INFO - stage1_gradient_single_runtime: 0.0022537708282470703
2023-09-28 23:25:09,132 - utils - INFO -  epoch: 218, all client loss: [0.6558434963226318, 0.6966329216957092], all pred client disparities: [0.1017879843711853, 0.04629366472363472], all client disparities: [0.07933865487575531, 0.013125111348927021], all client accs: [0.6331719160079956, 0.4498370289802551],  alpha_performance: tensor([0.7876, 0.2124], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:09,184 - utils - INFO - stage1_gradient_single_runtime: 0.002346515655517578
2023-09-28 23:25:09,186 - utils - INFO -  epoch: 219, all client loss: [0.6557701230049133, 0.6967107653617859], all pred client disparities: [0.09850260615348816, 0.04562246426939964], all client disparities: [0.0739004909992218, 0.011238125152885914], all client accs: [0.6307505965232849, 0.4480260908603668],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:09,205 - utils - INFO - valid: True, epoch: 219, loss: [0.6492137312889099, 0.6943040490150452], accuracy: [0.6656000018119812, 0.4567272663116455], mean_accuracy:0.5611636340618134,variance_accuracy:0.10443636775016785, disparity: [0.12140175700187683, 0.04105263203382492], mean_disparity:0.08122719451785088,variance_disparity:0.040174562484025955, pred_disparity: [0.13130566477775574, 0.07186859101057053]
2023-09-28 23:25:09,217 - utils - INFO - global_valid: True, epoch: 219,  global_loss: 0.6802133321762085, global_accuracy: 0.7062725090036015,  global_disparity:0.0592130646109581, global_pred_disparity: 0.08498089015483856,
2023-09-28 23:25:09,269 - utils - INFO - stage1_gradient_single_runtime: 0.0022394657135009766
2023-09-28 23:25:09,270 - utils - INFO -  epoch: 220, all client loss: [0.6509822607040405, 0.6912375092506409], all pred client disparities: [0.12220566719770432, 0.06050946190953255], all client disparities: [0.11196764558553696, 0.03225256875157356], all client accs: [0.6509281396865845, 0.46522998809814453],  alpha_performance: tensor([0.7913, 0.2087], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:09,320 - utils - INFO - stage1_gradient_single_runtime: 0.002364635467529297
2023-09-28 23:25:09,322 - utils - INFO -  epoch: 221, all client loss: [0.6508991122245789, 0.6913252472877502], all pred client disparities: [0.11889523267745972, 0.05980278179049492], all client disparities: [0.10652948915958405, 0.03139598295092583], all client accs: [0.6493139266967773, 0.4643245339393616],  alpha_performance: tensor([0.7916, 0.2084], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:09,374 - utils - INFO - stage1_gradient_single_runtime: 0.0022950172424316406
2023-09-28 23:25:09,375 - utils - INFO -  epoch: 222, all client loss: [0.6508196592330933, 0.6914091110229492], all pred client disparities: [0.11558186262845993, 0.059115931391716], all client disparities: [0.09938165545463562, 0.02968280389904976], all client accs: [0.643260657787323, 0.46233248710632324],  alpha_performance: tensor([0.7917, 0.2083], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:09,424 - utils - INFO - stage1_gradient_single_runtime: 0.0022733211517333984
2023-09-28 23:25:09,425 - utils - INFO -  epoch: 223, all client loss: [0.6507440209388733, 0.6914891004562378], all pred client disparities: [0.11227644979953766, 0.05844980850815773], all client disparities: [0.09683866053819656, 0.02856861613690853], all client accs: [0.6404358148574829, 0.4614270329475403],  alpha_performance: tensor([0.7917, 0.2083], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:09,480 - utils - INFO - stage1_gradient_single_runtime: 0.0021791458129882812
2023-09-28 23:25:09,480 - utils - INFO -  epoch: 224, all client loss: [0.650672197341919, 0.6915652751922607], all pred client disparities: [0.10898955166339874, 0.05780515819787979], all client disparities: [0.09056716412305832, 0.027712026610970497], all client accs: [0.6372073888778687, 0.4605215787887573],  alpha_performance: tensor([0.7915, 0.2085], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:09,528 - utils - INFO - stage1_gradient_single_runtime: 0.0025186538696289062
2023-09-28 23:25:09,529 - utils - INFO -  epoch: 225, all client loss: [0.6506041884422302, 0.6916375160217285], all pred client disparities: [0.10573145747184753, 0.057182565331459045], all client disparities: [0.08096232265233994, 0.02659783698618412], all client accs: [0.6319612264633179, 0.4592539072036743],  alpha_performance: tensor([0.7912, 0.2088], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:09,581 - utils - INFO - stage1_gradient_single_runtime: 0.0025968551635742188
2023-09-28 23:25:09,582 - utils - INFO -  epoch: 226, all client loss: [0.6505399942398071, 0.6917060017585754], all pred client disparities: [0.10251197218894958, 0.056582532823085785], all client disparities: [0.07675265520811081, 0.024710850790143013], all client accs: [0.6291363835334778, 0.45762407779693604],  alpha_performance: tensor([0.7908, 0.2092], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:09,681 - utils - INFO - stage1_gradient_single_runtime: 0.0023560523986816406
2023-09-28 23:25:09,682 - utils - INFO -  epoch: 227, all client loss: [0.6504794955253601, 0.6917706727981567], all pred client disparities: [0.09934020042419434, 0.05600536987185478], all client disparities: [0.07170966267585754, 0.023596663028001785], all client accs: [0.6246973276138306, 0.45653748512268066],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:09,730 - utils - INFO - stage1_gradient_single_runtime: 0.002254486083984375
2023-09-28 23:25:09,730 - utils - INFO -  epoch: 228, all client loss: [0.645964503288269, 0.6865613460540771], all pred client disparities: [0.12131853401660919, 0.07120407372713089], all client disparities: [0.10811015218496323, 0.04605424031615257], all client accs: [0.6456819772720337, 0.4768199920654297],  alpha_performance: tensor([0.7935, 0.2065], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:09,781 - utils - INFO - stage1_gradient_single_runtime: 0.0027015209197998047
2023-09-28 23:25:09,782 - utils - INFO -  epoch: 229, all client loss: [0.6458978652954102, 0.6866321563720703], all pred client disparities: [0.11813235282897949, 0.07061781734228134], all client disparities: [0.10061015188694, 0.045539043843746185], all client accs: [0.6428571343421936, 0.4764578342437744],  alpha_performance: tensor([0.7937, 0.2063], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:09,829 - utils - INFO - stage1_gradient_single_runtime: 0.002276897430419922
2023-09-28 23:25:09,829 - utils - INFO -  epoch: 230, all client loss: [0.6458350419998169, 0.6866990327835083], all pred client disparities: [0.11497634649276733, 0.07005222886800766], all client disparities: [0.0947338193655014, 0.043993446975946426], all client accs: [0.6388216018676758, 0.47537124156951904],  alpha_performance: tensor([0.7938, 0.2062], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:09,879 - utils - INFO - stage1_gradient_single_runtime: 0.0022487640380859375
2023-09-28 23:25:09,881 - utils - INFO -  epoch: 231, all client loss: [0.6457759737968445, 0.6867620944976807], all pred client disparities: [0.11185849457979202, 0.06950756162405014], all client disparities: [0.08969082683324814, 0.04305306822061539], all client accs: [0.6343825459480286, 0.4739224910736084],  alpha_performance: tensor([0.7938, 0.2062], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:09,927 - utils - INFO - stage1_gradient_single_runtime: 0.0024068355560302734
2023-09-28 23:25:09,929 - utils - INFO -  epoch: 232, all client loss: [0.6457205414772034, 0.686821460723877], all pred client disparities: [0.1087862178683281, 0.06898391991853714], all client disparities: [0.08425266295671463, 0.042795468121767044], all client accs: [0.6311541199684143, 0.4741035997867584],  alpha_performance: tensor([0.7937, 0.2063], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:09,975 - utils - INFO - stage1_gradient_single_runtime: 0.00215911865234375
2023-09-28 23:25:09,977 - utils - INFO -  epoch: 233, all client loss: [0.6456687450408936, 0.6868770718574524], all pred client disparities: [0.10576631128787994, 0.06848133355379105], all client disparities: [0.07964783161878586, 0.04193888232111931], all client accs: [0.6283292770385742, 0.47301703691482544],  alpha_performance: tensor([0.7934, 0.2066], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:10,025 - utils - INFO - stage1_gradient_single_runtime: 0.0022912025451660156
2023-09-28 23:25:10,026 - utils - INFO -  epoch: 234, all client loss: [0.6456204056739807, 0.6869291663169861], all pred client disparities: [0.10280489176511765, 0.06799975782632828], all client disparities: [0.07420966774225235, 0.04039328172802925], all client accs: [0.6255044341087341, 0.47193047404289246],  alpha_performance: tensor([0.7931, 0.2069], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:10,075 - utils - INFO - stage1_gradient_single_runtime: 0.002192974090576172
2023-09-28 23:25:10,077 - utils - INFO -  epoch: 235, all client loss: [0.6455754637718201, 0.6869778037071228], all pred client disparities: [0.09990719705820084, 0.06753896176815033], all client disparities: [0.07254299521446228, 0.03962048515677452], all client accs: [0.6246973276138306, 0.47174936532974243],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:10,126 - utils - INFO - stage1_gradient_single_runtime: 0.0022695064544677734
2023-09-28 23:25:10,127 - utils - INFO -  epoch: 236, all client loss: [0.6413253545761108, 0.6820319294929504], all pred client disparities: [0.12036138772964478, 0.08252216875553131], all client disparities: [0.10473383218050003, 0.06767389923334122], all client accs: [0.6424535512924194, 0.49257516860961914],  alpha_performance: tensor([0.7940, 0.2060], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:10,175 - utils - INFO - stage1_gradient_single_runtime: 0.002197265625
2023-09-28 23:25:10,176 - utils - INFO -  epoch: 237, all client loss: [0.6412768959999084, 0.6820840239524841], all pred client disparities: [0.11742880195379257, 0.08205980807542801], all client disparities: [0.09556715935468674, 0.06612830609083176], all client accs: [0.6384180784225464, 0.4916697144508362],  alpha_performance: tensor([0.7941, 0.2059], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:10,225 - utils - INFO - stage1_gradient_single_runtime: 0.0024039745330810547
2023-09-28 23:25:10,226 - utils - INFO -  epoch: 238, all client loss: [0.6412319540977478, 0.6821326017379761], all pred client disparities: [0.11454376578330994, 0.08161570131778717], all client disparities: [0.09219083189964294, 0.06612830609083176], all client accs: [0.6355931758880615, 0.4922129809856415],  alpha_performance: tensor([0.7941, 0.2059], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:10,273 - utils - INFO - stage1_gradient_single_runtime: 0.002258777618408203
2023-09-28 23:25:10,273 - utils - INFO -  epoch: 239, all client loss: [0.6411904096603394, 0.682177722454071], all pred client disparities: [0.1117110475897789, 0.08118969947099686], all client disparities: [0.08464782685041428, 0.06621832400560379], all client accs: [0.6303470134735107, 0.49148860573768616],  alpha_performance: tensor([0.7941, 0.2059], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:10,288 - utils - INFO - valid: True, epoch: 239, loss: [0.6386273503303528, 0.6859551668167114], accuracy: [0.646399974822998, 0.48072725534439087], mean_accuracy:0.5635636150836945,variance_accuracy:0.08283635973930359, disparity: [0.08865248411893845, 0.08466015756130219], mean_disparity:0.08665632084012032,variance_disparity:0.0019961632788181305, pred_disparity: [0.11489973217248917, 0.09714097529649734]
2023-09-28 23:25:10,299 - utils - INFO - global_valid: True, epoch: 239,  global_loss: 0.6711651682853699, global_accuracy: 0.7567106842737095,  global_disparity:0.08561302721500397, global_pred_disparity: 0.10139994323253632,
2023-09-28 23:25:10,401 - utils - INFO - stage1_gradient_single_runtime: 0.002378702163696289
2023-09-28 23:25:10,403 - utils - INFO -  epoch: 240, all client loss: [0.6411520838737488, 0.6822194457054138], all pred client disparities: [0.10893485695123672, 0.08078154921531677], all client disparities: [0.08131449669599533, 0.06449892371892929], all client accs: [0.6287328600883484, 0.4911264181137085],  alpha_performance: tensor([0.7939, 0.2061], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:10,459 - utils - INFO - stage1_gradient_single_runtime: 0.002665281295776367
2023-09-28 23:25:10,461 - utils - INFO -  epoch: 241, all client loss: [0.6411169171333313, 0.6822579503059387], all pred client disparities: [0.10621875524520874, 0.08039096742868423], all client disparities: [0.07964783161878586, 0.06527172029018402], all client accs: [0.6279257535934448, 0.4916697144508362],  alpha_performance: tensor([0.7937, 0.2063], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:10,511 - utils - INFO - stage1_gradient_single_runtime: 0.0022428035736083984
2023-09-28 23:25:10,512 - utils - INFO -  epoch: 242, all client loss: [0.6410849094390869, 0.6822932958602905], all pred client disparities: [0.10356583446264267, 0.08001764118671417], all client disparities: [0.07798115909099579, 0.06484030932188034], all client accs: [0.6271186470985413, 0.4916697144508362],  alpha_performance: tensor([0.7933, 0.2067], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:10,563 - utils - INFO - stage1_gradient_single_runtime: 0.0022661685943603516
2023-09-28 23:25:10,564 - utils - INFO -  epoch: 243, all client loss: [0.6410556435585022, 0.6823257207870483], all pred client disparities: [0.10097846388816833, 0.07966113090515137], all client disparities: [0.07420966774225235, 0.06493032723665237], all client accs: [0.6246973276138306, 0.4905831217765808],  alpha_performance: tensor([0.7929, 0.2071], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:10,612 - utils - INFO - stage1_gradient_single_runtime: 0.002025127410888672
2023-09-28 23:25:10,613 - utils - INFO -  epoch: 244, all client loss: [0.6410292387008667, 0.6823552250862122], all pred client disparities: [0.09845858812332153, 0.07932102680206299], all client disparities: [0.06920966506004333, 0.06518793106079102], all client accs: [0.6234866380691528, 0.49076423048973083],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:10,663 - utils - INFO - stage1_gradient_single_runtime: 0.0024635791778564453
2023-09-28 23:25:10,664 - utils - INFO -  epoch: 245, all client loss: [0.637027382850647, 0.6776627898216248], all pred client disparities: [0.11750151962041855, 0.09357310831546783], all client disparities: [0.09390048682689667, 0.08661511540412903], all client accs: [0.6376109719276428, 0.5117710828781128],  alpha_performance: tensor([0.7923, 0.2077], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:10,711 - utils - INFO - stage1_gradient_single_runtime: 0.0022995471954345703
2023-09-28 23:25:10,712 - utils - INFO -  epoch: 246, all client loss: [0.636999785900116, 0.6776936054229736], all pred client disparities: [0.11490298807621002, 0.09322749823331833], all client disparities: [0.09302416443824768, 0.08609990775585175], all client accs: [0.6355931758880615, 0.5114089250564575],  alpha_performance: tensor([0.7923, 0.2077], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:10,763 - utils - INFO - stage1_gradient_single_runtime: 0.0022482872009277344
2023-09-28 23:25:10,764 - utils - INFO -  epoch: 247, all client loss: [0.636975109577179, 0.677721381187439], all pred client disparities: [0.11235962063074112, 0.09289632737636566], all client disparities: [0.08802416175603867, 0.08601611852645874], all client accs: [0.633575439453125, 0.5110467672348022],  alpha_performance: tensor([0.7922, 0.2078], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:10,814 - utils - INFO - stage1_gradient_single_runtime: 0.002562284469604492
2023-09-28 23:25:10,814 - utils - INFO -  epoch: 248, all client loss: [0.6369532346725464, 0.6777462363243103], all pred client disparities: [0.10987342149019241, 0.09257929027080536], all client disparities: [0.08631449937820435, 0.08601611852645874], all client accs: [0.6307505965232849, 0.5112278461456299],  alpha_performance: tensor([0.7920, 0.2080], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:10,868 - utils - INFO - stage1_gradient_single_runtime: 0.002566814422607422
2023-09-28 23:25:10,869 - utils - INFO -  epoch: 249, all client loss: [0.6369341015815735, 0.677768349647522], all pred client disparities: [0.10744600743055344, 0.09227598458528519], all client disparities: [0.08464782685041428, 0.0857585221529007], all client accs: [0.6303470134735107, 0.5105034708976746],  alpha_performance: tensor([0.7917, 0.2083], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:10,916 - utils - INFO - stage1_gradient_single_runtime: 0.0022766590118408203
2023-09-28 23:25:10,917 - utils - INFO -  epoch: 250, all client loss: [0.6369175910949707, 0.677787721157074], all pred client disparities: [0.10507850348949432, 0.09198607504367828], all client disparities: [0.07881449908018112, 0.08481191098690033], all client accs: [0.6279257535934448, 0.5103223323822021],  alpha_performance: tensor([0.7914, 0.2086], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:10,966 - utils - INFO - stage1_gradient_single_runtime: 0.002263307571411133
2023-09-28 23:25:10,967 - utils - INFO -  epoch: 251, all client loss: [0.6369035840034485, 0.6778045892715454], all pred client disparities: [0.10277176648378372, 0.09170911461114883], all client disparities: [0.07837633043527603, 0.08558471500873566], all client accs: [0.6267150640487671, 0.5112278461456299],  alpha_performance: tensor([0.7911, 0.2089], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:11,084 - utils - INFO - stage1_gradient_single_runtime: 0.002299070358276367
2023-09-28 23:25:11,085 - utils - INFO -  epoch: 252, all client loss: [0.6368919610977173, 0.677819013595581], all pred client disparities: [0.10052623599767685, 0.09144468605518341], all client disparities: [0.07504300028085709, 0.08524332195520401], all client accs: [0.6255044341087341, 0.5101412534713745],  alpha_performance: tensor([0.7906, 0.2094], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:11,137 - utils - INFO - stage1_gradient_single_runtime: 0.002109527587890625
2023-09-28 23:25:11,138 - utils - INFO -  epoch: 253, all client loss: [0.6368825435638428, 0.6778310537338257], all pred client disparities: [0.09834206849336624, 0.09119240939617157], all client disparities: [0.07170966267585754, 0.08498572558164597], all client accs: [0.623890221118927, 0.5101412534713745],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:11,188 - utils - INFO - stage1_gradient_single_runtime: 0.0022742748260498047
2023-09-28 23:25:11,189 - utils - INFO -  epoch: 254, all client loss: [0.6331188678741455, 0.6733896732330322], all pred client disparities: [0.11606280505657196, 0.10430740565061569], all client disparities: [0.09306715428829193, 0.10126714408397675], all client accs: [0.6372073888778687, 0.5248098373413086],  alpha_performance: tensor([0.7886, 0.2114], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:11,240 - utils - INFO - stage1_gradient_single_runtime: 0.0025680065155029297
2023-09-28 23:25:11,243 - utils - INFO -  epoch: 255, all client loss: [0.6331102252006531, 0.6734012365341187], all pred client disparities: [0.11377723515033722, 0.1040463000535965], all client disparities: [0.09096232801675797, 0.10126714408397675], all client accs: [0.6351896524429321, 0.5248098373413086],  alpha_performance: tensor([0.7885, 0.2115], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:11,301 - utils - INFO - stage1_gradient_single_runtime: 0.003000020980834961
2023-09-28 23:25:11,302 - utils - INFO -  epoch: 256, all client loss: [0.6331037878990173, 0.6734103560447693], all pred client disparities: [0.11154516041278839, 0.10379613935947418], all client disparities: [0.09008599072694778, 0.10195615887641907], all client accs: [0.6331719160079956, 0.5251720547676086],  alpha_performance: tensor([0.7883, 0.2117], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:11,354 - utils - INFO - stage1_gradient_single_runtime: 0.002238035202026367
2023-09-28 23:25:11,355 - utils - INFO -  epoch: 257, all client loss: [0.6330998539924622, 0.6734169125556946], all pred client disparities: [0.10936702787876129, 0.10355658084154129], all client disparities: [0.08841933310031891, 0.10221375524997711], all client accs: [0.6327683329582214, 0.5251720547676086],  alpha_performance: tensor([0.7880, 0.2120], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:11,406 - utils - INFO - stage1_gradient_single_runtime: 0.0022699832916259766
2023-09-28 23:25:11,407 - utils - INFO -  epoch: 258, all client loss: [0.6330980062484741, 0.673421323299408], all pred client disparities: [0.10724303871393204, 0.10332726687192917], all client disparities: [0.08631449937820435, 0.10152475535869598], all client accs: [0.6315577030181885, 0.5251720547676086],  alpha_performance: tensor([0.7878, 0.2122], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:11,457 - utils - INFO - stage1_gradient_single_runtime: 0.002247333526611328
2023-09-28 23:25:11,459 - utils - INFO -  epoch: 259, all client loss: [0.6330984234809875, 0.6734235286712646], all pred client disparities: [0.10517323017120361, 0.10310786962509155], all client disparities: [0.08131449669599533, 0.10049435496330261], all client accs: [0.6291363835334778, 0.5242666006088257],  alpha_performance: tensor([0.7874, 0.2126], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:11,477 - utils - INFO - valid: True, epoch: 259, loss: [0.6301529407501221, 0.6779230833053589], accuracy: [0.646399974822998, 0.5156363248825073], mean_accuracy:0.5810181498527527,variance_accuracy:0.06538182497024536, disparity: [0.08865248411893845, 0.133673757314682], mean_disparity:0.11116312071681023,variance_disparity:0.02251063659787178, pred_disparity: [0.1075940877199173, 0.12264557182788849]
2023-09-28 23:25:11,489 - utils - INFO - global_valid: True, epoch: 259,  global_loss: 0.6629950404167175, global_accuracy: 0.7706217486994797,  global_disparity:0.12364182621240616, global_pred_disparity: 0.11986038088798523,
2023-09-28 23:25:11,541 - utils - INFO - stage1_gradient_single_runtime: 0.0025022029876708984
2023-09-28 23:25:11,543 - utils - INFO -  epoch: 260, all client loss: [0.6331008076667786, 0.6734235286712646], all pred client disparities: [0.10315737873315811, 0.10289803147315979], all client disparities: [0.08131449669599533, 0.10066816210746765], all client accs: [0.6295399069786072, 0.523723304271698],  alpha_performance: tensor([0.7871, 0.2129], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:11,593 - utils - INFO - stage1_gradient_single_runtime: 0.0022308826446533203
2023-09-28 23:25:11,594 - utils - INFO -  epoch: 261, all client loss: [0.6331050992012024, 0.6734216213226318], all pred client disparities: [0.1011950671672821, 0.10269745439291], all client disparities: [0.08087633550167084, 0.09997914731502533], all client accs: [0.6283292770385742, 0.5231800079345703],  alpha_performance: tensor([0.7866, 0.2134], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:11,648 - utils - INFO - stage1_gradient_single_runtime: 0.002269744873046875
2023-09-28 23:25:11,649 - utils - INFO -  epoch: 262, all client loss: [0.633111298084259, 0.6734177470207214], all pred client disparities: [0.09928572922945023, 0.10250578075647354], all client disparities: [0.07837633043527603, 0.10023675858974457], all client accs: [0.6271186470985413, 0.523361086845398],  alpha_performance: tensor([0.7862, 0.2138], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:11,760 - utils - INFO - stage1_gradient_single_runtime: 0.002232074737548828
2023-09-28 23:25:11,761 - utils - INFO -  epoch: 263, all client loss: [0.6331192851066589, 0.673412024974823], all pred client disparities: [0.09742869436740875, 0.10232267528772354], all client disparities: [0.07337633520364761, 0.10049435496330261], all client accs: [0.6246973276138306, 0.5239043831825256],  alpha_performance: tensor([0.7857, 0.2143], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:11,816 - utils - INFO - stage1_gradient_single_runtime: 0.002527952194213867
2023-09-28 23:25:11,817 - utils - INFO -  epoch: 264, all client loss: [0.6331288814544678, 0.6734045743942261], all pred client disparities: [0.09562312811613083, 0.10214781016111374], all client disparities: [0.07087632268667221, 0.10023675858974457], all client accs: [0.623890221118927, 0.524085521697998],  alpha_performance: tensor([0.7852, 0.2148], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:11,867 - utils - INFO - stage1_gradient_single_runtime: 0.0022873878479003906
2023-09-28 23:25:11,870 - utils - INFO -  epoch: 265, all client loss: [0.6331401467323303, 0.6733954548835754], all pred client disparities: [0.09386812150478363, 0.10198087245225906], all client disparities: [0.06920966506004333, 0.09980534762144089], all client accs: [0.6234866380691528, 0.5242666006088257],  alpha_performance: tensor([0.7847, 0.2153], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:11,919 - utils - INFO - stage1_gradient_single_runtime: 0.002213001251220703
2023-09-28 23:25:11,919 - utils - INFO -  epoch: 266, all client loss: [0.6331529021263123, 0.6733847856521606], all pred client disparities: [0.09216269850730896, 0.10182152688503265], all client disparities: [0.068376325070858, 0.10040432959794998], all client accs: [0.6234866380691528, 0.524990975856781],  alpha_performance: tensor([0.7841, 0.2159], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:11,974 - utils - INFO - stage1_gradient_single_runtime: 0.002852201461791992
2023-09-28 23:25:11,976 - utils - INFO -  epoch: 267, all client loss: [0.6331671476364136, 0.6733725070953369], all pred client disparities: [0.09050582349300385, 0.10166952013969421], all client disparities: [0.06504299491643906, 0.10040432959794998], all client accs: [0.6218724846839905, 0.524990975856781],  alpha_performance: tensor([0.7835, 0.2165], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:12,030 - utils - INFO - stage1_gradient_single_runtime: 0.0025382041931152344
2023-09-28 23:25:12,031 - utils - INFO -  epoch: 268, all client loss: [0.6331827640533447, 0.6733588576316833], all pred client disparities: [0.08889636397361755, 0.10152450203895569], all client disparities: [0.0654381737112999, 0.09988913685083389], all client accs: [0.6210653781890869, 0.524628758430481],  alpha_performance: tensor([0.7829, 0.2171], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:12,081 - utils - INFO - stage1_gradient_single_runtime: 0.0023069381713867188
2023-09-28 23:25:12,082 - utils - INFO -  epoch: 269, all client loss: [0.6331996917724609, 0.6733438372612], all pred client disparities: [0.08733319491147995, 0.10138620436191559], all client disparities: [0.0629381611943245, 0.10040432959794998], all client accs: [0.6202582716941833, 0.5253531336784363],  alpha_performance: tensor([0.7823, 0.2177], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:12,135 - utils - INFO - stage1_gradient_single_runtime: 0.00252532958984375
2023-09-28 23:25:12,136 - utils - INFO -  epoch: 270, all client loss: [0.6332179307937622, 0.6733275055885315], all pred client disparities: [0.08581510186195374, 0.10125435888767242], all client disparities: [0.05960483103990555, 0.10040432959794998], all client accs: [0.6186440587043762, 0.5253531336784363],  alpha_performance: tensor([0.7816, 0.2184], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:12,188 - utils - INFO - stage1_gradient_single_runtime: 0.002227783203125
2023-09-28 23:25:12,190 - utils - INFO -  epoch: 271, all client loss: [0.6332372426986694, 0.6733099222183228], all pred client disparities: [0.08434093743562698, 0.1011287122964859], all client disparities: [0.05877149477601051, 0.10074573010206223], all client accs: [0.618240475654602, 0.5260775089263916],  alpha_performance: tensor([0.7810, 0.2190], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:12,247 - utils - INFO - stage1_gradient_single_runtime: 0.0021893978118896484
2023-09-28 23:25:12,248 - utils - INFO -  epoch: 272, all client loss: [0.6332578659057617, 0.6732911467552185], all pred client disparities: [0.082909494638443, 0.10100896656513214], all client disparities: [0.05877149477601051, 0.10100332647562027], all client accs: [0.618240475654602, 0.5262585878372192],  alpha_performance: tensor([0.7803, 0.2197], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:12,303 - utils - INFO - stage1_gradient_single_runtime: 0.002321481704711914
2023-09-28 23:25:12,304 - utils - INFO -  epoch: 273, all client loss: [0.6332794427871704, 0.6732712388038635], all pred client disparities: [0.08151956647634506, 0.10089492797851562], all client disparities: [0.05583333224058151, 0.1001405119895935], all client accs: [0.6158192157745361, 0.5266208052635193],  alpha_performance: tensor([0.7796, 0.2204], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:12,356 - utils - INFO - stage1_gradient_single_runtime: 0.0022182464599609375
2023-09-28 23:25:12,356 - utils - INFO -  epoch: 274, all client loss: [0.6333020925521851, 0.6732503175735474], all pred client disparities: [0.0801699236035347, 0.10078626871109009], all client disparities: [0.054999999701976776, 0.09996669739484787], all client accs: [0.615415632724762, 0.5268018841743469],  alpha_performance: tensor([0.7789, 0.2211], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:12,462 - utils - INFO - stage1_gradient_single_runtime: 0.002778291702270508
2023-09-28 23:25:12,464 - utils - INFO -  epoch: 275, all client loss: [0.6333256959915161, 0.6732282638549805], all pred client disparities: [0.07885939627885818, 0.10068285465240479], all client disparities: [0.0533333346247673, 0.10030809789896011], all client accs: [0.6146085262298584, 0.5277073383331299],  alpha_performance: tensor([0.7782, 0.2218], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:12,514 - utils - INFO - stage1_gradient_single_runtime: 0.0022859573364257812
2023-09-28 23:25:12,515 - utils - INFO -  epoch: 276, all client loss: [0.6333501935005188, 0.6732052564620972], all pred client disparities: [0.07758679986000061, 0.10058441013097763], all client disparities: [0.05249999836087227, 0.10056569427251816], all client accs: [0.614205002784729, 0.5278884768486023],  alpha_performance: tensor([0.7775, 0.2225], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:12,569 - utils - INFO - stage1_gradient_single_runtime: 0.002293109893798828
2023-09-28 23:25:12,569 - utils - INFO -  epoch: 277, all client loss: [0.6333756446838379, 0.673181414604187], all pred client disparities: [0.07635095715522766, 0.1004907563328743], all client disparities: [0.05000000074505806, 0.10056569427251816], all client accs: [0.6138014197349548, 0.5277073383331299],  alpha_performance: tensor([0.7767, 0.2233], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:12,621 - utils - INFO - stage1_gradient_single_runtime: 0.0022592544555664062
2023-09-28 23:25:12,623 - utils - INFO -  epoch: 278, all client loss: [0.6334018707275391, 0.6731566190719604], all pred client disparities: [0.07515071332454681, 0.10040166974067688], all client disparities: [0.04833333194255829, 0.10013429075479507], all client accs: [0.6129943132400513, 0.5277073383331299],  alpha_performance: tensor([0.7760, 0.2240], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:12,678 - utils - INFO - stage1_gradient_single_runtime: 0.002545595169067383
2023-09-28 23:25:12,679 - utils - INFO -  epoch: 279, all client loss: [0.6334289312362671, 0.673130989074707], all pred client disparities: [0.07398498058319092, 0.10031697154045105], all client disparities: [0.04749999940395355, 0.09970288723707199], all client accs: [0.6125907897949219, 0.5280695557594299],  alpha_performance: tensor([0.7752, 0.2248], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:12,697 - utils - INFO - valid: True, epoch: 279, loss: [0.6296641230583191, 0.6776801943778992], accuracy: [0.6287999749183655, 0.5134545564651489], mean_accuracy:0.5711272656917572,variance_accuracy:0.057672709226608276, disparity: [0.042553190141916275, 0.11968281120061874], mean_disparity:0.08111800067126751,variance_disparity:0.038564810529351234, pred_disparity: [0.0739380344748497, 0.11957909911870956]
2023-09-28 23:25:12,708 - utils - INFO - global_valid: True, epoch: 279,  global_loss: 0.6626752018928528, global_accuracy: 0.7724119647859145,  global_disparity:0.10245756059885025, global_pred_disparity: 0.11008474230766296,
2023-09-28 23:25:12,757 - utils - INFO - stage1_gradient_single_runtime: 0.0024480819702148438
2023-09-28 23:25:12,759 - utils - INFO -  epoch: 280, all client loss: [0.6334567070007324, 0.6731046438217163], all pred client disparities: [0.07285262644290924, 0.1002364382147789], all client disparities: [0.046666666865348816, 0.09970288723707199], all client accs: [0.6121872067451477, 0.5282506346702576],  alpha_performance: tensor([0.7745, 0.2255], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:12,810 - utils - INFO - stage1_gradient_single_runtime: 0.002518892288208008
2023-09-28 23:25:12,812 - utils - INFO -  epoch: 281, all client loss: [0.6334852576255798, 0.6730775237083435], all pred client disparities: [0.07175254821777344, 0.10015997290611267], all client disparities: [0.04416666552424431, 0.10013429075479507], all client accs: [0.6109765768051147, 0.5282506346702576],  alpha_performance: tensor([0.7737, 0.2263], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:12,867 - utils - INFO - stage1_gradient_single_runtime: 0.0025577545166015625
2023-09-28 23:25:12,869 - utils - INFO -  epoch: 282, all client loss: [0.6335144639015198, 0.6730496287345886], all pred client disparities: [0.07068373262882233, 0.10008732974529266], all client disparities: [0.04333333298563957, 0.09927147626876831], all client accs: [0.6109765768051147, 0.5282506346702576],  alpha_performance: tensor([0.7729, 0.2271], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:12,924 - utils - INFO - stage1_gradient_single_runtime: 0.0021827220916748047
2023-09-28 23:25:12,925 - utils - INFO -  epoch: 283, all client loss: [0.6335443258285522, 0.6730210781097412], all pred client disparities: [0.06964513659477234, 0.10001838207244873], all client disparities: [0.042500000447034836, 0.09857624769210815], all client accs: [0.6105730533599854, 0.5295183062553406],  alpha_performance: tensor([0.7722, 0.2278], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:12,974 - utils - INFO - stage1_gradient_single_runtime: 0.0021009445190429688
2023-09-28 23:25:12,975 - utils - INFO -  epoch: 284, all client loss: [0.6335747838020325, 0.6729918122291565], all pred client disparities: [0.06863575428724289, 0.09995295107364655], all client disparities: [0.0416666679084301, 0.09771343320608139], all client accs: [0.6101694703102112, 0.5296993851661682],  alpha_performance: tensor([1., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:13,026 - utils - INFO - stage1_gradient_single_runtime: 0.002246379852294922
2023-09-28 23:25:13,027 - utils - INFO -  epoch: 285, all client loss: [0.6299569606781006, 0.668747067451477], all pred client disparities: [0.08378223329782486, 0.11164866387844086], all client disparities: [0.0625, 0.11021465808153152], all client accs: [0.6186440587043762, 0.541832685470581],  alpha_performance: tensor([0.7747, 0.2253], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:13,080 - utils - INFO - stage1_gradient_single_runtime: 0.0025970935821533203
2023-09-28 23:25:13,081 - utils - INFO -  epoch: 286, all client loss: [0.6299920678138733, 0.6687134504318237], all pred client disparities: [0.08260553330183029, 0.11156732589006424], all client disparities: [0.05999999865889549, 0.10926806181669235], all client accs: [0.6174333691596985, 0.5414705276489258],  alpha_performance: tensor([0.7741, 0.2259], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:13,180 - utils - INFO - stage1_gradient_single_runtime: 0.002225637435913086
2023-09-28 23:25:13,181 - utils - INFO -  epoch: 287, all client loss: [0.6300278902053833, 0.6686790585517883], all pred client disparities: [0.08145995438098907, 0.11148970574140549], all client disparities: [0.05833333358168602, 0.10892044007778168], all client accs: [0.6170298457145691, 0.5420137643814087],  alpha_performance: tensor([0.7735, 0.2265], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:13,233 - utils - INFO - stage1_gradient_single_runtime: 0.002284526824951172
2023-09-28 23:25:13,234 - utils - INFO -  epoch: 288, all client loss: [0.6300644874572754, 0.6686438322067261], all pred client disparities: [0.0803445503115654, 0.11141566932201385], all client disparities: [0.05833333358168602, 0.10917803645133972], all client accs: [0.6170298457145691, 0.5421948432922363],  alpha_performance: tensor([0.7729, 0.2271], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:13,286 - utils - INFO - stage1_gradient_single_runtime: 0.002206563949584961
2023-09-28 23:25:13,288 - utils - INFO -  epoch: 289, all client loss: [0.63010174036026, 0.6686078906059265], all pred client disparities: [0.07925847172737122, 0.1113450676202774], all client disparities: [0.05666666850447655, 0.10892044007778168], all client accs: [0.6162227392196655, 0.5416516065597534],  alpha_performance: tensor([0.7722, 0.2278], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:13,344 - utils - INFO - stage1_gradient_single_runtime: 0.002537250518798828
2023-09-28 23:25:13,346 - utils - INFO -  epoch: 290, all client loss: [0.6301396489143372, 0.6685712933540344], all pred client disparities: [0.07820078730583191, 0.11127780377864838], all client disparities: [0.05583333224058151, 0.10900423675775528], all client accs: [0.6158192157745361, 0.5420137643814087],  alpha_performance: tensor([0.7716, 0.2284], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:13,400 - utils - INFO - stage1_gradient_single_runtime: 0.0021822452545166016
2023-09-28 23:25:13,401 - utils - INFO -  epoch: 291, all client loss: [0.6301781535148621, 0.6685340404510498], all pred client disparities: [0.07717063277959824, 0.11121370643377304], all client disparities: [0.054999999701976776, 0.10960321873426437], all client accs: [0.615415632724762, 0.542738139629364],  alpha_performance: tensor([0.7710, 0.2290], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:13,454 - utils - INFO - stage1_gradient_single_runtime: 0.0023005008697509766
2023-09-28 23:25:13,455 - utils - INFO -  epoch: 292, all client loss: [0.6302172541618347, 0.6684962511062622], all pred client disparities: [0.07616721838712692, 0.11115262657403946], all client disparities: [0.05249999836087227, 0.11011842638254166], all client accs: [0.614205002784729, 0.5431003570556641],  alpha_performance: tensor([0.7703, 0.2297], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:13,506 - utils - INFO - stage1_gradient_single_runtime: 0.0022268295288085938
2023-09-28 23:25:13,507 - utils - INFO -  epoch: 293, all client loss: [0.6302570104598999, 0.6684577465057373], all pred client disparities: [0.07518967986106873, 0.11109451204538345], all client disparities: [0.05249999836087227, 0.1103760227560997], all client accs: [0.6146085262298584, 0.5431003570556641],  alpha_performance: tensor([0.7697, 0.2303], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:13,559 - utils - INFO - stage1_gradient_single_runtime: 0.0022182464599609375
2023-09-28 23:25:13,561 - utils - INFO -  epoch: 294, all client loss: [0.6302971839904785, 0.6684187650680542], all pred client disparities: [0.07423722743988037, 0.11103923618793488], all client disparities: [0.04916666820645332, 0.10899802297353745], all client accs: [0.6129943132400513, 0.5431003570556641],  alpha_performance: tensor([0.7690, 0.2310], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:13,617 - utils - INFO - stage1_gradient_single_runtime: 0.0027627944946289062
2023-09-28 23:25:13,619 - utils - INFO -  epoch: 295, all client loss: [0.6303378939628601, 0.6683792471885681], all pred client disparities: [0.07330910116434097, 0.11098664999008179], all client disparities: [0.04916666820645332, 0.10925561189651489], all client accs: [0.6129943132400513, 0.5432814359664917],  alpha_performance: tensor([0.7684, 0.2316], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:13,674 - utils - INFO - stage1_gradient_single_runtime: 0.002993345260620117
2023-09-28 23:25:13,675 - utils - INFO -  epoch: 296, all client loss: [0.6303790807723999, 0.668339192867279], all pred client disparities: [0.07240451872348785, 0.11093666404485703], all client disparities: [0.04916666820645332, 0.10796139389276505], all client accs: [0.6129943132400513, 0.5432814359664917],  alpha_performance: tensor([0.7678, 0.2322], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:13,726 - utils - INFO - stage1_gradient_single_runtime: 0.0022830963134765625
2023-09-28 23:25:13,728 - utils - INFO -  epoch: 297, all client loss: [0.6304207444190979, 0.668298602104187], all pred client disparities: [0.0715228021144867, 0.11088920384645462], all client disparities: [0.04749999940395355, 0.10718236863613129], all client accs: [0.6121872067451477, 0.5441868901252747],  alpha_performance: tensor([0.7671, 0.2329], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:13,779 - utils - INFO - stage1_gradient_single_runtime: 0.002229928970336914
2023-09-28 23:25:13,780 - utils - INFO -  epoch: 298, all client loss: [0.6304627656936646, 0.6682575941085815], all pred client disparities: [0.07066319137811661, 0.11084415763616562], all client disparities: [0.04749999940395355, 0.10614574700593948], all client accs: [0.6121872067451477, 0.54491126537323],  alpha_performance: tensor([0.7665, 0.2335], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:13,835 - utils - INFO - stage1_gradient_single_runtime: 0.0022330284118652344
2023-09-28 23:25:13,836 - utils - INFO -  epoch: 299, all client loss: [0.6305052638053894, 0.6682161688804626], all pred client disparities: [0.06982503831386566, 0.11080139875411987], all client disparities: [0.04749999940395355, 0.1074337437748909], all client accs: [0.6125907897949219, 0.5458167791366577],  alpha_performance: tensor([0.7658, 0.2342], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:13,853 - utils - INFO - valid: True, epoch: 299, loss: [0.6265084743499756, 0.6732223629951477], accuracy: [0.6255999803543091, 0.5323635935783386], mean_accuracy:0.5789817869663239,variance_accuracy:0.04661819338798523, disparity: [0.03546099364757538, 0.14072498679161072], mean_disparity:0.08809299021959305,variance_disparity:0.05263199657201767, pred_disparity: [0.06932295858860016, 0.13067884743213654]
2023-09-28 23:25:13,864 - utils - INFO - global_valid: True, epoch: 299,  global_loss: 0.6586243510246277, global_accuracy: 0.7699689875950381,  global_disparity:0.11733316630125046, global_pred_disparity: 0.11787469685077667,
2023-09-28 23:25:13,976 - utils - INFO - stage1_gradient_single_runtime: 0.0022907257080078125
2023-09-28 23:25:13,977 - utils - INFO -  epoch: 300, all client loss: [0.6305481195449829, 0.6681743860244751], all pred client disparities: [0.06900765001773834, 0.11076091974973679], all client disparities: [0.046666666865348816, 0.10846414417028427], all client accs: [0.6121872067451477, 0.5463600158691406],  alpha_performance: tensor([0.7652, 0.2348], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:14,033 - utils - INFO - stage1_gradient_single_runtime: 0.002386331558227539
2023-09-28 23:25:14,034 - utils - INFO -  epoch: 301, all client loss: [0.6305913925170898, 0.6681321263313293], all pred client disparities: [0.06821040064096451, 0.11072257161140442], all client disparities: [0.04583333432674408, 0.1092369481921196], all client accs: [0.6117836833000183, 0.5469033122062683],  alpha_performance: tensor([0.7645, 0.2355], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:14,086 - utils - INFO - stage1_gradient_single_runtime: 0.0021698474884033203
2023-09-28 23:25:14,087 - utils - INFO -  epoch: 302, all client loss: [0.6306349039077759, 0.6680895686149597], all pred client disparities: [0.06743264198303223, 0.11068626493215561], all client disparities: [0.04500000178813934, 0.10975214093923569], all client accs: [0.6113801002502441, 0.5472655296325684],  alpha_performance: tensor([0.7639, 0.2361], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:14,140 - utils - INFO - stage1_gradient_single_runtime: 0.002279520034790039
2023-09-28 23:25:14,141 - utils - INFO -  epoch: 303, all client loss: [0.6306788325309753, 0.6680465936660767], all pred client disparities: [0.06667381525039673, 0.11065198481082916], all client disparities: [0.04500000178813934, 0.10975214093923569], all client accs: [0.6113801002502441, 0.5472655296325684],  alpha_performance: tensor([0.7632, 0.2368], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:14,193 - utils - INFO - stage1_gradient_single_runtime: 0.0025713443756103516
2023-09-28 23:25:14,194 - utils - INFO -  epoch: 304, all client loss: [0.6307229995727539, 0.6680033206939697], all pred client disparities: [0.06593328714370728, 0.11061961948871613], all client disparities: [0.0416666679084301, 0.10957833379507065], all client accs: [0.6097659468650818, 0.547084391117096],  alpha_performance: tensor([0.7626, 0.2374], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:14,246 - utils - INFO - stage1_gradient_single_runtime: 0.002249479293823242
2023-09-28 23:25:14,248 - utils - INFO -  epoch: 305, all client loss: [0.6307675242424011, 0.6679597496986389], all pred client disparities: [0.06521054357290268, 0.11058910936117172], all client disparities: [0.0416666679084301, 0.10957833379507065], all client accs: [0.6101694703102112, 0.547084391117096],  alpha_performance: tensor([0.7619, 0.2381], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:14,306 - utils - INFO - stage1_gradient_single_runtime: 0.0023453235626220703
2023-09-28 23:25:14,308 - utils - INFO -  epoch: 306, all client loss: [0.6308122873306274, 0.6679158210754395], all pred client disparities: [0.06450499594211578, 0.11056037992238998], all client disparities: [0.0416666679084301, 0.11035113036632538], all client accs: [0.6101694703102112, 0.5476276874542236],  alpha_performance: tensor([0.7613, 0.2387], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:14,357 - utils - INFO - stage1_gradient_single_runtime: 0.0022149085998535156
2023-09-28 23:25:14,358 - utils - INFO -  epoch: 307, all client loss: [0.6308574080467224, 0.6678716540336609], all pred client disparities: [0.0638161227107048, 0.11053335666656494], all client disparities: [0.0416666679084301, 0.11060872673988342], all client accs: [0.6101694703102112, 0.5472655296325684],  alpha_performance: tensor([0.7606, 0.2394], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:14,408 - utils - INFO - stage1_gradient_single_runtime: 0.0022840499877929688
2023-09-28 23:25:14,409 - utils - INFO -  epoch: 308, all client loss: [0.6309026479721069, 0.667827308177948], all pred client disparities: [0.06314343959093094, 0.1105080172419548], all client disparities: [0.0416666679084301, 0.11060872673988342], all client accs: [0.6105730533599854, 0.5472655296325684],  alpha_performance: tensor([0.7600, 0.2400], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:14,461 - utils - INFO - stage1_gradient_single_runtime: 0.0022230148315429688
2023-09-28 23:25:14,462 - utils - INFO -  epoch: 309, all client loss: [0.6309481263160706, 0.6677825450897217], all pred client disparities: [0.0624864362180233, 0.11048426479101181], all client disparities: [0.0416666679084301, 0.11215432733297348], all client accs: [0.6105730533599854, 0.548352062702179],  alpha_performance: tensor([0.7594, 0.2406], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:14,516 - utils - INFO - stage1_gradient_single_runtime: 0.002771615982055664
2023-09-28 23:25:14,517 - utils - INFO -  epoch: 310, all client loss: [0.6309939026832581, 0.667737603187561], all pred client disparities: [0.06184464320540428, 0.11046202480792999], all client disparities: [0.03999999910593033, 0.1118067055940628], all client accs: [0.6097659468650818, 0.5490764379501343],  alpha_performance: tensor([0.7587, 0.2413], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:14,570 - utils - INFO - stage1_gradient_single_runtime: 0.0023016929626464844
2023-09-28 23:25:14,571 - utils - INFO -  epoch: 311, all client loss: [0.6310398578643799, 0.6676925420761108], all pred client disparities: [0.06121758371591568, 0.11044128239154816], all client disparities: [0.03916666656732559, 0.11163290590047836], all client accs: [0.6093623638153076, 0.5492575168609619],  alpha_performance: tensor([0.7581, 0.2419], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:14,679 - utils - INFO - stage1_gradient_single_runtime: 0.0022516250610351562
2023-09-28 23:25:14,680 - utils - INFO -  epoch: 312, all client loss: [0.6310859322547913, 0.6676472425460815], all pred client disparities: [0.060604825615882874, 0.11042197048664093], all client disparities: [0.03916666656732559, 0.11171669512987137], all client accs: [0.6093623638153076, 0.549619734287262],  alpha_performance: tensor([0.7575, 0.2425], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:14,730 - utils - INFO - stage1_gradient_single_runtime: 0.002283811569213867
2023-09-28 23:25:14,731 - utils - INFO -  epoch: 313, all client loss: [0.6311322450637817, 0.6676016449928284], all pred client disparities: [0.06000596284866333, 0.11040405929088593], all client disparities: [0.038333334028720856, 0.1108538806438446], all client accs: [0.6089588403701782, 0.5499818921089172],  alpha_performance: tensor([0.7568, 0.2432], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:14,784 - utils - INFO - stage1_gradient_single_runtime: 0.002526521682739258
2023-09-28 23:25:14,784 - utils - INFO -  epoch: 314, all client loss: [0.6311787366867065, 0.6675559878349304], all pred client disparities: [0.05942052975296974, 0.11038745194673538], all client disparities: [0.038333334028720856, 0.11111147701740265], all client accs: [0.6089588403701782, 0.5499818921089172],  alpha_performance: tensor([0.7562, 0.2438], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:14,833 - utils - INFO - stage1_gradient_single_runtime: 0.0021932125091552734
2023-09-28 23:25:14,835 - utils - INFO -  epoch: 315, all client loss: [0.6312253475189209, 0.6675100922584534], all pred client disparities: [0.05884816125035286, 0.1103721335530281], all client disparities: [0.038333334028720856, 0.11188428103923798], all client accs: [0.6089588403701782, 0.5505251884460449],  alpha_performance: tensor([0.7556, 0.2444], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:14,890 - utils - INFO - stage1_gradient_single_runtime: 0.0023386478424072266
2023-09-28 23:25:14,891 - utils - INFO -  epoch: 316, all client loss: [0.6312720775604248, 0.667464017868042], all pred client disparities: [0.05828845873475075, 0.11035805940628052], all client disparities: [0.038333334028720856, 0.11214187741279602], all client accs: [0.6089588403701782, 0.5507062673568726],  alpha_performance: tensor([0.7550, 0.2450], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:14,942 - utils - INFO - stage1_gradient_single_runtime: 0.0025937557220458984
2023-09-28 23:25:14,944 - utils - INFO -  epoch: 317, all client loss: [0.631318986415863, 0.6674178242683411], all pred client disparities: [0.057741064578294754, 0.11034517735242844], all client disparities: [0.03750000149011612, 0.11171047389507294], all client accs: [0.608555257320404, 0.5507062673568726],  alpha_performance: tensor([0.7543, 0.2457], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:14,998 - utils - INFO - stage1_gradient_single_runtime: 0.002460479736328125
2023-09-28 23:25:14,999 - utils - INFO -  epoch: 318, all client loss: [0.6313660144805908, 0.6673715114593506], all pred client disparities: [0.057205602526664734, 0.11033347994089127], all client disparities: [0.036666665226221085, 0.11274087429046631], all client accs: [0.6081517338752747, 0.5512495636940002],  alpha_performance: tensor([0.7537, 0.2463], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:15,052 - utils - INFO - stage1_gradient_single_runtime: 0.0021696090698242188
2023-09-28 23:25:15,053 - utils - INFO -  epoch: 319, all client loss: [0.6314131617546082, 0.6673250198364258], all pred client disparities: [0.05668172612786293, 0.11032287776470184], all client disparities: [0.03583333268761635, 0.11205185204744339], all client accs: [0.6077481508255005, 0.5508873462677002],  alpha_performance: tensor([0.7531, 0.2469], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:15,073 - utils - INFO - valid: True, epoch: 319, loss: [0.6269620656967163, 0.6724300384521484], accuracy: [0.6191999912261963, 0.5352727174758911], mean_accuracy:0.5772363543510437,variance_accuracy:0.04196363687515259, disparity: [0.021276595070958138, 0.13726037740707397], mean_disparity:0.07926848623901606,variance_disparity:0.05799189116805792, pred_disparity: [0.055316392332315445, 0.1297471970319748]
2023-09-28 23:25:15,084 - utils - INFO - global_valid: True, epoch: 319,  global_loss: 0.6582213640213013, global_accuracy: 0.7652831132452981,  global_disparity:0.11157097667455673, global_pred_disparity: 0.11414716392755508,
2023-09-28 23:25:15,134 - utils - INFO - stage1_gradient_single_runtime: 0.002479076385498047
2023-09-28 23:25:15,135 - utils - INFO -  epoch: 320, all client loss: [0.6314603686332703, 0.6672784686088562], all pred client disparities: [0.056169088929891586, 0.11031334102153778], all client disparities: [0.03583333268761635, 0.1117042526602745], all client accs: [0.6081517338752747, 0.5516117811203003],  alpha_performance: tensor([0.7525, 0.2475], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:15,189 - utils - INFO - stage1_gradient_single_runtime: 0.0026400089263916016
2023-09-28 23:25:15,191 - utils - INFO -  epoch: 321, all client loss: [0.6315076947212219, 0.6672318577766418], all pred client disparities: [0.05566739663481712, 0.11030484735965729], all client disparities: [0.03500000014901161, 0.11247703433036804], all client accs: [0.6077481508255005, 0.5517928600311279],  alpha_performance: tensor([0.7519, 0.2481], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:15,244 - utils - INFO - stage1_gradient_single_runtime: 0.0022077560424804688
2023-09-28 23:25:15,245 - utils - INFO -  epoch: 322, all client loss: [0.6315551400184631, 0.6671850681304932], all pred client disparities: [0.05517629534006119, 0.11029737442731857], all client disparities: [0.03500000014901161, 0.11204563826322556], all client accs: [0.6077481508255005, 0.5519739389419556],  alpha_performance: tensor([0.7513, 0.2487], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:15,343 - utils - INFO - stage1_gradient_single_runtime: 0.0022530555725097656
2023-09-28 23:25:15,344 - utils - INFO -  epoch: 323, all client loss: [0.6316026449203491, 0.6671382188796997], all pred client disparities: [0.054695501923561096, 0.11029082536697388], all client disparities: [0.03500000014901161, 0.11256084591150284], all client accs: [0.6077481508255005, 0.5523360967636108],  alpha_performance: tensor([0.7507, 0.2493], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:15,395 - utils - INFO - stage1_gradient_single_runtime: 0.0022766590118408203
2023-09-28 23:25:15,396 - utils - INFO -  epoch: 324, all client loss: [0.6316501498222351, 0.6670912504196167], all pred client disparities: [0.05422471836209297, 0.11028525233268738], all client disparities: [0.034166667610406876, 0.11333363503217697], all client accs: [0.6073446273803711, 0.5528793931007385],  alpha_performance: tensor([0.7501, 0.2499], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:15,450 - utils - INFO - stage1_gradient_single_runtime: 0.0022547245025634766
2023-09-28 23:25:15,451 - utils - INFO -  epoch: 325, all client loss: [0.6316977739334106, 0.6670442223548889], all pred client disparities: [0.05376366153359413, 0.11028056591749191], all client disparities: [0.03333333507180214, 0.11272842437028885], all client accs: [0.6069410443305969, 0.5534226894378662],  alpha_performance: tensor([0.7495, 0.2505], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:15,505 - utils - INFO - stage1_gradient_single_runtime: 0.0025501251220703125
2023-09-28 23:25:15,507 - utils - INFO -  epoch: 326, all client loss: [0.631745457649231, 0.6669971346855164], all pred client disparities: [0.053312063217163086, 0.11027678847312927], all client disparities: [0.03166666626930237, 0.11281221359968185], all client accs: [0.6061339378356934, 0.5539659857749939],  alpha_performance: tensor([0.7490, 0.2510], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:15,557 - utils - INFO - stage1_gradient_single_runtime: 0.0025167465209960938
2023-09-28 23:25:15,558 - utils - INFO -  epoch: 327, all client loss: [0.631793200969696, 0.666949987411499], all pred client disparities: [0.052869658917188644, 0.11027378588914871], all client disparities: [0.03166666626930237, 0.11350121349096298], all client accs: [0.6061339378356934, 0.5539659857749939],  alpha_performance: tensor([0.7484, 0.2516], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:15,611 - utils - INFO - stage1_gradient_single_runtime: 0.0022575855255126953
2023-09-28 23:25:15,612 - utils - INFO -  epoch: 328, all client loss: [0.6318409442901611, 0.6669027805328369], all pred client disparities: [0.05243618041276932, 0.1102716401219368], all client disparities: [0.03166666626930237, 0.11263840645551682], all client accs: [0.6061339378356934, 0.5543281435966492],  alpha_performance: tensor([0.7478, 0.2522], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:15,663 - utils - INFO - stage1_gradient_single_runtime: 0.003117799758911133
2023-09-28 23:25:15,664 - utils - INFO -  epoch: 329, all client loss: [0.631888747215271, 0.6668555736541748], all pred client disparities: [0.0520113967359066, 0.11027027666568756], all client disparities: [0.03166666626930237, 0.11272219568490982], all client accs: [0.6061339378356934, 0.5546903610229492],  alpha_performance: tensor([0.7472, 0.2528], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:15,720 - utils - INFO - stage1_gradient_single_runtime: 0.0024781227111816406
2023-09-28 23:25:15,721 - utils - INFO -  epoch: 330, all client loss: [0.6319366097450256, 0.6668081879615784], all pred client disparities: [0.0515950508415699, 0.11026964336633682], all client disparities: [0.03166666626930237, 0.11272219568490982], all client accs: [0.6061339378356934, 0.5546903610229492],  alpha_performance: tensor([0.7466, 0.2534], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:15,770 - utils - INFO - stage1_gradient_single_runtime: 0.002223491668701172
2023-09-28 23:25:15,771 - utils - INFO -  epoch: 331, all client loss: [0.6319844722747803, 0.6667608618736267], all pred client disparities: [0.051186926662921906, 0.11026978492736816], all client disparities: [0.03166666626930237, 0.11185937374830246], all client accs: [0.6061339378356934, 0.5550525188446045],  alpha_performance: tensor([0.7461, 0.2539], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:15,824 - utils - INFO - stage1_gradient_single_runtime: 0.0022449493408203125
2023-09-28 23:25:15,825 - utils - INFO -  epoch: 332, all client loss: [0.6320323348045349, 0.6667135953903198], all pred client disparities: [0.050786782056093216, 0.11027057468891144], all client disparities: [0.029999999329447746, 0.11176937073469162], all client accs: [0.6053268313407898, 0.5557768940925598],  alpha_performance: tensor([0.7455, 0.2545], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:15,877 - utils - INFO - stage1_gradient_single_runtime: 0.0022580623626708984
2023-09-28 23:25:15,879 - utils - INFO -  epoch: 333, all client loss: [0.6320801377296448, 0.6666662096977234], all pred client disparities: [0.05039441958069801, 0.11027207225561142], all client disparities: [0.028333334252238274, 0.11202696710824966], all client accs: [0.604519784450531, 0.5559580326080322],  alpha_performance: tensor([0.7450, 0.2550], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:15,930 - utils - INFO - stage1_gradient_single_runtime: 0.0024886131286621094
2023-09-28 23:25:15,931 - utils - INFO -  epoch: 334, all client loss: [0.6321280598640442, 0.6666187644004822], all pred client disparities: [0.05000961571931839, 0.11027425527572632], all client disparities: [0.028333334252238274, 0.11262596398591995], all client accs: [0.6049233078956604, 0.5565012693405151],  alpha_performance: tensor([0.7444, 0.2556], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:16,029 - utils - INFO - stage1_gradient_single_runtime: 0.0026750564575195312
2023-09-28 23:25:16,031 - utils - INFO -  epoch: 335, all client loss: [0.6321759223937988, 0.6665714383125305], all pred client disparities: [0.049632176756858826, 0.11027704179286957], all client disparities: [0.028333334252238274, 0.11107414215803146], all client accs: [0.6049233078956604, 0.5566823482513428],  alpha_performance: tensor([0.7438, 0.2562], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:16,082 - utils - INFO - stage1_gradient_single_runtime: 0.0023441314697265625
2023-09-28 23:25:16,083 - utils - INFO -  epoch: 336, all client loss: [0.6322237849235535, 0.6665240526199341], all pred client disparities: [0.0492619089782238, 0.11028043925762177], all client disparities: [0.028333334252238274, 0.11167313903570175], all client accs: [0.6049233078956604, 0.5575878620147705],  alpha_performance: tensor([0.7433, 0.2567], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:16,135 - utils - INFO - stage1_gradient_single_runtime: 0.002219676971435547
2023-09-28 23:25:16,136 - utils - INFO -  epoch: 337, all client loss: [0.6322717070579529, 0.6664766073226929], all pred client disparities: [0.0488986037671566, 0.11028441786766052], all client disparities: [0.02666666731238365, 0.1120145171880722], all client accs: [0.6041162014007568, 0.5583122372627258],  alpha_performance: tensor([0.7428, 0.2572], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:16,186 - utils - INFO - stage1_gradient_single_runtime: 0.0021867752075195312
2023-09-28 23:25:16,187 - utils - INFO -  epoch: 338, all client loss: [0.6323195695877075, 0.6664292216300964], all pred client disparities: [0.04854210466146469, 0.11028897762298584], all client disparities: [0.02666666731238365, 0.11209830641746521], all client accs: [0.6041162014007568, 0.5588555335998535],  alpha_performance: tensor([0.7422, 0.2578], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:16,235 - utils - INFO - stage1_gradient_single_runtime: 0.002145528793334961
2023-09-28 23:25:16,236 - utils - INFO -  epoch: 339, all client loss: [0.6323674321174622, 0.6663818359375], all pred client disparities: [0.048192210495471954, 0.11029407382011414], all client disparities: [0.02666666731238365, 0.11243970692157745], all client accs: [0.6041162014007568, 0.5593987703323364],  alpha_performance: tensor([0.7417, 0.2583], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:16,256 - utils - INFO - valid: True, epoch: 339, loss: [0.6275753974914551, 0.67158043384552], accuracy: [0.6191999912261963, 0.5418181419372559], mean_accuracy:0.5805090665817261,variance_accuracy:0.038690924644470215, disparity: [0.01773049682378769, 0.14281979203224182], mean_disparity:0.08027514442801476,variance_disparity:0.06254464760422707, pred_disparity: [0.04643621668219566, 0.1293160766363144]
2023-09-28 23:25:16,267 - utils - INFO - global_valid: True, epoch: 339,  global_loss: 0.6578288674354553, global_accuracy: 0.7609503801520608,  global_disparity:0.11516329646110535, global_pred_disparity: 0.11195223033428192,
2023-09-28 23:25:16,314 - utils - INFO - stage1_gradient_single_runtime: 0.002308368682861328
2023-09-28 23:25:16,315 - utils - INFO -  epoch: 340, all client loss: [0.6324151754379272, 0.6663345098495483], all pred client disparities: [0.04784875735640526, 0.11029969900846481], all client disparities: [0.02666666731238365, 0.11347010731697083], all client accs: [0.6041162014007568, 0.5599420666694641],  alpha_performance: tensor([0.7411, 0.2589], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:16,368 - utils - INFO - stage1_gradient_single_runtime: 0.0022611618041992188
2023-09-28 23:25:16,369 - utils - INFO -  epoch: 341, all client loss: [0.6324630379676819, 0.6662871241569519], all pred client disparities: [0.04751158505678177, 0.11030585318803787], all client disparities: [0.025833332911133766, 0.11372770369052887], all client accs: [0.6037126779556274, 0.5603042840957642],  alpha_performance: tensor([0.7406, 0.2594], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:16,420 - utils - INFO - stage1_gradient_single_runtime: 0.002184629440307617
2023-09-28 23:25:16,420 - utils - INFO -  epoch: 342, all client loss: [0.632510781288147, 0.6662397980690002], all pred client disparities: [0.04718051478266716, 0.11031246930360794], all client disparities: [0.025833332911133766, 0.11424289643764496], all client accs: [0.6037126779556274, 0.5604853630065918],  alpha_performance: tensor([0.7401, 0.2599], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:16,471 - utils - INFO - stage1_gradient_single_runtime: 0.002544879913330078
2023-09-28 23:25:16,472 - utils - INFO -  epoch: 343, all client loss: [0.6325584650039673, 0.6661925315856934], all pred client disparities: [0.04685540497303009, 0.11031956970691681], all client disparities: [0.025833332911133766, 0.11424289643764496], all client accs: [0.6037126779556274, 0.5604853630065918],  alpha_performance: tensor([0.7396, 0.2604], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:16,523 - utils - INFO - stage1_gradient_single_runtime: 0.002245664596557617
2023-09-28 23:25:16,526 - utils - INFO -  epoch: 344, all client loss: [0.6326061487197876, 0.6661452651023865], all pred client disparities: [0.04653611406683922, 0.11032713204622269], all client disparities: [0.02500000037252903, 0.11381148546934128], all client accs: [0.6033090949058533, 0.5606664419174194],  alpha_performance: tensor([0.7390, 0.2610], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:16,575 - utils - INFO - stage1_gradient_single_runtime: 0.002177715301513672
2023-09-28 23:25:16,577 - utils - INFO -  epoch: 345, all client loss: [0.6326538324356079, 0.6660980582237244], all pred client disparities: [0.046222470700740814, 0.11033512651920319], all client disparities: [0.024166665971279144, 0.11312248557806015], all client accs: [0.6029055714607239, 0.5604853630065918],  alpha_performance: tensor([0.7385, 0.2615], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:16,627 - utils - INFO - stage1_gradient_single_runtime: 0.002269268035888672
2023-09-28 23:25:16,628 - utils - INFO -  epoch: 346, all client loss: [0.6327014565467834, 0.6660507917404175], all pred client disparities: [0.04591434821486473, 0.11034353822469711], all client disparities: [0.024166665971279144, 0.11389528959989548], all client accs: [0.6029055714607239, 0.5610285997390747],  alpha_performance: tensor([0.7380, 0.2620], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:16,678 - utils - INFO - stage1_gradient_single_runtime: 0.0022017955780029297
2023-09-28 23:25:16,679 - utils - INFO -  epoch: 347, all client loss: [0.6327489614486694, 0.6660037040710449], all pred client disparities: [0.04561159759759903, 0.11035238206386566], all client disparities: [0.024166665971279144, 0.11441048234701157], all client accs: [0.6029055714607239, 0.5612097382545471],  alpha_performance: tensor([0.7375, 0.2625], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:16,733 - utils - INFO - stage1_gradient_single_runtime: 0.002360105514526367
2023-09-28 23:25:16,734 - utils - INFO -  epoch: 348, all client loss: [0.6327965259552002, 0.6659565567970276], all pred client disparities: [0.04531409591436386, 0.11036159843206406], all client disparities: [0.024166665971279144, 0.11449428647756577], all client accs: [0.6029055714607239, 0.5615718960762024],  alpha_performance: tensor([0.7370, 0.2630], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:16,852 - utils - INFO - stage1_gradient_single_runtime: 0.0023407936096191406
2023-09-28 23:25:16,853 - utils - INFO -  epoch: 349, all client loss: [0.6328439712524414, 0.665909469127655], all pred client disparities: [0.04502170532941818, 0.1103711947798729], all client disparities: [0.023333333432674408, 0.11414666473865509], all client accs: [0.6025019884109497, 0.5621151924133301],  alpha_performance: tensor([0.7365, 0.2635], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:16,907 - utils - INFO - stage1_gradient_single_runtime: 0.0023758411407470703
2023-09-28 23:25:16,907 - utils - INFO -  epoch: 350, all client loss: [0.6328912973403931, 0.6658624410629272], all pred client disparities: [0.04473431035876274, 0.11038113385438919], all client disparities: [0.02250000089406967, 0.11466185748577118], all client accs: [0.6020984649658203, 0.5622962713241577],  alpha_performance: tensor([0.7360, 0.2640], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:16,958 - utils - INFO - stage1_gradient_single_runtime: 0.0022525787353515625
2023-09-28 23:25:16,960 - utils - INFO -  epoch: 351, all client loss: [0.6329386830329895, 0.6658154726028442], all pred client disparities: [0.04445177689194679, 0.11039145290851593], all client disparities: [0.02250000089406967, 0.11440426111221313], all client accs: [0.6020984649658203, 0.5621151924133301],  alpha_performance: tensor([0.7355, 0.2645], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:17,013 - utils - INFO - stage1_gradient_single_runtime: 0.0022842884063720703
2023-09-28 23:25:17,014 - utils - INFO -  epoch: 352, all client loss: [0.6329859495162964, 0.665768563747406], all pred client disparities: [0.04417398199439049, 0.11040206998586655], all client disparities: [0.021666666492819786, 0.11414666473865509], all client accs: [0.6016948819160461, 0.5619341135025024],  alpha_performance: tensor([0.7350, 0.2650], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:17,064 - utils - INFO - stage1_gradient_single_runtime: 0.002216339111328125
2023-09-28 23:25:17,065 - utils - INFO -  epoch: 353, all client loss: [0.6330331563949585, 0.6657217144966125], all pred client disparities: [0.04390082508325577, 0.11041303724050522], all client disparities: [0.021666666492819786, 0.11414666473865509], all client accs: [0.6016948819160461, 0.5619341135025024],  alpha_performance: tensor([0.7345, 0.2655], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:17,116 - utils - INFO - stage1_gradient_single_runtime: 0.0023164749145507812
2023-09-28 23:25:17,119 - utils - INFO -  epoch: 354, all client loss: [0.6330803036689758, 0.6656749248504639], all pred client disparities: [0.043632201850414276, 0.11042428016662598], all client disparities: [0.021666666492819786, 0.11397285759449005], all client accs: [0.6016948819160461, 0.5621151924133301],  alpha_performance: tensor([0.7340, 0.2660], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:17,171 - utils - INFO - stage1_gradient_single_runtime: 0.0022034645080566406
2023-09-28 23:25:17,172 - utils - INFO -  epoch: 355, all client loss: [0.6331273913383484, 0.66562819480896], all pred client disparities: [0.04336798936128616, 0.110435850918293], all client disparities: [0.021666666492819786, 0.11526085436344147], all client accs: [0.6016948819160461, 0.5628395676612854],  alpha_performance: tensor([0.7336, 0.2664], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:17,225 - utils - INFO - stage1_gradient_single_runtime: 0.002705812454223633
2023-09-28 23:25:17,227 - utils - INFO -  epoch: 356, all client loss: [0.6331743597984314, 0.6655815243721008], all pred client disparities: [0.043108079582452774, 0.11044768244028091], all client disparities: [0.02083333395421505, 0.11491323262453079], all client accs: [0.6012913584709167, 0.5633828639984131],  alpha_performance: tensor([0.7331, 0.2669], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:17,278 - utils - INFO - stage1_gradient_single_runtime: 0.0021660327911376953
2023-09-28 23:25:17,279 - utils - INFO -  epoch: 357, all client loss: [0.6332213282585144, 0.6655348539352417], all pred client disparities: [0.04285237938165665, 0.11045979708433151], all client disparities: [0.02083333395421505, 0.11568603664636612], all client accs: [0.6016948819160461, 0.5635639429092407],  alpha_performance: tensor([0.7326, 0.2674], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:17,334 - utils - INFO - stage1_gradient_single_runtime: 0.002310037612915039
2023-09-28 23:25:17,335 - utils - INFO -  epoch: 358, all client loss: [0.6332681775093079, 0.6654883623123169], all pred client disparities: [0.04260079190135002, 0.11047215014696121], all client disparities: [0.02083333395421505, 0.11645884066820145], all client accs: [0.6016948819160461, 0.563926100730896],  alpha_performance: tensor([0.7321, 0.2679], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:17,385 - utils - INFO - stage1_gradient_single_runtime: 0.002300739288330078
2023-09-28 23:25:17,386 - utils - INFO -  epoch: 359, all client loss: [0.6333150267601013, 0.6654419302940369], all pred client disparities: [0.042353205382823944, 0.11048475652933121], all client disparities: [0.02083333395421505, 0.11705781519412994], all client accs: [0.6016948819160461, 0.5644693970680237],  alpha_performance: tensor([0.7317, 0.2683], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:17,405 - utils - INFO - valid: True, epoch: 359, loss: [0.6282600164413452, 0.6707229614257812], accuracy: [0.6191999912261963, 0.5563636422157288], mean_accuracy:0.5877818167209625,variance_accuracy:0.031418174505233765, disparity: [0.01773049682378769, 0.14160335063934326], mean_disparity:0.07966692373156548,variance_disparity:0.061936426907777786, pred_disparity: [0.0404464490711689, 0.12911297380924225]
2023-09-28 23:25:17,416 - utils - INFO - global_valid: True, epoch: 359,  global_loss: 0.6574532985687256, global_accuracy: 0.7568147258903561,  global_disparity:0.11457663774490356, global_pred_disparity: 0.11057766526937485,
2023-09-28 23:25:17,468 - utils - INFO - stage1_gradient_single_runtime: 0.002549886703491211
2023-09-28 23:25:17,469 - utils - INFO -  epoch: 360, all client loss: [0.6333616971969604, 0.6653954982757568], all pred client disparities: [0.042109549045562744, 0.11049763858318329], all client disparities: [0.02083333395421505, 0.11731541156768799], all client accs: [0.6016948819160461, 0.5646505355834961],  alpha_performance: tensor([0.7312, 0.2688], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:17,521 - utils - INFO - stage1_gradient_single_runtime: 0.0021820068359375
2023-09-28 23:25:17,522 - utils - INFO -  epoch: 361, all client loss: [0.6334083676338196, 0.6653491854667664], all pred client disparities: [0.04186972603201866, 0.1105106920003891], all client disparities: [0.02083333395421505, 0.11645260453224182], all client accs: [0.6016948819160461, 0.5644693970680237],  alpha_performance: tensor([0.7307, 0.2693], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:17,628 - utils - INFO - stage1_gradient_single_runtime: 0.002187013626098633
2023-09-28 23:25:17,630 - utils - INFO -  epoch: 362, all client loss: [0.6334548592567444, 0.6653029322624207], all pred client disparities: [0.04163363203406334, 0.11052397638559341], all client disparities: [0.02083333395421505, 0.1169678121805191], all client accs: [0.6016948819160461, 0.5646505355834961],  alpha_performance: tensor([0.7303, 0.2697], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:17,684 - utils - INFO - stage1_gradient_single_runtime: 0.002239227294921875
2023-09-28 23:25:17,684 - utils - INFO -  epoch: 363, all client loss: [0.6335013508796692, 0.6652567982673645], all pred client disparities: [0.04140119627118111, 0.11053749918937683], all client disparities: [0.02083333395421505, 0.11722540855407715], all client accs: [0.6016948819160461, 0.5646505355834961],  alpha_performance: tensor([0.7298, 0.2702], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:17,734 - utils - INFO - stage1_gradient_single_runtime: 0.0021719932556152344
2023-09-28 23:25:17,735 - utils - INFO -  epoch: 364, all client loss: [0.6335477828979492, 0.6652107238769531], all pred client disparities: [0.0411723367869854, 0.11055117100477219], all client disparities: [0.02083333395421505, 0.11748300492763519], all client accs: [0.6016948819160461, 0.5648316144943237],  alpha_performance: tensor([0.7294, 0.2706], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:17,787 - utils - INFO - stage1_gradient_single_runtime: 0.0022783279418945312
2023-09-28 23:25:17,788 - utils - INFO -  epoch: 365, all client loss: [0.6335940957069397, 0.6651647090911865], all pred client disparities: [0.040946971625089645, 0.11056508123874664], all client disparities: [0.019999999552965164, 0.11808199435472488], all client accs: [0.6016948819160461, 0.5657370686531067],  alpha_performance: tensor([0.7289, 0.2711], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:17,837 - utils - INFO - stage1_gradient_single_runtime: 0.0022361278533935547
2023-09-28 23:25:17,838 - utils - INFO -  epoch: 366, all client loss: [0.6336402893066406, 0.6651188135147095], all pred client disparities: [0.040725015103816986, 0.11057913303375244], all client disparities: [0.019999999552965164, 0.11833959072828293], all client accs: [0.6016948819160461, 0.5657370686531067],  alpha_performance: tensor([0.7285, 0.2715], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:17,890 - utils - INFO - stage1_gradient_single_runtime: 0.0022735595703125
2023-09-28 23:25:17,891 - utils - INFO -  epoch: 367, all client loss: [0.633686363697052, 0.6650729775428772], all pred client disparities: [0.04050639644265175, 0.11059336364269257], all client disparities: [0.019999999552965164, 0.11885479837656021], all client accs: [0.6016948819160461, 0.5659181475639343],  alpha_performance: tensor([0.7280, 0.2720], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:17,941 - utils - INFO - stage1_gradient_single_runtime: 0.0022735595703125
2023-09-28 23:25:17,942 - utils - INFO -  epoch: 368, all client loss: [0.6337323784828186, 0.6650271415710449], all pred client disparities: [0.040291041135787964, 0.11060775816440582], all client disparities: [0.019166667014360428, 0.11893858760595322], all client accs: [0.6012913584709167, 0.5659181475639343],  alpha_performance: tensor([0.7276, 0.2724], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:17,992 - utils - INFO - stage1_gradient_single_runtime: 0.002285003662109375
2023-09-28 23:25:17,993 - utils - INFO -  epoch: 369, all client loss: [0.6337783932685852, 0.6649815440177917], all pred client disparities: [0.040078867226839066, 0.11062230169773102], all client disparities: [0.019166667014360428, 0.11919618397951126], all client accs: [0.6012913584709167, 0.5657370686531067],  alpha_performance: tensor([0.7272, 0.2728], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:18,044 - utils - INFO - stage1_gradient_single_runtime: 0.0022602081298828125
2023-09-28 23:25:18,046 - utils - INFO -  epoch: 370, all client loss: [0.6338242292404175, 0.6649359464645386], all pred client disparities: [0.03986981511116028, 0.11063697934150696], all client disparities: [0.019166667014360428, 0.12022658437490463], all client accs: [0.6012913584709167, 0.566461443901062],  alpha_performance: tensor([0.7267, 0.2733], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:18,098 - utils - INFO - stage1_gradient_single_runtime: 0.0025517940521240234
2023-09-28 23:25:18,100 - utils - INFO -  epoch: 371, all client loss: [0.633870005607605, 0.664890468120575], all pred client disparities: [0.03966381400823593, 0.11065179854631424], all client disparities: [0.019166667014360428, 0.11944755911827087], all client accs: [0.6012913584709167, 0.5671858191490173],  alpha_performance: tensor([0.7263, 0.2737], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:18,150 - utils - INFO - stage1_gradient_single_runtime: 0.0022287368774414062
2023-09-28 23:25:18,151 - utils - INFO -  epoch: 372, all client loss: [0.6339156627655029, 0.6648450493812561], all pred client disparities: [0.03946080431342125, 0.11066673696041107], all client disparities: [0.018333332613110542, 0.11884234100580215], all client accs: [0.6008877754211426, 0.567729115486145],  alpha_performance: tensor([0.7259, 0.2741], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:18,202 - utils - INFO - stage1_gradient_single_runtime: 0.002212047576904297
2023-09-28 23:25:18,203 - utils - INFO -  epoch: 373, all client loss: [0.6339612007141113, 0.664799690246582], all pred client disparities: [0.039260704070329666, 0.11068180203437805], all client disparities: [0.018333332613110542, 0.11909995228052139], all client accs: [0.6008877754211426, 0.567729115486145],  alpha_performance: tensor([0.7254, 0.2746], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:18,306 - utils - INFO - stage1_gradient_single_runtime: 0.002580881118774414
2023-09-28 23:25:18,307 - utils - INFO -  epoch: 374, all client loss: [0.634006679058075, 0.6647545099258423], all pred client disparities: [0.0390634648501873, 0.11069697886705399], all client disparities: [0.017500000074505806, 0.12021414190530777], all client accs: [0.6004842519760132, 0.568996787071228],  alpha_performance: tensor([0.7250, 0.2750], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:18,359 - utils - INFO - stage1_gradient_single_runtime: 0.0022704601287841797
2023-09-28 23:25:18,360 - utils - INFO -  epoch: 375, all client loss: [0.6340520977973938, 0.6647093892097473], all pred client disparities: [0.03886903449892998, 0.11071228981018066], all client disparities: [0.017500000074505806, 0.12029792368412018], all client accs: [0.6004842519760132, 0.5693589448928833],  alpha_performance: tensor([0.7246, 0.2754], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:18,409 - utils - INFO - stage1_gradient_single_runtime: 0.002209901809692383
2023-09-28 23:25:18,410 - utils - INFO -  epoch: 376, all client loss: [0.6340973377227783, 0.6646643280982971], all pred client disparities: [0.03867733106017113, 0.11072766035795212], all client disparities: [0.017500000074505806, 0.11908749490976334], all client accs: [0.6004842519760132, 0.5704455375671387],  alpha_performance: tensor([0.7242, 0.2758], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:18,461 - utils - INFO - stage1_gradient_single_runtime: 0.0022220611572265625
2023-09-28 23:25:18,462 - utils - INFO -  epoch: 377, all client loss: [0.6341425180435181, 0.6646193861961365], all pred client disparities: [0.03848830983042717, 0.11074312776327133], all client disparities: [0.017500000074505806, 0.11908749490976334], all client accs: [0.6004842519760132, 0.5700833201408386],  alpha_performance: tensor([0.7237, 0.2763], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:18,515 - utils - INFO - stage1_gradient_single_runtime: 0.002254009246826172
2023-09-28 23:25:18,516 - utils - INFO -  epoch: 378, all client loss: [0.6341876983642578, 0.6645745635032654], all pred client disparities: [0.03830191120505333, 0.11075868457555771], all client disparities: [0.017500000074505806, 0.11934510618448257], all client accs: [0.6004842519760132, 0.5702643990516663],  alpha_performance: tensor([0.7233, 0.2767], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:18,570 - utils - INFO - stage1_gradient_single_runtime: 0.002561807632446289
2023-09-28 23:25:18,571 - utils - INFO -  epoch: 379, all client loss: [0.6342325806617737, 0.6645298004150391], all pred client disparities: [0.03811807930469513, 0.11077431589365005], all client disparities: [0.017500000074505806, 0.1189136952161789], all client accs: [0.6004842519760132, 0.5704455375671387],  alpha_performance: tensor([0.7229, 0.2771], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:18,589 - utils - INFO - valid: True, epoch: 379, loss: [0.6289699077606201, 0.6698805093765259], accuracy: [0.6191999912261963, 0.5578181743621826], mean_accuracy:0.5885090827941895,variance_accuracy:0.030690908432006836, disparity: [0.01773049682378769, 0.14144998788833618], mean_disparity:0.07959024235606194,variance_disparity:0.061859745532274246, pred_disparity: [0.036179669201374054, 0.12898898124694824]
2023-09-28 23:25:18,600 - utils - INFO - global_valid: True, epoch: 379,  global_loss: 0.6570959687232971, global_accuracy: 0.7530132052821128,  global_disparity:0.11453644931316376, global_pred_disparity: 0.10964671522378922,
2023-09-28 23:25:18,652 - utils - INFO - stage1_gradient_single_runtime: 0.0025517940521240234
2023-09-28 23:25:18,653 - utils - INFO -  epoch: 380, all client loss: [0.6342775225639343, 0.6644852161407471], all pred client disparities: [0.03793676942586899, 0.11079004406929016], all client disparities: [0.017500000074505806, 0.11805088073015213], all client accs: [0.6004842519760132, 0.570807695388794],  alpha_performance: tensor([0.7225, 0.2775], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:18,701 - utils - INFO - stage1_gradient_single_runtime: 0.0023050308227539062
2023-09-28 23:25:18,702 - utils - INFO -  epoch: 381, all client loss: [0.6343223452568054, 0.6644406318664551], all pred client disparities: [0.03775791823863983, 0.11080580949783325], all client disparities: [0.017500000074505806, 0.11839226633310318], all client accs: [0.6004842519760132, 0.5715320706367493],  alpha_performance: tensor([0.7221, 0.2779], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:18,753 - utils - INFO - stage1_gradient_single_runtime: 0.002531766891479492
2023-09-28 23:25:18,754 - utils - INFO -  epoch: 382, all client loss: [0.6343669891357422, 0.6643961668014526], all pred client disparities: [0.03758148103952408, 0.1108216792345047], all client disparities: [0.017500000074505806, 0.11821845918893814], all client accs: [0.6004842519760132, 0.5717131495475769],  alpha_performance: tensor([0.7217, 0.2783], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:18,803 - utils - INFO - stage1_gradient_single_runtime: 0.002233743667602539
2023-09-28 23:25:18,804 - utils - INFO -  epoch: 383, all client loss: [0.634411633014679, 0.664351761341095], all pred client disparities: [0.03740740194916725, 0.11083757132291794], all client disparities: [0.017500000074505806, 0.11778704822063446], all client accs: [0.6004842519760132, 0.5717131495475769],  alpha_performance: tensor([0.7213, 0.2787], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:18,859 - utils - INFO - stage1_gradient_single_runtime: 0.0021810531616210938
2023-09-28 23:25:18,860 - utils - INFO -  epoch: 384, all client loss: [0.6344560384750366, 0.6643074750900269], all pred client disparities: [0.03723563998937607, 0.11085354536771774], all client disparities: [0.01666666753590107, 0.11778704822063446], all client accs: [0.600080668926239, 0.5717131495475769],  alpha_performance: tensor([0.7209, 0.2791], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:18,961 - utils - INFO - stage1_gradient_single_runtime: 0.0022153854370117188
2023-09-28 23:25:18,963 - utils - INFO -  epoch: 385, all client loss: [0.6345004439353943, 0.6642633080482483], all pred client disparities: [0.03706614300608635, 0.11086949706077576], all client disparities: [0.01666666753590107, 0.11830225586891174], all client accs: [0.600080668926239, 0.5717131495475769],  alpha_performance: tensor([0.7205, 0.2795], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:19,015 - utils - INFO - stage1_gradient_single_runtime: 0.0025374889373779297
2023-09-28 23:25:19,017 - utils - INFO -  epoch: 386, all client loss: [0.6345447301864624, 0.664219319820404], all pred client disparities: [0.036898866295814514, 0.11088556051254272], all client disparities: [0.014999999664723873, 0.11890125274658203], all client accs: [0.5992735624313354, 0.5726186037063599],  alpha_performance: tensor([0.7201, 0.2799], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:19,070 - utils - INFO - stage1_gradient_single_runtime: 0.002198934555053711
2023-09-28 23:25:19,070 - utils - INFO -  epoch: 387, all client loss: [0.634588897228241, 0.6641753315925598], all pred client disparities: [0.03673376142978668, 0.1109016016125679], all client disparities: [0.014999999664723873, 0.11941644549369812], all client accs: [0.5992735624313354, 0.5729808211326599],  alpha_performance: tensor([0.7197, 0.2803], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:19,124 - utils - INFO - stage1_gradient_single_runtime: 0.002190113067626953
2023-09-28 23:25:19,124 - utils - INFO -  epoch: 388, all client loss: [0.6346330046653748, 0.6641314029693604], all pred client disparities: [0.036570802330970764, 0.11091771721839905], all client disparities: [0.014166667126119137, 0.11993163824081421], all client accs: [0.598870038986206, 0.57334303855896],  alpha_performance: tensor([0.7193, 0.2807], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:19,175 - utils - INFO - stage1_gradient_single_runtime: 0.0022504329681396484
2023-09-28 23:25:19,176 - utils - INFO -  epoch: 389, all client loss: [0.6346769332885742, 0.6640876531600952], all pred client disparities: [0.036409929394721985, 0.1109338253736496], all client disparities: [0.014166667126119137, 0.11984162777662277], all client accs: [0.598870038986206, 0.5742484927177429],  alpha_performance: tensor([0.7190, 0.2810], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:19,224 - utils - INFO - stage1_gradient_single_runtime: 0.002217531204223633
2023-09-28 23:25:19,227 - utils - INFO -  epoch: 390, all client loss: [0.6347208023071289, 0.6640440225601196], all pred client disparities: [0.03625110536813736, 0.11094997823238373], all client disparities: [0.014166667126119137, 0.11984162777662277], all client accs: [0.598870038986206, 0.5742484927177429],  alpha_performance: tensor([0.7186, 0.2814], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:19,282 - utils - INFO - stage1_gradient_single_runtime: 0.0025763511657714844
2023-09-28 23:25:19,284 - utils - INFO -  epoch: 391, all client loss: [0.634764552116394, 0.6640004515647888], all pred client disparities: [0.0360943004488945, 0.11096613854169846], all client disparities: [0.014166667126119137, 0.11984162777662277], all client accs: [0.598870038986206, 0.5740673542022705],  alpha_performance: tensor([0.7182, 0.2818], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:19,336 - utils - INFO - stage1_gradient_single_runtime: 0.002152681350708008
2023-09-28 23:25:19,336 - utils - INFO -  epoch: 392, all client loss: [0.6348082423210144, 0.6639569997787476], all pred client disparities: [0.03593946248292923, 0.11098229885101318], all client disparities: [0.014166667126119137, 0.11984162777662277], all client accs: [0.598870038986206, 0.5738862752914429],  alpha_performance: tensor([0.7178, 0.2822], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:19,385 - utils - INFO - stage1_gradient_single_runtime: 0.002286672592163086
2023-09-28 23:25:19,386 - utils - INFO -  epoch: 393, all client loss: [0.6348518133163452, 0.6639136075973511], all pred client disparities: [0.03578655794262886, 0.1109984740614891], all client disparities: [0.014166667126119137, 0.12035682052373886], all client accs: [0.598870038986206, 0.5742484927177429],  alpha_performance: tensor([0.7174, 0.2826], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:19,439 - utils - INFO - stage1_gradient_single_runtime: 0.002590179443359375
2023-09-28 23:25:19,440 - utils - INFO -  epoch: 394, all client loss: [0.6348952651023865, 0.6638703942298889], all pred client disparities: [0.03563554584980011, 0.11101466417312622], all client disparities: [0.014166667126119137, 0.12087202817201614], all client accs: [0.598870038986206, 0.5744295716285706],  alpha_performance: tensor([0.7171, 0.2829], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:19,492 - utils - INFO - stage1_gradient_single_runtime: 0.0023534297943115234
2023-09-28 23:25:19,493 - utils - INFO -  epoch: 395, all client loss: [0.6349385380744934, 0.6638272404670715], all pred client disparities: [0.03548638895153999, 0.11103083193302155], all client disparities: [0.014166667126119137, 0.12095581740140915], all client accs: [0.598870038986206, 0.5749728679656982],  alpha_performance: tensor([0.7167, 0.2833], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:19,549 - utils - INFO - stage1_gradient_single_runtime: 0.0024900436401367188
2023-09-28 23:25:19,550 - utils - INFO -  epoch: 396, all client loss: [0.6349817514419556, 0.6637841463088989], all pred client disparities: [0.03533905744552612, 0.11104700714349747], all client disparities: [0.014166667126119137, 0.12052440643310547], all client accs: [0.598870038986206, 0.5751539468765259],  alpha_performance: tensor([0.7163, 0.2837], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:19,647 - utils - INFO - stage1_gradient_single_runtime: 0.0021982192993164062
2023-09-28 23:25:19,649 - utils - INFO -  epoch: 397, all client loss: [0.635024905204773, 0.6637412309646606], all pred client disparities: [0.03519352152943611, 0.11106318980455399], all client disparities: [0.014166667126119137, 0.12078200280666351], all client accs: [0.598870038986206, 0.5753350257873535],  alpha_performance: tensor([0.7160, 0.2840], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:19,698 - utils - INFO - stage1_gradient_single_runtime: 0.0022258758544921875
2023-09-28 23:25:19,699 - utils - INFO -  epoch: 398, all client loss: [0.6350679993629456, 0.6636984348297119], all pred client disparities: [0.03504972904920578, 0.11107932031154633], all client disparities: [0.014166667126119137, 0.12103959918022156], all client accs: [0.598870038986206, 0.5753350257873535],  alpha_performance: tensor([0.7156, 0.2844], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:19,755 - utils - INFO - stage1_gradient_single_runtime: 0.002165555953979492
2023-09-28 23:25:19,756 - utils - INFO -  epoch: 399, all client loss: [0.6351108551025391, 0.6636556386947632], all pred client disparities: [0.034907665103673935, 0.11109546571969986], all client disparities: [0.014166667126119137, 0.12103959918022156], all client accs: [0.598870038986206, 0.5753350257873535],  alpha_performance: tensor([0.7152, 0.2848], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:19,774 - utils - INFO - valid: True, epoch: 399, loss: [0.629680871963501, 0.669063150882721], accuracy: [0.6191999912261963, 0.5592727065086365], mean_accuracy:0.5892363488674164,variance_accuracy:0.029963642358779907, disparity: [0.01773049682378769, 0.13903799653053284], mean_disparity:0.07838424667716026,variance_disparity:0.060653749853372574, pred_disparity: [0.032996222376823425, 0.12885911762714386]
2023-09-28 23:25:19,787 - utils - INFO - global_valid: True, epoch: 399,  global_loss: 0.6567562222480774, global_accuracy: 0.7494942977190877,  global_disparity:0.11283271014690399, global_pred_disparity: 0.10895080119371414,
2023-09-28 23:25:19,833 - utils - INFO - stage1_gradient_single_runtime: 0.002263307571411133
2023-09-28 23:25:19,835 - utils - INFO -  epoch: 400, all client loss: [0.6351537108421326, 0.6636130809783936], all pred client disparities: [0.03476729243993759, 0.11111157387495041], all client disparities: [0.014166667126119137, 0.12017679214477539], all client accs: [0.598870038986206, 0.5756972432136536],  alpha_performance: tensor([0.7149, 0.2851], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:19,886 - utils - INFO - stage1_gradient_single_runtime: 0.0022182464599609375
2023-09-28 23:25:19,886 - utils - INFO -  epoch: 401, all client loss: [0.6351963877677917, 0.6635705232620239], all pred client disparities: [0.034628573805093765, 0.11112765967845917], all client disparities: [0.014166667126119137, 0.11974538117647171], all client accs: [0.598870038986206, 0.5758783221244812],  alpha_performance: tensor([0.7145, 0.2855], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:19,938 - utils - INFO - stage1_gradient_single_runtime: 0.0022516250610351562
2023-09-28 23:25:19,938 - utils - INFO -  epoch: 402, all client loss: [0.6352390050888062, 0.6635280847549438], all pred client disparities: [0.03449149429798126, 0.11114373803138733], all client disparities: [0.014166667126119137, 0.11888256669044495], all client accs: [0.598870038986206, 0.5762405395507812],  alpha_performance: tensor([0.7142, 0.2858], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:19,990 - utils - INFO - stage1_gradient_single_runtime: 0.002229928970336914
2023-09-28 23:25:19,991 - utils - INFO -  epoch: 403, all client loss: [0.635281503200531, 0.6634857058525085], all pred client disparities: [0.034355998039245605, 0.11115976423025131], all client disparities: [0.014166667126119137, 0.11845116317272186], all client accs: [0.598870038986206, 0.5764216184616089],  alpha_performance: tensor([0.7138, 0.2862], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:20,043 - utils - INFO - stage1_gradient_single_runtime: 0.0022759437561035156
2023-09-28 23:25:20,044 - utils - INFO -  epoch: 404, all client loss: [0.6353238224983215, 0.6634435653686523], all pred client disparities: [0.0342220701277256, 0.11117575317621231], all client disparities: [0.014166667126119137, 0.11827737092971802], all client accs: [0.598870038986206, 0.5767837762832642],  alpha_performance: tensor([0.7135, 0.2865], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:20,096 - utils - INFO - stage1_gradient_single_runtime: 0.002207517623901367
2023-09-28 23:25:20,098 - utils - INFO -  epoch: 405, all client loss: [0.6353660821914673, 0.6634014248847961], all pred client disparities: [0.03408968821167946, 0.1111917495727539], all client disparities: [0.014166667126119137, 0.11827737092971802], all client accs: [0.598870038986206, 0.5766026973724365],  alpha_performance: tensor([0.7131, 0.2869], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:20,148 - utils - INFO - stage1_gradient_single_runtime: 0.0025167465209960938
2023-09-28 23:25:20,150 - utils - INFO -  epoch: 406, all client loss: [0.635408341884613, 0.6633594036102295], all pred client disparities: [0.03395882993936539, 0.11120767146348953], all client disparities: [0.014166667126119137, 0.11784595996141434], all client accs: [0.598870038986206, 0.5766026973724365],  alpha_performance: tensor([0.7128, 0.2872], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:20,206 - utils - INFO - stage1_gradient_single_runtime: 0.0024847984313964844
2023-09-28 23:25:20,208 - utils - INFO -  epoch: 407, all client loss: [0.6354503631591797, 0.6633175015449524], all pred client disparities: [0.03382944315671921, 0.11122355610132217], all client disparities: [0.014166667126119137, 0.11741455644369125], all client accs: [0.598870038986206, 0.5767837762832642],  alpha_performance: tensor([0.7124, 0.2876], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:20,258 - utils - INFO - stage1_gradient_single_runtime: 0.0021924972534179688
2023-09-28 23:25:20,259 - utils - INFO -  epoch: 408, all client loss: [0.6354923248291016, 0.6632757186889648], all pred client disparities: [0.033701520413160324, 0.11123940348625183], all client disparities: [0.014166667126119137, 0.11689312756061554], all client accs: [0.598870038986206, 0.5776892900466919],  alpha_performance: tensor([0.7121, 0.2879], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:20,358 - utils - INFO - stage1_gradient_single_runtime: 0.002213716506958008
2023-09-28 23:25:20,359 - utils - INFO -  epoch: 409, all client loss: [0.6355341672897339, 0.6632339954376221], all pred client disparities: [0.03357502445578575, 0.1112552210688591], all client disparities: [0.014166667126119137, 0.11740832030773163], all client accs: [0.598870038986206, 0.5780514478683472],  alpha_performance: tensor([0.7117, 0.2883], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:20,412 - utils - INFO - stage1_gradient_single_runtime: 0.0025398731231689453
2023-09-28 23:25:20,414 - utils - INFO -  epoch: 410, all client loss: [0.6355759501457214, 0.6631923913955688], all pred client disparities: [0.033449936658144, 0.111270971596241], all client disparities: [0.014166667126119137, 0.11792352795600891], all client accs: [0.598870038986206, 0.5784136056900024],  alpha_performance: tensor([0.7114, 0.2886], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:20,467 - utils - INFO - stage1_gradient_single_runtime: 0.0021660327911376953
2023-09-28 23:25:20,468 - utils - INFO -  epoch: 411, all client loss: [0.6356176137924194, 0.66315096616745], all pred client disparities: [0.03332623466849327, 0.11128667742013931], all client disparities: [0.014166667126119137, 0.11800730973482132], all client accs: [0.598870038986206, 0.5789569020271301],  alpha_performance: tensor([0.7111, 0.2889], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:20,524 - utils - INFO - stage1_gradient_single_runtime: 0.0028450489044189453
2023-09-28 23:25:20,525 - utils - INFO -  epoch: 412, all client loss: [0.6356590986251831, 0.663109540939331], all pred client disparities: [0.033203888684511185, 0.11130231618881226], all client disparities: [0.014166667126119137, 0.11783350259065628], all client accs: [0.598870038986206, 0.5793191194534302],  alpha_performance: tensor([0.7107, 0.2893], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:20,573 - utils - INFO - stage1_gradient_single_runtime: 0.0021965503692626953
2023-09-28 23:25:20,574 - utils - INFO -  epoch: 413, all client loss: [0.6357005834579468, 0.6630682945251465], all pred client disparities: [0.03308287635445595, 0.11131789535284042], all client disparities: [0.014166667126119137, 0.11791730672121048], all client accs: [0.598870038986206, 0.5798623561859131],  alpha_performance: tensor([0.7104, 0.2896], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:20,623 - utils - INFO - stage1_gradient_single_runtime: 0.002226591110229492
2023-09-28 23:25:20,624 - utils - INFO -  epoch: 414, all client loss: [0.6357418894767761, 0.6630270481109619], all pred client disparities: [0.03296317905187607, 0.1113334372639656], all client disparities: [0.013333333656191826, 0.11817490309476852], all client accs: [0.5984665155410767, 0.5800434947013855],  alpha_performance: tensor([0.7101, 0.2899], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:20,677 - utils - INFO - stage1_gradient_single_runtime: 0.0024619102478027344
2023-09-28 23:25:20,677 - utils - INFO -  epoch: 415, all client loss: [0.6357830762863159, 0.6629860401153564], all pred client disparities: [0.032844774425029755, 0.11134888976812363], all client disparities: [0.013333333656191826, 0.11817490309476852], all client accs: [0.5984665155410767, 0.5798623561859131],  alpha_performance: tensor([0.7097, 0.2903], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:20,738 - utils - INFO - stage1_gradient_single_runtime: 0.002530813217163086
