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lunwentest_cifar100_DPFC_noiid8_400.log
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nohup: ignoring input
cuda:1
Namespace(batch_size=144, bn_sparsity=0.9, classes_per_user=8, clip_bound=2, clipping_style='all-layer', cluster_project_lr=0.03, cluster_temperature=1.0, dataset='CIFAR-100', dataset_dir='/home/chenyannan/fast-differential-privacy-main/examples/image_classification/data', downsample_lr=0.04, epochs=12, epsilon=8, feature_dim=128, global_lr=8, image_size=224, instance_project_lr=0.03, instance_temperature=0.5, kl_threshold=0.7, learning_rate=0.04, linear_sparsity=0.75, local_epoch=5, loss_KL=0.5, mini_bs=144, miu=0.05, miuh=0.5, miuw=0, model_path='save/Cifar-100-DPFL-ResNet18-dpfc', momentum=0.3, n_clients=400, num_class=20, r_conv=6, r_proj=16, reload=False, resnet='ResNet18_lora', resnet_lr=0.13, sample_ratio=1, seed=17, smooth_K=6, smooth_loss_radius=2, smooth_step=0, start_epoch=0, test_image_size=256, thou=0.1, trans_lr=0.02, weight_decay=1e-05, workers=8)
len label: 57600
sigma: 1.8017578125
W.weight 10240 torch.Size([20, 512])
H.weight 1152000 torch.Size([57600, 20])
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Round: 0 User: 382 Train Loss: 1359.292
Norm: tensor(30.5886, device='cuda:1')
Round: 0 User: 383 Train Loss: 1309.246
Norm: tensor(28.0580, device='cuda:1')
Round: 0 User: 384 Train Loss: 1254.174
Norm: tensor(30.4860, device='cuda:1')
Round: 0 User: 385 Train Loss: 1307.686
Norm: tensor(29.3595, device='cuda:1')
Round: 0 User: 386 Train Loss: 1305.482
Norm: tensor(29.6884, device='cuda:1')
Round: 0 User: 387 Train Loss: 1277.351
Norm: tensor(31.0493, device='cuda:1')
Round: 0 User: 388 Train Loss: 1355.252
Norm: tensor(29.4180, device='cuda:1')
Round: 0 User: 389 Train Loss: 1276.247
Norm: tensor(28.8808, device='cuda:1')
Round: 0 User: 390 Train Loss: 1297.308
Norm: tensor(29.1420, device='cuda:1')
Round: 0 User: 391 Train Loss: 1277.036
Norm: tensor(29.2666, device='cuda:1')
Round: 0 User: 392 Train Loss: 1293.697
Norm: tensor(29.5016, device='cuda:1')
Round: 0 User: 393 Train Loss: 1256.943
Norm: tensor(30.1118, device='cuda:1')
Round: 0 User: 394 Train Loss: 1310.125
Norm: tensor(28.3278, device='cuda:1')
Round: 0 User: 395 Train Loss: 1258.905
Norm: tensor(29.7696, device='cuda:1')
Round: 0 User: 396 Train Loss: 1299.001
Norm: tensor(29.3777, device='cuda:1')
Round: 0 User: 397 Train Loss: 1301.006
Norm: tensor(30.4860, device='cuda:1')
Round: 0 User: 398 Train Loss: 1328.744
Norm: tensor(30.0779, device='cuda:1')
Round: 0 User: 399 Train Loss: 1317.240
count 400
updated norm: tensor(1.9726, device='cuda:1')
tensor([ 9, 11, 16, ..., 11, 11, 8]) [15 15 15 ... 14 14 14]
### Creating features from model ###
Global NMI = 0.0171 ARI = 0.0030 F = 0.1