2023-09-28 23:25:20,740 - utils - INFO -  epoch: 416, all client loss: [0.6358242630958557, 0.6629450917243958], all pred client disparities: [0.03272762522101402, 0.11136430501937866], all client disparities: [0.013333333656191826, 0.11800108850002289], all client accs: [0.5984665155410767, 0.5800434947013855],  alpha_performance: tensor([0.7094, 0.2906], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:20,790 - utils - INFO - stage1_gradient_single_runtime: 0.002236604690551758
2023-09-28 23:25:20,791 - utils - INFO -  epoch: 417, all client loss: [0.6358652114868164, 0.6629042029380798], all pred client disparities: [0.03261173889040947, 0.11137967556715012], all client disparities: [0.013333333656191826, 0.11739587038755417], all client accs: [0.5984665155410767, 0.5805867910385132],  alpha_performance: tensor([0.7091, 0.2909], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:20,841 - utils - INFO - stage1_gradient_single_runtime: 0.0021827220916748047
2023-09-28 23:25:20,842 - utils - INFO -  epoch: 418, all client loss: [0.6359061002731323, 0.6628634929656982], all pred client disparities: [0.032497063279151917, 0.11139494180679321], all client disparities: [0.013333333656191826, 0.11765348166227341], all client accs: [0.5984665155410767, 0.5807678699493408],  alpha_performance: tensor([0.7087, 0.2913], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:20,894 - utils - INFO - stage1_gradient_single_runtime: 0.002416372299194336
2023-09-28 23:25:20,895 - utils - INFO -  epoch: 419, all client loss: [0.6359469294548035, 0.6628227829933167], all pred client disparities: [0.03238359093666077, 0.11141014844179153], all client disparities: [0.013333333656191826, 0.11722207814455032], all client accs: [0.5984665155410767, 0.5807678699493408],  alpha_performance: tensor([0.7084, 0.2916], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:20,914 - utils - INFO - valid: True, epoch: 419, loss: [0.6303797960281372, 0.6682750582695007], accuracy: [0.6175999641418457, 0.5629090666770935], mean_accuracy:0.5902545154094696,variance_accuracy:0.0273454487323761, disparity: [0.014184396713972092, 0.14685605466365814], mean_disparity:0.08052022568881512,variance_disparity:0.06633582897484303, pred_disparity: [0.030527528375387192, 0.12867531180381775]
2023-09-28 23:25:20,930 - utils - INFO - global_valid: True, epoch: 419,  global_loss: 0.6564328670501709, global_accuracy: 0.7463295318127251,  global_disparity:0.11808859556913376, global_pred_disparity: 0.10837086290121078,
2023-09-28 23:25:20,983 - utils - INFO - stage1_gradient_single_runtime: 0.0022423267364501953
2023-09-28 23:25:20,983 - utils - INFO -  epoch: 420, all client loss: [0.6359875798225403, 0.6627821922302246], all pred client disparities: [0.03227130323648453, 0.11142528802156448], all client disparities: [0.013333333656191826, 0.11782106012105942], all client accs: [0.5984665155410767, 0.5814922451972961],  alpha_performance: tensor([0.7081, 0.2919], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:21,096 - utils - INFO - stage1_gradient_single_runtime: 0.002409696578979492
2023-09-28 23:25:21,097 - utils - INFO -  epoch: 421, all client loss: [0.6360281705856323, 0.6627417802810669], all pred client disparities: [0.03216017782688141, 0.11144036054611206], all client disparities: [0.013333333656191826, 0.11764724552631378], all client accs: [0.5984665155410767, 0.5813111066818237],  alpha_performance: tensor([0.7078, 0.2922], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:21,154 - utils - INFO - stage1_gradient_single_runtime: 0.0029909610748291016
2023-09-28 23:25:21,155 - utils - INFO -  epoch: 422, all client loss: [0.6360687017440796, 0.662701427936554], all pred client disparities: [0.03205019608139992, 0.11145533621311188], all client disparities: [0.012500000186264515, 0.11764724552631378], all client accs: [0.5980629324913025, 0.5813111066818237],  alpha_performance: tensor([0.7075, 0.2925], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:21,212 - utils - INFO - stage1_gradient_single_runtime: 0.002524137496948242
2023-09-28 23:25:21,214 - utils - INFO -  epoch: 423, all client loss: [0.6361090540885925, 0.6626611948013306], all pred client disparities: [0.031941331923007965, 0.11147025227546692], all client disparities: [0.012500000186264515, 0.11790485680103302], all client accs: [0.5980629324913025, 0.5813111066818237],  alpha_performance: tensor([0.7071, 0.2929], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:21,265 - utils - INFO - stage1_gradient_single_runtime: 0.0022690296173095703
2023-09-28 23:25:21,266 - utils - INFO -  epoch: 424, all client loss: [0.6361492872238159, 0.6626210808753967], all pred client disparities: [0.03183358162641525, 0.1114850789308548], all client disparities: [0.012500000186264515, 0.11824624240398407], all client accs: [0.5980629324913025, 0.5820355415344238],  alpha_performance: tensor([0.7068, 0.2932], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:21,315 - utils - INFO - stage1_gradient_single_runtime: 0.0021839141845703125
2023-09-28 23:25:21,316 - utils - INFO -  epoch: 425, all client loss: [0.6361894607543945, 0.6625810265541077], all pred client disparities: [0.03172691538929939, 0.1114998608827591], all client disparities: [0.012500000186264515, 0.11781483143568039], all client accs: [0.5980629324913025, 0.5822166204452515],  alpha_performance: tensor([0.7065, 0.2935], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:21,369 - utils - INFO - stage1_gradient_single_runtime: 0.002775907516479492
2023-09-28 23:25:21,371 - utils - INFO -  epoch: 426, all client loss: [0.6362295746803284, 0.6625410914421082], all pred client disparities: [0.03162132948637009, 0.11151453107595444], all client disparities: [0.012500000186264515, 0.11789863556623459], all client accs: [0.5980629324913025, 0.5827598571777344],  alpha_performance: tensor([0.7062, 0.2938], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:21,427 - utils - INFO - stage1_gradient_single_runtime: 0.0021753311157226562
2023-09-28 23:25:21,428 - utils - INFO -  epoch: 427, all client loss: [0.6362694501876831, 0.6625012755393982], all pred client disparities: [0.03151678666472435, 0.11152911931276321], all client disparities: [0.012500000186264515, 0.1179824247956276], all client accs: [0.5980629324913025, 0.5831220746040344],  alpha_performance: tensor([0.7059, 0.2941], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:21,477 - utils - INFO - stage1_gradient_single_runtime: 0.0022780895233154297
2023-09-28 23:25:21,477 - utils - INFO -  epoch: 428, all client loss: [0.6363093256950378, 0.662461519241333], all pred client disparities: [0.03141327574849129, 0.11154361069202423], all client disparities: [0.012500000186264515, 0.11849761754274368], all client accs: [0.5980629324913025, 0.5834842920303345],  alpha_performance: tensor([0.7056, 0.2944], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:21,526 - utils - INFO - stage1_gradient_single_runtime: 0.002213001251220703
2023-09-28 23:25:21,526 - utils - INFO -  epoch: 429, all client loss: [0.6363491415977478, 0.6624219417572021], all pred client disparities: [0.0313107967376709, 0.11155803501605988], all client disparities: [0.011666666716337204, 0.11849761754274368], all client accs: [0.5976594090461731, 0.5829409956932068],  alpha_performance: tensor([0.7053, 0.2947], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:21,580 - utils - INFO - stage1_gradient_single_runtime: 0.0022280216217041016
2023-09-28 23:25:21,581 - utils - INFO -  epoch: 430, all client loss: [0.6363887190818787, 0.6623823642730713], all pred client disparities: [0.031209314242005348, 0.11157238483428955], all client disparities: [0.011666666716337204, 0.11832381784915924], all client accs: [0.5976594090461731, 0.5831220746040344],  alpha_performance: tensor([0.7050, 0.2950], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:21,631 - utils - INFO - stage1_gradient_single_runtime: 0.002332448959350586
2023-09-28 23:25:21,632 - utils - INFO -  epoch: 431, all client loss: [0.6364282965660095, 0.6623430252075195], all pred client disparities: [0.031108809635043144, 0.11158662289381027], all client disparities: [0.011666666716337204, 0.11858141422271729], all client accs: [0.5976594090461731, 0.5833031535148621],  alpha_performance: tensor([0.7047, 0.2953], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:21,738 - utils - INFO - stage1_gradient_single_runtime: 0.0022153854370117188
2023-09-28 23:25:21,740 - utils - INFO -  epoch: 432, all client loss: [0.636467695236206, 0.6623036861419678], all pred client disparities: [0.031009288504719734, 0.11160077899694443], all client disparities: [0.011666666716337204, 0.11909660696983337], all client accs: [0.5976594090461731, 0.5836653709411621],  alpha_performance: tensor([0.7044, 0.2956], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:21,788 - utils - INFO - stage1_gradient_single_runtime: 0.0022056102752685547
2023-09-28 23:25:21,789 - utils - INFO -  epoch: 433, all client loss: [0.6365070343017578, 0.6622644066810608], all pred client disparities: [0.03091072291135788, 0.11161484569311142], all client disparities: [0.011666666716337204, 0.11909660696983337], all client accs: [0.5976594090461731, 0.5834842920303345],  alpha_performance: tensor([0.7041, 0.2959], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:21,849 - utils - INFO - stage1_gradient_single_runtime: 0.0028226375579833984
2023-09-28 23:25:21,850 - utils - INFO -  epoch: 434, all client loss: [0.6365463137626648, 0.6622253060340881], all pred client disparities: [0.030813094228506088, 0.11162881553173065], all client disparities: [0.011666666716337204, 0.11866520345211029], all client accs: [0.5976594090461731, 0.5836653709411621],  alpha_performance: tensor([0.7038, 0.2962], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:21,900 - utils - INFO - stage1_gradient_single_runtime: 0.0021812915802001953
2023-09-28 23:25:21,901 - utils - INFO -  epoch: 435, all client loss: [0.6365854144096375, 0.662186324596405], all pred client disparities: [0.030716387555003166, 0.11164269596338272], all client disparities: [0.011666666716337204, 0.11823379993438721], all client accs: [0.5976594090461731, 0.5838464498519897],  alpha_performance: tensor([0.7035, 0.2965], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:21,953 - utils - INFO - stage1_gradient_single_runtime: 0.002277374267578125
2023-09-28 23:25:21,953 - utils - INFO -  epoch: 436, all client loss: [0.6366244554519653, 0.6621474027633667], all pred client disparities: [0.030620599165558815, 0.11165647953748703], all client disparities: [0.011666666716337204, 0.11840138584375381], all client accs: [0.5976594090461731, 0.5847519040107727],  alpha_performance: tensor([0.7032, 0.2968], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:22,006 - utils - INFO - stage1_gradient_single_runtime: 0.002578258514404297
2023-09-28 23:25:22,008 - utils - INFO -  epoch: 437, all client loss: [0.6366633772850037, 0.6621086001396179], all pred client disparities: [0.030525706708431244, 0.11167018115520477], all client disparities: [0.011666666716337204, 0.11865898221731186], all client accs: [0.5976594090461731, 0.5847519040107727],  alpha_performance: tensor([0.7029, 0.2971], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:22,058 - utils - INFO - stage1_gradient_single_runtime: 0.0022125244140625
2023-09-28 23:25:22,059 - utils - INFO -  epoch: 438, all client loss: [0.6367022395133972, 0.6620698571205139], all pred client disparities: [0.030431697145104408, 0.11168377846479416], all client disparities: [0.011666666716337204, 0.11874276399612427], all client accs: [0.5976594090461731, 0.5851141214370728],  alpha_performance: tensor([0.7026, 0.2974], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:22,110 - utils - INFO - stage1_gradient_single_runtime: 0.0023241043090820312
2023-09-28 23:25:22,111 - utils - INFO -  epoch: 439, all client loss: [0.6367409229278564, 0.6620312929153442], all pred client disparities: [0.030338551849126816, 0.1116972491145134], all client disparities: [0.011666666716337204, 0.11856897175312042], all client accs: [0.5976594090461731, 0.5851141214370728],  alpha_performance: tensor([0.7023, 0.2977], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:22,131 - utils - INFO - valid: True, epoch: 439, loss: [0.6310599446296692, 0.6675174832344055], accuracy: [0.6159999966621399, 0.5687272548675537], mean_accuracy:0.5923636257648468,variance_accuracy:0.02363637089729309, disparity: [0.010638297535479069, 0.14429068565368652], mean_disparity:0.0774644915945828,variance_disparity:0.06682619405910373, pred_disparity: [0.02855086326599121, 0.1284129023551941]
2023-09-28 23:25:22,144 - utils - INFO - global_valid: True, epoch: 439,  global_loss: 0.6561245322227478, global_accuracy: 0.7432988195278111,  global_disparity:0.11553297936916351, global_pred_disparity: 0.10783856362104416,
2023-09-28 23:25:22,198 - utils - INFO - stage1_gradient_single_runtime: 0.0021867752075195312
2023-09-28 23:25:22,199 - utils - INFO -  epoch: 440, all client loss: [0.6367795467376709, 0.6619927883148193], all pred client disparities: [0.03024626336991787, 0.11171066015958786], all client disparities: [0.011666666716337204, 0.11865276098251343], all client accs: [0.5976594090461731, 0.5856573581695557],  alpha_performance: tensor([0.7020, 0.2980], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:22,251 - utils - INFO - stage1_gradient_single_runtime: 0.002578258514404297
2023-09-28 23:25:22,253 - utils - INFO -  epoch: 441, all client loss: [0.6368181109428406, 0.661954402923584], all pred client disparities: [0.03015482984483242, 0.11172393709421158], all client disparities: [0.011666666716337204, 0.11865276098251343], all client accs: [0.5976594090461731, 0.5856573581695557],  alpha_performance: tensor([0.7017, 0.2983], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:22,303 - utils - INFO - stage1_gradient_single_runtime: 0.0022041797637939453
2023-09-28 23:25:22,304 - utils - INFO -  epoch: 442, all client loss: [0.6368564963340759, 0.6619160175323486], all pred client disparities: [0.030064227059483528, 0.11173713952302933], all client disparities: [0.011666666716337204, 0.11865276098251343], all client accs: [0.5976594090461731, 0.5856573581695557],  alpha_performance: tensor([0.7014, 0.2986], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:22,409 - utils - INFO - stage1_gradient_single_runtime: 0.002844095230102539
2023-09-28 23:25:22,409 - utils - INFO -  epoch: 443, all client loss: [0.6368948221206665, 0.6618778109550476], all pred client disparities: [0.0299744363874197, 0.11175022274255753], all client disparities: [0.011666666716337204, 0.11804754287004471], all client accs: [0.5976594090461731, 0.5862006545066833],  alpha_performance: tensor([0.7012, 0.2988], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:22,463 - utils - INFO - stage1_gradient_single_runtime: 0.0025641918182373047
2023-09-28 23:25:22,464 - utils - INFO -  epoch: 444, all client loss: [0.6369330286979675, 0.6618397235870361], all pred client disparities: [0.02988545037806034, 0.11176321655511856], all client disparities: [0.011666666716337204, 0.11830513924360275], all client accs: [0.5980629324913025, 0.5863817930221558],  alpha_performance: tensor([0.7009, 0.2991], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:22,517 - utils - INFO - stage1_gradient_single_runtime: 0.0025377273559570312
2023-09-28 23:25:22,518 - utils - INFO -  epoch: 445, all client loss: [0.6369711756706238, 0.6618016362190247], all pred client disparities: [0.0297972671687603, 0.11177610605955124], all client disparities: [0.011666666716337204, 0.11830513924360275], all client accs: [0.5980629324913025, 0.5862006545066833],  alpha_performance: tensor([0.7006, 0.2994], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:22,566 - utils - INFO - stage1_gradient_single_runtime: 0.0022177696228027344
2023-09-28 23:25:22,567 - utils - INFO -  epoch: 446, all client loss: [0.6370092034339905, 0.6617637276649475], all pred client disparities: [0.02970985695719719, 0.11178888380527496], all client disparities: [0.011666666716337204, 0.11769993603229523], all client accs: [0.5980629324913025, 0.586743950843811],  alpha_performance: tensor([0.7003, 0.2997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:22,622 - utils - INFO - stage1_gradient_single_runtime: 0.0022406578063964844
2023-09-28 23:25:22,622 - utils - INFO -  epoch: 447, all client loss: [0.6370471119880676, 0.6617258787155151], all pred client disparities: [0.02962322160601616, 0.11180155724287033], all client disparities: [0.011666666716337204, 0.11769993603229523], all client accs: [0.5980629324913025, 0.5865628719329834],  alpha_performance: tensor([0.7000, 0.3000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:22,675 - utils - INFO - stage1_gradient_single_runtime: 0.002103090286254883
2023-09-28 23:25:22,675 - utils - INFO -  epoch: 448, all client loss: [0.6370849609375, 0.6616882085800171], all pred client disparities: [0.029537342488765717, 0.11181412637233734], all client disparities: [0.011666666716337204, 0.11769993603229523], all client accs: [0.5980629324913025, 0.5863817930221558],  alpha_performance: tensor([0.6998, 0.3002], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:22,726 - utils - INFO - stage1_gradient_single_runtime: 0.0023102760314941406
2023-09-28 23:25:22,727 - utils - INFO -  epoch: 449, all client loss: [0.6371226906776428, 0.661650538444519], all pred client disparities: [0.029452210292220116, 0.11182656139135361], all client disparities: [0.011666666716337204, 0.11821512877941132], all client accs: [0.5980629324913025, 0.586743950843811],  alpha_performance: tensor([0.6995, 0.3005], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:22,780 - utils - INFO - stage1_gradient_single_runtime: 0.0021865367889404297
2023-09-28 23:25:22,781 - utils - INFO -  epoch: 450, all client loss: [0.6371603012084961, 0.6616130471229553], all pred client disparities: [0.029367830604314804, 0.11183890700340271], all client disparities: [0.010833333246409893, 0.11855652928352356], all client accs: [0.5976594090461731, 0.5874683260917664],  alpha_performance: tensor([0.6992, 0.3008], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:22,831 - utils - INFO - stage1_gradient_single_runtime: 0.0022110939025878906
2023-09-28 23:25:22,832 - utils - INFO -  epoch: 451, all client loss: [0.6371978521347046, 0.6615755558013916], all pred client disparities: [0.0292841624468565, 0.11185116320848465], all client disparities: [0.010833333246409893, 0.11838271468877792], all client accs: [0.5976594090461731, 0.5878305435180664],  alpha_performance: tensor([0.6989, 0.3011], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:22,889 - utils - INFO - stage1_gradient_single_runtime: 0.0024557113647460938
2023-09-28 23:25:22,890 - utils - INFO -  epoch: 452, all client loss: [0.6372352838516235, 0.6615382432937622], all pred client disparities: [0.029201215133070946, 0.11186328530311584], all client disparities: [0.010833333246409893, 0.11864031106233597], all client accs: [0.5976594090461731, 0.5878305435180664],  alpha_performance: tensor([0.6987, 0.3013], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:22,938 - utils - INFO - stage1_gradient_single_runtime: 0.00226593017578125
2023-09-28 23:25:22,939 - utils - INFO -  epoch: 453, all client loss: [0.6372726559638977, 0.6615009903907776], all pred client disparities: [0.029118970036506653, 0.11187529563903809], all client disparities: [0.010833333246409893, 0.11846650391817093], all client accs: [0.5976594090461731, 0.5881927013397217],  alpha_performance: tensor([0.6984, 0.3016], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:23,036 - utils - INFO - stage1_gradient_single_runtime: 0.002241373062133789
2023-09-28 23:25:23,036 - utils - INFO -  epoch: 454, all client loss: [0.6373098492622375, 0.6614638566970825], all pred client disparities: [0.029037417843937874, 0.11188722401857376], all client disparities: [0.010833333246409893, 0.11872410029172897], all client accs: [0.5976594090461731, 0.5883737802505493],  alpha_performance: tensor([0.6981, 0.3019], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:23,087 - utils - INFO - stage1_gradient_single_runtime: 0.0021827220916748047
2023-09-28 23:25:23,088 - utils - INFO -  epoch: 455, all client loss: [0.6373470425605774, 0.6614267826080322], all pred client disparities: [0.02895655855536461, 0.1118989959359169], all client disparities: [0.010833333246409893, 0.11923930794000626], all client accs: [0.5976594090461731, 0.5887359976768494],  alpha_performance: tensor([0.6978, 0.3022], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:23,142 - utils - INFO - stage1_gradient_single_runtime: 0.0022563934326171875
2023-09-28 23:25:23,143 - utils - INFO -  epoch: 456, all client loss: [0.6373841166496277, 0.6613898277282715], all pred client disparities: [0.028876379132270813, 0.11191070079803467], all client disparities: [0.010833333246409893, 0.11906550079584122], all client accs: [0.5976594090461731, 0.5890981554985046],  alpha_performance: tensor([0.6976, 0.3024], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:23,194 - utils - INFO - stage1_gradient_single_runtime: 0.0022308826446533203
2023-09-28 23:25:23,196 - utils - INFO -  epoch: 457, all client loss: [0.6374210715293884, 0.6613529920578003], all pred client disparities: [0.028796857222914696, 0.1119222491979599], all client disparities: [0.010833333246409893, 0.11871787905693054], all client accs: [0.5976594090461731, 0.5896414518356323],  alpha_performance: tensor([0.6973, 0.3027], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:23,245 - utils - INFO - stage1_gradient_single_runtime: 0.0022580623626708984
2023-09-28 23:25:23,246 - utils - INFO -  epoch: 458, all client loss: [0.6374579071998596, 0.6613162159919739], all pred client disparities: [0.028718000277876854, 0.11193372309207916], all client disparities: [0.010833333246409893, 0.11828646808862686], all client accs: [0.5976594090461731, 0.5896414518356323],  alpha_performance: tensor([0.6971, 0.3029], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:23,299 - utils - INFO - stage1_gradient_single_runtime: 0.0022034645080566406
2023-09-28 23:25:23,301 - utils - INFO -  epoch: 459, all client loss: [0.6374946236610413, 0.6612794995307922], all pred client disparities: [0.028639785945415497, 0.11194505542516708], all client disparities: [0.010833333246409893, 0.11828646808862686], all client accs: [0.5976594090461731, 0.5894603729248047],  alpha_performance: tensor([0.6968, 0.3032], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:23,319 - utils - INFO - valid: True, epoch: 459, loss: [0.6317179799079895, 0.6667898297309875], accuracy: [0.6159999966621399, 0.5723636150360107], mean_accuracy:0.5941818058490753,variance_accuracy:0.021818190813064575, disparity: [0.010638297535479069, 0.13917045295238495], mean_disparity:0.07490437524393201,variance_disparity:0.06426607770845294, pred_disparity: [0.026925452053546906, 0.12806253135204315]
2023-09-28 23:25:23,333 - utils - INFO - global_valid: True, epoch: 459,  global_loss: 0.6558299660682678, global_accuracy: 0.7402390956382553,  global_disparity:0.11177992075681686, global_pred_disparity: 0.1073155626654625,
2023-09-28 23:25:23,381 - utils - INFO - stage1_gradient_single_runtime: 0.002195596694946289
2023-09-28 23:25:23,382 - utils - INFO -  epoch: 460, all client loss: [0.6375313401222229, 0.6612429022789001], all pred client disparities: [0.028562212362885475, 0.11195627599954605], all client disparities: [0.010833333246409893, 0.11828646808862686], all client accs: [0.5976594090461731, 0.5894603729248047],  alpha_performance: tensor([0.6965, 0.3035], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:23,435 - utils - INFO - stage1_gradient_single_runtime: 0.0025167465209960938
2023-09-28 23:25:23,436 - utils - INFO -  epoch: 461, all client loss: [0.6375678777694702, 0.6612064242362976], all pred client disparities: [0.028485268354415894, 0.11196738481521606], all client disparities: [0.010833333246409893, 0.11828646808862686], all client accs: [0.5980629324913025, 0.5894603729248047],  alpha_performance: tensor([0.6963, 0.3037], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:23,487 - utils - INFO - stage1_gradient_single_runtime: 0.002232789993286133
2023-09-28 23:25:23,488 - utils - INFO -  epoch: 462, all client loss: [0.6376044154167175, 0.6611700654029846], all pred client disparities: [0.028408942744135857, 0.11197837442159653], all client disparities: [0.010833333246409893, 0.1185440644621849], all client accs: [0.5980629324913025, 0.5896414518356323],  alpha_performance: tensor([0.6960, 0.3040], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:23,540 - utils - INFO - stage1_gradient_single_runtime: 0.0026047229766845703
2023-09-28 23:25:23,541 - utils - INFO -  epoch: 463, all client loss: [0.6376408338546753, 0.6611337065696716], all pred client disparities: [0.02833322435617447, 0.11198924481868744], all client disparities: [0.010833333246409893, 0.11880167573690414], all client accs: [0.5980629324913025, 0.5896414518356323],  alpha_performance: tensor([0.6958, 0.3042], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:23,595 - utils - INFO - stage1_gradient_single_runtime: 0.002185821533203125
2023-09-28 23:25:23,595 - utils - INFO -  epoch: 464, all client loss: [0.6376771330833435, 0.661097526550293], all pred client disparities: [0.028258126229047775, 0.1119999811053276], all client disparities: [0.010833333246409893, 0.11957446485757828], all client accs: [0.5980629324913025, 0.59018474817276],  alpha_performance: tensor([0.6955, 0.3045], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:23,647 - utils - INFO - stage1_gradient_single_runtime: 0.0023317337036132812
2023-09-28 23:25:23,648 - utils - INFO -  epoch: 465, all client loss: [0.6377133131027222, 0.6610614061355591], all pred client disparities: [0.02818361297249794, 0.11201063543558121], all client disparities: [0.010833333246409893, 0.11940065771341324], all client accs: [0.5980629324913025, 0.5903658270835876],  alpha_performance: tensor([0.6952, 0.3048], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:23,698 - utils - INFO - stage1_gradient_single_runtime: 0.0022411346435546875
2023-09-28 23:25:23,699 - utils - INFO -  epoch: 466, all client loss: [0.637749433517456, 0.6610252857208252], all pred client disparities: [0.02810969389975071, 0.11202115565538406], all client disparities: [0.010833333246409893, 0.11948446184396744], all client accs: [0.5980629324913025, 0.591090202331543],  alpha_performance: tensor([0.6950, 0.3050], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:23,751 - utils - INFO - stage1_gradient_single_runtime: 0.0022869110107421875
2023-09-28 23:25:23,752 - utils - INFO -  epoch: 467, all client loss: [0.6377854347229004, 0.6609894037246704], all pred client disparities: [0.028036344796419144, 0.11203154921531677], all client disparities: [0.010833333246409893, 0.11982583999633789], all client accs: [0.5980629324913025, 0.5918145775794983],  alpha_performance: tensor([0.6947, 0.3053], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:23,881 - utils - INFO - stage1_gradient_single_runtime: 0.003512144088745117
2023-09-28 23:25:23,882 - utils - INFO -  epoch: 468, all client loss: [0.6378213763237, 0.6609535217285156], all pred client disparities: [0.027963576838374138, 0.11204183101654053], all client disparities: [0.010833333246409893, 0.11939443647861481], all client accs: [0.5980629324913025, 0.5919956564903259],  alpha_performance: tensor([0.6945, 0.3055], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:23,972 - utils - INFO - stage1_gradient_single_runtime: 0.003535032272338867
2023-09-28 23:25:23,974 - utils - INFO -  epoch: 469, all client loss: [0.6378572583198547, 0.6609177589416504], all pred client disparities: [0.02789136953651905, 0.11205197125673294], all client disparities: [0.010833333246409893, 0.12025102227926254], all client accs: [0.5984665155410767, 0.5927200317382812],  alpha_performance: tensor([0.6942, 0.3058], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:24,057 - utils - INFO - stage1_gradient_single_runtime: 0.002291440963745117
2023-09-28 23:25:24,058 - utils - INFO -  epoch: 470, all client loss: [0.6378929615020752, 0.6608821153640747], all pred client disparities: [0.027819711714982986, 0.1120620146393776], all client disparities: [0.010833333246409893, 0.12025102227926254], all client accs: [0.5984665155410767, 0.5925389528274536],  alpha_performance: tensor([0.6940, 0.3060], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:24,111 - utils - INFO - stage1_gradient_single_runtime: 0.0024755001068115234
2023-09-28 23:25:24,112 - utils - INFO -  epoch: 471, all client loss: [0.6379287242889404, 0.6608465313911438], all pred client disparities: [0.027748610824346542, 0.1120719313621521], all client disparities: [0.010833333246409893, 0.11981961876153946], all client accs: [0.5984665155410767, 0.5925389528274536],  alpha_performance: tensor([0.6937, 0.3063], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:24,164 - utils - INFO - stage1_gradient_single_runtime: 0.002239227294921875
2023-09-28 23:25:24,165 - utils - INFO -  epoch: 472, all client loss: [0.6379642486572266, 0.6608110666275024], all pred client disparities: [0.027678044512867928, 0.11208170652389526], all client disparities: [0.010833333246409893, 0.11938821524381638], all client accs: [0.5984665155410767, 0.592357873916626],  alpha_performance: tensor([0.6935, 0.3065], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:24,217 - utils - INFO - stage1_gradient_single_runtime: 0.002279043197631836
2023-09-28 23:25:24,218 - utils - INFO -  epoch: 473, all client loss: [0.6379997134208679, 0.6607756614685059], all pred client disparities: [0.02760801464319229, 0.11209138482809067], all client disparities: [0.010833333246409893, 0.11938821524381638], all client accs: [0.5984665155410767, 0.592357873916626],  alpha_performance: tensor([0.6932, 0.3068], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:24,267 - utils - INFO - stage1_gradient_single_runtime: 0.002247333526611328
2023-09-28 23:25:24,268 - utils - INFO -  epoch: 474, all client loss: [0.6380351781845093, 0.660740315914154], all pred client disparities: [0.027538510039448738, 0.11210092902183533], all client disparities: [0.010833333246409893, 0.11938821524381638], all client accs: [0.5984665155410767, 0.592357873916626],  alpha_performance: tensor([0.6930, 0.3070], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:24,319 - utils - INFO - stage1_gradient_single_runtime: 0.0022292137145996094
2023-09-28 23:25:24,321 - utils - INFO -  epoch: 475, all client loss: [0.6380704641342163, 0.6607050895690918], all pred client disparities: [0.02746952883899212, 0.11211036145687103], all client disparities: [0.010833333246409893, 0.11852540075778961], all client accs: [0.5984665155410767, 0.5927200317382812],  alpha_performance: tensor([0.6928, 0.3072], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:24,373 - utils - INFO - stage1_gradient_single_runtime: 0.0024793148040771484
2023-09-28 23:25:24,375 - utils - INFO -  epoch: 476, all client loss: [0.6381056904792786, 0.6606699228286743], all pred client disparities: [0.02740105800330639, 0.1121196523308754], all client disparities: [0.010833333246409893, 0.11878299713134766], all client accs: [0.5984665155410767, 0.5929011106491089],  alpha_performance: tensor([0.6925, 0.3075], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:24,428 - utils - INFO - stage1_gradient_single_runtime: 0.002265453338623047
2023-09-28 23:25:24,429 - utils - INFO -  epoch: 477, all client loss: [0.6381407976150513, 0.6606348156929016], all pred client disparities: [0.027333099395036697, 0.11212880164384842], all client disparities: [0.010833333246409893, 0.1190406084060669], all client accs: [0.5984665155410767, 0.5925389528274536],  alpha_performance: tensor([0.6923, 0.3077], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:24,483 - utils - INFO - stage1_gradient_single_runtime: 0.002229928970336914
2023-09-28 23:25:24,483 - utils - INFO -  epoch: 478, all client loss: [0.638175904750824, 0.6605998873710632], all pred client disparities: [0.027265634387731552, 0.11213784664869308], all client disparities: [0.010833333246409893, 0.11929820477962494], all client accs: [0.5984665155410767, 0.5925389528274536],  alpha_performance: tensor([0.6920, 0.3080], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:24,535 - utils - INFO - stage1_gradient_single_runtime: 0.0026597976684570312
2023-09-28 23:25:24,536 - utils - INFO -  epoch: 479, all client loss: [0.6382108926773071, 0.6605649590492249], all pred client disparities: [0.0271986722946167, 0.1121467873454094], all client disparities: [0.010833333246409893, 0.11929820477962494], all client accs: [0.5984665155410767, 0.5925389528274536],  alpha_performance: tensor([0.6918, 0.3082], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:24,554 - utils - INFO - valid: True, epoch: 479, loss: [0.6323531270027161, 0.666090726852417], accuracy: [0.6159999966621399, 0.5745454430580139], mean_accuracy:0.5952727198600769,variance_accuracy:0.02072727680206299, disparity: [0.010638297535479069, 0.13630880415439606], mean_disparity:0.07347355084493756,variance_disparity:0.0628352533094585, pred_disparity: [0.025558460503816605, 0.1276242733001709]
2023-09-28 23:25:24,567 - utils - INFO - global_valid: True, epoch: 479,  global_loss: 0.6555477976799011, global_accuracy: 0.7376820728291316,  global_disparity:0.10969042778015137, global_pred_disparity: 0.10678160190582275,
2023-09-28 23:25:24,668 - utils - INFO - stage1_gradient_single_runtime: 0.0022199153900146484
2023-09-28 23:25:24,669 - utils - INFO -  epoch: 480, all client loss: [0.6382457613945007, 0.660530149936676], all pred client disparities: [0.0271321851760149, 0.11215555667877197], all client disparities: [0.010833333246409893, 0.11869298666715622], all client accs: [0.5984665155410767, 0.5930822491645813],  alpha_performance: tensor([0.6916, 0.3084], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:24,722 - utils - INFO - stage1_gradient_single_runtime: 0.0022292137145996094
2023-09-28 23:25:24,724 - utils - INFO -  epoch: 481, all client loss: [0.6382805109024048, 0.6604954600334167], all pred client disparities: [0.02706618793308735, 0.112164206802845], all client disparities: [0.009999999776482582, 0.11895058304071426], all client accs: [0.5980629324913025, 0.5929011106491089],  alpha_performance: tensor([0.6913, 0.3087], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:24,783 - utils - INFO - stage1_gradient_single_runtime: 0.0025339126586914062
2023-09-28 23:25:24,785 - utils - INFO -  epoch: 482, all client loss: [0.6383152008056641, 0.6604608297348022], all pred client disparities: [0.027000667527318, 0.11217278242111206], all client disparities: [0.009999999776482582, 0.11920817941427231], all client accs: [0.5980629324913025, 0.5929011106491089],  alpha_performance: tensor([0.6911, 0.3089], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:24,838 - utils - INFO - stage1_gradient_single_runtime: 0.002201080322265625
2023-09-28 23:25:24,839 - utils - INFO -  epoch: 483, all client loss: [0.6383498907089233, 0.6604262590408325], all pred client disparities: [0.026935607194900513, 0.11218120157718658], all client disparities: [0.009999999776482582, 0.11860297620296478], all client accs: [0.5980629324913025, 0.5934444069862366],  alpha_performance: tensor([0.6909, 0.3091], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:24,892 - utils - INFO - stage1_gradient_single_runtime: 0.0022439956665039062
2023-09-28 23:25:24,893 - utils - INFO -  epoch: 484, all client loss: [0.6383844017982483, 0.6603918075561523], all pred client disparities: [0.026871005073189735, 0.11218945682048798], all client disparities: [0.009999999776482582, 0.1182553619146347], all client accs: [0.5980629324913025, 0.5941687822341919],  alpha_performance: tensor([0.6906, 0.3094], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:24,944 - utils - INFO - stage1_gradient_single_runtime: 0.002190828323364258
2023-09-28 23:25:24,945 - utils - INFO -  epoch: 485, all client loss: [0.6384189128875732, 0.6603574156761169], all pred client disparities: [0.026806864887475967, 0.11219759285449982], all client disparities: [0.009999999776482582, 0.1182553619146347], all client accs: [0.5980629324913025, 0.5941687822341919],  alpha_performance: tensor([0.6904, 0.3096], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:25,002 - utils - INFO - stage1_gradient_single_runtime: 0.0038590431213378906
2023-09-28 23:25:25,004 - utils - INFO -  epoch: 486, all client loss: [0.6384532451629639, 0.6603231430053711], all pred client disparities: [0.026743177324533463, 0.1122056171298027], all client disparities: [0.009999999776482582, 0.11782395094633102], all client accs: [0.5980629324913025, 0.5943498611450195],  alpha_performance: tensor([0.6902, 0.3098], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:25,055 - utils - INFO - stage1_gradient_single_runtime: 0.0021245479583740234
2023-09-28 23:25:25,056 - utils - INFO -  epoch: 487, all client loss: [0.6384875178337097, 0.6602888703346252], all pred client disparities: [0.026679931208491325, 0.11221352964639664], all client disparities: [0.009166666306555271, 0.11739254742860794], all client accs: [0.5976594090461731, 0.5943498611450195],  alpha_performance: tensor([0.6899, 0.3101], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:25,110 - utils - INFO - stage1_gradient_single_runtime: 0.002586841583251953
2023-09-28 23:25:25,111 - utils - INFO -  epoch: 488, all client loss: [0.6385217308998108, 0.6602546572685242], all pred client disparities: [0.02661711908876896, 0.11222125589847565], all client disparities: [0.009166666306555271, 0.11747632920742035], all client accs: [0.5976594090461731, 0.5947120785713196],  alpha_performance: tensor([0.6897, 0.3103], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:25,160 - utils - INFO - stage1_gradient_single_runtime: 0.002180337905883789
2023-09-28 23:25:25,161 - utils - INFO -  epoch: 489, all client loss: [0.6385558843612671, 0.6602206826210022], all pred client disparities: [0.02655474655330181, 0.1122288629412651], all client disparities: [0.009166666306555271, 0.11799153685569763], all client accs: [0.5976594090461731, 0.5948931574821472],  alpha_performance: tensor([0.6895, 0.3105], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:25,212 - utils - INFO - stage1_gradient_single_runtime: 0.002227783203125
2023-09-28 23:25:25,213 - utils - INFO -  epoch: 490, all client loss: [0.6385899186134338, 0.6601867079734802], all pred client disparities: [0.026492802426218987, 0.1122363954782486], all client disparities: [0.009166666306555271, 0.11781772971153259], all client accs: [0.5976594090461731, 0.5948931574821472],  alpha_performance: tensor([0.6892, 0.3108], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:25,272 - utils - INFO - stage1_gradient_single_runtime: 0.0021855831146240234
2023-09-28 23:25:25,273 - utils - INFO -  epoch: 491, all client loss: [0.6386238932609558, 0.660152792930603], all pred client disparities: [0.026431282982230186, 0.11224376410245895], all client disparities: [0.009166666306555271, 0.11884813010692596], all client accs: [0.5976594090461731, 0.5956175327301025],  alpha_performance: tensor([0.6890, 0.3110], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:25,324 - utils - INFO - stage1_gradient_single_runtime: 0.002278566360473633
2023-09-28 23:25:25,325 - utils - INFO -  epoch: 492, all client loss: [0.638657808303833, 0.6601189374923706], all pred client disparities: [0.026370180770754814, 0.11225100606679916], all client disparities: [0.009166666306555271, 0.11867432296276093], all client accs: [0.5976594090461731, 0.5959797501564026],  alpha_performance: tensor([0.6888, 0.3112], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:25,442 - utils - INFO - stage1_gradient_single_runtime: 0.0021944046020507812
2023-09-28 23:25:25,445 - utils - INFO -  epoch: 493, all client loss: [0.6386916637420654, 0.6600852012634277], all pred client disparities: [0.026309490203857422, 0.11225807666778564], all client disparities: [0.009166666306555271, 0.11789529770612717], all client accs: [0.5976594090461731, 0.5968852043151855],  alpha_performance: tensor([0.6886, 0.3114], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:25,499 - utils - INFO - stage1_gradient_single_runtime: 0.002560853958129883
2023-09-28 23:25:25,501 - utils - INFO -  epoch: 494, all client loss: [0.6387253403663635, 0.6600515842437744], all pred client disparities: [0.026249215006828308, 0.11226507276296616], all client disparities: [0.009166666306555271, 0.11789529770612717], all client accs: [0.5976594090461731, 0.5968852043151855],  alpha_performance: tensor([0.6883, 0.3117], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:25,551 - utils - INFO - stage1_gradient_single_runtime: 0.0022521018981933594
2023-09-28 23:25:25,552 - utils - INFO -  epoch: 495, all client loss: [0.6387590765953064, 0.6600179672241211], all pred client disparities: [0.026189332827925682, 0.11227191239595413], all client disparities: [0.009166666306555271, 0.11746388673782349], all client accs: [0.5976594090461731, 0.5968852043151855],  alpha_performance: tensor([0.6881, 0.3119], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:25,603 - utils - INFO - stage1_gradient_single_runtime: 0.002276182174682617
2023-09-28 23:25:25,604 - utils - INFO -  epoch: 496, all client loss: [0.6387925744056702, 0.6599844694137573], all pred client disparities: [0.02612985298037529, 0.11227861791849136], all client disparities: [0.009166666306555271, 0.11746388673782349], all client accs: [0.5976594090461731, 0.5967041254043579],  alpha_performance: tensor([0.6879, 0.3121], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:25,657 - utils - INFO - stage1_gradient_single_runtime: 0.0022704601287841797
2023-09-28 23:25:25,658 - utils - INFO -  epoch: 497, all client loss: [0.6388260722160339, 0.6599510312080383], all pred client disparities: [0.026070769876241684, 0.11228518933057785], all client disparities: [0.009166666306555271, 0.11729007959365845], all client accs: [0.5976594090461731, 0.5968852043151855],  alpha_performance: tensor([0.6877, 0.3123], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:25,713 - utils - INFO - stage1_gradient_single_runtime: 0.0023012161254882812
2023-09-28 23:25:25,715 - utils - INFO -  epoch: 498, all client loss: [0.6388595700263977, 0.6599176526069641], all pred client disparities: [0.026012064889073372, 0.112291619181633], all client disparities: [0.009166666306555271, 0.11651106923818588], all client accs: [0.5976594090461731, 0.5977906584739685],  alpha_performance: tensor([0.6875, 0.3125], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:25,766 - utils - INFO - stage1_gradient_single_runtime: 0.0022735595703125
2023-09-28 23:25:25,767 - utils - INFO -  epoch: 499, all client loss: [0.6388928294181824, 0.6598843932151794], all pred client disparities: [0.0259537510573864, 0.112297922372818], all client disparities: [0.009166666306555271, 0.11633725464344025], all client accs: [0.5976594090461731, 0.5979717969894409],  alpha_performance: tensor([0.6873, 0.3127], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:25,786 - utils - INFO - valid: True, epoch: 499, loss: [0.6329658031463623, 0.6654177904129028], accuracy: [0.6159999966621399, 0.5759999752044678], mean_accuracy:0.5959999859333038,variance_accuracy:0.02000001072883606, disparity: [0.010638297535479069, 0.13555246591567993], mean_disparity:0.0730953817255795,variance_disparity:0.06245708419010043, pred_disparity: [0.02438630722463131, 0.12710349261760712]
2023-09-28 23:25:25,798 - utils - INFO - global_valid: True, epoch: 499,  global_loss: 0.6552766561508179, global_accuracy: 0.7351490596238495,  global_disparity:0.10922431200742722, global_pred_disparity: 0.10622697323560715,
2023-09-28 23:25:25,843 - utils - INFO - stage1_gradient_single_runtime: 0.0022211074829101562
2023-09-28 23:25:25,844 - utils - INFO -  epoch: 500, all client loss: [0.6389261484146118, 0.6598511338233948], all pred client disparities: [0.02589580975472927, 0.11230409890413284], all client disparities: [0.009166666306555271, 0.11633725464344025], all client accs: [0.5976594090461731, 0.5979717969894409],  alpha_performance: tensor([0.6870, 0.3130], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:25,895 - utils - INFO - stage1_gradient_single_runtime: 0.0022182464599609375
2023-09-28 23:25:25,895 - utils - INFO -  epoch: 501, all client loss: [0.6389592885971069, 0.6598180532455444], all pred client disparities: [0.025838248431682587, 0.11231011152267456], all client disparities: [0.009166666306555271, 0.11685244739055634], all client accs: [0.5976594090461731, 0.5979717969894409],  alpha_performance: tensor([0.6868, 0.3132], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:25,948 - utils - INFO - stage1_gradient_single_runtime: 0.0021886825561523438
2023-09-28 23:25:25,949 - utils - INFO -  epoch: 502, all client loss: [0.638992428779602, 0.6597849726676941], all pred client disparities: [0.025781046599149704, 0.11231602728366852], all client disparities: [0.009166666306555271, 0.11685244739055634], all client accs: [0.5976594090461731, 0.5977906584739685],  alpha_performance: tensor([0.6866, 0.3134], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:26,000 - utils - INFO - stage1_gradient_single_runtime: 0.002255678176879883
2023-09-28 23:25:26,002 - utils - INFO -  epoch: 503, all client loss: [0.6390254497528076, 0.6597520112991333], all pred client disparities: [0.02572421170771122, 0.11232175678014755], all client disparities: [0.009166666306555271, 0.1166786402463913], all client accs: [0.5976594090461731, 0.5979717969894409],  alpha_performance: tensor([0.6864, 0.3136], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:26,054 - utils - INFO - stage1_gradient_single_runtime: 0.0025234222412109375
2023-09-28 23:25:26,056 - utils - INFO -  epoch: 504, all client loss: [0.6390584707260132, 0.6597191095352173], all pred client disparities: [0.02566773258149624, 0.11232737451791763], all client disparities: [0.009166666306555271, 0.1166786402463913], all client accs: [0.5976594090461731, 0.5977906584739685],  alpha_performance: tensor([0.6862, 0.3138], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:26,111 - utils - INFO - stage1_gradient_single_runtime: 0.0025289058685302734
2023-09-28 23:25:26,112 - utils - INFO -  epoch: 505, all client loss: [0.6390913724899292, 0.659686267375946], all pred client disparities: [0.02561161480844021, 0.11233283579349518], all client disparities: [0.009166666306555271, 0.1166786402463913], all client accs: [0.5976594090461731, 0.5976095795631409],  alpha_performance: tensor([0.6860, 0.3140], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:26,218 - utils - INFO - stage1_gradient_single_runtime: 0.0022766590118408203
2023-09-28 23:25:26,219 - utils - INFO -  epoch: 506, all client loss: [0.6391241550445557, 0.6596534848213196], all pred client disparities: [0.02555585280060768, 0.11233820766210556], all client disparities: [0.009166666306555271, 0.11770904064178467], all client accs: [0.5976594090461731, 0.5979717969894409],  alpha_performance: tensor([0.6858, 0.3142], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:26,270 - utils - INFO - stage1_gradient_single_runtime: 0.0022459030151367188
2023-09-28 23:25:26,271 - utils - INFO -  epoch: 507, all client loss: [0.6391568779945374, 0.6596208214759827], all pred client disparities: [0.025500433519482613, 0.11234337091445923], all client disparities: [0.009166666306555271, 0.11727762967348099], all client accs: [0.5976594090461731, 0.5981528759002686],  alpha_performance: tensor([0.6856, 0.3144], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:26,321 - utils - INFO - stage1_gradient_single_runtime: 0.0022649765014648438
2023-09-28 23:25:26,323 - utils - INFO -  epoch: 508, all client loss: [0.639189600944519, 0.6595881581306458], all pred client disparities: [0.02544536255300045, 0.11234844475984573], all client disparities: [0.009166666306555271, 0.11753522604703903], all client accs: [0.5976594090461731, 0.5983339548110962],  alpha_performance: tensor([0.6854, 0.3146], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:26,381 - utils - INFO - stage1_gradient_single_runtime: 0.002490520477294922
2023-09-28 23:25:26,382 - utils - INFO -  epoch: 509, all client loss: [0.6392222046852112, 0.6595556735992432], all pred client disparities: [0.025390634313225746, 0.1123533844947815], all client disparities: [0.009166666306555271, 0.11736143380403519], all client accs: [0.5976594090461731, 0.5986961126327515],  alpha_performance: tensor([0.6851, 0.3149], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:26,432 - utils - INFO - stage1_gradient_single_runtime: 0.002156972885131836
2023-09-28 23:25:26,432 - utils - INFO -  epoch: 510, all client loss: [0.6392547488212585, 0.6595231294631958], all pred client disparities: [0.025336239486932755, 0.11235816776752472], all client disparities: [0.009166666306555271, 0.11736143380403519], all client accs: [0.5976594090461731, 0.5986961126327515],  alpha_performance: tensor([0.6849, 0.3151], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:26,483 - utils - INFO - stage1_gradient_single_runtime: 0.002251863479614258
2023-09-28 23:25:26,484 - utils - INFO -  epoch: 511, all client loss: [0.6392871737480164, 0.6594907641410828], all pred client disparities: [0.025282172486186028, 0.1123628094792366], all client disparities: [0.009166666306555271, 0.11675621569156647], all client accs: [0.5976594090461731, 0.5985150337219238],  alpha_performance: tensor([0.6847, 0.3153], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:26,534 - utils - INFO - stage1_gradient_single_runtime: 0.0021882057189941406
2023-09-28 23:25:26,535 - utils - INFO -  epoch: 512, all client loss: [0.6393195986747742, 0.6594583988189697], all pred client disparities: [0.025228438898921013, 0.11236730962991714], all client disparities: [0.009166666306555271, 0.11701381206512451], all client accs: [0.5976594090461731, 0.5986961126327515],  alpha_performance: tensor([0.6845, 0.3155], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:26,589 - utils - INFO - stage1_gradient_single_runtime: 0.002304553985595703
2023-09-28 23:25:26,590 - utils - INFO -  epoch: 513, all client loss: [0.6393519043922424, 0.6594261527061462], all pred client disparities: [0.025175029411911964, 0.11237166821956635], all client disparities: [0.009166666306555271, 0.11701381206512451], all client accs: [0.5976594090461731, 0.5983339548110962],  alpha_performance: tensor([0.6843, 0.3157], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:26,643 - utils - INFO - stage1_gradient_single_runtime: 0.0025246143341064453
2023-09-28 23:25:26,645 - utils - INFO -  epoch: 514, all client loss: [0.6393841505050659, 0.6593939661979675], all pred client disparities: [0.025121942162513733, 0.112375907599926], all client disparities: [0.009166666306555271, 0.11649239808320999], all client accs: [0.5976594090461731, 0.5994205474853516],  alpha_performance: tensor([0.6841, 0.3159], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:26,695 - utils - INFO - stage1_gradient_single_runtime: 0.0022614002227783203
2023-09-28 23:25:26,696 - utils - INFO -  epoch: 515, all client loss: [0.6394163370132446, 0.6593618392944336], all pred client disparities: [0.02506916970014572, 0.1123799979686737], all client disparities: [0.009166666306555271, 0.11649239808320999], all client accs: [0.5976594090461731, 0.5992394089698792],  alpha_performance: tensor([0.6839, 0.3161], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:26,750 - utils - INFO - stage1_gradient_single_runtime: 0.002412557601928711
2023-09-28 23:25:26,751 - utils - INFO -  epoch: 516, all client loss: [0.6394484043121338, 0.6593298316001892], all pred client disparities: [0.025016706436872482, 0.11238392442464828], all client disparities: [0.009166666306555271, 0.116576187312603], all client accs: [0.5976594090461731, 0.5997827053070068],  alpha_performance: tensor([0.6837, 0.3163], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:26,801 - utils - INFO - stage1_gradient_single_runtime: 0.002237081527709961
2023-09-28 23:25:26,802 - utils - INFO -  epoch: 517, all client loss: [0.6394805312156677, 0.6592978239059448], all pred client disparities: [0.024964552372694016, 0.11238771677017212], all client disparities: [0.009166666306555271, 0.11614477634429932], all client accs: [0.5976594090461731, 0.5997827053070068],  alpha_performance: tensor([0.6835, 0.3165], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:26,905 - utils - INFO - stage1_gradient_single_runtime: 0.00260162353515625
2023-09-28 23:25:26,906 - utils - INFO -  epoch: 518, all client loss: [0.6395124793052673, 0.6592658162117004], all pred client disparities: [0.024912703782320023, 0.11239135265350342], all client disparities: [0.009166666306555271, 0.11691756546497345], all client accs: [0.5976594090461731, 0.6001448631286621],  alpha_performance: tensor([0.6833, 0.3167], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:26,955 - utils - INFO - stage1_gradient_single_runtime: 0.002233266830444336
2023-09-28 23:25:26,956 - utils - INFO -  epoch: 519, all client loss: [0.6395444273948669, 0.6592339873313904], all pred client disparities: [0.024861156940460205, 0.11239483952522278], all client disparities: [0.009166666306555271, 0.11648616194725037], all client accs: [0.5976594090461731, 0.6003260016441345],  alpha_performance: tensor([0.6831, 0.3169], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:26,975 - utils - INFO - valid: True, epoch: 519, loss: [0.633557915687561, 0.6647679805755615], accuracy: [0.6159999966621399, 0.581818163394928], mean_accuracy:0.5989090800285339,variance_accuracy:0.017090916633605957, disparity: [0.010638297535479069, 0.12877658009529114], mean_disparity:0.0697074388153851,variance_disparity:0.059069141279906034, pred_disparity: [0.0233641117811203, 0.12650786340236664]
2023-09-28 23:25:26,986 - utils - INFO - global_valid: True, epoch: 519,  global_loss: 0.6550148725509644, global_accuracy: 0.7327896158463386,  global_disparity:0.10423364490270615, global_pred_disparity: 0.10564810037612915,
2023-09-28 23:25:27,039 - utils - INFO - stage1_gradient_single_runtime: 0.0029821395874023438
2023-09-28 23:25:27,040 - utils - INFO -  epoch: 520, all client loss: [0.6395763158798218, 0.6592021584510803], all pred client disparities: [0.024809908121824265, 0.1123981922864914], all client disparities: [0.009166666306555271, 0.1156233474612236], all client accs: [0.5976594090461731, 0.6006881594657898],  alpha_performance: tensor([0.6829, 0.3171], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:27,095 - utils - INFO - stage1_gradient_single_runtime: 0.002459287643432617
2023-09-28 23:25:27,096 - utils - INFO -  epoch: 521, all client loss: [0.6396080255508423, 0.6591705083847046], all pred client disparities: [0.0247589573264122, 0.11240142583847046], all client disparities: [0.009166666306555271, 0.11536575108766556], all client accs: [0.5976594090461731, 0.6005070805549622],  alpha_performance: tensor([0.6827, 0.3173], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:27,147 - utils - INFO - stage1_gradient_single_runtime: 0.0022978782653808594
2023-09-28 23:25:27,148 - utils - INFO -  epoch: 522, all client loss: [0.6396397352218628, 0.6591388583183289], all pred client disparities: [0.024708300828933716, 0.1124044805765152], all client disparities: [0.009166666306555271, 0.11501814424991608], all client accs: [0.5976594090461731, 0.6010503768920898],  alpha_performance: tensor([0.6825, 0.3175], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:27,201 - utils - INFO - stage1_gradient_single_runtime: 0.0025610923767089844
2023-09-28 23:25:27,202 - utils - INFO -  epoch: 523, all client loss: [0.6396713852882385, 0.6591072082519531], all pred client disparities: [0.024657927453517914, 0.11240740120410919], all client disparities: [0.009166666306555271, 0.11553333699703217], all client accs: [0.5976594090461731, 0.6014125347137451],  alpha_performance: tensor([0.6824, 0.3176], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:27,252 - utils - INFO - stage1_gradient_single_runtime: 0.002219676971435547
2023-09-28 23:25:27,253 - utils - INFO -  epoch: 524, all client loss: [0.6397029757499695, 0.6590757369995117], all pred client disparities: [0.024607844650745392, 0.11241015791893005], all client disparities: [0.009166666306555271, 0.11510193347930908], all client accs: [0.5976594090461731, 0.6015936136245728],  alpha_performance: tensor([0.6822, 0.3178], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:27,307 - utils - INFO - stage1_gradient_single_runtime: 0.002177715301513672
2023-09-28 23:25:27,308 - utils - INFO -  epoch: 525, all client loss: [0.6397345066070557, 0.6590442657470703], all pred client disparities: [0.024558041244745255, 0.11241279542446136], all client disparities: [0.009166666306555271, 0.11449671536684036], all client accs: [0.5976594090461731, 0.6019558310508728],  alpha_performance: tensor([0.6820, 0.3180], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:27,358 - utils - INFO - stage1_gradient_single_runtime: 0.002258777618408203
2023-09-28 23:25:27,359 - utils - INFO -  epoch: 526, all client loss: [0.6397659778594971, 0.6590128540992737], all pred client disparities: [0.0245085246860981, 0.11241526901721954], all client disparities: [0.009166666306555271, 0.11475431174039841], all client accs: [0.5976594090461731, 0.6021369099617004],  alpha_performance: tensor([0.6818, 0.3182], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:27,409 - utils - INFO - stage1_gradient_single_runtime: 0.0022122859954833984
2023-09-28 23:25:27,411 - utils - INFO -  epoch: 527, all client loss: [0.6397973895072937, 0.6589815020561218], all pred client disparities: [0.024459276348352432, 0.11241760849952698], all client disparities: [0.009166666306555271, 0.11458051949739456], all client accs: [0.5976594090461731, 0.6023180484771729],  alpha_performance: tensor([0.6816, 0.3184], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:27,463 - utils - INFO - stage1_gradient_single_runtime: 0.002544879913330078
2023-09-28 23:25:27,465 - utils - INFO -  epoch: 528, all client loss: [0.6398287415504456, 0.65895015001297], all pred client disparities: [0.024410305544734, 0.11241976916790009], all client disparities: [0.009166666306555271, 0.11492190510034561], all client accs: [0.5976594090461731, 0.6030423641204834],  alpha_performance: tensor([0.6814, 0.3186], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:27,563 - utils - INFO - stage1_gradient_single_runtime: 0.0022437572479248047
2023-09-28 23:25:27,564 - utils - INFO -  epoch: 529, all client loss: [0.6398599743843079, 0.6589189171791077], all pred client disparities: [0.024361608549952507, 0.11242179572582245], all client disparities: [0.009166666306555271, 0.11500570178031921], all client accs: [0.5976594090461731, 0.6034045815467834],  alpha_performance: tensor([0.6812, 0.3188], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:27,614 - utils - INFO - stage1_gradient_single_runtime: 0.002244234085083008
2023-09-28 23:25:27,614 - utils - INFO -  epoch: 530, all client loss: [0.6398912072181702, 0.6588878035545349], all pred client disparities: [0.024313172325491905, 0.11242368817329407], all client disparities: [0.009166666306555271, 0.11500570178031921], all client accs: [0.5976594090461731, 0.6032235026359558],  alpha_performance: tensor([0.6810, 0.3190], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:27,667 - utils - INFO - stage1_gradient_single_runtime: 0.0024793148040771484
2023-09-28 23:25:27,668 - utils - INFO -  epoch: 531, all client loss: [0.6399223804473877, 0.6588566899299622], all pred client disparities: [0.024264998733997345, 0.11242540180683136], all client disparities: [0.009166666306555271, 0.11483189463615417], all client accs: [0.5976594090461731, 0.6035856604576111],  alpha_performance: tensor([0.6808, 0.3192], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:27,720 - utils - INFO - stage1_gradient_single_runtime: 0.002317667007446289
2023-09-28 23:25:27,722 - utils - INFO -  epoch: 532, all client loss: [0.6399534344673157, 0.6588256359100342], all pred client disparities: [0.024217087775468826, 0.11242698132991791], all client disparities: [0.009166666306555271, 0.11465808004140854], all client accs: [0.5976594090461731, 0.6037667989730835],  alpha_performance: tensor([0.6807, 0.3193], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:27,773 - utils - INFO - stage1_gradient_single_runtime: 0.0021240711212158203
2023-09-28 23:25:27,774 - utils - INFO -  epoch: 533, all client loss: [0.6399844884872437, 0.6587947010993958], all pred client disparities: [0.0241694338619709, 0.11242838203907013], all client disparities: [0.009166666306555271, 0.11465808004140854], all client accs: [0.5976594090461731, 0.6037667989730835],  alpha_performance: tensor([0.6805, 0.3195], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:27,826 - utils - INFO - stage1_gradient_single_runtime: 0.002275228500366211
2023-09-28 23:25:27,828 - utils - INFO -  epoch: 534, all client loss: [0.6400154232978821, 0.6587638258934021], all pred client disparities: [0.02412204071879387, 0.112429678440094], all client disparities: [0.009166666306555271, 0.11422667652368546], all client accs: [0.5976594090461731, 0.6037667989730835],  alpha_performance: tensor([0.6803, 0.3197], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:27,880 - utils - INFO - stage1_gradient_single_runtime: 0.0024721622467041016
2023-09-28 23:25:27,881 - utils - INFO -  epoch: 535, all client loss: [0.6400463581085205, 0.6587328910827637], all pred client disparities: [0.02407490462064743, 0.11243078112602234], all client disparities: [0.009166666306555271, 0.11379527300596237], all client accs: [0.5976594090461731, 0.6037667989730835],  alpha_performance: tensor([0.6801, 0.3199], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:27,931 - utils - INFO - stage1_gradient_single_runtime: 0.0022132396697998047
2023-09-28 23:25:27,932 - utils - INFO -  epoch: 536, all client loss: [0.6400771737098694, 0.6587021350860596], all pred client disparities: [0.02402801252901554, 0.11243174970149994], all client disparities: [0.009166666306555271, 0.11379527300596237], all client accs: [0.5976594090461731, 0.6035856604576111],  alpha_performance: tensor([0.6799, 0.3201], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:27,987 - utils - INFO - stage1_gradient_single_runtime: 0.0021829605102539062
2023-09-28 23:25:27,987 - utils - INFO -  epoch: 537, all client loss: [0.640108048915863, 0.6586713790893555], all pred client disparities: [0.02398137003183365, 0.11243253946304321], all client disparities: [0.009166666306555271, 0.11293245851993561], all client accs: [0.5976594090461731, 0.6037667989730835],  alpha_performance: tensor([0.6798, 0.3202], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:28,037 - utils - INFO - stage1_gradient_single_runtime: 0.002235889434814453
2023-09-28 23:25:28,038 - utils - INFO -  epoch: 538, all client loss: [0.6401387453079224, 0.6586406826972961], all pred client disparities: [0.023934971541166306, 0.11243321001529694], all client disparities: [0.009166666306555271, 0.11293245851993561], all client accs: [0.5976594090461731, 0.6032235026359558],  alpha_performance: tensor([0.6796, 0.3204], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:28,087 - utils - INFO - stage1_gradient_single_runtime: 0.0022284984588623047
2023-09-28 23:25:28,089 - utils - INFO -  epoch: 539, all client loss: [0.6401694416999817, 0.6586100459098816], all pred client disparities: [0.023888809606432915, 0.11243371665477753], all client disparities: [0.009166666306555271, 0.11293245851993561], all client accs: [0.5976594090461731, 0.6030423641204834],  alpha_performance: tensor([0.6794, 0.3206], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:28,108 - utils - INFO - valid: True, epoch: 539, loss: [0.634131669998169, 0.6641383171081543], accuracy: [0.6159999966621399, 0.5839999914169312], mean_accuracy:0.5999999940395355,variance_accuracy:0.01600000262260437, disparity: [0.010638297535479069, 0.12967583537101746], mean_disparity:0.07015706645324826,variance_disparity:0.059518768917769194, pred_disparity: [0.02245943993330002, 0.12584583461284637]
2023-09-28 23:25:28,119 - utils - INFO - global_valid: True, epoch: 539,  global_loss: 0.6547612547874451, global_accuracy: 0.7304391756702682,  global_disparity:0.10500515252351761, global_pred_disparity: 0.10504477471113205,
2023-09-28 23:25:28,166 - utils - INFO - stage1_gradient_single_runtime: 0.0025434494018554688
2023-09-28 23:25:28,167 - utils - INFO -  epoch: 540, all client loss: [0.6402000784873962, 0.6585795283317566], all pred client disparities: [0.02384290099143982, 0.1124340295791626], all client disparities: [0.009166666306555271, 0.1134476512670517], all client accs: [0.5976594090461731, 0.6032235026359558],  alpha_performance: tensor([0.6792, 0.3208], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:28,220 - utils - INFO - stage1_gradient_single_runtime: 0.002401590347290039
2023-09-28 23:25:28,220 - utils - INFO -  epoch: 541, all client loss: [0.6402305960655212, 0.6585489511489868], all pred client disparities: [0.02379721961915493, 0.11243420839309692], all client disparities: [0.009166666306555271, 0.11301624029874802], all client accs: [0.5976594090461731, 0.6034045815467834],  alpha_performance: tensor([0.6790, 0.3210], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:28,270 - utils - INFO - stage1_gradient_single_runtime: 0.0023393630981445312
2023-09-28 23:25:28,272 - utils - INFO -  epoch: 542, all client loss: [0.6402611136436462, 0.6585185527801514], all pred client disparities: [0.023751776665449142, 0.1124342679977417], all client disparities: [0.009166666306555271, 0.11327383667230606], all client accs: [0.5976594090461731, 0.6034045815467834],  alpha_performance: tensor([0.6789, 0.3211], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:28,374 - utils - INFO - stage1_gradient_single_runtime: 0.0022096633911132812
2023-09-28 23:25:28,375 - utils - INFO -  epoch: 543, all client loss: [0.6402915716171265, 0.6584881544113159], all pred client disparities: [0.02370656654238701, 0.11243413388729095], all client disparities: [0.009166666306555271, 0.1135314479470253], all client accs: [0.5976594090461731, 0.6030423641204834],  alpha_performance: tensor([0.6787, 0.3213], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:28,432 - utils - INFO - stage1_gradient_single_runtime: 0.0024771690368652344
2023-09-28 23:25:28,432 - utils - INFO -  epoch: 544, all client loss: [0.6403220295906067, 0.6584578156471252], all pred client disparities: [0.02366158552467823, 0.11243382096290588], all client disparities: [0.009166666306555271, 0.11378904432058334], all client accs: [0.5976594090461731, 0.6032235026359558],  alpha_performance: tensor([0.6785, 0.3215], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:28,480 - utils - INFO - stage1_gradient_single_runtime: 0.0021326541900634766
2023-09-28 23:25:28,481 - utils - INFO -  epoch: 545, all client loss: [0.6403523683547974, 0.6584274768829346], all pred client disparities: [0.023616833612322807, 0.11243337392807007], all client disparities: [0.009166666306555271, 0.11378904432058334], all client accs: [0.5976594090461731, 0.6030423641204834],  alpha_performance: tensor([0.6783, 0.3217], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:28,531 - utils - INFO - stage1_gradient_single_runtime: 0.002221345901489258
2023-09-28 23:25:28,532 - utils - INFO -  epoch: 546, all client loss: [0.6403825879096985, 0.6583972573280334], all pred client disparities: [0.023572314530611038, 0.11243276298046112], all client disparities: [0.009166666306555271, 0.11378904432058334], all client accs: [0.5976594090461731, 0.6028612852096558],  alpha_performance: tensor([0.6782, 0.3218], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:28,582 - utils - INFO - stage1_gradient_single_runtime: 0.0022325515747070312
2023-09-28 23:25:28,583 - utils - INFO -  epoch: 547, all client loss: [0.6404128670692444, 0.6583670377731323], all pred client disparities: [0.02352801337838173, 0.11243200302124023], all client disparities: [0.009166666306555271, 0.11430423706769943], all client accs: [0.5976594090461731, 0.6028612852096558],  alpha_performance: tensor([0.6780, 0.3220], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:28,635 - utils - INFO - stage1_gradient_single_runtime: 0.0022885799407958984
2023-09-28 23:25:28,635 - utils - INFO -  epoch: 548, all client loss: [0.6404430270195007, 0.6583369374275208], all pred client disparities: [0.02348392829298973, 0.11243109405040741], all client disparities: [0.009166666306555271, 0.11456183344125748], all client accs: [0.5976594090461731, 0.6030423641204834],  alpha_performance: tensor([0.6778, 0.3222], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:28,699 - utils - INFO - stage1_gradient_single_runtime: 0.002447843551635742
2023-09-28 23:25:28,700 - utils - INFO -  epoch: 549, all client loss: [0.6404731869697571, 0.6583068370819092], all pred client disparities: [0.02344006486237049, 0.11242999136447906], all client disparities: [0.009166666306555271, 0.11481944471597672], all client accs: [0.5976594090461731, 0.6030423641204834],  alpha_performance: tensor([0.6777, 0.3223], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:28,748 - utils - INFO - stage1_gradient_single_runtime: 0.0026140213012695312
2023-09-28 23:25:28,748 - utils - INFO -  epoch: 550, all client loss: [0.6405032277107239, 0.6582767963409424], all pred client disparities: [0.02339641936123371, 0.11242873966693878], all client disparities: [0.009166666306555271, 0.11481944471597672], all client accs: [0.5976594090461731, 0.6026802062988281],  alpha_performance: tensor([0.6775, 0.3225], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:28,802 - utils - INFO - stage1_gradient_single_runtime: 0.002574920654296875
2023-09-28 23:25:28,803 - utils - INFO -  epoch: 551, all client loss: [0.6405333280563354, 0.6582468152046204], all pred client disparities: [0.023352984338998795, 0.11242732405662537], all client disparities: [0.009166666306555271, 0.11481944471597672], all client accs: [0.5976594090461731, 0.6023180484771729],  alpha_performance: tensor([0.6773, 0.3227], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:28,853 - utils - INFO - stage1_gradient_single_runtime: 0.0027587413787841797
2023-09-28 23:25:28,854 - utils - INFO -  epoch: 552, all client loss: [0.6405632495880127, 0.6582168936729431], all pred client disparities: [0.02330976352095604, 0.11242574453353882], all client disparities: [0.009166666306555271, 0.11447183042764664], all client accs: [0.5976594090461731, 0.6030423641204834],  alpha_performance: tensor([0.6772, 0.3228], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:28,906 - utils - INFO - stage1_gradient_single_runtime: 0.0021347999572753906
2023-09-28 23:25:28,906 - utils - INFO -  epoch: 553, all client loss: [0.6405931711196899, 0.6581870317459106], all pred client disparities: [0.02326674945652485, 0.11242398619651794], all client disparities: [0.009166666306555271, 0.114298015832901], all client accs: [0.5976594090461731, 0.6034045815467834],  alpha_performance: tensor([0.6770, 0.3230], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:28,958 - utils - INFO - stage1_gradient_single_runtime: 0.002522706985473633
2023-09-28 23:25:28,960 - utils - INFO -  epoch: 554, all client loss: [0.6406230330467224, 0.6581571698188782], all pred client disparities: [0.02322394773364067, 0.11242206394672394], all client disparities: [0.009166666306555271, 0.114298015832901], all client accs: [0.5976594090461731, 0.6034045815467834],  alpha_performance: tensor([0.6768, 0.3232], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:29,055 - utils - INFO - stage1_gradient_single_runtime: 0.0022420883178710938
2023-09-28 23:25:29,058 - utils - INFO -  epoch: 555, all client loss: [0.6406528353691101, 0.6581274271011353], all pred client disparities: [0.023181352764368057, 0.1124199777841568], all client disparities: [0.009166666306555271, 0.11455561220645905], all client accs: [0.5976594090461731, 0.6035856604576111],  alpha_performance: tensor([0.6767, 0.3233], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:29,111 - utils - INFO - stage1_gradient_single_runtime: 0.002185344696044922
2023-09-28 23:25:29,112 - utils - INFO -  epoch: 556, all client loss: [0.6406826376914978, 0.6580976247787476], all pred client disparities: [0.02313896082341671, 0.11241774260997772], all client disparities: [0.009166666306555271, 0.11481322348117828], all client accs: [0.5976594090461731, 0.6032235026359558],  alpha_performance: tensor([0.6765, 0.3235], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:29,165 - utils - INFO - stage1_gradient_single_runtime: 0.002450704574584961
2023-09-28 23:25:29,166 - utils - INFO -  epoch: 557, all client loss: [0.6407123804092407, 0.658068060874939], all pred client disparities: [0.023096775636076927, 0.11241531372070312], all client disparities: [0.009166666306555271, 0.11481322348117828], all client accs: [0.5976594090461731, 0.6032235026359558],  alpha_performance: tensor([0.6763, 0.3237], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:29,218 - utils - INFO - stage1_gradient_single_runtime: 0.002297639846801758
2023-09-28 23:25:29,219 - utils - INFO -  epoch: 558, all client loss: [0.6407420635223389, 0.6580384373664856], all pred client disparities: [0.023054789751768112, 0.11241278052330017], all client disparities: [0.009166666306555271, 0.11481322348117828], all client accs: [0.5976594090461731, 0.6032235026359558],  alpha_performance: tensor([0.6762, 0.3238], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:29,274 - utils - INFO - stage1_gradient_single_runtime: 0.0025475025177001953
2023-09-28 23:25:29,275 - utils - INFO -  epoch: 559, all client loss: [0.6407716870307922, 0.6580088138580322], all pred client disparities: [0.023013001307845116, 0.11240997910499573], all client disparities: [0.009166666306555271, 0.11507081985473633], all client accs: [0.5976594090461731, 0.6030423641204834],  alpha_performance: tensor([0.6760, 0.3240], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:29,293 - utils - INFO - valid: True, epoch: 559, loss: [0.6346897482872009, 0.663525402545929], accuracy: [0.6159999966621399, 0.589090883731842], mean_accuracy:0.602545440196991,variance_accuracy:0.013454556465148926, disparity: [0.010638297535479069, 0.1244022324681282], mean_disparity:0.06752026500180364,variance_disparity:0.05688196746632457, pred_disparity: [0.021648552268743515, 0.12512554228305817]
2023-09-28 23:25:29,304 - utils - INFO - global_valid: True, epoch: 559,  global_loss: 0.6545142531394958, global_accuracy: 0.7281347539015606,  global_disparity:0.10121189802885056, global_pred_disparity: 0.10441847890615463,
2023-09-28 23:25:29,355 - utils - INFO - stage1_gradient_single_runtime: 0.0021665096282958984
2023-09-28 23:25:29,356 - utils - INFO -  epoch: 560, all client loss: [0.6408012509346008, 0.6579792499542236], all pred client disparities: [0.02297140657901764, 0.11240708827972412], all client disparities: [0.009166666306555271, 0.11507081985473633], all client accs: [0.5976594090461731, 0.6028612852096558],  alpha_performance: tensor([0.6758, 0.3242], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:29,405 - utils - INFO - stage1_gradient_single_runtime: 0.0022063255310058594
2023-09-28 23:25:29,406 - utils - INFO -  epoch: 561, all client loss: [0.6408308148384094, 0.6579498052597046], all pred client disparities: [0.022930003702640533, 0.112404003739357], all client disparities: [0.009166666306555271, 0.11532841622829437], all client accs: [0.5976594090461731, 0.6030423641204834],  alpha_performance: tensor([0.6757, 0.3243], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:29,461 - utils - INFO - stage1_gradient_single_runtime: 0.002506256103515625
2023-09-28 23:25:29,462 - utils - INFO -  epoch: 562, all client loss: [0.6408602595329285, 0.6579203605651855], all pred client disparities: [0.02288879081606865, 0.11240072548389435], all client disparities: [0.009166666306555271, 0.11584360897541046], all client accs: [0.5976594090461731, 0.6032235026359558],  alpha_performance: tensor([0.6755, 0.3245], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:29,513 - utils - INFO - stage1_gradient_single_runtime: 0.0022287368774414062
2023-09-28 23:25:29,515 - utils - INFO -  epoch: 563, all client loss: [0.6408897042274475, 0.657891035079956], all pred client disparities: [0.022847773507237434, 0.11239728331565857], all client disparities: [0.009166666306555271, 0.11566981673240662], all client accs: [0.5976594090461731, 0.6034045815467834],  alpha_performance: tensor([0.6754, 0.3246], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:29,568 - utils - INFO - stage1_gradient_single_runtime: 0.002147674560546875
2023-09-28 23:25:29,568 - utils - INFO -  epoch: 564, all client loss: [0.6409191489219666, 0.6578616499900818], all pred client disparities: [0.02280694618821144, 0.11239366233348846], all client disparities: [0.009166666306555271, 0.11601120233535767], all client accs: [0.5976594090461731, 0.6039478778839111],  alpha_performance: tensor([0.6752, 0.3248], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:29,621 - utils - INFO - stage1_gradient_single_runtime: 0.0021467208862304688
2023-09-28 23:25:29,623 - utils - INFO -  epoch: 565, all client loss: [0.6409484148025513, 0.6578323245048523], all pred client disparities: [0.02276630699634552, 0.11238989233970642], all client disparities: [0.009166666306555271, 0.11704160273075104], all client accs: [0.5976594090461731, 0.6043100357055664],  alpha_performance: tensor([0.6751, 0.3249], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:29,729 - utils - INFO - stage1_gradient_single_runtime: 0.0025811195373535156
2023-09-28 23:25:29,731 - utils - INFO -  epoch: 566, all client loss: [0.6409777402877808, 0.6578031182289124], all pred client disparities: [0.022725854068994522, 0.11238594353199005], all client disparities: [0.009166666306555271, 0.11729919910430908], all client accs: [0.5976594090461731, 0.6043100357055664],  alpha_performance: tensor([0.6749, 0.3251], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:29,784 - utils - INFO - stage1_gradient_single_runtime: 0.0023102760314941406
2023-09-28 23:25:29,785 - utils - INFO -  epoch: 567, all client loss: [0.6410070061683655, 0.6577738523483276], all pred client disparities: [0.022685576230287552, 0.11238180100917816], all client disparities: [0.009166666306555271, 0.1168677881360054], all client accs: [0.5976594090461731, 0.604491114616394],  alpha_performance: tensor([0.6747, 0.3253], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:29,836 - utils - INFO - stage1_gradient_single_runtime: 0.0021653175354003906
2023-09-28 23:25:29,837 - utils - INFO -  epoch: 568, all client loss: [0.6410362124443054, 0.6577446460723877], all pred client disparities: [0.022645488381385803, 0.11237749457359314], all client disparities: [0.009166666306555271, 0.1168677881360054], all client accs: [0.5976594090461731, 0.6041289567947388],  alpha_performance: tensor([0.6746, 0.3254], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:29,888 - utils - INFO - stage1_gradient_single_runtime: 0.002261638641357422
2023-09-28 23:25:29,889 - utils - INFO -  epoch: 569, all client loss: [0.6410653591156006, 0.6577155590057373], all pred client disparities: [0.022605575621128082, 0.11237302422523499], all client disparities: [0.009166666306555271, 0.11669398099184036], all client accs: [0.5976594090461731, 0.6041289567947388],  alpha_performance: tensor([0.6744, 0.3256], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:29,940 - utils - INFO - stage1_gradient_single_runtime: 0.002261638641357422
2023-09-28 23:25:29,942 - utils - INFO -  epoch: 570, all client loss: [0.641094446182251, 0.6576865315437317], all pred client disparities: [0.022565841674804688, 0.11236834526062012], all client disparities: [0.009166666306555271, 0.11608876287937164], all client accs: [0.5976594090461731, 0.604491114616394],  alpha_performance: tensor([0.6743, 0.3257], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:29,992 - utils - INFO - stage1_gradient_single_runtime: 0.002567768096923828
2023-09-28 23:25:29,994 - utils - INFO -  epoch: 571, all client loss: [0.6411235928535461, 0.6576575040817261], all pred client disparities: [0.02252628654241562, 0.11236348748207092], all client disparities: [0.009166666306555271, 0.11608876287937164], all client accs: [0.5976594090461731, 0.6039478778839111],  alpha_performance: tensor([0.6741, 0.3259], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:30,043 - utils - INFO - stage1_gradient_single_runtime: 0.0024394989013671875
2023-09-28 23:25:30,044 - utils - INFO -  epoch: 572, all client loss: [0.6411526203155518, 0.6576284766197205], all pred client disparities: [0.022486906498670578, 0.11235849559307098], all client disparities: [0.009166666306555271, 0.11660397052764893], all client accs: [0.5976594090461731, 0.6041289567947388],  alpha_performance: tensor([0.6740, 0.3260], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:30,093 - utils - INFO - stage1_gradient_single_runtime: 0.002457141876220703
2023-09-28 23:25:30,095 - utils - INFO -  epoch: 573, all client loss: [0.6411816477775574, 0.6575995683670044], all pred client disparities: [0.022447701543569565, 0.11235328018665314], all client disparities: [0.009166666306555271, 0.11686156690120697], all client accs: [0.5976594090461731, 0.6041289567947388],  alpha_performance: tensor([0.6738, 0.3262], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:30,146 - utils - INFO - stage1_gradient_single_runtime: 0.0022230148315429688
2023-09-28 23:25:30,146 - utils - INFO -  epoch: 574, all client loss: [0.6412105560302734, 0.6575706601142883], all pred client disparities: [0.02240867353975773, 0.11234790086746216], all client disparities: [0.009166666306555271, 0.11643016338348389], all client accs: [0.5976594090461731, 0.6041289567947388],  alpha_performance: tensor([0.6737, 0.3263], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:30,200 - utils - INFO - stage1_gradient_single_runtime: 0.0022230148315429688
2023-09-28 23:25:30,200 - utils - INFO -  epoch: 575, all client loss: [0.6412394642829895, 0.657541811466217], all pred client disparities: [0.022369809448719025, 0.11234234273433685], all client disparities: [0.009166666306555271, 0.11702916026115417], all client accs: [0.5976594090461731, 0.6050344109535217],  alpha_performance: tensor([0.6735, 0.3265], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:30,255 - utils - INFO - stage1_gradient_single_runtime: 0.0021445751190185547
2023-09-28 23:25:30,256 - utils - INFO -  epoch: 576, all client loss: [0.6412683129310608, 0.6575129628181458], all pred client disparities: [0.0223311185836792, 0.11233659088611603], all client disparities: [0.009166666306555271, 0.11728675663471222], all client accs: [0.5976594090461731, 0.6052155494689941],  alpha_performance: tensor([0.6734, 0.3266], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:30,309 - utils - INFO - stage1_gradient_single_runtime: 0.002461671829223633
2023-09-28 23:25:30,309 - utils - INFO -  epoch: 577, all client loss: [0.6412971019744873, 0.657484233379364], all pred client disparities: [0.022292595356702805, 0.11233064532279968], all client disparities: [0.009166666306555271, 0.11685533821582794], all client accs: [0.5976594090461731, 0.6053966283798218],  alpha_performance: tensor([0.6732, 0.3268], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:30,411 - utils - INFO - stage1_gradient_single_runtime: 0.0022923946380615234
2023-09-28 23:25:30,413 - utils - INFO -  epoch: 578, all client loss: [0.6413258910179138, 0.6574555039405823], all pred client disparities: [0.022254236042499542, 0.1123245507478714], all client disparities: [0.009166666306555271, 0.11711293458938599], all client accs: [0.5976594090461731, 0.6053966283798218],  alpha_performance: tensor([0.6731, 0.3269], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:30,468 - utils - INFO - stage1_gradient_single_runtime: 0.002161264419555664
2023-09-28 23:25:30,468 - utils - INFO -  epoch: 579, all client loss: [0.6413546204566956, 0.6574267745018005], all pred client disparities: [0.02221604809165001, 0.11231827735900879], all client disparities: [0.009166666306555271, 0.1156449168920517], all client accs: [0.5976594090461731, 0.6063020825386047],  alpha_performance: tensor([0.6729, 0.3271], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:30,490 - utils - INFO - valid: True, epoch: 579, loss: [0.635234534740448, 0.6629263758659363], accuracy: [0.6159999966621399, 0.5912727117538452], mean_accuracy:0.6036363542079926,variance_accuracy:0.012363642454147339, disparity: [0.010638297535479069, 0.1253015100955963], mean_disparity:0.06796990381553769,variance_disparity:0.05733160628005862, pred_disparity: [0.02091393992304802, 0.12435412406921387]
2023-09-28 23:25:30,503 - utils - INFO - global_valid: True, epoch: 579,  global_loss: 0.654272735118866, global_accuracy: 0.7257693077230891,  global_disparity:0.10198340564966202, global_pred_disparity: 0.10377141833305359,
2023-09-28 23:25:30,551 - utils - INFO - stage1_gradient_single_runtime: 0.002573251724243164
2023-09-28 23:25:30,553 - utils - INFO -  epoch: 580, all client loss: [0.6413833498954773, 0.6573981046676636], all pred client disparities: [0.02217802405357361, 0.11231176555156708], all client disparities: [0.009166666306555271, 0.1156449168920517], all client accs: [0.5976594090461731, 0.6061210036277771],  alpha_performance: tensor([0.6728, 0.3272], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:30,605 - utils - INFO - stage1_gradient_single_runtime: 0.0022385120391845703
2023-09-28 23:25:30,606 - utils - INFO -  epoch: 581, all client loss: [0.6414120197296143, 0.6573694944381714], all pred client disparities: [0.022140154615044594, 0.11230507493019104], all client disparities: [0.009166666306555271, 0.11590251326560974], all client accs: [0.5976594090461731, 0.6063020825386047],  alpha_performance: tensor([0.6727, 0.3273], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:30,660 - utils - INFO - stage1_gradient_single_runtime: 0.0025701522827148438
2023-09-28 23:25:30,661 - utils - INFO -  epoch: 582, all client loss: [0.6414406299591064, 0.657340943813324], all pred client disparities: [0.02210245467722416, 0.11229822039604187], all client disparities: [0.009166666306555271, 0.11616012454032898], all client accs: [0.5976594090461731, 0.6063020825386047],  alpha_performance: tensor([0.6725, 0.3275], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:30,713 - utils - INFO - stage1_gradient_single_runtime: 0.0023374557495117188
2023-09-28 23:25:30,714 - utils - INFO -  epoch: 583, all client loss: [0.6414692401885986, 0.6573123931884766], all pred client disparities: [0.02206490747630596, 0.11229117214679718], all client disparities: [0.009166666306555271, 0.11693291366100311], all client accs: [0.5976594090461731, 0.6068453788757324],  alpha_performance: tensor([0.6724, 0.3276], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:30,767 - utils - INFO - stage1_gradient_single_runtime: 0.0025162696838378906
2023-09-28 23:25:30,768 - utils - INFO -  epoch: 584, all client loss: [0.6414977312088013, 0.6572839021682739], all pred client disparities: [0.02202751487493515, 0.11228393018245697], all client disparities: [0.009166666306555271, 0.11650149524211884], all client accs: [0.5976594090461731, 0.6066642999649048],  alpha_performance: tensor([0.6722, 0.3278], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:30,820 - utils - INFO - stage1_gradient_single_runtime: 0.0021820068359375
2023-09-28 23:25:30,822 - utils - INFO -  epoch: 585, all client loss: [0.6415262818336487, 0.6572554707527161], all pred client disparities: [0.02199028991162777, 0.11227649450302124], all client disparities: [0.009166666306555271, 0.11727429926395416], all client accs: [0.5976594090461731, 0.6070264577865601],  alpha_performance: tensor([0.6721, 0.3279], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:30,874 - utils - INFO - stage1_gradient_single_runtime: 0.002268075942993164
2023-09-28 23:25:30,874 - utils - INFO -  epoch: 586, all client loss: [0.6415547728538513, 0.6572270393371582], all pred client disparities: [0.021953212097287178, 0.1122688353061676], all client disparities: [0.009166666306555271, 0.11753189563751221], all client accs: [0.5976594090461731, 0.6072075366973877],  alpha_performance: tensor([0.6719, 0.3281], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:30,930 - utils - INFO - stage1_gradient_single_runtime: 0.0023834705352783203
2023-09-28 23:25:30,931 - utils - INFO -  epoch: 587, all client loss: [0.6415831446647644, 0.6571986675262451], all pred client disparities: [0.02191629633307457, 0.11226102709770203], all client disparities: [0.009166666306555271, 0.11778949201107025], all client accs: [0.5976594090461731, 0.6073886156082153],  alpha_performance: tensor([0.6718, 0.3282], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:30,983 - utils - INFO - stage1_gradient_single_runtime: 0.0021033287048339844
2023-09-28 23:25:30,984 - utils - INFO -  epoch: 588, all client loss: [0.6416115760803223, 0.657170295715332], all pred client disparities: [0.021879535168409348, 0.11225302517414093], all client disparities: [0.009166666306555271, 0.11778949201107025], all client accs: [0.5976594090461731, 0.6072075366973877],  alpha_performance: tensor([0.6717, 0.3283], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:31,041 - utils - INFO - stage1_gradient_single_runtime: 0.0021867752075195312
2023-09-28 23:25:31,042 - utils - INFO -  epoch: 589, all client loss: [0.6416398882865906, 0.6571419835090637], all pred client disparities: [0.021842926740646362, 0.11224481463432312], all client disparities: [0.009166666306555271, 0.11830469965934753], all client accs: [0.5976594090461731, 0.6073886156082153],  alpha_performance: tensor([0.6715, 0.3285], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:31,160 - utils - INFO - stage1_gradient_single_runtime: 0.002349853515625
2023-09-28 23:25:31,162 - utils - INFO -  epoch: 590, all client loss: [0.6416682004928589, 0.6571137309074402], all pred client disparities: [0.021806463599205017, 0.11223641037940979], all client disparities: [0.009166666306555271, 0.11787329614162445], all client accs: [0.5976594090461731, 0.6073886156082153],  alpha_performance: tensor([0.6714, 0.3286], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:31,214 - utils - INFO - stage1_gradient_single_runtime: 0.0022733211517333984
2023-09-28 23:25:31,215 - utils - INFO -  epoch: 591, all client loss: [0.6416964530944824, 0.6570854783058167], all pred client disparities: [0.02177015133202076, 0.11222781240940094], all client disparities: [0.009166666306555271, 0.1181308925151825], all client accs: [0.5976594090461731, 0.6073886156082153],  alpha_performance: tensor([0.6713, 0.3287], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:31,272 - utils - INFO - stage1_gradient_single_runtime: 0.002191305160522461
2023-09-28 23:25:31,272 - utils - INFO -  epoch: 592, all client loss: [0.641724705696106, 0.6570573449134827], all pred client disparities: [0.021733993664383888, 0.11221900582313538], all client disparities: [0.009166666306555271, 0.11795708537101746], all client accs: [0.5976594090461731, 0.6073886156082153],  alpha_performance: tensor([0.6711, 0.3289], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:31,323 - utils - INFO - stage1_gradient_single_runtime: 0.002235889434814453
2023-09-28 23:25:31,324 - utils - INFO -  epoch: 593, all client loss: [0.6417528986930847, 0.6570291519165039], all pred client disparities: [0.02169797569513321, 0.11221000552177429], all client disparities: [0.009166666306555271, 0.11795708537101746], all client accs: [0.5976594090461731, 0.6072075366973877],  alpha_performance: tensor([0.6710, 0.3290], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:31,377 - utils - INFO - stage1_gradient_single_runtime: 0.0021750926971435547
2023-09-28 23:25:31,377 - utils - INFO -  epoch: 594, all client loss: [0.6417810916900635, 0.6570010185241699], all pred client disparities: [0.02166210673749447, 0.11220081150531769], all client disparities: [0.009166666306555271, 0.11778327822685242], all client accs: [0.5976594090461731, 0.6073886156082153],  alpha_performance: tensor([0.6709, 0.3291], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:31,430 - utils - INFO - stage1_gradient_single_runtime: 0.002270936965942383
2023-09-28 23:25:31,431 - utils - INFO -  epoch: 595, all client loss: [0.6418092250823975, 0.6569729447364807], all pred client disparities: [0.021626390516757965, 0.11219142377376556], all client disparities: [0.009166666306555271, 0.11692047119140625], all client accs: [0.5976594090461731, 0.6075697541236877],  alpha_performance: tensor([0.6707, 0.3293], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:31,490 - utils - INFO - stage1_gradient_single_runtime: 0.002512693405151367
2023-09-28 23:25:31,493 - utils - INFO -  epoch: 596, all client loss: [0.6418373584747314, 0.6569448709487915], all pred client disparities: [0.021590813994407654, 0.11218181252479553], all client disparities: [0.009166666306555271, 0.1171780675649643], all client accs: [0.5976594090461731, 0.6073886156082153],  alpha_performance: tensor([0.6706, 0.3294], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:31,543 - utils - INFO - stage1_gradient_single_runtime: 0.0022602081298828125
2023-09-28 23:25:31,544 - utils - INFO -  epoch: 597, all client loss: [0.6418653726577759, 0.6569168567657471], all pred client disparities: [0.021555382758378983, 0.11217200756072998], all client disparities: [0.009166666306555271, 0.11743566393852234], all client accs: [0.5976594090461731, 0.6073886156082153],  alpha_performance: tensor([0.6705, 0.3295], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:31,596 - utils - INFO - stage1_gradient_single_runtime: 0.0022318363189697266
2023-09-28 23:25:31,598 - utils - INFO -  epoch: 598, all client loss: [0.6418934464454651, 0.6568889021873474], all pred client disparities: [0.021520087495446205, 0.1121620237827301], all client disparities: [0.009166666306555271, 0.1172618567943573], all client accs: [0.5980629324913025, 0.6075697541236877],  alpha_performance: tensor([0.6703, 0.3297], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:31,654 - utils - INFO - stage1_gradient_single_runtime: 0.0024814605712890625
2023-09-28 23:25:31,656 - utils - INFO -  epoch: 599, all client loss: [0.6419214010238647, 0.6568609476089478], all pred client disparities: [0.021484937518835068, 0.11215180158615112], all client disparities: [0.009166666306555271, 0.11751945316791534], all client accs: [0.5980629324913025, 0.6077508330345154],  alpha_performance: tensor([0.6702, 0.3298], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:31,676 - utils - INFO - valid: True, epoch: 599, loss: [0.6357684135437012, 0.6623384952545166], accuracy: [0.6159999966621399, 0.5963636040687561], mean_accuracy:0.606181800365448,variance_accuracy:0.009818196296691895, disparity: [0.010638297535479069, 0.12499478459358215], mean_disparity:0.06781654106453061,variance_disparity:0.05717824352905154, pred_disparity: [0.020242806524038315, 0.12353755533695221]
2023-09-28 23:25:31,689 - utils - INFO - global_valid: True, epoch: 599,  global_loss: 0.6540354490280151, global_accuracy: 0.7233803521408564,  global_disparity:0.1019030436873436, global_pred_disparity: 0.10310591012239456,
2023-09-28 23:25:31,739 - utils - INFO - stage1_gradient_single_runtime: 0.002519845962524414
2023-09-28 23:25:31,740 - utils - INFO -  epoch: 600, all client loss: [0.6419493556022644, 0.6568329930305481], all pred client disparities: [0.02144993469119072, 0.11214137077331543], all client disparities: [0.009166666306555271, 0.1173456460237503], all client accs: [0.5980629324913025, 0.6077508330345154],  alpha_performance: tensor([0.6701, 0.3299], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:31,794 - utils - INFO - stage1_gradient_single_runtime: 0.0025577545166015625
2023-09-28 23:25:31,795 - utils - INFO -  epoch: 601, all client loss: [0.6419773101806641, 0.656805157661438], all pred client disparities: [0.021415062248706818, 0.11213074624538422], all client disparities: [0.009166666306555271, 0.11742943525314331], all client accs: [0.5980629324913025, 0.607931911945343],  alpha_performance: tensor([0.6699, 0.3301], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:31,910 - utils - INFO - stage1_gradient_single_runtime: 0.0022852420806884766
2023-09-28 23:25:31,912 - utils - INFO -  epoch: 602, all client loss: [0.642005205154419, 0.6567773222923279], all pred client disparities: [0.021380331367254257, 0.11211991310119629], all client disparities: [0.009166666306555271, 0.11768704652786255], all client accs: [0.5980629324913025, 0.607931911945343],  alpha_performance: tensor([0.6698, 0.3302], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:31,965 - utils - INFO - stage1_gradient_single_runtime: 0.00222015380859375
2023-09-28 23:25:31,966 - utils - INFO -  epoch: 603, all client loss: [0.6420331001281738, 0.6567494869232178], all pred client disparities: [0.02134573832154274, 0.11210885643959045], all client disparities: [0.009166666306555271, 0.11733943223953247], all client accs: [0.5980629324913025, 0.6086562871932983],  alpha_performance: tensor([0.6697, 0.3303], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:32,016 - utils - INFO - stage1_gradient_single_runtime: 0.002269268035888672
2023-09-28 23:25:32,017 - utils - INFO -  epoch: 604, all client loss: [0.6420608758926392, 0.6567216515541077], all pred client disparities: [0.021311284974217415, 0.1120976060628891], all client disparities: [0.009166666306555271, 0.11759704351425171], all client accs: [0.5980629324913025, 0.608837366104126],  alpha_performance: tensor([0.6696, 0.3304], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:32,072 - utils - INFO - stage1_gradient_single_runtime: 0.002521514892578125
2023-09-28 23:25:32,074 - utils - INFO -  epoch: 605, all client loss: [0.6420886516571045, 0.6566939353942871], all pred client disparities: [0.021276963874697685, 0.11208617687225342], all client disparities: [0.009166666306555271, 0.11759704351425171], all client accs: [0.5980629324913025, 0.6086562871932983],  alpha_performance: tensor([0.6694, 0.3306], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:32,130 - utils - INFO - stage1_gradient_single_runtime: 0.002254486083984375
2023-09-28 23:25:32,130 - utils - INFO -  epoch: 606, all client loss: [0.6421164274215698, 0.6566662192344666], all pred client disparities: [0.02124277874827385, 0.11207447946071625], all client disparities: [0.009166666306555271, 0.11742320656776428], all client accs: [0.5980629324913025, 0.6084752082824707],  alpha_performance: tensor([0.6693, 0.3307], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:32,186 - utils - INFO - stage1_gradient_single_runtime: 0.002269268035888672
2023-09-28 23:25:32,187 - utils - INFO -  epoch: 607, all client loss: [0.6421440839767456, 0.6566385626792908], all pred client disparities: [0.02120872773230076, 0.11206258833408356], all client disparities: [0.009166666306555271, 0.11724941432476044], all client accs: [0.5980629324913025, 0.6084752082824707],  alpha_performance: tensor([0.6692, 0.3308], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:32,235 - utils - INFO - stage1_gradient_single_runtime: 0.002399921417236328
2023-09-28 23:25:32,236 - utils - INFO -  epoch: 608, all client loss: [0.6421718001365662, 0.656610906124115], all pred client disparities: [0.021174808964133263, 0.11205045878887177], all client disparities: [0.009166666306555271, 0.11750699579715729], all client accs: [0.5980629324913025, 0.6086562871932983],  alpha_performance: tensor([0.6691, 0.3309], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:32,287 - utils - INFO - stage1_gradient_single_runtime: 0.0026862621307373047
2023-09-28 23:25:32,288 - utils - INFO -  epoch: 609, all client loss: [0.6421994566917419, 0.656583309173584], all pred client disparities: [0.02114102803170681, 0.11203816533088684], all client disparities: [0.009166666306555271, 0.11664418876171112], all client accs: [0.5980629324913025, 0.6086562871932983],  alpha_performance: tensor([0.6689, 0.3311], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:32,340 - utils - INFO - stage1_gradient_single_runtime: 0.002800464630126953
2023-09-28 23:25:32,342 - utils - INFO -  epoch: 610, all client loss: [0.6422271728515625, 0.656555712223053], all pred client disparities: [0.021107368171215057, 0.11202563345432281], all client disparities: [0.009166666306555271, 0.11672800779342651], all client accs: [0.5980629324913025, 0.609199583530426],  alpha_performance: tensor([0.6688, 0.3312], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:32,395 - utils - INFO - stage1_gradient_single_runtime: 0.002251863479614258
2023-09-28 23:25:32,398 - utils - INFO -  epoch: 611, all client loss: [0.6422547698020935, 0.6565281748771667], all pred client disparities: [0.0210738442838192, 0.11201287806034088], all client disparities: [0.009166666306555271, 0.1172432005405426], all client accs: [0.5980629324913025, 0.6093806624412537],  alpha_performance: tensor([0.6687, 0.3313], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:32,451 - utils - INFO - stage1_gradient_single_runtime: 0.0024771690368652344
2023-09-28 23:25:32,453 - utils - INFO -  epoch: 612, all client loss: [0.642282247543335, 0.6565006375312805], all pred client disparities: [0.021040458232164383, 0.11199988424777985], all client disparities: [0.009166666306555271, 0.11750078201293945], all client accs: [0.5980629324913025, 0.6095618009567261],  alpha_performance: tensor([0.6686, 0.3314], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:32,557 - utils - INFO - stage1_gradient_single_runtime: 0.002211332321166992
2023-09-28 23:25:32,558 - utils - INFO -  epoch: 613, all client loss: [0.642309844493866, 0.6564731597900391], all pred client disparities: [0.021007193252444267, 0.1119866669178009], all client disparities: [0.009166666306555271, 0.11775839328765869], all client accs: [0.5980629324913025, 0.6097428798675537],  alpha_performance: tensor([0.6684, 0.3316], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:32,613 - utils - INFO - stage1_gradient_single_runtime: 0.002291440963745117
2023-09-28 23:25:32,614 - utils - INFO -  epoch: 614, all client loss: [0.6423373222351074, 0.6564456820487976], all pred client disparities: [0.02097405679523945, 0.11197327077388763], all client disparities: [0.009166666306555271, 0.1178421676158905], all client accs: [0.5980629324913025, 0.6102861166000366],  alpha_performance: tensor([0.6683, 0.3317], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:32,664 - utils - INFO - stage1_gradient_single_runtime: 0.002209901809692383
2023-09-28 23:25:32,665 - utils - INFO -  epoch: 615, all client loss: [0.6423647999763489, 0.6564182639122009], all pred client disparities: [0.02094104513525963, 0.11195962131023407], all client disparities: [0.009166666306555271, 0.1178421676158905], all client accs: [0.5980629324913025, 0.610105037689209],  alpha_performance: tensor([0.6682, 0.3318], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:32,718 - utils - INFO - stage1_gradient_single_runtime: 0.002559185028076172
2023-09-28 23:25:32,720 - utils - INFO -  epoch: 616, all client loss: [0.6423922181129456, 0.656390905380249], all pred client disparities: [0.020908163860440254, 0.11194576323032379], all client disparities: [0.009166666306555271, 0.11809977889060974], all client accs: [0.5980629324913025, 0.6102861166000366],  alpha_performance: tensor([0.6681, 0.3319], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:32,774 - utils - INFO - stage1_gradient_single_runtime: 0.0022118091583251953
2023-09-28 23:25:32,775 - utils - INFO -  epoch: 617, all client loss: [0.6424196362495422, 0.6563634872436523], all pred client disparities: [0.020875411108136177, 0.11193165183067322], all client disparities: [0.009166666306555271, 0.11809977889060974], all client accs: [0.5980629324913025, 0.610105037689209],  alpha_performance: tensor([0.6680, 0.3320], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:32,833 - utils - INFO - stage1_gradient_single_runtime: 0.0022830963134765625
2023-09-28 23:25:32,833 - utils - INFO -  epoch: 618, all client loss: [0.6424469947814941, 0.6563361883163452], all pred client disparities: [0.0208427831530571, 0.11191736161708832], all client disparities: [0.009166666306555271, 0.11792595684528351], all client accs: [0.5980629324913025, 0.6102861166000366],  alpha_performance: tensor([0.6679, 0.3321], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:32,884 - utils - INFO - stage1_gradient_single_runtime: 0.0022232532501220703
2023-09-28 23:25:32,885 - utils - INFO -  epoch: 619, all client loss: [0.642474353313446, 0.6563088893890381], all pred client disparities: [0.020810281857848167, 0.11190277338027954], all client disparities: [0.009166666306555271, 0.11818356812000275], all client accs: [0.5980629324913025, 0.610467255115509],  alpha_performance: tensor([0.6677, 0.3323], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:32,904 - utils - INFO - valid: True, epoch: 619, loss: [0.6362935304641724, 0.6617597341537476], accuracy: [0.6159999966621399, 0.5956363677978516], mean_accuracy:0.6058181822299957,variance_accuracy:0.010181814432144165, disparity: [0.010638297535479069, 0.12544439733028412], mean_disparity:0.0680413474328816,variance_disparity:0.057403049897402525, pred_disparity: [0.019626013934612274, 0.12268027663230896]
2023-09-28 23:25:32,915 - utils - INFO - global_valid: True, epoch: 619,  global_loss: 0.6538016200065613, global_accuracy: 0.7210124049619848,  global_disparity:0.10228879749774933, global_pred_disparity: 0.10242385417222977,
2023-09-28 23:25:32,965 - utils - INFO - stage1_gradient_single_runtime: 0.0022346973419189453
2023-09-28 23:25:32,965 - utils - INFO -  epoch: 620, all client loss: [0.6425016522407532, 0.6562816500663757], all pred client disparities: [0.020777899771928787, 0.11188805103302002], all client disparities: [0.009166666306555271, 0.11775216460227966], all client accs: [0.5980629324913025, 0.6106483340263367],  alpha_performance: tensor([0.6676, 0.3324], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:33,017 - utils - INFO - stage1_gradient_single_runtime: 0.002160787582397461
2023-09-28 23:25:33,019 - utils - INFO -  epoch: 621, all client loss: [0.6425290107727051, 0.6562543511390686], all pred client disparities: [0.020745644345879555, 0.11187303066253662], all client disparities: [0.009166666306555271, 0.11775216460227966], all client accs: [0.5980629324913025, 0.610105037689209],  alpha_performance: tensor([0.6675, 0.3325], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:33,074 - utils - INFO - stage1_gradient_single_runtime: 0.002202272415161133
2023-09-28 23:25:33,075 - utils - INFO -  epoch: 622, all client loss: [0.6425562500953674, 0.656227171421051], all pred client disparities: [0.02071351185441017, 0.11185778677463531], all client disparities: [0.009166666306555271, 0.1180935651063919], all client accs: [0.5980629324913025, 0.6106483340263367],  alpha_performance: tensor([0.6674, 0.3326], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:33,128 - utils - INFO - stage1_gradient_single_runtime: 0.002267122268676758
2023-09-28 23:25:33,129 - utils - INFO -  epoch: 623, all client loss: [0.6425834894180298, 0.6561999320983887], all pred client disparities: [0.020681504160165787, 0.1118423342704773], all client disparities: [0.009166666306555271, 0.11766216158866882], all client accs: [0.5980629324913025, 0.610467255115509],  alpha_performance: tensor([0.6673, 0.3327], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:33,180 - utils - INFO - stage1_gradient_single_runtime: 0.0025217533111572266
2023-09-28 23:25:33,180 - utils - INFO -  epoch: 624, all client loss: [0.6426107287406921, 0.6561727523803711], all pred client disparities: [0.02064961940050125, 0.11182665824890137], all client disparities: [0.009166666306555271, 0.11791974306106567], all client accs: [0.5980629324913025, 0.6106483340263367],  alpha_performance: tensor([0.6672, 0.3328], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:33,285 - utils - INFO - stage1_gradient_single_runtime: 0.0025985240936279297
2023-09-28 23:25:33,286 - utils - INFO -  epoch: 625, all client loss: [0.6426378488540649, 0.6561456918716431], all pred client disparities: [0.020617857575416565, 0.11181072890758514], all client disparities: [0.009166666306555271, 0.11843493580818176], all client accs: [0.5980629324913025, 0.6110105514526367],  alpha_performance: tensor([0.6671, 0.3329], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:33,336 - utils - INFO - stage1_gradient_single_runtime: 0.0022161006927490234
2023-09-28 23:25:33,338 - utils - INFO -  epoch: 626, all client loss: [0.6426650285720825, 0.6561185717582703], all pred client disparities: [0.02058621309697628, 0.11179456114768982], all client disparities: [0.009166666306555271, 0.118692547082901], all client accs: [0.5980629324913025, 0.6110105514526367],  alpha_performance: tensor([0.6670, 0.3330], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:33,391 - utils - INFO - stage1_gradient_single_runtime: 0.0022361278533935547
2023-09-28 23:25:33,391 - utils - INFO -  epoch: 627, all client loss: [0.6426920890808105, 0.6560914516448975], all pred client disparities: [0.020554684102535248, 0.1117781549692154], all client disparities: [0.009166666306555271, 0.11895015835762024], all client accs: [0.5980629324913025, 0.6110105514526367],  alpha_performance: tensor([0.6668, 0.3332], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:33,447 - utils - INFO - stage1_gradient_single_runtime: 0.0024652481079101562
2023-09-28 23:25:33,448 - utils - INFO -  epoch: 628, all client loss: [0.6427192091941833, 0.6560644507408142], all pred client disparities: [0.020523281767964363, 0.11176152527332306], all client disparities: [0.009166666306555271, 0.11851873993873596], all client accs: [0.5980629324913025, 0.6108294129371643],  alpha_performance: tensor([0.6667, 0.3333], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:33,498 - utils - INFO - stage1_gradient_single_runtime: 0.0027120113372802734
2023-09-28 23:25:33,499 - utils - INFO -  epoch: 629, all client loss: [0.6427462100982666, 0.656037449836731], all pred client disparities: [0.02049199678003788, 0.11174465715885162], all client disparities: [0.009166666306555271, 0.11851873993873596], all client accs: [0.5980629324913025, 0.6108294129371643],  alpha_performance: tensor([0.6666, 0.3334], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:33,554 - utils - INFO - stage1_gradient_single_runtime: 0.0022325515747070312
2023-09-28 23:25:33,554 - utils - INFO -  epoch: 630, all client loss: [0.6427732706069946, 0.6560104489326477], all pred client disparities: [0.020460834726691246, 0.1117275208234787], all client disparities: [0.009166666306555271, 0.11903393268585205], all client accs: [0.5980629324913025, 0.6110105514526367],  alpha_performance: tensor([0.6665, 0.3335], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:33,604 - utils - INFO - stage1_gradient_single_runtime: 0.002260446548461914
2023-09-28 23:25:33,606 - utils - INFO -  epoch: 631, all client loss: [0.6428003311157227, 0.6559835076332092], all pred client disparities: [0.020429788157343864, 0.11171016097068787], all client disparities: [0.009166666306555271, 0.11903393268585205], all client accs: [0.5980629324913025, 0.6110105514526367],  alpha_performance: tensor([0.6664, 0.3336], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:33,657 - utils - INFO - stage1_gradient_single_runtime: 0.0021970272064208984
2023-09-28 23:25:33,658 - utils - INFO -  epoch: 632, all client loss: [0.6428272724151611, 0.6559566259384155], all pred client disparities: [0.020398860797286034, 0.11169254779815674], all client disparities: [0.009166666306555271, 0.11842870712280273], all client accs: [0.5980629324913025, 0.6115537881851196],  alpha_performance: tensor([0.6663, 0.3337], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:33,711 - utils - INFO - stage1_gradient_single_runtime: 0.0028553009033203125
2023-09-28 23:25:33,713 - utils - INFO -  epoch: 633, all client loss: [0.6428542137145996, 0.655929684638977], all pred client disparities: [0.020368048921227455, 0.11167475581169128], all client disparities: [0.009166666306555271, 0.11868631839752197], all client accs: [0.5980629324913025, 0.6117348670959473],  alpha_performance: tensor([0.6662, 0.3338], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:33,767 - utils - INFO - stage1_gradient_single_runtime: 0.0024755001068115234
2023-09-28 23:25:33,769 - utils - INFO -  epoch: 634, all client loss: [0.6428810954093933, 0.6559028029441833], all pred client disparities: [0.020337354391813278, 0.11165660619735718], all client disparities: [0.009166666306555271, 0.11971670389175415], all client accs: [0.5980629324913025, 0.612278163433075],  alpha_performance: tensor([0.6661, 0.3339], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:33,822 - utils - INFO - stage1_gradient_single_runtime: 0.0025262832641601562
2023-09-28 23:25:33,824 - utils - INFO -  epoch: 635, all client loss: [0.6429080367088318, 0.6558759808540344], all pred client disparities: [0.020306773483753204, 0.11163830757141113], all client disparities: [0.009166666306555271, 0.11885389685630798], all client accs: [0.5980629324913025, 0.6124593019485474],  alpha_performance: tensor([0.6660, 0.3340], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:33,873 - utils - INFO - stage1_gradient_single_runtime: 0.002680540084838867
2023-09-28 23:25:33,874 - utils - INFO -  epoch: 636, all client loss: [0.6429348587989807, 0.6558492183685303], all pred client disparities: [0.020276308059692383, 0.1116197258234024], all client disparities: [0.009166666306555271, 0.11868008971214294], all client accs: [0.5980629324913025, 0.6124593019485474],  alpha_performance: tensor([0.6659, 0.3341], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:33,928 - utils - INFO - stage1_gradient_single_runtime: 0.002166271209716797
2023-09-28 23:25:33,929 - utils - INFO -  epoch: 637, all client loss: [0.6429616808891296, 0.6558223366737366], all pred client disparities: [0.020245954394340515, 0.11160089075565338], all client disparities: [0.009166666306555271, 0.1185062974691391], all client accs: [0.5980629324913025, 0.6124593019485474],  alpha_performance: tensor([0.6658, 0.3342], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:34,031 - utils - INFO - stage1_gradient_single_runtime: 0.0022034645080566406
2023-09-28 23:25:34,032 - utils - INFO -  epoch: 638, all client loss: [0.6429885625839233, 0.6557956337928772], all pred client disparities: [0.020215725526213646, 0.11158178746700287], all client disparities: [0.009166666306555271, 0.11833247542381287], all client accs: [0.5980629324913025, 0.6128214597702026],  alpha_performance: tensor([0.6657, 0.3343], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:34,084 - utils - INFO - stage1_gradient_single_runtime: 0.0022530555725097656
2023-09-28 23:25:34,085 - utils - INFO -  epoch: 639, all client loss: [0.6430152654647827, 0.655768871307373], all pred client disparities: [0.02018561214208603, 0.11156247556209564], all client disparities: [0.009166666306555271, 0.11790107190608978], all client accs: [0.5980629324913025, 0.6124593019485474],  alpha_performance: tensor([0.6656, 0.3344], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:34,105 - utils - INFO - valid: True, epoch: 639, loss: [0.6368111968040466, 0.6611887812614441], accuracy: [0.6143999695777893, 0.5999999642372131], mean_accuracy:0.6071999669075012,variance_accuracy:0.007200002670288086, disparity: [0.007092198356986046, 0.11866852641105652], mean_disparity:0.06288036238402128,variance_disparity:0.055788164027035236, pred_disparity: [0.019057346507906914, 0.1217845231294632]
2023-09-28 23:25:34,116 - utils - INFO - global_valid: True, epoch: 639,  global_loss: 0.653570830821991, global_accuracy: 0.718609443777511,  global_disparity:0.09648643434047699, global_pred_disparity: 0.10172612965106964,
2023-09-28 23:25:34,165 - utils - INFO - stage1_gradient_single_runtime: 0.0025177001953125
2023-09-28 23:25:34,166 - utils - INFO -  epoch: 640, all client loss: [0.6430420279502869, 0.6557421684265137], all pred client disparities: [0.020155610516667366, 0.11154289543628693], all client disparities: [0.009166666306555271, 0.1174696683883667], all client accs: [0.5980629324913025, 0.6124593019485474],  alpha_performance: tensor([0.6655, 0.3345], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:34,224 - utils - INFO - stage1_gradient_single_runtime: 0.002247333526611328
2023-09-28 23:25:34,225 - utils - INFO -  epoch: 641, all client loss: [0.6430687308311462, 0.6557155251502991], all pred client disparities: [0.020125718787312508, 0.11152304708957672], all client disparities: [0.009166666306555271, 0.11703826487064362], all client accs: [0.5980629324913025, 0.612278163433075],  alpha_performance: tensor([0.6654, 0.3346], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:34,275 - utils - INFO - stage1_gradient_single_runtime: 0.0022041797637939453
2023-09-28 23:25:34,277 - utils - INFO -  epoch: 642, all client loss: [0.6430954337120056, 0.6556888818740845], all pred client disparities: [0.0200959462672472, 0.111503005027771], all client disparities: [0.009166666306555271, 0.11703826487064362], all client accs: [0.5980629324913025, 0.612278163433075],  alpha_performance: tensor([0.6653, 0.3347], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:34,329 - utils - INFO - stage1_gradient_single_runtime: 0.0028274059295654297
2023-09-28 23:25:34,330 - utils - INFO -  epoch: 643, all client loss: [0.643122136592865, 0.6556622385978699], all pred client disparities: [0.020066287368535995, 0.111482635140419], all client disparities: [0.009166666306555271, 0.11703826487064362], all client accs: [0.5980629324913025, 0.6120970845222473],  alpha_performance: tensor([0.6652, 0.3348], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:34,384 - utils - INFO - stage1_gradient_single_runtime: 0.0021903514862060547
2023-09-28 23:25:34,386 - utils - INFO -  epoch: 644, all client loss: [0.6431487798690796, 0.6556356549263], all pred client disparities: [0.020036738365888596, 0.1114620566368103], all client disparities: [0.009166666306555271, 0.11703826487064362], all client accs: [0.5980629324913025, 0.6119160056114197],  alpha_performance: tensor([0.6651, 0.3349], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:34,442 - utils - INFO - stage1_gradient_single_runtime: 0.002290010452270508
2023-09-28 23:25:34,443 - utils - INFO -  epoch: 645, all client loss: [0.6431753635406494, 0.655609130859375], all pred client disparities: [0.02000730112195015, 0.11144118010997772], all client disparities: [0.009166666306555271, 0.11729587614536285], all client accs: [0.5980629324913025, 0.6119160056114197],  alpha_performance: tensor([0.6650, 0.3350], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:34,493 - utils - INFO - stage1_gradient_single_runtime: 0.002190113067626953
2023-09-28 23:25:34,494 - utils - INFO -  epoch: 646, all client loss: [0.6432019472122192, 0.65558260679245], all pred client disparities: [0.019977977499365807, 0.11142005026340485], all client disparities: [0.009166666306555271, 0.1175534576177597], all client accs: [0.5980629324913025, 0.6119160056114197],  alpha_performance: tensor([0.6649, 0.3351], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:34,548 - utils - INFO - stage1_gradient_single_runtime: 0.0022165775299072266
2023-09-28 23:25:34,549 - utils - INFO -  epoch: 647, all client loss: [0.6432285308837891, 0.6555560827255249], all pred client disparities: [0.019948769360780716, 0.11139868199825287], all client disparities: [0.009166666306555271, 0.1175534576177597], all client accs: [0.5980629324913025, 0.6115537881851196],  alpha_performance: tensor([0.6648, 0.3352], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:34,603 - utils - INFO - stage1_gradient_single_runtime: 0.002147674560546875
2023-09-28 23:25:34,604 - utils - INFO -  epoch: 648, all client loss: [0.6432550549507141, 0.6555295586585999], all pred client disparities: [0.01991966925561428, 0.1113770455121994], all client disparities: [0.009166666306555271, 0.11669063568115234], all client accs: [0.5980629324913025, 0.611372709274292],  alpha_performance: tensor([0.6647, 0.3353], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:34,705 - utils - INFO - stage1_gradient_single_runtime: 0.0021982192993164062
2023-09-28 23:25:34,707 - utils - INFO -  epoch: 649, all client loss: [0.6432815790176392, 0.6555030941963196], all pred client disparities: [0.019890686497092247, 0.11135515570640564], all client disparities: [0.009166666306555271, 0.11625923216342926], all client accs: [0.5980629324913025, 0.6115537881851196],  alpha_performance: tensor([0.6646, 0.3354], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:34,757 - utils - INFO - stage1_gradient_single_runtime: 0.002259969711303711
2023-09-28 23:25:34,758 - utils - INFO -  epoch: 650, all client loss: [0.6433080434799194, 0.6554766893386841], all pred client disparities: [0.019861815497279167, 0.111332967877388], all client disparities: [0.009166666306555271, 0.11582782864570618], all client accs: [0.5980629324913025, 0.6117348670959473],  alpha_performance: tensor([0.6645, 0.3355], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:34,813 - utils - INFO - stage1_gradient_single_runtime: 0.002485990524291992
2023-09-28 23:25:34,814 - utils - INFO -  epoch: 651, all client loss: [0.6433345079421997, 0.6554502844810486], all pred client disparities: [0.019833052530884743, 0.11131057143211365], all client disparities: [0.009166666306555271, 0.11582782864570618], all client accs: [0.5980629324913025, 0.6117348670959473],  alpha_performance: tensor([0.6644, 0.3356], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:34,870 - utils - INFO - stage1_gradient_single_runtime: 0.002239227294921875
2023-09-28 23:25:34,870 - utils - INFO -  epoch: 652, all client loss: [0.6433608531951904, 0.6554239392280579], all pred client disparities: [0.019804401323199272, 0.11128787696361542], all client disparities: [0.009166666306555271, 0.1166006326675415], all client accs: [0.5980629324913025, 0.6120970845222473],  alpha_performance: tensor([0.6643, 0.3357], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:34,922 - utils - INFO - stage1_gradient_single_runtime: 0.002221345901489258
2023-09-28 23:25:34,923 - utils - INFO -  epoch: 653, all client loss: [0.6433872580528259, 0.6553975343704224], all pred client disparities: [0.019775858148932457, 0.1112649142742157], all client disparities: [0.009166666306555271, 0.11642684042453766], all client accs: [0.5980629324913025, 0.612278163433075],  alpha_performance: tensor([0.6642, 0.3358], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:34,973 - utils - INFO - stage1_gradient_single_runtime: 0.0022301673889160156
2023-09-28 23:25:34,975 - utils - INFO -  epoch: 654, all client loss: [0.6434136033058167, 0.6553712487220764], all pred client disparities: [0.019747428596019745, 0.1112416535615921], all client disparities: [0.009166666306555271, 0.11642684042453766], all client accs: [0.5980629324913025, 0.6120970845222473],  alpha_performance: tensor([0.6641, 0.3359], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:35,028 - utils - INFO - stage1_gradient_single_runtime: 0.00251007080078125
2023-09-28 23:25:35,030 - utils - INFO -  epoch: 655, all client loss: [0.6434400081634521, 0.6553449630737305], all pred client disparities: [0.019719108939170837, 0.1112181693315506], all client disparities: [0.009166666306555271, 0.11668442189693451], all client accs: [0.5980629324913025, 0.612278163433075],  alpha_performance: tensor([0.6640, 0.3360], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:35,082 - utils - INFO - stage1_gradient_single_runtime: 0.0025217533111572266
2023-09-28 23:25:35,083 - utils - INFO -  epoch: 656, all client loss: [0.6434662938117981, 0.6553186774253845], all pred client disparities: [0.019690902903676033, 0.11119438707828522], all client disparities: [0.009166666306555271, 0.11694203317165375], all client accs: [0.5980629324913025, 0.6124593019485474],  alpha_performance: tensor([0.6639, 0.3361], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:35,139 - utils - INFO - stage1_gradient_single_runtime: 0.0022470951080322266
2023-09-28 23:25:35,140 - utils - INFO -  epoch: 657, all client loss: [0.643492579460144, 0.6552924513816833], all pred client disparities: [0.019662804901599884, 0.11117036640644073], all client disparities: [0.009166666306555271, 0.11719964444637299], all client accs: [0.5980629324913025, 0.612640380859375],  alpha_performance: tensor([0.6639, 0.3361], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:35,190 - utils - INFO - stage1_gradient_single_runtime: 0.002192258834838867
2023-09-28 23:25:35,191 - utils - INFO -  epoch: 658, all client loss: [0.64351886510849, 0.6552662253379822], all pred client disparities: [0.01963481493294239, 0.11114606261253357], all client disparities: [0.009166666306555271, 0.11745722591876984], all client accs: [0.5980629324913025, 0.612278163433075],  alpha_performance: tensor([0.6638, 0.3362], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:35,243 - utils - INFO - stage1_gradient_single_runtime: 0.0022106170654296875
2023-09-28 23:25:35,244 - utils - INFO -  epoch: 659, all client loss: [0.6435450911521912, 0.6552401185035706], all pred client disparities: [0.019606932997703552, 0.11112144589424133], all client disparities: [0.009166666306555271, 0.11771483719348907], all client accs: [0.5980629324913025, 0.6124593019485474],  alpha_performance: tensor([0.6637, 0.3363], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:35,264 - utils - INFO - valid: True, epoch: 659, loss: [0.6373220682144165, 0.6606249213218689], accuracy: [0.6128000020980835, 0.6029090881347656], mean_accuracy:0.6078545451164246,variance_accuracy:0.0049454569816589355, disparity: [0.003546099178493023, 0.1189647912979126], mean_disparity:0.06125544523820281,variance_disparity:0.05770934605970979, pred_disparity: [0.018532993271946907, 0.12085026502609253]
2023-09-28 23:25:35,275 - utils - INFO - global_valid: True, epoch: 659,  global_loss: 0.6533427834510803, global_accuracy: 0.7161924769907964,  global_disparity:0.09602031856775284, global_pred_disparity: 0.10101237893104553,
2023-09-28 23:25:35,327 - utils - INFO - stage1_gradient_single_runtime: 0.0022432804107666016
2023-09-28 23:25:35,328 - utils - INFO -  epoch: 660, all client loss: [0.6435712575912476, 0.6552139520645142], all pred client disparities: [0.019579164683818817, 0.11109660565853119], all client disparities: [0.009166666306555271, 0.11754100024700165], all client accs: [0.5980629324913025, 0.612640380859375],  alpha_performance: tensor([0.6636, 0.3364], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:35,380 - utils - INFO - stage1_gradient_single_runtime: 0.0022504329681396484
2023-09-28 23:25:35,381 - utils - INFO -  epoch: 661, all client loss: [0.643597424030304, 0.6551878452301025], all pred client disparities: [0.019551509991288185, 0.11107146739959717], all client disparities: [0.008333333767950535, 0.11762478947639465], all client accs: [0.5976594090461731, 0.6130025386810303],  alpha_performance: tensor([0.6635, 0.3365], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:35,431 - utils - INFO - stage1_gradient_single_runtime: 0.0021948814392089844
2023-09-28 23:25:35,433 - utils - INFO -  epoch: 662, all client loss: [0.6436235904693604, 0.6551617980003357], all pred client disparities: [0.019523967057466507, 0.11104604601860046], all client disparities: [0.008333333767950535, 0.11788240075111389], all client accs: [0.5976594090461731, 0.6130025386810303],  alpha_performance: tensor([0.6634, 0.3366], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:35,535 - utils - INFO - stage1_gradient_single_runtime: 0.0026636123657226562
2023-09-28 23:25:35,537 - utils - INFO -  epoch: 663, all client loss: [0.643649697303772, 0.6551356911659241], all pred client disparities: [0.019496526569128036, 0.11102035641670227], all client disparities: [0.008333333767950535, 0.11745099723339081], all client accs: [0.5976594090461731, 0.6130025386810303],  alpha_performance: tensor([0.6633, 0.3367], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:35,592 - utils - INFO - stage1_gradient_single_runtime: 0.0022711753845214844
2023-09-28 23:25:35,592 - utils - INFO -  epoch: 664, all client loss: [0.6436757445335388, 0.6551095843315125], all pred client disparities: [0.01946919597685337, 0.1109943836927414], all client disparities: [0.008333333767950535, 0.11770860850811005], all client accs: [0.5976594090461731, 0.6130025386810303],  alpha_performance: tensor([0.6632, 0.3368], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:35,645 - utils - INFO - stage1_gradient_single_runtime: 0.0025484561920166016
2023-09-28 23:25:35,645 - utils - INFO -  epoch: 665, all client loss: [0.6437018513679504, 0.6550836563110352], all pred client disparities: [0.01944197528064251, 0.11096814274787903], all client disparities: [0.008333333767950535, 0.11736099421977997], all client accs: [0.5976594090461731, 0.613545835018158],  alpha_performance: tensor([0.6632, 0.3368], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:35,695 - utils - INFO - stage1_gradient_single_runtime: 0.002218961715698242
2023-09-28 23:25:35,695 - utils - INFO -  epoch: 666, all client loss: [0.6437278985977173, 0.6550576686859131], all pred client disparities: [0.019414864480495453, 0.11094158887863159], all client disparities: [0.008333333767950535, 0.1181337982416153], all client accs: [0.5976594090461731, 0.6140891313552856],  alpha_performance: tensor([0.6631, 0.3369], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:35,750 - utils - INFO - stage1_gradient_single_runtime: 0.002209901809692383
2023-09-28 23:25:35,751 - utils - INFO -  epoch: 667, all client loss: [0.6437538862228394, 0.655031681060791], all pred client disparities: [0.01938786171376705, 0.11091479659080505], all client disparities: [0.008333333767950535, 0.11795996129512787], all client accs: [0.5976594090461731, 0.6142702102661133],  alpha_performance: tensor([0.6630, 0.3370], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:35,811 - utils - INFO - stage1_gradient_single_runtime: 0.0022902488708496094
2023-09-28 23:25:35,811 - utils - INFO -  epoch: 668, all client loss: [0.6437798142433167, 0.6550058126449585], all pred client disparities: [0.019360968843102455, 0.11088770627975464], all client disparities: [0.008333333767950535, 0.11804375052452087], all client accs: [0.5976594090461731, 0.6142702102661133],  alpha_performance: tensor([0.6629, 0.3371], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:35,861 - utils - INFO - stage1_gradient_single_runtime: 0.0022394657135009766
2023-09-28 23:25:35,862 - utils - INFO -  epoch: 669, all client loss: [0.6438058018684387, 0.6549798846244812], all pred client disparities: [0.019334185868501663, 0.11086030304431915], all client disparities: [0.008333333767950535, 0.11838515102863312], all client accs: [0.5976594090461731, 0.6146323680877686],  alpha_performance: tensor([0.6628, 0.3372], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:35,915 - utils - INFO - stage1_gradient_single_runtime: 0.002249479293823242
2023-09-28 23:25:35,917 - utils - INFO -  epoch: 670, all client loss: [0.643831729888916, 0.6549540162086487], all pred client disparities: [0.019307512789964676, 0.11083266139030457], all client disparities: [0.008333333767950535, 0.11846894025802612], all client accs: [0.5976594090461731, 0.6149945855140686],  alpha_performance: tensor([0.6627, 0.3373], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:35,969 - utils - INFO - stage1_gradient_single_runtime: 0.002526998519897461
2023-09-28 23:25:35,970 - utils - INFO -  epoch: 671, all client loss: [0.6438575983047485, 0.6549282073974609], all pred client disparities: [0.019280949607491493, 0.11080470681190491], all client disparities: [0.008333333767950535, 0.11872655153274536], all client accs: [0.5976594090461731, 0.614813506603241],  alpha_performance: tensor([0.6627, 0.3373], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:36,024 - utils - INFO - stage1_gradient_single_runtime: 0.002203702926635742
2023-09-28 23:25:36,024 - utils - INFO -  epoch: 672, all client loss: [0.643883466720581, 0.6549023985862732], all pred client disparities: [0.019254494458436966, 0.11077645421028137], all client disparities: [0.008333333767950535, 0.11975693702697754], all client accs: [0.5976594090461731, 0.6153568029403687],  alpha_performance: tensor([0.6626, 0.3374], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:36,073 - utils - INFO - stage1_gradient_single_runtime: 0.0022292137145996094
2023-09-28 23:25:36,074 - utils - INFO -  epoch: 673, all client loss: [0.6439092755317688, 0.6548765897750854], all pred client disparities: [0.019228145480155945, 0.11074791848659515], all client disparities: [0.008333333767950535, 0.12035594880580902], all client accs: [0.5976594090461731, 0.6159000396728516],  alpha_performance: tensor([0.6625, 0.3375], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:36,124 - utils - INFO - stage1_gradient_single_runtime: 0.002271890640258789
2023-09-28 23:25:36,125 - utils - INFO -  epoch: 674, all client loss: [0.6439350843429565, 0.6548509001731873], all pred client disparities: [0.019201908260583878, 0.11071908473968506], all client disparities: [0.008333333767950535, 0.11992453038692474], all client accs: [0.5976594090461731, 0.6159000396728516],  alpha_performance: tensor([0.6624, 0.3376], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:36,180 - utils - INFO - stage1_gradient_single_runtime: 0.0030450820922851562
2023-09-28 23:25:36,182 - utils - INFO -  epoch: 675, all client loss: [0.6439608931541443, 0.6548251509666443], all pred client disparities: [0.019175784662365913, 0.11068999767303467], all client disparities: [0.008333333767950535, 0.11931930482387543], all client accs: [0.5976594090461731, 0.6164433360099792],  alpha_performance: tensor([0.6624, 0.3376], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:36,282 - utils - INFO - stage1_gradient_single_runtime: 0.0022573471069335938
2023-09-28 23:25:36,284 - utils - INFO -  epoch: 676, all client loss: [0.6439865827560425, 0.6547994613647461], all pred client disparities: [0.019149765372276306, 0.1106605976819992], all client disparities: [0.008333333767950535, 0.11845649778842926], all client accs: [0.5976594090461731, 0.6166244149208069],  alpha_performance: tensor([0.6623, 0.3377], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:36,335 - utils - INFO - stage1_gradient_single_runtime: 0.002536296844482422
2023-09-28 23:25:36,335 - utils - INFO -  epoch: 677, all client loss: [0.6440123319625854, 0.6547737717628479], all pred client disparities: [0.019123852252960205, 0.11063089221715927], all client disparities: [0.008333333767950535, 0.11845649778842926], all client accs: [0.5976594090461731, 0.6164433360099792],  alpha_performance: tensor([0.6622, 0.3378], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:36,388 - utils - INFO - stage1_gradient_single_runtime: 0.0025594234466552734
2023-09-28 23:25:36,389 - utils - INFO -  epoch: 678, all client loss: [0.6440379619598389, 0.6547481417655945], all pred client disparities: [0.019098050892353058, 0.11060093343257904], all client disparities: [0.008333333767950535, 0.1187141090631485], all client accs: [0.5976594090461731, 0.6162622570991516],  alpha_performance: tensor([0.6621, 0.3379], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:36,450 - utils - INFO - stage1_gradient_single_runtime: 0.0025119781494140625
2023-09-28 23:25:36,452 - utils - INFO -  epoch: 679, all client loss: [0.6440635919570923, 0.6547225713729858], all pred client disparities: [0.019072359427809715, 0.11057060956954956], all client disparities: [0.008333333767950535, 0.11828269064426422], all client accs: [0.5976594090461731, 0.6162622570991516],  alpha_performance: tensor([0.6620, 0.3380], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:36,469 - utils - INFO - valid: True, epoch: 679, loss: [0.6378260850906372, 0.6600686311721802], accuracy: [0.6128000020980835, 0.6072726845741272], mean_accuracy:0.6100363433361053,variance_accuracy:0.0027636587619781494, disparity: [0.003546099178493023, 0.12136632204055786], mean_disparity:0.06245621060952544,variance_disparity:0.05891011143103242, pred_disparity: [0.018051236867904663, 0.11987484991550446]
2023-09-28 23:25:36,482 - utils - INFO - global_valid: True, epoch: 679,  global_loss: 0.6531179547309875, global_accuracy: 0.7137334933973589,  global_disparity:0.09798925369977951, global_pred_disparity: 0.10028047114610672,
2023-09-28 23:25:36,528 - utils - INFO - stage1_gradient_single_runtime: 0.002294301986694336
2023-09-28 23:25:36,529 - utils - INFO -  epoch: 680, all client loss: [0.6440892815589905, 0.6546970009803772], all pred client disparities: [0.019046775996685028, 0.11054006218910217], all client disparities: [0.008333333767950535, 0.11767749488353729], all client accs: [0.5976594090461731, 0.6164433360099792],  alpha_performance: tensor([0.6620, 0.3380], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:36,579 - utils - INFO - stage1_gradient_single_runtime: 0.0025649070739746094
2023-09-28 23:25:36,581 - utils - INFO -  epoch: 681, all client loss: [0.6441148519515991, 0.6546714901924133], all pred client disparities: [0.019021306186914444, 0.11050918698310852], all client disparities: [0.008333333767950535, 0.11707226932048798], all client accs: [0.5976594090461731, 0.6168055534362793],  alpha_performance: tensor([0.6619, 0.3381], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:36,633 - utils - INFO - stage1_gradient_single_runtime: 0.0022668838500976562
2023-09-28 23:25:36,634 - utils - INFO -  epoch: 682, all client loss: [0.644140362739563, 0.6546459794044495], all pred client disparities: [0.018995944410562515, 0.11047802120447159], all client disparities: [0.008333333767950535, 0.1167246401309967], all client accs: [0.5976594090461731, 0.6173487901687622],  alpha_performance: tensor([0.6618, 0.3382], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:36,690 - utils - INFO - stage1_gradient_single_runtime: 0.002146005630493164
2023-09-28 23:25:36,691 - utils - INFO -  epoch: 683, all client loss: [0.6441659331321716, 0.6546205282211304], all pred client disparities: [0.01897069253027439, 0.11044655740261078], all client disparities: [0.008333333767950535, 0.1167246401309967], all client accs: [0.5976594090461731, 0.6171677112579346],  alpha_performance: tensor([0.6617, 0.3383], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:36,737 - utils - INFO - stage1_gradient_single_runtime: 0.0022482872009277344
2023-09-28 23:25:36,738 - utils - INFO -  epoch: 684, all client loss: [0.6441914439201355, 0.6545950770378113], all pred client disparities: [0.01894555240869522, 0.1104147881269455], all client disparities: [0.008333333767950535, 0.11698225140571594], all client accs: [0.5976594090461731, 0.6173487901687622],  alpha_performance: tensor([0.6617, 0.3383], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:36,783 - utils - INFO - stage1_gradient_single_runtime: 0.002203226089477539
2023-09-28 23:25:36,784 - utils - INFO -  epoch: 685, all client loss: [0.6442168951034546, 0.654569685459137], all pred client disparities: [0.018920522183179855, 0.11038275063037872], all client disparities: [0.008333333767950535, 0.11749744415283203], all client accs: [0.5976594090461731, 0.6173487901687622],  alpha_performance: tensor([0.6616, 0.3384], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:36,833 - utils - INFO - stage1_gradient_single_runtime: 0.0025806427001953125
2023-09-28 23:25:36,834 - utils - INFO -  epoch: 686, all client loss: [0.6442422866821289, 0.6545442342758179], all pred client disparities: [0.018895601853728294, 0.11035040020942688], all client disparities: [0.008333333767950535, 0.11732365190982819], all client accs: [0.5976594090461731, 0.6177110075950623],  alpha_performance: tensor([0.6615, 0.3385], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:36,930 - utils - INFO - stage1_gradient_single_runtime: 0.002193450927734375
2023-09-28 23:25:36,931 - utils - INFO -  epoch: 687, all client loss: [0.6442676782608032, 0.6545189023017883], all pred client disparities: [0.01887078955769539, 0.11031775176525116], all client disparities: [0.008333333767950535, 0.11671842634677887], all client accs: [0.5976594090461731, 0.6180731654167175],  alpha_performance: tensor([0.6615, 0.3385], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:36,978 - utils - INFO - stage1_gradient_single_runtime: 0.002242565155029297
2023-09-28 23:25:36,979 - utils - INFO -  epoch: 688, all client loss: [0.6442930102348328, 0.6544936299324036], all pred client disparities: [0.018846087157726288, 0.11028476059436798], all client disparities: [0.008333333767950535, 0.11585560441017151], all client accs: [0.5976594090461731, 0.6184353828430176],  alpha_performance: tensor([0.6614, 0.3386], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:37,028 - utils - INFO - stage1_gradient_single_runtime: 0.002538442611694336
2023-09-28 23:25:37,029 - utils - INFO -  epoch: 689, all client loss: [0.6443184018135071, 0.6544683575630188], all pred client disparities: [0.01882149837911129, 0.11025156080722809], all client disparities: [0.008333333767950535, 0.11619700491428375], all client accs: [0.5976594090461731, 0.6191597580909729],  alpha_performance: tensor([0.6613, 0.3387], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:37,075 - utils - INFO - stage1_gradient_single_runtime: 0.002241373062133789
2023-09-28 23:25:37,076 - utils - INFO -  epoch: 690, all client loss: [0.6443436741828918, 0.654443085193634], all pred client disparities: [0.018797017633914948, 0.11021794378757477], all client disparities: [0.008333333767950535, 0.11645461618900299], all client accs: [0.5976594090461731, 0.6193408370018005],  alpha_performance: tensor([0.6612, 0.3388], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:37,131 - utils - INFO - stage1_gradient_single_runtime: 0.0021610260009765625
2023-09-28 23:25:37,132 - utils - INFO -  epoch: 691, all client loss: [0.6443689465522766, 0.6544179320335388], all pred client disparities: [0.018772650510072708, 0.11018410325050354], all client disparities: [0.008333333767950535, 0.11671219766139984], all client accs: [0.5976594090461731, 0.6193408370018005],  alpha_performance: tensor([0.6612, 0.3388], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:37,185 - utils - INFO - stage1_gradient_single_runtime: 0.0021784305572509766
2023-09-28 23:25:37,187 - utils - INFO -  epoch: 692, all client loss: [0.6443941593170166, 0.6543927192687988], all pred client disparities: [0.018748391419649124, 0.11014993488788605], all client disparities: [0.008333333767950535, 0.11628079414367676], all client accs: [0.5976594090461731, 0.6195219159126282],  alpha_performance: tensor([0.6611, 0.3389], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:37,238 - utils - INFO - stage1_gradient_single_runtime: 0.0025434494018554688
2023-09-28 23:25:37,239 - utils - INFO -  epoch: 693, all client loss: [0.6444194316864014, 0.6543675661087036], all pred client disparities: [0.018724244087934494, 0.1101154237985611], all client disparities: [0.008333333767950535, 0.116538405418396], all client accs: [0.5976594090461731, 0.6191597580909729],  alpha_performance: tensor([0.6610, 0.3390], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:37,291 - utils - INFO - stage1_gradient_single_runtime: 0.0025682449340820312
2023-09-28 23:25:37,292 - utils - INFO -  epoch: 694, all client loss: [0.6444445252418518, 0.6543424129486084], all pred client disparities: [0.018700208514928818, 0.11008065938949585], all client disparities: [0.008333333767950535, 0.11610700190067291], all client accs: [0.5976594090461731, 0.6193408370018005],  alpha_performance: tensor([0.6610, 0.3390], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:37,345 - utils - INFO - stage1_gradient_single_runtime: 0.0023462772369384766
2023-09-28 23:25:37,347 - utils - INFO -  epoch: 695, all client loss: [0.644469678401947, 0.6543174386024475], all pred client disparities: [0.018676280975341797, 0.11004559695720673], all client disparities: [0.008333333767950535, 0.116622194647789], all client accs: [0.5976594090461731, 0.6186164617538452],  alpha_performance: tensor([0.6609, 0.3391], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:37,399 - utils - INFO - stage1_gradient_single_runtime: 0.0021491050720214844
2023-09-28 23:25:37,400 - utils - INFO -  epoch: 696, all client loss: [0.6444947719573975, 0.6542923450469971], all pred client disparities: [0.018652470782399178, 0.11001016199588776], all client disparities: [0.008333333767950535, 0.116622194647789], all client accs: [0.5976594090461731, 0.6182543039321899],  alpha_performance: tensor([0.6608, 0.3392], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:37,448 - utils - INFO - stage1_gradient_single_runtime: 0.002267122268676758
2023-09-28 23:25:37,450 - utils - INFO -  epoch: 697, all client loss: [0.6445198655128479, 0.6542673707008362], all pred client disparities: [0.018628770485520363, 0.10997447371482849], all client disparities: [0.008333333767950535, 0.11619079113006592], all client accs: [0.5976594090461731, 0.6184353828430176],  alpha_performance: tensor([0.6608, 0.3392], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:37,501 - utils - INFO - stage1_gradient_single_runtime: 0.0026674270629882812
2023-09-28 23:25:37,502 - utils - INFO -  epoch: 698, all client loss: [0.6445448994636536, 0.6542423367500305], all pred client disparities: [0.0186051856726408, 0.10993850231170654], all client disparities: [0.008333333767950535, 0.11644840240478516], all client accs: [0.5976594090461731, 0.6186164617538452],  alpha_performance: tensor([0.6607, 0.3393], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:37,550 - utils - INFO - stage1_gradient_single_runtime: 0.0022721290588378906
2023-09-28 23:25:37,550 - utils - INFO -  epoch: 699, all client loss: [0.6445698738098145, 0.6542174220085144], all pred client disparities: [0.018581707030534744, 0.10990215837955475], all client disparities: [0.008333333767950535, 0.1173049807548523], all client accs: [0.5976594090461731, 0.6195219159126282],  alpha_performance: tensor([0.6606, 0.3394], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:37,568 - utils - INFO - valid: True, epoch: 699, loss: [0.638322114944458, 0.6595214009284973], accuracy: [0.6128000020980835, 0.6130908727645874], mean_accuracy:0.6129454374313354,variance_accuracy:0.00014543533325195312, disparity: [0.003546099178493023, 0.12090623378753662], mean_disparity:0.06222616648301482,variance_disparity:0.0586800673045218, pred_disparity: [0.017612000927329063, 0.11885316669940948]
2023-09-28 23:25:37,578 - utils - INFO - global_valid: True, epoch: 699,  global_loss: 0.6528967618942261, global_accuracy: 0.7113080232092838,  global_disparity:0.09786871820688248, global_pred_disparity: 0.09952675551176071,
2023-09-28 23:25:37,677 - utils - INFO - stage1_gradient_single_runtime: 0.002590656280517578
2023-09-28 23:25:37,679 - utils - INFO -  epoch: 700, all client loss: [0.6445948481559753, 0.6541925072669983], all pred client disparities: [0.01855834200978279, 0.10986553132534027], all client disparities: [0.008333333767950535, 0.11756256222724915], all client accs: [0.5976594090461731, 0.6191597580909729],  alpha_performance: tensor([0.6606, 0.3394], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:37,728 - utils - INFO - stage1_gradient_single_runtime: 0.002209186553955078
2023-09-28 23:25:37,730 - utils - INFO -  epoch: 701, all client loss: [0.6446197628974915, 0.654167652130127], all pred client disparities: [0.01853509061038494, 0.10982862114906311], all client disparities: [0.008333333767950535, 0.11756256222724915], all client accs: [0.5976594090461731, 0.6186164617538452],  alpha_performance: tensor([0.6605, 0.3395], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:37,782 - utils - INFO - stage1_gradient_single_runtime: 0.002277374267578125
2023-09-28 23:25:37,783 - utils - INFO -  epoch: 702, all client loss: [0.6446446180343628, 0.6541427969932556], all pred client disparities: [0.018511950969696045, 0.10979138314723969], all client disparities: [0.008333333767950535, 0.11790396273136139], all client accs: [0.5976594090461731, 0.6189786195755005],  alpha_performance: tensor([0.6605, 0.3395], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:37,842 - utils - INFO - stage1_gradient_single_runtime: 0.0021789073944091797
2023-09-28 23:25:37,844 - utils - INFO -  epoch: 703, all client loss: [0.6446694731712341, 0.6541180610656738], all pred client disparities: [0.018488924950361252, 0.10975383222103119], all client disparities: [0.008333333767950535, 0.11729876697063446], all client accs: [0.5976594090461731, 0.6191597580909729],  alpha_performance: tensor([0.6604, 0.3396], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:37,894 - utils - INFO - stage1_gradient_single_runtime: 0.0021829605102539062
2023-09-28 23:25:37,895 - utils - INFO -  epoch: 704, all client loss: [0.6446942687034607, 0.654093325138092], all pred client disparities: [0.01846601441502571, 0.10971596837043762], all client disparities: [0.008333333767950535, 0.11781395971775055], all client accs: [0.5976594090461731, 0.6193408370018005],  alpha_performance: tensor([0.6603, 0.3397], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:37,947 - utils - INFO - stage1_gradient_single_runtime: 0.0024335384368896484
2023-09-28 23:25:37,948 - utils - INFO -  epoch: 705, all client loss: [0.6447190642356873, 0.6540685892105103], all pred client disparities: [0.018443215638399124, 0.1096777692437172], all client disparities: [0.008333333767950535, 0.11832915246486664], all client accs: [0.5976594090461731, 0.6195219159126282],  alpha_performance: tensor([0.6603, 0.3397], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:37,998 - utils - INFO - stage1_gradient_single_runtime: 0.0023751258850097656
2023-09-28 23:25:37,999 - utils - INFO -  epoch: 706, all client loss: [0.6447438597679138, 0.6540439128875732], all pred client disparities: [0.01842053234577179, 0.10963928699493408], all client disparities: [0.007499999832361937, 0.11729253828525543], all client accs: [0.5972558259963989, 0.6198841333389282],  alpha_performance: tensor([0.6602, 0.3398], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:38,056 - utils - INFO - stage1_gradient_single_runtime: 0.0025691986083984375
2023-09-28 23:25:38,057 - utils - INFO -  epoch: 707, all client loss: [0.644768476486206, 0.6540192365646362], all pred client disparities: [0.018397964537143707, 0.10960053652524948], all client disparities: [0.007499999832361937, 0.11686113476753235], all client accs: [0.5972558259963989, 0.6198841333389282],  alpha_performance: tensor([0.6602, 0.3398], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:38,107 - utils - INFO - stage1_gradient_single_runtime: 0.0022280216217041016
2023-09-28 23:25:38,107 - utils - INFO -  epoch: 708, all client loss: [0.6447932124137878, 0.6539946794509888], all pred client disparities: [0.01837550476193428, 0.10956142842769623], all client disparities: [0.007499999832361937, 0.11694492399692535], all client accs: [0.5972558259963989, 0.6200652122497559],  alpha_performance: tensor([0.6601, 0.3399], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:38,161 - utils - INFO - stage1_gradient_single_runtime: 0.002576112747192383
2023-09-28 23:25:38,163 - utils - INFO -  epoch: 709, all client loss: [0.6448178291320801, 0.6539700627326965], all pred client disparities: [0.018353162333369255, 0.10952198505401611], all client disparities: [0.007499999832361937, 0.11746011674404144], all client accs: [0.5972558259963989, 0.6202462911605835],  alpha_performance: tensor([0.6600, 0.3400], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:38,214 - utils - INFO - stage1_gradient_single_runtime: 0.0025255680084228516
2023-09-28 23:25:38,215 - utils - INFO -  epoch: 710, all client loss: [0.6448423862457275, 0.6539455652236938], all pred client disparities: [0.01833094097673893, 0.1094822883605957], all client disparities: [0.007499999832361937, 0.11659729480743408], all client accs: [0.5972558259963989, 0.6202462911605835],  alpha_performance: tensor([0.6600, 0.3400], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:38,276 - utils - INFO - stage1_gradient_single_runtime: 0.0025310516357421875
2023-09-28 23:25:38,277 - utils - INFO -  epoch: 711, all client loss: [0.6448668837547302, 0.6539210677146912], all pred client disparities: [0.01830882392823696, 0.10944226384162903], all client disparities: [0.007499999832361937, 0.11642350256443024], all client accs: [0.5972558259963989, 0.6206085085868835],  alpha_performance: tensor([0.6599, 0.3401], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:38,391 - utils - INFO - stage1_gradient_single_runtime: 0.0023174285888671875
2023-09-28 23:25:38,393 - utils - INFO -  epoch: 712, all client loss: [0.6448914408683777, 0.6538965702056885], all pred client disparities: [0.01828683167695999, 0.10940183699131012], all client disparities: [0.007499999832361937, 0.116249680519104], all client accs: [0.5972558259963989, 0.6209706664085388],  alpha_performance: tensor([0.6599, 0.3401], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:38,441 - utils - INFO - stage1_gradient_single_runtime: 0.002166748046875
2023-09-28 23:25:38,442 - utils - INFO -  epoch: 713, all client loss: [0.6449158787727356, 0.6538721919059753], all pred client disparities: [0.018264947459101677, 0.10936121642589569], all client disparities: [0.007499999832361937, 0.11607588827610016], all client accs: [0.5972558259963989, 0.6211518049240112],  alpha_performance: tensor([0.6598, 0.3402], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:38,496 - utils - INFO - stage1_gradient_single_runtime: 0.002727031707763672
2023-09-28 23:25:38,496 - utils - INFO -  epoch: 714, all client loss: [0.6449403166770935, 0.6538478136062622], all pred client disparities: [0.018243182450532913, 0.10932020843029022], all client disparities: [0.007499999832361937, 0.11503924429416656], all client accs: [0.5972558259963989, 0.6216950416564941],  alpha_performance: tensor([0.6597, 0.3403], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:38,548 - utils - INFO - stage1_gradient_single_runtime: 0.002123594284057617
2023-09-28 23:25:38,549 - utils - INFO -  epoch: 715, all client loss: [0.6449646949768066, 0.6538234949111938], all pred client disparities: [0.018221532925963402, 0.10927894711494446], all client disparities: [0.007499999832361937, 0.11486545205116272], all client accs: [0.5972558259963989, 0.6218761205673218],  alpha_performance: tensor([0.6597, 0.3403], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:38,599 - utils - INFO - stage1_gradient_single_runtime: 0.002580404281616211
2023-09-28 23:25:38,600 - utils - INFO -  epoch: 716, all client loss: [0.6449890732765198, 0.653799295425415], all pred client disparities: [0.01820000261068344, 0.10923735797405243], all client disparities: [0.007499999832361937, 0.11512303352355957], all client accs: [0.5972558259963989, 0.6220572590827942],  alpha_performance: tensor([0.6596, 0.3404], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:38,651 - utils - INFO - stage1_gradient_single_runtime: 0.0021996498107910156
2023-09-28 23:25:38,652 - utils - INFO -  epoch: 717, all client loss: [0.6450133323669434, 0.6537750363349915], all pred client disparities: [0.018178587779402733, 0.10919541120529175], all client disparities: [0.007499999832361937, 0.11494924128055573], all client accs: [0.5972558259963989, 0.6224194169044495],  alpha_performance: tensor([0.6596, 0.3404], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:38,708 - utils - INFO - stage1_gradient_single_runtime: 0.0029947757720947266
2023-09-28 23:25:38,709 - utils - INFO -  epoch: 718, all client loss: [0.6450376510620117, 0.6537508368492126], all pred client disparities: [0.018157292157411575, 0.10915318131446838], all client disparities: [0.007499999832361937, 0.11408643424510956], all client accs: [0.5972558259963989, 0.6226005554199219],  alpha_performance: tensor([0.6595, 0.3405], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:38,765 - utils - INFO - stage1_gradient_single_runtime: 0.0022110939025878906
2023-09-28 23:25:38,766 - utils - INFO -  epoch: 719, all client loss: [0.6450617909431458, 0.6537266373634338], all pred client disparities: [0.01813611015677452, 0.10911062359809875], all client disparities: [0.007499999832361937, 0.11485923826694489], all client accs: [0.5972558259963989, 0.6226005554199219],  alpha_performance: tensor([0.6595, 0.3405], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:38,783 - utils - INFO - valid: True, epoch: 719, loss: [0.6388083100318909, 0.6589857339859009], accuracy: [0.6128000020980835, 0.614545464515686], mean_accuracy:0.6136727333068848,variance_accuracy:0.0008727312088012695, disparity: [0.003546099178493023, 0.12120252847671509], mean_disparity:0.062374313827604055,variance_disparity:0.05882821464911103, pred_disparity: [0.01721647009253502, 0.11777834594249725]
2023-09-28 23:25:38,796 - utils - INFO - global_valid: True, epoch: 719,  global_loss: 0.6526803374290466, global_accuracy: 0.7087815126050421,  global_disparity:0.0982142835855484, global_pred_disparity: 0.09874621033668518,
2023-09-28 23:25:38,843 - utils - INFO - stage1_gradient_single_runtime: 0.0022306442260742188
2023-09-28 23:25:38,844 - utils - INFO -  epoch: 720, all client loss: [0.6450859904289246, 0.6537025570869446], all pred client disparities: [0.018115047365427017, 0.10906782746315002], all client disparities: [0.006666666828095913, 0.11485923826694489], all client accs: [0.5968523025512695, 0.6226005554199219],  alpha_performance: tensor([0.6594, 0.3406], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:38,895 - utils - INFO - stage1_gradient_single_runtime: 0.002163410186767578
2023-09-28 23:25:38,896 - utils - INFO -  epoch: 721, all client loss: [0.6451101303100586, 0.6536784768104553], all pred client disparities: [0.018094100058078766, 0.10902461409568787], all client disparities: [0.006666666828095913, 0.11511681973934174], all client accs: [0.5968523025512695, 0.6226005554199219],  alpha_performance: tensor([0.6594, 0.3406], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:38,952 - utils - INFO - stage1_gradient_single_runtime: 0.002665281295776367
2023-09-28 23:25:38,954 - utils - INFO -  epoch: 722, all client loss: [0.6451342105865479, 0.6536544561386108], all pred client disparities: [0.018073271960020065, 0.1089811623096466], all client disparities: [0.006666666828095913, 0.11382259428501129], all client accs: [0.5968523025512695, 0.6226005554199219],  alpha_performance: tensor([0.6593, 0.3407], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:39,055 - utils - INFO - stage1_gradient_single_runtime: 0.0024271011352539062
2023-09-28 23:25:39,056 - utils - INFO -  epoch: 723, all client loss: [0.6451582312583923, 0.6536304354667664], all pred client disparities: [0.018052568659186363, 0.10893736779689789], all client disparities: [0.006666666828095913, 0.11295978724956512], all client accs: [0.5968523025512695, 0.6220572590827942],  alpha_performance: tensor([0.6593, 0.3407], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:39,108 - utils - INFO - stage1_gradient_single_runtime: 0.0021910667419433594
2023-09-28 23:25:39,108 - utils - INFO -  epoch: 724, all client loss: [0.6451822519302368, 0.6536065340042114], all pred client disparities: [0.018031980842351913, 0.10889329016208649], all client disparities: [0.006666666828095913, 0.11321739852428436], all client accs: [0.5968523025512695, 0.6216950416564941],  alpha_performance: tensor([0.6592, 0.3408], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:39,163 - utils - INFO - stage1_gradient_single_runtime: 0.0022132396697998047
2023-09-28 23:25:39,165 - utils - INFO -  epoch: 725, all client loss: [0.6452062129974365, 0.6535826325416565], all pred client disparities: [0.018011512234807014, 0.10884889960289001], all client disparities: [0.006666666828095913, 0.11373259127140045], all client accs: [0.5968523025512695, 0.6220572590827942],  alpha_performance: tensor([0.6592, 0.3408], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:39,220 - utils - INFO - stage1_gradient_single_runtime: 0.002165555953979492
2023-09-28 23:25:39,222 - utils - INFO -  epoch: 726, all client loss: [0.6452301144599915, 0.6535587906837463], all pred client disparities: [0.017991159111261368, 0.10880415141582489], all client disparities: [0.006666666828095913, 0.11450539529323578], all client accs: [0.5968523025512695, 0.6226005554199219],  alpha_performance: tensor([0.6591, 0.3409], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:39,274 - utils - INFO - stage1_gradient_single_runtime: 0.002402782440185547
2023-09-28 23:25:39,275 - utils - INFO -  epoch: 727, all client loss: [0.6452540159225464, 0.653535008430481], all pred client disparities: [0.01797093078494072, 0.10875910520553589], all client disparities: [0.006666666828095913, 0.11450539529323578], all client accs: [0.5968523025512695, 0.6224194169044495],  alpha_performance: tensor([0.6591, 0.3409], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:39,326 - utils - INFO - stage1_gradient_single_runtime: 0.002218484878540039
2023-09-28 23:25:39,327 - utils - INFO -  epoch: 728, all client loss: [0.6452777981758118, 0.6535112261772156], all pred client disparities: [0.017950821667909622, 0.10871374607086182], all client disparities: [0.006666666828095913, 0.1152781993150711], all client accs: [0.5968523025512695, 0.6226005554199219],  alpha_performance: tensor([0.6590, 0.3410], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:39,380 - utils - INFO - stage1_gradient_single_runtime: 0.002233743667602539
2023-09-28 23:25:39,381 - utils - INFO -  epoch: 729, all client loss: [0.6453015208244324, 0.6534875631332397], all pred client disparities: [0.017930831760168076, 0.10866810381412506], all client disparities: [0.006666666828095913, 0.11441537737846375], all client accs: [0.5968523025512695, 0.6227816343307495],  alpha_performance: tensor([0.6590, 0.3410], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:39,438 - utils - INFO - stage1_gradient_single_runtime: 0.0021643638610839844
2023-09-28 23:25:39,439 - utils - INFO -  epoch: 730, all client loss: [0.645325243473053, 0.6534638404846191], all pred client disparities: [0.01791095919907093, 0.10862214863300323], all client disparities: [0.006666666828095913, 0.11441537737846375], all client accs: [0.5968523025512695, 0.6226005554199219],  alpha_performance: tensor([0.6589, 0.3411], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:39,489 - utils - INFO - stage1_gradient_single_runtime: 0.0022611618041992188
2023-09-28 23:25:39,490 - utils - INFO -  epoch: 731, all client loss: [0.6453489065170288, 0.6534402966499329], all pred client disparities: [0.017891213297843933, 0.10857588052749634], all client disparities: [0.006666666828095913, 0.11424155533313751], all client accs: [0.5968523025512695, 0.6227816343307495],  alpha_performance: tensor([0.6589, 0.3411], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:39,541 - utils - INFO - stage1_gradient_single_runtime: 0.002222299575805664
2023-09-28 23:25:39,542 - utils - INFO -  epoch: 732, all client loss: [0.6453725695610046, 0.6534166932106018], all pred client disparities: [0.017871588468551636, 0.10852932929992676], all client disparities: [0.006666666828095913, 0.11381015181541443], all client accs: [0.5968523025512695, 0.6222383379936218],  alpha_performance: tensor([0.6588, 0.3412], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:39,595 - utils - INFO - stage1_gradient_single_runtime: 0.002557039260864258
2023-09-28 23:25:39,598 - utils - INFO -  epoch: 733, all client loss: [0.6453961133956909, 0.6533932089805603], all pred client disparities: [0.01785208098590374, 0.10848238319158554], all client disparities: [0.006666666828095913, 0.11406776309013367], all client accs: [0.5968523025512695, 0.6216950416564941],  alpha_performance: tensor([0.6588, 0.3412], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:39,652 - utils - INFO - stage1_gradient_single_runtime: 0.0021736621856689453
2023-09-28 23:25:39,653 - utils - INFO -  epoch: 734, all client loss: [0.645419716835022, 0.6533697247505188], all pred client disparities: [0.017832698300480843, 0.10843519866466522], all client disparities: [0.006666666828095913, 0.114840567111969], all client accs: [0.5968523025512695, 0.6211518049240112],  alpha_performance: tensor([0.6587, 0.3413], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:39,759 - utils - INFO - stage1_gradient_single_runtime: 0.0022535324096679688
2023-09-28 23:25:39,760 - utils - INFO -  epoch: 735, all client loss: [0.6454431414604187, 0.6533463001251221], all pred client disparities: [0.017813436686992645, 0.10838770866394043], all client disparities: [0.006666666828095913, 0.11509814858436584], all client accs: [0.5968523025512695, 0.6209706664085388],  alpha_performance: tensor([0.6587, 0.3413], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:39,813 - utils - INFO - stage1_gradient_single_runtime: 0.0024187564849853516
2023-09-28 23:25:39,815 - utils - INFO -  epoch: 736, all client loss: [0.6454666256904602, 0.6533229351043701], all pred client disparities: [0.017794299870729446, 0.10833987593650818], all client disparities: [0.006666666828095913, 0.11466674506664276], all client accs: [0.5968523025512695, 0.6211518049240112],  alpha_performance: tensor([0.6586, 0.3414], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:39,870 - utils - INFO - stage1_gradient_single_runtime: 0.002544879913330078
2023-09-28 23:25:39,872 - utils - INFO -  epoch: 737, all client loss: [0.6454899907112122, 0.6532996296882629], all pred client disparities: [0.017775285989046097, 0.10829174518585205], all client disparities: [0.006666666828095913, 0.11518196761608124], all client accs: [0.5968523025512695, 0.6211518049240112],  alpha_performance: tensor([0.6586, 0.3414], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:39,922 - utils - INFO - stage1_gradient_single_runtime: 0.0021638870239257812
2023-09-28 23:25:39,923 - utils - INFO -  epoch: 738, all client loss: [0.6455132961273193, 0.6532763242721558], all pred client disparities: [0.017756396904587746, 0.10824331641197205], all client disparities: [0.006666666828095913, 0.11500813066959381], all client accs: [0.5968523025512695, 0.6206085085868835],  alpha_performance: tensor([0.6585, 0.3415], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:39,977 - utils - INFO - stage1_gradient_single_runtime: 0.00226593017578125
2023-09-28 23:25:39,977 - utils - INFO -  epoch: 739, all client loss: [0.6455365419387817, 0.6532531380653381], all pred client disparities: [0.017737632617354393, 0.10819460451602936], all client disparities: [0.006666666828095913, 0.11526574194431305], all client accs: [0.5968523025512695, 0.6202462911605835],  alpha_performance: tensor([0.6585, 0.3415], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:39,995 - utils - INFO - valid: True, epoch: 739, loss: [0.6392819285392761, 0.6584648489952087], accuracy: [0.6128000020980835, 0.6138181686401367], mean_accuracy:0.6133090853691101,variance_accuracy:0.0005090832710266113, disparity: [0.003546099178493023, 0.11502964794635773], mean_disparity:0.059287873562425375,variance_disparity:0.05574177438393235, pred_disparity: [0.01686670444905758, 0.11664292216300964]
2023-09-28 23:25:40,008 - utils - INFO - global_valid: True, epoch: 739,  global_loss: 0.6524702310562134, global_accuracy: 0.7061524609843938,  global_disparity:0.09364953637123108, global_pred_disparity: 0.09793341159820557,
2023-09-28 23:25:40,056 - utils - INFO - stage1_gradient_single_runtime: 0.002211332321166992
2023-09-28 23:25:40,057 - utils - INFO -  epoch: 740, all client loss: [0.6455597877502441, 0.6532299518585205], all pred client disparities: [0.01771899126470089, 0.10814562439918518], all client disparities: [0.006666666828095913, 0.11440293490886688], all client accs: [0.5968523025512695, 0.6202462911605835],  alpha_performance: tensor([0.6584, 0.3416], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:40,111 - utils - INFO - stage1_gradient_single_runtime: 0.0025091171264648438
2023-09-28 23:25:40,112 - utils - INFO -  epoch: 741, all client loss: [0.6455829739570618, 0.6532068848609924], all pred client disparities: [0.017700474709272385, 0.10809628665447235], all client disparities: [0.006666666828095913, 0.11466051638126373], all client accs: [0.5968523025512695, 0.6200652122497559],  alpha_performance: tensor([0.6584, 0.3416], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:40,161 - utils - INFO - stage1_gradient_single_runtime: 0.002160787582397461
2023-09-28 23:25:40,161 - utils - INFO -  epoch: 742, all client loss: [0.6456061005592346, 0.6531838178634644], all pred client disparities: [0.01768208108842373, 0.10804665088653564], all client disparities: [0.006666666828095913, 0.11466051638126373], all client accs: [0.5968523025512695, 0.6198841333389282],  alpha_performance: tensor([0.6583, 0.3417], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:40,212 - utils - INFO - stage1_gradient_single_runtime: 0.002304553985595703
2023-09-28 23:25:40,214 - utils - INFO -  epoch: 743, all client loss: [0.6456291675567627, 0.653160810470581], all pred client disparities: [0.01766381226480007, 0.10799671709537506], all client disparities: [0.006666666828095913, 0.11466051638126373], all client accs: [0.5968523025512695, 0.6198841333389282],  alpha_performance: tensor([0.6583, 0.3417], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:40,266 - utils - INFO - stage1_gradient_single_runtime: 0.002231597900390625
2023-09-28 23:25:40,267 - utils - INFO -  epoch: 744, all client loss: [0.6456521153450012, 0.6531378030776978], all pred client disparities: [0.017645670101046562, 0.10794645547866821], all client disparities: [0.006666666828095913, 0.11517573893070221], all client accs: [0.5968523025512695, 0.6198841333389282],  alpha_performance: tensor([0.6583, 0.3417], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:40,318 - utils - INFO - stage1_gradient_single_runtime: 0.0022857189178466797
2023-09-28 23:25:40,320 - utils - INFO -  epoch: 745, all client loss: [0.6456751823425293, 0.653114914894104], all pred client disparities: [0.01762765273451805, 0.10789591073989868], all client disparities: [0.006666666828095913, 0.11474433541297913], all client accs: [0.5968523025512695, 0.6200652122497559],  alpha_performance: tensor([0.6582, 0.3418], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:40,370 - utils - INFO - stage1_gradient_single_runtime: 0.0021753311157226562
2023-09-28 23:25:40,372 - utils - INFO -  epoch: 746, all client loss: [0.645698070526123, 0.653092086315155], all pred client disparities: [0.017609763890504837, 0.10784508287906647], all client disparities: [0.006666666828095913, 0.11474433541297913], all client accs: [0.5968523025512695, 0.6198841333389282],  alpha_performance: tensor([0.6582, 0.3418], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:40,475 - utils - INFO - stage1_gradient_single_runtime: 0.0021970272064208984
2023-09-28 23:25:40,476 - utils - INFO -  epoch: 747, all client loss: [0.645720899105072, 0.6530693173408508], all pred client disparities: [0.017591997981071472, 0.10779394209384918], all client disparities: [0.005833333358168602, 0.11482812464237213], all client accs: [0.5964487195014954, 0.6198841333389282],  alpha_performance: tensor([0.6581, 0.3419], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:40,530 - utils - INFO - stage1_gradient_single_runtime: 0.0025548934936523438
2023-09-28 23:25:40,531 - utils - INFO -  epoch: 748, all client loss: [0.6457436680793762, 0.6530466079711914], all pred client disparities: [0.017574358731508255, 0.10774248838424683], all client disparities: [0.005833333358168602, 0.11439670622348785], all client accs: [0.5964487195014954, 0.6193408370018005],  alpha_performance: tensor([0.6581, 0.3419], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:40,582 - utils - INFO - stage1_gradient_single_runtime: 0.002195119857788086
2023-09-28 23:25:40,583 - utils - INFO -  epoch: 749, all client loss: [0.6457664370536804, 0.6530239582061768], all pred client disparities: [0.017556842416524887, 0.10769078135490417], all client disparities: [0.005833333358168602, 0.1146542876958847], all client accs: [0.5964487195014954, 0.6193408370018005],  alpha_performance: tensor([0.6580, 0.3420], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:40,587 - utils - INFO - stage1_runtime: 45.246092081069946
2023-09-28 23:25:40,649 - utils - INFO - stage2_gradient_single_runtime: 0.007122993469238281
2023-09-28 23:25:40,654 - utils - INFO - 1, epoch: 750, all client loss: [0.6457890868186951, 0.6530013680458069], all pred client disparities: [0.017539456486701965, 0.10763871669769287], all client disparities: [0.005833333358168602, 0.11473807692527771], all client accs: [0.5964487195014954, 0.6197030544281006],  alphas:tensor([0.0463, 0.0000, 0.4689, 0.4847], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:40,718 - utils - INFO - stage2_gradient_single_runtime: 0.006214618682861328
2023-09-28 23:25:40,723 - utils - INFO - 1, epoch: 751, all client loss: [0.6478495597839355, 0.6550372838973999], all pred client disparities: [0.014677710831165314, 0.10267071425914764], all client disparities: [0.0016666667070239782, 0.1088133156299591], all client accs: [0.5944309830665588, 0.6153568029403687],  alphas:tensor([0.0468, 0.0000, 0.4747, 0.4785], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:40,786 - utils - INFO - stage2_gradient_single_runtime: 0.00619816780090332
2023-09-28 23:25:40,792 - utils - INFO - 1, epoch: 752, all client loss: [0.6497602462768555, 0.6569319367408752], all pred client disparities: [0.012352341786026955, 0.09799078106880188], all client disparities: [0.0016666667070239782, 0.10383512079715729], all client accs: [0.5944309830665588, 0.6106483340263367],  alphas:tensor([0.8212, 0.0000, 0.1788, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:40,857 - utils - INFO - stage2_gradient_single_runtime: 0.006308555603027344
2023-09-28 23:25:40,864 - utils - INFO - 1, epoch: 753, all client loss: [0.6513089537620544, 0.6585436463356018], all pred client disparities: [0.01067396905273199, 0.09400199353694916], all client disparities: [0.0016666667070239782, 0.10134917497634888], all client accs: [0.5944309830665588, 0.6068453788757324],  alphas:tensor([0.7072, 0.0000, 0.2928, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:40,926 - utils - INFO - stage2_gradient_single_runtime: 0.006541728973388672
2023-09-28 23:25:40,934 - utils - INFO - 1, epoch: 754, all client loss: [0.6522741913795471, 0.6595551371574402], all pred client disparities: [0.009725211188197136, 0.09145015478134155], all client disparities: [0.0008333333535119891, 0.09894697368144989], all client accs: [0.5940274000167847, 0.6039478778839111],  alphas:tensor([0.6594, 0.0000, 0.3406, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:40,995 - utils - INFO - stage2_gradient_single_runtime: 0.006436586380004883
2023-09-28 23:25:41,002 - utils - INFO - 1, epoch: 755, all client loss: [0.6530067324638367, 0.6603272557258606], all pred client disparities: [0.009053260087966919, 0.08947211503982544], all client disparities: [0.0008333333535119891, 0.09688617289066315], all client accs: [0.5940274000167847, 0.6008692979812622],  alphas:tensor([0.6318, 0.0000, 0.3682, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:41,064 - utils - INFO - stage2_gradient_single_runtime: 0.006300926208496094
2023-09-28 23:25:41,070 - utils - INFO - 1, epoch: 756, all client loss: [0.6536141037940979, 0.6609703302383423], all pred client disparities: [0.008526947349309921, 0.08780275285243988], all client disparities: [0.0008333333535119891, 0.09301595389842987], all client accs: [0.5940274000167847, 0.5992394089698792],  alphas:tensor([0.6132, 0.0000, 0.3868, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:41,131 - utils - INFO - stage2_gradient_single_runtime: 0.006360054016113281
2023-09-28 23:25:41,138 - utils - INFO - 1, epoch: 757, all client loss: [0.6541445255279541, 0.6615341305732727], all pred client disparities: [0.008089544251561165, 0.08632220327854156], all client disparities: [0.0008333333535119891, 0.09190179407596588], all client accs: [0.5940274000167847, 0.5976095795631409],  alphas:tensor([0.5996, 0.0000, 0.4004, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:41,198 - utils - INFO - stage2_gradient_single_runtime: 0.006130695343017578
2023-09-28 23:25:41,204 - utils - INFO - 1, epoch: 758, all client loss: [0.6546245217323303, 0.6620458960533142], all pred client disparities: [0.0077113318257033825, 0.08496490120887756], all client disparities: [0.0008333333535119891, 0.08915196359157562], all client accs: [0.5940274000167847, 0.5959797501564026],  alphas:tensor([0.5891, 0.0000, 0.4109, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:41,268 - utils - INFO - stage2_gradient_single_runtime: 0.00640106201171875
2023-09-28 23:25:41,274 - utils - INFO - 1, epoch: 759, all client loss: [0.6550701856613159, 0.6625221371650696], all pred client disparities: [0.007374823559075594, 0.08369076251983643], all client disparities: [0.0, 0.08863677084445953], all client accs: [0.5936238765716553, 0.5948931574821472],  alphas:tensor([0.5806, 0.0000, 0.4194, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:41,289 - utils - INFO - valid: True, epoch: 759, loss: [0.6481606960296631, 0.6671119928359985], accuracy: [0.6111999750137329, 0.5927272439002991], mean_accuracy:0.601963609457016,variance_accuracy:0.009236365556716919, disparity: [0.0, 0.09457999467849731], mean_disparity:0.04728999733924866,variance_disparity:0.04728999733924866, pred_disparity: [0.006712889298796654, 0.09257884323596954]
2023-09-28 23:25:41,300 - utils - INFO - global_valid: True, epoch: 759,  global_loss: 0.6611897349357605, global_accuracy: 0.6814825930372149,  global_disparity:0.07703003287315369, global_pred_disparity: 0.0772102028131485,
2023-09-28 23:25:41,410 - utils - INFO - stage2_gradient_single_runtime: 0.006133079528808594
2023-09-28 23:25:41,417 - utils - INFO - 1, epoch: 760, all client loss: [0.6554922461509705, 0.662973940372467], all pred client disparities: [0.007068878039717674, 0.08247299492359161], all client disparities: [0.0, 0.08640217781066895], all client accs: [0.5936238765716553, 0.5921767950057983],  alphas:tensor([0.5736, 0.0000, 0.4264, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:41,477 - utils - INFO - stage2_gradient_single_runtime: 0.006217241287231445
2023-09-28 23:25:41,482 - utils - INFO - 1, epoch: 761, all client loss: [0.6558982133865356, 0.6634091734886169], all pred client disparities: [0.006785975769162178, 0.08129258453845978], all client disparities: [0.0, 0.08494038879871368], all client accs: [0.5936238765716553, 0.5907280445098877],  alphas:tensor([0.5676, 0.0000, 0.4324, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:41,544 - utils - INFO - stage2_gradient_single_runtime: 0.00605010986328125
2023-09-28 23:25:41,549 - utils - INFO - 1, epoch: 762, all client loss: [0.6562937498092651, 0.6638334393501282], all pred client disparities: [0.006520826835185289, 0.08013537526130676], all client disparities: [0.0, 0.08261574804782867], all client accs: [0.5936238765716553, 0.5903658270835876],  alphas:tensor([0.5624, 0.0000, 0.4376, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:41,616 - utils - INFO - stage2_gradient_single_runtime: 0.006357431411743164
2023-09-28 23:25:41,622 - utils - INFO - 1, epoch: 763, all client loss: [0.6566832065582275, 0.6642515063285828], all pred client disparities: [0.006269583944231272, 0.07899026572704315], all client disparities: [0.0, 0.08184297382831573], all client accs: [0.5936238765716553, 0.5887359976768494],  alphas:tensor([0.5579, 0.0000, 0.4421, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:41,682 - utils - INFO - stage2_gradient_single_runtime: 0.006247520446777344
2023-09-28 23:25:41,688 - utils - INFO - 1, epoch: 764, all client loss: [0.6570701599121094, 0.6646668910980225], all pred client disparities: [0.006029379554092884, 0.07784834504127502], all client disparities: [0.0, 0.08081255853176117], all client accs: [0.5936238765716553, 0.5874683260917664],  alphas:tensor([0.5538, 0.0000, 0.4462, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:41,750 - utils - INFO - stage2_gradient_single_runtime: 0.006279945373535156
2023-09-28 23:25:41,756 - utils - INFO - 1, epoch: 765, all client loss: [0.6574574708938599, 0.6650826930999756], all pred client disparities: [0.00579804228618741, 0.07670216262340546], all client disparities: [0.0, 0.07926076650619507], all client accs: [0.5936238765716553, 0.5872872471809387],  alphas:tensor([0.5502, 0.0000, 0.4498, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:41,818 - utils - INFO - stage2_gradient_single_runtime: 0.0063076019287109375
2023-09-28 23:25:41,825 - utils - INFO - 1, epoch: 766, all client loss: [0.6578476428985596, 0.6655013561248779], all pred client disparities: [0.0055739134550094604, 0.0755452960729599], all client disparities: [0.0, 0.07848796248435974], all client accs: [0.5936238765716553, 0.586743950843811],  alphas:tensor([0.5469, 0.0000, 0.4531, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:41,884 - utils - INFO - stage2_gradient_single_runtime: 0.006188631057739258
2023-09-28 23:25:41,889 - utils - INFO - 1, epoch: 767, all client loss: [0.6582427024841309, 0.6659253835678101], all pred client disparities: [0.005355719942599535, 0.07437212765216827], all client disparities: [0.0, 0.07693612575531006], all client accs: [0.5936238765716553, 0.5865628719329834],  alphas:tensor([0.5439, 0.0000, 0.4561, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:41,952 - utils - INFO - stage2_gradient_single_runtime: 0.00632023811340332
2023-09-28 23:25:41,959 - utils - INFO - 1, epoch: 768, all client loss: [0.6586447954177856, 0.6663565039634705], all pred client disparities: [0.005142490845173597, 0.07317766547203064], all client disparities: [0.0, 0.07650472223758698], all client accs: [0.5936238765716553, 0.585476279258728],  alphas:tensor([0.5412, 0.0000, 0.4588, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:42,022 - utils - INFO - stage2_gradient_single_runtime: 0.006600379943847656
2023-09-28 23:25:42,029 - utils - INFO - 1, epoch: 769, all client loss: [0.6590554118156433, 0.6667965650558472], all pred client disparities: [0.004933497402817011, 0.07195748388767242], all client disparities: [0.0, 0.07435391843318939], all client accs: [0.5936238765716553, 0.5845708250999451],  alphas:tensor([0.5387, 0.0000, 0.4613, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:42,092 - utils - INFO - stage2_gradient_single_runtime: 0.0063190460205078125
2023-09-28 23:25:42,098 - utils - INFO - 1, epoch: 770, all client loss: [0.6594761610031128, 0.6672472953796387], all pred client disparities: [0.0047282082960009575, 0.07070738077163696], all client disparities: [0.0, 0.07263451814651489], all client accs: [0.5936238765716553, 0.5823976993560791],  alphas:tensor([0.5364, 0.0000, 0.4636, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:42,161 - utils - INFO - stage2_gradient_single_runtime: 0.006474018096923828
2023-09-28 23:25:42,168 - utils - INFO - 1, epoch: 771, all client loss: [0.6599084734916687, 0.6677101850509644], all pred client disparities: [0.004526258911937475, 0.06942369043827057], all client disparities: [0.0, 0.07143032550811768], all client accs: [0.5936238765716553, 0.5816733241081238],  alphas:tensor([0.5343, 0.0000, 0.4657, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:42,275 - utils - INFO - stage2_gradient_single_runtime: 0.00623011589050293
2023-09-28 23:25:42,282 - utils - INFO - 1, epoch: 772, all client loss: [0.6603535413742065, 0.6681864261627197], all pred client disparities: [0.0043274215422570705, 0.06810298562049866], all client disparities: [0.0, 0.07005229592323303], all client accs: [0.5936238765716553, 0.5813111066818237],  alphas:tensor([0.5324, 0.0000, 0.4676, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:42,340 - utils - INFO - stage2_gradient_single_runtime: 0.006402015686035156
2023-09-28 23:25:42,346 - utils - INFO - 1, epoch: 773, all client loss: [0.660812497138977, 0.6686773896217346], all pred client disparities: [0.004131588153541088, 0.06674216687679291], all client disparities: [0.0, 0.0693633109331131], all client accs: [0.5936238765716553, 0.5805867910385132],  alphas:tensor([0.5306, 0.0000, 0.4694, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:42,405 - utils - INFO - stage2_gradient_single_runtime: 0.006316423416137695
2023-09-28 23:25:42,409 - utils - INFO - 1, epoch: 774, all client loss: [0.6612864136695862, 0.6691840887069702], all pred client disparities: [0.003938750829547644, 0.06533844769001007], all client disparities: [0.0, 0.0682428777217865], all client accs: [0.5936238765716553, 0.5800434947013855],  alphas:tensor([0.5289, 0.0000, 0.4711, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:42,462 - utils - INFO - stage2_gradient_single_runtime: 0.006047725677490234
2023-09-28 23:25:42,466 - utils - INFO - 1, epoch: 775, all client loss: [0.661776065826416, 0.6697075963020325], all pred client disparities: [0.0037489798851311207, 0.06388935446739197], all client disparities: [0.0, 0.06402505934238434], all client accs: [0.5936238765716553, 0.5791380405426025],  alphas:tensor([0.5274, 0.0000, 0.4726, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:42,518 - utils - INFO - stage2_gradient_single_runtime: 0.00613856315612793
2023-09-28 23:25:42,522 - utils - INFO - 1, epoch: 776, all client loss: [0.6622822880744934, 0.6702486276626587], all pred client disparities: [0.0035624157171696424, 0.06239280104637146], all client disparities: [0.0, 0.06230565905570984], all client accs: [0.5936238765716553, 0.5773270726203918],  alphas:tensor([0.5260, 0.0000, 0.4740, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:42,574 - utils - INFO - stage2_gradient_single_runtime: 0.0062236785888671875
2023-09-28 23:25:42,578 - utils - INFO - 1, epoch: 777, all client loss: [0.6628056764602661, 0.6708080172538757], all pred client disparities: [0.0033792469184845686, 0.06084704399108887], all client disparities: [0.0, 0.06058625876903534], all client accs: [0.5936238765716553, 0.5760594010353088],  alphas:tensor([0.5247, 0.0000, 0.4753, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:42,630 - utils - INFO - stage2_gradient_single_runtime: 0.006070375442504883
2023-09-28 23:25:42,633 - utils - INFO - 1, epoch: 778, all client loss: [0.6633467078208923, 0.671386182308197], all pred client disparities: [0.0031996960751712322, 0.059250667691230774], all client disparities: [0.0, 0.05860303342342377], all client accs: [0.5936238765716553, 0.5753350257873535],  alphas:tensor([0.5236, 0.0000, 0.4764, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:42,692 - utils - INFO - stage2_gradient_single_runtime: 0.006357669830322266
2023-09-28 23:25:42,697 - utils - INFO - 1, epoch: 779, all client loss: [0.6639057397842407, 0.6719836592674255], all pred client disparities: [0.003024008823558688, 0.05760274827480316], all client disparities: [0.0, 0.05662603676319122], all client accs: [0.5936238765716553, 0.57334303855896],  alphas:tensor([0.5225, 0.0000, 0.4775, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:42,712 - utils - INFO - valid: True, epoch: 779, loss: [0.6562723517417908, 0.6756739616394043], accuracy: [0.6111999750137329, 0.5789090991020203], mean_accuracy:0.5950545370578766,variance_accuracy:0.016145437955856323, disparity: [0.0, 0.0674973726272583], mean_disparity:0.03374868631362915,variance_disparity:0.03374868631362915, pred_disparity: [0.0028636781498789787, 0.06683436036109924]
2023-09-28 23:25:42,725 - utils - INFO - global_valid: True, epoch: 779,  global_loss: 0.6696110367774963, global_accuracy: 0.6544437775110044,  global_disparity:0.05653691291809082, global_pred_disparity: 0.05673234164714813,
2023-09-28 23:25:42,786 - utils - INFO - stage2_gradient_single_runtime: 0.0062732696533203125
2023-09-28 23:25:42,789 - utils - INFO - 1, epoch: 780, all client loss: [0.6644829511642456, 0.6726006865501404], all pred client disparities: [0.002852433593943715, 0.05590265989303589], all client disparities: [0.0, 0.05550561845302582], all client accs: [0.5936238765716553, 0.5724375247955322],  alphas:tensor([0.5215, 0.0000, 0.4785, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:42,845 - utils - INFO - stage2_gradient_single_runtime: 0.00615382194519043
2023-09-28 23:25:42,848 - utils - INFO - 1, epoch: 781, all client loss: [0.6650782823562622, 0.6732373237609863], all pred client disparities: [0.002685210667550564, 0.0541502982378006], all client disparities: [0.0, 0.054217636585235596], all client accs: [0.5936238765716553, 0.5702643990516663],  alphas:tensor([0.5206, 0.0000, 0.4794, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:42,902 - utils - INFO - stage2_gradient_single_runtime: 0.006013154983520508
2023-09-28 23:25:42,907 - utils - INFO - 1, epoch: 782, all client loss: [0.6656917929649353, 0.6738935708999634], all pred client disparities: [0.002522562863305211, 0.05234590172767639], all client disparities: [0.0, 0.05223439633846283], all client accs: [0.5936238765716553, 0.5700833201408386],  alphas:tensor([0.5198, 0.0000, 0.4802, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:42,969 - utils - INFO - stage2_gradient_single_runtime: 0.00650787353515625
2023-09-28 23:25:42,974 - utils - INFO - 1, epoch: 783, all client loss: [0.6663231253623962, 0.674569308757782], all pred client disparities: [0.002364679705351591, 0.050490155816078186], all client disparities: [0.0, 0.05120401456952095], all client accs: [0.5936238765716553, 0.5682723522186279],  alphas:tensor([0.5190, 0.0000, 0.4810, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:43,080 - utils - INFO - stage2_gradient_single_runtime: 0.006128787994384766
2023-09-28 23:25:43,085 - utils - INFO - 1, epoch: 784, all client loss: [0.6669718027114868, 0.6752640604972839], all pred client disparities: [0.0022117120679467916, 0.04858414828777313], all client disparities: [0.0, 0.04965217411518097], all client accs: [0.5936238765716553, 0.567366898059845],  alphas:tensor([0.5184, 0.0000, 0.4816, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:43,142 - utils - INFO - stage2_gradient_single_runtime: 0.006020307540893555
2023-09-28 23:25:43,147 - utils - INFO - 1, epoch: 785, all client loss: [0.667637288570404, 0.6759774684906006], all pred client disparities: [0.002063766587525606, 0.04662942886352539], all client disparities: [0.0, 0.04896317422389984], all client accs: [0.5936238765716553, 0.5659181475639343],  alphas:tensor([0.5178, 0.0000, 0.4822, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:43,210 - utils - INFO - stage2_gradient_single_runtime: 0.006310224533081055
2023-09-28 23:25:43,215 - utils - INFO - 1, epoch: 786, all client loss: [0.668319046497345, 0.6767088770866394], all pred client disparities: [0.0019208985613659024, 0.04462778568267822], all client disparities: [0.0, 0.04629094898700714], all client accs: [0.5936238765716553, 0.5653748512268066],  alphas:tensor([0.5172, 0.0000, 0.4828, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:43,275 - utils - INFO - stage2_gradient_single_runtime: 0.006184577941894531
2023-09-28 23:25:43,282 - utils - INFO - 1, epoch: 787, all client loss: [0.6690161824226379, 0.6774575114250183], all pred client disparities: [0.001783112296834588, 0.0425814688205719], all client disparities: [0.0, 0.04336734116077423], all client accs: [0.5936238765716553, 0.5624773502349854],  alphas:tensor([0.5167, 0.0000, 0.4833, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:43,338 - utils - INFO - stage2_gradient_single_runtime: 0.007368803024291992
2023-09-28 23:25:43,343 - utils - INFO - 1, epoch: 788, all client loss: [0.6697278618812561, 0.6782225966453552], all pred client disparities: [0.0016503588994964957, 0.04049298167228699], all client disparities: [0.0, 0.04276835918426514], all client accs: [0.5936238765716553, 0.5601231455802917],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:43,404 - utils - INFO - stage2_gradient_single_runtime: 0.006479501724243164
2023-09-28 23:25:43,410 - utils - INFO - 1, epoch: 789, all client loss: [0.6639156937599182, 0.6722118258476257], all pred client disparities: [0.003068839432671666, 0.0556473582983017], all client disparities: [0.0, 0.056085944175720215], all client accs: [0.5936238765716553, 0.5726186037063599],  alphas:tensor([0.5222, 0.0000, 0.4778, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:43,470 - utils - INFO - stage2_gradient_single_runtime: 0.006241798400878906
2023-09-28 23:25:43,476 - utils - INFO - 1, epoch: 790, all client loss: [0.6645418405532837, 0.6728780269622803], all pred client disparities: [0.002880921121686697, 0.053795695304870605], all client disparities: [0.0, 0.0537613183259964], all client accs: [0.5936238765716553, 0.572075366973877],  alphas:tensor([0.5212, 0.0000, 0.4788, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:43,537 - utils - INFO - stage2_gradient_single_runtime: 0.006392478942871094
2023-09-28 23:25:43,544 - utils - INFO - 1, epoch: 791, all client loss: [0.6651875972747803, 0.6735655665397644], all pred client disparities: [0.00269824406132102, 0.05188716948032379], all client disparities: [0.0, 0.051784321665763855], all client accs: [0.5936238765716553, 0.5697211027145386],  alphas:tensor([0.5203, 0.0000, 0.4797, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:43,605 - utils - INFO - stage2_gradient_single_runtime: 0.006053447723388672
2023-09-28 23:25:43,610 - utils - INFO - 1, epoch: 792, all client loss: [0.6658527255058289, 0.6742742657661438], all pred client disparities: [0.0025210375897586346, 0.04992265999317169], all client disparities: [0.0, 0.04945969581604004], all client accs: [0.5936238765716553, 0.5688156485557556],  alphas:tensor([0.5195, 0.0000, 0.4805, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:43,667 - utils - INFO - stage2_gradient_single_runtime: 0.0062792301177978516
2023-09-28 23:25:43,672 - utils - INFO - 1, epoch: 793, all client loss: [0.6665368676185608, 0.6750038266181946], all pred client disparities: [0.0023494826164096594, 0.04790344834327698], all client disparities: [0.0, 0.04782409965991974], all client accs: [0.5936238765716553, 0.567729115486145],  alphas:tensor([0.5187, 0.0000, 0.4813, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:43,731 - utils - INFO - stage2_gradient_single_runtime: 0.0062291622161865234
2023-09-28 23:25:43,736 - utils - INFO - 1, epoch: 794, all client loss: [0.6672393679618835, 0.6757535338401794], all pred client disparities: [0.0021837102249264717, 0.04583124816417694], all client disparities: [0.0, 0.046188488602638245], all client accs: [0.5936238765716553, 0.5660992860794067],  alphas:tensor([0.5181, 0.0000, 0.4819, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:43,845 - utils - INFO - stage2_gradient_single_runtime: 0.006112575531005859
2023-09-28 23:25:43,851 - utils - INFO - 1, epoch: 795, all client loss: [0.6679593920707703, 0.6765229105949402], all pred client disparities: [0.0020237870048731565, 0.043708473443984985], all client disparities: [0.0, 0.04515810310840607], all client accs: [0.5936238765716553, 0.5632017850875854],  alphas:tensor([0.5175, 0.0000, 0.4825, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:43,911 - utils - INFO - stage2_gradient_single_runtime: 0.006185770034790039
2023-09-28 23:25:43,916 - utils - INFO - 1, epoch: 796, all client loss: [0.6686959266662598, 0.6773108243942261], all pred client disparities: [0.0018697165651246905, 0.04153759777545929], all client disparities: [0.0, 0.044642895460128784], all client accs: [0.5936238765716553, 0.5619341135025024],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:43,977 - utils - INFO - stage2_gradient_single_runtime: 0.00621795654296875
2023-09-28 23:25:43,983 - utils - INFO - 1, epoch: 797, all client loss: [0.662918746471405, 0.6713279485702515], all pred client disparities: [0.0034546961542218924, 0.05681516230106354], all client disparities: [0.0, 0.057954251766204834], all client accs: [0.5936238765716553, 0.5751539468765259],  alphas:tensor([0.5240, 0.0000, 0.4760, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:44,045 - utils - INFO - stage2_gradient_single_runtime: 0.006247043609619141
2023-09-28 23:25:44,051 - utils - INFO - 1, epoch: 798, all client loss: [0.663555920124054, 0.6720030307769775], all pred client disparities: [0.0032413029111921787, 0.05491925776004791], all client disparities: [0.0, 0.054599255323410034], all client accs: [0.5936238765716553, 0.5737051963806152],  alphas:tensor([0.5228, 0.0000, 0.4772, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:44,108 - utils - INFO - stage2_gradient_single_runtime: 0.006082296371459961
2023-09-28 23:25:44,115 - utils - INFO - 1, epoch: 799, all client loss: [0.6642143130302429, 0.6727011799812317], all pred client disparities: [0.003033580258488655, 0.0529620498418808], all client disparities: [0.0, 0.0528736412525177], all client accs: [0.5936238765716553, 0.5735241174697876],  alphas:tensor([0.5217, 0.0000, 0.4783, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:44,129 - utils - INFO - valid: True, epoch: 799, loss: [0.6567962765693665, 0.676226019859314], accuracy: [0.6111999750137329, 0.5796363353729248], mean_accuracy:0.5954181551933289,variance_accuracy:0.015781819820404053, disparity: [0.0, 0.06493204832077026], mean_disparity:0.03246602416038513,variance_disparity:0.03246602416038513, pred_disparity: [0.0028873097617179155, 0.06189243495464325]
2023-09-28 23:25:44,140 - utils - INFO - global_valid: True, epoch: 799,  global_loss: 0.6701542735099792, global_accuracy: 0.6486054421768707,  global_disparity:0.05479298532009125, global_pred_disparity: 0.05317990481853485,
2023-09-28 23:25:44,199 - utils - INFO - stage2_gradient_single_runtime: 0.006274700164794922
2023-09-28 23:25:44,205 - utils - INFO - 1, epoch: 800, all client loss: [0.6648936867713928, 0.6734221577644348], all pred client disparities: [0.0028318201657384634, 0.0509437620639801], all client disparities: [0.0, 0.05107042193412781], all client accs: [0.5936238765716553, 0.5711698532104492],  alphas:tensor([0.5207, 0.0000, 0.4793, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:44,266 - utils - INFO - stage2_gradient_single_runtime: 0.007272958755493164
2023-09-28 23:25:44,270 - utils - INFO - 1, epoch: 801, all client loss: [0.6655939221382141, 0.6741658449172974], all pred client disparities: [0.0026362764183431864, 0.04886539280414581], all client disparities: [0.0, 0.04960861802101135], all client accs: [0.5936238765716553, 0.568996787071228],  alphas:tensor([0.5198, 0.0000, 0.4802, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:44,324 - utils - INFO - stage2_gradient_single_runtime: 0.00603938102722168
2023-09-28 23:25:44,326 - utils - INFO - 1, epoch: 802, all client loss: [0.6663143634796143, 0.6749318838119507], all pred client disparities: [0.002447151578962803, 0.04672853648662567], all client disparities: [0.0, 0.04745781421661377], all client accs: [0.5936238765716553, 0.5675480365753174],  alphas:tensor([0.5190, 0.0000, 0.4810, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:44,379 - utils - INFO - stage2_gradient_single_runtime: 0.0062901973724365234
2023-09-28 23:25:44,382 - utils - INFO - 1, epoch: 803, all client loss: [0.6670543551445007, 0.6757194995880127], all pred client disparities: [0.0022645844146609306, 0.04453538358211517], all client disparities: [0.0, 0.0465112179517746], all client accs: [0.5936238765716553, 0.565555989742279],  alphas:tensor([0.5183, 0.0000, 0.4817, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:44,439 - utils - INFO - stage2_gradient_single_runtime: 0.006215333938598633
2023-09-28 23:25:44,441 - utils - INFO - 1, epoch: 804, all client loss: [0.6678129434585571, 0.6765278577804565], all pred client disparities: [0.0020886387210339308, 0.04228873550891876], all client disparities: [0.0, 0.042808592319488525], all client accs: [0.5936238765716553, 0.5641072392463684],  alphas:tensor([0.5177, 0.0000, 0.4823, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:44,500 - utils - INFO - stage2_gradient_single_runtime: 0.007047176361083984
2023-09-28 23:25:44,503 - utils - INFO - 1, epoch: 805, all client loss: [0.6685889363288879, 0.677355945110321], all pred client disparities: [0.001919300528243184, 0.03999185562133789], all client disparities: [0.0, 0.03918975591659546], all client accs: [0.5936238765716553, 0.5628395676612854],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:44,556 - utils - INFO - stage2_gradient_single_runtime: 0.006053924560546875
2023-09-28 23:25:44,558 - utils - INFO - 1, epoch: 806, all client loss: [0.662781834602356, 0.6713321208953857], all pred client disparities: [0.00357460486702621, 0.05554285645484924], all client disparities: [0.0, 0.05809696018695831], all client accs: [0.5936238765716553, 0.5773270726203918],  alphas:tensor([0.5243, 0.0000, 0.4757, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:44,612 - utils - INFO - stage2_gradient_single_runtime: 0.006490945816040039
2023-09-28 23:25:44,616 - utils - INFO - 1, epoch: 807, all client loss: [0.6634541749954224, 0.6720427870750427], all pred client disparities: [0.0033423907589167356, 0.053531959652900696], all client disparities: [0.0, 0.054915741086006165], all client accs: [0.5936238765716553, 0.5753350257873535],  alphas:tensor([0.5230, 0.0000, 0.4770, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:44,671 - utils - INFO - stage2_gradient_single_runtime: 0.006299018859863281
2023-09-28 23:25:44,675 - utils - INFO - 1, epoch: 808, all client loss: [0.6641489267349243, 0.6727778315544128], all pred client disparities: [0.0031166397966444492, 0.051455751061439514], all client disparities: [0.0, 0.052681148052215576], all client accs: [0.5936238765716553, 0.5729808211326599],  alphas:tensor([0.5219, 0.0000, 0.4781, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:44,778 - utils - INFO - stage2_gradient_single_runtime: 0.006124734878540039
2023-09-28 23:25:44,781 - utils - INFO - 1, epoch: 809, all client loss: [0.6648659110069275, 0.6735372543334961], all pred client disparities: [0.002897656988352537, 0.049314990639686584], all client disparities: [0.0, 0.05087172985076904], all client accs: [0.5936238765716553, 0.5726186037063599],  alphas:tensor([0.5208, 0.0000, 0.4792, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:44,839 - utils - INFO - stage2_gradient_single_runtime: 0.006489992141723633
2023-09-28 23:25:44,841 - utils - INFO - 1, epoch: 810, all client loss: [0.6656048893928528, 0.674320638179779], all pred client disparities: [0.0026857040356844664, 0.04711100459098816], all client disparities: [0.0, 0.047432929277420044], all client accs: [0.5936238765716553, 0.569902241230011],  alphas:tensor([0.5199, 0.0000, 0.4801, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:44,897 - utils - INFO - stage2_gradient_single_runtime: 0.006290435791015625
2023-09-28 23:25:44,899 - utils - INFO - 1, epoch: 811, all client loss: [0.6663650274276733, 0.6751274466514587], all pred client disparities: [0.0024809804745018482, 0.044845908880233765], all client disparities: [0.0, 0.04536589980125427], all client accs: [0.5936238765716553, 0.5688156485557556],  alphas:tensor([0.5191, 0.0000, 0.4809, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:44,960 - utils - INFO - stage2_gradient_single_runtime: 0.0068874359130859375
2023-09-28 23:25:44,965 - utils - INFO - 1, epoch: 812, all client loss: [0.6671453714370728, 0.6759567856788635], all pred client disparities: [0.002283603185787797, 0.04252256453037262], all client disparities: [0.0, 0.04123188555240631], all client accs: [0.5936238765716553, 0.5660992860794067],  alphas:tensor([0.5184, 0.0000, 0.4816, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:45,021 - utils - INFO - stage2_gradient_single_runtime: 0.005987882614135742
2023-09-28 23:25:45,026 - utils - INFO - 1, epoch: 813, all client loss: [0.6679449677467346, 0.676807701587677], all pred client disparities: [0.0020936017390340567, 0.040144458413124084], all client disparities: [0.0, 0.040201470255851746], all client accs: [0.5936238765716553, 0.5641072392463684],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:45,087 - utils - INFO - stage2_gradient_single_runtime: 0.0062389373779296875
2023-09-28 23:25:45,091 - utils - INFO - 1, epoch: 814, all client loss: [0.662149965763092, 0.6707885265350342], all pred client disparities: [0.0038923087995499372, 0.055847957730293274], all client disparities: [0.0, 0.058677271008491516], all client accs: [0.5936238765716553, 0.5791380405426025],  alphas:tensor([0.5259, 0.0000, 0.4741, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:45,151 - utils - INFO - stage2_gradient_single_runtime: 0.006125926971435547
2023-09-28 23:25:45,156 - utils - INFO - 1, epoch: 815, all client loss: [0.662836492061615, 0.6715126633644104], all pred client disparities: [0.003635791363194585, 0.05378183722496033], all client disparities: [0.0, 0.05670025944709778], all client accs: [0.5936238765716553, 0.5767837762832642],  alphas:tensor([0.5244, 0.0000, 0.4756, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:45,226 - utils - INFO - stage2_gradient_single_runtime: 0.006215810775756836
2023-09-28 23:25:45,232 - utils - INFO - 1, epoch: 816, all client loss: [0.6635465621948242, 0.6722623705863953], all pred client disparities: [0.0033862688578665257, 0.05164721608161926], all client disparities: [0.0, 0.05523847043514252], all client accs: [0.5936238765716553, 0.5755161046981812],  alphas:tensor([0.5231, 0.0000, 0.4769, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:45,293 - utils - INFO - stage2_gradient_single_runtime: 0.00604557991027832
2023-09-28 23:25:45,300 - utils - INFO - 1, epoch: 817, all client loss: [0.664280116558075, 0.6730377078056335], all pred client disparities: [0.0031440688762813807, 0.04944424331188202], all client disparities: [0.0, 0.05214105546474457], all client accs: [0.5936238765716553, 0.5729808211326599],  alphas:tensor([0.5219, 0.0000, 0.4781, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:45,362 - utils - INFO - stage2_gradient_single_runtime: 0.006418704986572266
2023-09-28 23:25:45,369 - utils - INFO - 1, epoch: 818, all client loss: [0.6650369763374329, 0.6738384366035461], all pred client disparities: [0.0029094929341226816, 0.04717397689819336], all client disparities: [0.0, 0.04861225187778473], all client accs: [0.5936238765716553, 0.5704455375671387],  alphas:tensor([0.5208, 0.0000, 0.4792, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:45,440 - utils - INFO - stage2_gradient_single_runtime: 0.006226778030395508
2023-09-28 23:25:45,446 - utils - INFO - 1, epoch: 819, all client loss: [0.6658164262771606, 0.6746641993522644], all pred client disparities: [0.0026827873662114143, 0.04483842849731445], all client disparities: [0.0, 0.04507717490196228], all client accs: [0.5936238765716553, 0.569902241230011],  alphas:tensor([0.5199, 0.0000, 0.4801, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:45,460 - utils - INFO - valid: True, epoch: 819, loss: [0.6585083603858948, 0.677954912185669], accuracy: [0.6111999750137329, 0.5687272548675537], mean_accuracy:0.5899636149406433,variance_accuracy:0.0212363600730896, disparity: [0.0, 0.05665390193462372], mean_disparity:0.02832695096731186,variance_disparity:0.02832695096731186, pred_disparity: [0.002578754909336567, 0.05347992479801178]
2023-09-28 23:25:45,471 - utils - INFO - global_valid: True, epoch: 819,  global_loss: 0.6718779802322388, global_accuracy: 0.6394907963185275,  global_disparity:0.04860486090183258, global_pred_disparity: 0.04690147936344147,
2023-09-28 23:25:45,532 - utils - INFO - stage2_gradient_single_runtime: 0.006052970886230469
2023-09-28 23:25:45,537 - utils - INFO - 1, epoch: 820, all client loss: [0.6666176915168762, 0.6755140423774719], all pred client disparities: [0.0024641158524900675, 0.042440593242645264], all client disparities: [0.0, 0.043273985385894775], all client accs: [0.5936238765716553, 0.5679101943969727],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:45,595 - utils - INFO - stage2_gradient_single_runtime: 0.006590127944946289
2023-09-28 23:25:45,601 - utils - INFO - 1, epoch: 821, all client loss: [0.6608867049217224, 0.6695556640625], all pred client disparities: [0.004516160115599632, 0.058145672082901], all client disparities: [0.0, 0.06347541511058807], all client accs: [0.5936238765716553, 0.5818544030189514],  alphas:tensor([0.5298, 0.0000, 0.4702, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:45,713 - utils - INFO - stage2_gradient_single_runtime: 0.0061113834381103516
2023-09-28 23:25:45,718 - utils - INFO - 1, epoch: 822, all client loss: [0.6615617275238037, 0.6702658534049988], all pred client disparities: [0.004227261524647474, 0.056099727749824524], all client disparities: [0.0, 0.06209741532802582], all client accs: [0.5936238765716553, 0.5804056525230408],  alphas:tensor([0.5278, 0.0000, 0.4722, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:45,778 - utils - INFO - stage2_gradient_single_runtime: 0.00588679313659668
2023-09-28 23:25:45,782 - utils - INFO - 1, epoch: 823, all client loss: [0.6622602939605713, 0.6710015535354614], all pred client disparities: [0.003945659380406141, 0.053984567523002625], all client disparities: [0.0, 0.058736175298690796], all client accs: [0.5936238765716553, 0.5796812772750854],  alphas:tensor([0.5260, 0.0000, 0.4740, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:45,843 - utils - INFO - stage2_gradient_single_runtime: 0.00657200813293457
2023-09-28 23:25:45,849 - utils - INFO - 1, epoch: 824, all client loss: [0.6629830598831177, 0.67176353931427], all pred client disparities: [0.0036716058384627104, 0.05179852247238159], all client disparities: [0.0, 0.05692675709724426], all client accs: [0.5936238765716553, 0.5784136056900024],  alphas:tensor([0.5245, 0.0000, 0.4755, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:45,910 - utils - INFO - stage2_gradient_single_runtime: 0.006085872650146484
2023-09-28 23:25:45,916 - utils - INFO - 1, epoch: 825, all client loss: [0.6637303829193115, 0.6725521683692932], all pred client disparities: [0.0034054128918796778, 0.049541175365448], all client disparities: [0.0, 0.052019909024238586], all client accs: [0.5936238765716553, 0.5760594010353088],  alphas:tensor([0.5231, 0.0000, 0.4769, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:45,973 - utils - INFO - stage2_gradient_single_runtime: 0.006263017654418945
2023-09-28 23:25:45,979 - utils - INFO - 1, epoch: 826, all client loss: [0.664501965045929, 0.6733675599098206], all pred client disparities: [0.0031474034767597914, 0.04721316695213318], all client disparities: [0.0, 0.0499529093503952], all client accs: [0.5936238765716553, 0.5756972432136536],  alphas:tensor([0.5219, 0.0000, 0.4781, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:46,039 - utils - INFO - stage2_gradient_single_runtime: 0.006192445755004883
2023-09-28 23:25:46,044 - utils - INFO - 1, epoch: 827, all client loss: [0.6652976274490356, 0.6742091774940491], all pred client disparities: [0.0028978579211980104, 0.04481613636016846], all client disparities: [0.0, 0.04728688299655914], all client accs: [0.5936238765716553, 0.5737051963806152],  alphas:tensor([0.5209, 0.0000, 0.4791, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:46,108 - utils - INFO - stage2_gradient_single_runtime: 0.007205009460449219
2023-09-28 23:25:46,117 - utils - INFO - 1, epoch: 828, all client loss: [0.6661162972450256, 0.6750763654708862], all pred client disparities: [0.0026569862384349108, 0.042353034019470215], all client disparities: [0.0, 0.04462088644504547], all client accs: [0.5936238765716553, 0.5713509917259216],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:46,178 - utils - INFO - stage2_gradient_single_runtime: 0.006047725677490234
2023-09-28 23:25:46,183 - utils - INFO - 1, epoch: 829, all client loss: [0.6603908538818359, 0.6691166758537292], all pred client disparities: [0.004864795599132776, 0.05820086598396301], all client disparities: [0.0, 0.06489987671375275], all client accs: [0.5936238765716553, 0.587649405002594],  alphas:tensor([0.5320, 0.0000, 0.4680, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:46,242 - utils - INFO - stage2_gradient_single_runtime: 0.006278276443481445
2023-09-28 23:25:46,248 - utils - INFO - 1, epoch: 830, all client loss: [0.6610783934593201, 0.6698393225669861], all pred client disparities: [0.004549991339445114, 0.05610455572605133], all client disparities: [0.0, 0.06128726899623871], all client accs: [0.5936238765716553, 0.5852952003479004],  alphas:tensor([0.5297, 0.0000, 0.4703, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:46,309 - utils - INFO - stage2_gradient_single_runtime: 0.006417512893676758
2023-09-28 23:25:46,316 - utils - INFO - 1, epoch: 831, all client loss: [0.6617895364761353, 0.6705875396728516], all pred client disparities: [0.004243258386850357, 0.05393868684768677], all client disparities: [0.0, 0.059136465191841125], all client accs: [0.5936238765716553, 0.5833031535148621],  alphas:tensor([0.5277, 0.0000, 0.4723, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:46,380 - utils - INFO - stage2_gradient_single_runtime: 0.00730443000793457
2023-09-28 23:25:46,385 - utils - INFO - 1, epoch: 832, all client loss: [0.6625252366065979, 0.6713624000549316], all pred client disparities: [0.003944722935557365, 0.05170063674449921], all client disparities: [0.0, 0.055260032415390015], all client accs: [0.5936238765716553, 0.5818544030189514],  alphas:tensor([0.5259, 0.0000, 0.4741, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:46,447 - utils - INFO - stage2_gradient_single_runtime: 0.006456136703491211
2023-09-28 23:25:46,453 - utils - INFO - 1, epoch: 833, all client loss: [0.6632860898971558, 0.6721646785736084], all pred client disparities: [0.003654635511338711, 0.049389198422431946], all client disparities: [0.0, 0.054145827889442444], all client accs: [0.5936238765716553, 0.5796812772750854],  alphas:tensor([0.5244, 0.0000, 0.4756, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:46,512 - utils - INFO - stage2_gradient_single_runtime: 0.006146907806396484
2023-09-28 23:25:46,517 - utils - INFO - 1, epoch: 834, all client loss: [0.6640722155570984, 0.6729946732521057], all pred client disparities: [0.003373300191015005, 0.047004520893096924], all client disparities: [0.0, 0.049844205379486084], all client accs: [0.5936238765716553, 0.5778703689575195],  alphas:tensor([0.5230, 0.0000, 0.4770, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:46,626 - utils - INFO - stage2_gradient_single_runtime: 0.006165266036987305
2023-09-28 23:25:46,632 - utils - INFO - 1, epoch: 835, all client loss: [0.6648832559585571, 0.6738519072532654], all pred client disparities: [0.0031010089442133904, 0.04454803466796875], all client disparities: [0.0, 0.047777190804481506], all client accs: [0.5936238765716553, 0.5758783221244812],  alphas:tensor([0.5218, 0.0000, 0.4782, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:46,692 - utils - INFO - stage2_gradient_single_runtime: 0.006341218948364258
2023-09-28 23:25:46,698 - utils - INFO - 1, epoch: 836, all client loss: [0.6657186150550842, 0.6747359037399292], all pred client disparities: [0.0028379957657307386, 0.042022302746772766], all client disparities: [0.0, 0.04795101284980774], all client accs: [0.5936238765716553, 0.5746106505393982],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:46,758 - utils - INFO - stage2_gradient_single_runtime: 0.006243467330932617
2023-09-28 23:25:46,764 - utils - INFO - 1, epoch: 837, all client loss: [0.6599928140640259, 0.6687690019607544], all pred client disparities: [0.005197453312575817, 0.058017343282699585], all client disparities: [0.0, 0.06685197353363037], all client accs: [0.5936238765716553, 0.59018474817276],  alphas:tensor([0.5343, 0.0000, 0.4657, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:46,830 - utils - INFO - stage2_gradient_single_runtime: 0.007048130035400391
2023-09-28 23:25:46,837 - utils - INFO - 1, epoch: 838, all client loss: [0.6606940627098083, 0.6695058345794678], all pred client disparities: [0.004856499377638102, 0.05586712062358856], all client disparities: [0.0, 0.06159752607345581], all client accs: [0.5936238765716553, 0.5896414518356323],  alphas:tensor([0.5317, 0.0000, 0.4683, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:46,898 - utils - INFO - stage2_gradient_single_runtime: 0.0063323974609375
2023-09-28 23:25:46,904 - utils - INFO - 1, epoch: 839, all client loss: [0.661418616771698, 0.6702679395675659], all pred client disparities: [0.004524594638496637, 0.05364811420440674], all client disparities: [0.0, 0.06048336625099182], all client accs: [0.5936238765716553, 0.587649405002594],  alphas:tensor([0.5294, 0.0000, 0.4706, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:46,921 - utils - INFO - valid: True, epoch: 839, loss: [0.6547282338142395, 0.6736935377120972], accuracy: [0.6111999750137329, 0.5839999914169312], mean_accuracy:0.597599983215332,variance_accuracy:0.013599991798400879, disparity: [0.0, 0.06987801194190979], mean_disparity:0.034939005970954895,variance_disparity:0.034939005970954895, pred_disparity: [0.004306683782488108, 0.062265023589134216]
2023-09-28 23:25:46,933 - utils - INFO - global_valid: True, epoch: 839,  global_loss: 0.6677668690681458, global_accuracy: 0.6476870748299319,  global_disparity:0.059036269783973694, global_pred_disparity: 0.05429895222187042,
2023-09-28 23:25:46,991 - utils - INFO - stage2_gradient_single_runtime: 0.0063512325286865234
2023-09-28 23:25:46,998 - utils - INFO - 1, epoch: 840, all client loss: [0.6621678471565247, 0.6710567474365234], all pred client disparities: [0.004201667383313179, 0.05135659873485565], all client disparities: [0.0, 0.05635553598403931], all client accs: [0.5936238765716553, 0.5845708250999451],  alphas:tensor([0.5274, 0.0000, 0.4726, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:47,063 - utils - INFO - stage2_gradient_single_runtime: 0.007059335708618164
2023-09-28 23:25:47,068 - utils - INFO - 1, epoch: 841, all client loss: [0.6629425883293152, 0.6718732714653015], all pred client disparities: [0.0038878486957401037, 0.04899059236049652], all client disparities: [0.0, 0.054893746972084045], all client accs: [0.5936238765716553, 0.5823976993560791],  alphas:tensor([0.5257, 0.0000, 0.4743, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:47,131 - utils - INFO - stage2_gradient_single_runtime: 0.006345510482788086
2023-09-28 23:25:47,136 - utils - INFO - 1, epoch: 842, all client loss: [0.6637431383132935, 0.6727181673049927], all pred client disparities: [0.003583383047953248, 0.046549662947654724], all client disparities: [0.0, 0.05274292826652527], all client accs: [0.5936238765716553, 0.5811300277709961],  alphas:tensor([0.5242, 0.0000, 0.4758, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:47,198 - utils - INFO - stage2_gradient_single_runtime: 0.006184101104736328
2023-09-28 23:25:47,203 - utils - INFO - 1, epoch: 843, all client loss: [0.6645693778991699, 0.6735911965370178], all pred client disparities: [0.0032885398250073195, 0.044034749269485474], all client disparities: [0.0, 0.049477919936180115], all client accs: [0.5936238765716553, 0.5776892900466919],  alphas:tensor([0.5229, 0.0000, 0.4771, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:47,270 - utils - INFO - stage2_gradient_single_runtime: 0.0071032047271728516
2023-09-28 23:25:47,275 - utils - INFO - 1, epoch: 844, all client loss: [0.6654207706451416, 0.6744918823242188], all pred client disparities: [0.003003552323207259, 0.041448354721069336], all client disparities: [0.0, 0.044481098651885986], all client accs: [0.5936238765716553, 0.5762405395507812],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:47,333 - utils - INFO - stage2_gradient_single_runtime: 0.006155490875244141
2023-09-28 23:25:47,340 - utils - INFO - 1, epoch: 845, all client loss: [0.6596889495849609, 0.6685119271278381], all pred client disparities: [0.005509524140506983, 0.05759568512439728], all client disparities: [0.0, 0.06648571789264679], all client accs: [0.5936238765716553, 0.5921767950057983],  alphas:tensor([0.5367, 0.0000, 0.4633, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:47,402 - utils - INFO - stage2_gradient_single_runtime: 0.006401777267456055
2023-09-28 23:25:47,407 - utils - INFO - 1, epoch: 846, all client loss: [0.6604053974151611, 0.6692647933959961], all pred client disparities: [0.005142176989465952, 0.0553874671459198], all client disparities: [0.0, 0.0637296736240387], all client accs: [0.5936238765716553, 0.5907280445098877],  alphas:tensor([0.5337, 0.0000, 0.4663, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:47,522 - utils - INFO - stage2_gradient_single_runtime: 0.0069713592529296875
2023-09-28 23:25:47,528 - utils - INFO - 1, epoch: 847, all client loss: [0.661144495010376, 0.6700422167778015], all pred client disparities: [0.00478509021922946, 0.05311225354671478], all client disparities: [0.0, 0.060200855135917664], all client accs: [0.5936238765716553, 0.5883737802505493],  alphas:tensor([0.5312, 0.0000, 0.4688, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:47,590 - utils - INFO - stage2_gradient_single_runtime: 0.0063571929931640625
2023-09-28 23:25:47,597 - utils - INFO - 1, epoch: 848, all client loss: [0.6619080901145935, 0.6708462238311768], all pred client disparities: [0.004437911789864302, 0.05076521635055542], all client disparities: [0.0, 0.05830766260623932], all client accs: [0.5936238765716553, 0.586743950843811],  alphas:tensor([0.5289, 0.0000, 0.4711, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:47,657 - utils - INFO - stage2_gradient_single_runtime: 0.00632929801940918
2023-09-28 23:25:47,663 - utils - INFO - 1, epoch: 849, all client loss: [0.6626972556114197, 0.6716781258583069], all pred client disparities: [0.00410059466958046, 0.04834343492984772], all client disparities: [0.0, 0.054089829325675964], all client accs: [0.5936238765716553, 0.5847519040107727],  alphas:tensor([0.5270, 0.0000, 0.4730, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:47,724 - utils - INFO - stage2_gradient_single_runtime: 0.0074481964111328125
2023-09-28 23:25:47,730 - utils - INFO - 1, epoch: 850, all client loss: [0.6635125279426575, 0.6725385785102844], all pred client disparities: [0.0037732759956270456, 0.045845821499824524], all client disparities: [0.0, 0.04987822473049164], all client accs: [0.5936238765716553, 0.5814922451972961],  alphas:tensor([0.5253, 0.0000, 0.4747, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:47,790 - utils - INFO - stage2_gradient_single_runtime: 0.006185054779052734
2023-09-28 23:25:47,796 - utils - INFO - 1, epoch: 851, all client loss: [0.6643540263175964, 0.6734276413917542], all pred client disparities: [0.003456166945397854, 0.043273091316223145], all client disparities: [0.0, 0.04574419558048248], all client accs: [0.5936238765716553, 0.5793191194534302],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:47,856 - utils - INFO - stage2_gradient_single_runtime: 0.006252288818359375
2023-09-28 23:25:47,863 - utils - INFO - 1, epoch: 852, all client loss: [0.6586732864379883, 0.6674956679344177], all pred client disparities: [0.006259994115680456, 0.05940099060535431], all client disparities: [0.0, 0.06559798121452332], all client accs: [0.5936238765716553, 0.5954364538192749],  alphas:tensor([0.5436, 0.0000, 0.4564, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:47,924 - utils - INFO - stage2_gradient_single_runtime: 0.00626373291015625
2023-09-28 23:25:47,930 - utils - INFO - 1, epoch: 853, all client loss: [0.659386157989502, 0.6682443618774414], all pred client disparities: [0.005850847344845533, 0.057191506028175354], all client disparities: [0.0, 0.06284196674823761], all client accs: [0.5936238765716553, 0.593625545501709],  alphas:tensor([0.5396, 0.0000, 0.4604, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:47,996 - utils - INFO - stage2_gradient_single_runtime: 0.006277322769165039
2023-09-28 23:25:48,002 - utils - INFO - 1, epoch: 854, all client loss: [0.6601170897483826, 0.6690128445625305], all pred client disparities: [0.005455027334392071, 0.05492791533470154], all client disparities: [0.0, 0.059744566679000854], all client accs: [0.5936238765716553, 0.5914523601531982],  alphas:tensor([0.5362, 0.0000, 0.4638, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:48,064 - utils - INFO - stage2_gradient_single_runtime: 0.006617069244384766
2023-09-28 23:25:48,070 - utils - INFO - 1, epoch: 855, all client loss: [0.6608694195747375, 0.6698043346405029], all pred client disparities: [0.005071063991636038, 0.052601203322410583], all client disparities: [0.0, 0.056647151708602905], all client accs: [0.5936238765716553, 0.5890981554985046],  alphas:tensor([0.5333, 0.0000, 0.4667, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:48,134 - utils - INFO - stage2_gradient_single_runtime: 0.0064084529876708984
2023-09-28 23:25:48,141 - utils - INFO - 1, epoch: 856, all client loss: [0.661645233631134, 0.6706216335296631], all pred client disparities: [0.004698173142969608, 0.050204887986183167], all client disparities: [0.0, 0.05414871871471405], all client accs: [0.5936238765716553, 0.5887359976768494],  alphas:tensor([0.5308, 0.0000, 0.4692, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:48,205 - utils - INFO - stage2_gradient_single_runtime: 0.006955146789550781
2023-09-28 23:25:48,211 - utils - INFO - 1, epoch: 857, all client loss: [0.6624463796615601, 0.6714664101600647], all pred client disparities: [0.004336019046604633, 0.04773491621017456], all client disparities: [0.0, 0.05139271914958954], all client accs: [0.5936238765716553, 0.586743950843811],  alphas:tensor([0.5286, 0.0000, 0.4714, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:48,271 - utils - INFO - stage2_gradient_single_runtime: 0.006308555603027344
2023-09-28 23:25:48,277 - utils - INFO - 1, epoch: 858, all client loss: [0.6632736921310425, 0.6723397970199585], all pred client disparities: [0.003984555136412382, 0.04518933594226837], all client disparities: [0.0, 0.0482952743768692], all client accs: [0.5936238765716553, 0.5825787782669067],  alphas:tensor([0.5268, 0.0000, 0.4732, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:48,397 - utils - INFO - stage2_gradient_single_runtime: 0.006205081939697266
2023-09-28 23:25:48,404 - utils - INFO - 1, epoch: 859, all client loss: [0.66412752866745, 0.6732420921325684], all pred client disparities: [0.0036438843235373497, 0.04256795346736908], all client disparities: [0.0, 0.04364606738090515], all client accs: [0.5936238765716553, 0.5804056525230408],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:48,419 - utils - INFO - valid: True, epoch: 859, loss: [0.6515966057777405, 0.6700853109359741], accuracy: [0.6111999750137329, 0.5898181796073914], mean_accuracy:0.6005090773105621,variance_accuracy:0.010690897703170776, disparity: [0.0, 0.0709201842546463], mean_disparity:0.03546009212732315,variance_disparity:0.03546009212732315, pred_disparity: [0.006693667266517878, 0.06952343881130219]
2023-09-28 23:25:48,431 - utils - INFO - global_valid: True, epoch: 859,  global_loss: 0.6643076539039612, global_accuracy: 0.6543027210884353,  global_disparity:0.060113146901130676, global_pred_disparity: 0.060674890875816345,
2023-09-28 23:25:48,493 - utils - INFO - stage2_gradient_single_runtime: 0.006340503692626953
2023-09-28 23:25:48,499 - utils - INFO - 1, epoch: 860, all client loss: [0.6584376692771912, 0.6672943830490112], all pred client disparities: [0.006611434742808342, 0.05883598327636719], all client disparities: [0.0, 0.06290087103843689], all client accs: [0.5936238765716553, 0.5976095795631409],  alphas:tensor([0.5473, 0.0000, 0.4527, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:48,558 - utils - INFO - stage2_gradient_single_runtime: 0.0061566829681396484
2023-09-28 23:25:48,565 - utils - INFO - 1, epoch: 861, all client loss: [0.6591697335243225, 0.6680638194084167], all pred client disparities: [0.006170227192342281, 0.056557849049568176], all client disparities: [0.0, 0.06083384156227112], all client accs: [0.5936238765716553, 0.5961608290672302],  alphas:tensor([0.5427, 0.0000, 0.4573, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:48,629 - utils - INFO - stage2_gradient_single_runtime: 0.0069751739501953125
2023-09-28 23:25:48,636 - utils - INFO - 1, epoch: 862, all client loss: [0.6599171757698059, 0.6688501834869385], all pred client disparities: [0.005745189264416695, 0.05423332750797272], all client disparities: [0.0, 0.05894064903259277], all client accs: [0.5936238765716553, 0.5943498611450195],  alphas:tensor([0.5388, 0.0000, 0.4612, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:48,698 - utils - INFO - stage2_gradient_single_runtime: 0.0060367584228515625
2023-09-28 23:25:48,703 - utils - INFO - 1, epoch: 863, all client loss: [0.6606841087341309, 0.6696578860282898], all pred client disparities: [0.005333998706191778, 0.051850855350494385], all client disparities: [0.0, 0.05627463757991791], all client accs: [0.5936238765716553, 0.5905469059944153],  alphas:tensor([0.5355, 0.0000, 0.4645, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:48,761 - utils - INFO - stage2_gradient_single_runtime: 0.006456613540649414
2023-09-28 23:25:48,766 - utils - INFO - 1, epoch: 864, all client loss: [0.6614736318588257, 0.6704900860786438], all pred client disparities: [0.004935295321047306, 0.049402281641960144], all client disparities: [0.0, 0.05154162645339966], all client accs: [0.5936238765716553, 0.5874683260917664],  alphas:tensor([0.5326, 0.0000, 0.4674, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:48,821 - utils - INFO - stage2_gradient_single_runtime: 0.006211996078491211
2023-09-28 23:25:48,824 - utils - INFO - 1, epoch: 865, all client loss: [0.6622877717018127, 0.671349048614502], all pred client disparities: [0.004548367112874985, 0.04688215255737305], all client disparities: [0.0, 0.04878561198711395], all client accs: [0.5936238765716553, 0.5862006545066833],  alphas:tensor([0.5303, 0.0000, 0.4697, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:48,887 - utils - INFO - stage2_gradient_single_runtime: 0.00619959831237793
2023-09-28 23:25:48,893 - utils - INFO - 1, epoch: 866, all client loss: [0.6631277799606323, 0.6722363233566284], all pred client disparities: [0.00417291047051549, 0.04428752884268761], all client disparities: [0.0, 0.0461195707321167], all client accs: [0.5936238765716553, 0.584208607673645],  alphas:tensor([0.5282, 0.0000, 0.4718, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:48,952 - utils - INFO - stage2_gradient_single_runtime: 0.006549358367919922
2023-09-28 23:25:48,958 - utils - INFO - 1, epoch: 867, all client loss: [0.6639941334724426, 0.673152506351471], all pred client disparities: [0.003808868583291769, 0.041617512702941895], all client disparities: [0.0, 0.04198557138442993], all client accs: [0.5936238765716553, 0.5836653709411621],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:49,020 - utils - INFO - stage2_gradient_single_runtime: 0.006384372711181641
2023-09-28 23:25:49,025 - utils - INFO - 1, epoch: 868, all client loss: [0.6582897305488586, 0.6671832799911499], all pred client disparities: [0.006933816242963076, 0.05803242325782776], all client disparities: [0.0, 0.061755552887916565], all client accs: [0.5936238765716553, 0.5990583300590515],  alphas:tensor([0.5510, 0.0000, 0.4490, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:49,087 - utils - INFO - stage2_gradient_single_runtime: 0.006201028823852539
2023-09-28 23:25:49,094 - utils - INFO - 1, epoch: 869, all client loss: [0.659043550491333, 0.6679765582084656], all pred client disparities: [0.006459349300712347, 0.05567803978919983], all client disparities: [0.0, 0.05908955633640289], all client accs: [0.5936238765716553, 0.5959797501564026],  alphas:tensor([0.5457, 0.0000, 0.4543, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:49,214 - utils - INFO - stage2_gradient_single_runtime: 0.006242513656616211
2023-09-28 23:25:49,221 - utils - INFO - 1, epoch: 870, all client loss: [0.6598097085952759, 0.66878342628479], all pred client disparities: [0.006004483439028263, 0.053286582231521606], all client disparities: [0.0, 0.054350316524505615], all client accs: [0.5936238765716553, 0.5939877033233643],  alphas:tensor([0.5413, 0.0000, 0.4587, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:49,281 - utils - INFO - stage2_gradient_single_runtime: 0.006280183792114258
2023-09-28 23:25:49,286 - utils - INFO - 1, epoch: 871, all client loss: [0.6605933904647827, 0.6696094274520874], all pred client disparities: [0.005565832369029522, 0.050843745470047], all client disparities: [0.0, 0.05340370535850525], all client accs: [0.5936238765716553, 0.592357873916626],  alphas:tensor([0.5376, 0.0000, 0.4624, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:49,354 - utils - INFO - stage2_gradient_single_runtime: 0.009767532348632812
2023-09-28 23:25:49,359 - utils - INFO - 1, epoch: 872, all client loss: [0.6613980531692505, 0.6704584360122681], all pred client disparities: [0.005141329951584339, 0.04833918809890747], all client disparities: [0.0, 0.04953348636627197], all client accs: [0.5936238765716553, 0.59018474817276],  alphas:tensor([0.5345, 0.0000, 0.4655, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:49,456 - utils - INFO - stage2_gradient_single_runtime: 0.011307954788208008
2023-09-28 23:25:49,462 - utils - INFO - 1, epoch: 873, all client loss: [0.6622264981269836, 0.6713333129882812], all pred client disparities: [0.0047297910787165165, 0.04576614499092102], all client disparities: [0.0, 0.04643607139587402], all client accs: [0.5936238765716553, 0.5874683260917664],  alphas:tensor([0.5319, 0.0000, 0.4681, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:49,544 - utils - INFO - stage2_gradient_single_runtime: 0.006116628646850586
2023-09-28 23:25:49,549 - utils - INFO - 1, epoch: 874, all client loss: [0.6630802154541016, 0.6722357273101807], all pred client disparities: [0.004330598283559084, 0.04312053322792053], all client disparities: [0.0, 0.042991042137145996], all client accs: [0.5936238765716553, 0.5860195755958557],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:49,618 - utils - INFO - stage2_gradient_single_runtime: 0.006770133972167969
2023-09-28 23:25:49,625 - utils - INFO - 1, epoch: 875, all client loss: [0.6574188470840454, 0.6663064956665039], all pred client disparities: [0.007790020667016506, 0.05950140953063965], all client disparities: [0.0, 0.06276106834411621], all client accs: [0.5936238765716553, 0.6024991273880005],  alphas:tensor([0.5625, 0.0000, 0.4375, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:49,683 - utils - INFO - stage2_gradient_single_runtime: 0.006257534027099609
2023-09-28 23:25:49,690 - utils - INFO - 1, epoch: 876, all client loss: [0.6581975817680359, 0.6671262383460999], all pred client disparities: [0.007248145528137684, 0.05706369876861572], all client disparities: [0.0, 0.058543235063552856], all client accs: [0.5936238765716553, 0.5994205474853516],  alphas:tensor([0.5550, 0.0000, 0.4450, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:49,750 - utils - INFO - stage2_gradient_single_runtime: 0.006135225296020508
2023-09-28 23:25:49,756 - utils - INFO - 1, epoch: 877, all client loss: [0.6589757800102234, 0.6679463386535645], all pred client disparities: [0.006737805437296629, 0.05462604761123657], all client disparities: [0.0, 0.055362045764923096], all client accs: [0.5936238765716553, 0.5968852043151855],  alphas:tensor([0.5490, 0.0000, 0.4510, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:49,821 - utils - INFO - stage2_gradient_single_runtime: 0.006655216217041016
2023-09-28 23:25:49,825 - utils - INFO - 1, epoch: 878, all client loss: [0.6597625017166138, 0.6687757968902588], all pred client disparities: [0.006251353304833174, 0.052163273096084595], all client disparities: [0.0, 0.05346882343292236], all client accs: [0.5936238765716553, 0.5947120785713196],  alphas:tensor([0.5441, 0.0000, 0.4559, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:49,887 - utils - INFO - stage2_gradient_single_runtime: 0.00646209716796875
2023-09-28 23:25:49,893 - utils - INFO - 1, epoch: 879, all client loss: [0.6605638861656189, 0.6696215867996216], all pred client disparities: [0.0057840109802782536, 0.04965740442276001], all client disparities: [0.0, 0.049940019845962524], all client accs: [0.5936238765716553, 0.5927200317382812],  alphas:tensor([0.5400, 0.0000, 0.4600, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:49,908 - utils - INFO - valid: True, epoch: 879, loss: [0.6544485092163086, 0.6728394031524658], accuracy: [0.6111999750137329, 0.5789090991020203], mean_accuracy:0.5950545370578766,variance_accuracy:0.016145437955856323, disparity: [0.0, 0.05797140300273895], mean_disparity:0.028985701501369476,variance_disparity:0.028985701501369476, pred_disparity: [0.005550140514969826, 0.058185845613479614]
2023-09-28 23:25:49,920 - utils - INFO - global_valid: True, epoch: 879,  global_loss: 0.6670923233032227, global_accuracy: 0.642686074429772,  global_disparity:0.050557732582092285, global_pred_disparity: 0.05199390649795532,
2023-09-28 23:25:49,980 - utils - INFO - stage2_gradient_single_runtime: 0.006120443344116211
2023-09-28 23:25:49,985 - utils - INFO - 1, epoch: 880, all client loss: [0.6613845229148865, 0.6704883575439453], all pred client disparities: [0.005332804750651121, 0.04709574580192566], all client disparities: [0.0, 0.04692637920379639], all client accs: [0.5936238765716553, 0.5903658270835876],  alphas:tensor([0.5366, 0.0000, 0.4634, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:50,059 - utils - INFO - stage2_gradient_single_runtime: 0.007511615753173828
2023-09-28 23:25:50,063 - utils - INFO - 1, epoch: 881, all client loss: [0.6622275114059448, 0.671379566192627], all pred client disparities: [0.004895949736237526, 0.04446983337402344], all client disparities: [0.0, 0.04253476858139038], all client accs: [0.5936238765716553, 0.587649405002594],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:50,172 - utils - INFO - stage2_gradient_single_runtime: 0.0062139034271240234
2023-09-28 23:25:50,175 - utils - INFO - 1, epoch: 882, all client loss: [0.6566057205200195, 0.6654863357543945], all pred client disparities: [0.00870961882174015, 0.06081181764602661], all client disparities: [0.0, 0.06609117984771729], all client accs: [0.5936238765716553, 0.6046722531318665],  alphas:tensor([0.5782, 0.0000, 0.4218, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:50,228 - utils - INFO - stage2_gradient_single_runtime: 0.006285429000854492
2023-09-28 23:25:50,231 - utils - INFO - 1, epoch: 883, all client loss: [0.6574397683143616, 0.6663652062416077], all pred client disparities: [0.008070767857134342, 0.058200716972351074], all client disparities: [0.0, 0.06256237626075745], all client accs: [0.5936238765716553, 0.6028612852096558],  alphas:tensor([0.5671, 0.0000, 0.4329, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:50,288 - utils - INFO - stage2_gradient_single_runtime: 0.006896018981933594
2023-09-28 23:25:50,293 - utils - INFO - 1, epoch: 884, all client loss: [0.6582513451576233, 0.667220950126648], all pred client disparities: [0.007487020920962095, 0.055654674768447876], all client disparities: [0.0, 0.05688273906707764], all client accs: [0.5936238765716553, 0.6005070805549622],  alphas:tensor([0.5586, 0.0000, 0.4414, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:50,357 - utils - INFO - stage2_gradient_single_runtime: 0.006106138229370117
2023-09-28 23:25:50,362 - utils - INFO - 1, epoch: 885, all client loss: [0.6590567231178284, 0.6680708527565002], all pred client disparities: [0.0069416239857673645, 0.05312654376029968], all client disparities: [0.0, 0.05352771282196045], all client accs: [0.5936238765716553, 0.5972473621368408],  alphas:tensor([0.5519, 0.0000, 0.4481, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:50,423 - utils - INFO - stage2_gradient_single_runtime: 0.006169795989990234
2023-09-28 23:25:50,428 - utils - INFO - 1, epoch: 886, all client loss: [0.6598666906356812, 0.6689262986183167], all pred client disparities: [0.0064245047979056835, 0.05058509111404419], all client disparities: [0.0, 0.050777941942214966], all client accs: [0.5936238765716553, 0.5932633280754089],  alphas:tensor([0.5465, 0.0000, 0.4535, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:50,491 - utils - INFO - stage2_gradient_single_runtime: 0.006834268569946289
2023-09-28 23:25:50,497 - utils - INFO - 1, epoch: 887, all client loss: [0.6606888771057129, 0.6697950959205627], all pred client disparities: [0.005929423496127129, 0.04800871014595032], all client disparities: [0.0, 0.04647010564804077], all client accs: [0.5936238765716553, 0.5919956564903259],  alphas:tensor([0.5421, 0.0000, 0.4579, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:50,570 - utils - INFO - stage2_gradient_single_runtime: 0.0060765743255615234
2023-09-28 23:25:50,576 - utils - INFO - 1, epoch: 888, all client loss: [0.6615283489227295, 0.6706830859184265], all pred client disparities: [0.005452483426779509, 0.04538258910179138], all client disparities: [0.0, 0.045098304748535156], all client accs: [0.5936238765716553, 0.5869250297546387],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:50,636 - utils - INFO - stage2_gradient_single_runtime: 0.006278038024902344
2023-09-28 23:25:50,641 - utils - INFO - 1, epoch: 889, all client loss: [0.6559358835220337, 0.6648151278495789], all pred client disparities: [0.009614366106688976, 0.06170213222503662], all client disparities: [0.0, 0.06950509548187256], all client accs: [0.5936238765716553, 0.6081130504608154],  alphas:tensor([0.5979, 0.0000, 0.4021, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:50,701 - utils - INFO - stage2_gradient_single_runtime: 0.006283998489379883
2023-09-28 23:25:50,706 - utils - INFO - 1, epoch: 890, all client loss: [0.6568633317947388, 0.6657935380935669], all pred client disparities: [0.008840974420309067, 0.058804988861083984], all client disparities: [0.0, 0.06305268406867981], all client accs: [0.5936238765716553, 0.605758786201477],  alphas:tensor([0.5811, 0.0000, 0.4189, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:50,766 - utils - INFO - stage2_gradient_single_runtime: 0.006867647171020508
2023-09-28 23:25:50,773 - utils - INFO - 1, epoch: 891, all client loss: [0.6577326655387878, 0.6667112708091736], all pred client disparities: [0.00816442258656025, 0.056078195571899414], all client disparities: [0.0, 0.060991883277893066], all client accs: [0.5936238765716553, 0.6010503768920898],  alphas:tensor([0.5692, 0.0000, 0.4308, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:50,837 - utils - INFO - stage2_gradient_single_runtime: 0.006625175476074219
2023-09-28 23:25:50,843 - utils - INFO - 1, epoch: 892, all client loss: [0.6585747599601746, 0.6676007509231567], all pred client disparities: [0.007549556903541088, 0.05343201756477356], all client disparities: [0.0, 0.05728927254676819], all client accs: [0.5936238765716553, 0.5985150337219238],  alphas:tensor([0.5603, 0.0000, 0.4397, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:50,905 - utils - INFO - stage2_gradient_single_runtime: 0.006404876708984375
2023-09-28 23:25:50,911 - utils - INFO - 1, epoch: 893, all client loss: [0.6594077348709106, 0.6684813499450684], all pred client disparities: [0.0069770184345543385, 0.05081307888031006], all client disparities: [0.0, 0.05177721381187439], all client accs: [0.5936238765716553, 0.5967041254043579],  alphas:tensor([0.5533, 0.0000, 0.4467, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:50,971 - utils - INFO - stage2_gradient_single_runtime: 0.007121562957763672
2023-09-28 23:25:50,977 - utils - INFO - 1, epoch: 894, all client loss: [0.6602436304092407, 0.6693655252456665], all pred client disparities: [0.006435330491513014, 0.048186928033828735], all client disparities: [0.0, 0.0478232204914093], all client accs: [0.5936238765716553, 0.5921767950057983],  alphas:tensor([0.5477, 0.0000, 0.4523, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:51,089 - utils - INFO - stage2_gradient_single_runtime: 0.006420612335205078
2023-09-28 23:25:51,094 - utils - INFO - 1, epoch: 895, all client loss: [0.6610904335975647, 0.6702618598937988], all pred client disparities: [0.005917439237236977, 0.0455302894115448], all client disparities: [0.0, 0.04265254735946655], all client accs: [0.5936238765716553, 0.5914523601531982],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:51,149 - utils - INFO - stage2_gradient_single_runtime: 0.006150484085083008
2023-09-28 23:25:51,152 - utils - INFO - 1, epoch: 896, all client loss: [0.655509352684021, 0.6644005179405212], all pred client disparities: [0.010385027155280113, 0.06187143921852112], all client disparities: [0.0, 0.06723940372467041], all client accs: [0.5936238765716553, 0.608837366104126],  alphas:tensor([0.6189, 0.0000, 0.3811, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:51,210 - utils - INFO - stage2_gradient_single_runtime: 0.006421089172363281
2023-09-28 23:25:51,213 - utils - INFO - 1, epoch: 897, all client loss: [0.656557559967041, 0.6655077338218689], all pred client disparities: [0.00945105031132698, 0.05860653519630432], all client disparities: [0.0, 0.0631115734577179], all client accs: [0.5936238765716553, 0.6048533320426941],  alphas:tensor([0.5947, 0.0000, 0.4053, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:51,273 - utils - INFO - stage2_gradient_single_runtime: 0.0060498714447021484
2023-09-28 23:25:51,280 - utils - INFO - 1, epoch: 898, all client loss: [0.6574994325637817, 0.6665031909942627], all pred client disparities: [0.008673766627907753, 0.05565524101257324], all client disparities: [0.0, 0.06087696552276611], all client accs: [0.5936238765716553, 0.6017747521400452],  alphas:tensor([0.5790, 0.0000, 0.4210, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:51,340 - utils - INFO - stage2_gradient_single_runtime: 0.00616002082824707
2023-09-28 23:25:51,345 - utils - INFO - 1, epoch: 899, all client loss: [0.6583889722824097, 0.6674441695213318], all pred client disparities: [0.0079877357929945, 0.05285924673080444], all client disparities: [0.0, 0.05553874373435974], all client accs: [0.5936238765716553, 0.6005070805549622],  alphas:tensor([0.5677, 0.0000, 0.4323, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:51,360 - utils - INFO - valid: True, epoch: 899, loss: [0.6527899503707886, 0.670729398727417], accuracy: [0.6111999750137329, 0.5876363515853882], mean_accuracy:0.5994181632995605,variance_accuracy:0.011781811714172363, disparity: [0.0, 0.057051241397857666], mean_disparity:0.028525620698928833,variance_disparity:0.028525620698928833, pred_disparity: [0.007624030113220215, 0.06123444437980652]
2023-09-28 23:25:51,371 - utils - INFO - global_valid: True, epoch: 899,  global_loss: 0.6651234030723572, global_accuracy: 0.6454346738695479,  global_disparity:0.050316646695137024, global_pred_disparity: 0.05509403347969055,
2023-09-28 23:25:51,432 - utils - INFO - stage2_gradient_single_runtime: 0.006153106689453125
2023-09-28 23:25:51,436 - utils - INFO - 1, epoch: 900, all client loss: [0.659254789352417, 0.6683604717254639], all pred client disparities: [0.007360565476119518, 0.0501348078250885], all client disparities: [0.0, 0.0520099401473999], all client accs: [0.5936238765716553, 0.5967041254043579],  alphas:tensor([0.5592, 0.0000, 0.4408, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:51,501 - utils - INFO - stage2_gradient_single_runtime: 0.006042003631591797
2023-09-28 23:25:51,506 - utils - INFO - 1, epoch: 901, all client loss: [0.6601139903068542, 0.669270396232605], all pred client disparities: [0.006774209905415773, 0.04743179678916931], all client disparities: [0.0, 0.04710307717323303], all client accs: [0.5936238765716553, 0.5945309996604919],  alphas:tensor([0.5525, 0.0000, 0.4475, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:51,568 - utils - INFO - stage2_gradient_single_runtime: 0.006285905838012695
2023-09-28 23:25:51,574 - utils - INFO - 1, epoch: 902, all client loss: [0.6609777212142944, 0.6701856851577759], all pred client disparities: [0.006217914633452892, 0.044717881828546524], all client disparities: [0.0, 0.04392188787460327], all client accs: [0.5936238765716553, 0.5914523601531982],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:51,632 - utils - INFO - stage2_gradient_single_runtime: 0.0061609745025634766
2023-09-28 23:25:51,637 - utils - INFO - 1, epoch: 903, all client loss: [0.6553856134414673, 0.6643074154853821], all pred client disparities: [0.010921083390712738, 0.06114381551742554], all client disparities: [0.0, 0.06841245293617249], all client accs: [0.5936238765716553, 0.6102861166000366],  alphas:tensor([0.6365, 0.0000, 0.3635, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:51,701 - utils - INFO - stage2_gradient_single_runtime: 0.0072040557861328125
2023-09-28 23:25:51,706 - utils - INFO - 1, epoch: 904, all client loss: [0.6565518379211426, 0.6655407547950745], all pred client disparities: [0.009835464879870415, 0.057518213987350464], all client disparities: [0.0, 0.06307423114776611], all client accs: [0.5936238765716553, 0.6070264577865601],  alphas:tensor([0.6051, 0.0000, 0.3949, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:51,771 - utils - INFO - stage2_gradient_single_runtime: 0.006560087203979492
2023-09-28 23:25:51,777 - utils - INFO - 1, epoch: 905, all client loss: [0.6575624346733093, 0.6666103601455688], all pred client disparities: [0.008969727903604507, 0.054353564977645874], all client disparities: [0.0, 0.05774223804473877], all client accs: [0.5936238765716553, 0.6035856604576111],  alphas:tensor([0.5860, 0.0000, 0.4140, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:51,909 - utils - INFO - stage2_gradient_single_runtime: 0.007344484329223633
2023-09-28 23:25:51,914 - utils - INFO - 1, epoch: 906, all client loss: [0.6584985256195068, 0.6676018238067627], all pred client disparities: [0.008222782984375954, 0.05141142010688782], all client disparities: [0.0, 0.05430963635444641], all client accs: [0.5936238765716553, 0.5985150337219238],  alphas:tensor([0.5729, 0.0000, 0.4271, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:51,980 - utils - INFO - stage2_gradient_single_runtime: 0.008363008499145508
2023-09-28 23:25:51,987 - utils - INFO - 1, epoch: 907, all client loss: [0.6593987941741943, 0.6685558557510376], all pred client disparities: [0.007549085654318333, 0.04857781529426575], all client disparities: [0.0, 0.05164363980293274], all client accs: [0.5936238765716553, 0.5959797501564026],  alphas:tensor([0.5633, 0.0000, 0.4367, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:52,049 - utils - INFO - stage2_gradient_single_runtime: 0.006256580352783203
2023-09-28 23:25:52,054 - utils - INFO - 1, epoch: 908, all client loss: [0.6602851152420044, 0.6694955825805664], all pred client disparities: [0.0069245342165231705, 0.04578855633735657], all client disparities: [0.0, 0.04845619201660156], all client accs: [0.5936238765716553, 0.5943498611450195],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:52,113 - utils - INFO - stage2_gradient_single_runtime: 0.006171703338623047
2023-09-28 23:25:52,120 - utils - INFO - 1, epoch: 909, all client loss: [0.6547256112098694, 0.6636466383934021], all pred client disparities: [0.012033729813992977, 0.06214269995689392], all client disparities: [0.0, 0.06950798630714417], all client accs: [0.5936238765716553, 0.6106483340263367],  alphas:tensor([0.6808, 0.0000, 0.3192, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:52,189 - utils - INFO - stage2_gradient_single_runtime: 0.00774693489074707
2023-09-28 23:25:52,197 - utils - INFO - 1, epoch: 910, all client loss: [0.65617436170578, 0.665179967880249], all pred client disparities: [0.010573984123766422, 0.05766907334327698], all client disparities: [0.0, 0.06546398997306824], all client accs: [0.5936238765716553, 0.6075697541236877],  alphas:tensor([0.6271, 0.0000, 0.3729, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:52,259 - utils - INFO - stage2_gradient_single_runtime: 0.0061550140380859375
2023-09-28 23:25:52,265 - utils - INFO - 1, epoch: 911, all client loss: [0.6573162078857422, 0.666389524936676], all pred client disparities: [0.009532802738249302, 0.05410569906234741], all client disparities: [0.0, 0.06013193726539612], all client accs: [0.5936238765716553, 0.6026802062988281],  alphas:tensor([0.5998, 0.0000, 0.4002, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:52,329 - utils - INFO - stage2_gradient_single_runtime: 0.006247282028198242
2023-09-28 23:25:52,335 - utils - INFO - 1, epoch: 912, all client loss: [0.658328115940094, 0.6674622893333435], all pred client disparities: [0.008679993450641632, 0.0509304404258728], all client disparities: [0.0, 0.05548274517059326], all client accs: [0.5936238765716553, 0.6010503768920898],  alphas:tensor([0.5826, 0.0000, 0.4174, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:52,399 - utils - INFO - stage2_gradient_single_runtime: 0.006060123443603516
2023-09-28 23:25:52,404 - utils - INFO - 1, epoch: 913, all client loss: [0.6592769622802734, 0.6684687733650208], all pred client disparities: [0.007932995446026325, 0.047945618629455566], all client disparities: [0.0, 0.05239152908325195], all client accs: [0.5936238765716553, 0.5968852043151855],  alphas:tensor([0.5706, 0.0000, 0.4294, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:52,465 - utils - INFO - stage2_gradient_single_runtime: 0.006112813949584961
2023-09-28 23:25:52,471 - utils - INFO - 1, epoch: 914, all client loss: [0.6601963043212891, 0.6694443821907043], all pred client disparities: [0.007252794224768877, 0.04505237936973572], all client disparities: [0.0, 0.04981553554534912], all client accs: [0.5936238765716553, 0.593625545501709],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:52,536 - utils - INFO - stage2_gradient_single_runtime: 0.0062389373779296875
2023-09-28 23:25:52,541 - utils - INFO - 1, epoch: 915, all client loss: [0.6546272039413452, 0.6635805368423462], all pred client disparities: [0.012607675045728683, 0.0614679753780365], all client disparities: [0.0, 0.06827887892723083], all client accs: [0.5936238765716553, 0.6106483340263367],  alphas:tensor([0.7098, 0.0000, 0.2902, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:52,604 - utils - INFO - stage2_gradient_single_runtime: 0.006083250045776367
2023-09-28 23:25:52,609 - utils - INFO - 1, epoch: 916, all client loss: [0.6562846899032593, 0.6653363108634949], all pred client disparities: [0.010872962884604931, 0.056362926959991455], all client disparities: [0.0, 0.06371968984603882], all client accs: [0.5936238765716553, 0.605758786201477],  alphas:tensor([0.6388, 0.0000, 0.3612, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:52,673 - utils - INFO - stage2_gradient_single_runtime: 0.006289243698120117
2023-09-28 23:25:52,679 - utils - INFO - 1, epoch: 917, all client loss: [0.6575138568878174, 0.6666397452354431], all pred client disparities: [0.00972052663564682, 0.05253145098686218], all client disparities: [0.0, 0.06113746762275696], all client accs: [0.5936238765716553, 0.6039478778839111],  alphas:tensor([0.6066, 0.0000, 0.3934, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:52,738 - utils - INFO - stage2_gradient_single_runtime: 0.006099700927734375
2023-09-28 23:25:52,743 - utils - INFO - 1, epoch: 918, all client loss: [0.6585786938667297, 0.6677696108818054], all pred client disparities: [0.008801287040114403, 0.04919275641441345], all client disparities: [0.0, 0.05753105878829956], all client accs: [0.5936238765716553, 0.6001448631286621],  alphas:tensor([0.5873, 0.0000, 0.4127, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:52,863 - utils - INFO - stage2_gradient_single_runtime: 0.0064661502838134766
2023-09-28 23:25:52,869 - utils - INFO - 1, epoch: 919, all client loss: [0.6595653891563416, 0.6688172221183777], all pred client disparities: [0.008006833493709564, 0.04609110951423645], all client disparities: [0.0, 0.052372872829437256], all client accs: [0.5936238765716553, 0.5963419079780579],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:52,883 - utils - INFO - valid: True, epoch: 919, loss: [0.6483821868896484, 0.6656591892242432], accuracy: [0.6111999750137329, 0.6021817922592163], mean_accuracy:0.6066908836364746,variance_accuracy:0.004509091377258301, disparity: [0.0, 0.07824677228927612], mean_disparity:0.03912338614463806,variance_disparity:0.03912338614463806, pred_disparity: [0.014003310352563858, 0.0733238160610199]
2023-09-28 23:25:52,896 - utils - INFO - global_valid: True, epoch: 919,  global_loss: 0.6602601408958435, global_accuracy: 0.6569087635054022,  global_disparity:0.0668557733297348, global_pred_disparity: 0.06610333919525146,
2023-09-28 23:25:52,956 - utils - INFO - stage2_gradient_single_runtime: 0.006148815155029297
2023-09-28 23:25:52,962 - utils - INFO - 1, epoch: 920, all client loss: [0.65402752161026, 0.6629818081855774], all pred client disparities: [0.01377111580222845, 0.06241697072982788], all client disparities: [0.0, 0.06610319018363953], all client accs: [0.5936238765716553, 0.611372709274292],  alphas:tensor([0.7793, 0.0000, 0.2207, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:53,024 - utils - INFO - stage2_gradient_single_runtime: 0.007748842239379883
2023-09-28 23:25:53,031 - utils - INFO - 1, epoch: 921, all client loss: [0.6561674475669861, 0.6652496457099915], all pred client disparities: [0.011383234523236752, 0.05586785078048706], all client disparities: [0.0, 0.06327581405639648], all client accs: [0.5936238765716553, 0.6061210036277771],  alphas:tensor([0.6595, 0.0000, 0.3405, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:53,095 - utils - INFO - stage2_gradient_single_runtime: 0.0071735382080078125
2023-09-28 23:25:53,101 - utils - INFO - 1, epoch: 922, all client loss: [0.6575382947921753, 0.6667040586471558], all pred client disparities: [0.010044767521321774, 0.05160719156265259], all client disparities: [0.0, 0.05784758925437927], all client accs: [0.5936238765716553, 0.6034045815467834],  alphas:tensor([0.6176, 0.0000, 0.3824, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:53,161 - utils - INFO - stage2_gradient_single_runtime: 0.006189107894897461
2023-09-28 23:25:53,166 - utils - INFO - 1, epoch: 923, all client loss: [0.65867680311203, 0.6679130792617798], all pred client disparities: [0.009028362110257149, 0.04804319143295288], all client disparities: [0.0, 0.054318755865097046], all client accs: [0.5936238765716553, 0.6008692979812622],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:53,233 - utils - INFO - stage2_gradient_single_runtime: 0.007283449172973633
2023-09-28 23:25:53,238 - utils - INFO - 1, epoch: 924, all client loss: [0.6531909108161926, 0.6621281504631042], all pred client disparities: [0.015283104032278061, 0.06419193744659424], all client disparities: [0.0, 0.0660783052444458], all client accs: [0.5936238765716553, 0.6157189607620239],  alphas:tensor([0.8969, 0.0000, 0.1031, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:53,305 - utils - INFO - stage2_gradient_single_runtime: 0.006261348724365234
2023-09-28 23:25:53,310 - utils - INFO - 1, epoch: 925, all client loss: [0.656151533126831, 0.6652666926383972], all pred client disparities: [0.011758632957935333, 0.05519378185272217], all client disparities: [0.0, 0.05912312865257263], all client accs: [0.5936238765716553, 0.6077508330345154],  alphas:tensor([0.6773, 0.0000, 0.3227, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:53,374 - utils - INFO - stage2_gradient_single_runtime: 0.006428718566894531
2023-09-28 23:25:53,379 - utils - INFO - 1, epoch: 926, all client loss: [0.6576513051986694, 0.6668586730957031], all pred client disparities: [0.010250338353216648, 0.050542086362838745], all client disparities: [0.0, 0.05637329816818237], all client accs: [0.5936238765716553, 0.6026802062988281],  alphas:tensor([0.6263, 0.0000, 0.3737, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:53,442 - utils - INFO - stage2_gradient_single_runtime: 0.00646662712097168
2023-09-28 23:25:53,447 - utils - INFO - 1, epoch: 927, all client loss: [0.6588528752326965, 0.6681351661682129], all pred client disparities: [0.009151953272521496, 0.04678589105606079], all client disparities: [0.0, 0.05448010563850403], all client accs: [0.5936238765716553, 0.6005070805549622],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:53,510 - utils - INFO - stage2_gradient_single_runtime: 0.00607609748840332
2023-09-28 23:25:53,516 - utils - INFO - 1, epoch: 928, all client loss: [0.6533435583114624, 0.6623222231864929], all pred client disparities: [0.015551394782960415, 0.06302645802497864], all client disparities: [0.0, 0.06786903738975525], all client accs: [0.5936238765716553, 0.6168055534362793],  alphas:tensor([0.9243, 0.0000, 0.0757, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:53,581 - utils - INFO - stage2_gradient_single_runtime: 0.006425619125366211
2023-09-28 23:25:53,588 - utils - INFO - 1, epoch: 929, all client loss: [0.6565225124359131, 0.6656940579414368], all pred client disparities: [0.011723270639777184, 0.05336344242095947], all client disparities: [0.0, 0.05893063545227051], all client accs: [0.5936238765716553, 0.6072075366973877],  alphas:tensor([0.6797, 0.0000, 0.3203, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:53,649 - utils - INFO - stage2_gradient_single_runtime: 0.006092548370361328
2023-09-28 23:25:53,654 - utils - INFO - 1, epoch: 930, all client loss: [0.6580579876899719, 0.6673248410224915], all pred client disparities: [0.010171270929276943, 0.04860043525695801], all client disparities: [0.0, 0.0564446747303009], all client accs: [0.5936238765716553, 0.6028612852096558],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:53,789 - utils - INFO - stage2_gradient_single_runtime: 0.0063343048095703125
2023-09-28 23:25:53,795 - utils - INFO - 1, epoch: 931, all client loss: [0.6525965332984924, 0.6615587472915649], all pred client disparities: [0.017028547823429108, 0.06466278433799744], all client disparities: [0.0, 0.0709477961063385], all client accs: [0.5936238765716553, 0.6200652122497559],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:53,854 - utils - INFO - stage2_gradient_single_runtime: 0.0061647891998291016
2023-09-28 23:25:53,862 - utils - INFO - 1, epoch: 932, all client loss: [0.656144380569458, 0.6653252243995667], all pred client disparities: [0.012489406391978264, 0.05390253663063049], all client disparities: [0.0, 0.05977478623390198], all client accs: [0.5936238765716553, 0.607931911945343],  alphas:tensor([0.7184, 0.0000, 0.2816, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:53,922 - utils - INFO - stage2_gradient_single_runtime: 0.006238460540771484
2023-09-28 23:25:53,928 - utils - INFO - 1, epoch: 933, all client loss: [0.6579496264457703, 0.6672426462173462], all pred client disparities: [0.01057304535061121, 0.048326525837183], all client disparities: [0.0, 0.05608460307121277], all client accs: [0.5936238765716553, 0.6023180484771729],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:53,997 - utils - INFO - stage2_gradient_single_runtime: 0.007452964782714844
2023-09-28 23:25:54,003 - utils - INFO - 1, epoch: 934, all client loss: [0.6524871587753296, 0.6614724397659302], all pred client disparities: [0.017664426937699318, 0.06439059972763062], all client disparities: [0.0008333333535119891, 0.06989872455596924], all client accs: [0.5940274000167847, 0.6204273700714111],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:54,066 - utils - INFO - stage2_gradient_single_runtime: 0.0063402652740478516
2023-09-28 23:25:54,071 - utils - INFO - 1, epoch: 935, all client loss: [0.6559098958969116, 0.665109395980835], all pred client disparities: [0.013142861425876617, 0.05400088429450989], all client disparities: [0.0, 0.05958855152130127], all client accs: [0.5936238765716553, 0.6084752082824707],  alphas:tensor([0.7584, 0.0000, 0.2416, 0.0000], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:54,133 - utils - INFO - stage2_gradient_single_runtime: 0.006424665451049805
2023-09-28 23:25:54,139 - utils - INFO - 1, epoch: 936, all client loss: [0.6580069661140442, 0.6673370003700256], all pred client disparities: [0.010828476399183273, 0.047545403242111206], all client disparities: [0.0, 0.05641353130340576], all client accs: [0.5936238765716553, 0.6023180484771729],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:54,199 - utils - INFO - stage2_gradient_single_runtime: 0.006777763366699219
2023-09-28 23:25:54,204 - utils - INFO - 1, epoch: 937, all client loss: [0.6525317430496216, 0.6615502834320068], all pred client disparities: [0.018109114840626717, 0.06365415453910828], all client disparities: [0.0008333333535119891, 0.07074907422065735], all client accs: [0.5940274000167847, 0.6198841333389282],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:54,262 - utils - INFO - stage2_gradient_single_runtime: 0.006214618682861328
2023-09-28 23:25:54,268 - utils - INFO - 1, epoch: 938, all client loss: [0.6558738350868225, 0.6651042699813843], all pred client disparities: [0.013594085350632668, 0.05349966883659363], all client disparities: [0.0, 0.06026509404182434], all client accs: [0.5936238765716553, 0.6081130504608154],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:54,328 - utils - INFO - stage2_gradient_single_runtime: 0.006069660186767578
2023-09-28 23:25:54,333 - utils - INFO - 1, epoch: 939, all client loss: [0.6505442261695862, 0.6594664454460144], all pred client disparities: [0.021840795874595642, 0.06901514530181885], all client disparities: [0.0008333333535119891, 0.07959124445915222], all client accs: [0.5940274000167847, 0.6258602142333984],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:54,348 - utils - INFO - valid: True, epoch: 939, loss: [0.6479604840278625, 0.6647580862045288], accuracy: [0.6111999750137329, 0.6036363244056702], mean_accuracy:0.6074181497097015,variance_accuracy:0.003781825304031372, disparity: [0.0, 0.08755666017532349], mean_disparity:0.04377833008766174,variance_disparity:0.04377833008766174, pred_disparity: [0.01828635297715664, 0.07239237427711487]
2023-09-28 23:25:54,359 - utils - INFO - global_valid: True, epoch: 939,  global_loss: 0.6595089435577393, global_accuracy: 0.6563055222088836,  global_disparity:0.07438600063323975, global_pred_disparity: 0.06673642992973328,
2023-09-28 23:25:54,434 - utils - INFO - stage2_gradient_single_runtime: 0.010111570358276367
2023-09-28 23:25:54,440 - utils - INFO - 1, epoch: 940, all client loss: [0.6531145572662354, 0.6622104644775391], all pred client disparities: [0.017871594056487083, 0.0611969530582428], all client disparities: [0.0, 0.06901100277900696], all client accs: [0.5936238765716553, 0.6171677112579346],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:54,538 - utils - INFO - stage2_gradient_single_runtime: 0.010896921157836914
2023-09-28 23:25:54,544 - utils - INFO - 1, epoch: 941, all client loss: [0.6565322875976562, 0.6658454537391663], all pred client disparities: [0.013277909718453884, 0.050798505544662476], all client disparities: [0.0, 0.05879086256027222], all client accs: [0.5936238765716553, 0.6050344109535217],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:54,632 - utils - INFO - stage2_gradient_single_runtime: 0.006428718566894531
2023-09-28 23:25:54,638 - utils - INFO - 1, epoch: 942, all client loss: [0.6511457562446594, 0.6601445078849792], all pred client disparities: [0.021564016118645668, 0.06653249263763428], all client disparities: [0.0008333333535119891, 0.07561859488487244], all client accs: [0.5940274000167847, 0.6227816343307495],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:54,748 - utils - INFO - stage2_gradient_single_runtime: 0.006075620651245117
2023-09-28 23:25:54,753 - utils - INFO - 1, epoch: 943, all client loss: [0.6537920832633972, 0.6629693508148193], all pred client disparities: [0.01750154420733452, 0.058473944664001465], all client disparities: [0.0, 0.06753677129745483], all client accs: [0.5936238765716553, 0.6164433360099792],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:54,823 - utils - INFO - stage2_gradient_single_runtime: 0.007061004638671875
2023-09-28 23:25:54,830 - utils - INFO - 1, epoch: 944, all client loss: [0.6573095321655273, 0.6667104363441467], all pred client disparities: [0.012815617956221104, 0.04776012897491455], all client disparities: [0.0, 0.05567476153373718], all client accs: [0.5936238765716553, 0.6039478778839111],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:54,895 - utils - INFO - stage2_gradient_single_runtime: 0.006144523620605469
2023-09-28 23:25:54,908 - utils - INFO - 1, epoch: 945, all client loss: [0.6518580317497253, 0.6609382629394531], all pred client disparities: [0.0211077481508255, 0.06374117732048035], all client disparities: [0.0008333333535119891, 0.07371291518211365], all client accs: [0.5940274000167847, 0.6211518049240112],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:54,972 - utils - INFO - stage2_gradient_single_runtime: 0.006057262420654297
2023-09-28 23:25:54,978 - utils - INFO - 1, epoch: 946, all client loss: [0.6546120047569275, 0.6638768315315247], all pred client disparities: [0.01692192256450653, 0.055348366498947144], all client disparities: [0.0, 0.06416931748390198], all client accs: [0.5936238765716553, 0.6130025386810303],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:55,043 - utils - INFO - stage2_gradient_single_runtime: 0.006375551223754883
2023-09-28 23:25:55,048 - utils - INFO - 1, epoch: 947, all client loss: [0.6493472456932068, 0.658295750617981], all pred client disparities: [0.026458818465471268, 0.07052019238471985], all client disparities: [0.004166666883975267, 0.08341169357299805], all client accs: [0.5956416130065918, 0.6302064657211304],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:55,111 - utils - INFO - stage2_gradient_single_runtime: 0.0062253475189208984
2023-09-28 23:25:55,117 - utils - INFO - 1, epoch: 948, all client loss: [0.6511198878288269, 0.660200834274292], all pred client disparities: [0.023480873554944992, 0.06505367159843445], all client disparities: [0.0008333333535119891, 0.07798963785171509], all client accs: [0.5940274000167847, 0.6254980564117432],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:55,184 - utils - INFO - stage2_gradient_single_runtime: 0.007000923156738281
2023-09-28 23:25:55,190 - utils - INFO - 1, epoch: 949, all client loss: [0.6534290909767151, 0.6626707315444946], all pred client disparities: [0.019745534285902977, 0.05799195170402527], all client disparities: [0.0, 0.06758323311805725], all client accs: [0.5936238765716553, 0.6177110075950623],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:55,252 - utils - INFO - stage2_gradient_single_runtime: 0.00653529167175293
2023-09-28 23:25:55,258 - utils - INFO - 1, epoch: 950, all client loss: [0.648238480091095, 0.6571615934371948], all pred client disparities: [0.03014283813536167, 0.07278847694396973], all client disparities: [0.005833333358168602, 0.08949160575866699], all client accs: [0.5964487195014954, 0.63509601354599],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:55,320 - utils - INFO - stage2_gradient_single_runtime: 0.006545543670654297
2023-09-28 23:25:55,326 - utils - INFO - 1, epoch: 951, all client loss: [0.6494356393814087, 0.6584578156471252], all pred client disparities: [0.028220094740390778, 0.06898185610771179], all client disparities: [0.004999999888241291, 0.08320674300193787], all client accs: [0.596045196056366, 0.6320173740386963],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:55,388 - utils - INFO - stage2_gradient_single_runtime: 0.006100893020629883
2023-09-28 23:25:55,393 - utils - INFO - 1, epoch: 952, all client loss: [0.650937020778656, 0.6600738763809204], all pred client disparities: [0.025713959708809853, 0.06429803371429443], all client disparities: [0.0016666667070239782, 0.08001932501792908], all client accs: [0.5944309830665588, 0.6298443078994751],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:55,452 - utils - INFO - stage2_gradient_single_runtime: 0.0062024593353271484
2023-09-28 23:25:55,457 - utils - INFO - 1, epoch: 953, all client loss: [0.6459140777587891, 0.6547328233718872], all pred client disparities: [0.037477705627679825, 0.0782507061958313], all client disparities: [0.012500000186264515, 0.09254544973373413], all client accs: [0.5984665155410767, 0.6463238000869751],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:55,519 - utils - INFO - stage2_gradient_single_runtime: 0.006136655807495117
2023-09-28 23:25:55,525 - utils - INFO - 1, epoch: 954, all client loss: [0.6461295485496521, 0.6549861431121826], all pred client disparities: [0.03800942748785019, 0.07715082168579102], all client disparities: [0.013333333656191826, 0.09244918823242188], all client accs: [0.598870038986206, 0.6461427211761475],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:55,658 - utils - INFO - stage2_gradient_single_runtime: 0.006594181060791016
2023-09-28 23:25:55,663 - utils - INFO - 1, epoch: 955, all client loss: [0.6414436101913452, 0.6499903202056885], all pred client disparities: [0.05139463022351265, 0.08942633867263794], all client disparities: [0.027499999850988388, 0.10594680905342102], all client accs: [0.6053268313407898, 0.6564650535583496],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:55,726 - utils - INFO - stage2_gradient_single_runtime: 0.0062444210052490234
2023-09-28 23:25:55,731 - utils - INFO - 1, epoch: 956, all client loss: [0.6370898485183716, 0.6453379392623901], all pred client disparities: [0.06551521271467209, 0.10010412335395813], all client disparities: [0.04416666552424431, 0.11592182517051697], all client accs: [0.6117836833000183, 0.6649764776229858],  alphas:tensor([0.5040, 0.0000, 0.0000, 0.4960], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:55,792 - utils - INFO - stage2_gradient_single_runtime: 0.006555080413818359
2023-09-28 23:25:55,799 - utils - INFO - 1, epoch: 957, all client loss: [0.6408058404922485, 0.6492419838905334], all pred client disparities: [0.05267415940761566, 0.09096941351890564], all client disparities: [0.029999999329447746, 0.10732483863830566], all client accs: [0.6065375208854675, 0.6570083498954773],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:55,864 - utils - INFO - stage2_gradient_single_runtime: 0.0060999393463134766
2023-09-28 23:25:55,868 - utils - INFO - 1, epoch: 958, all client loss: [0.6364991068840027, 0.6446405649185181], all pred client disparities: [0.06673584133386612, 0.10140827298164368], all client disparities: [0.0446048304438591, 0.117299884557724], all client accs: [0.6129943132400513, 0.6658819317817688],  alphas:tensor([0.5040, 0.0000, 0.0000, 0.4960], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:55,925 - utils - INFO - stage2_gradient_single_runtime: 0.0062978267669677734
2023-09-28 23:25:55,930 - utils - INFO - 1, epoch: 959, all client loss: [0.6401655673980713, 0.6484883427619934], all pred client disparities: [0.05398436263203621, 0.09250444173812866], all client disparities: [0.029999999329447746, 0.10827144980430603], all client accs: [0.6061339378356934, 0.6579138040542603],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:55,946 - utils - INFO - valid: True, epoch: 959, loss: [0.6328927278518677, 0.648077130317688], accuracy: [0.6304000020027161, 0.6523635983467102], mean_accuracy:0.6413818001747131,variance_accuracy:0.01098179817199707, disparity: [0.044743429869413376, 0.1221296489238739], mean_disparity:0.08343653939664364,variance_disparity:0.03869310952723026, pred_disparity: [0.06794818490743637, 0.11372390389442444]
2023-09-28 23:25:55,959 - utils - INFO - global_valid: True, epoch: 959,  global_loss: 0.6433320641517639, global_accuracy: 0.6988205282112845,  global_disparity:0.11152276396751404, global_pred_disparity: 0.10992486774921417,
2023-09-28 23:25:56,020 - utils - INFO - stage2_gradient_single_runtime: 0.0062105655670166016
2023-09-28 23:25:56,025 - utils - INFO - 1, epoch: 960, all client loss: [0.6359061002731323, 0.6439382433891296], all pred client disparities: [0.06798357516527176, 0.10270706564188004], all client disparities: [0.04710482805967331, 0.11833027005195618], all client accs: [0.614205002784729, 0.6675118207931519],  alphas:tensor([0.5041, 0.0000, 0.0000, 0.4959], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:56,090 - utils - INFO - stage2_gradient_single_runtime: 0.006712198257446289
2023-09-28 23:25:56,095 - utils - INFO - 1, epoch: 961, all client loss: [0.6395230293273926, 0.6477298736572266], all pred client disparities: [0.055324673652648926, 0.0940304696559906], all client disparities: [0.03166666626930237, 0.10861283540725708], all client accs: [0.6065375208854675, 0.659724771976471],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:56,155 - utils - INFO - stage2_gradient_single_runtime: 0.006279468536376953
2023-09-28 23:25:56,160 - utils - INFO - 1, epoch: 962, all client loss: [0.6353110074996948, 0.6432312726974487], all pred client disparities: [0.06925767660140991, 0.1039995551109314], all client disparities: [0.0475429967045784, 0.12108626961708069], all client accs: [0.615415632724762, 0.6691416501998901],  alphas:tensor([0.5041, 0.0000, 0.0000, 0.4959], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:56,220 - utils - INFO - stage2_gradient_single_runtime: 0.006058454513549805
2023-09-28 23:25:56,225 - utils - INFO - 1, epoch: 963, all client loss: [0.638878583908081, 0.6469666957855225], all pred client disparities: [0.056694626808166504, 0.09554648399353027], all client disparities: [0.036666665226221085, 0.11162647604942322], all client accs: [0.6089588403701782, 0.6602680683135986],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:56,286 - utils - INFO - stage2_gradient_single_runtime: 0.006157636642456055
2023-09-28 23:25:56,293 - utils - INFO - 1, epoch: 964, all client loss: [0.6347141861915588, 0.6425199508666992], all pred client disparities: [0.07055747509002686, 0.10528501868247986], all client disparities: [0.05004299804568291, 0.12065485119819641], all client accs: [0.6162227392196655, 0.6702281832695007],  alphas:tensor([0.5041, 0.0000, 0.0000, 0.4959], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:56,352 - utils - INFO - stage2_gradient_single_runtime: 0.00621485710144043
2023-09-28 23:25:56,357 - utils - INFO - 1, epoch: 965, all client loss: [0.6382322311401367, 0.6461993455886841], all pred client disparities: [0.05809374153614044, 0.09705185890197754], all client disparities: [0.03750000149011612, 0.11239925026893616], all client accs: [0.6093623638153076, 0.6617168188095093],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:56,486 - utils - INFO - stage2_gradient_single_runtime: 0.006392717361450195
2023-09-28 23:25:56,492 - utils - INFO - 1, epoch: 966, all client loss: [0.6341156959533691, 0.6418046951293945], all pred client disparities: [0.07188237458467484, 0.10656288266181946], all client disparities: [0.052542995661497116, 0.12117007374763489], all client accs: [0.6174333691596985, 0.670952558517456],  alphas:tensor([0.5042, 0.0000, 0.0000, 0.4958], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:56,553 - utils - INFO - stage2_gradient_single_runtime: 0.006040096282958984
2023-09-28 23:25:56,558 - utils - INFO - 1, epoch: 967, all client loss: [0.6375843286514282, 0.6454280018806458], all pred client disparities: [0.05952158570289612, 0.09854590892791748], all client disparities: [0.038333334028720856, 0.11239925026893616], all client accs: [0.6089588403701782, 0.6633466482162476],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:56,619 - utils - INFO - stage2_gradient_single_runtime: 0.006547212600708008
2023-09-28 23:25:56,624 - utils - INFO - 1, epoch: 968, all client loss: [0.6335157155990601, 0.6410855650901794], all pred client disparities: [0.07323183119297028, 0.10783261060714722], all client disparities: [0.05337633192539215, 0.12048107385635376], all client accs: [0.6174333691596985, 0.6720391511917114],  alphas:tensor([0.5042, 0.0000, 0.0000, 0.4958], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:56,685 - utils - INFO - stage2_gradient_single_runtime: 0.00629425048828125
2023-09-28 23:25:56,691 - utils - INFO - 1, epoch: 969, all client loss: [0.6369349956512451, 0.6446528434753418], all pred client disparities: [0.06097777560353279, 0.10002794861793518], all client disparities: [0.03916666656732559, 0.11473008990287781], all client accs: [0.6093623638153076, 0.6629844307899475],  alphas:tensor([0.5033, 0.0000, 0.0000, 0.4967], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:56,753 - utils - INFO - stage2_gradient_single_runtime: 0.007012367248535156
2023-09-28 23:25:56,761 - utils - INFO - 1, epoch: 970, all client loss: [0.6404629349708557, 0.6483320593833923], all pred client disparities: [0.0494639053940773, 0.09158137440681458], all client disparities: [0.027499999850988388, 0.10526403784751892], all client accs: [0.6053268313407898, 0.6580948829650879],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:56,820 - utils - INFO - stage2_gradient_single_runtime: 0.006300210952758789
2023-09-28 23:25:56,826 - utils - INFO - 1, epoch: 971, all client loss: [0.6393564343452454, 0.6472270488739014], all pred client disparities: [0.0541960708796978, 0.09358072280883789], all client disparities: [0.03166666626930237, 0.10800760984420776], all client accs: [0.6069410443305969, 0.658819317817688],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:56,886 - utils - INFO - stage2_gradient_single_runtime: 0.006113529205322266
2023-09-28 23:25:56,892 - utils - INFO - 1, epoch: 972, all client loss: [0.6351628303527832, 0.6427556872367859], all pred client disparities: [0.06783388555049896, 0.1033446192741394], all client disparities: [0.04587633162736893, 0.11987587809562683], all client accs: [0.6146085262298584, 0.6680550575256348],  alphas:tensor([0.5037, 0.0000, 0.0000, 0.4963], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:56,958 - utils - INFO - stage2_gradient_single_runtime: 0.0075168609619140625
2023-09-28 23:25:56,964 - utils - INFO - 1, epoch: 973, all client loss: [0.6386390328407288, 0.6463846564292908], all pred client disparities: [0.05584947019815445, 0.09527599811553955], all client disparities: [0.03583333268761635, 0.10972702503204346], all client accs: [0.608555257320404, 0.6604491472244263],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:57,025 - utils - INFO - stage2_gradient_single_runtime: 0.005918025970458984
2023-09-28 23:25:57,029 - utils - INFO - 1, epoch: 974, all client loss: [0.6344982981681824, 0.6419705748558044], all pred client disparities: [0.06943343579769135, 0.10479307174682617], all client disparities: [0.04920966178178787, 0.11944445967674255], all client accs: [0.6158192157745361, 0.6695038080215454],  alphas:tensor([0.5038, 0.0000, 0.0000, 0.4962], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:57,090 - utils - INFO - stage2_gradient_single_runtime: 0.006181955337524414
2023-09-28 23:25:57,094 - utils - INFO - 1, epoch: 975, all client loss: [0.6379262804985046, 0.6455450654029846], all pred client disparities: [0.05751396715641022, 0.09694033861160278], all client disparities: [0.03750000149011612, 0.11153644323348999], all client accs: [0.6093623638153076, 0.6608113050460815],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:57,157 - utils - INFO - stage2_gradient_single_runtime: 0.006447553634643555
2023-09-28 23:25:57,162 - utils - INFO - 1, epoch: 976, all client loss: [0.6338382363319397, 0.6411880850791931], all pred client disparities: [0.07103686779737473, 0.10621628165245056], all client disparities: [0.052542995661497116, 0.12064865231513977], all client accs: [0.6174333691596985, 0.6713147759437561],  alphas:tensor([0.5038, 0.0000, 0.0000, 0.4962], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:57,225 - utils - INFO - stage2_gradient_single_runtime: 0.006074428558349609
2023-09-28 23:25:57,230 - utils - INFO - 1, epoch: 977, all client loss: [0.6372177600860596, 0.6447078585624695], all pred client disparities: [0.059190746396780014, 0.09857535362243652], all client disparities: [0.038333334028720856, 0.11162024736404419], all client accs: [0.6089588403701782, 0.6620789766311646],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:57,294 - utils - INFO - stage2_gradient_single_runtime: 0.006079912185668945
2023-09-28 23:25:57,299 - utils - INFO - 1, epoch: 978, all client loss: [0.6331819295883179, 0.6404075622558594], all pred client disparities: [0.0726456418633461, 0.1076156497001648], all client disparities: [0.05337633192539215, 0.12082245945930481], all client accs: [0.6174333691596985, 0.6711336374282837],  alphas:tensor([0.5039, 0.0000, 0.0000, 0.4961], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:57,415 - utils - INFO - stage2_gradient_single_runtime: 0.0068743228912353516
2023-09-28 23:25:57,422 - utils - INFO - 1, epoch: 979, all client loss: [0.636512815952301, 0.6438724994659424], all pred client disparities: [0.060880836099386215, 0.10018259286880493], all client disparities: [0.03999999910593033, 0.11299824714660645], all client accs: [0.6097659468650818, 0.6635277271270752],  alphas:tensor([0.5030, 0.0000, 0.0000, 0.4970], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:57,436 - utils - INFO - valid: True, epoch: 979, loss: [0.6362942457199097, 0.6513274908065796], accuracy: [0.6207999587059021, 0.634181797504425], mean_accuracy:0.6274908781051636,variance_accuracy:0.006690919399261475, disparity: [0.024822695180773735, 0.11431160569190979], mean_disparity:0.06956715043634176,variance_disparity:0.04474445525556803, pred_disparity: [0.04992944747209549, 0.10331892967224121]
2023-09-28 23:25:57,448 - utils - INFO - global_valid: True, epoch: 979,  global_loss: 0.6466296911239624, global_accuracy: 0.6864415766306523,  global_disparity:0.1010109931230545, global_pred_disparity: 0.09795702993869781,
2023-09-28 23:25:57,508 - utils - INFO - stage2_gradient_single_runtime: 0.006242990493774414
2023-09-28 23:25:57,513 - utils - INFO - 1, epoch: 980, all client loss: [0.6399419903755188, 0.6474393606185913], all pred client disparities: [0.04980666562914848, 0.09216928482055664], all client disparities: [0.027499999850988388, 0.10680961608886719], all client accs: [0.6053268313407898, 0.6573705673217773],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:57,573 - utils - INFO - stage2_gradient_single_runtime: 0.006184577941894531
2023-09-28 23:25:57,579 - utils - INFO - 1, epoch: 981, all client loss: [0.6387505531311035, 0.6462675929069519], all pred client disparities: [0.05471320450305939, 0.09427416324615479], all client disparities: [0.03333333507180214, 0.10946321487426758], all client accs: [0.6073446273803711, 0.6593625545501709],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:57,642 - utils - INFO - stage2_gradient_single_runtime: 0.006124973297119141
2023-09-28 23:25:57,647 - utils - INFO - 1, epoch: 982, all client loss: [0.6346068978309631, 0.641855776309967], all pred client disparities: [0.06811868399381638, 0.1037064790725708], all client disparities: [0.0475429967045784, 0.11935442686080933], all client accs: [0.615415632724762, 0.6684172749519348],  alphas:tensor([0.5035, 0.0000, 0.0000, 0.4965], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:57,709 - utils - INFO - stage2_gradient_single_runtime: 0.005964517593383789
2023-09-28 23:25:57,714 - utils - INFO - 1, epoch: 983, all client loss: [0.6379836201667786, 0.64537113904953], all pred client disparities: [0.05657177418470383, 0.09606891870498657], all client disparities: [0.03750000149011612, 0.11153021454811096], all client accs: [0.6093623638153076, 0.6606302261352539],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:57,775 - utils - INFO - stage2_gradient_single_runtime: 0.006230354309082031
2023-09-28 23:25:57,781 - utils - INFO - 1, epoch: 984, all client loss: [0.6338964104652405, 0.6410202980041504], all pred client disparities: [0.06992831826210022, 0.10524845123291016], all client disparities: [0.05087633058428764, 0.11969581246376038], all client accs: [0.6166263222694397, 0.669684886932373],  alphas:tensor([0.5035, 0.0000, 0.0000, 0.4965], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:57,842 - utils - INFO - stage2_gradient_single_runtime: 0.006626129150390625
2023-09-28 23:25:57,847 - utils - INFO - 1, epoch: 985, all client loss: [0.6372256875038147, 0.6444821953773499], all pred client disparities: [0.05843031406402588, 0.09781995415687561], all client disparities: [0.038333334028720856, 0.11239302158355713], all client accs: [0.6089588403701782, 0.6608113050460815],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:57,913 - utils - INFO - stage2_gradient_single_runtime: 0.0062427520751953125
2023-09-28 23:25:57,920 - utils - INFO - 1, epoch: 986, all client loss: [0.6331942081451416, 0.6401916742324829], all pred client disparities: [0.0717286616563797, 0.10675391554832458], all client disparities: [0.05337633192539215, 0.12038484215736389], all client accs: [0.6178369522094727, 0.670952558517456],  alphas:tensor([0.5036, 0.0000, 0.0000, 0.4964], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:57,982 - utils - INFO - stage2_gradient_single_runtime: 0.006320476531982422
2023-09-28 23:25:57,987 - utils - INFO - 1, epoch: 987, all client loss: [0.6364758014678955, 0.643599808216095], all pred client disparities: [0.060290876775979996, 0.099530428647995], all client disparities: [0.03999999910593033, 0.1134234368801117], all client accs: [0.6097659468650818, 0.6626222729682922],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:58,042 - utils - INFO - stage2_gradient_single_runtime: 0.006223201751708984
2023-09-28 23:25:58,045 - utils - INFO - 1, epoch: 988, all client loss: [0.6324995756149292, 0.6393690705299377], all pred client disparities: [0.07352235913276672, 0.1082257628440857], all client disparities: [0.05837633088231087, 0.12090003490447998], all client accs: [0.6194511651992798, 0.6725823879241943],  alphas:tensor([0.5036, 0.0000, 0.0000, 0.4964], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:58,099 - utils - INFO - stage2_gradient_single_runtime: 0.006261348724365234
2023-09-28 23:25:58,103 - utils - INFO - 1, epoch: 989, all client loss: [0.6357329487800598, 0.6427231431007385], all pred client disparities: [0.06215530261397362, 0.10120320320129395], all client disparities: [0.04333333298563957, 0.11419621109962463], all client accs: [0.6113801002502441, 0.6637088060379028],  alphas:tensor([0.5029, 0.0000, 0.0000, 0.4971], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:58,207 - utils - INFO - stage2_gradient_single_runtime: 0.006152153015136719
2023-09-28 23:25:58,210 - utils - INFO - 1, epoch: 990, all client loss: [0.6390619874000549, 0.6461768746376038], all pred client disparities: [0.051388274878263474, 0.0936441421508789], all client disparities: [0.029999999329447746, 0.10740864276885986], all client accs: [0.6065375208854675, 0.6570083498954773],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:58,270 - utils - INFO - stage2_gradient_single_runtime: 0.0071833133697509766
2023-09-28 23:25:58,273 - utils - INFO - 1, epoch: 991, all client loss: [0.6377035975456238, 0.64485102891922], all pred client disparities: [0.0568058043718338, 0.09601455926895142], all client disparities: [0.03750000149011612, 0.11031976342201233], all client accs: [0.6093623638153076, 0.6602680683135986],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:58,330 - utils - INFO - stage2_gradient_single_runtime: 0.006171464920043945
2023-09-28 23:25:58,333 - utils - INFO - 1, epoch: 992, all client loss: [0.6336408853530884, 0.6405304074287415], all pred client disparities: [0.07002246379852295, 0.10500219464302063], all client disparities: [0.05170966684818268, 0.12012100219726562], all client accs: [0.6170298457145691, 0.6702281832695007],  alphas:tensor([0.5034, 0.0000, 0.0000, 0.4966], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:58,399 - utils - INFO - stage2_gradient_single_runtime: 0.006057024002075195
2023-09-28 23:25:58,404 - utils - INFO - 1, epoch: 993, all client loss: [0.636910080909729, 0.6439246535301208], all pred client disparities: [0.05880420655012131, 0.09783506393432617], all client disparities: [0.03916666656732559, 0.11221301555633545], all client accs: [0.6093623638153076, 0.6608113050460815],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:58,468 - utils - INFO - stage2_gradient_single_runtime: 0.006640434265136719
2023-09-28 23:25:58,474 - utils - INFO - 1, epoch: 994, all client loss: [0.6329056024551392, 0.6396670341491699], all pred client disparities: [0.0719653069972992, 0.10657346248626709], all client disparities: [0.05420966446399689, 0.12037861347198486], all client accs: [0.6178369522094727, 0.6713147759437561],  alphas:tensor([0.5034, 0.0000, 0.0000, 0.4966], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:58,538 - utils - INFO - stage2_gradient_single_runtime: 0.00646662712097168
2023-09-28 23:25:58,543 - utils - INFO - 1, epoch: 995, all client loss: [0.6361275315284729, 0.6430081725120544], all pred client disparities: [0.06079716980457306, 0.09960675239562988], all client disparities: [0.0416666679084301, 0.11384862661361694], all client accs: [0.6105730533599854, 0.6620789766311646],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:58,608 - utils - INFO - stage2_gradient_single_runtime: 0.006570577621459961
2023-09-28 23:25:58,611 - utils - INFO - 1, epoch: 996, all client loss: [0.6321806311607361, 0.6388126015663147], all pred client disparities: [0.0738927498459816, 0.10810378193855286], all client disparities: [0.0592096671462059, 0.12175661325454712], all client accs: [0.6198546886444092, 0.6720391511917114],  alphas:tensor([0.5035, 0.0000, 0.0000, 0.4965], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:58,666 - utils - INFO - stage2_gradient_single_runtime: 0.006003856658935547
2023-09-28 23:25:58,673 - utils - INFO - 1, epoch: 997, all client loss: [0.6353548169136047, 0.6421001553535461], all pred client disparities: [0.06278708577156067, 0.10133352875709534], all client disparities: [0.04416666552424431, 0.11513662338256836], all client accs: [0.6117836833000183, 0.6638898849487305],  alphas:tensor([0.5028, 0.0000, 0.0000, 0.4972], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:58,734 - utils - INFO - stage2_gradient_single_runtime: 0.0062656402587890625
2023-09-28 23:25:58,740 - utils - INFO - 1, epoch: 998, all client loss: [0.6386216282844543, 0.6454845666885376], all pred client disparities: [0.0522344671189785, 0.09405729174613953], all client disparities: [0.03166666626930237, 0.10912182927131653], all client accs: [0.6069410443305969, 0.6580948829650879],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:58,802 - utils - INFO - stage2_gradient_single_runtime: 0.006358146667480469
2023-09-28 23:25:58,809 - utils - INFO - 1, epoch: 999, all client loss: [0.6371687650680542, 0.6440750956535339], all pred client disparities: [0.057931795716285706, 0.09655651450157166], all client disparities: [0.038333334028720856, 0.11074495315551758], all client accs: [0.6089588403701782, 0.6599058508872986],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:58,824 - utils - INFO - valid: True, epoch: 999, loss: [0.6302148103713989, 0.6445249915122986], accuracy: [0.6335999965667725, 0.6559999585151672], mean_accuracy:0.6447999775409698,variance_accuracy:0.011199980974197388, disparity: [0.05183562636375427, 0.12558382749557495], mean_disparity:0.08870972692966461,variance_disparity:0.03687410056591034, pred_disparity: [0.07072213292121887, 0.11648300290107727]
2023-09-28 23:25:58,838 - utils - INFO - global_valid: True, epoch: 999,  global_loss: 0.6400531530380249, global_accuracy: 0.6999859943977591,  global_disparity:0.11592677235603333, global_pred_disparity: 0.11284063756465912,
2023-09-28 23:25:58,895 - utils - INFO - stage2_gradient_single_runtime: 0.0060482025146484375
2023-09-28 23:25:58,900 - utils - INFO - 1, epoch: 1000, all client loss: [0.6331482529640198, 0.6398027539253235], all pred client disparities: [0.0710282176733017, 0.1052880585193634], all client disparities: [0.05337633192539215, 0.11934196949005127], all client accs: [0.6178369522094727, 0.6691416501998901],  alphas:tensor([0.5032, 0.0000, 0.0000, 0.4968], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:58,964 - utils - INFO - stage2_gradient_single_runtime: 0.006352663040161133
2023-09-28 23:25:58,970 - utils - INFO - 1, epoch: 1001, all client loss: [0.6363517642021179, 0.6431239247322083], all pred client disparities: [0.060036271810531616, 0.09840840101242065], all client disparities: [0.040833331644535065, 0.11263817548751831], all client accs: [0.6101694703102112, 0.6608113050460815],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:59,030 - utils - INFO - stage2_gradient_single_runtime: 0.006316184997558594
2023-09-28 23:25:59,036 - utils - INFO - 1, epoch: 1002, all client loss: [0.6323911547660828, 0.6389161944389343], all pred client disparities: [0.07307375967502594, 0.10689175128936768], all client disparities: [0.05754299461841583, 0.11916819214820862], all client accs: [0.6190475821495056, 0.6707714796066284],  alphas:tensor([0.5033, 0.0000, 0.0000, 0.4967], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:59,098 - utils - INFO - stage2_gradient_single_runtime: 0.006011486053466797
2023-09-28 23:25:59,101 - utils - INFO - 1, epoch: 1003, all client loss: [0.6355475187301636, 0.6421843767166138], all pred client disparities: [0.062130749225616455, 0.10020717978477478], all client disparities: [0.04333333298563957, 0.11539420485496521], all client accs: [0.6113801002502441, 0.6618978977203369],  alphas:tensor([0.5026, 0.0000, 0.0000, 0.4974], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:59,160 - utils - INFO - stage2_gradient_single_runtime: 0.0062067508697509766
2023-09-28 23:25:59,166 - utils - INFO - 1, epoch: 1004, all client loss: [0.6387901306152344, 0.6455430388450623], all pred client disparities: [0.0517498143017292, 0.09303992986679077], all client disparities: [0.030833333730697632, 0.10730618238449097], all client accs: [0.6065375208854675, 0.6584571003913879],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:59,304 - utils - INFO - stage2_gradient_single_runtime: 0.006815671920776367
2023-09-28 23:25:59,311 - utils - INFO - 1, epoch: 1005, all client loss: [0.6373440623283386, 0.64415043592453], all pred client disparities: [0.05736615136265755, 0.09549233317375183], all client disparities: [0.03750000149011612, 0.10979214310646057], all client accs: [0.608555257320404, 0.6595436334609985],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:59,374 - utils - INFO - stage2_gradient_single_runtime: 0.0061740875244140625
2023-09-28 23:25:59,381 - utils - INFO - 1, epoch: 1006, all client loss: [0.6333132982254028, 0.6398692727088928], all pred client disparities: [0.07040472328662872, 0.10419490933418274], all client disparities: [0.052542995661497116, 0.11666351556777954], all client accs: [0.6174333691596985, 0.6680550575256348],  alphas:tensor([0.5031, 0.0000, 0.0000, 0.4969], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:59,446 - utils - INFO - stage2_gradient_single_runtime: 0.006325244903564453
2023-09-28 23:25:59,452 - utils - INFO - 1, epoch: 1007, all client loss: [0.6364961862564087, 0.6431680917739868], all pred client disparities: [0.059570327401161194, 0.09741246700286865], all client disparities: [0.040833331644535065, 0.1105649471282959], all client accs: [0.6101694703102112, 0.6611735224723816],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:59,515 - utils - INFO - stage2_gradient_single_runtime: 0.00636744499206543
2023-09-28 23:25:59,522 - utils - INFO - 1, epoch: 1008, all client loss: [0.6325273513793945, 0.6389536261558533], all pred client disparities: [0.07255490869283676, 0.1058616042137146], all client disparities: [0.05754299461841583, 0.11898812651634216], all client accs: [0.6190475821495056, 0.6702281832695007],  alphas:tensor([0.5032, 0.0000, 0.0000, 0.4968], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:59,586 - utils - INFO - stage2_gradient_single_runtime: 0.006144523620605469
2023-09-28 23:25:59,592 - utils - INFO - 1, epoch: 1009, all client loss: [0.6356635689735413, 0.642200231552124], all pred client disparities: [0.06175854802131653, 0.09927248954772949], all client disparities: [0.042500000447034836, 0.11348855495452881], all client accs: [0.6109765768051147, 0.6633466482162476],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:59,656 - utils - INFO - stage2_gradient_single_runtime: 0.006495237350463867
2023-09-28 23:25:59,663 - utils - INFO - 1, epoch: 1010, all client loss: [0.6317556500434875, 0.6380513310432434], all pred client disparities: [0.07467735558748245, 0.10747739672660828], all client disparities: [0.06004299595952034, 0.12019234895706177], all client accs: [0.6202582716941833, 0.6722202301025391],  alphas:tensor([0.5032, 0.0000, 0.0000, 0.4968], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:59,725 - utils - INFO - stage2_gradient_single_runtime: 0.006397724151611328
2023-09-28 23:25:59,732 - utils - INFO - 1, epoch: 1011, all client loss: [0.6348446011543274, 0.6412450671195984], all pred client disparities: [0.06393394619226456, 0.10107764601707458], all client disparities: [0.04377150163054466, 0.11693358421325684], all client accs: [0.6125907897949219, 0.6635277271270752],  alphas:tensor([0.5026, 0.0000, 0.0000, 0.4974], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:59,795 - utils - INFO - stage2_gradient_single_runtime: 0.005981922149658203
2023-09-28 23:25:59,800 - utils - INFO - 1, epoch: 1012, all client loss: [0.638022243976593, 0.644531786441803], all pred client disparities: [0.053675271570682526, 0.09421446919441223], all client disparities: [0.03500000014901161, 0.10686853528022766], all client accs: [0.6081517338752747, 0.6591814756393433],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:59,863 - utils - INFO - stage2_gradient_single_runtime: 0.00626373291015625
2023-09-28 23:25:59,870 - utils - INFO - 1, epoch: 1013, all client loss: [0.6364195942878723, 0.6429895758628845], all pred client disparities: [0.05983760952949524, 0.09690377116203308], all client disparities: [0.0416666679084301, 0.11012732982635498], all client accs: [0.6105730533599854, 0.6611735224723816],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:25:59,935 - utils - INFO - stage2_gradient_single_runtime: 0.006414890289306641
2023-09-28 23:25:59,941 - utils - INFO - 1, epoch: 1014, all client loss: [0.6324577331542969, 0.6387837529182434], all pred client disparities: [0.07277576625347137, 0.10526058077812195], all client disparities: [0.05754299461841583, 0.11855050921440125], all client accs: [0.6190475821495056, 0.6695038080215454],  alphas:tensor([0.5031, 0.0000, 0.0000, 0.4969], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:00,009 - utils - INFO - stage2_gradient_single_runtime: 0.00680994987487793
2023-09-28 23:26:00,014 - utils - INFO - 1, epoch: 1015, all client loss: [0.6355664730072021, 0.6420010328292847], all pred client disparities: [0.062099844217300415, 0.09880036115646362], all client disparities: [0.042500000447034836, 0.11348232626914978], all client accs: [0.6109765768051147, 0.6629844307899475],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:00,076 - utils - INFO - stage2_gradient_single_runtime: 0.006189584732055664
2023-09-28 23:26:00,083 - utils - INFO - 1, epoch: 1016, all client loss: [0.6316668391227722, 0.6378622651100159], all pred client disparities: [0.0749717503786087, 0.10691177845001221], all client disparities: [0.06004299595952034, 0.11811909079551697], all client accs: [0.6202582716941833, 0.670952558517456],  alphas:tensor([0.5031, 0.0000, 0.0000, 0.4969], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:00,200 - utils - INFO - stage2_gradient_single_runtime: 0.006115436553955078
2023-09-28 23:26:00,206 - utils - INFO - 1, epoch: 1017, all client loss: [0.6347284317016602, 0.6410267949104309], all pred client disparities: [0.0643455758690834, 0.10063841938972473], all client disparities: [0.04377150163054466, 0.11451271176338196], all client accs: [0.6125907897949219, 0.6651575565338135],  alphas:tensor([0.5025, 0.0000, 0.0000, 0.4975], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:00,271 - utils - INFO - stage2_gradient_single_runtime: 0.006139993667602539
2023-09-28 23:26:00,277 - utils - INFO - 1, epoch: 1018, all client loss: [0.6378772854804993, 0.644282877445221], all pred client disparities: [0.054182812571525574, 0.09391650557518005], all client disparities: [0.03583333268761635, 0.10867175459861755], all client accs: [0.608555257320404, 0.6582760214805603],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:00,341 - utils - INFO - stage2_gradient_single_runtime: 0.006345987319946289
2023-09-28 23:26:00,349 - utils - INFO - 1, epoch: 1019, all client loss: [0.6338253617286682, 0.6399915814399719], all pred client disparities: [0.06688165664672852, 0.10258078575134277], all client disparities: [0.048376329243183136, 0.11640593409538269], all client accs: [0.615415632724762, 0.6660630702972412],  alphas:tensor([0.5026, 0.0000, 0.0000, 0.4974], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:00,363 - utils - INFO - valid: True, epoch: 1019, loss: [0.6335278153419495, 0.6476343274116516], accuracy: [0.6223999857902527, 0.6370909214019775], mean_accuracy:0.6297454535961151,variance_accuracy:0.007345467805862427, disparity: [0.03191489353775978, 0.118215411901474], mean_disparity:0.07506515271961689,variance_disparity:0.04315025918185711, pred_disparity: [0.05664394423365593, 0.10752815008163452]
2023-09-28 23:26:00,374 - utils - INFO - global_valid: True, epoch: 1019,  global_loss: 0.6432260870933533, global_accuracy: 0.6897734093637455,  global_disparity:0.10580076277256012, global_pred_disparity: 0.1028980165719986,
2023-09-28 23:26:00,445 - utils - INFO - stage2_gradient_single_runtime: 0.007359743118286133
2023-09-28 23:26:00,450 - utils - INFO - 1, epoch: 1020, all client loss: [0.6369325518608093, 0.6432009339332581], all pred client disparities: [0.05668623000383377, 0.09604871273040771], all client disparities: [0.03750000149011612, 0.1093607246875763], all client accs: [0.608555257320404, 0.6591814756393433],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:00,512 - utils - INFO - stage2_gradient_single_runtime: 0.006150484085083008
2023-09-28 23:26:00,517 - utils - INFO - 1, epoch: 1021, all client loss: [0.6329492330551147, 0.6389830112457275], all pred client disparities: [0.06935876607894897, 0.10443949699401855], all client disparities: [0.052542995661497116, 0.11692112684249878], all client accs: [0.6174333691596985, 0.6680550575256348],  alphas:tensor([0.5027, 0.0000, 0.0000, 0.4973], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:00,582 - utils - INFO - stage2_gradient_single_runtime: 0.006193399429321289
2023-09-28 23:26:00,587 - utils - INFO - 1, epoch: 1022, all client loss: [0.636013388633728, 0.642143964767456], all pred client disparities: [0.05915428325533867, 0.0980941653251648], all client disparities: [0.040833331644535065, 0.11090633273124695], all client accs: [0.6101694703102112, 0.6611735224723816],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:00,652 - utils - INFO - stage2_gradient_single_runtime: 0.006058454513549805
2023-09-28 23:26:00,658 - utils - INFO - 1, epoch: 1023, all client loss: [0.6320968866348267, 0.6379976272583008], all pred client disparities: [0.07178396731615067, 0.1062239408493042], all client disparities: [0.056709665805101395, 0.1192457377910614], all client accs: [0.6186440587043762, 0.6695038080215454],  alphas:tensor([0.5028, 0.0000, 0.0000, 0.4972], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:00,716 - utils - INFO - stage2_gradient_single_runtime: 0.0062274932861328125
2023-09-28 23:26:00,721 - utils - INFO - 1, epoch: 1024, all client loss: [0.6351167559623718, 0.641109049320221], all pred client disparities: [0.06159145012497902, 0.10006195306777954], all client disparities: [0.04333333298563957, 0.11348855495452881], all client accs: [0.6113801002502441, 0.6633466482162476],  alphas:tensor([0.5022, 0.0000, 0.0000, 0.4978], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:00,780 - utils - INFO - stage2_gradient_single_runtime: 0.006028175354003906
2023-09-28 23:26:00,787 - utils - INFO - 1, epoch: 1025, all client loss: [0.6382074356079102, 0.6442958116531372], all pred client disparities: [0.05190900340676308, 0.09349697828292847], all client disparities: [0.032499998807907104, 0.1071261465549469], all client accs: [0.6073446273803711, 0.6586381793022156],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:00,851 - utils - INFO - stage2_gradient_single_runtime: 0.0063593387603759766
2023-09-28 23:26:00,857 - utils - INFO - 1, epoch: 1026, all client loss: [0.6366721987724304, 0.6428495049476624], all pred client disparities: [0.057606518268585205, 0.09598338603973389], all client disparities: [0.03916666656732559, 0.10900688171386719], all client accs: [0.6093623638153076, 0.6602680683135986],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:00,921 - utils - INFO - stage2_gradient_single_runtime: 0.006167411804199219
2023-09-28 23:26:00,926 - utils - INFO - 1, epoch: 1027, all client loss: [0.6327082514762878, 0.6386526226997375], all pred client disparities: [0.07025329768657684, 0.10423943400382996], all client disparities: [0.05337633192539215, 0.11768770217895508], all client accs: [0.6174333691596985, 0.6678739786148071],  alphas:tensor([0.5026, 0.0000, 0.0000, 0.4974], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:01,057 - utils - INFO - stage2_gradient_single_runtime: 0.006217241287231445
2023-09-28 23:26:01,062 - utils - INFO - 1, epoch: 1028, all client loss: [0.6357429027557373, 0.6417825222015381], all pred client disparities: [0.06011994183063507, 0.09803467988967896], all client disparities: [0.042500000447034836, 0.11115771532058716], all client accs: [0.6109765768051147, 0.6615356802940369],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:01,127 - utils - INFO - stage2_gradient_single_runtime: 0.005992889404296875
2023-09-28 23:26:01,133 - utils - INFO - 1, epoch: 1029, all client loss: [0.6318463683128357, 0.637657880783081], all pred client disparities: [0.07271872460842133, 0.10603222250938416], all client disparities: [0.0592096671462059, 0.11751389503479004], all client accs: [0.6198546886444092, 0.669684886932373],  alphas:tensor([0.5027, 0.0000, 0.0000, 0.4973], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:01,195 - utils - INFO - stage2_gradient_single_runtime: 0.006384849548339844
2023-09-28 23:26:01,202 - utils - INFO - 1, epoch: 1030, all client loss: [0.6348365545272827, 0.6407380104064941], all pred client disparities: [0.06260109692811966, 0.10000786185264587], all client disparities: [0.04416666552424431, 0.11399751901626587], all client accs: [0.6117836833000183, 0.6633466482162476],  alphas:tensor([0.5022, 0.0000, 0.0000, 0.4978], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:01,267 - utils - INFO - stage2_gradient_single_runtime: 0.0063478946685791016
2023-09-28 23:26:01,273 - utils - INFO - 1, epoch: 1031, all client loss: [0.6378989219665527, 0.6438950300216675], all pred client disparities: [0.05295766517519951, 0.09358876943588257], all client disparities: [0.03500000014901161, 0.10737752914428711], all client accs: [0.6081517338752747, 0.6571894288063049],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:01,339 - utils - INFO - stage2_gradient_single_runtime: 0.006352424621582031
2023-09-28 23:26:01,346 - utils - INFO - 1, epoch: 1032, all client loss: [0.6362766623497009, 0.6423661112785339], all pred client disparities: [0.05896575748920441, 0.09619906544685364], all client disparities: [0.0416666679084301, 0.10916826128959656], all client accs: [0.6105730533599854, 0.6611735224723816],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:01,408 - utils - INFO - stage2_gradient_single_runtime: 0.006239414215087891
2023-09-28 23:26:01,413 - utils - INFO - 1, epoch: 1033, all client loss: [0.6323411464691162, 0.6381994485855103], all pred client disparities: [0.07158925384283066, 0.10429024696350098], all client disparities: [0.056709665805101395, 0.11725005507469177], all client accs: [0.6186440587043762, 0.6682361364364624],  alphas:tensor([0.5026, 0.0000, 0.0000, 0.4974], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:01,477 - utils - INFO - stage2_gradient_single_runtime: 0.006412982940673828
2023-09-28 23:26:01,484 - utils - INFO - 1, epoch: 1034, all client loss: [0.6353428363800049, 0.6412947177886963], all pred client disparities: [0.06151191145181656, 0.09824022650718689], all client disparities: [0.042500000447034836, 0.11200806498527527], all client accs: [0.6109765768051147, 0.6629844307899475],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:01,547 - utils - INFO - stage2_gradient_single_runtime: 0.0061604976654052734
2023-09-28 23:26:01,553 - utils - INFO - 1, epoch: 1035, all client loss: [0.631475031375885, 0.6372005939483643], all pred client disparities: [0.0740794688463211, 0.10607737302780151], all client disparities: [0.06004299595952034, 0.11793908476829529], all client accs: [0.6202582716941833, 0.6695038080215454],  alphas:tensor([0.5027, 0.0000, 0.0000, 0.4973], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:01,617 - utils - INFO - stage2_gradient_single_runtime: 0.006545066833496094
2023-09-28 23:26:01,621 - utils - INFO - 1, epoch: 1036, all client loss: [0.634431779384613, 0.6402456164360046], all pred client disparities: [0.06402543932199478, 0.10020473599433899], all client disparities: [0.0446048304438591, 0.113901287317276], all client accs: [0.6129943132400513, 0.6646143198013306],  alphas:tensor([0.5022, 0.0000, 0.0000, 0.4978], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:01,680 - utils - INFO - stage2_gradient_single_runtime: 0.006078481674194336
2023-09-28 23:26:01,684 - utils - INFO - 1, epoch: 1037, all client loss: [0.6374636888504028, 0.6433702707290649], all pred client disparities: [0.05440041795372963, 0.09394362568855286], all client disparities: [0.036666665226221085, 0.10650849342346191], all client accs: [0.6089588403701782, 0.6580948829650879],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:01,746 - utils - INFO - stage2_gradient_single_runtime: 0.006219148635864258
2023-09-28 23:26:01,751 - utils - INFO - 1, epoch: 1038, all client loss: [0.6334577798843384, 0.6391383409500122], all pred client disparities: [0.06681829690933228, 0.10226008296012878], all client disparities: [0.048376329243183136, 0.11587828397750854], all client accs: [0.615415632724762, 0.6660630702972412],  alphas:tensor([0.5023, 0.0000, 0.0000, 0.4977], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:01,864 - utils - INFO - stage2_gradient_single_runtime: 0.006296873092651367
2023-09-28 23:26:01,870 - utils - INFO - 1, epoch: 1039, all client loss: [0.6364505290985107, 0.6422189474105835], all pred client disparities: [0.05714111775159836, 0.09617725014686584], all client disparities: [0.03916666656732559, 0.10883310437202454], all client accs: [0.6093623638153076, 0.6600869297981262],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:01,885 - utils - INFO - valid: True, epoch: 1039, loss: [0.6295523047447205, 0.6431297063827515], accuracy: [0.6335999965667725, 0.6494545340538025], mean_accuracy:0.6415272653102875,variance_accuracy:0.007927268743515015, disparity: [0.05183562636375427, 0.12648311257362366], mean_disparity:0.08915936946868896,variance_disparity:0.03732374310493469, pred_disparity: [0.06914130598306656, 0.11569574475288391]
2023-09-28 23:26:01,896 - utils - INFO - global_valid: True, epoch: 1039,  global_loss: 0.6388868689537048, global_accuracy: 0.6980182072829132,  global_disparity:0.11669827997684479, global_pred_disparity: 0.11202432215213776,
2023-09-28 23:26:01,958 - utils - INFO - stage2_gradient_single_runtime: 0.006192207336425781
2023-09-28 23:26:01,963 - utils - INFO - 1, epoch: 1040, all client loss: [0.6325176358222961, 0.6380648612976074], all pred client disparities: [0.06953693926334381, 0.10421726107597351], all client disparities: [0.052542995661497116, 0.11751389503479004], all client accs: [0.6174333691596985, 0.6680550575256348],  alphas:tensor([0.5024, 0.0000, 0.0000, 0.4976], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:02,028 - utils - INFO - stage2_gradient_single_runtime: 0.00600433349609375
2023-09-28 23:26:02,034 - utils - INFO - 1, epoch: 1041, all client loss: [0.6354694366455078, 0.6410993933677673], all pred client disparities: [0.05983467772603035, 0.09831017255783081], all client disparities: [0.042500000447034836, 0.11167293787002563], all client accs: [0.6109765768051147, 0.6617168188095093],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:02,097 - utils - INFO - stage2_gradient_single_runtime: 0.006979227066040039
2023-09-28 23:26:02,103 - utils - INFO - 1, epoch: 1042, all client loss: [0.631607174873352, 0.6370208859443665], all pred client disparities: [0.07218945026397705, 0.10608765482902527], all client disparities: [0.0592096671462059, 0.11734011769294739], all client accs: [0.6198546886444092, 0.6691416501998901],  alphas:tensor([0.5025, 0.0000, 0.0000, 0.4975], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:02,169 - utils - INFO - stage2_gradient_single_runtime: 0.006437540054321289
2023-09-28 23:26:02,175 - utils - INFO - 1, epoch: 1043, all client loss: [0.6345163583755493, 0.6400076746940613], all pred client disparities: [0.06248607486486435, 0.10035321116447449], all client disparities: [0.04293816536664963, 0.1148541271686554], all client accs: [0.6121872067451477, 0.6637088060379028],  alphas:tensor([0.5020, 0.0000, 0.0000, 0.4980], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:02,238 - utils - INFO - stage2_gradient_single_runtime: 0.0066187381744384766
2023-09-28 23:26:02,244 - utils - INFO - 1, epoch: 1044, all client loss: [0.637490451335907, 0.6430643200874329], all pred client disparities: [0.05322490632534027, 0.09426239132881165], all client disparities: [0.03583333268761635, 0.10677230358123779], all client accs: [0.608555257320404, 0.6573705673217773],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:02,303 - utils - INFO - stage2_gradient_single_runtime: 0.006249427795410156
2023-09-28 23:26:02,308 - utils - INFO - 1, epoch: 1045, all client loss: [0.635816216468811, 0.6415038108825684], all pred client disparities: [0.05928013473749161, 0.09688743948936462], all client disparities: [0.042500000447034836, 0.10899445414543152], all client accs: [0.6109765768051147, 0.6613546013832092],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:02,370 - utils - INFO - stage2_gradient_single_runtime: 0.006281375885009766
2023-09-28 23:26:02,377 - utils - INFO - 1, epoch: 1046, all client loss: [0.6319276690483093, 0.6373958587646484], all pred client disparities: [0.0716654509305954, 0.10471341013908386], all client disparities: [0.05837633088231087, 0.11750766634941101], all client accs: [0.6194511651992798, 0.6682361364364624],  alphas:tensor([0.5024, 0.0000, 0.0000, 0.4976], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:02,441 - utils - INFO - stage2_gradient_single_runtime: 0.006619930267333984
2023-09-28 23:26:02,447 - utils - INFO - 1, epoch: 1047, all client loss: [0.6348429918289185, 0.6403921842575073], all pred client disparities: [0.06197913736104965, 0.09897685050964355], all client disparities: [0.04333333298563957, 0.11217567324638367], all client accs: [0.6113801002502441, 0.6637088060379028],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:02,507 - utils - INFO - stage2_gradient_single_runtime: 0.0059812068939208984
2023-09-28 23:26:02,512 - utils - INFO - 1, epoch: 1048, all client loss: [0.6310245394706726, 0.6363592743873596], all pred client disparities: [0.07430987060070038, 0.10654899477958679], all client disparities: [0.06004299595952034, 0.11621347069740295], all client accs: [0.6202582716941833, 0.6695038080215454],  alphas:tensor([0.5025, 0.0000, 0.0000, 0.4975], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:02,573 - utils - INFO - stage2_gradient_single_runtime: 0.006405353546142578
2023-09-28 23:26:02,579 - utils - INFO - 1, epoch: 1049, all client loss: [0.6338962316513062, 0.6393068432807922], all pred client disparities: [0.0646376758813858, 0.10098180174827576], all client disparities: [0.0475429967045784, 0.11381125450134277], all client accs: [0.615415632724762, 0.6649764776229858],  alphas:tensor([0.5020, 0.0000, 0.0000, 0.4980], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:02,646 - utils - INFO - stage2_gradient_single_runtime: 0.006463766098022461
2023-09-28 23:26:02,652 - utils - INFO - 1, epoch: 1050, all client loss: [0.636838436126709, 0.642329752445221], all pred client disparities: [0.055349137634038925, 0.09506019949913025], all client disparities: [0.03750000149011612, 0.1076226532459259], all client accs: [0.608555257320404, 0.6591814756393433],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:02,759 - utils - INFO - stage2_gradient_single_runtime: 0.006174802780151367
2023-09-28 23:26:02,765 - utils - INFO - 1, epoch: 1051, all client loss: [0.6328914165496826, 0.6381688117980957], all pred client disparities: [0.06755692511796951, 0.10306328535079956], all client disparities: [0.05170966684818268, 0.11484166979789734], all client accs: [0.6170298457145691, 0.6664252281188965],  alphas:tensor([0.5021, 0.0000, 0.0000, 0.4979], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:02,825 - utils - INFO - stage2_gradient_single_runtime: 0.006204843521118164
2023-09-28 23:26:02,832 - utils - INFO - 1, epoch: 1052, all client loss: [0.6357956528663635, 0.6411488056182861], all pred client disparities: [0.05821376293897629, 0.09731140732765198], all client disparities: [0.0416666679084301, 0.11089390516281128], all client accs: [0.6105730533599854, 0.6611735224723816],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:02,895 - utils - INFO - stage2_gradient_single_runtime: 0.009516239166259766
2023-09-28 23:26:02,902 - utils - INFO - 1, epoch: 1053, all client loss: [0.6319233179092407, 0.6370674967765808], all pred client disparities: [0.07039583474397659, 0.10504195094108582], all client disparities: [0.056709665805101395, 0.11708250641822815], all client accs: [0.6186440587043762, 0.6676928997039795],  alphas:tensor([0.5022, 0.0000, 0.0000, 0.4978], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:02,965 - utils - INFO - stage2_gradient_single_runtime: 0.006180286407470703
2023-09-28 23:26:02,971 - utils - INFO - 1, epoch: 1054, all client loss: [0.6347874999046326, 0.6400024890899658], all pred client disparities: [0.0610259547829628, 0.09945753216743469], all client disparities: [0.042500000447034836, 0.11330229043960571], all client accs: [0.6109765768051147, 0.6633466482162476],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:03,031 - utils - INFO - stage2_gradient_single_runtime: 0.006204128265380859
2023-09-28 23:26:03,036 - utils - INFO - 1, epoch: 1055, all client loss: [0.6309874653816223, 0.6359983086585999], all pred client disparities: [0.0731627568602562, 0.10692983865737915], all client disparities: [0.06004299595952034, 0.11793908476829529], all client accs: [0.6202582716941833, 0.6702281832695007],  alphas:tensor([0.5023, 0.0000, 0.0000, 0.4977], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:03,099 - utils - INFO - stage2_gradient_single_runtime: 0.006106138229370117
2023-09-28 23:26:03,106 - utils - INFO - 1, epoch: 1056, all client loss: [0.6338098049163818, 0.638886570930481], all pred client disparities: [0.06379078328609467, 0.10150986909866333], all client disparities: [0.04543816298246384, 0.1150217056274414], all client accs: [0.6133978962898254, 0.6649764776229858],  alphas:tensor([0.5018, 0.0000, 0.0000, 0.4982], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:03,170 - utils - INFO - stage2_gradient_single_runtime: 0.0073277950286865234
2023-09-28 23:26:03,177 - utils - INFO - 1, epoch: 1057, all client loss: [0.6366958618164062, 0.6418436169624329], all pred client disparities: [0.05480070412158966, 0.09576037526130676], all client disparities: [0.03750000149011612, 0.10780271887779236], all client accs: [0.6089588403701782, 0.6586381793022156],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:03,236 - utils - INFO - stage2_gradient_single_runtime: 0.006034135818481445
2023-09-28 23:26:03,242 - utils - INFO - 1, epoch: 1058, all client loss: [0.6349022388458252, 0.640180230140686], all pred client disparities: [0.06119750067591667, 0.09850946068763733], all client disparities: [0.042500000447034836, 0.11225944757461548], all client accs: [0.6109765768051147, 0.6635277271270752],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:03,305 - utils - INFO - stage2_gradient_single_runtime: 0.006540775299072266
2023-09-28 23:26:03,312 - utils - INFO - 1, epoch: 1059, all client loss: [0.6310911774635315, 0.636162281036377], all pred client disparities: [0.07336898893117905, 0.10597798228263855], all client disparities: [0.06004299595952034, 0.11578205227851868], all client accs: [0.6202582716941833, 0.6687794327735901],  alphas:tensor([0.5023, 0.0000, 0.0000, 0.4977], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:03,327 - utils - INFO - valid: True, epoch: 1059, loss: [0.6307730674743652, 0.6440825462341309], accuracy: [0.6304000020027161, 0.6436363458633423], mean_accuracy:0.6370181739330292,variance_accuracy:0.00661817193031311, disparity: [0.044743429869413376, 0.12543046474456787], mean_disparity:0.08508694730699062,variance_disparity:0.04034351743757725, pred_disparity: [0.06371341645717621, 0.11226671934127808]
2023-09-28 23:26:03,338 - utils - INFO - global_valid: True, epoch: 1059,  global_loss: 0.6399233937263489, global_accuracy: 0.6938435374149661,  global_disparity:0.11426322162151337, global_pred_disparity: 0.10824202001094818,
2023-09-28 23:26:03,399 - utils - INFO - stage2_gradient_single_runtime: 0.006132364273071289
2023-09-28 23:26:03,406 - utils - INFO - 1, epoch: 1060, all client loss: [0.6339136958122253, 0.6390535831451416], all pred client disparities: [0.0639902800321579, 0.10058224201202393], all client disparities: [0.044209666550159454, 0.11165422201156616], all client accs: [0.6138014197349548, 0.6649764776229858],  alphas:tensor([0.5018, 0.0000, 0.0000, 0.4982], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:03,466 - utils - INFO - stage2_gradient_single_runtime: 0.006125688552856445
2023-09-28 23:26:03,471 - utils - INFO - 1, epoch: 1061, all client loss: [0.6367998719215393, 0.6420133113861084], all pred client disparities: [0.05499071255326271, 0.09485960006713867], all client disparities: [0.03750000149011612, 0.10658606886863708], all client accs: [0.608555257320404, 0.6593625545501709],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:03,530 - utils - INFO - stage2_gradient_single_runtime: 0.006203651428222656
2023-09-28 23:26:03,535 - utils - INFO - 1, epoch: 1062, all client loss: [0.6328673362731934, 0.6378746032714844], all pred client disparities: [0.06704312562942505, 0.10272729396820068], all client disparities: [0.05004299804568291, 0.11423644423484802], all client accs: [0.6162227392196655, 0.6664252281188965],  alphas:tensor([0.5019, 0.0000, 0.0000, 0.4981], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:03,668 - utils - INFO - stage2_gradient_single_runtime: 0.006136417388916016
2023-09-28 23:26:03,673 - utils - INFO - 1, epoch: 1063, all client loss: [0.6357173323631287, 0.6407934427261353], all pred client disparities: [0.05797592177987099, 0.09716832637786865], all client disparities: [0.0416666679084301, 0.10873687267303467], all client accs: [0.6105730533599854, 0.6611735224723816],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:03,734 - utils - INFO - stage2_gradient_single_runtime: 0.006230831146240234
2023-09-28 23:26:03,740 - utils - INFO - 1, epoch: 1064, all client loss: [0.6318621039390564, 0.6367368102073669], all pred client disparities: [0.07000751793384552, 0.10476085543632507], all client disparities: [0.05587632954120636, 0.11587205529212952], all client accs: [0.618240475654602, 0.6671496033668518],  alphas:tensor([0.5020, 0.0000, 0.0000, 0.4980], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:03,803 - utils - INFO - stage2_gradient_single_runtime: 0.006394863128662109
2023-09-28 23:26:03,810 - utils - INFO - 1, epoch: 1065, all client loss: [0.634673535823822, 0.6396121978759766], all pred client disparities: [0.060902465134859085, 0.09936359524726868], all client disparities: [0.042500000447034836, 0.11217567324638367], all client accs: [0.6109765768051147, 0.6637088060379028],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:03,876 - utils - INFO - stage2_gradient_single_runtime: 0.006987810134887695
2023-09-28 23:26:03,883 - utils - INFO - 1, epoch: 1066, all client loss: [0.6308926939964294, 0.6356348991394043], all pred client disparities: [0.0728922039270401, 0.1066964864730835], all client disparities: [0.06004299595952034, 0.11707627773284912], all client accs: [0.6202582716941833, 0.6693227291107178],  alphas:tensor([0.5021, 0.0000, 0.0000, 0.4979], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:03,946 - utils - INFO - stage2_gradient_single_runtime: 0.0064694881439208984
2023-09-28 23:26:03,952 - utils - INFO - 1, epoch: 1067, all client loss: [0.6336637139320374, 0.6384650468826294], all pred client disparities: [0.06377559155225754, 0.10145822167396545], all client disparities: [0.04504299536347389, 0.11381125450134277], all client accs: [0.614205002784729, 0.6651575565338135],  alphas:tensor([0.5017, 0.0000, 0.0000, 0.4983], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:04,018 - utils - INFO - stage2_gradient_single_runtime: 0.006089448928833008
2023-09-28 23:26:04,025 - utils - INFO - 1, epoch: 1068, all client loss: [0.6364939212799072, 0.6413595676422119], all pred client disparities: [0.05502290278673172, 0.09591299295425415], all client disparities: [0.03750000149011612, 0.10805407166481018], all client accs: [0.608555257320404, 0.6600869297981262],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:04,100 - utils - INFO - stage2_gradient_single_runtime: 0.006596803665161133
2023-09-28 23:26:04,106 - utils - INFO - 1, epoch: 1069, all client loss: [0.6346651911735535, 0.6396757364273071], all pred client disparities: [0.06145584583282471, 0.09866389632225037], all client disparities: [0.04210482910275459, 0.11010241508483887], all client accs: [0.6117836833000183, 0.6635277271270752],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:04,167 - utils - INFO - stage2_gradient_single_runtime: 0.006590366363525391
2023-09-28 23:26:04,170 - utils - INFO - 1, epoch: 1070, all client loss: [0.6308814287185669, 0.6356925964355469], all pred client disparities: [0.07348169386386871, 0.10596764087677002], all client disparities: [0.06004299595952034, 0.11603966355323792], all client accs: [0.6202582716941833, 0.6678739786148071],  alphas:tensor([0.5021, 0.0000, 0.0000, 0.4979], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:04,226 - utils - INFO - stage2_gradient_single_runtime: 0.006114959716796875
2023-09-28 23:26:04,230 - utils - INFO - 1, epoch: 1071, all client loss: [0.6336497068405151, 0.6385226845741272], all pred client disparities: [0.06434620171785355, 0.10076514631509781], all client disparities: [0.0475429967045784, 0.11104902625083923], all client accs: [0.615415632724762, 0.6649764776229858],  alphas:tensor([0.5017, 0.0000, 0.0000, 0.4983], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:04,287 - utils - INFO - stage2_gradient_single_runtime: 0.006477832794189453
2023-09-28 23:26:04,293 - utils - INFO - 1, epoch: 1072, all client loss: [0.6364784836769104, 0.6414181590080261], all pred client disparities: [0.05556422099471092, 0.095256507396698], all client disparities: [0.038333334028720856, 0.10735887289047241], all client accs: [0.6089588403701782, 0.6593625545501709],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:04,354 - utils - INFO - stage2_gradient_single_runtime: 0.007085561752319336
2023-09-28 23:26:04,359 - utils - INFO - 1, epoch: 1073, all client loss: [0.6325794458389282, 0.6373206973075867], all pred client disparities: [0.06748567521572113, 0.10292989015579224], all client disparities: [0.05170966684818268, 0.11414644122123718], all client accs: [0.6170298457145691, 0.6666063070297241],  alphas:tensor([0.5018, 0.0000, 0.0000, 0.4982], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:04,418 - utils - INFO - stage2_gradient_single_runtime: 0.006363391876220703
2023-09-28 23:26:04,424 - utils - INFO - 1, epoch: 1074, all client loss: [0.6353728771209717, 0.6401761770248413], all pred client disparities: [0.05863447114825249, 0.09757918119430542], all client disparities: [0.042500000447034836, 0.1095934510231018], all client accs: [0.6109765768051147, 0.6618978977203369],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:04,486 - utils - INFO - stage2_gradient_single_runtime: 0.006316184997558594
2023-09-28 23:26:04,493 - utils - INFO - 1, epoch: 1075, all client loss: [0.6315523982048035, 0.6361620426177979], all pred client disparities: [0.07053253799676895, 0.1049802303314209], all client disparities: [0.05754299461841583, 0.11595585942268372], all client accs: [0.6190475821495056, 0.6673306822776794],  alphas:tensor([0.5019, 0.0000, 0.0000, 0.4981], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:04,602 - utils - INFO - stage2_gradient_single_runtime: 0.006273508071899414
2023-09-28 23:26:04,607 - utils - INFO - 1, epoch: 1076, all client loss: [0.6343080401420593, 0.6389749050140381], all pred client disparities: [0.0616423599421978, 0.0997854471206665], all client disparities: [0.04293816536664963, 0.11182805895805359], all client accs: [0.6121872067451477, 0.6640710234642029],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:04,669 - utils - INFO - stage2_gradient_single_runtime: 0.007088899612426758
2023-09-28 23:26:04,675 - utils - INFO - 1, epoch: 1077, all client loss: [0.6305631995201111, 0.6350412964820862], all pred client disparities: [0.07349560409784317, 0.10692989826202393], all client disparities: [0.06004299595952034, 0.11578205227851868], all client accs: [0.6202582716941833, 0.6689605712890625],  alphas:tensor([0.5020, 0.0000, 0.0000, 0.4980], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:04,740 - utils - INFO - stage2_gradient_single_runtime: 0.006045341491699219
2023-09-28 23:26:04,745 - utils - INFO - 1, epoch: 1078, all client loss: [0.6332789659500122, 0.6378096342086792], all pred client disparities: [0.06459316611289978, 0.10188865661621094], all client disparities: [0.048376329243183136, 0.1130322515964508], all client accs: [0.6158192157745361, 0.6657008528709412],  alphas:tensor([0.5016, 0.0000, 0.0000, 0.4984], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:04,807 - utils - INFO - stage2_gradient_single_runtime: 0.006135225296020508
2023-09-28 23:26:04,813 - utils - INFO - 1, epoch: 1079, all client loss: [0.6360527873039246, 0.6406410932540894], all pred client disparities: [0.0560213178396225, 0.09655770659446716], all client disparities: [0.03999999910593033, 0.10753265023231506], all client accs: [0.6097659468650818, 0.6604491472244263],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:04,831 - utils - INFO - valid: True, epoch: 1079, loss: [0.6309771537780762, 0.6440148949623108], accuracy: [0.6304000020027161, 0.642909049987793], mean_accuracy:0.6366545259952545,variance_accuracy:0.006254523992538452, disparity: [0.044743429869413376, 0.124224454164505], mean_disparity:0.08448394201695919,variance_disparity:0.039740512147545815, pred_disparity: [0.06240866333246231, 0.1112261712551117]
2023-09-28 23:26:04,844 - utils - INFO - global_valid: True, epoch: 1079,  global_loss: 0.639940619468689, global_accuracy: 0.6924549819927972,  global_disparity:0.11341133713722229, global_pred_disparity: 0.1072094514966011,
2023-09-28 23:26:04,905 - utils - INFO - stage2_gradient_single_runtime: 0.0071201324462890625
2023-09-28 23:26:04,910 - utils - INFO - 1, epoch: 1080, all client loss: [0.6341521739959717, 0.6388981938362122], all pred client disparities: [0.06265345960855484, 0.0993662178516388], all client disparities: [0.04543816298246384, 0.10949718952178955], all client accs: [0.6133978962898254, 0.6638898849487305],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:04,974 - utils - INFO - stage2_gradient_single_runtime: 0.006325721740722656
2023-09-28 23:26:04,979 - utils - INFO - 1, epoch: 1081, all client loss: [0.6304139494895935, 0.6349683403968811], all pred client disparities: [0.07454168796539307, 0.10645249485969543], all client disparities: [0.06170966476202011, 0.11620724201202393], all client accs: [0.6202582716941833, 0.6691416501998901],  alphas:tensor([0.5020, 0.0000, 0.0000, 0.4980], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:05,042 - utils - INFO - stage2_gradient_single_runtime: 0.0062618255615234375
2023-09-28 23:26:05,048 - utils - INFO - 1, epoch: 1082, all client loss: [0.6331233978271484, 0.637732744216919], all pred client disparities: [0.06560957431793213, 0.1014607846736908], all client disparities: [0.048376329243183136, 0.11173182725906372], all client accs: [0.615415632724762, 0.6657008528709412],  alphas:tensor([0.5016, 0.0000, 0.0000, 0.4984], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:05,107 - utils - INFO - stage2_gradient_single_runtime: 0.006208658218383789
2023-09-28 23:26:05,114 - utils - INFO - 1, epoch: 1083, all client loss: [0.6358934640884399, 0.6405625343322754], all pred client disparities: [0.056989263743162155, 0.09617853164672852], all client disparities: [0.0416666679084301, 0.10795783996582031], all client accs: [0.6105730533599854, 0.659724771976471],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:05,176 - utils - INFO - stage2_gradient_single_runtime: 0.006139278411865234
2023-09-28 23:26:05,181 - utils - INFO - 1, epoch: 1084, all client loss: [0.632045328617096, 0.6365239024162292], all pred client disparities: [0.06879550963640213, 0.10360711812973022], all client disparities: [0.05504300072789192, 0.11285221576690674], all client accs: [0.6178369522094727, 0.6664252281188965],  alphas:tensor([0.5017, 0.0000, 0.0000, 0.4983], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:05,245 - utils - INFO - stage2_gradient_single_runtime: 0.006093502044677734
2023-09-28 23:26:05,252 - utils - INFO - 1, epoch: 1085, all client loss: [0.6347799301147461, 0.6393136978149414], all pred client disparities: [0.060114070773124695, 0.098477303981781], all client disparities: [0.042500000447034836, 0.11010241508483887], all client accs: [0.6109765768051147, 0.6633466482162476],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:05,316 - utils - INFO - stage2_gradient_single_runtime: 0.006236553192138672
2023-09-28 23:26:05,323 - utils - INFO - 1, epoch: 1086, all client loss: [0.6310105919837952, 0.6353586912155151], all pred client disparities: [0.07188782840967178, 0.10564082860946655], all client disparities: [0.0592096671462059, 0.11474543809890747], all client accs: [0.6198546886444092, 0.6678739786148071],  alphas:tensor([0.5018, 0.0000, 0.0000, 0.4982], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:05,388 - utils - INFO - stage2_gradient_single_runtime: 0.006401538848876953
2023-09-28 23:26:05,395 - utils - INFO - 1, epoch: 1087, all client loss: [0.6337074041366577, 0.6381058692932129], all pred client disparities: [0.06317481398582458, 0.10066154599189758], all client disparities: [0.044209666550159454, 0.11122283339500427], all client accs: [0.6138014197349548, 0.6640710234642029],  alphas:tensor([0.5014, 0.0000, 0.0000, 0.4986], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:05,530 - utils - INFO - stage2_gradient_single_runtime: 0.006111860275268555
2023-09-28 23:26:05,535 - utils - INFO - 1, epoch: 1088, all client loss: [0.6364551186561584, 0.6409092545509338], all pred client disparities: [0.0548112615942955, 0.09541064500808716], all client disparities: [0.038333334028720856, 0.10735887289047241], all client accs: [0.6089588403701782, 0.6590003967285156],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:05,599 - utils - INFO - stage2_gradient_single_runtime: 0.0064771175384521484
2023-09-28 23:26:05,606 - utils - INFO - 1, epoch: 1089, all client loss: [0.6345979571342468, 0.639221727848053], all pred client disparities: [0.06118931248784065, 0.0981195867061615], all client disparities: [0.041271500289440155, 0.10897576808929443], all client accs: [0.6113801002502441, 0.6635277271270752],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:05,669 - utils - INFO - stage2_gradient_single_runtime: 0.0062694549560546875
2023-09-28 23:26:05,675 - utils - INFO - 1, epoch: 1090, all client loss: [0.6308367848396301, 0.6352717876434326], all pred client disparities: [0.07300231605768204, 0.10522124171257019], all client disparities: [0.06004299595952034, 0.11344501376152039], all client accs: [0.6202582716941833, 0.6687794327735901],  alphas:tensor([0.5018, 0.0000, 0.0000, 0.4982], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:05,742 - utils - INFO - stage2_gradient_single_runtime: 0.007177591323852539
2023-09-28 23:26:05,747 - utils - INFO - 1, epoch: 1091, all client loss: [0.6335278749465942, 0.638015627861023], all pred client disparities: [0.06425190716981888, 0.10029039531946182], all client disparities: [0.048376329243183136, 0.11181560158729553], all client accs: [0.6158192157745361, 0.6653386354446411],  alphas:tensor([0.5015, 0.0000, 0.0000, 0.4985], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:05,810 - utils - INFO - stage2_gradient_single_runtime: 0.0062940120697021484
2023-09-28 23:26:05,817 - utils - INFO - 1, epoch: 1092, all client loss: [0.6362726092338562, 0.6408181190490723], all pred client disparities: [0.05583177134394646, 0.0950864851474762], all client disparities: [0.03999999910593033, 0.10666361451148987], all client accs: [0.6097659468650818, 0.6584571003913879],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:05,882 - utils - INFO - stage2_gradient_single_runtime: 0.006314516067504883
2023-09-28 23:26:05,888 - utils - INFO - 1, epoch: 1093, all client loss: [0.6324061155319214, 0.6367639899253845], all pred client disparities: [0.06755402684211731, 0.10251420736312866], all client disparities: [0.05170966684818268, 0.11293599009513855], all client accs: [0.6170298457145691, 0.6657008528709412],  alphas:tensor([0.5016, 0.0000, 0.0000, 0.4984], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:05,952 - utils - INFO - stage2_gradient_single_runtime: 0.0064868927001953125
2023-09-28 23:26:05,958 - utils - INFO - 1, epoch: 1094, all client loss: [0.6351175904273987, 0.6395285725593567], all pred client disparities: [0.05905558541417122, 0.09745901823043823], all client disparities: [0.042500000447034836, 0.10898199677467346], all client accs: [0.6109765768051147, 0.6620789766311646],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:06,018 - utils - INFO - stage2_gradient_single_runtime: 0.0060176849365234375
2023-09-28 23:26:06,023 - utils - INFO - 1, epoch: 1095, all client loss: [0.6313324570655823, 0.6355606913566589], all pred client disparities: [0.07075472921133041, 0.10461550951004028], all client disparities: [0.05837633088231087, 0.11379259824752808], all client accs: [0.6194511651992798, 0.6682361364364624],  alphas:tensor([0.5017, 0.0000, 0.0000, 0.4983], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:06,087 - utils - INFO - stage2_gradient_single_runtime: 0.006433010101318359
2023-09-28 23:26:06,093 - utils - INFO - 1, epoch: 1096, all client loss: [0.6340078711509705, 0.6382845044136047], all pred client disparities: [0.06220978498458862, 0.0997077226638794], all client disparities: [0.04543816298246384, 0.10975480079650879], all client accs: [0.6133978962898254, 0.6637088060379028],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:06,155 - utils - INFO - stage2_gradient_single_runtime: 0.0063130855560302734
2023-09-28 23:26:06,161 - utils - INFO - 1, epoch: 1097, all client loss: [0.6303009986877441, 0.6343997716903687], all pred client disparities: [0.0738632008433342, 0.10660958290100098], all client disparities: [0.06004299595952034, 0.11534443497657776], all client accs: [0.6194511651992798, 0.6689605712890625],  alphas:tensor([0.5018, 0.0000, 0.0000, 0.4982], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:06,226 - utils - INFO - stage2_gradient_single_runtime: 0.00601959228515625
2023-09-28 23:26:06,231 - utils - INFO - 1, epoch: 1098, all client loss: [0.6329379081726074, 0.6370804905891418], all pred client disparities: [0.06529974937438965, 0.10184687376022339], all client disparities: [0.048376329243183136, 0.11173182725906372], all client accs: [0.615415632724762, 0.6655197739601135],  alphas:tensor([0.5014, 0.0000, 0.0000, 0.4986], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:06,296 - utils - INFO - stage2_gradient_single_runtime: 0.0071239471435546875
2023-09-28 23:26:06,303 - utils - INFO - 1, epoch: 1099, all client loss: [0.6356289386749268, 0.6398205757141113], all pred client disparities: [0.05703127384185791, 0.09682214260101318], all client disparities: [0.0416666679084301, 0.1084730327129364], all client accs: [0.6105730533599854, 0.6600869297981262],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:06,317 - utils - INFO - valid: True, epoch: 1099, loss: [0.6288562417030334, 0.641398012638092], accuracy: [0.6319999694824219, 0.6487272381782532], mean_accuracy:0.6403636038303375,variance_accuracy:0.00836363434791565, disparity: [0.05183562636375427, 0.12798535823822021], mean_disparity:0.08991049230098724,variance_disparity:0.03807486593723297, pred_disparity: [0.06813304871320724, 0.11578533053398132]
2023-09-28 23:26:06,328 - utils - INFO - global_valid: True, epoch: 1099,  global_loss: 0.6374787092208862, global_accuracy: 0.6968177270908364,  global_disparity:0.11789570748806, global_pred_disparity: 0.11199651658535004,
2023-09-28 23:26:06,455 - utils - INFO - stage2_gradient_single_runtime: 0.006252288818359375
2023-09-28 23:26:06,461 - utils - INFO - 1, epoch: 1100, all client loss: [0.6318208575248718, 0.6358358263969421], all pred client disparities: [0.06861196458339691, 0.10403025150299072], all client disparities: [0.05504300072789192, 0.11310982704162598], all client accs: [0.6178369522094727, 0.6666063070297241],  alphas:tensor([0.5015, 0.0000, 0.0000, 0.4985], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:06,521 - utils - INFO - stage2_gradient_single_runtime: 0.006270408630371094
2023-09-28 23:26:06,528 - utils - INFO - 1, epoch: 1101, all client loss: [0.6344786286354065, 0.6385379433631897], all pred client disparities: [0.060273755341768265, 0.0991496741771698], all client disparities: [0.042500000447034836, 0.11010241508483887], all client accs: [0.6109765768051147, 0.6633466482162476],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:06,587 - utils - INFO - stage2_gradient_single_runtime: 0.005959987640380859
2023-09-28 23:26:06,592 - utils - INFO - 1, epoch: 1102, all client loss: [0.6307511925697327, 0.6346387267112732], all pred client disparities: [0.07182376086711884, 0.1060945987701416], all client disparities: [0.0592096671462059, 0.11474543809890747], all client accs: [0.6198546886444092, 0.6680550575256348],  alphas:tensor([0.5016, 0.0000, 0.0000, 0.4984], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:06,654 - utils - INFO - stage2_gradient_single_runtime: 0.006050586700439453
2023-09-28 23:26:06,659 - utils - INFO - 1, epoch: 1103, all client loss: [0.6333729028701782, 0.6373003125190735], all pred client disparities: [0.06344643980264664, 0.10135660320520401], all client disparities: [0.0475429967045784, 0.11104902625083923], all client accs: [0.615415632724762, 0.6642521023750305],  alphas:tensor([0.5013, 0.0000, 0.0000, 0.4987], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:06,720 - utils - INFO - stage2_gradient_single_runtime: 0.006263256072998047
2023-09-28 23:26:06,726 - utils - INFO - 1, epoch: 1104, all client loss: [0.6360415816307068, 0.640014111995697], all pred client disparities: [0.055388737469911575, 0.09637129306793213], all client disparities: [0.03999999910593033, 0.10735887289047241], all client accs: [0.6097659468650818, 0.6593625545501709],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:06,790 - utils - INFO - stage2_gradient_single_runtime: 0.0061228275299072266
2023-09-28 23:26:06,795 - utils - INFO - 1, epoch: 1105, all client loss: [0.6341346502304077, 0.6382959485054016], all pred client disparities: [0.06182382255792618, 0.09908631443977356], all client disparities: [0.04543816298246384, 0.10923337936401367], all client accs: [0.6133978962898254, 0.6640710234642029],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:06,858 - utils - INFO - stage2_gradient_single_runtime: 0.006338834762573242
2023-09-28 23:26:06,864 - utils - INFO - 1, epoch: 1106, all client loss: [0.6304256319999695, 0.6344120502471924], all pred client disparities: [0.07341243326663971, 0.10594108700752258], all client disparities: [0.06004299595952034, 0.11439159512519836], all client accs: [0.6198546886444092, 0.6691416501998901],  alphas:tensor([0.5017, 0.0000, 0.0000, 0.4983], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:06,922 - utils - INFO - stage2_gradient_single_runtime: 0.006036281585693359
2023-09-28 23:26:06,927 - utils - INFO - 1, epoch: 1107, all client loss: [0.6330388188362122, 0.6370668411254883], all pred client disparities: [0.06498527526855469, 0.10126250982284546], all client disparities: [0.048376329243183136, 0.11138421297073364], all client accs: [0.615415632724762, 0.6655197739601135],  alphas:tensor([0.5013, 0.0000, 0.0000, 0.4987], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:06,995 - utils - INFO - stage2_gradient_single_runtime: 0.006219625473022461
2023-09-28 23:26:07,001 - utils - INFO - 1, epoch: 1108, all client loss: [0.6357027888298035, 0.6397777795791626], all pred client disparities: [0.056851789355278015, 0.09633371233940125], all client disparities: [0.0416666679084301, 0.10872441530227661], all client accs: [0.6105730533599854, 0.6602680683135986],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:07,065 - utils - INFO - stage2_gradient_single_runtime: 0.006197452545166016
2023-09-28 23:26:07,071 - utils - INFO - 1, epoch: 1109, all client loss: [0.6318962574005127, 0.6357976198196411], all pred client disparities: [0.06836877763271332, 0.10348033905029297], all client disparities: [0.05504300072789192, 0.11172559857368469], all client accs: [0.6178369522094727, 0.6669685244560242],  alphas:tensor([0.5014, 0.0000, 0.0000, 0.4986], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:07,134 - utils - INFO - stage2_gradient_single_runtime: 0.006100654602050781
2023-09-28 23:26:07,139 - utils - INFO - 1, epoch: 1110, all client loss: [0.6345280408859253, 0.6384716033935547], all pred client disparities: [0.06015952304005623, 0.09869244694709778], all client disparities: [0.041271500289440155, 0.10889199376106262], all client accs: [0.6113801002502441, 0.6633466482162476],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:07,195 - utils - INFO - stage2_gradient_single_runtime: 0.006419658660888672
2023-09-28 23:26:07,200 - utils - INFO - 1, epoch: 1111, all client loss: [0.630803644657135, 0.6345784664154053], all pred client disparities: [0.07164768874645233, 0.10557493567466736], all client disparities: [0.0592096671462059, 0.11379259824752808], all client accs: [0.6198546886444092, 0.6684172749519348],  alphas:tensor([0.5015, 0.0000, 0.0000, 0.4985], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:07,260 - utils - INFO - stage2_gradient_single_runtime: 0.006046295166015625
2023-09-28 23:26:07,265 - utils - INFO - 1, epoch: 1112, all client loss: [0.6334002017974854, 0.6372126936912537], all pred client disparities: [0.06339417397975922, 0.10092654824256897], all client disparities: [0.04670966416597366, 0.11130040884017944], all client accs: [0.6150121092796326, 0.6653386354446411],  alphas:tensor([0.5012, 0.0000, 0.0000, 0.4988], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:07,382 - utils - INFO - stage2_gradient_single_runtime: 0.00607752799987793
2023-09-28 23:26:07,387 - utils - INFO - 1, epoch: 1113, all client loss: [0.6360414624214172, 0.6398971080780029], all pred client disparities: [0.05545361712574959, 0.09604120254516602], all client disparities: [0.040833331644535065, 0.10709503293037415], all client accs: [0.6101694703102112, 0.6591814756393433],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:07,449 - utils - INFO - stage2_gradient_single_runtime: 0.006253242492675781
2023-09-28 23:26:07,454 - utils - INFO - 1, epoch: 1114, all client loss: [0.6341162323951721, 0.6381693482398987], all pred client disparities: [0.06190699338912964, 0.09875154495239258], all client disparities: [0.04543816298246384, 0.10965856909751892], all client accs: [0.6133978962898254, 0.6640710234642029],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:07,516 - utils - INFO - stage2_gradient_single_runtime: 0.006228446960449219
2023-09-28 23:26:07,522 - utils - INFO - 1, epoch: 1115, all client loss: [0.6304145455360413, 0.634295642375946], all pred client disparities: [0.0734342560172081, 0.10553273558616638], all client disparities: [0.06004299595952034, 0.11387017369270325], all client accs: [0.6194511651992798, 0.6691416501998901],  alphas:tensor([0.5016, 0.0000, 0.0000, 0.4984], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:07,587 - utils - INFO - stage2_gradient_single_runtime: 0.006232500076293945
2023-09-28 23:26:07,593 - utils - INFO - 1, epoch: 1116, all client loss: [0.6330016255378723, 0.6369222402572632], all pred client disparities: [0.06512469798326492, 0.10094743967056274], all client disparities: [0.04920966178178787, 0.11112037301063538], all client accs: [0.6158192157745361, 0.6660630702972412],  alphas:tensor([0.5013, 0.0000, 0.0000, 0.4987], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:07,654 - utils - INFO - stage2_gradient_single_runtime: 0.006371974945068359
2023-09-28 23:26:07,659 - utils - INFO - 1, epoch: 1117, all client loss: [0.6356378197669983, 0.6396030783653259], all pred client disparities: [0.057099662721157074, 0.0961216390132904], all client disparities: [0.042500000447034836, 0.10682496428489685], all client accs: [0.6109765768051147, 0.6606302261352539],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:07,721 - utils - INFO - stage2_gradient_single_runtime: 0.00616908073425293
2023-09-28 23:26:07,726 - utils - INFO - 1, epoch: 1118, all client loss: [0.6318418383598328, 0.6356364488601685], all pred client disparities: [0.06856010854244232, 0.10318103432655334], all client disparities: [0.05587632954120636, 0.1118093729019165], all client accs: [0.618240475654602, 0.6671496033668518],  alphas:tensor([0.5014, 0.0000, 0.0000, 0.4986], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:07,789 - utils - INFO - stage2_gradient_single_runtime: 0.00759434700012207
2023-09-28 23:26:07,795 - utils - INFO - 1, epoch: 1119, all client loss: [0.6344462633132935, 0.638280987739563], all pred client disparities: [0.0604579783976078, 0.09849300980567932], all client disparities: [0.041271500289440155, 0.10854437947273254], all client accs: [0.6113801002502441, 0.6626222729682922],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:07,809 - utils - INFO - valid: True, epoch: 1119, loss: [0.6279024481773376, 0.6401986479759216], accuracy: [0.6351999640464783, 0.6516363620758057], mean_accuracy:0.643418163061142,variance_accuracy:0.008218199014663696, disparity: [0.05892782658338547, 0.13430115580558777], mean_disparity:0.09661449119448662,variance_disparity:0.03768666461110115, pred_disparity: [0.07131386548280716, 0.11718657612800598]
2023-09-28 23:26:07,822 - utils - INFO - global_valid: True, epoch: 1119,  global_loss: 0.6363561153411865, global_accuracy: 0.6983143257302921,  global_disparity:0.12438921630382538, global_pred_disparity: 0.11383257806301117,
2023-09-28 23:26:07,885 - utils - INFO - stage2_gradient_single_runtime: 0.0064716339111328125
2023-09-28 23:26:07,891 - utils - INFO - 1, epoch: 1120, all client loss: [0.6307334303855896, 0.634402334690094], all pred client disparities: [0.07188829779624939, 0.10528954863548279], all client disparities: [0.0592096671462059, 0.11344501376152039], all client accs: [0.6198546886444092, 0.6680550575256348],  alphas:tensor([0.5015, 0.0000, 0.0000, 0.4985], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:07,955 - utils - INFO - stage2_gradient_single_runtime: 0.006939411163330078
2023-09-28 23:26:07,962 - utils - INFO - 1, epoch: 1121, all client loss: [0.6333031058311462, 0.6370075941085815], all pred client disparities: [0.06374090909957886, 0.10073814541101456], all client disparities: [0.048376329243183136, 0.11103656888008118], all client accs: [0.615415632724762, 0.6657008528709412],  alphas:tensor([0.5011, 0.0000, 0.0000, 0.4989], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:08,023 - utils - INFO - stage2_gradient_single_runtime: 0.006981611251831055
2023-09-28 23:26:08,030 - utils - INFO - 1, epoch: 1122, all client loss: [0.6359167098999023, 0.639661967754364], all pred client disparities: [0.05589340999722481, 0.0959579348564148], all client disparities: [0.040833331644535065, 0.10708880424499512], all client accs: [0.6101694703102112, 0.6593625545501709],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:08,089 - utils - INFO - stage2_gradient_single_runtime: 0.006157398223876953
2023-09-28 23:26:08,096 - utils - INFO - 1, epoch: 1123, all client loss: [0.6339561939239502, 0.637907087802887], all pred client disparities: [0.062439050525426865, 0.09868767857551575], all client disparities: [0.04504299536347389, 0.10956856608390808], all client accs: [0.614205002784729, 0.6642521023750305],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:08,156 - utils - INFO - stage2_gradient_single_runtime: 0.006441593170166016
2023-09-28 23:26:08,163 - utils - INFO - 1, epoch: 1124, all client loss: [0.6302709579467773, 0.6340528726577759], all pred client disparities: [0.07390706241130829, 0.10537019371986389], all client disparities: [0.060876332223415375, 0.112659752368927], all client accs: [0.6198546886444092, 0.6693227291107178],  alphas:tensor([0.5015, 0.0000, 0.0000, 0.4985], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:08,301 - utils - INFO - stage2_gradient_single_runtime: 0.006301403045654297
2023-09-28 23:26:08,308 - utils - INFO - 1, epoch: 1125, all client loss: [0.6328297853469849, 0.6366488337516785], all pred client disparities: [0.06569872051477432, 0.10088679194450378], all client disparities: [0.05087633058428764, 0.10982614755630493], all client accs: [0.6166263222694397, 0.6657008528709412],  alphas:tensor([0.5012, 0.0000, 0.0000, 0.4988], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:08,372 - utils - INFO - stage2_gradient_single_runtime: 0.006500244140625
2023-09-28 23:26:08,378 - utils - INFO - 1, epoch: 1126, all client loss: [0.6354374289512634, 0.639298677444458], all pred client disparities: [0.057758815586566925, 0.09617048501968384], all client disparities: [0.042500000447034836, 0.10768157243728638], all client accs: [0.6109765768051147, 0.6608113050460815],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:08,440 - utils - INFO - stage2_gradient_single_runtime: 0.006208181381225586
2023-09-28 23:26:08,446 - utils - INFO - 1, epoch: 1127, all client loss: [0.6316606402397156, 0.6353542804718018], all pred client disparities: [0.06916800886392593, 0.10311847925186157], all client disparities: [0.056709665805101395, 0.11068272590637207], all client accs: [0.6186440587043762, 0.6684172749519348],  alphas:tensor([0.5013, 0.0000, 0.0000, 0.4987], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:08,511 - utils - INFO - stage2_gradient_single_runtime: 0.006310462951660156
2023-09-28 23:26:08,517 - utils - INFO - 1, epoch: 1128, all client loss: [0.6342365145683289, 0.6379678845405579], all pred client disparities: [0.061154089868068695, 0.09853717684745789], all client disparities: [0.0446048304438591, 0.10853815078735352], all client accs: [0.6129943132400513, 0.6638898849487305],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:08,583 - utils - INFO - stage2_gradient_single_runtime: 0.006255388259887695
2023-09-28 23:26:08,589 - utils - INFO - 1, epoch: 1129, all client loss: [0.6305434703826904, 0.6341119408607483], all pred client disparities: [0.07252880930900574, 0.10522547364234924], all client disparities: [0.06004299595952034, 0.11274975538253784], all client accs: [0.6202582716941833, 0.6685983538627625],  alphas:tensor([0.5014, 0.0000, 0.0000, 0.4986], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:08,655 - utils - INFO - stage2_gradient_single_runtime: 0.006123781204223633
2023-09-28 23:26:08,661 - utils - INFO - 1, epoch: 1130, all client loss: [0.6330847144126892, 0.636686384677887], all pred client disparities: [0.06447244435548782, 0.10077792406082153], all client disparities: [0.048376329243183136, 0.11043137311935425], all client accs: [0.615415632724762, 0.6653386354446411],  alphas:tensor([0.5011, 0.0000, 0.0000, 0.4989], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:08,728 - utils - INFO - stage2_gradient_single_runtime: 0.0066912174224853516
2023-09-28 23:26:08,734 - utils - INFO - 1, epoch: 1131, all client loss: [0.6356698870658875, 0.6393100619316101], all pred client disparities: [0.056697238236665726, 0.09610828757286072], all client disparities: [0.042500000447034836, 0.10639357566833496], all client accs: [0.6109765768051147, 0.6602680683135986],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:08,797 - utils - INFO - stage2_gradient_single_runtime: 0.0064923763275146484
2023-09-28 23:26:08,804 - utils - INFO - 1, epoch: 1132, all client loss: [0.6318886280059814, 0.6353673934936523], all pred client disparities: [0.06800729036331177, 0.10305222868919373], all client disparities: [0.05587632954120636, 0.11051517724990845], all client accs: [0.618240475654602, 0.6675118207931519],  alphas:tensor([0.5012, 0.0000, 0.0000, 0.4988], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:08,863 - utils - INFO - stage2_gradient_single_runtime: 0.006211996078491211
2023-09-28 23:26:08,869 - utils - INFO - 1, epoch: 1133, all client loss: [0.634443998336792, 0.6379567384719849], all pred client disparities: [0.06014538183808327, 0.0985146164894104], all client disparities: [0.041271500289440155, 0.1084543764591217], all client accs: [0.6113801002502441, 0.6635277271270752],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:08,928 - utils - INFO - stage2_gradient_single_runtime: 0.006365060806274414
2023-09-28 23:26:08,934 - utils - INFO - 1, epoch: 1134, all client loss: [0.6307477355003357, 0.6341038942337036], all pred client disparities: [0.07142937183380127, 0.10519525408744812], all client disparities: [0.0592096671462059, 0.11258217692375183], all client accs: [0.6198546886444092, 0.6678739786148071],  alphas:tensor([0.5013, 0.0000, 0.0000, 0.4987], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:08,994 - utils - INFO - stage2_gradient_single_runtime: 0.00602412223815918
2023-09-28 23:26:09,000 - utils - INFO - 1, epoch: 1135, all client loss: [0.6332701444625854, 0.6366556286811829], all pred client disparities: [0.06351368129253387, 0.10078877210617065], all client disparities: [0.048376329243183136, 0.11017376184463501], all client accs: [0.615415632724762, 0.6655197739601135],  alphas:tensor([0.5010, 0.0000, 0.0000, 0.4990], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:09,115 - utils - INFO - stage2_gradient_single_runtime: 0.006134748458862305
2023-09-28 23:26:09,120 - utils - INFO - 1, epoch: 1136, all client loss: [0.635832667350769, 0.6392529606819153], all pred client disparities: [0.05588690564036369, 0.09616965055465698], all client disparities: [0.0416666679084301, 0.10743018984794617], all client accs: [0.6105730533599854, 0.6599058508872986],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:09,184 - utils - INFO - stage2_gradient_single_runtime: 0.006372928619384766
2023-09-28 23:26:09,190 - utils - INFO - 1, epoch: 1137, all client loss: [0.6338583827018738, 0.637498676776886], all pred client disparities: [0.06238647922873497, 0.09887120127677917], all client disparities: [0.04504299536347389, 0.10956856608390808], all client accs: [0.614205002784729, 0.6640710234642029],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:09,253 - utils - INFO - stage2_gradient_single_runtime: 0.006274700164794922
2023-09-28 23:26:09,259 - utils - INFO - 1, epoch: 1138, all client loss: [0.6301956176757812, 0.6336758136749268], all pred client disparities: [0.07370853424072266, 0.10542401671409607], all client disparities: [0.060876332223415375, 0.11231213808059692], all client accs: [0.6198546886444092, 0.6700471043586731],  alphas:tensor([0.5014, 0.0000, 0.0000, 0.4986], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:09,325 - utils - INFO - stage2_gradient_single_runtime: 0.0064160823822021484
2023-09-28 23:26:09,332 - utils - INFO - 1, epoch: 1139, all client loss: [0.6327062845230103, 0.6362172961235046], all pred client disparities: [0.06572381407022476, 0.10108885169029236], all client disparities: [0.05087633058428764, 0.11034134030342102], all client accs: [0.6166263222694397, 0.6660630702972412],  alphas:tensor([0.5011, 0.0000, 0.0000, 0.4989], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:09,347 - utils - INFO - valid: True, epoch: 1139, loss: [0.6319426894187927, 0.6441584825515747], accuracy: [0.6240000128746033, 0.6349090933799744], mean_accuracy:0.6294545531272888,variance_accuracy:0.005454540252685547, disparity: [0.039007093757390976, 0.12046357989311218], mean_disparity:0.07973533682525158,variance_disparity:0.0407282430678606, pred_disparity: [0.057872019708156586, 0.10872623324394226]
2023-09-28 23:26:09,358 - utils - INFO - global_valid: True, epoch: 1139,  global_loss: 0.6403411030769348, global_accuracy: 0.6888815526210483,  global_disparity:0.10935291647911072, global_pred_disparity: 0.10438226163387299,
2023-09-28 23:26:09,418 - utils - INFO - stage2_gradient_single_runtime: 0.006409168243408203
2023-09-28 23:26:09,424 - utils - INFO - 1, epoch: 1140, all client loss: [0.6352625489234924, 0.6388095021247864], all pred client disparities: [0.05799432843923569, 0.09653642773628235], all client disparities: [0.042500000447034836, 0.10819676518440247], all client accs: [0.6109765768051147, 0.6609923839569092],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:09,486 - utils - INFO - stage2_gradient_single_runtime: 0.0062525272369384766
2023-09-28 23:26:09,491 - utils - INFO - 1, epoch: 1141, all client loss: [0.6315135359764099, 0.6349021792411804], all pred client disparities: [0.06926407665014267, 0.10333377122879028], all client disparities: [0.05754299461841583, 0.11094033718109131], all client accs: [0.6190475821495056, 0.6680550575256348],  alphas:tensor([0.5012, 0.0000, 0.0000, 0.4988], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:09,553 - utils - INFO - stage2_gradient_single_runtime: 0.006475687026977539
2023-09-28 23:26:09,558 - utils - INFO - 1, epoch: 1142, all client loss: [0.6340394020080566, 0.6374593377113342], all pred client disparities: [0.061457760632038116, 0.0989108681678772], all client disparities: [0.04627149552106857, 0.1090533435344696], all client accs: [0.6138014197349548, 0.6640710234642029],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:09,619 - utils - INFO - stage2_gradient_single_runtime: 0.006392717361450195
2023-09-28 23:26:09,624 - utils - INFO - 1, epoch: 1143, all client loss: [0.6303751468658447, 0.6336414217948914], all pred client disparities: [0.07269234210252762, 0.10545137524604797], all client disparities: [0.06004299595952034, 0.11326494812965393], all client accs: [0.6198546886444092, 0.6687794327735901],  alphas:tensor([0.5013, 0.0000, 0.0000, 0.4987], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:09,689 - utils - INFO - stage2_gradient_single_runtime: 0.006378889083862305
2023-09-28 23:26:09,696 - utils - INFO - 1, epoch: 1144, all client loss: [0.6328673362731934, 0.6361605525016785], all pred client disparities: [0.06484105437994003, 0.10115694999694824], all client disparities: [0.05087633058428764, 0.11025756597518921], all client accs: [0.6166263222694397, 0.6655197739601135],  alphas:tensor([0.5010, 0.0000, 0.0000, 0.4990], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:09,756 - utils - INFO - stage2_gradient_single_runtime: 0.00626373291015625
2023-09-28 23:26:09,761 - utils - INFO - 1, epoch: 1145, all client loss: [0.6354014873504639, 0.6387270092964172], all pred client disparities: [0.05725197121500969, 0.09665411710739136], all client disparities: [0.042500000447034836, 0.10742399096488953], all client accs: [0.6109765768051147, 0.6611735224723816],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:09,821 - utils - INFO - stage2_gradient_single_runtime: 0.006182193756103516
2023-09-28 23:26:09,827 - utils - INFO - 1, epoch: 1146, all client loss: [0.6316540241241455, 0.6348274946212769], all pred client disparities: [0.06843114644289017, 0.10343033075332642], all client disparities: [0.05587632954120636, 0.11068272590637207], all client accs: [0.618240475654602, 0.6685983538627625],  alphas:tensor([0.5011, 0.0000, 0.0000, 0.4989], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:09,889 - utils - INFO - stage2_gradient_single_runtime: 0.006204843521118164
2023-09-28 23:26:09,895 - utils - INFO - 1, epoch: 1147, all client loss: [0.6341592669487, 0.6373603940010071], all pred client disparities: [0.06075625866651535, 0.09905427694320679], all client disparities: [0.0446048304438591, 0.1084543764591217], all client accs: [0.6129943132400513, 0.6635277271270752],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:10,025 - utils - INFO - stage2_gradient_single_runtime: 0.006351947784423828
2023-09-28 23:26:10,031 - utils - INFO - 1, epoch: 1148, all client loss: [0.6304974555969238, 0.6335512399673462], all pred client disparities: [0.0719061940908432, 0.10557153820991516], all client disparities: [0.06004299595952034, 0.1124921441078186], all client accs: [0.6202582716941833, 0.6687794327735901],  alphas:tensor([0.5012, 0.0000, 0.0000, 0.4988], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:10,089 - utils - INFO - stage2_gradient_single_runtime: 0.006196022033691406
2023-09-28 23:26:10,094 - utils - INFO - 1, epoch: 1149, all client loss: [0.6329704523086548, 0.6360474824905396], all pred client disparities: [0.06417819857597351, 0.10132154822349548], all client disparities: [0.048376329243183136, 0.11043137311935425], all client accs: [0.615415632724762, 0.6657008528709412],  alphas:tensor([0.5009, 0.0000, 0.0000, 0.4991], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:10,155 - utils - INFO - stage2_gradient_single_runtime: 0.006268978118896484
2023-09-28 23:26:10,161 - utils - INFO - 1, epoch: 1150, all client loss: [0.6354824900627136, 0.6385883092880249], all pred client disparities: [0.056715697050094604, 0.09687086939811707], all client disparities: [0.042500000447034836, 0.10708257555961609], all client accs: [0.6109765768051147, 0.6608113050460815],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:10,223 - utils - INFO - stage2_gradient_single_runtime: 0.007173299789428711
2023-09-28 23:26:10,230 - utils - INFO - 1, epoch: 1151, all client loss: [0.6334589123725891, 0.6367976069450378], all pred client disparities: [0.0633285641670227, 0.09959310293197632], all client disparities: [0.0475429967045784, 0.10939472913742065], all client accs: [0.6150121092796326, 0.6642521023750305],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:10,290 - utils - INFO - stage2_gradient_single_runtime: 0.006151914596557617
2023-09-28 23:26:10,296 - utils - INFO - 1, epoch: 1152, all client loss: [0.629837691783905, 0.6330254673957825], all pred client disparities: [0.0745120644569397, 0.10596644878387451], all client disparities: [0.06170966476202011, 0.11213833093643188], all client accs: [0.6202582716941833, 0.6700471043586731],  alphas:tensor([0.5013, 0.0000, 0.0000, 0.4987], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:10,358 - utils - INFO - stage2_gradient_single_runtime: 0.0064280033111572266
2023-09-28 23:26:10,364 - utils - INFO - 1, epoch: 1153, all client loss: [0.6322969198226929, 0.6355091333389282], all pred client disparities: [0.06671091169118881, 0.10179370641708374], all client disparities: [0.05337633192539215, 0.11016753315925598], all client accs: [0.6174333691596985, 0.6664252281188965],  alphas:tensor([0.5010, 0.0000, 0.0000, 0.4990], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:10,429 - utils - INFO - stage2_gradient_single_runtime: 0.006252288818359375
2023-09-28 23:26:10,435 - utils - INFO - 1, epoch: 1154, all client loss: [0.6348013877868652, 0.6380430459976196], all pred client disparities: [0.05913833528757095, 0.09741497039794922], all client disparities: [0.041271500289440155, 0.10828056931495667], all client accs: [0.6113801002502441, 0.6620789766311646],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:10,495 - utils - INFO - stage2_gradient_single_runtime: 0.006155252456665039
2023-09-28 23:26:10,501 - utils - INFO - 1, epoch: 1155, all client loss: [0.6310983896255493, 0.6341909170150757], all pred client disparities: [0.07028195261955261, 0.1040143072605133], all client disparities: [0.0592096671462059, 0.11076653003692627], all client accs: [0.6198546886444092, 0.6682361364364624],  alphas:tensor([0.5011, 0.0000, 0.0000, 0.4989], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:10,563 - utils - INFO - stage2_gradient_single_runtime: 0.0062901973724365234
2023-09-28 23:26:10,568 - utils - INFO - 1, epoch: 1156, all client loss: [0.633572518825531, 0.636690080165863], all pred client disparities: [0.06263905763626099, 0.09976029396057129], all client disparities: [0.04587633162736893, 0.10999998450279236], all client accs: [0.6146085262298584, 0.6640710234642029],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:10,625 - utils - INFO - stage2_gradient_single_runtime: 0.006074428558349609
2023-09-28 23:26:10,631 - utils - INFO - 1, epoch: 1157, all client loss: [0.6299542188644409, 0.6329271793365479], all pred client disparities: [0.07374035567045212, 0.10610982775688171], all client disparities: [0.06170966476202011, 0.11343255639076233], all client accs: [0.6202582716941833, 0.6702281832695007],  alphas:tensor([0.5012, 0.0000, 0.0000, 0.4988], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:10,691 - utils - INFO - stage2_gradient_single_runtime: 0.006371974945068359
2023-09-28 23:26:10,694 - utils - INFO - 1, epoch: 1158, all client loss: [0.6323949098587036, 0.6353886127471924], all pred client disparities: [0.06605816632509232, 0.10197952389717102], all client disparities: [0.05087633058428764, 0.11034134030342102], all client accs: [0.6162227392196655, 0.6664252281188965],  alphas:tensor([0.5010, 0.0000, 0.0000, 0.4990], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:10,750 - utils - INFO - stage2_gradient_single_runtime: 0.00617671012878418
2023-09-28 23:26:10,753 - utils - INFO - 1, epoch: 1159, all client loss: [0.6348778605461121, 0.6378976702690125], all pred client disparities: [0.058608319610357285, 0.09765073657035828], all client disparities: [0.042500000447034836, 0.10802295804023743], all client accs: [0.6109765768051147, 0.6626222729682922],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:10,767 - utils - INFO - valid: True, epoch: 1159, loss: [0.6282991170883179, 0.6400439739227295], accuracy: [0.6351999640464783, 0.64654541015625], mean_accuracy:0.6408726871013641,variance_accuracy:0.005672723054885864, disparity: [0.05892782658338547, 0.13324850797653198], mean_disparity:0.09608816727995872,variance_disparity:0.03716034069657326, pred_disparity: [0.06912624835968018, 0.11626771092414856]
2023-09-28 23:26:10,778 - utils - INFO - global_valid: True, epoch: 1159,  global_loss: 0.63637375831604, global_accuracy: 0.6966941776710686,  global_disparity:0.12357752025127411, global_pred_disparity: 0.11269021034240723,
2023-09-28 23:26:10,897 - utils - INFO - stage2_gradient_single_runtime: 0.006442546844482422
2023-09-28 23:26:10,902 - utils - INFO - 1, epoch: 1160, all client loss: [0.631180465221405, 0.634057343006134], all pred client disparities: [0.06966803967952728, 0.10421839356422424], all client disparities: [0.05754299461841583, 0.11094033718109131], all client accs: [0.6190475821495056, 0.6684172749519348],  alphas:tensor([0.5010, 0.0000, 0.0000, 0.4990], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:10,965 - utils - INFO - stage2_gradient_single_runtime: 0.0063779354095458984
2023-09-28 23:26:10,971 - utils - INFO - 1, epoch: 1161, all client loss: [0.6336343884468079, 0.6365327835083008], all pred client disparities: [0.06214139610528946, 0.10001188516616821], all client disparities: [0.04504299536347389, 0.11043137311935425], all client accs: [0.614205002784729, 0.6642521023750305],  alphas:tensor([0.5008, 0.0000, 0.0000, 0.4992], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:11,034 - utils - INFO - stage2_gradient_single_runtime: 0.007042646408081055
2023-09-28 23:26:11,039 - utils - INFO - 1, epoch: 1162, all client loss: [0.636120080947876, 0.6390455961227417], all pred client disparities: [0.05490193888545036, 0.09561976790428162], all client disparities: [0.040833331644535065, 0.10587838292121887], all client accs: [0.6101694703102112, 0.6593625545501709],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:11,106 - utils - INFO - stage2_gradient_single_runtime: 0.00652766227722168
2023-09-28 23:26:11,110 - utils - INFO - 1, epoch: 1163, all client loss: [0.6341660618782043, 0.6373350620269775], all pred client disparities: [0.06115316227078438, 0.09821954369544983], all client disparities: [0.04627149552106857, 0.10887953639030457], all client accs: [0.6138014197349548, 0.6622600555419922],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:11,172 - utils - INFO - stage2_gradient_single_runtime: 0.006232261657714844
2023-09-28 23:26:11,177 - utils - INFO - 1, epoch: 1164, all client loss: [0.6305093765258789, 0.6335318684577942], all pred client disparities: [0.07225718349218369, 0.10464313626289368], all client disparities: [0.06004299595952034, 0.11101791262626648], all client accs: [0.6198546886444092, 0.669684886932373],  alphas:tensor([0.5011, 0.0000, 0.0000, 0.4989], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:11,234 - utils - INFO - stage2_gradient_single_runtime: 0.005970478057861328
2023-09-28 23:26:11,239 - utils - INFO - 1, epoch: 1165, all client loss: [0.6329523324966431, 0.6359972953796387], all pred client disparities: [0.06464489549398422, 0.1005081832408905], all client disparities: [0.05087633058428764, 0.11016753315925598], all client accs: [0.6166263222694397, 0.6647953987121582],  alphas:tensor([0.5009, 0.0000, 0.0000, 0.4991], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:11,299 - utils - INFO - stage2_gradient_single_runtime: 0.006181001663208008
2023-09-28 23:26:11,305 - utils - INFO - 1, epoch: 1166, all client loss: [0.6354331374168396, 0.6385059356689453], all pred client disparities: [0.057285163551568985, 0.09618178009986877], all client disparities: [0.042500000447034836, 0.10759153962135315], all client accs: [0.6109765768051147, 0.6606302261352539],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:11,371 - utils - INFO - stage2_gradient_single_runtime: 0.00640559196472168
2023-09-28 23:26:11,377 - utils - INFO - 1, epoch: 1167, all client loss: [0.6316996812820435, 0.634627640247345], all pred client disparities: [0.06833861768245697, 0.10281798243522644], all client disparities: [0.056709665805101395, 0.11076653003692627], all client accs: [0.6186440587043762, 0.6675118207931519],  alphas:tensor([0.5010, 0.0000, 0.0000, 0.4990], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:11,434 - utils - INFO - stage2_gradient_single_runtime: 0.006081342697143555
2023-09-28 23:26:11,439 - utils - INFO - 1, epoch: 1168, all client loss: [0.6341531872749329, 0.6371043920516968], all pred client disparities: [0.06088721379637718, 0.09861239790916443], all client disparities: [0.04543816298246384, 0.10862192511558533], all client accs: [0.6133978962898254, 0.6631655693054199],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:11,497 - utils - INFO - stage2_gradient_single_runtime: 0.006124973297119141
2023-09-28 23:26:11,502 - utils - INFO - 1, epoch: 1169, all client loss: [0.6305075287818909, 0.6333184838294983], all pred client disparities: [0.07191189378499985, 0.10499083995819092], all client disparities: [0.06004299595952034, 0.11119171977043152], all client accs: [0.6202582716941833, 0.669684886932373],  alphas:tensor([0.5011, 0.0000, 0.0000, 0.4989], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:11,562 - utils - INFO - stage2_gradient_single_runtime: 0.007451295852661133
2023-09-28 23:26:11,569 - utils - INFO - 1, epoch: 1170, all client loss: [0.6329302191734314, 0.6357600688934326], all pred client disparities: [0.0644022673368454, 0.10090562701225281], all client disparities: [0.05087633058428764, 0.10990992188453674], all client accs: [0.6166263222694397, 0.6657008528709412],  alphas:tensor([0.5008, 0.0000, 0.0000, 0.4992], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:11,627 - utils - INFO - stage2_gradient_single_runtime: 0.006232500076293945
2023-09-28 23:26:11,631 - utils - INFO - 1, epoch: 1171, all client loss: [0.6353891491889954, 0.6382433176040649], all pred client disparities: [0.057142455130815506, 0.09663477540016174], all client disparities: [0.042500000447034836, 0.10776534676551819], all client accs: [0.6109765768051147, 0.6608113050460815],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:11,693 - utils - INFO - stage2_gradient_single_runtime: 0.0061130523681640625
2023-09-28 23:26:11,698 - utils - INFO - 1, epoch: 1172, all client loss: [0.631668746471405, 0.6343843340873718], all pred client disparities: [0.06811796128749847, 0.10321858525276184], all client disparities: [0.056709665805101395, 0.11094033718109131], all client accs: [0.6186440587043762, 0.6675118207931519],  alphas:tensor([0.5009, 0.0000, 0.0000, 0.4991], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:11,812 - utils - INFO - stage2_gradient_single_runtime: 0.006086111068725586
2023-09-28 23:26:11,817 - utils - INFO - 1, epoch: 1173, all client loss: [0.6341012120246887, 0.636836588382721], all pred client disparities: [0.060763973742723465, 0.09906622767448425], all client disparities: [0.0446048304438591, 0.1090533435344696], all client accs: [0.6129943132400513, 0.6638898849487305],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:11,887 - utils - INFO - stage2_gradient_single_runtime: 0.00987553596496582
2023-09-28 23:26:11,893 - utils - INFO - 1, epoch: 1174, all client loss: [0.6304689645767212, 0.6330702900886536], all pred client disparities: [0.07171221822500229, 0.10539296269416809], all client disparities: [0.06004299595952034, 0.11128175258636475], all client accs: [0.6202582716941833, 0.6691416501998901],  alphas:tensor([0.5010, 0.0000, 0.0000, 0.4990], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:11,991 - utils - INFO - stage2_gradient_single_runtime: 0.009817838668823242
2023-09-28 23:26:11,999 - utils - INFO - 1, epoch: 1175, all client loss: [0.6328713297843933, 0.635487973690033], all pred client disparities: [0.06429759413003922, 0.10135886073112488], all client disparities: [0.05087633058428764, 0.10939472913742065], all client accs: [0.6166263222694397, 0.6658819317817688],  alphas:tensor([0.5008, 0.0000, 0.0000, 0.4992], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:12,067 - utils - INFO - stage2_gradient_single_runtime: 0.006127834320068359
2023-09-28 23:26:12,072 - utils - INFO - 1, epoch: 1176, all client loss: [0.6353086829185486, 0.6379462480545044], all pred client disparities: [0.05712827295064926, 0.097144216299057], all client disparities: [0.042500000447034836, 0.10819676518440247], all client accs: [0.6109765768051147, 0.6611735224723816],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:12,126 - utils - INFO - stage2_gradient_single_runtime: 0.0061779022216796875
2023-09-28 23:26:12,131 - utils - INFO - 1, epoch: 1177, all client loss: [0.6332470774650574, 0.6361391544342041], all pred client disparities: [0.0637514591217041, 0.0998430848121643], all client disparities: [0.04920966178178787, 0.10913094878196716], all client accs: [0.6158192157745361, 0.6646143198013306],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:12,191 - utils - INFO - stage2_gradient_single_runtime: 0.0061223506927490234
2023-09-28 23:26:12,196 - utils - INFO - 1, epoch: 1178, all client loss: [0.6296644806861877, 0.6324188709259033], all pred client disparities: [0.07473048567771912, 0.10600683093070984], all client disparities: [0.06337632238864899, 0.11247971653938293], all client accs: [0.6206617951393127, 0.6700471043586731],  alphas:tensor([0.5011, 0.0000, 0.0000, 0.4989], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:12,258 - utils - INFO - stage2_gradient_single_runtime: 0.007562875747680664
2023-09-28 23:26:12,267 - utils - INFO - 1, epoch: 1179, all client loss: [0.6320517063140869, 0.6348222494125366], all pred client disparities: [0.06723355501890182, 0.10205405950546265], all client disparities: [0.05504300072789192, 0.11033511161804199], all client accs: [0.6178369522094727, 0.6666063070297241],  alphas:tensor([0.5009, 0.0000, 0.0000, 0.4991], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:12,287 - utils - INFO - valid: True, epoch: 1179, loss: [0.631254255771637, 0.6429360508918762], accuracy: [0.6287999749183655, 0.6385454535484314], mean_accuracy:0.6336727142333984,variance_accuracy:0.004872739315032959, disparity: [0.04119732975959778, 0.12196582555770874], mean_disparity:0.08158157765865326,variance_disparity:0.04038424789905548, pred_disparity: [0.05975428596138954, 0.11022236943244934]
2023-09-28 23:26:12,298 - utils - INFO - global_valid: True, epoch: 1179,  global_loss: 0.6392855048179626, global_accuracy: 0.6900330132052821,  global_disparity:0.11093609035015106, global_pred_disparity: 0.10599842667579651,
2023-09-28 23:26:12,356 - utils - INFO - stage2_gradient_single_runtime: 0.007004261016845703
2023-09-28 23:26:12,360 - utils - INFO - 1, epoch: 1180, all client loss: [0.6344809532165527, 0.6372725963592529], all pred client disparities: [0.059942398220300674, 0.09791496396064758], all client disparities: [0.04293816536664963, 0.10819053649902344], all client accs: [0.6121872067451477, 0.6620789766311646],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:12,421 - utils - INFO - stage2_gradient_single_runtime: 0.00635838508605957
2023-09-28 23:26:12,425 - utils - INFO - 1, epoch: 1181, all client loss: [0.630824089050293, 0.6334798336029053], all pred client disparities: [0.07089157402515411, 0.10427695512771606], all client disparities: [0.0592096671462059, 0.11050271987915039], all client accs: [0.6198546886444092, 0.6691416501998901],  alphas:tensor([0.5010, 0.0000, 0.0000, 0.4990], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:12,489 - utils - INFO - stage2_gradient_single_runtime: 0.007267475128173828
2023-09-28 23:26:12,498 - utils - INFO - 1, epoch: 1182, all client loss: [0.6332241892814636, 0.6358967423439026], all pred client disparities: [0.06353044509887695, 0.10025486350059509], all client disparities: [0.048376329243183136, 0.10973614454269409], all client accs: [0.615415632724762, 0.6646143198013306],  alphas:tensor([0.5008, 0.0000, 0.0000, 0.4992], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:12,559 - utils - INFO - stage2_gradient_single_runtime: 0.005959987640380859
2023-09-28 23:26:12,564 - utils - INFO - 1, epoch: 1183, all client loss: [0.6356567740440369, 0.638351559638977], all pred client disparities: [0.05642437934875488, 0.09605750441551208], all client disparities: [0.042500000447034836, 0.10733392834663391], all client accs: [0.6109765768051147, 0.6602680683135986],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:12,693 - utils - INFO - stage2_gradient_single_runtime: 0.0062007904052734375
2023-09-28 23:26:12,699 - utils - INFO - 1, epoch: 1184, all client loss: [0.6319290995597839, 0.6344897747039795], all pred client disparities: [0.0673224925994873, 0.10261275619268417], all client disparities: [0.05587632954120636, 0.11076653003692627], all client accs: [0.618240475654602, 0.6671496033668518],  alphas:tensor([0.5008, 0.0000, 0.0000, 0.4992], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:12,765 - utils - INFO - stage2_gradient_single_runtime: 0.006045341491699219
2023-09-28 23:26:12,771 - utils - INFO - 1, epoch: 1185, all client loss: [0.6343369483947754, 0.6369152665138245], all pred client disparities: [0.06011229008436203, 0.09853038936853409], all client disparities: [0.0446048304438591, 0.10862192511558533], all client accs: [0.6129943132400513, 0.6628033518791199],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:12,830 - utils - INFO - stage2_gradient_single_runtime: 0.006098270416259766
2023-09-28 23:26:12,835 - utils - INFO - 1, epoch: 1186, all client loss: [0.6306992769241333, 0.6331478357315063], all pred client disparities: [0.07098880410194397, 0.1048259437084198], all client disparities: [0.0592096671462059, 0.11093413829803467], all client accs: [0.6198546886444092, 0.6693227291107178],  alphas:tensor([0.5009, 0.0000, 0.0000, 0.4991], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:12,896 - utils - INFO - stage2_gradient_single_runtime: 0.006097555160522461
2023-09-28 23:26:12,901 - utils - INFO - 1, epoch: 1187, all client loss: [0.633078396320343, 0.6355403065681458], all pred client disparities: [0.06370909512042999, 0.10085862874984741], all client disparities: [0.04920966178178787, 0.10965234041213989], all client accs: [0.6158192157745361, 0.6649764776229858],  alphas:tensor([0.5007, 0.0000, 0.0000, 0.4993], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:12,971 - utils - INFO - stage2_gradient_single_runtime: 0.00754094123840332
2023-09-28 23:26:12,977 - utils - INFO - 1, epoch: 1188, all client loss: [0.6354896426200867, 0.6379704475402832], all pred client disparities: [0.05667620897293091, 0.096719890832901], all client disparities: [0.042500000447034836, 0.10733392834663391], all client accs: [0.6109765768051147, 0.6609923839569092],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:13,034 - utils - INFO - stage2_gradient_single_runtime: 0.006006717681884766
2023-09-28 23:26:13,037 - utils - INFO - 1, epoch: 1189, all client loss: [0.6334372758865356, 0.6361814141273499], all pred client disparities: [0.06320024281740189, 0.09937892109155655], all client disparities: [0.048376329243183136, 0.10783672332763672], all client accs: [0.615415632724762, 0.6647953987121582],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:13,093 - utils - INFO - stage2_gradient_single_runtime: 0.006604909896850586
2023-09-28 23:26:13,097 - utils - INFO - 1, epoch: 1190, all client loss: [0.6298518776893616, 0.6324625015258789], all pred client disparities: [0.07411052286624908, 0.10550650954246521], all client disparities: [0.06170966476202011, 0.11204829812049866], all client accs: [0.6202582716941833, 0.6698660254478455],  alphas:tensor([0.5010, 0.0000, 0.0000, 0.4990], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:13,151 - utils - INFO - stage2_gradient_single_runtime: 0.0062351226806640625
2023-09-28 23:26:13,155 - utils - INFO - 1, epoch: 1191, all client loss: [0.63221675157547, 0.6348412036895752], all pred client disparities: [0.06674180924892426, 0.1016196608543396], all client disparities: [0.05504300072789192, 0.10929849743843079], all client accs: [0.618240475654602, 0.6666063070297241],  alphas:tensor([0.5008, 0.0000, 0.0000, 0.4992], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:13,229 - utils - INFO - stage2_gradient_single_runtime: 0.006066799163818359
2023-09-28 23:26:13,235 - utils - INFO - 1, epoch: 1192, all client loss: [0.6346204876899719, 0.6372640132904053], all pred client disparities: [0.05958053097128868, 0.09755519032478333], all client disparities: [0.04210482910275459, 0.10844814777374268], all client accs: [0.6117836833000183, 0.6615356802940369],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:13,297 - utils - INFO - stage2_gradient_single_runtime: 0.005967140197753906
2023-09-28 23:26:13,302 - utils - INFO - 1, epoch: 1193, all client loss: [0.6309641599655151, 0.6334758996963501], all pred client disparities: [0.07046008855104446, 0.10387039184570312], all client disparities: [0.0592096671462059, 0.11007130146026611], all client accs: [0.6198546886444092, 0.6685983538627625],  alphas:tensor([0.5009, 0.0000, 0.0000, 0.4991], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:13,366 - utils - INFO - stage2_gradient_single_runtime: 0.006286144256591797
2023-09-28 23:26:13,371 - utils - INFO - 1, epoch: 1194, all client loss: [0.6333401203155518, 0.6358665227890015], all pred client disparities: [0.06322266906499863, 0.09991991519927979], all client disparities: [0.048376329243183136, 0.10887333750724792], all client accs: [0.615415632724762, 0.6644331812858582],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:13,434 - utils - INFO - stage2_gradient_single_runtime: 0.007373809814453125
2023-09-28 23:26:13,439 - utils - INFO - 1, epoch: 1195, all client loss: [0.6297709941864014, 0.6321701407432556], all pred client disparities: [0.07405832409858704, 0.10599091649055481], all client disparities: [0.06170966476202011, 0.11153310537338257], all client accs: [0.6202582716941833, 0.6700471043586731],  alphas:tensor([0.5010, 0.0000, 0.0000, 0.4990], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:13,498 - utils - INFO - stage2_gradient_single_runtime: 0.006125450134277344
2023-09-28 23:26:13,500 - utils - INFO - 1, epoch: 1196, all client loss: [0.63211590051651, 0.6345252990722656], all pred client disparities: [0.06677631288766861, 0.10215383768081665], all client disparities: [0.05504300072789192, 0.11033511161804199], all client accs: [0.6178369522094727, 0.6666063070297241],  alphas:tensor([0.5008, 0.0000, 0.0000, 0.4992], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:13,608 - utils - INFO - stage2_gradient_single_runtime: 0.006219148635864258
2023-09-28 23:26:13,610 - utils - INFO - 1, epoch: 1197, all client loss: [0.6344987750053406, 0.6369238495826721], all pred client disparities: [0.059696342796087265, 0.0981435775756836], all client disparities: [0.04293816536664963, 0.10819053649902344], all client accs: [0.6121872067451477, 0.6620789766311646],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:13,677 - utils - INFO - stage2_gradient_single_runtime: 0.0064046382904052734
2023-09-28 23:26:13,680 - utils - INFO - 1, epoch: 1198, all client loss: [0.6308603286743164, 0.6331600546836853], all pred client disparities: [0.0705035999417305, 0.10439625382423401], all client disparities: [0.0592096671462059, 0.11007130146026611], all client accs: [0.6198546886444092, 0.6693227291107178],  alphas:tensor([0.5009, 0.0000, 0.0000, 0.4991], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:13,736 - utils - INFO - stage2_gradient_single_runtime: 0.006003618240356445
2023-09-28 23:26:13,740 - utils - INFO - 1, epoch: 1199, all client loss: [0.6332159638404846, 0.6355267763137817], all pred client disparities: [0.06334760040044785, 0.10049808025360107], all client disparities: [0.048376329243183136, 0.10973614454269409], all client accs: [0.615415632724762, 0.6646143198013306],  alphas:tensor([0.5007, 0.0000, 0.0000, 0.4993], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:13,754 - utils - INFO - valid: True, epoch: 1199, loss: [0.6322399377822876, 0.6435889601707458], accuracy: [0.6240000128746033, 0.6327272653579712], mean_accuracy:0.6283636391162872,variance_accuracy:0.00436362624168396, disparity: [0.039007093757390976, 0.11880794167518616], mean_disparity:0.07890751771628857,variance_disparity:0.03990042395889759, pred_disparity: [0.05634652450680733, 0.10874974727630615]
2023-09-28 23:26:13,765 - utils - INFO - global_valid: True, epoch: 1199,  global_loss: 0.6400423645973206, global_accuracy: 0.6881032412965186,  global_disparity:0.1081152856349945, global_pred_disparity: 0.10410721600055695,
2023-09-28 23:26:13,819 - utils - INFO - stage2_gradient_single_runtime: 0.00617218017578125
2023-09-28 23:26:13,822 - utils - INFO - 1, epoch: 1200, all client loss: [0.6356011629104614, 0.6379286646842957], all pred client disparities: [0.05643675848841667, 0.09643638134002686], all client disparities: [0.042500000447034836, 0.10759153962135315], all client accs: [0.6109765768051147, 0.6606302261352539],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:13,878 - utils - INFO - stage2_gradient_single_runtime: 0.006253719329833984
2023-09-28 23:26:13,881 - utils - INFO - 1, epoch: 1201, all client loss: [0.6318969130516052, 0.6341008543968201], all pred client disparities: [0.06719772517681122, 0.1028657853603363], all client disparities: [0.05587632954120636, 0.11076653003692627], all client accs: [0.618240475654602, 0.6671496033668518],  alphas:tensor([0.5007, 0.0000, 0.0000, 0.4993], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:13,943 - utils - INFO - stage2_gradient_single_runtime: 0.006171464920043945
2023-09-28 23:26:13,947 - utils - INFO - 1, epoch: 1202, all client loss: [0.6342589259147644, 0.6364749670028687], all pred client disparities: [0.06017964333295822, 0.09891408681869507], all client disparities: [0.0446048304438591, 0.10862192511558533], all client accs: [0.6129943132400513, 0.6631655693054199],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:14,009 - utils - INFO - stage2_gradient_single_runtime: 0.006520271301269531
2023-09-28 23:26:14,014 - utils - INFO - 1, epoch: 1203, all client loss: [0.6306454539299011, 0.6327422857284546], all pred client disparities: [0.07091957330703735, 0.10508635640144348], all client disparities: [0.0592096671462059, 0.11093413829803467], all client accs: [0.6198546886444092, 0.6693227291107178],  alphas:tensor([0.5008, 0.0000, 0.0000, 0.4992], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:14,070 - utils - INFO - stage2_gradient_single_runtime: 0.006219387054443359
2023-09-28 23:26:14,074 - utils - INFO - 1, epoch: 1204, all client loss: [0.6329801678657532, 0.6350846886634827], all pred client disparities: [0.0638289824128151, 0.1012449860572815], all client disparities: [0.05087633058428764, 0.10990992188453674], all client accs: [0.6166263222694397, 0.6655197739601135],  alphas:tensor([0.5006, 0.0000, 0.0000, 0.4994], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:14,135 - utils - INFO - stage2_gradient_single_runtime: 0.0061266422271728516
2023-09-28 23:26:14,140 - utils - INFO - 1, epoch: 1205, all client loss: [0.635344922542572, 0.6374627947807312], all pred client disparities: [0.05697207525372505, 0.09724286198616028], all client disparities: [0.042500000447034836, 0.10819676518440247], all client accs: [0.6109765768051147, 0.6606302261352539],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:14,203 - utils - INFO - stage2_gradient_single_runtime: 0.006158351898193359
2023-09-28 23:26:14,207 - utils - INFO - 1, epoch: 1206, all client loss: [0.6332733631134033, 0.6356674432754517], all pred client disparities: [0.06348700821399689, 0.09988447278738022], all client disparities: [0.05004299804568291, 0.10783672332763672], all client accs: [0.6162227392196655, 0.6649764776229858],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:14,263 - utils - INFO - stage2_gradient_single_runtime: 0.006198883056640625
2023-09-28 23:26:14,266 - utils - INFO - 1, epoch: 1207, all client loss: [0.629717230796814, 0.6319880485534668], all pred client disparities: [0.07425835728645325, 0.10587969422340393], all client disparities: [0.06337632238864899, 0.11204829812049866], all client accs: [0.6206617951393127, 0.669684886932373],  alphas:tensor([0.5009, 0.0000, 0.0000, 0.4991], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:14,327 - utils - INFO - stage2_gradient_single_runtime: 0.006432294845581055
2023-09-28 23:26:14,331 - utils - INFO - 1, epoch: 1208, all client loss: [0.6320371031761169, 0.6343158483505249], all pred client disparities: [0.06707488745450974, 0.10212013125419617], all client disparities: [0.05504300072789192, 0.1088671088218689], all client accs: [0.6178369522094727, 0.6671496033668518],  alphas:tensor([0.5007, 0.0000, 0.0000, 0.4993], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:14,393 - utils - INFO - stage2_gradient_single_runtime: 0.007536649703979492
2023-09-28 23:26:14,402 - utils - INFO - 1, epoch: 1209, all client loss: [0.634394109249115, 0.6366861462593079], all pred client disparities: [0.06008502095937729, 0.09819337725639343], all client disparities: [0.04543816298246384, 0.10896334052085876], all client accs: [0.6133978962898254, 0.6620789766311646],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:14,509 - utils - INFO - stage2_gradient_single_runtime: 0.0062770843505859375
2023-09-28 23:26:14,516 - utils - INFO - 1, epoch: 1210, all client loss: [0.6307712197303772, 0.6329419016838074], all pred client disparities: [0.07083138078451157, 0.10436135530471802], all client disparities: [0.0592096671462059, 0.11007130146026611], all client accs: [0.6198546886444092, 0.6687794327735901],  alphas:tensor([0.5008, 0.0000, 0.0000, 0.4992], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:14,575 - utils - INFO - stage2_gradient_single_runtime: 0.006251096725463867
2023-09-28 23:26:14,581 - utils - INFO - 1, epoch: 1211, all client loss: [0.6331012845039368, 0.6352807879447937], all pred client disparities: [0.06376650184392929, 0.10054407268762589], all client disparities: [0.05087633058428764, 0.10956233739852905], all client accs: [0.6166263222694397, 0.6647953987121582],  alphas:tensor([0.5006, 0.0000, 0.0000, 0.4994], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:14,648 - utils - INFO - stage2_gradient_single_runtime: 0.006901979446411133
2023-09-28 23:26:14,653 - utils - INFO - 1, epoch: 1212, all client loss: [0.635460615158081, 0.6376544833183289], all pred client disparities: [0.056935638189315796, 0.09656867384910583], all client disparities: [0.042500000447034836, 0.1074177622795105], all client accs: [0.6109765768051147, 0.6606302261352539],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:14,710 - utils - INFO - stage2_gradient_single_runtime: 0.006011962890625
2023-09-28 23:26:14,714 - utils - INFO - 1, epoch: 1213, all client loss: [0.6317743062973022, 0.6338485479354858], all pred client disparities: [0.06764048337936401, 0.10290449857711792], all client disparities: [0.056709665805101395, 0.10972991585731506], all client accs: [0.6186440587043762, 0.6675118207931519],  alphas:tensor([0.5007, 0.0000, 0.0000, 0.4993], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:14,768 - utils - INFO - stage2_gradient_single_runtime: 0.006166696548461914
2023-09-28 23:26:14,772 - utils - INFO - 1, epoch: 1214, all client loss: [0.6341105103492737, 0.6361945867538452], all pred client disparities: [0.06070500239729881, 0.09903660416603088], all client disparities: [0.04504299536347389, 0.10939472913742065], all client accs: [0.614205002784729, 0.6628033518791199],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:14,834 - utils - INFO - stage2_gradient_single_runtime: 0.006022453308105469
2023-09-28 23:26:14,838 - utils - INFO - 1, epoch: 1215, all client loss: [0.6305153369903564, 0.6324841380119324], all pred client disparities: [0.07138536125421524, 0.10511860251426697], all client disparities: [0.06004299595952034, 0.11076030135154724], all client accs: [0.6198546886444092, 0.6695038080215454],  alphas:tensor([0.5008, 0.0000, 0.0000, 0.4992], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:14,902 - utils - INFO - stage2_gradient_single_runtime: 0.006219387054443359
2023-09-28 23:26:14,906 - utils - INFO - 1, epoch: 1216, all client loss: [0.6328244805335999, 0.6347987055778503], all pred client disparities: [0.06437961012125015, 0.10135850310325623], all client disparities: [0.05087633058428764, 0.10973614454269409], all client accs: [0.6166263222694397, 0.6649764776229858],  alphas:tensor([0.5006, 0.0000, 0.0000, 0.4994], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:14,964 - utils - INFO - stage2_gradient_single_runtime: 0.006006479263305664
2023-09-28 23:26:14,968 - utils - INFO - 1, epoch: 1217, all client loss: [0.6351636648178101, 0.6371487975120544], all pred client disparities: [0.05759531259536743, 0.09744247794151306], all client disparities: [0.042500000447034836, 0.1074177622795105], all client accs: [0.6109765768051147, 0.6613546013832092],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:15,026 - utils - INFO - stage2_gradient_single_runtime: 0.006129026412963867
2023-09-28 23:26:15,031 - utils - INFO - 1, epoch: 1218, all client loss: [0.631506085395813, 0.6333776712417603], all pred client disparities: [0.06823938339948654, 0.10368800163269043], all client disparities: [0.05754299461841583, 0.11016133427619934], all client accs: [0.6190475821495056, 0.6680550575256348],  alphas:tensor([0.5007, 0.0000, 0.0000, 0.4993], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:15,097 - utils - INFO - stage2_gradient_single_runtime: 0.007246971130371094
2023-09-28 23:26:15,101 - utils - INFO - 1, epoch: 1219, all client loss: [0.6338217854499817, 0.6356998682022095], all pred client disparities: [0.06135617941617966, 0.0998779833316803], all client disparities: [0.04504299536347389, 0.10956856608390808], all client accs: [0.614205002784729, 0.6637088060379028],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:15,120 - utils - INFO - valid: True, epoch: 1219, loss: [0.6274970769882202, 0.6384589076042175], accuracy: [0.6351999640464783, 0.6501818299293518], mean_accuracy:0.642690896987915,variance_accuracy:0.007490932941436768, disparity: [0.05892782658338547, 0.13038688898086548], mean_disparity:0.09465735778212547,variance_disparity:0.035729531198740005, pred_disparity: [0.07131656259298325, 0.11802837252616882]
2023-09-28 23:26:15,132 - utils - INFO - global_valid: True, epoch: 1219,  global_loss: 0.635033369064331, global_accuracy: 0.6980872348939575,  global_disparity:0.1214880496263504, global_pred_disparity: 0.1145801693201065,
2023-09-28 23:26:15,192 - utils - INFO - stage2_gradient_single_runtime: 0.006255149841308594
2023-09-28 23:26:15,196 - utils - INFO - 1, epoch: 1220, all client loss: [0.6302545070648193, 0.6320233941078186], all pred client disparities: [0.07197131961584091, 0.1058744490146637], all client disparities: [0.06004299595952034, 0.11144933104515076], all client accs: [0.6194511651992798, 0.669684886932373],  alphas:tensor([0.5008, 0.0000, 0.0000, 0.4992], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:15,257 - utils - INFO - stage2_gradient_single_runtime: 0.0063323974609375
2023-09-28 23:26:15,263 - utils - INFO - 1, epoch: 1221, all client loss: [0.63254314661026, 0.6343139410018921], all pred client disparities: [0.06502274423837662, 0.10217052698135376], all client disparities: [0.05087633058428764, 0.10947853326797485], all client accs: [0.6162227392196655, 0.6660630702972412],  alphas:tensor([0.5006, 0.0000, 0.0000, 0.4994], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:15,388 - utils - INFO - stage2_gradient_single_runtime: 0.006144285202026367
2023-09-28 23:26:15,393 - utils - INFO - 1, epoch: 1222, all client loss: [0.6348623633384705, 0.6366409063339233], all pred client disparities: [0.05828310176730156, 0.09831288456916809], all client disparities: [0.041271500289440155, 0.10828056931495667], all client accs: [0.6113801002502441, 0.6620789766311646],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:15,454 - utils - INFO - stage2_gradient_single_runtime: 0.006377458572387695
2023-09-28 23:26:15,460 - utils - INFO - 1, epoch: 1223, all client loss: [0.632733941078186, 0.6348006725311279], all pred client disparities: [0.06496065855026245, 0.10098311305046082], all client disparities: [0.05087633058428764, 0.1087833046913147], all client accs: [0.6162227392196655, 0.6653386354446411],  alphas:tensor([0.5006, 0.0000, 0.0000, 0.4994], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:15,522 - utils - INFO - stage2_gradient_single_runtime: 0.006039142608642578
2023-09-28 23:26:15,528 - utils - INFO - 1, epoch: 1224, all client loss: [0.6350669860839844, 0.6371452808380127], all pred client disparities: [0.058172766119241714, 0.09710368514060974], all client disparities: [0.041271500289440155, 0.10775911808013916], all client accs: [0.6113801002502441, 0.6606302261352539],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:15,596 - utils - INFO - stage2_gradient_single_runtime: 0.006304025650024414
2023-09-28 23:26:15,601 - utils - INFO - 1, epoch: 1225, all client loss: [0.631413996219635, 0.6333765983581543], all pred client disparities: [0.06882985681295395, 0.10330694913864136], all client disparities: [0.05754299461841583, 0.11024510860443115], all client accs: [0.6190475821495056, 0.6669685244560242],  alphas:tensor([0.5007, 0.0000, 0.0000, 0.4993], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:15,659 - utils - INFO - stage2_gradient_single_runtime: 0.0061795711517333984
2023-09-28 23:26:15,665 - utils - INFO - 1, epoch: 1226, all client loss: [0.633723258972168, 0.6356928944587708], all pred client disparities: [0.061946891248226166, 0.09953299909830093], all client disparities: [0.04670966416597366, 0.10801050066947937], all client accs: [0.6146085262298584, 0.6640710234642029],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:15,725 - utils - INFO - stage2_gradient_single_runtime: 0.006056547164916992
2023-09-28 23:26:15,732 - utils - INFO - 1, epoch: 1227, all client loss: [0.6301607489585876, 0.6320189833641052], all pred client disparities: [0.0725708156824112, 0.10548925399780273], all client disparities: [0.060876332223415375, 0.11153310537338257], all client accs: [0.6198546886444092, 0.669684886932373],  alphas:tensor([0.5008, 0.0000, 0.0000, 0.4992], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:15,795 - utils - INFO - stage2_gradient_single_runtime: 0.007200002670288086
2023-09-28 23:26:15,800 - utils - INFO - 1, epoch: 1228, all client loss: [0.6324423551559448, 0.6343033313751221], all pred client disparities: [0.06562604010105133, 0.10182088613510132], all client disparities: [0.052542995661497116, 0.10895711183547974], all client accs: [0.6170298457145691, 0.6660630702972412],  alphas:tensor([0.5006, 0.0000, 0.0000, 0.4994], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:15,859 - utils - INFO - stage2_gradient_single_runtime: 0.006092548370361328
2023-09-28 23:26:15,865 - utils - INFO - 1, epoch: 1229, all client loss: [0.6347553730010986, 0.6366245746612549], all pred client disparities: [0.05888283625245094, 0.09799954295158386], all client disparities: [0.04210482910275459, 0.10844814777374268], all client accs: [0.6117836833000183, 0.6615356802940369],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:15,930 - utils - INFO - stage2_gradient_single_runtime: 0.006400585174560547
2023-09-28 23:26:15,936 - utils - INFO - 1, epoch: 1230, all client loss: [0.6311318874359131, 0.6328915357589722], all pred client disparities: [0.06947847455739975, 0.10411238670349121], all client disparities: [0.0592096671462059, 0.11024510860443115], all client accs: [0.6198546886444092, 0.6682361364364624],  alphas:tensor([0.5007, 0.0000, 0.0000, 0.4993], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:16,000 - utils - INFO - stage2_gradient_single_runtime: 0.0065059661865234375
2023-09-28 23:26:16,007 - utils - INFO - 1, epoch: 1231, all client loss: [0.6334208250045776, 0.6351841688156128], all pred client disparities: [0.06264616549015045, 0.1003950834274292], all client disparities: [0.048376329243183136, 0.10930472612380981], all client accs: [0.615415632724762, 0.6644331812858582],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:16,075 - utils - INFO - stage2_gradient_single_runtime: 0.006112813949584961
2023-09-28 23:26:16,081 - utils - INFO - 1, epoch: 1232, all client loss: [0.6357342600822449, 0.6375070810317993], all pred client disparities: [0.05604938045144081, 0.09653297066688538], all client disparities: [0.042500000447034836, 0.10716015100479126], all client accs: [0.6109765768051147, 0.6604491472244263],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:16,196 - utils - INFO - stage2_gradient_single_runtime: 0.006299734115600586
2023-09-28 23:26:16,202 - utils - INFO - 1, epoch: 1233, all client loss: [0.6336848139762878, 0.6357502341270447], all pred client disparities: [0.06235945224761963, 0.09909579157829285], all client disparities: [0.04670966416597366, 0.10809430480003357], all client accs: [0.6146085262298584, 0.6637088060379028],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:16,265 - utils - INFO - stage2_gradient_single_runtime: 0.006193876266479492
2023-09-28 23:26:16,272 - utils - INFO - 1, epoch: 1234, all client loss: [0.6301231980323792, 0.632074773311615], all pred client disparities: [0.07299305498600006, 0.10502341389656067], all client disparities: [0.06170966476202011, 0.1117907166481018], all client accs: [0.6202582716941833, 0.6687794327735901],  alphas:tensor([0.5008, 0.0000, 0.0000, 0.4992], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:16,331 - utils - INFO - stage2_gradient_single_runtime: 0.006128787994384766
2023-09-28 23:26:16,337 - utils - INFO - 1, epoch: 1235, all client loss: [0.6323990821838379, 0.6343543529510498], all pred client disparities: [0.06605501472949982, 0.10138505697250366], all client disparities: [0.05504300072789192, 0.1088671088218689], all client accs: [0.618240475654602, 0.6655197739601135],  alphas:tensor([0.5006, 0.0000, 0.0000, 0.4994], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:16,398 - utils - INFO - stage2_gradient_single_runtime: 0.006064653396606445
2023-09-28 23:26:16,405 - utils - INFO - 1, epoch: 1236, all client loss: [0.6347068548202515, 0.6366710662841797], all pred client disparities: [0.059313464909791946, 0.09759491682052612], all client disparities: [0.04293816536664963, 0.10723769664764404], all client accs: [0.6121872067451477, 0.6615356802940369],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:16,467 - utils - INFO - stage2_gradient_single_runtime: 0.006143093109130859
2023-09-28 23:26:16,473 - utils - INFO - 1, epoch: 1237, all client loss: [0.6310848593711853, 0.6329371929168701], all pred client disparities: [0.0699206292629242, 0.10367625951766968], all client disparities: [0.0592096671462059, 0.11032888293266296], all client accs: [0.6198546886444092, 0.6675118207931519],  alphas:tensor([0.5007, 0.0000, 0.0000, 0.4993], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:16,532 - utils - INFO - stage2_gradient_single_runtime: 0.006150245666503906
2023-09-28 23:26:16,538 - utils - INFO - 1, epoch: 1238, all client loss: [0.6333682537078857, 0.6352251172065735], all pred client disparities: [0.0630924254655838, 0.09998965263366699], all client disparities: [0.05004299804568291, 0.10783672332763672], all client accs: [0.6162227392196655, 0.6647953987121582],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:16,600 - utils - INFO - stage2_gradient_single_runtime: 0.006228923797607422
2023-09-28 23:26:16,606 - utils - INFO - 1, epoch: 1239, all client loss: [0.6298363208770752, 0.6315853595733643], all pred client disparities: [0.07365874946117401, 0.1058301031589508], all client disparities: [0.06170966476202011, 0.11204829812049866], all client accs: [0.6202582716941833, 0.669684886932373],  alphas:tensor([0.5008, 0.0000, 0.0000, 0.4992], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:16,620 - utils - INFO - valid: True, epoch: 1239, loss: [0.6291579008102417, 0.640100359916687], accuracy: [0.6319999694824219, 0.6472727060317993], mean_accuracy:0.6396363377571106,variance_accuracy:0.007636368274688721, disparity: [0.05183562636375427, 0.13038688898086548], mean_disparity:0.09111125767230988,variance_disparity:0.0392756313085556, pred_disparity: [0.06633082777261734, 0.11462321877479553]
2023-09-28 23:26:16,631 - utils - INFO - global_valid: True, epoch: 1239,  global_loss: 0.6366809010505676, global_accuracy: 0.6941956782713086,  global_disparity:0.11986465752124786, global_pred_disparity: 0.11089201271533966,
2023-09-28 23:26:16,695 - utils - INFO - stage2_gradient_single_runtime: 0.006242990493774414
2023-09-28 23:26:16,701 - utils - INFO - 1, epoch: 1240, all client loss: [0.6320914626121521, 0.6338409185409546], all pred client disparities: [0.06677619367837906, 0.10224699974060059], all client disparities: [0.05504300072789192, 0.1088671088218689], all client accs: [0.6178369522094727, 0.6667873859405518],  alphas:tensor([0.5006, 0.0000, 0.0000, 0.4994], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:16,765 - utils - INFO - stage2_gradient_single_runtime: 0.006516933441162109
2023-09-28 23:26:16,771 - utils - INFO - 1, epoch: 1241, all client loss: [0.6343792676925659, 0.6361343860626221], all pred client disparities: [0.06007738783955574, 0.09851396083831787], all client disparities: [0.044209666550159454, 0.10861572623252869], all client accs: [0.6138014197349548, 0.6626222729682922],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:16,830 - utils - INFO - stage2_gradient_single_runtime: 0.006131410598754883
2023-09-28 23:26:16,837 - utils - INFO - 1, epoch: 1242, all client loss: [0.6307878494262695, 0.6324370503425598], all pred client disparities: [0.07062239944934845, 0.10450437664985657], all client disparities: [0.0592096671462059, 0.1105864942073822], all client accs: [0.6198546886444092, 0.6687794327735901],  alphas:tensor([0.5007, 0.0000, 0.0000, 0.4993], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:16,898 - utils - INFO - stage2_gradient_single_runtime: 0.006244182586669922
2023-09-28 23:26:16,903 - utils - INFO - 1, epoch: 1243, all client loss: [0.6330509781837463, 0.6347014307975769], all pred client disparities: [0.06384319067001343, 0.10087341070175171], all client disparities: [0.05087633058428764, 0.10869953036308289], all client accs: [0.6166263222694397, 0.6649764776229858],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:16,965 - utils - INFO - stage2_gradient_single_runtime: 0.00612950325012207
2023-09-28 23:26:16,970 - utils - INFO - 1, epoch: 1244, all client loss: [0.6353402137756348, 0.6369974613189697], all pred client disparities: [0.05728067830204964, 0.09709995985031128], all client disparities: [0.042500000447034836, 0.10793295502662659], all client accs: [0.6109765768051147, 0.6606302261352539],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:17,081 - utils - INFO - stage2_gradient_single_runtime: 0.006291389465332031
2023-09-28 23:26:17,086 - utils - INFO - 1, epoch: 1245, all client loss: [0.6316921710968018, 0.6332454085350037], all pred client disparities: [0.06779170036315918, 0.10323569178581238], all client disparities: [0.056709665805101395, 0.1099875271320343], all client accs: [0.6186440587043762, 0.6671496033668518],  alphas:tensor([0.5006, 0.0000, 0.0000, 0.4994], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:17,150 - utils - INFO - stage2_gradient_single_runtime: 0.0065081119537353516
2023-09-28 23:26:17,156 - utils - INFO - 1, epoch: 1246, all client loss: [0.6339601874351501, 0.635515570640564], all pred client disparities: [0.06112324818968773, 0.09956252574920654], all client disparities: [0.04504299536347389, 0.10775288939476013], all client accs: [0.614205002784729, 0.6638898849487305],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:17,217 - utils - INFO - stage2_gradient_single_runtime: 0.006340980529785156
2023-09-28 23:26:17,223 - utils - INFO - 1, epoch: 1247, all client loss: [0.6304044723510742, 0.6318598985671997], all pred client disparities: [0.07160808145999908, 0.1054498553276062], all client disparities: [0.06004299595952034, 0.11127552390098572], all client accs: [0.6194511651992798, 0.6698660254478455],  alphas:tensor([0.5007, 0.0000, 0.0000, 0.4993], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:17,287 - utils - INFO - stage2_gradient_single_runtime: 0.006278038024902344
2023-09-28 23:26:17,294 - utils - INFO - 1, epoch: 1248, all client loss: [0.6326469779014587, 0.6341003179550171], all pred client disparities: [0.0648677796125412, 0.10187757015228271], all client disparities: [0.05087633058428764, 0.10938853025436401], all client accs: [0.6162227392196655, 0.6660630702972412],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:17,355 - utils - INFO - stage2_gradient_single_runtime: 0.006288766860961914
2023-09-28 23:26:17,360 - utils - INFO - 1, epoch: 1249, all client loss: [0.6349172592163086, 0.6363739967346191], all pred client disparities: [0.058328207582235336, 0.09816354513168335], all client disparities: [0.041271500289440155, 0.10793295502662659], all client accs: [0.6113801002502441, 0.6613546013832092],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:17,422 - utils - INFO - stage2_gradient_single_runtime: 0.006337404251098633
2023-09-28 23:26:17,427 - utils - INFO - 1, epoch: 1250, all client loss: [0.6313053369522095, 0.6326640248298645], all pred client disparities: [0.06878525018692017, 0.10419327020645142], all client disparities: [0.05754299461841583, 0.1099875271320343], all client accs: [0.6190475821495056, 0.6682361364364624],  alphas:tensor([0.5006, 0.0000, 0.0000, 0.4994], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:17,486 - utils - INFO - stage2_gradient_single_runtime: 0.0063648223876953125
2023-09-28 23:26:17,492 - utils - INFO - 1, epoch: 1251, all client loss: [0.6335535645484924, 0.6349111199378967], all pred client disparities: [0.06214900314807892, 0.10057848691940308], all client disparities: [0.0475429967045784, 0.10930472612380981], all client accs: [0.6150121092796326, 0.6646143198013306],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:17,554 - utils - INFO - stage2_gradient_single_runtime: 0.006186723709106445
2023-09-28 23:26:17,560 - utils - INFO - 1, epoch: 1252, all client loss: [0.6358233690261841, 0.6371855735778809], all pred client disparities: [0.055742647498846054, 0.09682914614677429], all client disparities: [0.042500000447034836, 0.10759153962135315], all client accs: [0.6109765768051147, 0.6602680683135986],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:17,621 - utils - INFO - stage2_gradient_single_runtime: 0.0065228939056396484
2023-09-28 23:26:17,628 - utils - INFO - 1, epoch: 1253, all client loss: [0.6337825655937195, 0.6354490518569946], all pred client disparities: [0.061933115124702454, 0.09934529662132263], all client disparities: [0.04670966416597366, 0.10783672332763672], all client accs: [0.6146085262298584, 0.6635277271270752],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:17,686 - utils - INFO - stage2_gradient_single_runtime: 0.006072282791137695
2023-09-28 23:26:17,691 - utils - INFO - 1, epoch: 1254, all client loss: [0.630236029624939, 0.6317998766899109], all pred client disparities: [0.07243015617132187, 0.10518452525138855], all client disparities: [0.060876332223415375, 0.1117907166481018], all client accs: [0.6198546886444092, 0.6691416501998901],  alphas:tensor([0.5007, 0.0000, 0.0000, 0.4993], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:17,756 - utils - INFO - stage2_gradient_single_runtime: 0.006270885467529297
2023-09-28 23:26:17,762 - utils - INFO - 1, epoch: 1255, all client loss: [0.6324719190597534, 0.6340343952178955], all pred client disparities: [0.06568212062120438, 0.10164719820022583], all client disparities: [0.05337633192539215, 0.10929849743843079], all client accs: [0.6174333691596985, 0.6653386354446411],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:17,824 - utils - INFO - stage2_gradient_single_runtime: 0.006537675857543945
2023-09-28 23:26:17,830 - utils - INFO - 1, epoch: 1256, all client loss: [0.6347370147705078, 0.6363034248352051], all pred client disparities: [0.05912572145462036, 0.09796804189682007], all client disparities: [0.04293816536664963, 0.1081005334854126], all client accs: [0.6121872067451477, 0.6613546013832092],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:17,893 - utils - INFO - stage2_gradient_single_runtime: 0.0063016414642333984
2023-09-28 23:26:17,899 - utils - INFO - 1, epoch: 1257, all client loss: [0.6311344504356384, 0.6326001882553101], all pred client disparities: [0.06959827244281769, 0.10394775867462158], all client disparities: [0.0592096671462059, 0.11007130146026611], all client accs: [0.6198546886444092, 0.6673306822776794],  alphas:tensor([0.5006, 0.0000, 0.0000, 0.4994], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:18,009 - utils - INFO - stage2_gradient_single_runtime: 0.00612187385559082
2023-09-28 23:26:18,015 - utils - INFO - 1, epoch: 1258, all client loss: [0.6333765983581543, 0.634841799736023], all pred client disparities: [0.06295101344585419, 0.10036766529083252], all client disparities: [0.05004299804568291, 0.10783672332763672], all client accs: [0.6162227392196655, 0.6649764776229858],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:18,076 - utils - INFO - stage2_gradient_single_runtime: 0.0063076019287109375
2023-09-28 23:26:18,082 - utils - INFO - 1, epoch: 1259, all client loss: [0.6356417536735535, 0.6371120810508728], all pred client disparities: [0.05652470141649246, 0.09665283560752869], all client disparities: [0.042500000447034836, 0.10750153660774231], all client accs: [0.6109765768051147, 0.6599058508872986],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:18,098 - utils - INFO - valid: True, epoch: 1259, loss: [0.6304922699928284, 0.6414573788642883], accuracy: [0.6319999694824219, 0.6392726898193359], mean_accuracy:0.6356363296508789,variance_accuracy:0.0036363601684570312, disparity: [0.04828952997922897, 0.12557336688041687], mean_disparity:0.08693144842982292,variance_disparity:0.03864191845059395, pred_disparity: [0.06260672211647034, 0.11179301142692566]
2023-09-28 23:26:18,110 - utils - INFO - global_valid: True, epoch: 1259,  global_loss: 0.6380307674407959, global_accuracy: 0.6911934773909564,  global_disparity:0.11538027226924896, global_pred_disparity: 0.10792627930641174,
2023-09-28 23:26:18,168 - utils - INFO - stage2_gradient_single_runtime: 0.006261587142944336
2023-09-28 23:26:18,173 - utils - INFO - 1, epoch: 1260, all client loss: [0.6335594654083252, 0.6353372931480408], all pred client disparities: [0.06287535279989243, 0.0992075502872467], all client disparities: [0.05004299804568291, 0.10680007934570312], all client accs: [0.6162227392196655, 0.6635277271270752],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:18,233 - utils - INFO - stage2_gradient_single_runtime: 0.006051301956176758
2023-09-28 23:26:18,238 - utils - INFO - 1, epoch: 1261, all client loss: [0.6300249695777893, 0.6316977143287659], all pred client disparities: [0.07338233292102814, 0.10499197244644165], all client disparities: [0.06170966476202011, 0.11221590638160706], all client accs: [0.6202582716941833, 0.6689605712890625],  alphas:tensor([0.5007, 0.0000, 0.0000, 0.4993], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:18,301 - utils - INFO - stage2_gradient_single_runtime: 0.006453752517700195
2023-09-28 23:26:18,307 - utils - INFO - 1, epoch: 1262, all client loss: [0.6322535872459412, 0.6339254379272461], all pred client disparities: [0.06662510335445404, 0.1014920100569725], all client disparities: [0.05587632954120636, 0.10826191306114197], all client accs: [0.618240475654602, 0.6655197739601135],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:18,364 - utils - INFO - stage2_gradient_single_runtime: 0.006102800369262695
2023-09-28 23:26:18,369 - utils - INFO - 1, epoch: 1263, all client loss: [0.634512722492218, 0.6361888647079468], all pred client disparities: [0.06004900485277176, 0.0978502631187439], all client disparities: [0.044209666550159454, 0.1071476936340332], all client accs: [0.6138014197349548, 0.6617168188095093],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:18,430 - utils - INFO - stage2_gradient_single_runtime: 0.006220579147338867
2023-09-28 23:26:18,435 - utils - INFO - 1, epoch: 1264, all client loss: [0.6309224367141724, 0.6324954032897949], all pred client disparities: [0.07053534686565399, 0.10377335548400879], all client disparities: [0.0592096671462059, 0.11110168695449829], all client accs: [0.6198546886444092, 0.6678739786148071],  alphas:tensor([0.5006, 0.0000, 0.0000, 0.4994], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:18,498 - utils - INFO - stage2_gradient_single_runtime: 0.007631778717041016
2023-09-28 23:26:18,503 - utils - INFO - 1, epoch: 1265, all client loss: [0.6331577897071838, 0.6347306966781616], all pred client disparities: [0.06387519836425781, 0.1002303957939148], all client disparities: [0.05087633058428764, 0.10748910903930664], all client accs: [0.6166263222694397, 0.6646143198013306],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:18,557 - utils - INFO - stage2_gradient_single_runtime: 0.006165742874145508
2023-09-28 23:26:18,560 - utils - INFO - 1, epoch: 1266, all client loss: [0.6354177594184875, 0.6369960904121399], all pred client disparities: [0.05742572247982025, 0.09655225276947021], all client disparities: [0.041271500289440155, 0.10594350099563599], all client accs: [0.6113801002502441, 0.6604491472244263],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:18,611 - utils - INFO - stage2_gradient_single_runtime: 0.00621795654296875
2023-09-28 23:26:18,614 - utils - INFO - 1, epoch: 1267, all client loss: [0.631774365901947, 0.6332513689994812], all pred client disparities: [0.06788048893213272, 0.10260951519012451], all client disparities: [0.05754299461841583, 0.10938230156898499], all client accs: [0.6190475821495056, 0.6664252281188965],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:18,671 - utils - INFO - stage2_gradient_single_runtime: 0.00617218017578125
2023-09-28 23:26:18,677 - utils - INFO - 1, epoch: 1268, all client loss: [0.634013831615448, 0.6354917287826538], all pred client disparities: [0.061323270201683044, 0.09902843832969666], all client disparities: [0.04587633162736893, 0.10783672332763672], all client accs: [0.614205002784729, 0.6629844307899475],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:18,737 - utils - INFO - stage2_gradient_single_runtime: 0.006455421447753906
2023-09-28 23:26:18,742 - utils - INFO - 1, epoch: 1269, all client loss: [0.6304641366004944, 0.631844699382782], all pred client disparities: [0.07175090163946152, 0.10483881831169128], all client disparities: [0.06004299595952034, 0.11135929822921753], all client accs: [0.6194511651992798, 0.6685983538627625],  alphas:tensor([0.5006, 0.0000, 0.0000, 0.4994], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:18,800 - utils - INFO - stage2_gradient_single_runtime: 0.006128072738647461
2023-09-28 23:26:18,805 - utils - INFO - 1, epoch: 1270, all client loss: [0.6326788663864136, 0.634056031703949], all pred client disparities: [0.06512020528316498, 0.1013554036617279], all client disparities: [0.052542995661497116, 0.10817807912826538], all client accs: [0.6170298457145691, 0.6655197739601135],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:18,863 - utils - INFO - stage2_gradient_single_runtime: 0.006158113479614258
2023-09-28 23:26:18,868 - utils - INFO - 1, epoch: 1271, all client loss: [0.6349202394485474, 0.6362993121147156], all pred client disparities: [0.058682508766651154, 0.09773692488670349], all client disparities: [0.04293816536664963, 0.10723769664764404], all client accs: [0.6121872067451477, 0.6615356802940369],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:18,988 - utils - INFO - stage2_gradient_single_runtime: 0.007100343704223633
2023-09-28 23:26:18,993 - utils - INFO - 1, epoch: 1272, all client loss: [0.6313176155090332, 0.632601261138916], all pred client disparities: [0.06908519566059113, 0.10367932915687561], all client disparities: [0.05837633088231087, 0.11007130146026611], all client accs: [0.6194511651992798, 0.6673306822776794],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:19,052 - utils - INFO - stage2_gradient_single_runtime: 0.006088972091674805
2023-09-28 23:26:19,057 - utils - INFO - 1, epoch: 1273, all client loss: [0.6335374116897583, 0.6348185539245605], all pred client disparities: [0.06255089491605759, 0.10015708208084106], all client disparities: [0.05004299804568291, 0.10783672332763672], all client accs: [0.6162227392196655, 0.6644331812858582],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:19,117 - utils - INFO - stage2_gradient_single_runtime: 0.00606846809387207
2023-09-28 23:26:19,122 - utils - INFO - 1, epoch: 1274, all client loss: [0.6357782483100891, 0.6370625495910645], all pred client disparities: [0.0562361441552639, 0.09650623798370361], all client disparities: [0.042500000447034836, 0.10663872957229614], all client accs: [0.6109765768051147, 0.6599058508872986],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:19,180 - utils - INFO - stage2_gradient_single_runtime: 0.006250858306884766
2023-09-28 23:26:19,185 - utils - INFO - 1, epoch: 1275, all client loss: [0.6337021589279175, 0.6353012323379517], all pred client disparities: [0.06251108646392822, 0.09903085231781006], all client disparities: [0.048376329243183136, 0.10636866092681885], all client accs: [0.615415632724762, 0.6631655693054199],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:19,243 - utils - INFO - stage2_gradient_single_runtime: 0.006070852279663086
2023-09-28 23:26:19,248 - utils - INFO - 1, epoch: 1276, all client loss: [0.630169689655304, 0.6316688060760498], all pred client disparities: [0.0729503184556961, 0.10477453470230103], all client disparities: [0.06170966476202011, 0.1124734878540039], all client accs: [0.6202582716941833, 0.6687794327735901],  alphas:tensor([0.5006, 0.0000, 0.0000, 0.4994], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:19,306 - utils - INFO - stage2_gradient_single_runtime: 0.00620722770690918
2023-09-28 23:26:19,311 - utils - INFO - 1, epoch: 1277, all client loss: [0.6323767304420471, 0.6338728070259094], all pred client disparities: [0.06630123406648636, 0.1013311967253685], all client disparities: [0.05587632954120636, 0.10739907622337341], all client accs: [0.618240475654602, 0.6657008528709412],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:19,373 - utils - INFO - stage2_gradient_single_runtime: 0.007151365280151367
2023-09-28 23:26:19,378 - utils - INFO - 1, epoch: 1278, all client loss: [0.6346123814582825, 0.6361106634140015], all pred client disparities: [0.05983245000243187, 0.09775194525718689], all client disparities: [0.044209666550159454, 0.10628488659858704], all client accs: [0.6138014197349548, 0.6617168188095093],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:19,438 - utils - INFO - stage2_gradient_single_runtime: 0.0063610076904296875
2023-09-28 23:26:19,443 - utils - INFO - 1, epoch: 1279, all client loss: [0.6310269236564636, 0.6324270963668823], all pred client disparities: [0.0702512338757515, 0.10362651199102402], all client disparities: [0.0592096671462059, 0.1106702983379364], all client accs: [0.6198546886444092, 0.6678739786148071],  alphas:tensor([0.5006, 0.0000, 0.0000, 0.4994], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:19,457 - utils - INFO - valid: True, epoch: 1279, loss: [0.6302112340927124, 0.6408998370170593], accuracy: [0.6319999694824219, 0.6407272815704346], mean_accuracy:0.6363636255264282,variance_accuracy:0.004363656044006348, disparity: [0.04828952997922897, 0.1272290050983429], mean_disparity:0.08775926753878593,variance_disparity:0.03946973755955696, pred_disparity: [0.06338176876306534, 0.1126997172832489]
2023-09-28 23:26:19,469 - utils - INFO - global_valid: True, epoch: 1279,  global_loss: 0.637559711933136, global_accuracy: 0.6919707883153261,  global_disparity:0.11661790311336517, global_pred_disparity: 0.10879509150981903,
2023-09-28 23:26:19,527 - utils - INFO - stage2_gradient_single_runtime: 0.0061953067779541016
2023-09-28 23:26:19,532 - utils - INFO - 1, epoch: 1280, all client loss: [0.6332398653030396, 0.6346378922462463], all pred client disparities: [0.06369471549987793, 0.1001434326171875], all client disparities: [0.05087633058428764, 0.10662627220153809], all client accs: [0.6166263222694397, 0.6644331812858582],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:19,592 - utils - INFO - stage2_gradient_single_runtime: 0.0068399906158447266
2023-09-28 23:26:19,598 - utils - INFO - 1, epoch: 1281, all client loss: [0.635475754737854, 0.6368770599365234], all pred client disparities: [0.05734555795788765, 0.09653070569038391], all client disparities: [0.041271500289440155, 0.10620111227035522], all client accs: [0.6113801002502441, 0.6604491472244263],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:19,659 - utils - INFO - stage2_gradient_single_runtime: 0.00625157356262207
2023-09-28 23:26:19,664 - utils - INFO - 1, epoch: 1282, all client loss: [0.6318399310112, 0.6331449747085571], all pred client disparities: [0.0677342414855957, 0.10253173112869263], all client disparities: [0.05754299461841583, 0.10895088315010071], all client accs: [0.6190475821495056, 0.6660630702972412],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:19,722 - utils - INFO - stage2_gradient_single_runtime: 0.006109476089477539
2023-09-28 23:26:19,727 - utils - INFO - 1, epoch: 1283, all client loss: [0.6340563297271729, 0.635360062122345], all pred client disparities: [0.061275046318769455, 0.09901347756385803], all client disparities: [0.04587633162736893, 0.10766288638114929], all client accs: [0.614205002784729, 0.6628033518791199],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:19,840 - utils - INFO - stage2_gradient_single_runtime: 0.006964206695556641
2023-09-28 23:26:19,845 - utils - INFO - 1, epoch: 1284, all client loss: [0.6305148005485535, 0.6317262649536133], all pred client disparities: [0.07163739949464798, 0.10476839542388916], all client disparities: [0.06004299595952034, 0.11135929822921753], all client accs: [0.6194511651992798, 0.6680550575256348],  alphas:tensor([0.5006, 0.0000, 0.0000, 0.4994], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:19,901 - utils - INFO - stage2_gradient_single_runtime: 0.0058667659759521484
2023-09-28 23:26:19,906 - utils - INFO - 1, epoch: 1285, all client loss: [0.6327072978019714, 0.6339131593704224], all pred client disparities: [0.06510249525308609, 0.10134539008140564], all client disparities: [0.052542995661497116, 0.10800430178642273], all client accs: [0.6170298457145691, 0.6655197739601135],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:19,962 - utils - INFO - stage2_gradient_single_runtime: 0.00576019287109375
2023-09-28 23:26:19,966 - utils - INFO - 1, epoch: 1286, all client loss: [0.6349252462387085, 0.6361309289932251], all pred client disparities: [0.05875616893172264, 0.09779238700866699], all client disparities: [0.04293816536664963, 0.10706391930580139], all client accs: [0.6121872067451477, 0.6617168188095093],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:20,023 - utils - INFO - stage2_gradient_single_runtime: 0.00576019287109375
2023-09-28 23:26:20,028 - utils - INFO - 1, epoch: 1287, all client loss: [0.6313331723213196, 0.6324484348297119], all pred client disparities: [0.06909523159265518, 0.10367226600646973], all client disparities: [0.05837633088231087, 0.11032888293266296], all client accs: [0.6194511651992798, 0.6675118207931519],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:20,089 - utils - INFO - stage2_gradient_single_runtime: 0.0063245296478271484
2023-09-28 23:26:20,093 - utils - INFO - 1, epoch: 1288, all client loss: [0.63353031873703, 0.6346408128738403], all pred client disparities: [0.06265135854482651, 0.10021308064460754], all client disparities: [0.05004299804568291, 0.10766288638114929], all client accs: [0.6162227392196655, 0.6646143198013306],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:20,148 - utils - INFO - stage2_gradient_single_runtime: 0.005797386169433594
2023-09-28 23:26:20,153 - utils - INFO - 1, epoch: 1289, all client loss: [0.6357476115226746, 0.636859118938446], all pred client disparities: [0.056420646607875824, 0.09662967920303345], all client disparities: [0.042500000447034836, 0.10672250390052795], all client accs: [0.6109765768051147, 0.6595436334609985],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:20,209 - utils - INFO - stage2_gradient_single_runtime: 0.005796670913696289
2023-09-28 23:26:20,214 - utils - INFO - 1, epoch: 1290, all client loss: [0.6336594223976135, 0.6350927948951721], all pred client disparities: [0.0627000704407692, 0.09914633631706238], all client disparities: [0.05004299804568291, 0.10593727231025696], all client accs: [0.6162227392196655, 0.6629844307899475],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:20,271 - utils - INFO - stage2_gradient_single_runtime: 0.005711555480957031
2023-09-28 23:26:20,276 - utils - INFO - 1, epoch: 1291, all client loss: [0.6301401257514954, 0.6314785480499268], all pred client disparities: [0.07307414710521698, 0.10482355952262878], all client disparities: [0.06170966476202011, 0.11273109912872314], all client accs: [0.6202582716941833, 0.6685983538627625],  alphas:tensor([0.5006, 0.0000, 0.0000, 0.4994], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:20,341 - utils - INFO - stage2_gradient_single_runtime: 0.006831645965576172
2023-09-28 23:26:20,347 - utils - INFO - 1, epoch: 1292, all client loss: [0.6323244571685791, 0.6336573958396912], all pred client disparities: [0.06651372462511063, 0.1014433205127716], all client disparities: [0.05587632954120636, 0.10748288035392761], all client accs: [0.618240475654602, 0.6662441492080688],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:20,399 - utils - INFO - stage2_gradient_single_runtime: 0.005785465240478516
2023-09-28 23:26:20,401 - utils - INFO - 1, epoch: 1293, all client loss: [0.634536623954773, 0.6358693838119507], all pred client disparities: [0.060127127915620804, 0.09793165326118469], all client disparities: [0.04504299536347389, 0.106111079454422], all client accs: [0.614205002784729, 0.6618978977203369],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:20,451 - utils - INFO - stage2_gradient_single_runtime: 0.0056993961334228516
2023-09-28 23:26:20,453 - utils - INFO - 1, epoch: 1294, all client loss: [0.6309664249420166, 0.6322061419487], all pred client disparities: [0.07048308104276657, 0.10373315215110779], all client disparities: [0.0592096671462059, 0.11049649119377136], all client accs: [0.6194511651992798, 0.6678739786148071],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:20,503 - utils - INFO - stage2_gradient_single_runtime: 0.005751132965087891
2023-09-28 23:26:20,506 - utils - INFO - 1, epoch: 1295, all client loss: [0.6331562995910645, 0.6343914270401001], all pred client disparities: [0.0640096515417099, 0.10031545162200928], all client disparities: [0.05087633058428764, 0.10662627220153809], all client accs: [0.6162227392196655, 0.6646143198013306],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:20,612 - utils - INFO - stage2_gradient_single_runtime: 0.0072290897369384766
2023-09-28 23:26:20,617 - utils - INFO - 1, epoch: 1296, all client loss: [0.6353687644004822, 0.6366048455238342], all pred client disparities: [0.057735394686460495, 0.09677204489707947], all client disparities: [0.041271500289440155, 0.10576969385147095], all client accs: [0.6113801002502441, 0.6604491472244263],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:20,674 - utils - INFO - stage2_gradient_single_runtime: 0.005807161331176758
2023-09-28 23:26:20,679 - utils - INFO - 1, epoch: 1297, all client loss: [0.6317502856254578, 0.6328950524330139], all pred client disparities: [0.06806433200836182, 0.10269343852996826], all client disparities: [0.05754299461841583, 0.1094660758972168], all client accs: [0.6190475821495056, 0.6664252281188965],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:20,736 - utils - INFO - stage2_gradient_single_runtime: 0.0069010257720947266
2023-09-28 23:26:20,741 - utils - INFO - 1, epoch: 1298, all client loss: [0.6339435577392578, 0.6350845694541931], all pred client disparities: [0.06168213486671448, 0.09924238920211792], all client disparities: [0.04670966416597366, 0.10766288638114929], all client accs: [0.6146085262298584, 0.6628033518791199],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:20,800 - utils - INFO - stage2_gradient_single_runtime: 0.005764007568359375
2023-09-28 23:26:20,805 - utils - INFO - 1, epoch: 1299, all client loss: [0.6304193735122681, 0.6314731240272522], all pred client disparities: [0.07198216021060944, 0.10492092370986938], all client disparities: [0.060876332223415375, 0.11092790961265564], all client accs: [0.6198546886444092, 0.6680550575256348],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:20,818 - utils - INFO - valid: True, epoch: 1299, loss: [0.6296393275260925, 0.6400722861289978], accuracy: [0.6319999694824219, 0.6450908780097961], mean_accuracy:0.638545423746109,variance_accuracy:0.006545454263687134, disparity: [0.05183562636375427, 0.13038688898086548], mean_disparity:0.09111125767230988,variance_disparity:0.0392756313085556, pred_disparity: [0.06513060629367828, 0.11408549547195435]
2023-09-28 23:26:20,829 - utils - INFO - global_valid: True, epoch: 1299,  global_loss: 0.6368120312690735, global_accuracy: 0.6932803121248499,  global_disparity:0.11986465752124786, global_pred_disparity: 0.11024998128414154,
2023-09-28 23:26:20,890 - utils - INFO - stage2_gradient_single_runtime: 0.005726337432861328
2023-09-28 23:26:20,895 - utils - INFO - 1, epoch: 1300, all client loss: [0.6325889825820923, 0.6336347460746765], all pred client disparities: [0.06552601605653763, 0.10156306624412537], all client disparities: [0.05504300072789192, 0.10783049464225769], all client accs: [0.618240475654602, 0.6658819317817688],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:20,951 - utils - INFO - stage2_gradient_single_runtime: 0.005738019943237305
2023-09-28 23:26:20,956 - utils - INFO - 1, epoch: 1301, all client loss: [0.6347838044166565, 0.6358270049095154], all pred client disparities: [0.05924971401691437, 0.0980789065361023], all client disparities: [0.0446048304438591, 0.1071476936340332], all client accs: [0.6129943132400513, 0.6620789766311646],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:21,017 - utils - INFO - stage2_gradient_single_runtime: 0.0057680606842041016
2023-09-28 23:26:21,021 - utils - INFO - 1, epoch: 1302, all client loss: [0.6312110424041748, 0.632168710231781], all pred client disparities: [0.06952960044145584, 0.10387623310089111], all client disparities: [0.0592096671462059, 0.1105864942073822], all client accs: [0.6198546886444092, 0.6676928997039795],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:21,078 - utils - INFO - stage2_gradient_single_runtime: 0.005742073059082031
2023-09-28 23:26:21,083 - utils - INFO - 1, epoch: 1303, all client loss: [0.6333851218223572, 0.6343358159065247], all pred client disparities: [0.06315860897302628, 0.10048377513885498], all client disparities: [0.05087633058428764, 0.1072314977645874], all client accs: [0.6166263222694397, 0.6644331812858582],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:21,143 - utils - INFO - stage2_gradient_single_runtime: 0.006983518600463867
2023-09-28 23:26:21,149 - utils - INFO - 1, epoch: 1304, all client loss: [0.6355795860290527, 0.6365287899971008], all pred client disparities: [0.05699066445231438, 0.09697061777114868], all client disparities: [0.042500000447034836, 0.10611730813980103], all client accs: [0.6109765768051147, 0.6602680683135986],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:21,208 - utils - INFO - stage2_gradient_single_runtime: 0.00765681266784668
2023-09-28 23:26:21,213 - utils - INFO - 1, epoch: 1305, all client loss: [0.6319606304168701, 0.6328262090682983], all pred client disparities: [0.06724263727664948, 0.10288229584693909], all client disparities: [0.056709665805101395, 0.10938230156898499], all client accs: [0.6186440587043762, 0.6667873859405518],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:21,272 - utils - INFO - stage2_gradient_single_runtime: 0.006124973297119141
2023-09-28 23:26:21,277 - utils - INFO - 1, epoch: 1306, all client loss: [0.6341373324394226, 0.6349967122077942], all pred client disparities: [0.060959961265325546, 0.09945917129516602], all client disparities: [0.04587633162736893, 0.10783672332763672], all client accs: [0.614205002784729, 0.6635277271270752],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:21,385 - utils - INFO - stage2_gradient_single_runtime: 0.006050586700439453
2023-09-28 23:26:21,391 - utils - INFO - 1, epoch: 1307, all client loss: [0.6306135654449463, 0.6313930749893188], all pred client disparities: [0.07118862122297287, 0.10512635111808777], all client disparities: [0.06004299595952034, 0.11135929822921753], all client accs: [0.6194511651992798, 0.6687794327735901],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:21,451 - utils - INFO - stage2_gradient_single_runtime: 0.007183551788330078
2023-09-28 23:26:21,456 - utils - INFO - 1, epoch: 1308, all client loss: [0.6327679753303528, 0.6335369944572449], all pred client disparities: [0.0648256242275238, 0.10179433226585388], all client disparities: [0.052542995661497116, 0.10860949754714966], all client accs: [0.6170298457145691, 0.6655197739601135],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:21,514 - utils - INFO - stage2_gradient_single_runtime: 0.00607752799987793
2023-09-28 23:26:21,519 - utils - INFO - 1, epoch: 1309, all client loss: [0.6349456310272217, 0.6357097029685974], all pred client disparities: [0.058645378798246384, 0.09834042191505432], all client disparities: [0.04293816536664963, 0.10723769664764404], all client accs: [0.6121872067451477, 0.6617168188095093],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:21,579 - utils - INFO - stage2_gradient_single_runtime: 0.006330013275146484
2023-09-28 23:26:21,585 - utils - INFO - 1, epoch: 1310, all client loss: [0.6313751339912415, 0.6320610642433167], all pred client disparities: [0.06885313987731934, 0.10412159562110901], all client disparities: [0.05837633088231087, 0.11007130146026611], all client accs: [0.6194511651992798, 0.6673306822776794],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:21,642 - utils - INFO - stage2_gradient_single_runtime: 0.005898952484130859
2023-09-28 23:26:21,647 - utils - INFO - 1, epoch: 1311, all client loss: [0.6335333585739136, 0.6342098116874695], all pred client disparities: [0.06257276237010956, 0.10075739026069641], all client disparities: [0.05004299804568291, 0.10783672332763672], all client accs: [0.6162227392196655, 0.6649764776229858],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:21,712 - utils - INFO - stage2_gradient_single_runtime: 0.0063130855560302734
2023-09-28 23:26:21,717 - utils - INFO - 1, epoch: 1312, all client loss: [0.6357101202011108, 0.6363828778266907], all pred client disparities: [0.05649663507938385, 0.0972764790058136], all client disparities: [0.042500000447034836, 0.10775911808013916], all client accs: [0.6109765768051147, 0.6604491472244263],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:21,775 - utils - INFO - stage2_gradient_single_runtime: 0.0061643123626708984
2023-09-28 23:26:21,780 - utils - INFO - 1, epoch: 1313, all client loss: [0.6336196064949036, 0.6346246004104614], all pred client disparities: [0.0627133920788765, 0.0997639000415802], all client disparities: [0.05087633058428764, 0.10680007934570312], all client accs: [0.6166263222694397, 0.6637088060379028],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:21,842 - utils - INFO - stage2_gradient_single_runtime: 0.0060710906982421875
2023-09-28 23:26:21,847 - utils - INFO - 1, epoch: 1314, all client loss: [0.6301249861717224, 0.6310470104217529], all pred client disparities: [0.07295512408018112, 0.10533863306045532], all client disparities: [0.06170966476202011, 0.11221590638160706], all client accs: [0.6202582716941833, 0.6689605712890625],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:21,910 - utils - INFO - stage2_gradient_single_runtime: 0.00722050666809082
2023-09-28 23:26:21,915 - utils - INFO - 1, epoch: 1315, all client loss: [0.6322708129882812, 0.6331823468208313], all pred client disparities: [0.06655574589967728, 0.10205236077308655], all client disparities: [0.056709665805101395, 0.10851949453353882], all client accs: [0.6186440587043762, 0.6658819317817688],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:21,973 - utils - INFO - stage2_gradient_single_runtime: 0.006240129470825195
2023-09-28 23:26:21,978 - utils - INFO - 1, epoch: 1316, all client loss: [0.634442925453186, 0.6353492736816406], all pred client disparities: [0.060321975499391556, 0.09864208102226257], all client disparities: [0.04504299536347389, 0.10697391629219055], all client accs: [0.614205002784729, 0.6626222729682922],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:22,038 - utils - INFO - stage2_gradient_single_runtime: 0.006081819534301758
2023-09-28 23:26:22,043 - utils - INFO - 1, epoch: 1317, all client loss: [0.6309008598327637, 0.6317261457443237], all pred client disparities: [0.07054851949214935, 0.10433092713356018], all client disparities: [0.0592096671462059, 0.11135929822921753], all client accs: [0.6194511651992798, 0.6678739786148071],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:22,101 - utils - INFO - stage2_gradient_single_runtime: 0.0062448978424072266
2023-09-28 23:26:22,107 - utils - INFO - 1, epoch: 1318, all client loss: [0.6330516338348389, 0.6338673233985901], all pred client disparities: [0.06422778964042664, 0.10101079940795898], all client disparities: [0.05087633058428764, 0.10705769062042236], all client accs: [0.6162227392196655, 0.6651575565338135],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:22,172 - utils - INFO - stage2_gradient_single_runtime: 0.006189107894897461
2023-09-28 23:26:22,177 - utils - INFO - 1, epoch: 1319, all client loss: [0.6352239847183228, 0.6360356211662292], all pred client disparities: [0.058095190674066544, 0.09757170081138611], all client disparities: [0.04293816536664963, 0.10663250088691711], all client accs: [0.6121872067451477, 0.6609923839569092],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:22,190 - utils - INFO - valid: True, epoch: 1319, loss: [0.6288032531738281, 0.6390121579170227], accuracy: [0.6351999640464783, 0.6487272381782532], mean_accuracy:0.6419636011123657,variance_accuracy:0.006763637065887451, disparity: [0.05892782658338547, 0.12978389859199524], mean_disparity:0.09435586258769035,variance_disparity:0.035428036004304886, pred_disparity: [0.06778572499752045, 0.11586040258407593]
2023-09-28 23:26:22,250 - utils - INFO - global_valid: True, epoch: 1319,  global_loss: 0.6358219385147095, global_accuracy: 0.6951420568227291,  global_disparity:0.12106211483478546, global_pred_disparity: 0.11220754683017731,
2023-09-28 23:26:22,309 - utils - INFO - stage2_gradient_single_runtime: 0.006052494049072266
2023-09-28 23:26:22,313 - utils - INFO - 1, epoch: 1320, all client loss: [0.6316368579864502, 0.6323692202568054], all pred client disparities: [0.06829895079135895, 0.10337060689926147], all client disparities: [0.05754299461841583, 0.11007130146026611], all client accs: [0.6190475821495056, 0.6667873859405518],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:22,375 - utils - INFO - stage2_gradient_single_runtime: 0.0061604976654052734
2023-09-28 23:26:22,380 - utils - INFO - 1, epoch: 1321, all client loss: [0.6337907314300537, 0.6345144510269165], all pred client disparities: [0.062060222029685974, 0.1000201404094696], all client disparities: [0.05004299804568291, 0.10809430480003357], all client accs: [0.6162227392196655, 0.6635277271270752],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:22,437 - utils - INFO - stage2_gradient_single_runtime: 0.0061414241790771484
2023-09-28 23:26:22,443 - utils - INFO - 1, epoch: 1322, all client loss: [0.635961651802063, 0.6366825103759766], all pred client disparities: [0.05602980777621269, 0.09655588865280151], all client disparities: [0.042500000447034836, 0.10629111528396606], all client accs: [0.6109765768051147, 0.6595436334609985],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:22,505 - utils - INFO - stage2_gradient_single_runtime: 0.006706714630126953
2023-09-28 23:26:22,509 - utils - INFO - 1, epoch: 1323, all client loss: [0.633881151676178, 0.6349371671676636], all pred client disparities: [0.06218617036938667, 0.0990220308303833], all client disparities: [0.048376329243183136, 0.10550585389137268], all client accs: [0.615415632724762, 0.6624411344528198],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:22,569 - utils - INFO - stage2_gradient_single_runtime: 0.006844758987426758
2023-09-28 23:26:22,574 - utils - INFO - 1, epoch: 1324, all client loss: [0.6303708553314209, 0.6313427090644836], all pred client disparities: [0.07242781668901443, 0.10461273789405823], all client disparities: [0.060876332223415375, 0.11298868060112], all client accs: [0.6198546886444092, 0.6684172749519348],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:22,638 - utils - INFO - stage2_gradient_single_runtime: 0.00704503059387207
2023-09-28 23:26:22,643 - utils - INFO - 1, epoch: 1325, all client loss: [0.6325132846832275, 0.6334755420684814], all pred client disparities: [0.06606494635343552, 0.10133880376815796], all client disparities: [0.05587632954120636, 0.10748288035392761], all client accs: [0.618240475654602, 0.6662441492080688],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:22,702 - utils - INFO - stage2_gradient_single_runtime: 0.006155729293823242
2023-09-28 23:26:22,707 - utils - INFO - 1, epoch: 1326, all client loss: [0.6346805691719055, 0.6356383562088013], all pred client disparities: [0.059872228652238846, 0.09794363379478455], all client disparities: [0.04504299536347389, 0.106111079454422], all client accs: [0.614205002784729, 0.6613546013832092],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:22,768 - utils - INFO - stage2_gradient_single_runtime: 0.005991697311401367
2023-09-28 23:26:22,773 - utils - INFO - 1, epoch: 1327, all client loss: [0.6311241984367371, 0.6319997310638428], all pred client disparities: [0.0700969249010086, 0.10364493727684021], all client disparities: [0.0592096671462059, 0.11058029532432556], all client accs: [0.6194511651992798, 0.6680550575256348],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:22,837 - utils - INFO - stage2_gradient_single_runtime: 0.006153583526611328
2023-09-28 23:26:22,842 - utils - INFO - 1, epoch: 1328, all client loss: [0.6332709193229675, 0.6341376304626465], all pred client disparities: [0.06381230056285858, 0.100338876247406], all client disparities: [0.05087633058428764, 0.10662627220153809], all client accs: [0.6162227392196655, 0.6642521023750305],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:22,900 - utils - INFO - stage2_gradient_single_runtime: 0.006209850311279297
2023-09-28 23:26:22,905 - utils - INFO - 1, epoch: 1329, all client loss: [0.6354379653930664, 0.6363013386726379], all pred client disparities: [0.057719212025403976, 0.09691646695137024], all client disparities: [0.041271500289440155, 0.10533827543258667], all client accs: [0.6113801002502441, 0.6604491472244263],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:22,967 - utils - INFO - stage2_gradient_single_runtime: 0.0067861080169677734
2023-09-28 23:26:22,972 - utils - INFO - 1, epoch: 1330, all client loss: [0.6318379640579224, 0.6326208710670471], all pred client disparities: [0.06791993975639343, 0.10272437334060669], all client disparities: [0.05754299461841583, 0.1094660758972168], all client accs: [0.6190475821495056, 0.6660630702972412],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:23,094 - utils - INFO - stage2_gradient_single_runtime: 0.006100177764892578
2023-09-28 23:26:23,099 - utils - INFO - 1, epoch: 1331, all client loss: [0.633987307548523, 0.6347622275352478], all pred client disparities: [0.06171627342700958, 0.09938958287239075], all client disparities: [0.04670966416597366, 0.1072314977645874], all client accs: [0.6146085262298584, 0.6628033518791199],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:23,157 - utils - INFO - stage2_gradient_single_runtime: 0.0061187744140625
2023-09-28 23:26:23,162 - utils - INFO - 1, epoch: 1332, all client loss: [0.6304826736450195, 0.6311808824539185], all pred client disparities: [0.07188859581947327, 0.10495725274085999], all client disparities: [0.060876332223415375, 0.11144310235977173], all client accs: [0.6198546886444092, 0.6680550575256348],  alphas:tensor([0.5005, 0.0000, 0.0000, 0.4995], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:23,224 - utils - INFO - stage2_gradient_single_runtime: 0.005995035171508789
2023-09-28 23:26:23,229 - utils - INFO - 1, epoch: 1333, all client loss: [0.6326097249984741, 0.6332956552505493], all pred client disparities: [0.06560823321342468, 0.10171112418174744], all client disparities: [0.05504300072789192, 0.10739907622337341], all client accs: [0.6178369522094727, 0.6658819317817688],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:23,293 - utils - INFO - stage2_gradient_single_runtime: 0.006407737731933594
2023-09-28 23:26:23,298 - utils - INFO - 1, epoch: 1334, all client loss: [0.6347602009773254, 0.6354392766952515], all pred client disparities: [0.059498611837625504, 0.09834733605384827], all client disparities: [0.044209666550159454, 0.1071476936340332], all client accs: [0.6138014197349548, 0.6618978977203369],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:23,355 - utils - INFO - stage2_gradient_single_runtime: 0.006136178970336914
2023-09-28 23:26:23,360 - utils - INFO - 1, epoch: 1335, all client loss: [0.6312111616134644, 0.6318153738975525], all pred client disparities: [0.06965400278568268, 0.1040215790271759], all client disparities: [0.0592096671462059, 0.11041271686553955], all client accs: [0.6198546886444092, 0.6678739786148071],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:23,421 - utils - INFO - stage2_gradient_single_runtime: 0.0060694217681884766
2023-09-28 23:26:23,427 - utils - INFO - 1, epoch: 1336, all client loss: [0.6333421468734741, 0.6339348554611206], all pred client disparities: [0.0634491890668869, 0.10074508190155029], all client disparities: [0.05087633058428764, 0.10705769062042236], all client accs: [0.6166263222694397, 0.6647953987121582],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:23,488 - utils - INFO - stage2_gradient_single_runtime: 0.006057024002075195
2023-09-28 23:26:23,493 - utils - INFO - 1, epoch: 1337, all client loss: [0.6354920268058777, 0.6360791325569153], all pred client disparities: [0.05743516981601715, 0.0973556637763977], all client disparities: [0.041271500289440155, 0.10620111227035522], all client accs: [0.6113801002502441, 0.6608113050460815],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:23,551 - utils - INFO - stage2_gradient_single_runtime: 0.00617218017578125
2023-09-28 23:26:23,556 - utils - INFO - 1, epoch: 1338, all client loss: [0.63190096616745, 0.6324148178100586], all pred client disparities: [0.06756722927093506, 0.1031322181224823], all client disparities: [0.05754299461841583, 0.10938230156898499], all client accs: [0.6190475821495056, 0.6666063070297241],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:23,614 - utils - INFO - stage2_gradient_single_runtime: 0.006232738494873047
2023-09-28 23:26:23,619 - utils - INFO - 1, epoch: 1339, all client loss: [0.6340340971946716, 0.6345375180244446], all pred client disparities: [0.061440180987119675, 0.09982869029045105], all client disparities: [0.04670966416597366, 0.10809430480003357], all client accs: [0.6146085262298584, 0.6637088060379028],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:23,633 - utils - INFO - valid: True, epoch: 1339, loss: [0.6278387308120728, 0.6378369927406311], accuracy: [0.6351999640464783, 0.6501818299293518], mean_accuracy:0.642690896987915,variance_accuracy:0.007490932941436768, disparity: [0.05892782658338547, 0.13083651661872864], mean_disparity:0.09488217160105705,variance_disparity:0.035954345017671585, pred_disparity: [0.07089863717556, 0.11781758069992065]
2023-09-28 23:26:23,647 - utils - INFO - global_valid: True, epoch: 1339,  global_loss: 0.6347125768661499, global_accuracy: 0.6972128851540615,  global_disparity:0.12187378108501434, global_pred_disparity: 0.11440664529800415,
2023-09-28 23:26:23,710 - utils - INFO - stage2_gradient_single_runtime: 0.007237434387207031
2023-09-28 23:26:23,715 - utils - INFO - 1, epoch: 1340, all client loss: [0.6305385828018188, 0.6309724450111389], all pred client disparities: [0.07154612243175507, 0.10536560416221619], all client disparities: [0.060876332223415375, 0.11135929822921753], all client accs: [0.6198546886444092, 0.6684172749519348],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:23,773 - utils - INFO - stage2_gradient_single_runtime: 0.006203889846801758
2023-09-28 23:26:23,778 - utils - INFO - 1, epoch: 1341, all client loss: [0.6326501965522766, 0.6330692768096924], all pred client disparities: [0.06533988565206528, 0.10214895009994507], all client disparities: [0.05504300072789192, 0.10800430178642273], all client accs: [0.618240475654602, 0.6658819317817688],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:23,835 - utils - INFO - stage2_gradient_single_runtime: 0.006213665008544922
2023-09-28 23:26:23,839 - utils - INFO - 1, epoch: 1342, all client loss: [0.6347842216491699, 0.6351940631866455], all pred client disparities: [0.05930326133966446, 0.09881773591041565], all client disparities: [0.044209666550159454, 0.10757911205291748], all client accs: [0.6138014197349548, 0.6620789766311646],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:23,901 - utils - INFO - stage2_gradient_single_runtime: 0.00729680061340332
2023-09-28 23:26:23,912 - utils - INFO - 1, epoch: 1343, all client loss: [0.6312456727027893, 0.6315877437591553], all pred client disparities: [0.0693928524851799, 0.10445749759674072], all client disparities: [0.0592096671462059, 0.11032888293266296], all client accs: [0.6198546886444092, 0.6675118207931519],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:24,027 - utils - INFO - stage2_gradient_single_runtime: 0.0061550140380859375
2023-09-28 23:26:24,031 - utils - INFO - 1, epoch: 1344, all client loss: [0.6333608627319336, 0.6336890459060669], all pred client disparities: [0.06325926631689072, 0.10121193528175354], all client disparities: [0.05087633058428764, 0.1072314977645874], all client accs: [0.6166263222694397, 0.6655197739601135],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:24,089 - utils - INFO - stage2_gradient_single_runtime: 0.006134510040283203
2023-09-28 23:26:24,093 - utils - INFO - 1, epoch: 1345, all client loss: [0.6354944109916687, 0.6358144283294678], all pred client disparities: [0.057314228266477585, 0.09785625338554382], all client disparities: [0.041271500289440155, 0.10766911506652832], all client accs: [0.6113801002502441, 0.6613546013832092],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:24,156 - utils - INFO - stage2_gradient_single_runtime: 0.0060117244720458984
2023-09-28 23:26:24,159 - utils - INFO - 1, epoch: 1346, all client loss: [0.6333672404289246, 0.6340328454971313], all pred client disparities: [0.06360296905040741, 0.10034438967704773], all client disparities: [0.05087633058428764, 0.10662627220153809], all client accs: [0.6162227392196655, 0.6638898849487305],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:24,217 - utils - INFO - stage2_gradient_single_runtime: 0.006201982498168945
2023-09-28 23:26:24,222 - utils - INFO - 1, epoch: 1347, all client loss: [0.6355119347572327, 0.6361722350120544], all pred client disparities: [0.05760295316576958, 0.09697845578193665], all client disparities: [0.041271500289440155, 0.10533827543258667], all client accs: [0.6113801002502441, 0.6604491472244263],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:24,280 - utils - INFO - stage2_gradient_single_runtime: 0.006041049957275391
2023-09-28 23:26:24,285 - utils - INFO - 1, epoch: 1348, all client loss: [0.6319194436073303, 0.6325048804283142], all pred client disparities: [0.06773795187473297, 0.1027362048625946], all client disparities: [0.05754299461841583, 0.1094660758972168], all client accs: [0.6190475821495056, 0.6660630702972412],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:24,344 - utils - INFO - stage2_gradient_single_runtime: 0.007503986358642578
2023-09-28 23:26:24,347 - utils - INFO - 1, epoch: 1349, all client loss: [0.634047269821167, 0.6346227526664734], all pred client disparities: [0.06162526085972786, 0.09945541620254517], all client disparities: [0.04670966416597366, 0.10636866092681885], all client accs: [0.6146085262298584, 0.6631655693054199],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:24,406 - utils - INFO - stage2_gradient_single_runtime: 0.0059468746185302734
2023-09-28 23:26:24,411 - utils - INFO - 1, epoch: 1350, all client loss: [0.6305508017539978, 0.6310551762580872], all pred client disparities: [0.07173288613557816, 0.1049739420413971], all client disparities: [0.060876332223415375, 0.11144310235977173], all client accs: [0.6198546886444092, 0.6680550575256348],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:24,470 - utils - INFO - stage2_gradient_single_runtime: 0.006134986877441406
2023-09-28 23:26:24,475 - utils - INFO - 1, epoch: 1351, all client loss: [0.6326571106910706, 0.6331471800804138], all pred client disparities: [0.06554141640663147, 0.10177966952323914], all client disparities: [0.05504300072789192, 0.10739907622337341], all client accs: [0.6178369522094727, 0.6657008528709412],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:24,533 - utils - INFO - stage2_gradient_single_runtime: 0.006155967712402344
2023-09-28 23:26:24,539 - utils - INFO - 1, epoch: 1352, all client loss: [0.6347858309745789, 0.6352669596672058], all pred client disparities: [0.05951732397079468, 0.09847190976142883], all client disparities: [0.04504299536347389, 0.10671630501747131], all client accs: [0.614205002784729, 0.6620789766311646],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:24,600 - utils - INFO - stage2_gradient_single_runtime: 0.006259441375732422
2023-09-28 23:26:24,606 - utils - INFO - 1, epoch: 1353, all client loss: [0.6312469840049744, 0.6316588521003723], all pred client disparities: [0.0696091502904892, 0.10409104824066162], all client disparities: [0.0592096671462059, 0.11041271686553955], all client accs: [0.6198546886444092, 0.6678739786148071],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:24,663 - utils - INFO - stage2_gradient_single_runtime: 0.006195068359375
2023-09-28 23:26:24,668 - utils - INFO - 1, epoch: 1354, all client loss: [0.6333568096160889, 0.6337552070617676], all pred client disparities: [0.06348883360624313, 0.10086843371391296], all client disparities: [0.05087633058428764, 0.10705769062042236], all client accs: [0.6162227392196655, 0.6647953987121582],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:24,726 - utils - INFO - stage2_gradient_single_runtime: 0.0060999393463134766
2023-09-28 23:26:24,731 - utils - INFO - 1, epoch: 1355, all client loss: [0.635485053062439, 0.6358755826950073], all pred client disparities: [0.05755441263318062, 0.09753674268722534], all client disparities: [0.041271500289440155, 0.10620111227035522], all client accs: [0.6113801002502441, 0.6606302261352539],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:24,788 - utils - INFO - stage2_gradient_single_runtime: 0.00614476203918457
2023-09-28 23:26:24,793 - utils - INFO - 1, epoch: 1356, all client loss: [0.6319061517715454, 0.6322290897369385], all pred client disparities: [0.06762474775314331, 0.10325253009796143], all client disparities: [0.05754299461841583, 0.10938230156898499], all client accs: [0.6190475821495056, 0.6666063070297241],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:24,898 - utils - INFO - stage2_gradient_single_runtime: 0.006201028823852539
2023-09-28 23:26:24,903 - utils - INFO - 1, epoch: 1357, all client loss: [0.6340180039405823, 0.6343284845352173], all pred client disparities: [0.061577342450618744, 0.10000449419021606], all client disparities: [0.04670966416597366, 0.10809430480003357], all client accs: [0.6146085262298584, 0.6635277271270752],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:24,961 - utils - INFO - stage2_gradient_single_runtime: 0.006130218505859375
2023-09-28 23:26:24,966 - utils - INFO - 1, epoch: 1358, all client loss: [0.6361443400382996, 0.6364482045173645], all pred client disparities: [0.05573245510458946, 0.09665164351463318], all client disparities: [0.042500000447034836, 0.1054283082485199], all client accs: [0.6109765768051147, 0.659724771976471],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:25,024 - utils - INFO - stage2_gradient_single_runtime: 0.006211280822753906
2023-09-28 23:26:25,029 - utils - INFO - 1, epoch: 1359, all client loss: [0.6340702176094055, 0.6347216367721558], all pred client disparities: [0.06177784875035286, 0.09907218813896179], all client disparities: [0.048376329243183136, 0.10550585389137268], all client accs: [0.615415632724762, 0.6624411344528198],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:25,044 - utils - INFO - valid: True, epoch: 1359, loss: [0.6279008388519287, 0.6380197405815125], accuracy: [0.6367999911308289, 0.64654541015625], mean_accuracy:0.6416727006435394,variance_accuracy:0.004872709512710571, disparity: [0.06247392296791077, 0.13083651661872864], mean_disparity:0.0966552197933197,variance_disparity:0.034181296825408936, pred_disparity: [0.07125971466302872, 0.11721324920654297]
2023-09-28 23:26:25,056 - utils - INFO - global_valid: True, epoch: 1359,  global_loss: 0.6348575949668884, global_accuracy: 0.6967326930772308,  global_disparity:0.12268547713756561, global_pred_disparity: 0.11405961215496063,
2023-09-28 23:26:25,117 - utils - INFO - stage2_gradient_single_runtime: 0.00604557991027832
2023-09-28 23:26:25,122 - utils - INFO - 1, epoch: 1360, all client loss: [0.6305719017982483, 0.6311506032943726], all pred client disparities: [0.07188819348812103, 0.10457518696784973], all client disparities: [0.060876332223415375, 0.11255726218223572], all client accs: [0.6198546886444092, 0.6687794327735901],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:25,180 - utils - INFO - stage2_gradient_single_runtime: 0.006211996078491211
2023-09-28 23:26:25,185 - utils - INFO - 1, epoch: 1361, all client loss: [0.6326735615730286, 0.6332383751869202], all pred client disparities: [0.06571048498153687, 0.10140123963356018], all client disparities: [0.05587632954120636, 0.10748288035392761], all client accs: [0.618240475654602, 0.6660630702972412],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:25,242 - utils - INFO - stage2_gradient_single_runtime: 0.006052970886230469
2023-09-28 23:26:25,247 - utils - INFO - 1, epoch: 1362, all client loss: [0.6347975134849548, 0.6353538036346436], all pred client disparities: [0.059698328375816345, 0.09811505675315857], all client disparities: [0.04504299536347389, 0.10636866092681885], all client accs: [0.614205002784729, 0.6615356802940369],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:25,308 - utils - INFO - stage2_gradient_single_runtime: 0.007353067398071289
2023-09-28 23:26:25,311 - utils - INFO - 1, epoch: 1363, all client loss: [0.6312575936317444, 0.6317429542541504], all pred client disparities: [0.06979328393936157, 0.10371646285057068], all client disparities: [0.0592096671462059, 0.11014887690544128], all client accs: [0.6194511651992798, 0.6682361364364624],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:25,372 - utils - INFO - stage2_gradient_single_runtime: 0.005991935729980469
2023-09-28 23:26:25,377 - utils - INFO - 1, epoch: 1364, all client loss: [0.6333626508712769, 0.633834958076477], all pred client disparities: [0.06368537992238998, 0.10051485896110535], all client disparities: [0.05087633058428764, 0.10662627220153809], all client accs: [0.6162227392196655, 0.6638898849487305],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:25,436 - utils - INFO - stage2_gradient_single_runtime: 0.006146430969238281
2023-09-28 23:26:25,441 - utils - INFO - 1, epoch: 1365, all client loss: [0.6354860067367554, 0.6359509229660034], all pred client disparities: [0.05776115879416466, 0.09720510244369507], all client disparities: [0.04293816536664963, 0.10533827543258667], all client accs: [0.6121872067451477, 0.6604491472244263],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:25,498 - utils - INFO - stage2_gradient_single_runtime: 0.00616455078125
2023-09-28 23:26:25,503 - utils - INFO - 1, epoch: 1366, all client loss: [0.6319067478179932, 0.632302463054657], all pred client disparities: [0.06783521920442581, 0.10290119051933289], all client disparities: [0.05754299461841583, 0.1094660758972168], all client accs: [0.6190475821495056, 0.6660630702972412],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:25,570 - utils - INFO - stage2_gradient_single_runtime: 0.0070683956146240234
2023-09-28 23:26:25,575 - utils - INFO - 1, epoch: 1367, all client loss: [0.6340137720108032, 0.6343973278999329], all pred client disparities: [0.061798788607120514, 0.09967467188835144], all client disparities: [0.048376329243183136, 0.10636866092681885], all client accs: [0.615415632724762, 0.6633466482162476],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:25,680 - utils - INFO - stage2_gradient_single_runtime: 0.006076812744140625
2023-09-28 23:26:25,684 - utils - INFO - 1, epoch: 1368, all client loss: [0.6305306553840637, 0.6308485865592957], all pred client disparities: [0.07184455543756485, 0.10513374209403992], all client disparities: [0.060876332223415375, 0.11144310235977173], all client accs: [0.6198546886444092, 0.6680550575256348],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:25,742 - utils - INFO - stage2_gradient_single_runtime: 0.006140708923339844
2023-09-28 23:26:25,746 - utils - INFO - 1, epoch: 1369, all client loss: [0.6326166987419128, 0.6329181790351868], all pred client disparities: [0.0657295510172844, 0.10199174284934998], all client disparities: [0.05587632954120636, 0.10739907622337341], all client accs: [0.618240475654602, 0.6658819317817688],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:25,812 - utils - INFO - stage2_gradient_single_runtime: 0.006124734878540039
2023-09-28 23:26:25,817 - utils - INFO - 1, epoch: 1370, all client loss: [0.6347246170043945, 0.635015070438385], all pred client disparities: [0.059776414185762405, 0.09873953461647034], all client disparities: [0.04504299536347389, 0.10654249787330627], all client accs: [0.614205002784729, 0.6622600555419922],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:25,877 - utils - INFO - stage2_gradient_single_runtime: 0.006240367889404297
2023-09-28 23:26:25,883 - utils - INFO - 1, epoch: 1371, all client loss: [0.6312008500099182, 0.6314274668693542], all pred client disparities: [0.06980821490287781, 0.1042943000793457], all client disparities: [0.0592096671462059, 0.11110168695449829], all client accs: [0.6194511651992798, 0.6678739786148071],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:25,940 - utils - INFO - stage2_gradient_single_runtime: 0.0059888362884521484
2023-09-28 23:26:25,945 - utils - INFO - 1, epoch: 1372, all client loss: [0.6332902312278748, 0.6335012316703796], all pred client disparities: [0.06375999748706818, 0.10112538933753967], all client disparities: [0.05087633058428764, 0.10705769062042236], all client accs: [0.6162227392196655, 0.6649764776229858],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:26,005 - utils - INFO - stage2_gradient_single_runtime: 0.006170988082885742
2023-09-28 23:26:26,009 - utils - INFO - 1, epoch: 1373, all client loss: [0.635397732257843, 0.6355987787246704], all pred client disparities: [0.05789101496338844, 0.09785044193267822], all client disparities: [0.04293816536664963, 0.10576969385147095], all client accs: [0.6121872067451477, 0.6613546013832092],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:26,072 - utils - INFO - stage2_gradient_single_runtime: 0.006220340728759766
2023-09-28 23:26:26,077 - utils - INFO - 1, epoch: 1374, all client loss: [0.6318355202674866, 0.631974458694458], all pred client disparities: [0.06790363788604736, 0.10349702835083008], all client disparities: [0.05754299461841583, 0.10989749431610107], all client accs: [0.6190475821495056, 0.6669685244560242],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:26,136 - utils - INFO - stage2_gradient_single_runtime: 0.00608372688293457
2023-09-28 23:26:26,141 - utils - INFO - 1, epoch: 1375, all client loss: [0.6339269280433655, 0.6340511441230774], all pred client disparities: [0.06192370504140854, 0.10030397772789001], all client disparities: [0.05004299804568291, 0.10766288638114929], all client accs: [0.6162227392196655, 0.6637088060379028],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:26,200 - utils - INFO - stage2_gradient_single_runtime: 0.006148338317871094
2023-09-28 23:26:26,205 - utils - INFO - 1, epoch: 1376, all client loss: [0.6360328197479248, 0.63614821434021], all pred client disparities: [0.056138668209314346, 0.09700879454612732], all client disparities: [0.042500000447034836, 0.10568591952323914], all client accs: [0.6109765768051147, 0.6600869297981262],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:26,265 - utils - INFO - stage2_gradient_single_runtime: 0.0060482025146484375
2023-09-28 23:26:26,270 - utils - INFO - 1, epoch: 1377, all client loss: [0.6339412927627563, 0.6344103813171387], all pred client disparities: [0.06221849471330643, 0.09943082928657532], all client disparities: [0.05087633058428764, 0.10550585389137268], all client accs: [0.6166263222694397, 0.6626222729682922],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:26,329 - utils - INFO - stage2_gradient_single_runtime: 0.007128238677978516
2023-09-28 23:26:26,335 - utils - INFO - 1, epoch: 1378, all client loss: [0.6304619312286377, 0.6308637261390686], all pred client disparities: [0.07226760685443878, 0.1048620343208313], all client disparities: [0.06170966476202011, 0.11281487345695496], all client accs: [0.6202582716941833, 0.6687794327735901],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:26,393 - utils - INFO - stage2_gradient_single_runtime: 0.0061037540435791016
2023-09-28 23:26:26,397 - utils - INFO - 1, epoch: 1379, all client loss: [0.6325427889823914, 0.6329283714294434], all pred client disparities: [0.06615804880857468, 0.10174340009689331], all client disparities: [0.05587632954120636, 0.10748288035392761], all client accs: [0.618240475654602, 0.6662441492080688],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:26,411 - utils - INFO - valid: True, epoch: 1379, loss: [0.6315147876739502, 0.6414470076560974], accuracy: [0.6304000020027161, 0.6378181576728821], mean_accuracy:0.6341090798377991,variance_accuracy:0.003709077835083008, disparity: [0.044743429869413376, 0.12286511063575745], mean_disparity:0.08380427025258541,variance_disparity:0.039060840383172035, pred_disparity: [0.06003228574991226, 0.11122387647628784]
2023-09-28 23:26:26,422 - utils - INFO - global_valid: True, epoch: 1379,  global_loss: 0.6383431553840637, global_accuracy: 0.6898784513805523,  global_disparity:0.1125192940235138, global_pred_disparity: 0.10695125162601471,
2023-09-28 23:26:26,481 - utils - INFO - stage2_gradient_single_runtime: 0.00612330436706543
2023-09-28 23:26:26,486 - utils - INFO - 1, epoch: 1380, all client loss: [0.6346458792686462, 0.6350205540657043], all pred client disparities: [0.06020627170801163, 0.09851530194282532], all client disparities: [0.04504299536347389, 0.10636866092681885], all client accs: [0.6138014197349548, 0.6615356802940369],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:26,546 - utils - INFO - stage2_gradient_single_runtime: 0.006308555603027344
2023-09-28 23:26:26,551 - utils - INFO - 1, epoch: 1381, all client loss: [0.631126344203949, 0.6314354538917542], all pred client disparities: [0.07024253159761429, 0.10404062271118164], all client disparities: [0.0592096671462059, 0.11083787679672241], all client accs: [0.6190475821495056, 0.6676928997039795],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:26,658 - utils - INFO - stage2_gradient_single_runtime: 0.00608515739440918
2023-09-28 23:26:26,663 - utils - INFO - 1, epoch: 1382, all client loss: [0.6332105994224548, 0.6335044503211975], all pred client disparities: [0.06419821083545685, 0.10089540481567383], all client disparities: [0.052542995661497116, 0.10696768760681152], all client accs: [0.6170298457145691, 0.6651575565338135],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:26,723 - utils - INFO - stage2_gradient_single_runtime: 0.006056547164916992
2023-09-28 23:26:26,728 - utils - INFO - 1, epoch: 1383, all client loss: [0.6353133320808411, 0.6355974674224854], all pred client disparities: [0.058328889310359955, 0.09764459729194641], all client disparities: [0.04377150163054466, 0.10654249787330627], all client accs: [0.6125907897949219, 0.6609923839569092],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:26,786 - utils - INFO - stage2_gradient_single_runtime: 0.005948066711425781
2023-09-28 23:26:26,791 - utils - INFO - 1, epoch: 1384, all client loss: [0.6317558288574219, 0.6319760084152222], all pred client disparities: [0.06834707409143448, 0.10326030850410461], all client disparities: [0.05754299461841583, 0.10929229855537415], all client accs: [0.6190475821495056, 0.6666063070297241],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:26,848 - utils - INFO - stage2_gradient_single_runtime: 0.006242275238037109
2023-09-28 23:26:26,852 - utils - INFO - 1, epoch: 1385, all client loss: [0.6338421702384949, 0.6340479254722595], all pred client disparities: [0.06236955523490906, 0.10009098052978516], all client disparities: [0.05087633058428764, 0.10636866092681885], all client accs: [0.6166263222694397, 0.6637088060379028],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:26,909 - utils - INFO - stage2_gradient_single_runtime: 0.006173610687255859
2023-09-28 23:26:26,914 - utils - INFO - 1, epoch: 1386, all client loss: [0.6359435319900513, 0.6361405849456787], all pred client disparities: [0.05658256635069847, 0.09682005643844604], all client disparities: [0.041271500289440155, 0.10490688681602478], all client accs: [0.6113801002502441, 0.6604491472244263],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:26,976 - utils - INFO - stage2_gradient_single_runtime: 0.0068552494049072266
2023-09-28 23:26:26,981 - utils - INFO - 1, epoch: 1387, all client loss: [0.6338284611701965, 0.6343823075294495], all pred client disparities: [0.06274734437465668, 0.09925916790962219], all client disparities: [0.05087633058428764, 0.10549962520599365], all client accs: [0.6166263222694397, 0.6633466482162476],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:27,039 - utils - INFO - stage2_gradient_single_runtime: 0.006066560745239258
2023-09-28 23:26:27,044 - utils - INFO - 1, epoch: 1388, all client loss: [0.6303555369377136, 0.6308401823043823], all pred client disparities: [0.07279851287603378, 0.1046571135520935], all client disparities: [0.06170966476202011, 0.11272487044334412], all client accs: [0.6198546886444092, 0.6693227291107178],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:27,103 - utils - INFO - stage2_gradient_single_runtime: 0.006274700164794922
2023-09-28 23:26:27,108 - utils - INFO - 1, epoch: 1389, all client loss: [0.6324306130409241, 0.6328993439674377], all pred client disparities: [0.0666922852396965, 0.10156354308128357], all client disparities: [0.056709665805101395, 0.1069614589214325], all client accs: [0.6186440587043762, 0.6664252281188965],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:27,167 - utils - INFO - stage2_gradient_single_runtime: 0.006194114685058594
2023-09-28 23:26:27,173 - utils - INFO - 1, epoch: 1390, all client loss: [0.6345285773277283, 0.6349866390228271], all pred client disparities: [0.06073877960443497, 0.09836074709892273], all client disparities: [0.04587633162736893, 0.10378023982048035], all client accs: [0.614205002784729, 0.6622600555419922],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:27,236 - utils - INFO - stage2_gradient_single_runtime: 0.006032705307006836
2023-09-28 23:26:27,240 - utils - INFO - 1, epoch: 1391, all client loss: [0.6310157179832458, 0.6314065456390381], all pred client disparities: [0.07077847421169281, 0.10385137796401978], all client disparities: [0.06004299595952034, 0.11057406663894653], all client accs: [0.6194511651992798, 0.6685983538627625],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:27,297 - utils - INFO - stage2_gradient_single_runtime: 0.00628972053527832
2023-09-28 23:26:27,302 - utils - INFO - 1, epoch: 1392, all client loss: [0.6330944299697876, 0.6334700584411621], all pred client disparities: [0.06473581492900848, 0.1007312536239624], all client disparities: [0.05420966446399689, 0.10662007331848145], all client accs: [0.6178369522094727, 0.6647953987121582],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:27,361 - utils - INFO - stage2_gradient_single_runtime: 0.006258249282836914
2023-09-28 23:26:27,366 - utils - INFO - 1, epoch: 1393, all client loss: [0.6351923942565918, 0.6355582475662231], all pred client disparities: [0.058863021433353424, 0.09750574827194214], all client disparities: [0.04254300147294998, 0.10524827241897583], all client accs: [0.6129943132400513, 0.6608113050460815],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:27,478 - utils - INFO - stage2_gradient_single_runtime: 0.006135225296020508
2023-09-28 23:26:27,482 - utils - INFO - 1, epoch: 1394, all client loss: [0.6316418051719666, 0.6319422125816345], all pred client disparities: [0.06888604164123535, 0.1030854880809784], all client disparities: [0.05837633088231087, 0.10997503995895386], all client accs: [0.6194511651992798, 0.6675118207931519],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:27,540 - utils - INFO - stage2_gradient_single_runtime: 0.006295680999755859
2023-09-28 23:26:27,545 - utils - INFO - 1, epoch: 1395, all client loss: [0.6337228417396545, 0.6340088844299316], all pred client disparities: [0.06290861964225769, 0.09994131326675415], all client disparities: [0.05087633058428764, 0.1061948835849762], all client accs: [0.6162227392196655, 0.6631655693054199],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:27,606 - utils - INFO - stage2_gradient_single_runtime: 0.009135723114013672
2023-09-28 23:26:27,612 - utils - INFO - 1, epoch: 1396, all client loss: [0.630267858505249, 0.6304919719696045], all pred client disparities: [0.07289592176675797, 0.10529035329818726], all client disparities: [0.06170966476202011, 0.11350390315055847], all client accs: [0.6198546886444092, 0.6687794327735901],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:27,679 - utils - INFO - stage2_gradient_single_runtime: 0.007428407669067383
2023-09-28 23:26:27,683 - utils - INFO - 1, epoch: 1397, all client loss: [0.6323275566101074, 0.6325329542160034], all pred client disparities: [0.06684662401676178, 0.10222867131233215], all client disparities: [0.056709665805101395, 0.1079980731010437], all client accs: [0.6186440587043762, 0.6664252281188965],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:27,740 - utils - INFO - stage2_gradient_single_runtime: 0.006258487701416016
2023-09-28 23:26:27,744 - utils - INFO - 1, epoch: 1398, all client loss: [0.6344098448753357, 0.6346019506454468], all pred client disparities: [0.06094539165496826, 0.09905973076820374], all client disparities: [0.04670966416597366, 0.10636866092681885], all client accs: [0.6146085262298584, 0.6622600555419922],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:27,802 - utils - INFO - stage2_gradient_single_runtime: 0.0061492919921875
2023-09-28 23:26:27,806 - utils - INFO - 1, epoch: 1399, all client loss: [0.6309158802032471, 0.6310478448867798], all pred client disparities: [0.07092290371656418, 0.104498952627182], all client disparities: [0.06004299595952034, 0.1112692654132843], all client accs: [0.6194511651992798, 0.6678739786148071],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:27,820 - utils - INFO - valid: True, epoch: 1399, loss: [0.630047082901001, 0.6397959589958191], accuracy: [0.6319999694824219, 0.6443636417388916], mean_accuracy:0.6381818056106567,variance_accuracy:0.006181836128234863, disparity: [0.05183562636375427, 0.13143953680992126], mean_disparity:0.09163758158683777,variance_disparity:0.039801955223083496, pred_disparity: [0.06456737220287323, 0.11407288908958435]
2023-09-28 23:26:27,831 - utils - INFO - global_valid: True, epoch: 1399,  global_loss: 0.6367495656013489, global_accuracy: 0.6928751500600239,  global_disparity:0.12067635357379913, global_pred_disparity: 0.1101527065038681,
2023-09-28 23:26:27,895 - utils - INFO - stage2_gradient_single_runtime: 0.0072536468505859375
2023-09-28 23:26:27,898 - utils - INFO - 1, epoch: 1400, all client loss: [0.632979154586792, 0.6330933570861816], all pred client disparities: [0.06493424624204636, 0.10141140222549438], all client disparities: [0.05504300072789192, 0.10696768760681152], all client accs: [0.618240475654602, 0.6657008528709412],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:27,951 - utils - INFO - stage2_gradient_single_runtime: 0.006064891815185547
2023-09-28 23:26:27,954 - utils - INFO - 1, epoch: 1401, all client loss: [0.6350616216659546, 0.6351634860038757], all pred client disparities: [0.05911022797226906, 0.09822022914886475], all client disparities: [0.044209666550159454, 0.10654249787330627], all client accs: [0.6138014197349548, 0.6611735224723816],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:28,006 - utils - INFO - stage2_gradient_single_runtime: 0.006261348724365234
2023-09-28 23:26:28,009 - utils - INFO - 1, epoch: 1402, all client loss: [0.6315305829048157, 0.6315740942955017], all pred client disparities: [0.0690729022026062, 0.10374632477760315], all client disparities: [0.0592096671462059, 0.1091184914112091], all client accs: [0.6198546886444092, 0.6675118207931519],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:28,062 - utils - INFO - stage2_gradient_single_runtime: 0.00621485710144043
2023-09-28 23:26:28,064 - utils - INFO - 1, epoch: 1403, all client loss: [0.6335963010787964, 0.6336228251457214], all pred client disparities: [0.06314645707607269, 0.10063531994819641], all client disparities: [0.05087633058428764, 0.10662627220153809], all client accs: [0.6162227392196655, 0.6644331812858582],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:28,117 - utils - INFO - stage2_gradient_single_runtime: 0.006208896636962891
2023-09-28 23:26:28,119 - utils - INFO - 1, epoch: 1404, all client loss: [0.6356777548789978, 0.6356930136680603], all pred client disparities: [0.0573996976017952, 0.0974242091178894], all client disparities: [0.04210482910275459, 0.10533827543258667], all client accs: [0.6117836833000183, 0.6608113050460815],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:28,180 - utils - INFO - stage2_gradient_single_runtime: 0.00600743293762207
2023-09-28 23:26:28,185 - utils - INFO - 1, epoch: 1405, all client loss: [0.6335322856903076, 0.6339107155799866], all pred client disparities: [0.06365704536437988, 0.09987825155258179], all client disparities: [0.05170966684818268, 0.10644623637199402], all client accs: [0.6166263222694397, 0.6640710234642029],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:28,306 - utils - INFO - stage2_gradient_single_runtime: 0.00711369514465332
2023-09-28 23:26:28,312 - utils - INFO - 1, epoch: 1406, all client loss: [0.6300883293151855, 0.6304028630256653], all pred client disparities: [0.07364554703235626, 0.10518431663513184], all client disparities: [0.060919325798749924, 0.11306625604629517], all client accs: [0.6214689016342163, 0.6698660254478455],  alphas:tensor([0.5004, 0.0000, 0.0000, 0.4996], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:28,366 - utils - INFO - stage2_gradient_single_runtime: 0.007585287094116211
2023-09-28 23:26:28,370 - utils - INFO - 1, epoch: 1407, all client loss: [0.632141649723053, 0.6324376463890076], all pred client disparities: [0.0675942450761795, 0.10215026140213013], all client disparities: [0.05754299461841583, 0.10781800746917725], all client accs: [0.6190475821495056, 0.6680550575256348],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:28,431 - utils - INFO - stage2_gradient_single_runtime: 0.005993366241455078
2023-09-28 23:26:28,436 - utils - INFO - 1, epoch: 1408, all client loss: [0.6342186331748962, 0.6345012784004211], all pred client disparities: [0.06168419122695923, 0.0990089476108551], all client disparities: [0.048376329243183136, 0.10446923971176147], all client accs: [0.615415632724762, 0.6626222729682922],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:28,496 - utils - INFO - stage2_gradient_single_runtime: 0.006169557571411133
2023-09-28 23:26:28,501 - utils - INFO - 1, epoch: 1409, all client loss: [0.6307356953620911, 0.6309564113616943], all pred client disparities: [0.07166481018066406, 0.1044042706489563], all client disparities: [0.060876332223415375, 0.1120358407497406], all client accs: [0.6198546886444092, 0.6693227291107178],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:28,561 - utils - INFO - stage2_gradient_single_runtime: 0.006922245025634766
2023-09-28 23:26:28,566 - utils - INFO - 1, epoch: 1410, all client loss: [0.6327929496765137, 0.6329959034919739], all pred client disparities: [0.06567229330539703, 0.10134416818618774], all client disparities: [0.05587632954120636, 0.10670384764671326], all client accs: [0.618240475654602, 0.6660630702972412],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:28,630 - utils - INFO - stage2_gradient_single_runtime: 0.006076812744140625
2023-09-28 23:26:28,635 - utils - INFO - 1, epoch: 1411, all client loss: [0.6348704099655151, 0.6350609660148621], all pred client disparities: [0.059837706387043, 0.09818029403686523], all client disparities: [0.04504299536347389, 0.10593727231025696], all client accs: [0.614205002784729, 0.6611735224723816],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:28,692 - utils - INFO - stage2_gradient_single_runtime: 0.006205081939697266
2023-09-28 23:26:28,697 - utils - INFO - 1, epoch: 1412, all client loss: [0.6313505172729492, 0.631480872631073], all pred client disparities: [0.0698053166270256, 0.10366165637969971], all client disparities: [0.0592096671462059, 0.11005887389183044], all client accs: [0.6194511651992798, 0.6682361364364624],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:28,756 - utils - INFO - stage2_gradient_single_runtime: 0.0063555240631103516
2023-09-28 23:26:28,761 - utils - INFO - 1, epoch: 1413, all client loss: [0.6334103941917419, 0.6335238814353943], all pred client disparities: [0.06387336552143097, 0.10057780146598816], all client disparities: [0.052542995661497116, 0.1067938506603241], all client accs: [0.6170298457145691, 0.6644331812858582],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:28,824 - utils - INFO - stage2_gradient_single_runtime: 0.007215738296508789
2023-09-28 23:26:28,827 - utils - INFO - 1, epoch: 1414, all client loss: [0.6354871988296509, 0.6355893015861511], all pred client disparities: [0.05811448022723198, 0.09739381074905396], all client disparities: [0.04377150163054466, 0.10524827241897583], all client accs: [0.6125907897949219, 0.6606302261352539],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:28,887 - utils - INFO - stage2_gradient_single_runtime: 0.005942344665527344
2023-09-28 23:26:28,892 - utils - INFO - 1, epoch: 1415, all client loss: [0.6319323778152466, 0.6319759488105774], all pred client disparities: [0.06806483864784241, 0.10295772552490234], all client disparities: [0.05754299461841583, 0.10868707299232483], all client accs: [0.6190475821495056, 0.6667873859405518],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:28,949 - utils - INFO - stage2_gradient_single_runtime: 0.006268739700317383
2023-09-28 23:26:28,954 - utils - INFO - 1, epoch: 1416, all client loss: [0.6339938640594482, 0.6340214014053345], all pred client disparities: [0.062194328755140305, 0.09985247254371643], all client disparities: [0.05087633058428764, 0.10593727231025696], all client accs: [0.6166263222694397, 0.6628033518791199],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:29,012 - utils - INFO - stage2_gradient_single_runtime: 0.006234169006347656
2023-09-28 23:26:29,016 - utils - INFO - 1, epoch: 1417, all client loss: [0.6305357813835144, 0.6305082440376282], all pred client disparities: [0.07211428135633469, 0.10518389940261841], all client disparities: [0.06170966476202011, 0.11298868060112], all client accs: [0.6202582716941833, 0.6685983538627625],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:29,082 - utils - INFO - stage2_gradient_single_runtime: 0.007028818130493164
2023-09-28 23:26:29,086 - utils - INFO - 1, epoch: 1418, all client loss: [0.6325774788856506, 0.6325294971466064], all pred client disparities: [0.06616535782814026, 0.1021588146686554], all client disparities: [0.056709665805101395, 0.10748288035392761], all client accs: [0.6186440587043762, 0.6660630702972412],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:29,199 - utils - INFO - stage2_gradient_single_runtime: 0.006289958953857422
2023-09-28 23:26:29,204 - utils - INFO - 1, epoch: 1419, all client loss: [0.6346397995948792, 0.634576678276062], all pred client disparities: [0.0603669099509716, 0.09903103113174438], all client disparities: [0.04587633162736893, 0.10680007934570312], all client accs: [0.614205002784729, 0.6620789766311646],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:29,218 - utils - INFO - valid: True, epoch: 1419, loss: [0.6284323334693909, 0.6380273103713989], accuracy: [0.6351999640464783, 0.6480000019073486], mean_accuracy:0.6415999829769135,variance_accuracy:0.006400018930435181, disparity: [0.05892782658338547, 0.13083651661872864], mean_disparity:0.09488217160105705,variance_disparity:0.035954345017671585, pred_disparity: [0.06968711316585541, 0.11706078052520752]
2023-09-28 23:26:29,229 - utils - INFO - global_valid: True, epoch: 1419,  global_loss: 0.6350289583206177, global_accuracy: 0.6961434573829531,  global_disparity:0.12187378108501434, global_pred_disparity: 0.11359180510044098,
2023-09-28 23:26:29,285 - utils - INFO - stage2_gradient_single_runtime: 0.0064165592193603516
2023-09-28 23:26:29,290 - utils - INFO - 1, epoch: 1420, all client loss: [0.6311450600624084, 0.6310287117958069], all pred client disparities: [0.07027633488178253, 0.10444697737693787], all client disparities: [0.0592096671462059, 0.11083787679672241], all client accs: [0.6190475821495056, 0.6682361364364624],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:29,350 - utils - INFO - stage2_gradient_single_runtime: 0.0059986114501953125
2023-09-28 23:26:29,353 - utils - INFO - 1, epoch: 1421, all client loss: [0.6331896781921387, 0.6330536603927612], all pred client disparities: [0.06438495963811874, 0.10139825940132141], all client disparities: [0.052542995661497116, 0.10696768760681152], all client accs: [0.6170298457145691, 0.6657008528709412],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:29,407 - utils - INFO - stage2_gradient_single_runtime: 0.006078243255615234
2023-09-28 23:26:29,412 - utils - INFO - 1, epoch: 1422, all client loss: [0.6352516412734985, 0.6351016759872437], all pred client disparities: [0.058658961206674576, 0.09825032949447632], all client disparities: [0.04337633401155472, 0.10654249787330627], all client accs: [0.6133978962898254, 0.6611735224723816],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:29,474 - utils - INFO - stage2_gradient_single_runtime: 0.007055759429931641
2023-09-28 23:26:29,480 - utils - INFO - 1, epoch: 1423, all client loss: [0.6317223906517029, 0.6315206289291382], all pred client disparities: [0.06855360418558121, 0.10374733805656433], all client disparities: [0.05837633088231087, 0.10929229855537415], all client accs: [0.6194511651992798, 0.6673306822776794],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:29,541 - utils - INFO - stage2_gradient_single_runtime: 0.006898641586303711
2023-09-28 23:26:29,546 - utils - INFO - 1, epoch: 1424, all client loss: [0.6337688565254211, 0.6335484385490417], all pred client disparities: [0.06272077560424805, 0.10067722201347351], all client disparities: [0.05087633058428764, 0.10662627220153809], all client accs: [0.6166263222694397, 0.6644331812858582],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:29,604 - utils - INFO - stage2_gradient_single_runtime: 0.006137847900390625
2023-09-28 23:26:29,609 - utils - INFO - 1, epoch: 1425, all client loss: [0.6358296871185303, 0.6355962157249451], all pred client disparities: [0.05706682428717613, 0.09751123189926147], all client disparities: [0.041271500289440155, 0.10576969385147095], all client accs: [0.6113801002502441, 0.6606302261352539],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:29,667 - utils - INFO - stage2_gradient_single_runtime: 0.006187915802001953
2023-09-28 23:26:29,672 - utils - INFO - 1, epoch: 1426, all client loss: [0.6336968541145325, 0.6338316202163696], all pred client disparities: [0.06323368847370148, 0.09993535280227661], all client disparities: [0.05087633058428764, 0.10636246204376221], all client accs: [0.6162227392196655, 0.6635277271270752],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:29,734 - utils - INFO - stage2_gradient_single_runtime: 0.007353782653808594
2023-09-28 23:26:29,739 - utils - INFO - 1, epoch: 1427, all client loss: [0.6302555799484253, 0.6303332448005676], all pred client disparities: [0.07315671443939209, 0.10521134734153748], all client disparities: [0.06254299730062485, 0.11298245191574097], all client accs: [0.6202582716941833, 0.6695038080215454],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:29,800 - utils - INFO - stage2_gradient_single_runtime: 0.00633692741394043
2023-09-28 23:26:29,805 - utils - INFO - 1, epoch: 1428, all client loss: [0.632290780544281, 0.6323478817939758], all pred client disparities: [0.06719549745321274, 0.10221630334854126], all client disparities: [0.05754299461841583, 0.10678762197494507], all client accs: [0.6190475821495056, 0.6673306822776794],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:29,862 - utils - INFO - stage2_gradient_single_runtime: 0.0061419010162353516
2023-09-28 23:26:29,867 - utils - INFO - 1, epoch: 1429, all client loss: [0.6343481540679932, 0.6343899369239807], all pred client disparities: [0.061375729739665985, 0.09911802411079407], all client disparities: [0.048376329243183136, 0.10507446527481079], all client accs: [0.615415632724762, 0.6620789766311646],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:29,928 - utils - INFO - stage2_gradient_single_runtime: 0.006980180740356445
2023-09-28 23:26:29,934 - utils - INFO - 1, epoch: 1430, all client loss: [0.6308701038360596, 0.6308565139770508], all pred client disparities: [0.0712907612323761, 0.10447821021080017], all client disparities: [0.060876332223415375, 0.11152064800262451], all client accs: [0.6198546886444092, 0.6691416501998901],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:29,994 - utils - INFO - stage2_gradient_single_runtime: 0.006222248077392578
2023-09-28 23:26:29,999 - utils - INFO - 1, epoch: 1431, all client loss: [0.6329087615013123, 0.632875382900238], all pred client disparities: [0.06538523733615875, 0.10145905613899231], all client disparities: [0.05587632954120636, 0.10730904340744019], all client accs: [0.618240475654602, 0.6657008528709412],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:30,102 - utils - INFO - stage2_gradient_single_runtime: 0.006292819976806641
2023-09-28 23:26:30,107 - utils - INFO - 1, epoch: 1432, all client loss: [0.634966254234314, 0.6349186301231384], all pred client disparities: [0.05963639169931412, 0.09833991527557373], all client disparities: [0.04504299536347389, 0.10593727231025696], all client accs: [0.614205002784729, 0.6611735224723816],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:30,168 - utils - INFO - stage2_gradient_single_runtime: 0.006125450134277344
2023-09-28 23:26:30,174 - utils - INFO - 1, epoch: 1433, all client loss: [0.631453275680542, 0.6313519477844238], all pred client disparities: [0.06953892111778259, 0.10378104448318481], all client disparities: [0.0592096671462059, 0.10997503995895386], all client accs: [0.6194511651992798, 0.6678739786148071],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:30,236 - utils - INFO - stage2_gradient_single_runtime: 0.006415605545043945
2023-09-28 23:26:30,241 - utils - INFO - 1, epoch: 1434, all client loss: [0.6334941983222961, 0.6333739757537842], all pred client disparities: [0.06369038671255112, 0.10073989629745483], all client disparities: [0.052542995661497116, 0.10627865791320801], all client accs: [0.6170298457145691, 0.6646143198013306],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:30,299 - utils - INFO - stage2_gradient_single_runtime: 0.006049394607543945
2023-09-28 23:26:30,304 - utils - INFO - 1, epoch: 1435, all client loss: [0.6355509161949158, 0.6354174017906189], all pred client disparities: [0.05801241099834442, 0.09760206937789917], all client disparities: [0.04377150163054466, 0.10567969083786011], all client accs: [0.6125907897949219, 0.6608113050460815],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:30,362 - utils - INFO - stage2_gradient_single_runtime: 0.006417989730834961
2023-09-28 23:26:30,368 - utils - INFO - 1, epoch: 1436, all client loss: [0.6320049166679382, 0.6318193078041077], all pred client disparities: [0.0678987205028534, 0.10312080383300781], all client disparities: [0.05754299461841583, 0.10868707299232483], all client accs: [0.6190475821495056, 0.6667873859405518],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:30,432 - utils - INFO - stage2_gradient_single_runtime: 0.006424665451049805
2023-09-28 23:26:30,439 - utils - INFO - 1, epoch: 1437, all client loss: [0.634047269821167, 0.6338435411453247], all pred client disparities: [0.06210772693157196, 0.10005978494882584], all client disparities: [0.05087633058428764, 0.10593727231025696], all client accs: [0.6166263222694397, 0.6635277271270752],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:30,497 - utils - INFO - stage2_gradient_single_runtime: 0.00615692138671875
2023-09-28 23:26:30,502 - utils - INFO - 1, epoch: 1438, all client loss: [0.6361024975776672, 0.6358864903450012], all pred client disparities: [0.05649978667497635, 0.0969051718711853], all client disparities: [0.041271500289440155, 0.10404407978057861], all client accs: [0.6113801002502441, 0.6600869297981262],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:30,560 - utils - INFO - stage2_gradient_single_runtime: 0.006182670593261719
2023-09-28 23:26:30,565 - utils - INFO - 1, epoch: 1439, all client loss: [0.6339846253395081, 0.6341390609741211], all pred client disparities: [0.06258765608072281, 0.09930577129125595], all client disparities: [0.05087633058428764, 0.10463681817054749], all client accs: [0.6162227392196655, 0.6633466482162476],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:30,579 - utils - INFO - valid: True, epoch: 1439, loss: [0.6279155611991882, 0.6376938819885254], accuracy: [0.6367999911308289, 0.6472727060317993], mean_accuracy:0.6420363485813141,variance_accuracy:0.0052363574504852295, disparity: [0.06247392296791077, 0.13294178247451782], mean_disparity:0.0977078527212143,variance_disparity:0.03523392975330353, pred_disparity: [0.07186422497034073, 0.11738720536231995]
2023-09-28 23:26:30,590 - utils - INFO - global_valid: True, epoch: 1439,  global_loss: 0.6346381902694702, global_accuracy: 0.6967617046818728,  global_disparity:0.12430886924266815, global_pred_disparity: 0.11436325311660767,
2023-09-28 23:26:30,654 - utils - INFO - stage2_gradient_single_runtime: 0.007069826126098633
2023-09-28 23:26:30,660 - utils - INFO - 1, epoch: 1440, all client loss: [0.6305273175239563, 0.6306241750717163], all pred client disparities: [0.07250723242759705, 0.10460221767425537], all client disparities: [0.06170966476202011, 0.11186206340789795], all client accs: [0.6202582716941833, 0.6695038080215454],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:30,719 - utils - INFO - stage2_gradient_single_runtime: 0.006254673004150391
2023-09-28 23:26:30,724 - utils - INFO - 1, epoch: 1441, all client loss: [0.632559597492218, 0.6326363682746887], all pred client disparities: [0.06658250838518143, 0.10161447525024414], all client disparities: [0.056709665805101395, 0.10799184441566467], all client accs: [0.6186440587043762, 0.6667873859405518],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:30,782 - utils - INFO - stage2_gradient_single_runtime: 0.0062406063079833984
2023-09-28 23:26:30,787 - utils - INFO - 1, epoch: 1442, all client loss: [0.6346124410629272, 0.634674608707428], all pred client disparities: [0.060804154723882675, 0.0985257625579834], all client disparities: [0.04670966416597366, 0.10429543256759644], all client accs: [0.6146085262298584, 0.6624411344528198],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:30,893 - utils - INFO - stage2_gradient_single_runtime: 0.00625157356262207
2023-09-28 23:26:30,898 - utils - INFO - 1, epoch: 1443, all client loss: [0.6311197280883789, 0.6311261057853699], all pred client disparities: [0.07071404904127121, 0.10390344262123108], all client disparities: [0.06004299595952034, 0.11065784096717834], all client accs: [0.6194511651992798, 0.6691416501998901],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:30,958 - utils - INFO - stage2_gradient_single_runtime: 0.006166219711303711
2023-09-28 23:26:30,963 - utils - INFO - 1, epoch: 1444, all client loss: [0.6331548690795898, 0.6331419944763184], all pred client disparities: [0.06484457105398178, 0.10089290142059326], all client disparities: [0.05420966446399689, 0.10670384764671326], all client accs: [0.6178369522094727, 0.6649764776229858],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:31,022 - utils - INFO - stage2_gradient_single_runtime: 0.006192445755004883
2023-09-28 23:26:31,027 - utils - INFO - 1, epoch: 1445, all client loss: [0.63520747423172, 0.6351809501647949], all pred client disparities: [0.05913582444190979, 0.09778466820716858], all client disparities: [0.044209666550159454, 0.10507446527481079], all client accs: [0.6138014197349548, 0.6611735224723816],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:31,084 - utils - INFO - stage2_gradient_single_runtime: 0.0064275264739990234
2023-09-28 23:26:31,087 - utils - INFO - 1, epoch: 1446, all client loss: [0.6316811442375183, 0.631600558757782], all pred client disparities: [0.06903199851512909, 0.10324028134346008], all client disparities: [0.05837633088231087, 0.10988503694534302], all client accs: [0.6194511651992798, 0.6678739786148071],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:31,141 - utils - INFO - stage2_gradient_single_runtime: 0.006235599517822266
2023-09-28 23:26:31,144 - utils - INFO - 1, epoch: 1447, all client loss: [0.6337181925773621, 0.6336191296577454], all pred client disparities: [0.06321867555379868, 0.10020899772644043], all client disparities: [0.05087633058428764, 0.10610488057136536], all client accs: [0.6162227392196655, 0.6637088060379028],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:31,196 - utils - INFO - stage2_gradient_single_runtime: 0.006168365478515625
2023-09-28 23:26:31,199 - utils - INFO - 1, epoch: 1448, all client loss: [0.635769784450531, 0.6356579661369324], all pred client disparities: [0.057579103857278824, 0.097083181142807], all client disparities: [0.04293816536664963, 0.10387024283409119], all client accs: [0.6121872067451477, 0.6599058508872986],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:31,251 - utils - INFO - stage2_gradient_single_runtime: 0.0062024593353271484
2023-09-28 23:26:31,254 - utils - INFO - 1, epoch: 1449, all client loss: [0.6322117447853088, 0.6320474743843079], all pred client disparities: [0.06745823472738266, 0.10261344909667969], all client disparities: [0.05754299461841583, 0.10721904039382935], all client accs: [0.6190475821495056, 0.6671496033668518],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:31,312 - utils - INFO - stage2_gradient_single_runtime: 0.006378889083862305
2023-09-28 23:26:31,319 - utils - INFO - 1, epoch: 1450, all client loss: [0.634249746799469, 0.6340678334236145], all pred client disparities: [0.06170129030942917, 0.09956339001655579], all client disparities: [0.05004299804568291, 0.10550585389137268], all client accs: [0.6162227392196655, 0.6624411344528198],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:31,377 - utils - INFO - stage2_gradient_single_runtime: 0.006656169891357422
2023-09-28 23:26:31,381 - utils - INFO - 1, epoch: 1451, all client loss: [0.6307897567749023, 0.6305587887763977], all pred client disparities: [0.07155384868383408, 0.10486042499542236], all client disparities: [0.060876332223415375, 0.1130724847316742], all client accs: [0.6198546886444092, 0.6691416501998901],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:31,439 - utils - INFO - stage2_gradient_single_runtime: 0.0062901973724365234
2023-09-28 23:26:31,444 - utils - INFO - 1, epoch: 1452, all client loss: [0.6328092217445374, 0.6325562000274658], all pred client disparities: [0.06571302562952042, 0.10188788175582886], all client disparities: [0.05587632954120636, 0.10705146193504333], all client accs: [0.618240475654602, 0.6662441492080688],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:31,503 - utils - INFO - stage2_gradient_single_runtime: 0.006658792495727539
2023-09-28 23:26:31,508 - utils - INFO - 1, epoch: 1453, all client loss: [0.6348475217819214, 0.6345778703689575], all pred client disparities: [0.06002264469861984, 0.09881779551506042], all client disparities: [0.04587633162736893, 0.10636866092681885], all client accs: [0.614205002784729, 0.6613546013832092],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:31,567 - utils - INFO - stage2_gradient_single_runtime: 0.006011486053466797
2023-09-28 23:26:31,571 - utils - INFO - 1, epoch: 1454, all client loss: [0.6313538551330566, 0.6310367584228516], all pred client disparities: [0.06986463814973831, 0.10419225692749023], all client disparities: [0.0592096671462059, 0.11083787679672241], all client accs: [0.6190475821495056, 0.6676928997039795],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:31,629 - utils - INFO - stage2_gradient_single_runtime: 0.0062313079833984375
2023-09-28 23:26:31,633 - utils - INFO - 1, epoch: 1455, all client loss: [0.6333757042884827, 0.6330373883247375], all pred client disparities: [0.06407712399959564, 0.10119861364364624], all client disparities: [0.052542995661497116, 0.10653626918792725], all client accs: [0.6170298457145691, 0.6653386354446411],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:31,744 - utils - INFO - stage2_gradient_single_runtime: 0.006922245025634766
2023-09-28 23:26:31,749 - utils - INFO - 1, epoch: 1456, all client loss: [0.635413408279419, 0.6350595355033875], all pred client disparities: [0.05845317989587784, 0.09811034798622131], all client disparities: [0.04377150163054466, 0.10654249787330627], all client accs: [0.6125907897949219, 0.6609923839569092],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:31,808 - utils - INFO - stage2_gradient_single_runtime: 0.006033897399902344
2023-09-28 23:26:31,812 - utils - INFO - 1, epoch: 1457, all client loss: [0.6318878531455994, 0.6314880847930908], all pred client disparities: [0.06828112155199051, 0.10355910658836365], all client disparities: [0.05837633088231087, 0.10886088013648987], all client accs: [0.6194511651992798, 0.6667873859405518],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:31,869 - utils - INFO - stage2_gradient_single_runtime: 0.006186246871948242
2023-09-28 23:26:31,873 - utils - INFO - 1, epoch: 1458, all client loss: [0.6339111924171448, 0.633491039276123], all pred client disparities: [0.06254741549491882, 0.10054618120193481], all client disparities: [0.05087633058428764, 0.1061948835849762], all client accs: [0.6166263222694397, 0.6642521023750305],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:31,929 - utils - INFO - stage2_gradient_single_runtime: 0.006161689758300781
2023-09-28 23:26:31,934 - utils - INFO - 1, epoch: 1459, all client loss: [0.635947585105896, 0.6355129480361938], all pred client disparities: [0.05698917433619499, 0.0974416732788086], all client disparities: [0.041271500289440155, 0.10533827543258667], all client accs: [0.6113801002502441, 0.6604491472244263],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:31,947 - utils - INFO - valid: True, epoch: 1459, loss: [0.6308302283287048, 0.6404572129249573], accuracy: [0.6319999694824219, 0.6407272815704346], mean_accuracy:0.6363636255264282,variance_accuracy:0.004363656044006348, disparity: [0.04828952997922897, 0.12707564234733582], mean_disparity:0.0876825861632824,variance_disparity:0.03939305618405342, pred_disparity: [0.06284834444522858, 0.1126793622970581]
2023-09-28 23:26:31,958 - utils - INFO - global_valid: True, epoch: 1459,  global_loss: 0.6374488472938538, global_accuracy: 0.691263505402161,  global_disparity:0.11657774448394775, global_pred_disparity: 0.10873334109783173,
2023-09-28 23:26:32,026 - utils - INFO - stage2_gradient_single_runtime: 0.006100893020629883
2023-09-28 23:26:32,031 - utils - INFO - 1, epoch: 1460, all client loss: [0.6338135004043579, 0.633754551410675], all pred client disparities: [0.06311339884996414, 0.09984421730041504], all client disparities: [0.05087633058428764, 0.10575723648071289], all client accs: [0.6162227392196655, 0.6640710234642029],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:32,089 - utils - INFO - stage2_gradient_single_runtime: 0.006203889846801758
2023-09-28 23:26:32,094 - utils - INFO - 1, epoch: 1461, all client loss: [0.6303783655166626, 0.630267858505249], all pred client disparities: [0.07297015190124512, 0.10506948828697205], all client disparities: [0.06254299730062485, 0.11298245191574097], all client accs: [0.6202582716941833, 0.6691416501998901],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:32,152 - utils - INFO - stage2_gradient_single_runtime: 0.006237983703613281
2023-09-28 23:26:32,157 - utils - INFO - 1, epoch: 1462, all client loss: [0.632391095161438, 0.6322581768035889], all pred client disparities: [0.06710495054721832, 0.10213020443916321], all client disparities: [0.05754299461841583, 0.1075604259967804], all client accs: [0.6190475821495056, 0.6675118207931519],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:32,223 - utils - INFO - stage2_gradient_single_runtime: 0.007094383239746094
2023-09-28 23:26:32,227 - utils - INFO - 1, epoch: 1463, all client loss: [0.6344246864318848, 0.6342747807502747], all pred client disparities: [0.061378490179777145, 0.09909212589263916], all client disparities: [0.048376329243183136, 0.10446923971176147], all client accs: [0.615415632724762, 0.6622600555419922],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:32,284 - utils - INFO - stage2_gradient_single_runtime: 0.006181240081787109
2023-09-28 23:26:32,288 - utils - INFO - 1, epoch: 1464, all client loss: [0.630955159664154, 0.6307554244995117], all pred client disparities: [0.07122784107923508, 0.10439532995223999], all client disparities: [0.060876332223415375, 0.11229345202445984], all client accs: [0.6198546886444092, 0.6695038080215454],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:32,346 - utils - INFO - stage2_gradient_single_runtime: 0.006096839904785156
2023-09-28 23:26:32,351 - utils - INFO - 1, epoch: 1465, all client loss: [0.632970929145813, 0.632749617099762], all pred client disparities: [0.06541416049003601, 0.10143396258354187], all client disparities: [0.05587632954120636, 0.1069614589214325], all client accs: [0.618240475654602, 0.6660630702972412],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:32,409 - utils - INFO - stage2_gradient_single_runtime: 0.0061452388763427734
2023-09-28 23:26:32,414 - utils - INFO - 1, epoch: 1466, all client loss: [0.6350046396255493, 0.6347671747207642], all pred client disparities: [0.05975298583507538, 0.09837675094604492], all client disparities: [0.04504299536347389, 0.10550585389137268], all client accs: [0.6138014197349548, 0.6613546013832092],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:32,477 - utils - INFO - stage2_gradient_single_runtime: 0.006125211715698242
2023-09-28 23:26:32,480 - utils - INFO - 1, epoch: 1467, all client loss: [0.6315023899078369, 0.631216824054718], all pred client disparities: [0.06959109008312225, 0.10375502705574036], all client disparities: [0.0592096671462059, 0.1103164553642273], all client accs: [0.6194511651992798, 0.6682361364364624],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:32,534 - utils - INFO - stage2_gradient_single_runtime: 0.0062525272369384766
2023-09-28 23:26:32,538 - utils - INFO - 1, epoch: 1468, all client loss: [0.633520245552063, 0.6332138776779175], all pred client disparities: [0.06382985413074493, 0.10077345371246338], all client disparities: [0.052542995661497116, 0.10705146193504333], all client accs: [0.6170298457145691, 0.6646143198013306],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:32,636 - utils - INFO - stage2_gradient_single_runtime: 0.0062160491943359375
2023-09-28 23:26:32,639 - utils - INFO - 1, epoch: 1469, all client loss: [0.6355531811714172, 0.635231614112854], all pred client disparities: [0.05823364853858948, 0.09769889712333679], all client disparities: [0.04377150163054466, 0.10524827241897583], all client accs: [0.6125907897949219, 0.6608113050460815],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:32,703 - utils - INFO - stage2_gradient_single_runtime: 0.007521867752075195
2023-09-28 23:26:32,708 - utils - INFO - 1, epoch: 1470, all client loss: [0.632020115852356, 0.6316521167755127], all pred client disparities: [0.06805726140737534, 0.10314899682998657], all client disparities: [0.05837633088231087, 0.10894465446472168], all client accs: [0.6194511651992798, 0.6667873859405518],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:32,765 - utils - INFO - stage2_gradient_single_runtime: 0.006266593933105469
2023-09-28 23:26:32,769 - utils - INFO - 1, epoch: 1471, all client loss: [0.6340392231941223, 0.6336511969566345], all pred client disparities: [0.062348730862140656, 0.100149005651474], all client disparities: [0.05087633058428764, 0.1061948835849762], all client accs: [0.6166263222694397, 0.6628033518791199],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:32,826 - utils - INFO - stage2_gradient_single_runtime: 0.006031990051269531
2023-09-28 23:26:32,830 - utils - INFO - 1, epoch: 1472, all client loss: [0.636070728302002, 0.6356684565544128], all pred client disparities: [0.05681661143898964, 0.09705889225006104], all client disparities: [0.041271500289440155, 0.10387024283409119], all client accs: [0.6113801002502441, 0.6600869297981262],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:32,887 - utils - INFO - stage2_gradient_single_runtime: 0.006203651428222656
2023-09-28 23:26:32,896 - utils - INFO - 1, epoch: 1473, all client loss: [0.6339377164840698, 0.6339133977890015], all pred client disparities: [0.06292232871055603, 0.09945317357778549], all client disparities: [0.05087633058428764, 0.10472062230110168], all client accs: [0.6162227392196655, 0.6637088060379028],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:32,957 - utils - INFO - stage2_gradient_single_runtime: 0.0060176849365234375
2023-09-28 23:26:32,962 - utils - INFO - 1, epoch: 1474, all client loss: [0.6304959654808044, 0.6304195523262024], all pred client disparities: [0.07277630269527435, 0.10467851161956787], all client disparities: [0.06170966476202011, 0.11168822646141052], all client accs: [0.6198546886444092, 0.669684886932373],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:33,020 - utils - INFO - stage2_gradient_single_runtime: 0.006169319152832031
2023-09-28 23:26:33,026 - utils - INFO - 1, epoch: 1475, all client loss: [0.6325048804283142, 0.6324064135551453], all pred client disparities: [0.06693369895219803, 0.10175150632858276], all client disparities: [0.05754299461841583, 0.10781800746917725], all client accs: [0.6190475821495056, 0.6669685244560242],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:33,083 - utils - INFO - stage2_gradient_single_runtime: 0.006203413009643555
2023-09-28 23:26:33,088 - utils - INFO - 1, epoch: 1476, all client loss: [0.6345341205596924, 0.6344188451766968], all pred client disparities: [0.06123095378279686, 0.09872707724571228], all client disparities: [0.048376329243183136, 0.10455304384231567], all client accs: [0.615415632724762, 0.6626222729682922],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:33,155 - utils - INFO - stage2_gradient_single_runtime: 0.006522417068481445
2023-09-28 23:26:33,160 - utils - INFO - 1, epoch: 1477, all client loss: [0.6310588717460632, 0.6308931708335876], all pred client disparities: [0.07107701897621155, 0.10402834415435791], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6695038080215454],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:33,220 - utils - INFO - stage2_gradient_single_runtime: 0.0065953731536865234
2023-09-28 23:26:33,225 - utils - INFO - 1, epoch: 1478, all client loss: [0.6330705881118774, 0.6328835487365723], all pred client disparities: [0.06528516858816147, 0.10108000040054321], all client disparities: [0.05587632954120636, 0.10747665166854858], all client accs: [0.618240475654602, 0.6653386354446411],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:33,284 - utils - INFO - stage2_gradient_single_runtime: 0.006079912185668945
2023-09-28 23:26:33,289 - utils - INFO - 1, epoch: 1479, all client loss: [0.6350997090339661, 0.6348968148231506], all pred client disparities: [0.059646449983119965, 0.09803709387779236], all client disparities: [0.04504299536347389, 0.1051582396030426], all client accs: [0.614205002784729, 0.6617168188095093],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:33,303 - utils - INFO - valid: True, epoch: 1479, loss: [0.6288725137710571, 0.6383771896362305], accuracy: [0.6351999640464783, 0.6450908780097961], mean_accuracy:0.6401454210281372,variance_accuracy:0.0049454569816589355, disparity: [0.05892782658338547, 0.129180908203125], mean_disparity:0.09405436739325523,variance_disparity:0.035126540809869766, pred_disparity: [0.06894852966070175, 0.11619651317596436]
2023-09-28 23:26:33,314 - utils - INFO - global_valid: True, epoch: 1479,  global_loss: 0.635407030582428, global_accuracy: 0.6951900760304122,  global_disparity:0.12063616514205933, global_pred_disparity: 0.11279734969139099,
2023-09-28 23:26:33,423 - utils - INFO - stage2_gradient_single_runtime: 0.006241559982299805
2023-09-28 23:26:33,428 - utils - INFO - 1, epoch: 1480, all client loss: [0.6315926313400269, 0.6313410401344299], all pred client disparities: [0.06948094815015793, 0.10341131687164307], all client disparities: [0.0592096671462059, 0.1104002296924591], all client accs: [0.6194511651992798, 0.6680550575256348],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:33,493 - utils - INFO - stage2_gradient_single_runtime: 0.007024049758911133
2023-09-28 23:26:33,498 - utils - INFO - 1, epoch: 1481, all client loss: [0.6336061954498291, 0.6333341598510742], all pred client disparities: [0.063740573823452, 0.10044345259666443], all client disparities: [0.052542995661497116, 0.1068776547908783], all client accs: [0.6170298457145691, 0.6642521023750305],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:33,556 - utils - INFO - stage2_gradient_single_runtime: 0.006194353103637695
2023-09-28 23:26:33,561 - utils - INFO - 1, epoch: 1482, all client loss: [0.6356344819068909, 0.6353473663330078], all pred client disparities: [0.058165423572063446, 0.09738385677337646], all client disparities: [0.04377150163054466, 0.10395404696464539], all client accs: [0.6125907897949219, 0.6606302261352539],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:33,623 - utils - INFO - stage2_gradient_single_runtime: 0.007376432418823242
2023-09-28 23:26:33,626 - utils - INFO - 1, epoch: 1483, all client loss: [0.6320974230766296, 0.6317632794380188], all pred client disparities: [0.06798537075519562, 0.1028279960155487], all client disparities: [0.05754299461841583, 0.10781800746917725], all client accs: [0.6190475821495056, 0.6680550575256348],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:33,680 - utils - INFO - stage2_gradient_single_runtime: 0.0063436031341552734
2023-09-28 23:26:33,683 - utils - INFO - 1, epoch: 1484, all client loss: [0.6341121196746826, 0.6337581872940063], all pred client disparities: [0.06229664012789726, 0.09984233975410461], all client disparities: [0.05087633058428764, 0.10558965802192688], all client accs: [0.6166263222694397, 0.6631655693054199],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:33,737 - utils - INFO - stage2_gradient_single_runtime: 0.006093740463256836
2023-09-28 23:26:33,740 - utils - INFO - 1, epoch: 1485, all client loss: [0.6306728720664978, 0.6302751302719116], all pred client disparities: [0.0720861628651619, 0.10505732893943787], all client disparities: [0.06170966476202011, 0.11272487044334412], all client accs: [0.6202582716941833, 0.6695038080215454],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:33,796 - utils - INFO - stage2_gradient_single_runtime: 0.0067598819732666016
2023-09-28 23:26:33,803 - utils - INFO - 1, epoch: 1486, all client loss: [0.6326691508293152, 0.6322471499443054], all pred client disparities: [0.06631676852703094, 0.10214731097221375], all client disparities: [0.056709665805101395, 0.10670384764671326], all client accs: [0.6186440587043762, 0.6667873859405518],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:33,859 - utils - INFO - stage2_gradient_single_runtime: 0.00605463981628418
2023-09-28 23:26:33,862 - utils - INFO - 1, epoch: 1487, all client loss: [0.6346843242645264, 0.6342436075210571], all pred client disparities: [0.06068927049636841, 0.09914246201515198], all client disparities: [0.04670966416597366, 0.10507446527481079], all client accs: [0.6146085262298584, 0.6620789766311646],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:33,916 - utils - INFO - stage2_gradient_single_runtime: 0.0062408447265625
2023-09-28 23:26:33,919 - utils - INFO - 1, epoch: 1488, all client loss: [0.6312129497528076, 0.6307300329208374], all pred client disparities: [0.07047060132026672, 0.10443040728569031], all client disparities: [0.06004299595952034, 0.11092168092727661], all client accs: [0.6194511651992798, 0.6682361364364624],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:33,973 - utils - INFO - stage2_gradient_single_runtime: 0.006131649017333984
2023-09-28 23:26:33,976 - utils - INFO - 1, epoch: 1489, all client loss: [0.6332116723060608, 0.6327053308486938], all pred client disparities: [0.06475003063678741, 0.10150015354156494], all client disparities: [0.05504300072789192, 0.1067938506603241], all client accs: [0.6178369522094727, 0.6653386354446411],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:34,038 - utils - INFO - stage2_gradient_single_runtime: 0.006135702133178711
2023-09-28 23:26:34,043 - utils - INFO - 1, epoch: 1490, all client loss: [0.6352265477180481, 0.6347024440765381], all pred client disparities: [0.05918366461992264, 0.09847798943519592], all client disparities: [0.04504299536347389, 0.10593727231025696], all client accs: [0.614205002784729, 0.6611735224723816],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:34,099 - utils - INFO - stage2_gradient_single_runtime: 0.006030559539794922
2023-09-28 23:26:34,102 - utils - INFO - 1, epoch: 1491, all client loss: [0.6317247152328491, 0.6311600208282471], all pred client disparities: [0.06895355135202408, 0.10383588075637817], all client disparities: [0.0592096671462059, 0.109717458486557], all client accs: [0.6198546886444092, 0.6682361364364624],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:34,156 - utils - INFO - stage2_gradient_single_runtime: 0.0062084197998046875
2023-09-28 23:26:34,159 - utils - INFO - 1, epoch: 1492, all client loss: [0.633725106716156, 0.6331377625465393], all pred client disparities: [0.06328223645687103, 0.1008872389793396], all client disparities: [0.05170966684818268, 0.10602104663848877], all client accs: [0.6166263222694397, 0.6644331812858582],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:34,277 - utils - INFO - stage2_gradient_single_runtime: 0.0061762332916259766
2023-09-28 23:26:34,280 - utils - INFO - 1, epoch: 1493, all client loss: [0.6357390284538269, 0.6351348161697388], all pred client disparities: [0.05777636542916298, 0.09784936904907227], all client disparities: [0.04377150163054466, 0.10567969083786011], all client accs: [0.6125907897949219, 0.6609923839569092],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:34,337 - utils - INFO - stage2_gradient_single_runtime: 0.00624847412109375
2023-09-28 23:26:34,340 - utils - INFO - 1, epoch: 1494, all client loss: [0.6335746049880981, 0.6333540081977844], all pred client disparities: [0.06398607045412064, 0.10026133060455322], all client disparities: [0.052542995661497116, 0.10678762197494507], all client accs: [0.6170298457145691, 0.6647953987121582],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:34,393 - utils - INFO - stage2_gradient_single_runtime: 0.006211519241333008
2023-09-28 23:26:34,396 - utils - INFO - 1, epoch: 1495, all client loss: [0.6355984210968018, 0.6353628635406494], all pred client disparities: [0.058417875319719315, 0.09722009301185608], all client disparities: [0.04254300147294998, 0.10317504405975342], all client accs: [0.6129943132400513, 0.6606302261352539],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:34,455 - utils - INFO - stage2_gradient_single_runtime: 0.006181955337524414
2023-09-28 23:26:34,463 - utils - INFO - 1, epoch: 1496, all client loss: [0.6320640444755554, 0.6317804455757141], all pred client disparities: [0.0682372897863388, 0.10264280438423157], all client disparities: [0.05837633088231087, 0.10859081149101257], all client accs: [0.6194511651992798, 0.6682361364364624],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:34,523 - utils - INFO - stage2_gradient_single_runtime: 0.006123781204223633
2023-09-28 23:26:34,528 - utils - INFO - 1, epoch: 1497, all client loss: [0.6340741515159607, 0.6337708830833435], all pred client disparities: [0.06255690008401871, 0.09967514872550964], all client disparities: [0.05087633058428764, 0.10549962520599365], all client accs: [0.6162227392196655, 0.6631655693054199],  alphas:tensor([1., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:34,586 - utils - INFO - stage2_gradient_single_runtime: 0.00600743293762207
2023-09-28 23:26:34,589 - utils - INFO - 1, epoch: 1498, all client loss: [0.6306377053260803, 0.630289614200592], all pred client disparities: [0.07234415411949158, 0.10486987233161926], all client disparities: [0.06170966476202011, 0.11186206340789795], all client accs: [0.6202582716941833, 0.6695038080215454],  alphas:tensor([0.5003, 0.0000, 0.0000, 0.4997], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:34,642 - utils - INFO - stage2_gradient_single_runtime: 0.006275653839111328
2023-09-28 23:26:34,646 - utils - INFO - 1, epoch: 1499, all client loss: [0.6326292753219604, 0.6322571039199829], all pred client disparities: [0.06658437848091125, 0.10197743773460388], all client disparities: [0.05754299461841583, 0.10799184441566467], all client accs: [0.6190475821495056, 0.6669685244560242],  alphas:tensor([0.5002, 0.0000, 0.0000, 0.4998], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:34,660 - utils - INFO - valid: True, epoch: 1499, loss: [0.6315751075744629, 0.6409433484077454], accuracy: [0.6319999694824219, 0.6392726898193359], mean_accuracy:0.6356363296508789,variance_accuracy:0.0036363601684570312, disparity: [0.04828952997922897, 0.12602302432060242], mean_disparity:0.0871562771499157,variance_disparity:0.03886674717068672, pred_disparity: [0.06077876687049866, 0.111824631690979]
2023-09-28 23:26:34,673 - utils - INFO - global_valid: True, epoch: 1499,  global_loss: 0.6380158066749573, global_accuracy: 0.6901990796318528,  global_disparity:0.11576604843139648, global_pred_disparity: 0.10761341452598572,
2023-09-28 23:26:34,673 - utils - INFO - stage2_runtime: 54.08608961105347
2023-09-28 23:26:34,729 - utils - INFO - stage3_gradient_single_runtime: 0.006894111633300781
2023-09-28 23:26:34,732 - utils - INFO - 1, epoch: 1500, all client loss: [0.6346399188041687, 0.6342489123344421], all pred client disparities: [0.06096400320529938, 0.09899076819419861], all client disparities: [0.048376329243183136, 0.10403785109519958], all client accs: [0.615415632724762, 0.6624411344528198],alphas:tensor([1., 0., 0., 0., 0.], device='cuda:0', dtype=torch.float64)
2023-09-28 23:26:34,788 - utils - INFO - stage3_gradient_single_runtime: 0.006129741668701172
2023-09-28 23:26:34,791 - utils - INFO - 1, epoch: 1501, all client loss: [0.631122887134552, 0.6308259963989258], all pred client disparities: [0.07095518708229065, 0.1040540337562561], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6693227291107178],alphas:tensor([0.4535, 0.2330, 0.3134, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:34,845 - utils - INFO - stage3_gradient_single_runtime: 0.0060214996337890625
2023-09-28 23:26:34,849 - utils - INFO - 1, epoch: 1502, all client loss: [0.6311228275299072, 0.6308260560035706], all pred client disparities: [0.07095634937286377, 0.10405287146568298], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6693227291107178],alphas:tensor([0.4535, 0.2330, 0.3134, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:34,962 - utils - INFO - stage3_gradient_single_runtime: 0.006256818771362305
2023-09-28 23:26:34,965 - utils - INFO - 1, epoch: 1503, all client loss: [0.6311227679252625, 0.6308261752128601], all pred client disparities: [0.0709574967622757, 0.10405173897743225], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6693227291107178],alphas:tensor([0.4535, 0.2330, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:35,021 - utils - INFO - stage3_gradient_single_runtime: 0.006357431411743164
2023-09-28 23:26:35,024 - utils - INFO - 1, epoch: 1504, all client loss: [0.6311227083206177, 0.6308262348175049], all pred client disparities: [0.07095865905284882, 0.10405054688453674], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4535, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:35,078 - utils - INFO - stage3_gradient_single_runtime: 0.005934000015258789
2023-09-28 23:26:35,081 - utils - INFO - 1, epoch: 1505, all client loss: [0.6311226487159729, 0.6308262944221497], all pred client disparities: [0.07095981389284134, 0.10404941439628601], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4535, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:35,139 - utils - INFO - stage3_gradient_single_runtime: 0.006190299987792969
2023-09-28 23:26:35,142 - utils - INFO - 1, epoch: 1506, all client loss: [0.6311225891113281, 0.6308262944221497], all pred client disparities: [0.07096096128225327, 0.10404825210571289], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4535, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:35,197 - utils - INFO - stage3_gradient_single_runtime: 0.006224632263183594
2023-09-28 23:26:35,203 - utils - INFO - 1, epoch: 1507, all client loss: [0.6311225891113281, 0.6308264136314392], all pred client disparities: [0.07096211612224579, 0.10404714941978455], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4535, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:35,266 - utils - INFO - stage3_gradient_single_runtime: 0.0073909759521484375
2023-09-28 23:26:35,272 - utils - INFO - 1, epoch: 1508, all client loss: [0.6311225295066833, 0.630826473236084], all pred client disparities: [0.07096325606107712, 0.10404595732688904], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4535, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:35,329 - utils - INFO - stage3_gradient_single_runtime: 0.006282329559326172
2023-09-28 23:26:35,335 - utils - INFO - 1, epoch: 1509, all client loss: [0.6311224102973938, 0.6308265328407288], all pred client disparities: [0.07096441090106964, 0.10404488444328308], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4535, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:35,397 - utils - INFO - stage3_gradient_single_runtime: 0.006175041198730469
2023-09-28 23:26:35,402 - utils - INFO - 1, epoch: 1510, all client loss: [0.6311224102973938, 0.6308265924453735], all pred client disparities: [0.07096553593873978, 0.10404372215270996], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4535, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:35,461 - utils - INFO - stage3_gradient_single_runtime: 0.0067653656005859375
2023-09-28 23:26:35,467 - utils - INFO - 1, epoch: 1511, all client loss: [0.6311222910881042, 0.6308266520500183], all pred client disparities: [0.0709666758775711, 0.10404258966445923], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4535, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:35,526 - utils - INFO - stage3_gradient_single_runtime: 0.006024599075317383
2023-09-28 23:26:35,531 - utils - INFO - 1, epoch: 1512, all client loss: [0.6311222910881042, 0.6308267712593079], all pred client disparities: [0.07096781581640244, 0.10404148697853088], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4535, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:35,593 - utils - INFO - stage3_gradient_single_runtime: 0.006173133850097656
2023-09-28 23:26:35,598 - utils - INFO - 1, epoch: 1513, all client loss: [0.6311222314834595, 0.6308268308639526], all pred client disparities: [0.07096894830465317, 0.10404035449028015], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4535, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:35,709 - utils - INFO - stage3_gradient_single_runtime: 0.0061855316162109375
2023-09-28 23:26:35,714 - utils - INFO - 1, epoch: 1514, all client loss: [0.6311222314834595, 0.6308268308639526], all pred client disparities: [0.0709700733423233, 0.10403922200202942], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4535, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:35,773 - utils - INFO - stage3_gradient_single_runtime: 0.0063097476959228516
2023-09-28 23:26:35,778 - utils - INFO - 1, epoch: 1515, all client loss: [0.6311221122741699, 0.6308269500732422], all pred client disparities: [0.07097118347883224, 0.10403811931610107], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:35,841 - utils - INFO - stage3_gradient_single_runtime: 0.006190061569213867
2023-09-28 23:26:35,846 - utils - INFO - 1, epoch: 1516, all client loss: [0.6311221122741699, 0.630827009677887], all pred client disparities: [0.07097230851650238, 0.10403698682785034], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:35,904 - utils - INFO - stage3_gradient_single_runtime: 0.0062503814697265625
2023-09-28 23:26:35,909 - utils - INFO - 1, epoch: 1517, all client loss: [0.6311219930648804, 0.6308270692825317], all pred client disparities: [0.07097342610359192, 0.10403585433959961], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:35,973 - utils - INFO - stage3_gradient_single_runtime: 0.0061037540435791016
2023-09-28 23:26:35,978 - utils - INFO - 1, epoch: 1518, all client loss: [0.6311219930648804, 0.6308271288871765], all pred client disparities: [0.07097455114126205, 0.10403478145599365], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:36,040 - utils - INFO - stage3_gradient_single_runtime: 0.006282329559326172
2023-09-28 23:26:36,045 - utils - INFO - 1, epoch: 1519, all client loss: [0.6311219334602356, 0.6308271884918213], all pred client disparities: [0.07097567617893219, 0.10403364896774292], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:36,059 - utils - INFO - valid: True, epoch: 1519, loss: [0.6284676790237427, 0.6379502415657043], accuracy: [0.6367999911308289, 0.6472727060317993], mean_accuracy:0.6420363485813141,variance_accuracy:0.0052363574504852295, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07038910686969757, 0.11684876680374146]
2023-09-28 23:26:36,070 - utils - INFO - global_valid: True, epoch: 1519,  global_loss: 0.6349869966506958, global_accuracy: 0.6959613845538215,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11362837255001068,
2023-09-28 23:26:36,127 - utils - INFO - stage3_gradient_single_runtime: 0.006197452545166016
2023-09-28 23:26:36,132 - utils - INFO - 1, epoch: 1520, all client loss: [0.6311218738555908, 0.6308271884918213], all pred client disparities: [0.07097677886486053, 0.10403254628181458], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:36,191 - utils - INFO - stage3_gradient_single_runtime: 0.006094932556152344
2023-09-28 23:26:36,196 - utils - INFO - 1, epoch: 1521, all client loss: [0.631121814250946, 0.6308273077011108], all pred client disparities: [0.07097788155078888, 0.10403141379356384], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:36,261 - utils - INFO - stage3_gradient_single_runtime: 0.0067479610443115234
2023-09-28 23:26:36,266 - utils - INFO - 1, epoch: 1522, all client loss: [0.6311217546463013, 0.6308273673057556], all pred client disparities: [0.07097898423671722, 0.10403037071228027], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:36,322 - utils - INFO - stage3_gradient_single_runtime: 0.006224155426025391
2023-09-28 23:26:36,326 - utils - INFO - 1, epoch: 1523, all client loss: [0.6311216950416565, 0.6308274865150452], all pred client disparities: [0.07098009437322617, 0.10402923822402954], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:36,382 - utils - INFO - stage3_gradient_single_runtime: 0.006624698638916016
2023-09-28 23:26:36,386 - utils - INFO - 1, epoch: 1524, all client loss: [0.6311216950416565, 0.6308275461196899], all pred client disparities: [0.07098119705915451, 0.10402816534042358], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:36,442 - utils - INFO - stage3_gradient_single_runtime: 0.0063593387603759766
2023-09-28 23:26:36,447 - utils - INFO - 1, epoch: 1525, all client loss: [0.6311216354370117, 0.6308275461196899], all pred client disparities: [0.07098229229450226, 0.10402706265449524], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:36,509 - utils - INFO - stage3_gradient_single_runtime: 0.006214618682861328
2023-09-28 23:26:36,513 - utils - INFO - 1, epoch: 1526, all client loss: [0.6311215758323669, 0.6308276653289795], all pred client disparities: [0.07098338007926941, 0.10402598977088928], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:36,571 - utils - INFO - stage3_gradient_single_runtime: 0.006231546401977539
2023-09-28 23:26:36,575 - utils - INFO - 1, epoch: 1527, all client loss: [0.6311215162277222, 0.6308276653289795], all pred client disparities: [0.07098446786403656, 0.10402491688728333], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:36,686 - utils - INFO - stage3_gradient_single_runtime: 0.007502079010009766
2023-09-28 23:26:36,690 - utils - INFO - 1, epoch: 1528, all client loss: [0.6311214566230774, 0.630827784538269], all pred client disparities: [0.07098556309938431, 0.10402381420135498], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:36,751 - utils - INFO - stage3_gradient_single_runtime: 0.006139039993286133
2023-09-28 23:26:36,756 - utils - INFO - 1, epoch: 1529, all client loss: [0.6311214566230774, 0.6308278441429138], all pred client disparities: [0.07098665088415146, 0.10402268171310425], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:36,816 - utils - INFO - stage3_gradient_single_runtime: 0.007559776306152344
2023-09-28 23:26:36,821 - utils - INFO - 1, epoch: 1530, all client loss: [0.6311213970184326, 0.6308279037475586], all pred client disparities: [0.07098773121833801, 0.10402166843414307], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:36,883 - utils - INFO - stage3_gradient_single_runtime: 0.0060977935791015625
2023-09-28 23:26:36,888 - utils - INFO - 1, epoch: 1531, all client loss: [0.6311213374137878, 0.6308280229568481], all pred client disparities: [0.07098880410194397, 0.10402056574821472], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:36,952 - utils - INFO - stage3_gradient_single_runtime: 0.0063228607177734375
2023-09-28 23:26:36,957 - utils - INFO - 1, epoch: 1532, all client loss: [0.6311212778091431, 0.6308280825614929], all pred client disparities: [0.07098989933729172, 0.10401955246925354], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:37,015 - utils - INFO - stage3_gradient_single_runtime: 0.0062541961669921875
2023-09-28 23:26:37,020 - utils - INFO - 1, epoch: 1533, all client loss: [0.6311211585998535, 0.6308281421661377], all pred client disparities: [0.07099097222089767, 0.1040184497833252], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:37,083 - utils - INFO - stage3_gradient_single_runtime: 0.006124019622802734
2023-09-28 23:26:37,088 - utils - INFO - 1, epoch: 1534, all client loss: [0.6311211585998535, 0.6308282017707825], all pred client disparities: [0.07099204510450363, 0.10401737689971924], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:37,152 - utils - INFO - stage3_gradient_single_runtime: 0.006489992141723633
2023-09-28 23:26:37,158 - utils - INFO - 1, epoch: 1535, all client loss: [0.6311211585998535, 0.6308282613754272], all pred client disparities: [0.0709931030869484, 0.10401633381843567], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:37,214 - utils - INFO - stage3_gradient_single_runtime: 0.006066560745239258
2023-09-28 23:26:37,219 - utils - INFO - 1, epoch: 1536, all client loss: [0.6311211585998535, 0.630828320980072], all pred client disparities: [0.07099417597055435, 0.1040152907371521], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:37,279 - utils - INFO - stage3_gradient_single_runtime: 0.006238698959350586
2023-09-28 23:26:37,284 - utils - INFO - 1, epoch: 1537, all client loss: [0.6311209797859192, 0.6308283805847168], all pred client disparities: [0.07099524885416031, 0.10401418805122375], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4534, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:37,346 - utils - INFO - stage3_gradient_single_runtime: 0.007284402847290039
2023-09-28 23:26:37,352 - utils - INFO - 1, epoch: 1538, all client loss: [0.6311209797859192, 0.6308284401893616], all pred client disparities: [0.07099631428718567, 0.10401314496994019], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:37,409 - utils - INFO - stage3_gradient_single_runtime: 0.006207942962646484
2023-09-28 23:26:37,414 - utils - INFO - 1, epoch: 1539, all client loss: [0.6311208605766296, 0.6308285593986511], all pred client disparities: [0.07099736481904984, 0.10401207208633423], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:37,428 - utils - INFO - valid: True, epoch: 1539, loss: [0.6284682750701904, 0.6379534006118774], accuracy: [0.6367999911308289, 0.6472727060317993], mean_accuracy:0.6420363485813141,variance_accuracy:0.0052363574504852295, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.0704110637307167, 0.11683419346809387]
2023-09-28 23:26:37,439 - utils - INFO - global_valid: True, epoch: 1539,  global_loss: 0.634989321231842, global_accuracy: 0.6959553821528612,  global_disparity:0.12307125329971313, global_pred_disparity: 0.1136234700679779,
2023-09-28 23:26:37,497 - utils - INFO - stage3_gradient_single_runtime: 0.006647586822509766
2023-09-28 23:26:37,503 - utils - INFO - 1, epoch: 1540, all client loss: [0.6311208605766296, 0.6308285593986511], all pred client disparities: [0.0709984228014946, 0.10401105880737305], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:37,617 - utils - INFO - stage3_gradient_single_runtime: 0.006194353103637695
2023-09-28 23:26:37,621 - utils - INFO - 1, epoch: 1541, all client loss: [0.6311208009719849, 0.6308286190032959], all pred client disparities: [0.07099948078393936, 0.10400998592376709], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:37,677 - utils - INFO - stage3_gradient_single_runtime: 0.006217479705810547
2023-09-28 23:26:37,682 - utils - INFO - 1, epoch: 1542, all client loss: [0.6311207413673401, 0.6308287382125854], all pred client disparities: [0.07100053131580353, 0.10400894284248352], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:37,743 - utils - INFO - stage3_gradient_single_runtime: 0.0064849853515625
2023-09-28 23:26:37,749 - utils - INFO - 1, epoch: 1543, all client loss: [0.6311207413673401, 0.6308287382125854], all pred client disparities: [0.0710015743970871, 0.10400795936584473], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:37,812 - utils - INFO - stage3_gradient_single_runtime: 0.006728649139404297
2023-09-28 23:26:37,818 - utils - INFO - 1, epoch: 1544, all client loss: [0.6311206221580505, 0.630828857421875], all pred client disparities: [0.07100263237953186, 0.104006826877594], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2331, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:37,874 - utils - INFO - stage3_gradient_single_runtime: 0.006201267242431641
2023-09-28 23:26:37,879 - utils - INFO - 1, epoch: 1545, all client loss: [0.6311206221580505, 0.6308289170265198], all pred client disparities: [0.07100366055965424, 0.10400587320327759], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2332, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:37,937 - utils - INFO - stage3_gradient_single_runtime: 0.006396293640136719
2023-09-28 23:26:37,942 - utils - INFO - 1, epoch: 1546, all client loss: [0.6311205625534058, 0.6308289766311646], all pred client disparities: [0.0710047036409378, 0.10400477051734924], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2332, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:38,004 - utils - INFO - stage3_gradient_single_runtime: 0.006069183349609375
2023-09-28 23:26:38,009 - utils - INFO - 1, epoch: 1547, all client loss: [0.6311205625534058, 0.6308290362358093], all pred client disparities: [0.07100574672222137, 0.10400378704071045], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2332, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:38,066 - utils - INFO - stage3_gradient_single_runtime: 0.006312370300292969
2023-09-28 23:26:38,071 - utils - INFO - 1, epoch: 1548, all client loss: [0.6311204433441162, 0.6308290958404541], all pred client disparities: [0.07100678235292435, 0.10400280356407166], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2332, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:38,127 - utils - INFO - stage3_gradient_single_runtime: 0.006181001663208008
2023-09-28 23:26:38,132 - utils - INFO - 1, epoch: 1549, all client loss: [0.6311204433441162, 0.6308291554450989], all pred client disparities: [0.07100781798362732, 0.10400170087814331], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2332, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:38,193 - utils - INFO - stage3_gradient_single_runtime: 0.00613093376159668
2023-09-28 23:26:38,198 - utils - INFO - 1, epoch: 1550, all client loss: [0.6311203837394714, 0.6308292150497437], all pred client disparities: [0.07100885361433029, 0.10400071740150452], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2332, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:38,257 - utils - INFO - stage3_gradient_single_runtime: 0.006197214126586914
2023-09-28 23:26:38,263 - utils - INFO - 1, epoch: 1551, all client loss: [0.6311203241348267, 0.6308293342590332], all pred client disparities: [0.07100986689329147, 0.10399967432022095], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2332, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:38,319 - utils - INFO - stage3_gradient_single_runtime: 0.006183624267578125
2023-09-28 23:26:38,323 - utils - INFO - 1, epoch: 1552, all client loss: [0.6311202645301819, 0.630829393863678], all pred client disparities: [0.07101090252399445, 0.10399863123893738], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2332, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:38,379 - utils - INFO - stage3_gradient_single_runtime: 0.006246089935302734
2023-09-28 23:26:38,383 - utils - INFO - 1, epoch: 1553, all client loss: [0.6311202645301819, 0.630829393863678], all pred client disparities: [0.07101192325353622, 0.1039976179599762], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2332, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:38,489 - utils - INFO - stage3_gradient_single_runtime: 0.006338596343994141
2023-09-28 23:26:38,494 - utils - INFO - 1, epoch: 1554, all client loss: [0.6311201453208923, 0.6308295130729675], all pred client disparities: [0.0710129514336586, 0.10399660468101501], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2332, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:38,551 - utils - INFO - stage3_gradient_single_runtime: 0.006185293197631836
2023-09-28 23:26:38,555 - utils - INFO - 1, epoch: 1555, all client loss: [0.6311200857162476, 0.6308295726776123], all pred client disparities: [0.07101397216320038, 0.10399565100669861], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2332, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:38,612 - utils - INFO - stage3_gradient_single_runtime: 0.006154060363769531
2023-09-28 23:26:38,616 - utils - INFO - 1, epoch: 1556, all client loss: [0.6311200261116028, 0.6308295726776123], all pred client disparities: [0.07101498544216156, 0.10399460792541504], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2332, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:38,680 - utils - INFO - stage3_gradient_single_runtime: 0.0061342716217041016
2023-09-28 23:26:38,686 - utils - INFO - 1, epoch: 1557, all client loss: [0.6311200261116028, 0.6308296918869019], all pred client disparities: [0.07101600617170334, 0.10399362444877625], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2332, 0.3135, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:38,743 - utils - INFO - stage3_gradient_single_runtime: 0.006330966949462891
2023-09-28 23:26:38,748 - utils - INFO - 1, epoch: 1558, all client loss: [0.631119966506958, 0.6308297514915466], all pred client disparities: [0.07101702690124512, 0.10399258136749268], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:38,803 - utils - INFO - stage3_gradient_single_runtime: 0.006054401397705078
2023-09-28 23:26:38,808 - utils - INFO - 1, epoch: 1559, all client loss: [0.631119966506958, 0.6308297514915466], all pred client disparities: [0.0710180401802063, 0.1039915680885315], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:38,822 - utils - INFO - valid: True, epoch: 1559, loss: [0.6284688115119934, 0.6379563808441162], accuracy: [0.6367999911308289, 0.6458181738853455], mean_accuracy:0.6413090825080872,variance_accuracy:0.004509091377258301, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07043198496103287, 0.11682036519050598]
2023-09-28 23:26:38,833 - utils - INFO - global_valid: True, epoch: 1559,  global_loss: 0.6349915266036987, global_accuracy: 0.6959463785514206,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11361880600452423,
2023-09-28 23:26:38,894 - utils - INFO - stage3_gradient_single_runtime: 0.006112337112426758
2023-09-28 23:26:38,899 - utils - INFO - 1, epoch: 1560, all client loss: [0.6311198472976685, 0.6308298707008362], all pred client disparities: [0.07101902365684509, 0.1039905846118927], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:38,957 - utils - INFO - stage3_gradient_single_runtime: 0.006284475326538086
2023-09-28 23:26:38,961 - utils - INFO - 1, epoch: 1561, all client loss: [0.6311198472976685, 0.630829930305481], all pred client disparities: [0.07102003693580627, 0.1039896011352539], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:39,017 - utils - INFO - stage3_gradient_single_runtime: 0.006152629852294922
2023-09-28 23:26:39,021 - utils - INFO - 1, epoch: 1562, all client loss: [0.6311197280883789, 0.6308300495147705], all pred client disparities: [0.07102103531360626, 0.10398858785629272], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:39,076 - utils - INFO - stage3_gradient_single_runtime: 0.006106853485107422
2023-09-28 23:26:39,081 - utils - INFO - 1, epoch: 1563, all client loss: [0.6311197280883789, 0.6308301091194153], all pred client disparities: [0.07102203369140625, 0.10398757457733154], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4533, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:39,144 - utils - INFO - stage3_gradient_single_runtime: 0.0061419010162353516
2023-09-28 23:26:39,148 - utils - INFO - 1, epoch: 1564, all client loss: [0.6311196684837341, 0.6308301091194153], all pred client disparities: [0.07102301716804504, 0.10398665070533752], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:39,205 - utils - INFO - stage3_gradient_single_runtime: 0.006287336349487305
2023-09-28 23:26:39,210 - utils - INFO - 1, epoch: 1565, all client loss: [0.6311196684837341, 0.6308302283287048], all pred client disparities: [0.07102401554584503, 0.10398563742637634], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:39,316 - utils - INFO - stage3_gradient_single_runtime: 0.007579803466796875
2023-09-28 23:26:39,322 - utils - INFO - 1, epoch: 1566, all client loss: [0.6311196088790894, 0.6308302283287048], all pred client disparities: [0.07102501392364502, 0.10398465394973755], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:39,384 - utils - INFO - stage3_gradient_single_runtime: 0.006966114044189453
2023-09-28 23:26:39,388 - utils - INFO - 1, epoch: 1567, all client loss: [0.6311195492744446, 0.6308302879333496], all pred client disparities: [0.07102601230144501, 0.10398367047309875], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:39,446 - utils - INFO - stage3_gradient_single_runtime: 0.0062520503997802734
2023-09-28 23:26:39,450 - utils - INFO - 1, epoch: 1568, all client loss: [0.631119430065155, 0.6308304071426392], all pred client disparities: [0.0710269957780838, 0.10398268699645996], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:39,507 - utils - INFO - stage3_gradient_single_runtime: 0.006252765655517578
2023-09-28 23:26:39,512 - utils - INFO - 1, epoch: 1569, all client loss: [0.631119430065155, 0.6308304667472839], all pred client disparities: [0.071027971804142, 0.10398173332214355], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:39,568 - utils - INFO - stage3_gradient_single_runtime: 0.006128072738647461
2023-09-28 23:26:39,572 - utils - INFO - 1, epoch: 1570, all client loss: [0.631119430065155, 0.6308305263519287], all pred client disparities: [0.07102895528078079, 0.10398072004318237], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:39,636 - utils - INFO - stage3_gradient_single_runtime: 0.0063059329986572266
2023-09-28 23:26:39,640 - utils - INFO - 1, epoch: 1571, all client loss: [0.6311193704605103, 0.6308305859565735], all pred client disparities: [0.07102994620800018, 0.10397979617118835], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:39,697 - utils - INFO - stage3_gradient_single_runtime: 0.006116151809692383
2023-09-28 23:26:39,701 - utils - INFO - 1, epoch: 1572, all client loss: [0.6311193108558655, 0.6308306455612183], all pred client disparities: [0.07103091478347778, 0.10397878289222717], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:39,758 - utils - INFO - stage3_gradient_single_runtime: 0.006238698959350586
2023-09-28 23:26:39,762 - utils - INFO - 1, epoch: 1573, all client loss: [0.6311192512512207, 0.6308307647705078], all pred client disparities: [0.07103188335895538, 0.10397785902023315], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:39,820 - utils - INFO - stage3_gradient_single_runtime: 0.007745265960693359
2023-09-28 23:26:39,823 - utils - INFO - 1, epoch: 1574, all client loss: [0.6311191916465759, 0.6308307647705078], all pred client disparities: [0.07103285193443298, 0.10397684574127197], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:39,883 - utils - INFO - stage3_gradient_single_runtime: 0.006491899490356445
2023-09-28 23:26:39,888 - utils - INFO - 1, epoch: 1575, all client loss: [0.6311191916465759, 0.6308308839797974], all pred client disparities: [0.07103382050991058, 0.10397589206695557], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:39,949 - utils - INFO - stage3_gradient_single_runtime: 0.0065517425537109375
2023-09-28 23:26:39,954 - utils - INFO - 1, epoch: 1576, all client loss: [0.6311191320419312, 0.6308309435844421], all pred client disparities: [0.07103479653596878, 0.10397493839263916], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:40,014 - utils - INFO - stage3_gradient_single_runtime: 0.006794929504394531
2023-09-28 23:26:40,019 - utils - INFO - 1, epoch: 1577, all client loss: [0.6311190724372864, 0.6308310031890869], all pred client disparities: [0.07103575766086578, 0.10397401452064514], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:40,083 - utils - INFO - stage3_gradient_single_runtime: 0.006425142288208008
2023-09-28 23:26:40,086 - utils - INFO - 1, epoch: 1578, all client loss: [0.6311190128326416, 0.6308310627937317], all pred client disparities: [0.07103671878576279, 0.10397303104400635], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:40,212 - utils - INFO - stage3_gradient_single_runtime: 0.006387948989868164
2023-09-28 23:26:40,215 - utils - INFO - 1, epoch: 1579, all client loss: [0.6311189532279968, 0.6308311223983765], all pred client disparities: [0.0710376724600792, 0.10397207736968994], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:40,230 - utils - INFO - valid: True, epoch: 1579, loss: [0.6284693479537964, 0.6379593014717102], accuracy: [0.6367999911308289, 0.6458181738853455], mean_accuracy:0.6413090825080872,variance_accuracy:0.004509091377258301, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07045188546180725, 0.11680713295936584]
2023-09-28 23:26:40,242 - utils - INFO - global_valid: True, epoch: 1579,  global_loss: 0.6349936723709106, global_accuracy: 0.6959353741496599,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11361432075500488,
2023-09-28 23:26:40,302 - utils - INFO - stage3_gradient_single_runtime: 0.006622314453125
2023-09-28 23:26:40,306 - utils - INFO - 1, epoch: 1580, all client loss: [0.631118893623352, 0.6308311820030212], all pred client disparities: [0.07103864848613739, 0.10397115349769592], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:40,368 - utils - INFO - stage3_gradient_single_runtime: 0.006676673889160156
2023-09-28 23:26:40,373 - utils - INFO - 1, epoch: 1581, all client loss: [0.631118893623352, 0.630831241607666], all pred client disparities: [0.0710396021604538, 0.10397014021873474], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:40,432 - utils - INFO - stage3_gradient_single_runtime: 0.0062410831451416016
2023-09-28 23:26:40,437 - utils - INFO - 1, epoch: 1582, all client loss: [0.631118893623352, 0.6308313012123108], all pred client disparities: [0.07104054093360901, 0.10396924614906311], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:40,497 - utils - INFO - stage3_gradient_single_runtime: 0.006739377975463867
2023-09-28 23:26:40,499 - utils - INFO - 1, epoch: 1583, all client loss: [0.6311187744140625, 0.6308314204216003], all pred client disparities: [0.07104148715734482, 0.10396823287010193], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:40,556 - utils - INFO - stage3_gradient_single_runtime: 0.0072422027587890625
2023-09-28 23:26:40,559 - utils - INFO - 1, epoch: 1584, all client loss: [0.6311187148094177, 0.6308314800262451], all pred client disparities: [0.07104244083166122, 0.10396730899810791], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:40,612 - utils - INFO - stage3_gradient_single_runtime: 0.006154298782348633
2023-09-28 23:26:40,614 - utils - INFO - 1, epoch: 1585, all client loss: [0.631118655204773, 0.6308314800262451], all pred client disparities: [0.07104339450597763, 0.10396638512611389], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:40,667 - utils - INFO - stage3_gradient_single_runtime: 0.006600856781005859
2023-09-28 23:26:40,670 - utils - INFO - 1, epoch: 1586, all client loss: [0.631118655204773, 0.6308315396308899], all pred client disparities: [0.07104432582855225, 0.1039654016494751], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:40,735 - utils - INFO - stage3_gradient_single_runtime: 0.007167339324951172
2023-09-28 23:26:40,739 - utils - INFO - 1, epoch: 1587, all client loss: [0.6311185956001282, 0.6308315992355347], all pred client disparities: [0.07104527205228806, 0.10396450757980347], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:40,797 - utils - INFO - stage3_gradient_single_runtime: 0.006330013275146484
2023-09-28 23:26:40,802 - utils - INFO - 1, epoch: 1588, all client loss: [0.6311185956001282, 0.6308317184448242], all pred client disparities: [0.07104621082544327, 0.10396355390548706], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:40,860 - utils - INFO - stage3_gradient_single_runtime: 0.0061681270599365234
2023-09-28 23:26:40,865 - utils - INFO - 1, epoch: 1589, all client loss: [0.6311184763908386, 0.630831778049469], all pred client disparities: [0.07104715704917908, 0.10396265983581543], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:40,997 - utils - INFO - stage3_gradient_single_runtime: 0.0063593387603759766
2023-09-28 23:26:41,002 - utils - INFO - 1, epoch: 1590, all client loss: [0.6311184763908386, 0.630831778049469], all pred client disparities: [0.07104810327291489, 0.10396173596382141], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:41,062 - utils - INFO - stage3_gradient_single_runtime: 0.006287336349487305
2023-09-28 23:26:41,067 - utils - INFO - 1, epoch: 1591, all client loss: [0.6311183571815491, 0.6308318972587585], all pred client disparities: [0.07104901969432831, 0.10396084189414978], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:41,125 - utils - INFO - stage3_gradient_single_runtime: 0.006215572357177734
2023-09-28 23:26:41,130 - utils - INFO - 1, epoch: 1592, all client loss: [0.6311183571815491, 0.6308319568634033], all pred client disparities: [0.07104995846748352, 0.1039598286151886], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:41,191 - utils - INFO - stage3_gradient_single_runtime: 0.006208181381225586
2023-09-28 23:26:41,196 - utils - INFO - 1, epoch: 1593, all client loss: [0.6311182975769043, 0.6308320760726929], all pred client disparities: [0.07105088979005814, 0.10395890474319458], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4532, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:41,253 - utils - INFO - stage3_gradient_single_runtime: 0.006208181381225586
2023-09-28 23:26:41,258 - utils - INFO - 1, epoch: 1594, all client loss: [0.6311182975769043, 0.6308320760726929], all pred client disparities: [0.07105181366205215, 0.10395804047584534], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4531, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:41,317 - utils - INFO - stage3_gradient_single_runtime: 0.006238222122192383
2023-09-28 23:26:41,322 - utils - INFO - 1, epoch: 1595, all client loss: [0.6311182379722595, 0.6308321356773376], all pred client disparities: [0.07105274498462677, 0.10395711660385132], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4531, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:41,381 - utils - INFO - stage3_gradient_single_runtime: 0.006245613098144531
2023-09-28 23:26:41,386 - utils - INFO - 1, epoch: 1596, all client loss: [0.6311181783676147, 0.6308321952819824], all pred client disparities: [0.07105366140604019, 0.10395622253417969], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4531, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:41,441 - utils - INFO - stage3_gradient_single_runtime: 0.006073951721191406
2023-09-28 23:26:41,444 - utils - INFO - 1, epoch: 1597, all client loss: [0.6311180591583252, 0.630832314491272], all pred client disparities: [0.07105459272861481, 0.10395529866218567], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4531, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:41,498 - utils - INFO - stage3_gradient_single_runtime: 0.00627899169921875
2023-09-28 23:26:41,501 - utils - INFO - 1, epoch: 1598, all client loss: [0.6311180591583252, 0.6308323740959167], all pred client disparities: [0.07105550915002823, 0.10395440459251404], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4531, 0.2332, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:41,554 - utils - INFO - stage3_gradient_single_runtime: 0.006111621856689453
2023-09-28 23:26:41,557 - utils - INFO - 1, epoch: 1599, all client loss: [0.6311180591583252, 0.6308324337005615], all pred client disparities: [0.07105642557144165, 0.10395345091819763], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:41,571 - utils - INFO - valid: True, epoch: 1599, loss: [0.6284697651863098, 0.6379621028900146], accuracy: [0.6367999911308289, 0.6458181738853455], mean_accuracy:0.6413090825080872,variance_accuracy:0.004509091377258301, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07047083973884583, 0.11679452657699585]
2023-09-28 23:26:41,582 - utils - INFO - global_valid: True, epoch: 1599,  global_loss: 0.6349957585334778, global_accuracy: 0.6959303721488596,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11361004412174225,
2023-09-28 23:26:41,638 - utils - INFO - stage3_gradient_single_runtime: 0.007108449935913086
2023-09-28 23:26:41,643 - utils - INFO - 1, epoch: 1600, all client loss: [0.6311179995536804, 0.6308324933052063], all pred client disparities: [0.07105731964111328, 0.10395261645317078], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:41,701 - utils - INFO - stage3_gradient_single_runtime: 0.006731510162353516
2023-09-28 23:26:41,707 - utils - INFO - 1, epoch: 1601, all client loss: [0.6311179995536804, 0.6308324933052063], all pred client disparities: [0.0710582360625267, 0.10395166277885437], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:41,766 - utils - INFO - stage3_gradient_single_runtime: 0.006249427795410156
2023-09-28 23:26:41,771 - utils - INFO - 1, epoch: 1602, all client loss: [0.6311178803443909, 0.6308326125144958], all pred client disparities: [0.07105915248394012, 0.10395079851150513], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:41,829 - utils - INFO - stage3_gradient_single_runtime: 0.006227731704711914
2023-09-28 23:26:41,834 - utils - INFO - 1, epoch: 1603, all client loss: [0.6311178803443909, 0.6308326721191406], all pred client disparities: [0.07106004655361176, 0.10394987463951111], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:41,902 - utils - INFO - stage3_gradient_single_runtime: 0.00701904296875
2023-09-28 23:26:41,908 - utils - INFO - 1, epoch: 1604, all client loss: [0.6311177611351013, 0.6308327913284302], all pred client disparities: [0.07106096297502518, 0.10394898056983948], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:42,031 - utils - INFO - stage3_gradient_single_runtime: 0.0062901973724365234
2023-09-28 23:26:42,036 - utils - INFO - 1, epoch: 1605, all client loss: [0.6311177611351013, 0.6308327913284302], all pred client disparities: [0.07106184959411621, 0.10394808650016785], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:42,100 - utils - INFO - stage3_gradient_single_runtime: 0.007280111312866211
2023-09-28 23:26:42,106 - utils - INFO - 1, epoch: 1606, all client loss: [0.6311177015304565, 0.630832850933075], all pred client disparities: [0.07106275111436844, 0.10394716262817383], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:42,165 - utils - INFO - stage3_gradient_single_runtime: 0.0061337947845458984
2023-09-28 23:26:42,170 - utils - INFO - 1, epoch: 1607, all client loss: [0.6311177015304565, 0.6308329701423645], all pred client disparities: [0.07106364518404007, 0.1039462685585022], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:42,228 - utils - INFO - stage3_gradient_single_runtime: 0.006299734115600586
2023-09-28 23:26:42,233 - utils - INFO - 1, epoch: 1608, all client loss: [0.631117582321167, 0.6308330297470093], all pred client disparities: [0.0710645467042923, 0.10394540429115295], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:42,290 - utils - INFO - stage3_gradient_single_runtime: 0.0064771175384521484
2023-09-28 23:26:42,296 - utils - INFO - 1, epoch: 1609, all client loss: [0.631117582321167, 0.630833089351654], all pred client disparities: [0.07106544822454453, 0.10394451022148132], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6691416501998901],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:42,357 - utils - INFO - stage3_gradient_single_runtime: 0.0073201656341552734
2023-09-28 23:26:42,360 - utils - INFO - 1, epoch: 1610, all client loss: [0.6311175227165222, 0.6308331489562988], all pred client disparities: [0.07106633484363556, 0.1039435863494873], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:42,413 - utils - INFO - stage3_gradient_single_runtime: 0.0060465335845947266
2023-09-28 23:26:42,416 - utils - INFO - 1, epoch: 1611, all client loss: [0.6311174631118774, 0.6308332085609436], all pred client disparities: [0.071067214012146, 0.10394269227981567], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:42,468 - utils - INFO - stage3_gradient_single_runtime: 0.00627446174621582
2023-09-28 23:26:42,470 - utils - INFO - 1, epoch: 1612, all client loss: [0.6311174631118774, 0.6308332681655884], all pred client disparities: [0.07106810808181763, 0.10394185781478882], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:42,523 - utils - INFO - stage3_gradient_single_runtime: 0.006317138671875
2023-09-28 23:26:42,525 - utils - INFO - 1, epoch: 1613, all client loss: [0.6311174631118774, 0.6308333277702332], all pred client disparities: [0.07106900215148926, 0.10394102334976196], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:42,578 - utils - INFO - stage3_gradient_single_runtime: 0.0071141719818115234
2023-09-28 23:26:42,583 - utils - INFO - 1, epoch: 1614, all client loss: [0.6311173439025879, 0.6308333873748779], all pred client disparities: [0.0710698813199997, 0.10394009947776794], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:42,639 - utils - INFO - stage3_gradient_single_runtime: 0.006045818328857422
2023-09-28 23:26:42,642 - utils - INFO - 1, epoch: 1615, all client loss: [0.6311172842979431, 0.6308335065841675], all pred client disparities: [0.07107075303792953, 0.1039392352104187], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:42,693 - utils - INFO - stage3_gradient_single_runtime: 0.0063173770904541016
2023-09-28 23:26:42,696 - utils - INFO - 1, epoch: 1616, all client loss: [0.6311172246932983, 0.6308335065841675], all pred client disparities: [0.07107163220643997, 0.10393837094306946], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:42,807 - utils - INFO - stage3_gradient_single_runtime: 0.007630825042724609
2023-09-28 23:26:42,810 - utils - INFO - 1, epoch: 1617, all client loss: [0.6311172246932983, 0.630833625793457], all pred client disparities: [0.07107250392436981, 0.10393747687339783], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:42,867 - utils - INFO - stage3_gradient_single_runtime: 0.006025552749633789
2023-09-28 23:26:42,870 - utils - INFO - 1, epoch: 1618, all client loss: [0.6311171650886536, 0.6308336853981018], all pred client disparities: [0.07107337564229965, 0.10393664240837097], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:42,921 - utils - INFO - stage3_gradient_single_runtime: 0.006260395050048828
2023-09-28 23:26:42,924 - utils - INFO - 1, epoch: 1619, all client loss: [0.6311171054840088, 0.6308337450027466], all pred client disparities: [0.07107426971197128, 0.10393580794334412], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:42,938 - utils - INFO - valid: True, epoch: 1619, loss: [0.6284701228141785, 0.6379648447036743], accuracy: [0.6367999911308289, 0.6458181738853455], mean_accuracy:0.6413090825080872,variance_accuracy:0.004509091377258301, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07048890739679337, 0.11678251624107361]
2023-09-28 23:26:42,949 - utils - INFO - global_valid: True, epoch: 1619,  global_loss: 0.6349978446960449, global_accuracy: 0.6959153661464588,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11360600590705872,
2023-09-28 23:26:43,002 - utils - INFO - stage3_gradient_single_runtime: 0.006387948989868164
2023-09-28 23:26:43,004 - utils - INFO - 1, epoch: 1620, all client loss: [0.6311171054840088, 0.6308338046073914], all pred client disparities: [0.07107514142990112, 0.1039348840713501], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:43,063 - utils - INFO - stage3_gradient_single_runtime: 0.006085872650146484
2023-09-28 23:26:43,066 - utils - INFO - 1, epoch: 1621, all client loss: [0.631117045879364, 0.6308338642120361], all pred client disparities: [0.07107601314783096, 0.10393404960632324], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:43,120 - utils - INFO - stage3_gradient_single_runtime: 0.005999326705932617
2023-09-28 23:26:43,123 - utils - INFO - 1, epoch: 1622, all client loss: [0.6311169862747192, 0.6308339238166809], all pred client disparities: [0.07107686996459961, 0.10393321514129639], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:43,176 - utils - INFO - stage3_gradient_single_runtime: 0.006289482116699219
2023-09-28 23:26:43,180 - utils - INFO - 1, epoch: 1623, all client loss: [0.6311169266700745, 0.6308339834213257], all pred client disparities: [0.07107774168252945, 0.10393235087394714], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4531, 0.2333, 0.3136, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:43,238 - utils - INFO - stage3_gradient_single_runtime: 0.006294965744018555
2023-09-28 23:26:43,243 - utils - INFO - 1, epoch: 1624, all client loss: [0.6311168670654297, 0.6308340430259705], all pred client disparities: [0.07107861340045929, 0.1039314866065979], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4531, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:43,311 - utils - INFO - stage3_gradient_single_runtime: 0.006830930709838867
2023-09-28 23:26:43,316 - utils - INFO - 1, epoch: 1625, all client loss: [0.6311168670654297, 0.6308341026306152], all pred client disparities: [0.07107946276664734, 0.10393056273460388], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4531, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:43,372 - utils - INFO - stage3_gradient_single_runtime: 0.006025075912475586
2023-09-28 23:26:43,377 - utils - INFO - 1, epoch: 1626, all client loss: [0.6311168074607849, 0.63083416223526], all pred client disparities: [0.07108032703399658, 0.10392975807189941], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4531, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:43,443 - utils - INFO - stage3_gradient_single_runtime: 0.007637977600097656
2023-09-28 23:26:43,448 - utils - INFO - 1, epoch: 1627, all client loss: [0.6311167478561401, 0.6308342218399048], all pred client disparities: [0.07108118385076523, 0.10392892360687256], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4531, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:43,570 - utils - INFO - stage3_gradient_single_runtime: 0.0060617923736572266
2023-09-28 23:26:43,575 - utils - INFO - 1, epoch: 1628, all client loss: [0.6311166882514954, 0.6308342814445496], all pred client disparities: [0.07108204066753387, 0.10392805933952332], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4531, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:43,632 - utils - INFO - stage3_gradient_single_runtime: 0.006098031997680664
2023-09-28 23:26:43,637 - utils - INFO - 1, epoch: 1629, all client loss: [0.6311166286468506, 0.6308343410491943], all pred client disparities: [0.07108289748430252, 0.10392725467681885], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4531, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:43,695 - utils - INFO - stage3_gradient_single_runtime: 0.006334781646728516
2023-09-28 23:26:43,700 - utils - INFO - 1, epoch: 1630, all client loss: [0.6311166286468506, 0.6308344006538391], all pred client disparities: [0.07108374685049057, 0.10392636060714722], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:43,763 - utils - INFO - stage3_gradient_single_runtime: 0.006283760070800781
2023-09-28 23:26:43,768 - utils - INFO - 1, epoch: 1631, all client loss: [0.6311166286468506, 0.6308345198631287], all pred client disparities: [0.07108459621667862, 0.10392552614212036], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:43,827 - utils - INFO - stage3_gradient_single_runtime: 0.0059735774993896484
2023-09-28 23:26:43,831 - utils - INFO - 1, epoch: 1632, all client loss: [0.631116509437561, 0.6308345794677734], all pred client disparities: [0.07108545303344727, 0.1039246916770935], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:43,888 - utils - INFO - stage3_gradient_single_runtime: 0.0062255859375
2023-09-28 23:26:43,892 - utils - INFO - 1, epoch: 1633, all client loss: [0.631116509437561, 0.6308346390724182], all pred client disparities: [0.07108628749847412, 0.10392387956380844], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:43,952 - utils - INFO - stage3_gradient_single_runtime: 0.006119728088378906
2023-09-28 23:26:43,958 - utils - INFO - 1, epoch: 1634, all client loss: [0.6311164498329163, 0.630834698677063], all pred client disparities: [0.07108713686466217, 0.10392305254936218], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:44,021 - utils - INFO - stage3_gradient_single_runtime: 0.006317138671875
2023-09-28 23:26:44,025 - utils - INFO - 1, epoch: 1635, all client loss: [0.6311163902282715, 0.630834698677063], all pred client disparities: [0.07108797132968903, 0.10392221808433533], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:44,080 - utils - INFO - stage3_gradient_single_runtime: 0.006059408187866211
2023-09-28 23:26:44,085 - utils - INFO - 1, epoch: 1636, all client loss: [0.6311163306236267, 0.6308348178863525], all pred client disparities: [0.07108882069587708, 0.10392138361930847], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:44,142 - utils - INFO - stage3_gradient_single_runtime: 0.006201267242431641
2023-09-28 23:26:44,148 - utils - INFO - 1, epoch: 1637, all client loss: [0.6311163306236267, 0.6308348774909973], all pred client disparities: [0.07108965516090393, 0.10392054915428162], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:44,208 - utils - INFO - stage3_gradient_single_runtime: 0.0062983036041259766
2023-09-28 23:26:44,214 - utils - INFO - 1, epoch: 1638, all client loss: [0.6311162710189819, 0.6308349370956421], all pred client disparities: [0.07109048962593079, 0.10391971468925476], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:44,326 - utils - INFO - stage3_gradient_single_runtime: 0.006303548812866211
2023-09-28 23:26:44,330 - utils - INFO - 1, epoch: 1639, all client loss: [0.6311162114143372, 0.6308349967002869], all pred client disparities: [0.07109131664037704, 0.1039188802242279], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:44,344 - utils - INFO - valid: True, epoch: 1639, loss: [0.6284705400466919, 0.6379674673080444], accuracy: [0.6367999911308289, 0.6458181738853455], mean_accuracy:0.6413090825080872,variance_accuracy:0.004509091377258301, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07050617039203644, 0.11677107214927673]
2023-09-28 23:26:44,355 - utils - INFO - global_valid: True, epoch: 1639,  global_loss: 0.634999692440033, global_accuracy: 0.6959033613445378,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11360211670398712,
2023-09-28 23:26:44,413 - utils - INFO - stage3_gradient_single_runtime: 0.006138801574707031
2023-09-28 23:26:44,419 - utils - INFO - 1, epoch: 1640, all client loss: [0.6311161518096924, 0.6308350563049316], all pred client disparities: [0.0710921585559845, 0.10391801595687866], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:44,480 - utils - INFO - stage3_gradient_single_runtime: 0.0061740875244140625
2023-09-28 23:26:44,485 - utils - INFO - 1, epoch: 1641, all client loss: [0.6311160922050476, 0.6308351755142212], all pred client disparities: [0.07109298557043076, 0.10391724109649658], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:44,541 - utils - INFO - stage3_gradient_single_runtime: 0.006254434585571289
2023-09-28 23:26:44,546 - utils - INFO - 1, epoch: 1642, all client loss: [0.6311160922050476, 0.630835235118866], all pred client disparities: [0.07109381258487701, 0.1039164662361145], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:44,605 - utils - INFO - stage3_gradient_single_runtime: 0.006630897521972656
2023-09-28 23:26:44,611 - utils - INFO - 1, epoch: 1643, all client loss: [0.6311160326004028, 0.630835235118866], all pred client disparities: [0.07109463214874268, 0.10391560196876526], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:44,673 - utils - INFO - stage3_gradient_single_runtime: 0.007421731948852539
2023-09-28 23:26:44,679 - utils - INFO - 1, epoch: 1644, all client loss: [0.6311160326004028, 0.6308353543281555], all pred client disparities: [0.07109545916318893, 0.1039147675037384], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:44,735 - utils - INFO - stage3_gradient_single_runtime: 0.006125926971435547
2023-09-28 23:26:44,739 - utils - INFO - 1, epoch: 1645, all client loss: [0.6311159133911133, 0.6308354139328003], all pred client disparities: [0.0710962787270546, 0.10391396284103394], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:44,796 - utils - INFO - stage3_gradient_single_runtime: 0.006312370300292969
2023-09-28 23:26:44,802 - utils - INFO - 1, epoch: 1646, all client loss: [0.6311159133911133, 0.6308354139328003], all pred client disparities: [0.07109711319208145, 0.10391315817832947], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:44,861 - utils - INFO - stage3_gradient_single_runtime: 0.00628662109375
2023-09-28 23:26:44,867 - utils - INFO - 1, epoch: 1647, all client loss: [0.6311157941818237, 0.6308355331420898], all pred client disparities: [0.07109792530536652, 0.10391232371330261], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:44,928 - utils - INFO - stage3_gradient_single_runtime: 0.006195068359375
2023-09-28 23:26:44,933 - utils - INFO - 1, epoch: 1648, all client loss: [0.6311157941818237, 0.6308355927467346], all pred client disparities: [0.07109873741865158, 0.10391154885292053], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:44,989 - utils - INFO - stage3_gradient_single_runtime: 0.006270408630371094
2023-09-28 23:26:44,994 - utils - INFO - 1, epoch: 1649, all client loss: [0.631115734577179, 0.6308356523513794], all pred client disparities: [0.07109954208135605, 0.10391071438789368], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:45,053 - utils - INFO - stage3_gradient_single_runtime: 0.006081104278564453
2023-09-28 23:26:45,058 - utils - INFO - 1, epoch: 1650, all client loss: [0.631115734577179, 0.6308357119560242], all pred client disparities: [0.07110035419464111, 0.1039099395275116], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:45,167 - utils - INFO - stage3_gradient_single_runtime: 0.00612640380859375
2023-09-28 23:26:45,171 - utils - INFO - 1, epoch: 1651, all client loss: [0.631115734577179, 0.630835771560669], all pred client disparities: [0.07110116630792618, 0.10390910506248474], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:45,231 - utils - INFO - stage3_gradient_single_runtime: 0.006243228912353516
2023-09-28 23:26:45,236 - utils - INFO - 1, epoch: 1652, all client loss: [0.6311156153678894, 0.6308358311653137], all pred client disparities: [0.07110197842121124, 0.10390833020210266], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:45,299 - utils - INFO - stage3_gradient_single_runtime: 0.006041765213012695
2023-09-28 23:26:45,303 - utils - INFO - 1, epoch: 1653, all client loss: [0.6311156153678894, 0.6308358907699585], all pred client disparities: [0.07110277563333511, 0.1039075255393982], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:45,363 - utils - INFO - stage3_gradient_single_runtime: 0.006245613098144531
2023-09-28 23:26:45,368 - utils - INFO - 1, epoch: 1654, all client loss: [0.6311155557632446, 0.6308359503746033], all pred client disparities: [0.07110357284545898, 0.10390675067901611], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:45,422 - utils - INFO - stage3_gradient_single_runtime: 0.006045341491699219
2023-09-28 23:26:45,426 - utils - INFO - 1, epoch: 1655, all client loss: [0.6311154961585999, 0.6308360695838928], all pred client disparities: [0.07110439240932465, 0.10390594601631165], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:45,485 - utils - INFO - stage3_gradient_single_runtime: 0.006296396255493164
2023-09-28 23:26:45,491 - utils - INFO - 1, epoch: 1656, all client loss: [0.6311154961585999, 0.6308361291885376], all pred client disparities: [0.07110518962144852, 0.10390514135360718], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:45,557 - utils - INFO - stage3_gradient_single_runtime: 0.007501840591430664
2023-09-28 23:26:45,564 - utils - INFO - 1, epoch: 1657, all client loss: [0.6311154365539551, 0.6308361887931824], all pred client disparities: [0.07110598683357239, 0.10390433669090271], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:45,620 - utils - INFO - stage3_gradient_single_runtime: 0.006130695343017578
2023-09-28 23:26:45,624 - utils - INFO - 1, epoch: 1658, all client loss: [0.6311153769493103, 0.6308362483978271], all pred client disparities: [0.07110679149627686, 0.10390359163284302], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:45,679 - utils - INFO - stage3_gradient_single_runtime: 0.006329774856567383
2023-09-28 23:26:45,683 - utils - INFO - 1, epoch: 1659, all client loss: [0.6311153173446655, 0.6308363080024719], all pred client disparities: [0.07110757380723953, 0.10390275716781616], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:45,697 - utils - INFO - valid: True, epoch: 1659, loss: [0.6284708380699158, 0.637969970703125], accuracy: [0.6367999911308289, 0.6458181738853455], mean_accuracy:0.6413090825080872,variance_accuracy:0.004509091377258301, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07052261382341385, 0.11676010489463806]
2023-09-28 23:26:45,709 - utils - INFO - global_valid: True, epoch: 1659,  global_loss: 0.635001540184021, global_accuracy: 0.6958893557422969,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11359837651252747,
2023-09-28 23:26:45,767 - utils - INFO - stage3_gradient_single_runtime: 0.006161928176879883
2023-09-28 23:26:45,773 - utils - INFO - 1, epoch: 1660, all client loss: [0.6311153173446655, 0.6308363676071167], all pred client disparities: [0.0711083635687828, 0.10390198230743408], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:45,841 - utils - INFO - stage3_gradient_single_runtime: 0.006455659866333008
2023-09-28 23:26:45,846 - utils - INFO - 1, epoch: 1661, all client loss: [0.6311152577400208, 0.6308364272117615], all pred client disparities: [0.07110916823148727, 0.103901207447052], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:45,904 - utils - INFO - stage3_gradient_single_runtime: 0.00618290901184082
2023-09-28 23:26:45,909 - utils - INFO - 1, epoch: 1662, all client loss: [0.631115198135376, 0.6308364868164062], all pred client disparities: [0.07110995799303055, 0.10390043258666992], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:46,044 - utils - INFO - stage3_gradient_single_runtime: 0.006188392639160156
2023-09-28 23:26:46,049 - utils - INFO - 1, epoch: 1663, all client loss: [0.631115198135376, 0.6308366060256958], all pred client disparities: [0.07111074030399323, 0.10389965772628784], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:46,107 - utils - INFO - stage3_gradient_single_runtime: 0.006221294403076172
2023-09-28 23:26:46,112 - utils - INFO - 1, epoch: 1664, all client loss: [0.6311151385307312, 0.6308366060256958], all pred client disparities: [0.0711115300655365, 0.10389888286590576], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:46,171 - utils - INFO - stage3_gradient_single_runtime: 0.00609898567199707
2023-09-28 23:26:46,176 - utils - INFO - 1, epoch: 1665, all client loss: [0.6311150789260864, 0.6308366656303406], all pred client disparities: [0.07111230492591858, 0.1038980484008789], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:46,236 - utils - INFO - stage3_gradient_single_runtime: 0.006586790084838867
2023-09-28 23:26:46,242 - utils - INFO - 1, epoch: 1666, all client loss: [0.6311150193214417, 0.6308367848396301], all pred client disparities: [0.07111309468746185, 0.10389730334281921], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:46,299 - utils - INFO - stage3_gradient_single_runtime: 0.006101131439208984
2023-09-28 23:26:46,304 - utils - INFO - 1, epoch: 1667, all client loss: [0.6311150193214417, 0.6308368444442749], all pred client disparities: [0.07111387699842453, 0.10389649868011475], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:46,363 - utils - INFO - stage3_gradient_single_runtime: 0.007487297058105469
2023-09-28 23:26:46,369 - utils - INFO - 1, epoch: 1668, all client loss: [0.6311149597167969, 0.6308369040489197], all pred client disparities: [0.07111465930938721, 0.10389575362205505], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:46,427 - utils - INFO - stage3_gradient_single_runtime: 0.005928993225097656
2023-09-28 23:26:46,432 - utils - INFO - 1, epoch: 1669, all client loss: [0.6311149001121521, 0.6308369636535645], all pred client disparities: [0.07111544907093048, 0.10389497876167297], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:46,495 - utils - INFO - stage3_gradient_single_runtime: 0.006384372711181641
2023-09-28 23:26:46,500 - utils - INFO - 1, epoch: 1670, all client loss: [0.6311149001121521, 0.6308370232582092], all pred client disparities: [0.07111621648073196, 0.10389423370361328], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:46,558 - utils - INFO - stage3_gradient_single_runtime: 0.006244659423828125
2023-09-28 23:26:46,563 - utils - INFO - 1, epoch: 1671, all client loss: [0.6311148405075073, 0.630837082862854], all pred client disparities: [0.07111698389053345, 0.1038934588432312], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:46,624 - utils - INFO - stage3_gradient_single_runtime: 0.006077766418457031
2023-09-28 23:26:46,629 - utils - INFO - 1, epoch: 1672, all client loss: [0.6311147809028625, 0.6308371424674988], all pred client disparities: [0.07111777365207672, 0.10389268398284912], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:46,691 - utils - INFO - stage3_gradient_single_runtime: 0.007115364074707031
2023-09-28 23:26:46,697 - utils - INFO - 1, epoch: 1673, all client loss: [0.6311147212982178, 0.6308372020721436], all pred client disparities: [0.07111853361129761, 0.10389190912246704], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4530, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:46,754 - utils - INFO - stage3_gradient_single_runtime: 0.006211519241333008
2023-09-28 23:26:46,758 - utils - INFO - 1, epoch: 1674, all client loss: [0.6311147212982178, 0.6308372616767883], all pred client disparities: [0.07111930847167969, 0.10389116406440735], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:46,816 - utils - INFO - stage3_gradient_single_runtime: 0.007040262222290039
2023-09-28 23:26:46,822 - utils - INFO - 1, epoch: 1675, all client loss: [0.6311146020889282, 0.6308373212814331], all pred client disparities: [0.07112008333206177, 0.10389038920402527], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:46,931 - utils - INFO - stage3_gradient_single_runtime: 0.006310462951660156
2023-09-28 23:26:46,935 - utils - INFO - 1, epoch: 1676, all client loss: [0.6311146020889282, 0.6308373808860779], all pred client disparities: [0.07112085074186325, 0.10388964414596558], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:46,991 - utils - INFO - stage3_gradient_single_runtime: 0.006117343902587891
2023-09-28 23:26:46,996 - utils - INFO - 1, epoch: 1677, all client loss: [0.6311146020889282, 0.6308374404907227], all pred client disparities: [0.07112160325050354, 0.10388889908790588], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:47,057 - utils - INFO - stage3_gradient_single_runtime: 0.006129741668701172
2023-09-28 23:26:47,063 - utils - INFO - 1, epoch: 1678, all client loss: [0.6311145424842834, 0.6308375597000122], all pred client disparities: [0.07112236320972443, 0.10388815402984619], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:47,122 - utils - INFO - stage3_gradient_single_runtime: 0.0071828365325927734
2023-09-28 23:26:47,127 - utils - INFO - 1, epoch: 1679, all client loss: [0.6311144828796387, 0.6308375597000122], all pred client disparities: [0.07112313061952591, 0.1038874089717865], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:47,141 - utils - INFO - valid: True, epoch: 1679, loss: [0.6284710764884949, 0.6379724144935608], accuracy: [0.6367999911308289, 0.6458181738853455], mean_accuracy:0.6413090825080872,variance_accuracy:0.004509091377258301, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07053835690021515, 0.11674970388412476]
2023-09-28 23:26:47,154 - utils - INFO - global_valid: True, epoch: 1679,  global_loss: 0.6350033283233643, global_accuracy: 0.6958793517406963,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11359485983848572,
2023-09-28 23:26:47,209 - utils - INFO - stage3_gradient_single_runtime: 0.006168842315673828
2023-09-28 23:26:47,214 - utils - INFO - 1, epoch: 1680, all client loss: [0.6311144232749939, 0.630837619304657], all pred client disparities: [0.0711238905787468, 0.10388663411140442], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:47,273 - utils - INFO - stage3_gradient_single_runtime: 0.006236076354980469
2023-09-28 23:26:47,278 - utils - INFO - 1, epoch: 1681, all client loss: [0.6311144232749939, 0.6308377385139465], all pred client disparities: [0.07112465798854828, 0.10388588905334473], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:47,338 - utils - INFO - stage3_gradient_single_runtime: 0.006219625473022461
2023-09-28 23:26:47,345 - utils - INFO - 1, epoch: 1682, all client loss: [0.6311143636703491, 0.6308377981185913], all pred client disparities: [0.07112541049718857, 0.10388514399528503], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:47,405 - utils - INFO - stage3_gradient_single_runtime: 0.00618290901184082
2023-09-28 23:26:47,410 - utils - INFO - 1, epoch: 1683, all client loss: [0.6311143636703491, 0.6308377981185913], all pred client disparities: [0.07112614810466766, 0.10388442873954773], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:47,467 - utils - INFO - stage3_gradient_single_runtime: 0.006239652633666992
2023-09-28 23:26:47,472 - utils - INFO - 1, epoch: 1684, all client loss: [0.6311143040657043, 0.6308379173278809], all pred client disparities: [0.07112690806388855, 0.10388368368148804], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:47,533 - utils - INFO - stage3_gradient_single_runtime: 0.006074190139770508
2023-09-28 23:26:47,538 - utils - INFO - 1, epoch: 1685, all client loss: [0.6311142444610596, 0.6308379769325256], all pred client disparities: [0.07112765312194824, 0.10388290882110596], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:47,600 - utils - INFO - stage3_gradient_single_runtime: 0.007213592529296875
2023-09-28 23:26:47,605 - utils - INFO - 1, epoch: 1686, all client loss: [0.6311141848564148, 0.6308379769325256], all pred client disparities: [0.07112841308116913, 0.10388222336769104], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:47,663 - utils - INFO - stage3_gradient_single_runtime: 0.006107807159423828
2023-09-28 23:26:47,668 - utils - INFO - 1, epoch: 1687, all client loss: [0.63111412525177, 0.6308380961418152], all pred client disparities: [0.07112916558980942, 0.10388141870498657], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:47,773 - utils - INFO - stage3_gradient_single_runtime: 0.006120204925537109
2023-09-28 23:26:47,778 - utils - INFO - 1, epoch: 1688, all client loss: [0.6311140656471252, 0.63083815574646], all pred client disparities: [0.07112991064786911, 0.10388070344924927], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:47,840 - utils - INFO - stage3_gradient_single_runtime: 0.006196737289428711
2023-09-28 23:26:47,845 - utils - INFO - 1, epoch: 1689, all client loss: [0.6311140656471252, 0.6308382153511047], all pred client disparities: [0.07113063335418701, 0.10387992858886719], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:47,901 - utils - INFO - stage3_gradient_single_runtime: 0.006284475326538086
2023-09-28 23:26:47,905 - utils - INFO - 1, epoch: 1690, all client loss: [0.6311140656471252, 0.6308383345603943], all pred client disparities: [0.0711313858628273, 0.10387921333312988], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:47,971 - utils - INFO - stage3_gradient_single_runtime: 0.00828242301940918
2023-09-28 23:26:47,982 - utils - INFO - 1, epoch: 1691, all client loss: [0.6311140060424805, 0.6308383345603943], all pred client disparities: [0.0711321234703064, 0.10387849807739258], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:48,042 - utils - INFO - stage3_gradient_single_runtime: 0.006295204162597656
2023-09-28 23:26:48,047 - utils - INFO - 1, epoch: 1692, all client loss: [0.6311139464378357, 0.6308384537696838], all pred client disparities: [0.07113286852836609, 0.10387778282165527], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:48,104 - utils - INFO - stage3_gradient_single_runtime: 0.006122589111328125
2023-09-28 23:26:48,109 - utils - INFO - 1, epoch: 1693, all client loss: [0.6311138868331909, 0.6308385133743286], all pred client disparities: [0.07113362103700638, 0.10387703776359558], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2333, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:48,166 - utils - INFO - stage3_gradient_single_runtime: 0.006144523620605469
2023-09-28 23:26:48,172 - utils - INFO - 1, epoch: 1694, all client loss: [0.6311138272285461, 0.6308385133743286], all pred client disparities: [0.07113435119390488, 0.10387635231018066], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:48,234 - utils - INFO - stage3_gradient_single_runtime: 0.0060422420501708984
2023-09-28 23:26:48,239 - utils - INFO - 1, epoch: 1695, all client loss: [0.6311137676239014, 0.6308386325836182], all pred client disparities: [0.07113508135080338, 0.10387560725212097], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:48,298 - utils - INFO - stage3_gradient_single_runtime: 0.0070917606353759766
2023-09-28 23:26:48,303 - utils - INFO - 1, epoch: 1696, all client loss: [0.6311137676239014, 0.6308386921882629], all pred client disparities: [0.07113580405712128, 0.10387486219406128], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:48,360 - utils - INFO - stage3_gradient_single_runtime: 0.006253957748413086
2023-09-28 23:26:48,364 - utils - INFO - 1, epoch: 1697, all client loss: [0.6311137676239014, 0.6308388113975525], all pred client disparities: [0.07113653421401978, 0.10387411713600159], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:48,426 - utils - INFO - stage3_gradient_single_runtime: 0.006108522415161133
2023-09-28 23:26:48,431 - utils - INFO - 1, epoch: 1698, all client loss: [0.6311136484146118, 0.6308388710021973], all pred client disparities: [0.07113726437091827, 0.10387343168258667], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:48,493 - utils - INFO - stage3_gradient_single_runtime: 0.0060939788818359375
2023-09-28 23:26:48,498 - utils - INFO - 1, epoch: 1699, all client loss: [0.6311136484146118, 0.6308388710021973], all pred client disparities: [0.07113800197839737, 0.10387271642684937], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:48,512 - utils - INFO - valid: True, epoch: 1699, loss: [0.6284713745117188, 0.6379747986793518], accuracy: [0.6367999911308289, 0.6450908780097961], mean_accuracy:0.6409454345703125,variance_accuracy:0.004145443439483643, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07055339217185974, 0.11673969030380249]
2023-09-28 23:26:48,523 - utils - INFO - global_valid: True, epoch: 1699,  global_loss: 0.6350050568580627, global_accuracy: 0.6958753501400561,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11359141767024994,
2023-09-28 23:26:48,653 - utils - INFO - stage3_gradient_single_runtime: 0.006092548370361328
2023-09-28 23:26:48,658 - utils - INFO - 1, epoch: 1700, all client loss: [0.6311135292053223, 0.6308389902114868], all pred client disparities: [0.07113871723413467, 0.10387200117111206], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:48,722 - utils - INFO - stage3_gradient_single_runtime: 0.006124734878540039
2023-09-28 23:26:48,727 - utils - INFO - 1, epoch: 1701, all client loss: [0.6311135292053223, 0.6308389902114868], all pred client disparities: [0.07113943994045258, 0.10387125611305237], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:48,785 - utils - INFO - stage3_gradient_single_runtime: 0.006182670593261719
2023-09-28 23:26:48,790 - utils - INFO - 1, epoch: 1702, all client loss: [0.6311134696006775, 0.6308390498161316], all pred client disparities: [0.07114015519618988, 0.10387057065963745], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:48,848 - utils - INFO - stage3_gradient_single_runtime: 0.006241321563720703
2023-09-28 23:26:48,853 - utils - INFO - 1, epoch: 1703, all client loss: [0.6311134696006775, 0.6308391690254211], all pred client disparities: [0.07114087045192719, 0.10386981815099716], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:48,911 - utils - INFO - stage3_gradient_single_runtime: 0.0071315765380859375
2023-09-28 23:26:48,916 - utils - INFO - 1, epoch: 1704, all client loss: [0.6311134696006775, 0.6308392286300659], all pred client disparities: [0.07114159315824509, 0.10386911034584045], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:48,976 - utils - INFO - stage3_gradient_single_runtime: 0.006284952163696289
2023-09-28 23:26:48,981 - utils - INFO - 1, epoch: 1705, all client loss: [0.6311133503913879, 0.6308392286300659], all pred client disparities: [0.0711423009634018, 0.10386845469474792], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:49,039 - utils - INFO - stage3_gradient_single_runtime: 0.006076812744140625
2023-09-28 23:26:49,044 - utils - INFO - 1, epoch: 1706, all client loss: [0.6311133503913879, 0.6308393478393555], all pred client disparities: [0.07114303857088089, 0.10386770963668823], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3137, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:49,103 - utils - INFO - stage3_gradient_single_runtime: 0.00713038444519043
2023-09-28 23:26:49,108 - utils - INFO - 1, epoch: 1707, all client loss: [0.6311132907867432, 0.6308394074440002], all pred client disparities: [0.0711437463760376, 0.10386699438095093], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:49,168 - utils - INFO - stage3_gradient_single_runtime: 0.006075859069824219
2023-09-28 23:26:49,173 - utils - INFO - 1, epoch: 1708, all client loss: [0.6311132311820984, 0.6308395266532898], all pred client disparities: [0.07114444673061371, 0.10386624932289124], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:49,234 - utils - INFO - stage3_gradient_single_runtime: 0.006242275238037109
2023-09-28 23:26:49,239 - utils - INFO - 1, epoch: 1709, all client loss: [0.6311132311820984, 0.6308395266532898], all pred client disparities: [0.07114515453577042, 0.10386556386947632], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:49,297 - utils - INFO - stage3_gradient_single_runtime: 0.00628972053527832
2023-09-28 23:26:49,302 - utils - INFO - 1, epoch: 1710, all client loss: [0.6311131715774536, 0.6308395862579346], all pred client disparities: [0.07114587724208832, 0.10386490821838379], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:49,362 - utils - INFO - stage3_gradient_single_runtime: 0.006118059158325195
2023-09-28 23:26:49,366 - utils - INFO - 1, epoch: 1711, all client loss: [0.6311131715774536, 0.6308396458625793], all pred client disparities: [0.07114658504724503, 0.10386419296264648], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:49,429 - utils - INFO - stage3_gradient_single_runtime: 0.006368398666381836
2023-09-28 23:26:49,435 - utils - INFO - 1, epoch: 1712, all client loss: [0.6311130523681641, 0.6308397650718689], all pred client disparities: [0.07114729285240173, 0.10386353731155396], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:49,538 - utils - INFO - stage3_gradient_single_runtime: 0.006314754486083984
2023-09-28 23:26:49,542 - utils - INFO - 1, epoch: 1713, all client loss: [0.6311130523681641, 0.6308397650718689], all pred client disparities: [0.07114800065755844, 0.10386279225349426], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:49,599 - utils - INFO - stage3_gradient_single_runtime: 0.006084442138671875
2023-09-28 23:26:49,602 - utils - INFO - 1, epoch: 1714, all client loss: [0.6311129331588745, 0.6308398246765137], all pred client disparities: [0.07114869356155396, 0.10386207699775696], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:49,662 - utils - INFO - stage3_gradient_single_runtime: 0.006304502487182617
2023-09-28 23:26:49,667 - utils - INFO - 1, epoch: 1715, all client loss: [0.6311129331588745, 0.6308399438858032], all pred client disparities: [0.07114938646554947, 0.10386145114898682], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:49,724 - utils - INFO - stage3_gradient_single_runtime: 0.006173372268676758
2023-09-28 23:26:49,729 - utils - INFO - 1, epoch: 1716, all client loss: [0.6311129331588745, 0.630840003490448], all pred client disparities: [0.07115008682012558, 0.10386070609092712], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:49,788 - utils - INFO - stage3_gradient_single_runtime: 0.006847858428955078
2023-09-28 23:26:49,794 - utils - INFO - 1, epoch: 1717, all client loss: [0.6311128735542297, 0.630840003490448], all pred client disparities: [0.07115078717470169, 0.10385999083518982], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:49,853 - utils - INFO - stage3_gradient_single_runtime: 0.006718158721923828
2023-09-28 23:26:49,858 - utils - INFO - 1, epoch: 1718, all client loss: [0.6311128735542297, 0.6308401226997375], all pred client disparities: [0.0711514800786972, 0.1038593053817749], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:49,916 - utils - INFO - stage3_gradient_single_runtime: 0.0062448978424072266
2023-09-28 23:26:49,921 - utils - INFO - 1, epoch: 1719, all client loss: [0.631112813949585, 0.6308401823043823], all pred client disparities: [0.07115218788385391, 0.10385861992835999], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:49,934 - utils - INFO - valid: True, epoch: 1719, loss: [0.6284715533256531, 0.637977123260498], accuracy: [0.6367999911308289, 0.6450908780097961], mean_accuracy:0.6409454345703125,variance_accuracy:0.004145443439483643, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07056775689125061, 0.11673003435134888]
2023-09-28 23:26:49,945 - utils - INFO - global_valid: True, epoch: 1719,  global_loss: 0.6350066065788269, global_accuracy: 0.6958663465386155,  global_disparity:0.12307125329971313, global_pred_disparity: 0.1135881096124649,
2023-09-28 23:26:50,006 - utils - INFO - stage3_gradient_single_runtime: 0.006293535232543945
2023-09-28 23:26:50,011 - utils - INFO - 1, epoch: 1720, all client loss: [0.6311127543449402, 0.6308401823043823], all pred client disparities: [0.07115287333726883, 0.10385793447494507], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:50,072 - utils - INFO - stage3_gradient_single_runtime: 0.006077289581298828
2023-09-28 23:26:50,077 - utils - INFO - 1, epoch: 1721, all client loss: [0.6311127543449402, 0.6308403015136719], all pred client disparities: [0.07115356624126434, 0.10385724902153015], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:50,139 - utils - INFO - stage3_gradient_single_runtime: 0.006367206573486328
2023-09-28 23:26:50,144 - utils - INFO - 1, epoch: 1722, all client loss: [0.6311126351356506, 0.6308403611183167], all pred client disparities: [0.07115425169467926, 0.10385653376579285], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:50,202 - utils - INFO - stage3_gradient_single_runtime: 0.006083488464355469
2023-09-28 23:26:50,206 - utils - INFO - 1, epoch: 1723, all client loss: [0.6311126351356506, 0.6308404207229614], all pred client disparities: [0.07115495204925537, 0.10385593771934509], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:50,266 - utils - INFO - stage3_gradient_single_runtime: 0.0062220096588134766
2023-09-28 23:26:50,271 - utils - INFO - 1, epoch: 1724, all client loss: [0.6311125755310059, 0.630840539932251], all pred client disparities: [0.07115563750267029, 0.10385525226593018], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:50,381 - utils - INFO - stage3_gradient_single_runtime: 0.0062983036041259766
2023-09-28 23:26:50,386 - utils - INFO - 1, epoch: 1725, all client loss: [0.6311125755310059, 0.630840539932251], all pred client disparities: [0.0711563229560852, 0.10385456681251526], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:50,443 - utils - INFO - stage3_gradient_single_runtime: 0.0061092376708984375
2023-09-28 23:26:50,448 - utils - INFO - 1, epoch: 1726, all client loss: [0.6311125159263611, 0.6308405995368958], all pred client disparities: [0.07115701586008072, 0.10385385155677795], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:50,512 - utils - INFO - stage3_gradient_single_runtime: 0.006145954132080078
2023-09-28 23:26:50,517 - utils - INFO - 1, epoch: 1727, all client loss: [0.6311124563217163, 0.6308407187461853], all pred client disparities: [0.07115770876407623, 0.10385316610336304], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:50,578 - utils - INFO - stage3_gradient_single_runtime: 0.006096839904785156
2023-09-28 23:26:50,583 - utils - INFO - 1, epoch: 1728, all client loss: [0.6311124563217163, 0.6308407187461853], all pred client disparities: [0.07115836441516876, 0.1038525402545929], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:50,643 - utils - INFO - stage3_gradient_single_runtime: 0.00622868537902832
2023-09-28 23:26:50,648 - utils - INFO - 1, epoch: 1729, all client loss: [0.6311123967170715, 0.6308408379554749], all pred client disparities: [0.07115904241800308, 0.10385185480117798], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:50,706 - utils - INFO - stage3_gradient_single_runtime: 0.0061991214752197266
2023-09-28 23:26:50,711 - utils - INFO - 1, epoch: 1730, all client loss: [0.6311123371124268, 0.6308408975601196], all pred client disparities: [0.0711597353219986, 0.10385113954544067], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:50,781 - utils - INFO - stage3_gradient_single_runtime: 0.006264209747314453
2023-09-28 23:26:50,785 - utils - INFO - 1, epoch: 1731, all client loss: [0.6311123371124268, 0.6308410167694092], all pred client disparities: [0.07116040587425232, 0.10385051369667053], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:50,848 - utils - INFO - stage3_gradient_single_runtime: 0.009115457534790039
2023-09-28 23:26:50,853 - utils - INFO - 1, epoch: 1732, all client loss: [0.631112277507782, 0.6308410167694092], all pred client disparities: [0.07116109877824783, 0.103849858045578], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:50,912 - utils - INFO - stage3_gradient_single_runtime: 0.006522655487060547
2023-09-28 23:26:50,917 - utils - INFO - 1, epoch: 1733, all client loss: [0.6311122179031372, 0.630841076374054], all pred client disparities: [0.07116176187992096, 0.10384917259216309], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:50,978 - utils - INFO - stage3_gradient_single_runtime: 0.0061664581298828125
2023-09-28 23:26:50,983 - utils - INFO - 1, epoch: 1734, all client loss: [0.6311121582984924, 0.6308411955833435], all pred client disparities: [0.07116243988275528, 0.10384851694107056], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:51,050 - utils - INFO - stage3_gradient_single_runtime: 0.0062983036041259766
2023-09-28 23:26:51,054 - utils - INFO - 1, epoch: 1735, all client loss: [0.6311121582984924, 0.6308411955833435], all pred client disparities: [0.07116309553384781, 0.10384783148765564], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:51,171 - utils - INFO - stage3_gradient_single_runtime: 0.0062961578369140625
2023-09-28 23:26:51,175 - utils - INFO - 1, epoch: 1736, all client loss: [0.6311120986938477, 0.6308412551879883], all pred client disparities: [0.07116375863552094, 0.10384714603424072], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4529, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:51,243 - utils - INFO - stage3_gradient_single_runtime: 0.0061798095703125
2023-09-28 23:26:51,247 - utils - INFO - 1, epoch: 1737, all client loss: [0.6311120390892029, 0.6308413743972778], all pred client disparities: [0.07116443663835526, 0.1038464605808258], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:51,309 - utils - INFO - stage3_gradient_single_runtime: 0.00686192512512207
2023-09-28 23:26:51,313 - utils - INFO - 1, epoch: 1738, all client loss: [0.6311119794845581, 0.6308414340019226], all pred client disparities: [0.07116510719060898, 0.10384586453437805], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:51,370 - utils - INFO - stage3_gradient_single_runtime: 0.0060367584228515625
2023-09-28 23:26:51,374 - utils - INFO - 1, epoch: 1739, all client loss: [0.6311119794845581, 0.6308414936065674], all pred client disparities: [0.0711657777428627, 0.10384517908096313], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:51,388 - utils - INFO - valid: True, epoch: 1739, loss: [0.6284717321395874, 0.63797926902771], accuracy: [0.6367999911308289, 0.6450908780097961], mean_accuracy:0.6409454345703125,variance_accuracy:0.004145443439483643, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07058153301477432, 0.11672088503837585]
2023-09-28 23:26:51,399 - utils - INFO - global_valid: True, epoch: 1739,  global_loss: 0.6350082159042358, global_accuracy: 0.6958633453381352,  global_disparity:0.12307125329971313, global_pred_disparity: 0.1135849803686142,
2023-09-28 23:26:51,470 - utils - INFO - stage3_gradient_single_runtime: 0.007084846496582031
2023-09-28 23:26:51,475 - utils - INFO - 1, epoch: 1740, all client loss: [0.6311119198799133, 0.6308415532112122], all pred client disparities: [0.07116645574569702, 0.103844553232193], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:51,533 - utils - INFO - stage3_gradient_single_runtime: 0.006342649459838867
2023-09-28 23:26:51,538 - utils - INFO - 1, epoch: 1741, all client loss: [0.6311118602752686, 0.6308415532112122], all pred client disparities: [0.07116710394620895, 0.10384389758110046], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:51,595 - utils - INFO - stage3_gradient_single_runtime: 0.006043434143066406
2023-09-28 23:26:51,600 - utils - INFO - 1, epoch: 1742, all client loss: [0.6311118602752686, 0.6308416128158569], all pred client disparities: [0.07116776704788208, 0.10384321212768555], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:51,659 - utils - INFO - stage3_gradient_single_runtime: 0.00627446174621582
2023-09-28 23:26:51,664 - utils - INFO - 1, epoch: 1743, all client loss: [0.6311118006706238, 0.6308417320251465], all pred client disparities: [0.07116842269897461, 0.1038425862789154], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:51,728 - utils - INFO - stage3_gradient_single_runtime: 0.006255626678466797
2023-09-28 23:26:51,733 - utils - INFO - 1, epoch: 1744, all client loss: [0.6311118006706238, 0.6308417916297913], all pred client disparities: [0.07116908580064774, 0.1038418710231781], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:51,791 - utils - INFO - stage3_gradient_single_runtime: 0.006253242492675781
2023-09-28 23:26:51,796 - utils - INFO - 1, epoch: 1745, all client loss: [0.6311118006706238, 0.6308419108390808], all pred client disparities: [0.07116973400115967, 0.10384127497673035], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:51,854 - utils - INFO - stage3_gradient_single_runtime: 0.006221294403076172
2023-09-28 23:26:51,859 - utils - INFO - 1, epoch: 1746, all client loss: [0.6311116814613342, 0.6308419108390808], all pred client disparities: [0.0711703971028328, 0.10384058952331543], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:51,921 - utils - INFO - stage3_gradient_single_runtime: 0.007448911666870117
2023-09-28 23:26:51,925 - utils - INFO - 1, epoch: 1747, all client loss: [0.6311116218566895, 0.6308419704437256], all pred client disparities: [0.07117106020450592, 0.10383996367454529], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:52,037 - utils - INFO - stage3_gradient_single_runtime: 0.006148576736450195
2023-09-28 23:26:52,041 - utils - INFO - 1, epoch: 1748, all client loss: [0.6311115622520447, 0.6308420896530151], all pred client disparities: [0.07117170095443726, 0.10383933782577515], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:52,101 - utils - INFO - stage3_gradient_single_runtime: 0.006192207336425781
2023-09-28 23:26:52,106 - utils - INFO - 1, epoch: 1749, all client loss: [0.6311115622520447, 0.6308421492576599], all pred client disparities: [0.07117234915494919, 0.10383868217468262], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:52,167 - utils - INFO - stage3_gradient_single_runtime: 0.0061872005462646484
2023-09-28 23:26:52,172 - utils - INFO - 1, epoch: 1750, all client loss: [0.6311115026473999, 0.6308421492576599], all pred client disparities: [0.07117300480604172, 0.10383802652359009], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:52,230 - utils - INFO - stage3_gradient_single_runtime: 0.00618743896484375
2023-09-28 23:26:52,235 - utils - INFO - 1, epoch: 1751, all client loss: [0.6311115026473999, 0.6308422684669495], all pred client disparities: [0.07117365300655365, 0.10383743047714233], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:52,292 - utils - INFO - stage3_gradient_single_runtime: 0.006195545196533203
2023-09-28 23:26:52,297 - utils - INFO - 1, epoch: 1752, all client loss: [0.6311114430427551, 0.6308423280715942], all pred client disparities: [0.07117430120706558, 0.1038367748260498], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:52,356 - utils - INFO - stage3_gradient_single_runtime: 0.0066356658935546875
2023-09-28 23:26:52,362 - utils - INFO - 1, epoch: 1753, all client loss: [0.6311113834381104, 0.630842387676239], all pred client disparities: [0.07117495685815811, 0.10383611917495728], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:52,423 - utils - INFO - stage3_gradient_single_runtime: 0.0062487125396728516
2023-09-28 23:26:52,428 - utils - INFO - 1, epoch: 1754, all client loss: [0.6311113834381104, 0.630842387676239], all pred client disparities: [0.07117560505867004, 0.10383546352386475], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:52,486 - utils - INFO - stage3_gradient_single_runtime: 0.0061283111572265625
2023-09-28 23:26:52,491 - utils - INFO - 1, epoch: 1755, all client loss: [0.6311113238334656, 0.6308425068855286], all pred client disparities: [0.07117623835802078, 0.10383486747741699], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6689605712890625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:52,549 - utils - INFO - stage3_gradient_single_runtime: 0.006110429763793945
2023-09-28 23:26:52,554 - utils - INFO - 1, epoch: 1756, all client loss: [0.6311112642288208, 0.6308425664901733], all pred client disparities: [0.07117687165737152, 0.10383424162864685], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:52,614 - utils - INFO - stage3_gradient_single_runtime: 0.006085872650146484
2023-09-28 23:26:52,618 - utils - INFO - 1, epoch: 1757, all client loss: [0.6311112642288208, 0.6308425664901733], all pred client disparities: [0.07117752730846405, 0.10383358597755432], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:52,678 - utils - INFO - stage3_gradient_single_runtime: 0.006224632263183594
2023-09-28 23:26:52,683 - utils - INFO - 1, epoch: 1758, all client loss: [0.631111204624176, 0.6308426856994629], all pred client disparities: [0.07117816060781479, 0.10383296012878418], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:52,740 - utils - INFO - stage3_gradient_single_runtime: 0.006229877471923828
2023-09-28 23:26:52,745 - utils - INFO - 1, epoch: 1759, all client loss: [0.631111204624176, 0.6308427453041077], all pred client disparities: [0.07117880135774612, 0.10383233428001404], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:52,759 - utils - INFO - valid: True, epoch: 1759, loss: [0.628471851348877, 0.6379815340042114], accuracy: [0.6367999911308289, 0.6450908780097961], mean_accuracy:0.6409454345703125,variance_accuracy:0.004145443439483643, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07059469819068909, 0.11671209335327148]
2023-09-28 23:26:52,770 - utils - INFO - global_valid: True, epoch: 1759,  global_loss: 0.6350098252296448, global_accuracy: 0.6958553421368547,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11358191072940826,
2023-09-28 23:26:52,875 - utils - INFO - stage3_gradient_single_runtime: 0.006256103515625
2023-09-28 23:26:52,879 - utils - INFO - 1, epoch: 1760, all client loss: [0.6311110854148865, 0.6308428049087524], all pred client disparities: [0.07117943465709686, 0.10383167862892151], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:52,935 - utils - INFO - stage3_gradient_single_runtime: 0.0066487789154052734
2023-09-28 23:26:52,939 - utils - INFO - 1, epoch: 1761, all client loss: [0.6311110854148865, 0.6308428645133972], all pred client disparities: [0.0711800828576088, 0.10383105278015137], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:52,995 - utils - INFO - stage3_gradient_single_runtime: 0.006171464920043945
2023-09-28 23:26:52,999 - utils - INFO - 1, epoch: 1762, all client loss: [0.6311110258102417, 0.630842924118042], all pred client disparities: [0.07118072360754013, 0.10383045673370361], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:53,064 - utils - INFO - stage3_gradient_single_runtime: 0.006193876266479492
2023-09-28 23:26:53,069 - utils - INFO - 1, epoch: 1763, all client loss: [0.6311109662055969, 0.6308430433273315], all pred client disparities: [0.07118134945631027, 0.10382980108261108], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:53,126 - utils - INFO - stage3_gradient_single_runtime: 0.00629115104675293
2023-09-28 23:26:53,128 - utils - INFO - 1, epoch: 1764, all client loss: [0.6311109662055969, 0.6308431029319763], all pred client disparities: [0.07118197530508041, 0.10382917523384094], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:53,180 - utils - INFO - stage3_gradient_single_runtime: 0.00615239143371582
2023-09-28 23:26:53,183 - utils - INFO - 1, epoch: 1765, all client loss: [0.6311109662055969, 0.6308431625366211], all pred client disparities: [0.07118260860443115, 0.10382851958274841], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:53,236 - utils - INFO - stage3_gradient_single_runtime: 0.006177663803100586
2023-09-28 23:26:53,242 - utils - INFO - 1, epoch: 1766, all client loss: [0.6311109066009521, 0.6308432221412659], all pred client disparities: [0.0711832344532013, 0.10382795333862305], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:53,300 - utils - INFO - stage3_gradient_single_runtime: 0.006027936935424805
2023-09-28 23:26:53,305 - utils - INFO - 1, epoch: 1767, all client loss: [0.6311107873916626, 0.6308432817459106], all pred client disparities: [0.07118386030197144, 0.10382726788520813], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:53,363 - utils - INFO - stage3_gradient_single_runtime: 0.006216287612915039
2023-09-28 23:26:53,368 - utils - INFO - 1, epoch: 1768, all client loss: [0.6311108469963074, 0.6308433413505554], all pred client disparities: [0.07118448615074158, 0.10382664203643799], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:53,427 - utils - INFO - stage3_gradient_single_runtime: 0.006419181823730469
2023-09-28 23:26:53,433 - utils - INFO - 1, epoch: 1769, all client loss: [0.6311107277870178, 0.6308434009552002], all pred client disparities: [0.07118511945009232, 0.10382607579231262], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
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2023-09-28 23:26:53,492 - utils - INFO - stage3_gradient_single_runtime: 0.006102085113525391
2023-09-28 23:26:53,498 - utils - INFO - 1, epoch: 1770, all client loss: [0.631110668182373, 0.630843460559845], all pred client disparities: [0.07118575274944305, 0.10382547974586487], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:53,559 - utils - INFO - stage3_gradient_single_runtime: 0.0062711238861083984
2023-09-28 23:26:53,563 - utils - INFO - 1, epoch: 1771, all client loss: [0.631110668182373, 0.6308435201644897], all pred client disparities: [0.0711863711476326, 0.10382485389709473], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:53,620 - utils - INFO - stage3_gradient_single_runtime: 0.006117105484008789
2023-09-28 23:26:53,624 - utils - INFO - 1, epoch: 1772, all client loss: [0.631110668182373, 0.6308436393737793], all pred client disparities: [0.07118698209524155, 0.10382422804832458], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:53,731 - utils - INFO - stage3_gradient_single_runtime: 0.0060939788818359375
2023-09-28 23:26:53,734 - utils - INFO - 1, epoch: 1773, all client loss: [0.6311106085777283, 0.6308436393737793], all pred client disparities: [0.07118760049343109, 0.10382366180419922], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:53,797 - utils - INFO - stage3_gradient_single_runtime: 0.006449460983276367
2023-09-28 23:26:53,802 - utils - INFO - 1, epoch: 1774, all client loss: [0.6311105489730835, 0.6308437585830688], all pred client disparities: [0.07118821889162064, 0.10382303595542908], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:53,861 - utils - INFO - stage3_gradient_single_runtime: 0.006110191345214844
2023-09-28 23:26:53,866 - utils - INFO - 1, epoch: 1775, all client loss: [0.6311104893684387, 0.6308437585830688], all pred client disparities: [0.07118882983922958, 0.10382241010665894], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:53,923 - utils - INFO - stage3_gradient_single_runtime: 0.006235361099243164
2023-09-28 23:26:53,929 - utils - INFO - 1, epoch: 1776, all client loss: [0.6311104893684387, 0.6308438181877136], all pred client disparities: [0.07118944823741913, 0.1038217842578888], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:53,994 - utils - INFO - stage3_gradient_single_runtime: 0.006705760955810547
2023-09-28 23:26:53,999 - utils - INFO - 1, epoch: 1777, all client loss: [0.631110429763794, 0.6308439373970032], all pred client disparities: [0.07119008153676987, 0.10382118821144104], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:54,058 - utils - INFO - stage3_gradient_single_runtime: 0.006190299987792969
2023-09-28 23:26:54,063 - utils - INFO - 1, epoch: 1778, all client loss: [0.6311103701591492, 0.630843997001648], all pred client disparities: [0.07119067758321762, 0.10382059216499329], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:54,120 - utils - INFO - stage3_gradient_single_runtime: 0.006237030029296875
2023-09-28 23:26:54,125 - utils - INFO - 1, epoch: 1779, all client loss: [0.6311103701591492, 0.6308440566062927], all pred client disparities: [0.07119128853082657, 0.10381996631622314], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:54,139 - utils - INFO - valid: True, epoch: 1779, loss: [0.6284719705581665, 0.6379836201667786], accuracy: [0.6367999911308289, 0.6450908780097961], mean_accuracy:0.6409454345703125,variance_accuracy:0.004145443439483643, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07060732692480087, 0.11670368909835815]
2023-09-28 23:26:54,150 - utils - INFO - global_valid: True, epoch: 1779,  global_loss: 0.6350112557411194, global_accuracy: 0.6958513405362146,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11357904970645905,
2023-09-28 23:26:54,211 - utils - INFO - stage3_gradient_single_runtime: 0.006159543991088867
2023-09-28 23:26:54,216 - utils - INFO - 1, epoch: 1780, all client loss: [0.6311103105545044, 0.6308441162109375], all pred client disparities: [0.07119189202785492, 0.10381940007209778], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:54,274 - utils - INFO - stage3_gradient_single_runtime: 0.006268978118896484
2023-09-28 23:26:54,279 - utils - INFO - 1, epoch: 1781, all client loss: [0.6311103105545044, 0.6308441758155823], all pred client disparities: [0.07119251042604446, 0.10381877422332764], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:54,341 - utils - INFO - stage3_gradient_single_runtime: 0.0070688724517822266
2023-09-28 23:26:54,347 - utils - INFO - 1, epoch: 1782, all client loss: [0.6311102509498596, 0.6308442950248718], all pred client disparities: [0.07119311392307281, 0.10381820797920227], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:54,408 - utils - INFO - stage3_gradient_single_runtime: 0.006422996520996094
2023-09-28 23:26:54,413 - utils - INFO - 1, epoch: 1783, all client loss: [0.6311101913452148, 0.6308442950248718], all pred client disparities: [0.07119372487068176, 0.10381758213043213], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:54,534 - utils - INFO - stage3_gradient_single_runtime: 0.006106138229370117
2023-09-28 23:26:54,539 - utils - INFO - 1, epoch: 1784, all client loss: [0.6311101913452148, 0.6308443546295166], all pred client disparities: [0.07119433581829071, 0.10381698608398438], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:54,597 - utils - INFO - stage3_gradient_single_runtime: 0.006225109100341797
2023-09-28 23:26:54,602 - utils - INFO - 1, epoch: 1785, all client loss: [0.6311100721359253, 0.6308444738388062], all pred client disparities: [0.07119495421648026, 0.10381639003753662], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:54,667 - utils - INFO - stage3_gradient_single_runtime: 0.006073474884033203
2023-09-28 23:26:54,672 - utils - INFO - 1, epoch: 1786, all client loss: [0.6311100721359253, 0.6308444738388062], all pred client disparities: [0.0711955577135086, 0.10381579399108887], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:54,730 - utils - INFO - stage3_gradient_single_runtime: 0.006278514862060547
2023-09-28 23:26:54,735 - utils - INFO - 1, epoch: 1787, all client loss: [0.6311100721359253, 0.6308445334434509], all pred client disparities: [0.07119613885879517, 0.10381516814231873], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:54,793 - utils - INFO - stage3_gradient_single_runtime: 0.006014823913574219
2023-09-28 23:26:54,798 - utils - INFO - 1, epoch: 1788, all client loss: [0.6311100125312805, 0.6308446526527405], all pred client disparities: [0.07119674980640411, 0.10381460189819336], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:54,859 - utils - INFO - stage3_gradient_single_runtime: 0.006380558013916016
2023-09-28 23:26:54,864 - utils - INFO - 1, epoch: 1789, all client loss: [0.6311099529266357, 0.6308446526527405], all pred client disparities: [0.07119734585285187, 0.103814035654068], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:54,945 - utils - INFO - stage3_gradient_single_runtime: 0.006514310836791992
2023-09-28 23:26:54,950 - utils - INFO - 1, epoch: 1790, all client loss: [0.631109893321991, 0.63084477186203], all pred client disparities: [0.07119794189929962, 0.10381343960762024], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:55,009 - utils - INFO - stage3_gradient_single_runtime: 0.0061969757080078125
2023-09-28 23:26:55,014 - utils - INFO - 1, epoch: 1791, all client loss: [0.631109893321991, 0.6308448314666748], all pred client disparities: [0.07119854539632797, 0.1038128137588501], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:55,071 - utils - INFO - stage3_gradient_single_runtime: 0.0061872005462646484
2023-09-28 23:26:55,076 - utils - INFO - 1, epoch: 1792, all client loss: [0.6311098337173462, 0.6308448910713196], all pred client disparities: [0.07119914144277573, 0.10381221771240234], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:55,136 - utils - INFO - stage3_gradient_single_runtime: 0.006050825119018555
2023-09-28 23:26:55,142 - utils - INFO - 1, epoch: 1793, all client loss: [0.6311097741127014, 0.6308448910713196], all pred client disparities: [0.07119973748922348, 0.10381165146827698], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:55,197 - utils - INFO - stage3_gradient_single_runtime: 0.006070137023925781
2023-09-28 23:26:55,202 - utils - INFO - 1, epoch: 1794, all client loss: [0.6311097741127014, 0.6308450102806091], all pred client disparities: [0.07120032608509064, 0.10381108522415161], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:55,259 - utils - INFO - stage3_gradient_single_runtime: 0.006159067153930664
2023-09-28 23:26:55,263 - utils - INFO - 1, epoch: 1795, all client loss: [0.6311097145080566, 0.6308450698852539], all pred client disparities: [0.0712009146809578, 0.10381048917770386], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:55,320 - utils - INFO - stage3_gradient_single_runtime: 0.006222248077392578
2023-09-28 23:26:55,325 - utils - INFO - 1, epoch: 1796, all client loss: [0.6311097145080566, 0.6308451294898987], all pred client disparities: [0.07120149582624435, 0.1038098931312561], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:55,441 - utils - INFO - stage3_gradient_single_runtime: 0.00616908073425293
2023-09-28 23:26:55,446 - utils - INFO - 1, epoch: 1797, all client loss: [0.6311096549034119, 0.6308451890945435], all pred client disparities: [0.07120208442211151, 0.10380935668945312], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:55,505 - utils - INFO - stage3_gradient_single_runtime: 0.006247997283935547
2023-09-28 23:26:55,510 - utils - INFO - 1, epoch: 1798, all client loss: [0.6311095952987671, 0.6308452486991882], all pred client disparities: [0.07120267301797867, 0.10380873084068298], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:55,569 - utils - INFO - stage3_gradient_single_runtime: 0.006983280181884766
2023-09-28 23:26:55,574 - utils - INFO - 1, epoch: 1799, all client loss: [0.6311095952987671, 0.630845308303833], all pred client disparities: [0.07120326906442642, 0.10380816459655762], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:55,589 - utils - INFO - valid: True, epoch: 1799, loss: [0.6284719705581665, 0.6379857063293457], accuracy: [0.6367999911308289, 0.6450908780097961], mean_accuracy:0.6409454345703125,variance_accuracy:0.004145443439483643, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07061944901943207, 0.11669552326202393]
2023-09-28 23:26:55,605 - utils - INFO - global_valid: True, epoch: 1799,  global_loss: 0.6350127458572388, global_accuracy: 0.6958463385354141,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11357620358467102,
2023-09-28 23:26:55,659 - utils - INFO - stage3_gradient_single_runtime: 0.006072282791137695
2023-09-28 23:26:55,663 - utils - INFO - 1, epoch: 1800, all client loss: [0.6311095356941223, 0.6308453679084778], all pred client disparities: [0.07120385020971298, 0.10380756855010986], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:55,719 - utils - INFO - stage3_gradient_single_runtime: 0.00629878044128418
2023-09-28 23:26:55,723 - utils - INFO - 1, epoch: 1801, all client loss: [0.6311094760894775, 0.6308454275131226], all pred client disparities: [0.07120443880558014, 0.1038070023059845], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:55,779 - utils - INFO - stage3_gradient_single_runtime: 0.0062944889068603516
2023-09-28 23:26:55,783 - utils - INFO - 1, epoch: 1802, all client loss: [0.6311094164848328, 0.6308454871177673], all pred client disparities: [0.0712050199508667, 0.10380643606185913], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:55,846 - utils - INFO - stage3_gradient_single_runtime: 0.00722813606262207
2023-09-28 23:26:55,851 - utils - INFO - 1, epoch: 1803, all client loss: [0.6311094164848328, 0.6308456063270569], all pred client disparities: [0.07120560109615326, 0.10380584001541138], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:55,909 - utils - INFO - stage3_gradient_single_runtime: 0.005980730056762695
2023-09-28 23:26:55,913 - utils - INFO - 1, epoch: 1804, all client loss: [0.6311094164848328, 0.6308456659317017], all pred client disparities: [0.07120616734027863, 0.10380527377128601], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:55,970 - utils - INFO - stage3_gradient_single_runtime: 0.0062732696533203125
2023-09-28 23:26:55,975 - utils - INFO - 1, epoch: 1805, all client loss: [0.631109356880188, 0.6308457255363464], all pred client disparities: [0.07120674848556519, 0.10380470752716064], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:56,032 - utils - INFO - stage3_gradient_single_runtime: 0.006249904632568359
2023-09-28 23:26:56,036 - utils - INFO - 1, epoch: 1806, all client loss: [0.6311092972755432, 0.6308457851409912], all pred client disparities: [0.07120733708143234, 0.10380414128303528], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:56,100 - utils - INFO - stage3_gradient_single_runtime: 0.006079912185668945
2023-09-28 23:26:56,105 - utils - INFO - 1, epoch: 1807, all client loss: [0.6311092376708984, 0.630845844745636], all pred client disparities: [0.0712079107761383, 0.10380357503890991], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:56,161 - utils - INFO - stage3_gradient_single_runtime: 0.00622248649597168
2023-09-28 23:26:56,166 - utils - INFO - 1, epoch: 1808, all client loss: [0.6311092376708984, 0.6308459043502808], all pred client disparities: [0.07120849192142487, 0.10380300879478455], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:56,224 - utils - INFO - stage3_gradient_single_runtime: 0.006184101104736328
2023-09-28 23:26:56,229 - utils - INFO - 1, epoch: 1809, all client loss: [0.6311091780662537, 0.6308459639549255], all pred client disparities: [0.07120907306671143, 0.10380241274833679], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:56,336 - utils - INFO - stage3_gradient_single_runtime: 0.0060884952545166016
2023-09-28 23:26:56,339 - utils - INFO - 1, epoch: 1810, all client loss: [0.6311091184616089, 0.6308460235595703], all pred client disparities: [0.07120965421199799, 0.10380184650421143], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:56,392 - utils - INFO - stage3_gradient_single_runtime: 0.006160259246826172
2023-09-28 23:26:56,395 - utils - INFO - 1, epoch: 1811, all client loss: [0.6311090588569641, 0.6308461427688599], all pred client disparities: [0.07121022045612335, 0.10380128026008606], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:56,453 - utils - INFO - stage3_gradient_single_runtime: 0.006143331527709961
2023-09-28 23:26:56,458 - utils - INFO - 1, epoch: 1812, all client loss: [0.6311089992523193, 0.6308461427688599], all pred client disparities: [0.07121077924966812, 0.10380074381828308], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:56,517 - utils - INFO - stage3_gradient_single_runtime: 0.007472991943359375
2023-09-28 23:26:56,528 - utils - INFO - 1, epoch: 1813, all client loss: [0.6311089992523193, 0.6308462023735046], all pred client disparities: [0.07121134549379349, 0.10380017757415771], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:56,589 - utils - INFO - stage3_gradient_single_runtime: 0.006013154983520508
2023-09-28 23:26:56,594 - utils - INFO - 1, epoch: 1814, all client loss: [0.6311089992523193, 0.6308463215827942], all pred client disparities: [0.07121191918849945, 0.10379961133003235], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:56,652 - utils - INFO - stage3_gradient_single_runtime: 0.006257534027099609
2023-09-28 23:26:56,657 - utils - INFO - 1, epoch: 1815, all client loss: [0.6311089396476746, 0.6308463215827942], all pred client disparities: [0.07121248543262482, 0.1037990152835846], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:56,714 - utils - INFO - stage3_gradient_single_runtime: 0.00628352165222168
2023-09-28 23:26:56,720 - utils - INFO - 1, epoch: 1816, all client loss: [0.6311089396476746, 0.6308464407920837], all pred client disparities: [0.07121305167675018, 0.10379847884178162], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:56,785 - utils - INFO - stage3_gradient_single_runtime: 0.0073871612548828125
2023-09-28 23:26:56,791 - utils - INFO - 1, epoch: 1817, all client loss: [0.6311088800430298, 0.6308465003967285], all pred client disparities: [0.07121362537145615, 0.10379788279533386], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:56,849 - utils - INFO - stage3_gradient_single_runtime: 0.005963325500488281
2023-09-28 23:26:56,853 - utils - INFO - 1, epoch: 1818, all client loss: [0.631108820438385, 0.6308465003967285], all pred client disparities: [0.07121419161558151, 0.10379737615585327], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3138, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:56,909 - utils - INFO - stage3_gradient_single_runtime: 0.006257057189941406
2023-09-28 23:26:56,914 - utils - INFO - 1, epoch: 1819, all client loss: [0.6311087608337402, 0.6308466792106628], all pred client disparities: [0.07121476531028748, 0.1037968099117279], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:56,928 - utils - INFO - valid: True, epoch: 1819, loss: [0.6284720301628113, 0.6379876732826233], accuracy: [0.6367999911308289, 0.6450908780097961], mean_accuracy:0.6409454345703125,variance_accuracy:0.004145443439483643, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07063107192516327, 0.11668771505355835]
2023-09-28 23:26:56,939 - utils - INFO - global_valid: True, epoch: 1819,  global_loss: 0.6350140571594238, global_accuracy: 0.6958383353341336,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11357350647449493,
2023-09-28 23:26:56,996 - utils - INFO - stage3_gradient_single_runtime: 0.007685184478759766
2023-09-28 23:26:57,001 - utils - INFO - 1, epoch: 1820, all client loss: [0.6311087012290955, 0.6308466792106628], all pred client disparities: [0.07121532410383224, 0.10379627346992493], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:57,062 - utils - INFO - stage3_gradient_single_runtime: 0.006036520004272461
2023-09-28 23:26:57,065 - utils - INFO - 1, epoch: 1821, all client loss: [0.6311087012290955, 0.6308467388153076], all pred client disparities: [0.07121588289737701, 0.10379573702812195], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:57,164 - utils - INFO - stage3_gradient_single_runtime: 0.006283998489379883
2023-09-28 23:26:57,167 - utils - INFO - 1, epoch: 1822, all client loss: [0.6311086416244507, 0.6308468580245972], all pred client disparities: [0.07121644169092178, 0.1037951111793518], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:57,223 - utils - INFO - stage3_gradient_single_runtime: 0.007412433624267578
2023-09-28 23:26:57,228 - utils - INFO - 1, epoch: 1823, all client loss: [0.6311086416244507, 0.6308468580245972], all pred client disparities: [0.07121700048446655, 0.10379460453987122], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:57,292 - utils - INFO - stage3_gradient_single_runtime: 0.0071904659271240234
2023-09-28 23:26:57,296 - utils - INFO - 1, epoch: 1824, all client loss: [0.6311086416244507, 0.6308469176292419], all pred client disparities: [0.07121756672859192, 0.10379403829574585], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:57,352 - utils - INFO - stage3_gradient_single_runtime: 0.0062029361724853516
2023-09-28 23:26:57,357 - utils - INFO - 1, epoch: 1825, all client loss: [0.6311085224151611, 0.6308470368385315], all pred client disparities: [0.07121812552213669, 0.10379347205162048], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:57,414 - utils - INFO - stage3_gradient_single_runtime: 0.0062639713287353516
2023-09-28 23:26:57,418 - utils - INFO - 1, epoch: 1826, all client loss: [0.6311085224151611, 0.6308470368385315], all pred client disparities: [0.07121867686510086, 0.1037929356098175], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:57,480 - utils - INFO - stage3_gradient_single_runtime: 0.0061719417572021484
2023-09-28 23:26:57,485 - utils - INFO - 1, epoch: 1827, all client loss: [0.6311084032058716, 0.6308470964431763], all pred client disparities: [0.07121924310922623, 0.10379242897033691], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:57,545 - utils - INFO - stage3_gradient_single_runtime: 0.0060482025146484375
2023-09-28 23:26:57,549 - utils - INFO - 1, epoch: 1828, all client loss: [0.6311084032058716, 0.6308472156524658], all pred client disparities: [0.0712197944521904, 0.10379183292388916], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:57,604 - utils - INFO - stage3_gradient_single_runtime: 0.006119728088378906
2023-09-28 23:26:57,608 - utils - INFO - 1, epoch: 1829, all client loss: [0.6311084032058716, 0.6308472752571106], all pred client disparities: [0.07122035324573517, 0.1037912666797638], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:57,666 - utils - INFO - stage3_gradient_single_runtime: 0.007718086242675781
2023-09-28 23:26:57,672 - utils - INFO - 1, epoch: 1830, all client loss: [0.6311084032058716, 0.6308473348617554], all pred client disparities: [0.07122089713811874, 0.1037907600402832], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:57,734 - utils - INFO - stage3_gradient_single_runtime: 0.006239652633666992
2023-09-28 23:26:57,738 - utils - INFO - 1, epoch: 1831, all client loss: [0.6311083436012268, 0.6308473944664001], all pred client disparities: [0.07122144103050232, 0.10379022359848022], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:57,796 - utils - INFO - stage3_gradient_single_runtime: 0.006005048751831055
2023-09-28 23:26:57,800 - utils - INFO - 1, epoch: 1832, all client loss: [0.631108283996582, 0.6308474540710449], all pred client disparities: [0.07122199982404709, 0.10378971695899963], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:57,914 - utils - INFO - stage3_gradient_single_runtime: 0.00726771354675293
2023-09-28 23:26:57,920 - utils - INFO - 1, epoch: 1833, all client loss: [0.631108283996582, 0.6308475136756897], all pred client disparities: [0.07122254371643066, 0.10378912091255188], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:57,982 - utils - INFO - stage3_gradient_single_runtime: 0.006826877593994141
2023-09-28 23:26:57,987 - utils - INFO - 1, epoch: 1834, all client loss: [0.6311082243919373, 0.6308475732803345], all pred client disparities: [0.07122309505939484, 0.10378855466842651], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:58,043 - utils - INFO - stage3_gradient_single_runtime: 0.0059490203857421875
2023-09-28 23:26:58,047 - utils - INFO - 1, epoch: 1835, all client loss: [0.6311081051826477, 0.6308476328849792], all pred client disparities: [0.07122363150119781, 0.10378801822662354], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:58,105 - utils - INFO - stage3_gradient_single_runtime: 0.007086992263793945
2023-09-28 23:26:58,111 - utils - INFO - 1, epoch: 1836, all client loss: [0.6311081051826477, 0.630847692489624], all pred client disparities: [0.07122419029474258, 0.10378751158714294], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:58,172 - utils - INFO - stage3_gradient_single_runtime: 0.006177663803100586
2023-09-28 23:26:58,177 - utils - INFO - 1, epoch: 1837, all client loss: [0.6311080455780029, 0.6308477520942688], all pred client disparities: [0.07122474908828735, 0.10378691554069519], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:58,237 - utils - INFO - stage3_gradient_single_runtime: 0.00599360466003418
2023-09-28 23:26:58,242 - utils - INFO - 1, epoch: 1838, all client loss: [0.6311080455780029, 0.6308478116989136], all pred client disparities: [0.07122528553009033, 0.1037864089012146], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:58,297 - utils - INFO - stage3_gradient_single_runtime: 0.006002664566040039
2023-09-28 23:26:58,302 - utils - INFO - 1, epoch: 1839, all client loss: [0.6311080455780029, 0.6308478713035583], all pred client disparities: [0.07122582197189331, 0.10378590226173401], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:58,316 - utils - INFO - valid: True, epoch: 1839, loss: [0.6284720301628113, 0.6379895806312561], accuracy: [0.6367999911308289, 0.6450908780097961], mean_accuracy:0.6409454345703125,variance_accuracy:0.004145443439483643, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07064227014780045, 0.11668023467063904]
2023-09-28 23:26:58,328 - utils - INFO - global_valid: True, epoch: 1839,  global_loss: 0.6350154280662537, global_accuracy: 0.6958313325330132,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11357088387012482,
2023-09-28 23:26:58,395 - utils - INFO - stage3_gradient_single_runtime: 0.008179903030395508
2023-09-28 23:26:58,400 - utils - INFO - 1, epoch: 1840, all client loss: [0.6311079263687134, 0.6308479905128479], all pred client disparities: [0.0712263435125351, 0.10378536581993103], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:58,458 - utils - INFO - stage3_gradient_single_runtime: 0.006259441375732422
2023-09-28 23:26:58,463 - utils - INFO - 1, epoch: 1841, all client loss: [0.6311079263687134, 0.6308480501174927], all pred client disparities: [0.07122690230607986, 0.10378482937812805], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:58,521 - utils - INFO - stage3_gradient_single_runtime: 0.006142854690551758
2023-09-28 23:26:58,526 - utils - INFO - 1, epoch: 1842, all client loss: [0.6311078667640686, 0.6308480501174927], all pred client disparities: [0.07122743129730225, 0.10378432273864746], all client disparities: [0.060876332223415375, 0.11143064498901367], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:58,587 - utils - INFO - stage3_gradient_single_runtime: 0.0061855316162109375
2023-09-28 23:26:58,593 - utils - INFO - 1, epoch: 1843, all client loss: [0.6311078071594238, 0.6308481693267822], all pred client disparities: [0.07122797518968582, 0.10378381609916687], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:58,650 - utils - INFO - stage3_gradient_single_runtime: 0.006066560745239258
2023-09-28 23:26:58,655 - utils - INFO - 1, epoch: 1844, all client loss: [0.6311078071594238, 0.630848228931427], all pred client disparities: [0.0712285041809082, 0.1037832498550415], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:58,776 - utils - INFO - stage3_gradient_single_runtime: 0.007450103759765625
2023-09-28 23:26:58,782 - utils - INFO - 1, epoch: 1845, all client loss: [0.6311078071594238, 0.6308482885360718], all pred client disparities: [0.07122905552387238, 0.10378271341323853], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:58,837 - utils - INFO - stage3_gradient_single_runtime: 0.00611114501953125
2023-09-28 23:26:58,839 - utils - INFO - 1, epoch: 1846, all client loss: [0.631107747554779, 0.6308483481407166], all pred client disparities: [0.07122959941625595, 0.10378223657608032], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:58,890 - utils - INFO - stage3_gradient_single_runtime: 0.0061626434326171875
2023-09-28 23:26:58,893 - utils - INFO - 1, epoch: 1847, all client loss: [0.631107747554779, 0.6308484077453613], all pred client disparities: [0.07123012840747833, 0.10378167033195496], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:58,945 - utils - INFO - stage3_gradient_single_runtime: 0.006159782409667969
2023-09-28 23:26:58,947 - utils - INFO - 1, epoch: 1848, all client loss: [0.6311076283454895, 0.6308484673500061], all pred client disparities: [0.07123065739870071, 0.10378113389015198], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:59,001 - utils - INFO - stage3_gradient_single_runtime: 0.007551431655883789
2023-09-28 23:26:59,007 - utils - INFO - 1, epoch: 1849, all client loss: [0.6311076283454895, 0.6308485269546509], all pred client disparities: [0.0712311789393425, 0.10378062725067139], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:59,063 - utils - INFO - stage3_gradient_single_runtime: 0.006098508834838867
2023-09-28 23:26:59,065 - utils - INFO - 1, epoch: 1850, all client loss: [0.6311075091362, 0.6308485865592957], all pred client disparities: [0.07123170793056488, 0.10378009080886841], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:59,116 - utils - INFO - stage3_gradient_single_runtime: 0.006129026412963867
2023-09-28 23:26:59,118 - utils - INFO - 1, epoch: 1851, all client loss: [0.6311075091362, 0.6308487057685852], all pred client disparities: [0.07123224437236786, 0.10377958416938782], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:59,171 - utils - INFO - stage3_gradient_single_runtime: 0.006183624267578125
2023-09-28 23:26:59,173 - utils - INFO - 1, epoch: 1852, all client loss: [0.6311075091362, 0.63084876537323], all pred client disparities: [0.07123277336359024, 0.10377901792526245], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:59,225 - utils - INFO - stage3_gradient_single_runtime: 0.006638765335083008
2023-09-28 23:26:59,231 - utils - INFO - 1, epoch: 1853, all client loss: [0.6311074495315552, 0.63084876537323], all pred client disparities: [0.07123330235481262, 0.10377854108810425], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:59,289 - utils - INFO - stage3_gradient_single_runtime: 0.006090402603149414
2023-09-28 23:26:59,292 - utils - INFO - 1, epoch: 1854, all client loss: [0.6311074495315552, 0.6308488845825195], all pred client disparities: [0.0712338238954544, 0.10377800464630127], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:59,345 - utils - INFO - stage3_gradient_single_runtime: 0.0061833858489990234
2023-09-28 23:26:59,348 - utils - INFO - 1, epoch: 1855, all client loss: [0.6311073899269104, 0.6308489441871643], all pred client disparities: [0.07123435288667679, 0.10377749800682068], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:59,400 - utils - INFO - stage3_gradient_single_runtime: 0.0061376094818115234
2023-09-28 23:26:59,402 - utils - INFO - 1, epoch: 1856, all client loss: [0.6311073303222656, 0.6308489441871643], all pred client disparities: [0.07123488932847977, 0.10377699136734009], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:59,455 - utils - INFO - stage3_gradient_single_runtime: 0.007449626922607422
2023-09-28 23:26:59,461 - utils - INFO - 1, epoch: 1857, all client loss: [0.6311073303222656, 0.6308490633964539], all pred client disparities: [0.07123541831970215, 0.10377642512321472], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:59,576 - utils - INFO - stage3_gradient_single_runtime: 0.0062618255615234375
2023-09-28 23:26:59,580 - utils - INFO - 1, epoch: 1858, all client loss: [0.6311072707176208, 0.6308491230010986], all pred client disparities: [0.07123592495918274, 0.1037759780883789], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:59,636 - utils - INFO - stage3_gradient_single_runtime: 0.006161928176879883
2023-09-28 23:26:59,640 - utils - INFO - 1, epoch: 1859, all client loss: [0.6311072707176208, 0.6308491826057434], all pred client disparities: [0.07123643904924393, 0.10377544164657593], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:59,653 - utils - INFO - valid: True, epoch: 1859, loss: [0.6284719705581665, 0.6379915475845337], accuracy: [0.6367999911308289, 0.6450908780097961], mean_accuracy:0.6409454345703125,variance_accuracy:0.004145443439483643, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.0706530213356018, 0.11667299270629883]
2023-09-28 23:26:59,664 - utils - INFO - global_valid: True, epoch: 1859,  global_loss: 0.635016679763794, global_accuracy: 0.6958223289315726,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11356841027736664,
2023-09-28 23:26:59,727 - utils - INFO - stage3_gradient_single_runtime: 0.0065038204193115234
2023-09-28 23:26:59,733 - utils - INFO - 1, epoch: 1860, all client loss: [0.6311072111129761, 0.6308492422103882], all pred client disparities: [0.07123696058988571, 0.10377490520477295], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:59,792 - utils - INFO - stage3_gradient_single_runtime: 0.006031036376953125
2023-09-28 23:26:59,797 - utils - INFO - 1, epoch: 1861, all client loss: [0.6311071515083313, 0.630849301815033], all pred client disparities: [0.0712374821305275, 0.10377439856529236], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:59,855 - utils - INFO - stage3_gradient_single_runtime: 0.006183624267578125
2023-09-28 23:26:59,860 - utils - INFO - 1, epoch: 1862, all client loss: [0.6311071515083313, 0.6308494210243225], all pred client disparities: [0.07123799622058868, 0.10377389192581177], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:59,922 - utils - INFO - stage3_gradient_single_runtime: 0.006661891937255859
2023-09-28 23:26:59,928 - utils - INFO - 1, epoch: 1863, all client loss: [0.6311070322990417, 0.6308494210243225], all pred client disparities: [0.07123852521181107, 0.10377338528633118], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:26:59,986 - utils - INFO - stage3_gradient_single_runtime: 0.0060727596282958984
2023-09-28 23:26:59,990 - utils - INFO - 1, epoch: 1864, all client loss: [0.6311070322990417, 0.6308494806289673], all pred client disparities: [0.07123903930187225, 0.10377287864685059], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:00,051 - utils - INFO - stage3_gradient_single_runtime: 0.006279706954956055
2023-09-28 23:27:00,056 - utils - INFO - 1, epoch: 1865, all client loss: [0.631106972694397, 0.6308495998382568], all pred client disparities: [0.07123956084251404, 0.10377237945795059], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:00,114 - utils - INFO - stage3_gradient_single_runtime: 0.006155490875244141
2023-09-28 23:27:00,119 - utils - INFO - 1, epoch: 1866, all client loss: [0.631106972694397, 0.6308495998382568], all pred client disparities: [0.07124008983373642, 0.10377189517021179], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:00,177 - utils - INFO - stage3_gradient_single_runtime: 0.006250143051147461
2023-09-28 23:27:00,182 - utils - INFO - 1, epoch: 1867, all client loss: [0.6311069130897522, 0.6308496594429016], all pred client disparities: [0.07124058902263641, 0.10377132892608643], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:00,241 - utils - INFO - stage3_gradient_single_runtime: 0.006030082702636719
2023-09-28 23:27:00,245 - utils - INFO - 1, epoch: 1868, all client loss: [0.6311068534851074, 0.6308497786521912], all pred client disparities: [0.0712411031126976, 0.10377085208892822], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:00,302 - utils - INFO - stage3_gradient_single_runtime: 0.007290363311767578
2023-09-28 23:27:00,307 - utils - INFO - 1, epoch: 1869, all client loss: [0.6311068534851074, 0.6308498382568359], all pred client disparities: [0.0712416023015976, 0.10377034544944763], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2334, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:00,365 - utils - INFO - stage3_gradient_single_runtime: 0.006222963333129883
2023-09-28 23:27:00,370 - utils - INFO - 1, epoch: 1870, all client loss: [0.6311067938804626, 0.6308498978614807], all pred client disparities: [0.07124210894107819, 0.10376980900764465], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:00,427 - utils - INFO - stage3_gradient_single_runtime: 0.00615382194519043
2023-09-28 23:27:00,432 - utils - INFO - 1, epoch: 1871, all client loss: [0.6311067342758179, 0.6308499574661255], all pred client disparities: [0.07124263048171997, 0.10376933217048645], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:00,540 - utils - INFO - stage3_gradient_single_runtime: 0.0063323974609375
2023-09-28 23:27:00,545 - utils - INFO - 1, epoch: 1872, all client loss: [0.6311067342758179, 0.6308500170707703], all pred client disparities: [0.07124313712120056, 0.10376885533332825], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:00,603 - utils - INFO - stage3_gradient_single_runtime: 0.006117105484008789
2023-09-28 23:27:00,608 - utils - INFO - 1, epoch: 1873, all client loss: [0.6311066746711731, 0.6308501362800598], all pred client disparities: [0.07124363631010056, 0.10376831889152527], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:00,667 - utils - INFO - stage3_gradient_single_runtime: 0.007582902908325195
2023-09-28 23:27:00,672 - utils - INFO - 1, epoch: 1874, all client loss: [0.6311066746711731, 0.6308501362800598], all pred client disparities: [0.07124415040016174, 0.10376781225204468], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:00,732 - utils - INFO - stage3_gradient_single_runtime: 0.006023406982421875
2023-09-28 23:27:00,737 - utils - INFO - 1, epoch: 1875, all client loss: [0.6311066150665283, 0.6308501958847046], all pred client disparities: [0.07124466449022293, 0.10376736521720886], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:00,795 - utils - INFO - stage3_gradient_single_runtime: 0.006448984146118164
2023-09-28 23:27:00,801 - utils - INFO - 1, epoch: 1876, all client loss: [0.6311065554618835, 0.6308503150939941], all pred client disparities: [0.07124517858028412, 0.10376685857772827], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:00,858 - utils - INFO - stage3_gradient_single_runtime: 0.0062372684478759766
2023-09-28 23:27:00,863 - utils - INFO - 1, epoch: 1877, all client loss: [0.6311065554618835, 0.6308503746986389], all pred client disparities: [0.07124568521976471, 0.10376632213592529], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:00,925 - utils - INFO - stage3_gradient_single_runtime: 0.006882429122924805
2023-09-28 23:27:00,929 - utils - INFO - 1, epoch: 1878, all client loss: [0.6311064958572388, 0.6308503746986389], all pred client disparities: [0.0712461769580841, 0.10376584529876709], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:00,987 - utils - INFO - stage3_gradient_single_runtime: 0.006359577178955078
2023-09-28 23:27:00,992 - utils - INFO - 1, epoch: 1879, all client loss: [0.631106436252594, 0.6308504343032837], all pred client disparities: [0.0712466761469841, 0.1037653386592865], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:01,006 - utils - INFO - valid: True, epoch: 1879, loss: [0.6284719705581665, 0.6379933953285217], accuracy: [0.6367999911308289, 0.6450908780097961], mean_accuracy:0.6409454345703125,variance_accuracy:0.004145443439483643, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07066335529088974, 0.1166660487651825]
2023-09-28 23:27:01,017 - utils - INFO - global_valid: True, epoch: 1879,  global_loss: 0.635017991065979, global_accuracy: 0.6958183273309324,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11356592178344727,
2023-09-28 23:27:01,074 - utils - INFO - stage3_gradient_single_runtime: 0.006148815155029297
2023-09-28 23:27:01,079 - utils - INFO - 1, epoch: 1880, all client loss: [0.6311063766479492, 0.6308505535125732], all pred client disparities: [0.0712471604347229, 0.1037648618221283], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:01,138 - utils - INFO - stage3_gradient_single_runtime: 0.006153583526611328
2023-09-28 23:27:01,143 - utils - INFO - 1, epoch: 1881, all client loss: [0.6311063766479492, 0.6308505535125732], all pred client disparities: [0.07124766707420349, 0.1037643551826477], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:01,202 - utils - INFO - stage3_gradient_single_runtime: 0.006121158599853516
2023-09-28 23:27:01,207 - utils - INFO - 1, epoch: 1882, all client loss: [0.6311063766479492, 0.630850613117218], all pred client disparities: [0.07124816626310349, 0.1037638783454895], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:01,266 - utils - INFO - stage3_gradient_single_runtime: 0.006186008453369141
2023-09-28 23:27:01,270 - utils - INFO - 1, epoch: 1883, all client loss: [0.6311063170433044, 0.6308507323265076], all pred client disparities: [0.07124866545200348, 0.10376337170600891], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:01,379 - utils - INFO - stage3_gradient_single_runtime: 0.0061419010162353516
2023-09-28 23:27:01,384 - utils - INFO - 1, epoch: 1884, all client loss: [0.6311062574386597, 0.6308507919311523], all pred client disparities: [0.07124915719032288, 0.10376289486885071], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:01,442 - utils - INFO - stage3_gradient_single_runtime: 0.006310939788818359
2023-09-28 23:27:01,448 - utils - INFO - 1, epoch: 1885, all client loss: [0.6311062574386597, 0.6308507919311523], all pred client disparities: [0.07124966382980347, 0.1037624180316925], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:01,505 - utils - INFO - stage3_gradient_single_runtime: 0.006181240081787109
2023-09-28 23:27:01,510 - utils - INFO - 1, epoch: 1886, all client loss: [0.6311061382293701, 0.6308509111404419], all pred client disparities: [0.07125017046928406, 0.10376191139221191], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:01,568 - utils - INFO - stage3_gradient_single_runtime: 0.006112098693847656
2023-09-28 23:27:01,573 - utils - INFO - 1, epoch: 1887, all client loss: [0.6311061382293701, 0.6308509707450867], all pred client disparities: [0.07125067710876465, 0.10376140475273132], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:01,634 - utils - INFO - stage3_gradient_single_runtime: 0.006010532379150391
2023-09-28 23:27:01,638 - utils - INFO - 1, epoch: 1888, all client loss: [0.6311060786247253, 0.6308510303497314], all pred client disparities: [0.07125116139650345, 0.10376092791557312], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:01,696 - utils - INFO - stage3_gradient_single_runtime: 0.006325721740722656
2023-09-28 23:27:01,701 - utils - INFO - 1, epoch: 1889, all client loss: [0.6311060786247253, 0.6308510899543762], all pred client disparities: [0.07125164568424225, 0.1037604808807373], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:01,759 - utils - INFO - stage3_gradient_single_runtime: 0.0060575008392333984
2023-09-28 23:27:01,764 - utils - INFO - 1, epoch: 1890, all client loss: [0.6311060786247253, 0.630851149559021], all pred client disparities: [0.07125212997198105, 0.10375997424125671], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:01,823 - utils - INFO - stage3_gradient_single_runtime: 0.006411075592041016
2023-09-28 23:27:01,828 - utils - INFO - 1, epoch: 1891, all client loss: [0.6311059594154358, 0.6308512687683105], all pred client disparities: [0.07125262171030045, 0.10375946760177612], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:01,885 - utils - INFO - stage3_gradient_single_runtime: 0.006033420562744141
2023-09-28 23:27:01,890 - utils - INFO - 1, epoch: 1892, all client loss: [0.6311059594154358, 0.6308513283729553], all pred client disparities: [0.07125312089920044, 0.10375902056694031], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:01,949 - utils - INFO - stage3_gradient_single_runtime: 0.006185054779052734
2023-09-28 23:27:01,953 - utils - INFO - 1, epoch: 1893, all client loss: [0.6311059594154358, 0.6308513283729553], all pred client disparities: [0.07125359773635864, 0.10375848412513733], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:02,012 - utils - INFO - stage3_gradient_single_runtime: 0.006259918212890625
2023-09-28 23:27:02,017 - utils - INFO - 1, epoch: 1894, all client loss: [0.6311058402061462, 0.6308514475822449], all pred client disparities: [0.07125409692525864, 0.10375803709030151], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:02,077 - utils - INFO - stage3_gradient_single_runtime: 0.006112337112426758
2023-09-28 23:27:02,081 - utils - INFO - 1, epoch: 1895, all client loss: [0.6311058402061462, 0.6308515071868896], all pred client disparities: [0.07125458121299744, 0.10375756025314331], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:02,188 - utils - INFO - stage3_gradient_single_runtime: 0.0061855316162109375
2023-09-28 23:27:02,192 - utils - INFO - 1, epoch: 1896, all client loss: [0.6311058402061462, 0.6308515667915344], all pred client disparities: [0.07125505805015564, 0.1037571132183075], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:02,250 - utils - INFO - stage3_gradient_single_runtime: 0.0062100887298583984
2023-09-28 23:27:02,255 - utils - INFO - 1, epoch: 1897, all client loss: [0.6311057806015015, 0.6308516263961792], all pred client disparities: [0.07125555723905563, 0.1037566065788269], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:02,317 - utils - INFO - stage3_gradient_single_runtime: 0.0060460567474365234
2023-09-28 23:27:02,322 - utils - INFO - 1, epoch: 1898, all client loss: [0.6311057209968567, 0.630851686000824], all pred client disparities: [0.07125604897737503, 0.10375609993934631], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:02,380 - utils - INFO - stage3_gradient_single_runtime: 0.006295919418334961
2023-09-28 23:27:02,385 - utils - INFO - 1, epoch: 1899, all client loss: [0.6311056613922119, 0.630851686000824], all pred client disparities: [0.07125652581453323, 0.10375568270683289], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:02,398 - utils - INFO - valid: True, epoch: 1899, loss: [0.628471851348877, 0.637995183467865], accuracy: [0.6367999911308289, 0.6450908780097961], mean_accuracy:0.6409454345703125,variance_accuracy:0.004145443439483643, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07067333161830902, 0.11665928363800049]
2023-09-28 23:27:02,409 - utils - INFO - global_valid: True, epoch: 1899,  global_loss: 0.6350191831588745, global_accuracy: 0.6958188275310124,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11356359720230103,
2023-09-28 23:27:02,465 - utils - INFO - stage3_gradient_single_runtime: 0.006230831146240234
2023-09-28 23:27:02,470 - utils - INFO - 1, epoch: 1900, all client loss: [0.6311056613922119, 0.6308518052101135], all pred client disparities: [0.07125701010227203, 0.10375520586967468], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:02,530 - utils - INFO - stage3_gradient_single_runtime: 0.0064051151275634766
2023-09-28 23:27:02,536 - utils - INFO - 1, epoch: 1901, all client loss: [0.6311056017875671, 0.6308518648147583], all pred client disparities: [0.07125747948884964, 0.1037546694278717], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:02,593 - utils - INFO - stage3_gradient_single_runtime: 0.0062961578369140625
2023-09-28 23:27:02,598 - utils - INFO - 1, epoch: 1902, all client loss: [0.6311055421829224, 0.6308519840240479], all pred client disparities: [0.07125796377658844, 0.10375422239303589], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:02,658 - utils - INFO - stage3_gradient_single_runtime: 0.006307840347290039
2023-09-28 23:27:02,663 - utils - INFO - 1, epoch: 1903, all client loss: [0.6311055421829224, 0.6308519840240479], all pred client disparities: [0.07125844806432724, 0.10375374555587769], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:02,722 - utils - INFO - stage3_gradient_single_runtime: 0.006186485290527344
2023-09-28 23:27:02,726 - utils - INFO - 1, epoch: 1904, all client loss: [0.6311054825782776, 0.6308520436286926], all pred client disparities: [0.07125893235206604, 0.10375329852104187], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:02,789 - utils - INFO - stage3_gradient_single_runtime: 0.0061223506927490234
2023-09-28 23:27:02,794 - utils - INFO - 1, epoch: 1905, all client loss: [0.6311054825782776, 0.6308521628379822], all pred client disparities: [0.07125940918922424, 0.10375279188156128], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:02,853 - utils - INFO - stage3_gradient_single_runtime: 0.00623774528503418
2023-09-28 23:27:02,858 - utils - INFO - 1, epoch: 1906, all client loss: [0.6311054825782776, 0.6308521628379822], all pred client disparities: [0.07125989347696304, 0.10375234484672546], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:02,967 - utils - INFO - stage3_gradient_single_runtime: 0.0073719024658203125
2023-09-28 23:27:02,973 - utils - INFO - 1, epoch: 1907, all client loss: [0.631105363368988, 0.630852222442627], all pred client disparities: [0.07126036286354065, 0.10375186800956726], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:03,031 - utils - INFO - stage3_gradient_single_runtime: 0.0059473514556884766
2023-09-28 23:27:03,036 - utils - INFO - 1, epoch: 1908, all client loss: [0.631105363368988, 0.6308523416519165], all pred client disparities: [0.07126084715127945, 0.10375139117240906], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:03,094 - utils - INFO - stage3_gradient_single_runtime: 0.006208896636962891
2023-09-28 23:27:03,099 - utils - INFO - 1, epoch: 1909, all client loss: [0.6311053037643433, 0.6308524012565613], all pred client disparities: [0.07126133143901825, 0.10375094413757324], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:03,156 - utils - INFO - stage3_gradient_single_runtime: 0.0062067508697509766
2023-09-28 23:27:03,161 - utils - INFO - 1, epoch: 1910, all client loss: [0.6311052441596985, 0.630852460861206], all pred client disparities: [0.07126180082559586, 0.10375043749809265], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:03,222 - utils - INFO - stage3_gradient_single_runtime: 0.006198883056640625
2023-09-28 23:27:03,227 - utils - INFO - 1, epoch: 1911, all client loss: [0.6311052441596985, 0.6308525204658508], all pred client disparities: [0.07126227021217346, 0.10374999046325684], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:03,284 - utils - INFO - stage3_gradient_single_runtime: 0.0062427520751953125
2023-09-28 23:27:03,289 - utils - INFO - 1, epoch: 1912, all client loss: [0.6311051845550537, 0.6308525800704956], all pred client disparities: [0.07126273214817047, 0.10374951362609863], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:03,353 - utils - INFO - stage3_gradient_single_runtime: 0.006953716278076172
2023-09-28 23:27:03,358 - utils - INFO - 1, epoch: 1913, all client loss: [0.6311051845550537, 0.6308526992797852], all pred client disparities: [0.07126319408416748, 0.1037490963935852], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:03,417 - utils - INFO - stage3_gradient_single_runtime: 0.007768392562866211
2023-09-28 23:27:03,423 - utils - INFO - 1, epoch: 1914, all client loss: [0.6311051249504089, 0.6308526992797852], all pred client disparities: [0.07126366347074509, 0.103748619556427], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:03,482 - utils - INFO - stage3_gradient_single_runtime: 0.005970478057861328
2023-09-28 23:27:03,487 - utils - INFO - 1, epoch: 1915, all client loss: [0.6311050653457642, 0.6308528184890747], all pred client disparities: [0.07126414030790329, 0.1037481427192688], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:03,546 - utils - INFO - stage3_gradient_single_runtime: 0.006192684173583984
2023-09-28 23:27:03,550 - utils - INFO - 1, epoch: 1916, all client loss: [0.6311050653457642, 0.6308528780937195], all pred client disparities: [0.0712646022439003, 0.1037476658821106], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:03,608 - utils - INFO - stage3_gradient_single_runtime: 0.0062255859375
2023-09-28 23:27:03,613 - utils - INFO - 1, epoch: 1917, all client loss: [0.6311050057411194, 0.6308529376983643], all pred client disparities: [0.0712650790810585, 0.10374724864959717], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:03,670 - utils - INFO - stage3_gradient_single_runtime: 0.006073713302612305
2023-09-28 23:27:03,675 - utils - INFO - 1, epoch: 1918, all client loss: [0.6311049461364746, 0.630852997303009], all pred client disparities: [0.07126554846763611, 0.10374677181243896], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:03,732 - utils - INFO - stage3_gradient_single_runtime: 0.00621795654296875
2023-09-28 23:27:03,737 - utils - INFO - 1, epoch: 1919, all client loss: [0.6311049461364746, 0.6308530569076538], all pred client disparities: [0.07126603275537491, 0.10374632477760315], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:03,751 - utils - INFO - valid: True, epoch: 1919, loss: [0.6284717321395874, 0.6379969120025635], accuracy: [0.6367999911308289, 0.6450908780097961], mean_accuracy:0.6409454345703125,variance_accuracy:0.004145443439483643, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07068295031785965, 0.11665284633636475]
2023-09-28 23:27:03,822 - utils - INFO - global_valid: True, epoch: 1919,  global_loss: 0.63502037525177, global_accuracy: 0.6958083233293317,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11356133222579956,
2023-09-28 23:27:03,882 - utils - INFO - stage3_gradient_single_runtime: 0.006224155426025391
2023-09-28 23:27:03,887 - utils - INFO - 1, epoch: 1920, all client loss: [0.6311048865318298, 0.6308531165122986], all pred client disparities: [0.07126649469137192, 0.10374581813812256], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:03,944 - utils - INFO - stage3_gradient_single_runtime: 0.006077289581298828
2023-09-28 23:27:03,949 - utils - INFO - 1, epoch: 1921, all client loss: [0.6311048865318298, 0.6308531761169434], all pred client disparities: [0.07126696407794952, 0.10374540090560913], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:04,007 - utils - INFO - stage3_gradient_single_runtime: 0.006171226501464844
2023-09-28 23:27:04,012 - utils - INFO - 1, epoch: 1922, all client loss: [0.6311048269271851, 0.6308531761169434], all pred client disparities: [0.07126741856336594, 0.10374492406845093], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:04,071 - utils - INFO - stage3_gradient_single_runtime: 0.006388425827026367
2023-09-28 23:27:04,076 - utils - INFO - 1, epoch: 1923, all client loss: [0.6311048269271851, 0.6308532953262329], all pred client disparities: [0.07126788049936295, 0.1037445068359375], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:04,136 - utils - INFO - stage3_gradient_single_runtime: 0.006100893020629883
2023-09-28 23:27:04,141 - utils - INFO - 1, epoch: 1924, all client loss: [0.6311047673225403, 0.6308533549308777], all pred client disparities: [0.07126832008361816, 0.10374400019645691], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:04,199 - utils - INFO - stage3_gradient_single_runtime: 0.006258726119995117
2023-09-28 23:27:04,204 - utils - INFO - 1, epoch: 1925, all client loss: [0.6311047077178955, 0.6308534741401672], all pred client disparities: [0.07126879692077637, 0.1037435531616211], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:04,261 - utils - INFO - stage3_gradient_single_runtime: 0.0061206817626953125
2023-09-28 23:27:04,266 - utils - INFO - 1, epoch: 1926, all client loss: [0.6311047077178955, 0.6308534741401672], all pred client disparities: [0.07126925885677338, 0.10374310612678528], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:04,323 - utils - INFO - stage3_gradient_single_runtime: 0.006348609924316406
2023-09-28 23:27:04,329 - utils - INFO - 1, epoch: 1927, all client loss: [0.6311046481132507, 0.630853533744812], all pred client disparities: [0.07126972824335098, 0.10374262928962708], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:04,391 - utils - INFO - stage3_gradient_single_runtime: 0.006015777587890625
2023-09-28 23:27:04,396 - utils - INFO - 1, epoch: 1928, all client loss: [0.631104588508606, 0.6308536529541016], all pred client disparities: [0.0712701827287674, 0.10374224185943604], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:04,455 - utils - INFO - stage3_gradient_single_runtime: 0.006163597106933594
2023-09-28 23:27:04,460 - utils - INFO - 1, epoch: 1929, all client loss: [0.631104588508606, 0.6308537125587463], all pred client disparities: [0.0712706446647644, 0.10374176502227783], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:04,522 - utils - INFO - stage3_gradient_single_runtime: 0.00622868537902832
2023-09-28 23:27:04,527 - utils - INFO - 1, epoch: 1930, all client loss: [0.631104588508606, 0.6308537125587463], all pred client disparities: [0.07127109915018082, 0.10374131798744202], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:04,640 - utils - INFO - stage3_gradient_single_runtime: 0.006319999694824219
2023-09-28 23:27:04,645 - utils - INFO - 1, epoch: 1931, all client loss: [0.6311044692993164, 0.6308538317680359], all pred client disparities: [0.07127156853675842, 0.1037408709526062], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:04,707 - utils - INFO - stage3_gradient_single_runtime: 0.006838321685791016
2023-09-28 23:27:04,712 - utils - INFO - 1, epoch: 1932, all client loss: [0.6311044692993164, 0.6308538913726807], all pred client disparities: [0.07127201557159424, 0.10374045372009277], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:04,770 - utils - INFO - stage3_gradient_single_runtime: 0.006155729293823242
2023-09-28 23:27:04,774 - utils - INFO - 1, epoch: 1933, all client loss: [0.6311044096946716, 0.6308538913726807], all pred client disparities: [0.07127248495817184, 0.10373997688293457], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:04,837 - utils - INFO - stage3_gradient_single_runtime: 0.006067514419555664
2023-09-28 23:27:04,842 - utils - INFO - 1, epoch: 1934, all client loss: [0.6311044096946716, 0.6308540105819702], all pred client disparities: [0.07127292454242706, 0.10373950004577637], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:04,900 - utils - INFO - stage3_gradient_single_runtime: 0.006184577941894531
2023-09-28 23:27:04,905 - utils - INFO - 1, epoch: 1935, all client loss: [0.6311042904853821, 0.630854070186615], all pred client disparities: [0.07127337902784348, 0.10373908281326294], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:04,965 - utils - INFO - stage3_gradient_single_runtime: 0.0060672760009765625
2023-09-28 23:27:04,970 - utils - INFO - 1, epoch: 1936, all client loss: [0.6311042904853821, 0.630854070186615], all pred client disparities: [0.0712738186120987, 0.10373863577842712], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:05,030 - utils - INFO - stage3_gradient_single_runtime: 0.006013631820678711
2023-09-28 23:27:05,035 - utils - INFO - 1, epoch: 1937, all client loss: [0.6311042904853821, 0.6308541893959045], all pred client disparities: [0.07127426564693451, 0.10373818874359131], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:05,092 - utils - INFO - stage3_gradient_single_runtime: 0.006020545959472656
2023-09-28 23:27:05,097 - utils - INFO - 1, epoch: 1938, all client loss: [0.6311042308807373, 0.6308542490005493], all pred client disparities: [0.07127472013235092, 0.1037377417087555], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:05,161 - utils - INFO - stage3_gradient_single_runtime: 0.007486581802368164
2023-09-28 23:27:05,166 - utils - INFO - 1, epoch: 1939, all client loss: [0.6311041712760925, 0.6308542490005493], all pred client disparities: [0.07127517461776733, 0.10373726487159729], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:05,180 - utils - INFO - valid: True, epoch: 1939, loss: [0.6284715533256531, 0.637998640537262], accuracy: [0.6367999911308289, 0.6450908780097961], mean_accuracy:0.6409454345703125,variance_accuracy:0.004145443439483643, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07069219648838043, 0.11664658784866333]
2023-09-28 23:27:05,191 - utils - INFO - global_valid: True, epoch: 1939,  global_loss: 0.6350215077400208, global_accuracy: 0.6958033213285314,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11355912685394287,
2023-09-28 23:27:05,250 - utils - INFO - stage3_gradient_single_runtime: 0.006212472915649414
2023-09-28 23:27:05,256 - utils - INFO - 1, epoch: 1940, all client loss: [0.6311041712760925, 0.6308543682098389], all pred client disparities: [0.07127562165260315, 0.10373687744140625], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:05,314 - utils - INFO - stage3_gradient_single_runtime: 0.006281375885009766
2023-09-28 23:27:05,319 - utils - INFO - 1, epoch: 1941, all client loss: [0.6311041116714478, 0.6308544278144836], all pred client disparities: [0.07127606868743896, 0.10373640060424805], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:05,379 - utils - INFO - stage3_gradient_single_runtime: 0.006109714508056641
2023-09-28 23:27:05,384 - utils - INFO - 1, epoch: 1942, all client loss: [0.6311041116714478, 0.6308545470237732], all pred client disparities: [0.07127651572227478, 0.103736013174057], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:05,442 - utils - INFO - stage3_gradient_single_runtime: 0.0066986083984375
2023-09-28 23:27:05,448 - utils - INFO - 1, epoch: 1943, all client loss: [0.6311041116714478, 0.6308545470237732], all pred client disparities: [0.07127697020769119, 0.1037355363368988], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:05,556 - utils - INFO - stage3_gradient_single_runtime: 0.006297111511230469
2023-09-28 23:27:05,561 - utils - INFO - 1, epoch: 1944, all client loss: [0.6311039924621582, 0.630854606628418], all pred client disparities: [0.0712774246931076, 0.10373508930206299], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:05,620 - utils - INFO - stage3_gradient_single_runtime: 0.006112337112426758
2023-09-28 23:27:05,626 - utils - INFO - 1, epoch: 1945, all client loss: [0.6311039924621582, 0.6308546662330627], all pred client disparities: [0.07127787917852402, 0.10373464226722717], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:05,686 - utils - INFO - stage3_gradient_single_runtime: 0.006114482879638672
2023-09-28 23:27:05,691 - utils - INFO - 1, epoch: 1946, all client loss: [0.6311038732528687, 0.6308547258377075], all pred client disparities: [0.07127831876277924, 0.10373419523239136], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:05,750 - utils - INFO - stage3_gradient_single_runtime: 0.006268978118896484
2023-09-28 23:27:05,755 - utils - INFO - 1, epoch: 1947, all client loss: [0.6311038732528687, 0.6308548450469971], all pred client disparities: [0.07127875089645386, 0.10373377799987793], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:05,813 - utils - INFO - stage3_gradient_single_runtime: 0.0061495304107666016
2023-09-28 23:27:05,818 - utils - INFO - 1, epoch: 1948, all client loss: [0.6311038136482239, 0.6308549046516418], all pred client disparities: [0.07127920538187027, 0.10373333096504211], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:05,876 - utils - INFO - stage3_gradient_single_runtime: 0.006158351898193359
2023-09-28 23:27:05,881 - utils - INFO - 1, epoch: 1949, all client loss: [0.6311038136482239, 0.6308549046516418], all pred client disparities: [0.0712796300649643, 0.1037328839302063], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:05,944 - utils - INFO - stage3_gradient_single_runtime: 0.006095409393310547
2023-09-28 23:27:05,949 - utils - INFO - 1, epoch: 1950, all client loss: [0.6311038136482239, 0.6308549642562866], all pred client disparities: [0.07128007709980011, 0.10373249650001526], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:06,007 - utils - INFO - stage3_gradient_single_runtime: 0.0062601566314697266
2023-09-28 23:27:06,012 - utils - INFO - 1, epoch: 1951, all client loss: [0.6311038136482239, 0.6308550834655762], all pred client disparities: [0.07128050923347473, 0.10373201966285706], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:06,073 - utils - INFO - stage3_gradient_single_runtime: 0.0060613155364990234
2023-09-28 23:27:06,078 - utils - INFO - 1, epoch: 1952, all client loss: [0.6311036944389343, 0.630855143070221], all pred client disparities: [0.07128095626831055, 0.10373160243034363], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:06,138 - utils - INFO - stage3_gradient_single_runtime: 0.006083488464355469
2023-09-28 23:27:06,143 - utils - INFO - 1, epoch: 1953, all client loss: [0.6311036348342896, 0.6308552622795105], all pred client disparities: [0.07128140330314636, 0.10373115539550781], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:06,202 - utils - INFO - stage3_gradient_single_runtime: 0.006238460540771484
2023-09-28 23:27:06,207 - utils - INFO - 1, epoch: 1954, all client loss: [0.6311036348342896, 0.6308552622795105], all pred client disparities: [0.07128184288740158, 0.10373073816299438], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:06,265 - utils - INFO - stage3_gradient_single_runtime: 0.006167888641357422
2023-09-28 23:27:06,270 - utils - INFO - 1, epoch: 1955, all client loss: [0.6311035752296448, 0.6308553218841553], all pred client disparities: [0.0712822750210762, 0.10373029112815857], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:06,330 - utils - INFO - stage3_gradient_single_runtime: 0.00617671012878418
2023-09-28 23:27:06,335 - utils - INFO - 1, epoch: 1956, all client loss: [0.6311035752296448, 0.6308554410934448], all pred client disparities: [0.07128272205591202, 0.10372984409332275], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:06,440 - utils - INFO - stage3_gradient_single_runtime: 0.006339550018310547
2023-09-28 23:27:06,445 - utils - INFO - 1, epoch: 1957, all client loss: [0.631103515625, 0.6308554410934448], all pred client disparities: [0.07128315418958664, 0.10372945666313171], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:06,506 - utils - INFO - stage3_gradient_single_runtime: 0.006456851959228516
2023-09-28 23:27:06,511 - utils - INFO - 1, epoch: 1958, all client loss: [0.6311034560203552, 0.6308555006980896], all pred client disparities: [0.07128360122442245, 0.10372903943061829], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:06,568 - utils - INFO - stage3_gradient_single_runtime: 0.006126880645751953
2023-09-28 23:27:06,574 - utils - INFO - 1, epoch: 1959, all client loss: [0.631103515625, 0.6308556199073792], all pred client disparities: [0.07128404080867767, 0.10372856259346008], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:06,589 - utils - INFO - valid: True, epoch: 1959, loss: [0.6284714937210083, 0.6380003690719604], accuracy: [0.6367999911308289, 0.6450908780097961], mean_accuracy:0.6409454345703125,variance_accuracy:0.004145443439483643, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07070114463567734, 0.11664050817489624]
2023-09-28 23:27:06,600 - utils - INFO - global_valid: True, epoch: 1959,  global_loss: 0.6350226402282715, global_accuracy: 0.6957983193277311,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11355695128440857,
2023-09-28 23:27:06,659 - utils - INFO - stage3_gradient_single_runtime: 0.006264686584472656
2023-09-28 23:27:06,664 - utils - INFO - 1, epoch: 1960, all client loss: [0.6311033964157104, 0.6308556795120239], all pred client disparities: [0.0712844654917717, 0.10372817516326904], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:06,725 - utils - INFO - stage3_gradient_single_runtime: 0.00675201416015625
2023-09-28 23:27:06,730 - utils - INFO - 1, epoch: 1961, all client loss: [0.6311033368110657, 0.6308557391166687], all pred client disparities: [0.07128489017486572, 0.10372775793075562], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:06,788 - utils - INFO - stage3_gradient_single_runtime: 0.0061800479888916016
2023-09-28 23:27:06,792 - utils - INFO - 1, epoch: 1962, all client loss: [0.6311033368110657, 0.6308557391166687], all pred client disparities: [0.07128532230854034, 0.10372728109359741], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:06,856 - utils - INFO - stage3_gradient_single_runtime: 0.00603795051574707
2023-09-28 23:27:06,860 - utils - INFO - 1, epoch: 1963, all client loss: [0.6311032772064209, 0.6308558583259583], all pred client disparities: [0.07128575444221497, 0.10372689366340637], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:06,918 - utils - INFO - stage3_gradient_single_runtime: 0.006293773651123047
2023-09-28 23:27:06,924 - utils - INFO - 1, epoch: 1964, all client loss: [0.6311032772064209, 0.630855917930603], all pred client disparities: [0.07128618657588959, 0.10372644662857056], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:06,984 - utils - INFO - stage3_gradient_single_runtime: 0.006078481674194336
2023-09-28 23:27:06,989 - utils - INFO - 1, epoch: 1965, all client loss: [0.6311032176017761, 0.6308559775352478], all pred client disparities: [0.07128661870956421, 0.10372602939605713], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:07,051 - utils - INFO - stage3_gradient_single_runtime: 0.006121158599853516
2023-09-28 23:27:07,056 - utils - INFO - 1, epoch: 1966, all client loss: [0.6311032176017761, 0.6308560371398926], all pred client disparities: [0.07128705084323883, 0.10372564196586609], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:07,113 - utils - INFO - stage3_gradient_single_runtime: 0.0061495304107666016
2023-09-28 23:27:07,118 - utils - INFO - 1, epoch: 1967, all client loss: [0.6311031579971313, 0.6308560967445374], all pred client disparities: [0.07128749787807465, 0.10372522473335266], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:07,225 - utils - INFO - stage3_gradient_single_runtime: 0.006285905838012695
2023-09-28 23:27:07,230 - utils - INFO - 1, epoch: 1968, all client loss: [0.6311030983924866, 0.6308561563491821], all pred client disparities: [0.07128791511058807, 0.10372477769851685], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:07,292 - utils - INFO - stage3_gradient_single_runtime: 0.006127595901489258
2023-09-28 23:27:07,298 - utils - INFO - 1, epoch: 1969, all client loss: [0.631102979183197, 0.6308562159538269], all pred client disparities: [0.0712883397936821, 0.1037243902683258], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:07,355 - utils - INFO - stage3_gradient_single_runtime: 0.006269931793212891
2023-09-28 23:27:07,360 - utils - INFO - 1, epoch: 1970, all client loss: [0.631102979183197, 0.6308562755584717], all pred client disparities: [0.07128877937793732, 0.10372397303581238], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:07,420 - utils - INFO - stage3_gradient_single_runtime: 0.0060923099517822266
2023-09-28 23:27:07,424 - utils - INFO - 1, epoch: 1971, all client loss: [0.631102979183197, 0.6308563351631165], all pred client disparities: [0.07128920406103134, 0.10372352600097656], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:07,483 - utils - INFO - stage3_gradient_single_runtime: 0.007273674011230469
2023-09-28 23:27:07,489 - utils - INFO - 1, epoch: 1972, all client loss: [0.631102979183197, 0.6308563947677612], all pred client disparities: [0.07128963619470596, 0.10372313857078552], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:07,546 - utils - INFO - stage3_gradient_single_runtime: 0.005975008010864258
2023-09-28 23:27:07,551 - utils - INFO - 1, epoch: 1973, all client loss: [0.631102979183197, 0.630856454372406], all pred client disparities: [0.0712900459766388, 0.1037227213382721], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:07,610 - utils - INFO - stage3_gradient_single_runtime: 0.006221771240234375
2023-09-28 23:27:07,615 - utils - INFO - 1, epoch: 1974, all client loss: [0.6311029195785522, 0.6308565735816956], all pred client disparities: [0.07129047811031342, 0.10372227430343628], all client disparities: [0.060876332223415375, 0.11099925637245178], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:07,675 - utils - INFO - stage3_gradient_single_runtime: 0.006218433380126953
2023-09-28 23:27:07,679 - utils - INFO - 1, epoch: 1975, all client loss: [0.6311028599739075, 0.6308566331863403], all pred client disparities: [0.07129088789224625, 0.10372191667556763], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:07,740 - utils - INFO - stage3_gradient_single_runtime: 0.0064814090728759766
2023-09-28 23:27:07,745 - utils - INFO - 1, epoch: 1976, all client loss: [0.6311028003692627, 0.6308566331863403], all pred client disparities: [0.07129130512475967, 0.10372141003608704], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:07,802 - utils - INFO - stage3_gradient_single_runtime: 0.006211280822753906
2023-09-28 23:27:07,807 - utils - INFO - 1, epoch: 1977, all client loss: [0.6311028003692627, 0.6308567523956299], all pred client disparities: [0.0712917298078537, 0.10372099280357361], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:07,867 - utils - INFO - stage3_gradient_single_runtime: 0.006104946136474609
2023-09-28 23:27:07,872 - utils - INFO - 1, epoch: 1978, all client loss: [0.6311026811599731, 0.6308568120002747], all pred client disparities: [0.07129216194152832, 0.10372057557106018], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:07,929 - utils - INFO - stage3_gradient_single_runtime: 0.006200075149536133
2023-09-28 23:27:07,934 - utils - INFO - 1, epoch: 1979, all client loss: [0.6311026811599731, 0.6308568716049194], all pred client disparities: [0.07129258662462234, 0.10372021794319153], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6687794327735901],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:07,950 - utils - INFO - valid: True, epoch: 1979, loss: [0.6284712553024292, 0.6380019783973694], accuracy: [0.6367999911308289, 0.6450908780097961], mean_accuracy:0.6409454345703125,variance_accuracy:0.004145443439483643, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.07070979475975037, 0.11663466691970825]
2023-09-28 23:27:07,961 - utils - INFO - global_valid: True, epoch: 1979,  global_loss: 0.6350237131118774, global_accuracy: 0.6957943177270909,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11355488002300262,
2023-09-28 23:27:08,019 - utils - INFO - stage3_gradient_single_runtime: 0.0061266422271728516
2023-09-28 23:27:08,024 - utils - INFO - 1, epoch: 1980, all client loss: [0.6311026811599731, 0.6308569312095642], all pred client disparities: [0.07129300385713577, 0.1037198007106781], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:08,085 - utils - INFO - stage3_gradient_single_runtime: 0.006211042404174805
2023-09-28 23:27:08,090 - utils - INFO - 1, epoch: 1981, all client loss: [0.6311026215553284, 0.630856990814209], all pred client disparities: [0.0712934210896492, 0.10371938347816467], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:08,200 - utils - INFO - stage3_gradient_single_runtime: 0.0063974857330322266
2023-09-28 23:27:08,206 - utils - INFO - 1, epoch: 1982, all client loss: [0.6311025619506836, 0.6308570504188538], all pred client disparities: [0.07129383832216263, 0.10371899604797363], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:08,263 - utils - INFO - stage3_gradient_single_runtime: 0.006255626678466797
2023-09-28 23:27:08,268 - utils - INFO - 1, epoch: 1983, all client loss: [0.6311025023460388, 0.6308571100234985], all pred client disparities: [0.07129425555467606, 0.10371854901313782], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:08,331 - utils - INFO - stage3_gradient_single_runtime: 0.006101131439208984
2023-09-28 23:27:08,336 - utils - INFO - 1, epoch: 1984, all client loss: [0.6311025023460388, 0.6308571696281433], all pred client disparities: [0.07129468023777008, 0.10371816158294678], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:08,394 - utils - INFO - stage3_gradient_single_runtime: 0.006128787994384766
2023-09-28 23:27:08,400 - utils - INFO - 1, epoch: 1985, all client loss: [0.631102442741394, 0.6308572292327881], all pred client disparities: [0.07129509747028351, 0.10371771454811096], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:08,461 - utils - INFO - stage3_gradient_single_runtime: 0.0060236454010009766
2023-09-28 23:27:08,465 - utils - INFO - 1, epoch: 1986, all client loss: [0.631102442741394, 0.6308572888374329], all pred client disparities: [0.07129550725221634, 0.10371732711791992], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:08,525 - utils - INFO - stage3_gradient_single_runtime: 0.006251811981201172
2023-09-28 23:27:08,530 - utils - INFO - 1, epoch: 1987, all client loss: [0.631102442741394, 0.6308573484420776], all pred client disparities: [0.07129591703414917, 0.1037169098854065], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:08,590 - utils - INFO - stage3_gradient_single_runtime: 0.0061800479888916016
2023-09-28 23:27:08,595 - utils - INFO - 1, epoch: 1988, all client loss: [0.6311023831367493, 0.6308574676513672], all pred client disparities: [0.0712963193655014, 0.10371652245521545], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:08,658 - utils - INFO - stage3_gradient_single_runtime: 0.006079912185668945
2023-09-28 23:27:08,663 - utils - INFO - 1, epoch: 1989, all client loss: [0.6311023235321045, 0.630857527256012], all pred client disparities: [0.07129673659801483, 0.10371610522270203], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:08,722 - utils - INFO - stage3_gradient_single_runtime: 0.006266593933105469
2023-09-28 23:27:08,727 - utils - INFO - 1, epoch: 1990, all client loss: [0.6311023235321045, 0.6308575868606567], all pred client disparities: [0.07129713892936707, 0.10371565818786621], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:08,787 - utils - INFO - stage3_gradient_single_runtime: 0.006145954132080078
2023-09-28 23:27:08,792 - utils - INFO - 1, epoch: 1991, all client loss: [0.6311023235321045, 0.6308576464653015], all pred client disparities: [0.0712975561618805, 0.10371524095535278], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:08,849 - utils - INFO - stage3_gradient_single_runtime: 0.006201267242431641
2023-09-28 23:27:08,854 - utils - INFO - 1, epoch: 1992, all client loss: [0.6311022043228149, 0.6308577060699463], all pred client disparities: [0.07129797339439392, 0.10371488332748413], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:08,917 - utils - INFO - stage3_gradient_single_runtime: 0.006036281585693359
2023-09-28 23:27:08,922 - utils - INFO - 1, epoch: 1993, all client loss: [0.6311021447181702, 0.6308577656745911], all pred client disparities: [0.07129839062690735, 0.10371449589729309], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2333, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:09,032 - utils - INFO - stage3_gradient_single_runtime: 0.006078243255615234
2023-09-28 23:27:09,037 - utils - INFO - 1, epoch: 1994, all client loss: [0.6311021447181702, 0.6308578252792358], all pred client disparities: [0.07129880040884018, 0.10371407866477966], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2332, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:09,095 - utils - INFO - stage3_gradient_single_runtime: 0.006112813949584961
2023-09-28 23:27:09,101 - utils - INFO - 1, epoch: 1995, all client loss: [0.6311020851135254, 0.6308578848838806], all pred client disparities: [0.07129920274019241, 0.10371369123458862], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2332, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:09,162 - utils - INFO - stage3_gradient_single_runtime: 0.005972385406494141
2023-09-28 23:27:09,166 - utils - INFO - 1, epoch: 1996, all client loss: [0.6311020851135254, 0.6308580040931702], all pred client disparities: [0.07129961252212524, 0.10371321439743042], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2332, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:09,228 - utils - INFO - stage3_gradient_single_runtime: 0.0062105655670166016
2023-09-28 23:27:09,233 - utils - INFO - 1, epoch: 1997, all client loss: [0.6311020255088806, 0.6308580040931702], all pred client disparities: [0.07130002230405807, 0.10371288657188416], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2332, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:09,294 - utils - INFO - stage3_gradient_single_runtime: 0.0077931880950927734
2023-09-28 23:27:09,300 - utils - INFO - 1, epoch: 1998, all client loss: [0.6311019659042358, 0.6308580636978149], all pred client disparities: [0.0713004469871521, 0.10371246933937073], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2332, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:09,361 - utils - INFO - stage3_gradient_single_runtime: 0.006126880645751953
2023-09-28 23:27:09,366 - utils - INFO - 1, epoch: 1999, all client loss: [0.6311019659042358, 0.6308581829071045], all pred client disparities: [0.07130086421966553, 0.10371208190917969], all client disparities: [0.060876332223415375, 0.1105678379535675], all client accs: [0.6198546886444092, 0.6685983538627625],alphas:tensor([0.4528, 0.2332, 0.3139, 0.0000, 0.0000], device='cuda:0',
       dtype=torch.float64)
2023-09-28 23:27:09,380 - utils - INFO - valid: True, epoch: 1999, loss: [0.6284710764884949, 0.6380036473274231], accuracy: [0.6367999911308289, 0.6450908780097961], mean_accuracy:0.6409454345703125,variance_accuracy:0.004145443439483643, disparity: [0.06247392296791077, 0.13128617405891418], mean_disparity:0.09688004851341248,variance_disparity:0.03440612554550171, pred_disparity: [0.0707181841135025, 0.11662900447845459]
2023-09-28 23:27:09,391 - utils - INFO - global_valid: True, epoch: 1999,  global_loss: 0.6350247859954834, global_accuracy: 0.6957888155262105,  global_disparity:0.12307125329971313, global_pred_disparity: 0.11355286836624146,
2023-09-28 23:27:09,391 - utils - INFO - stage3_runtime: 34.71777558326721
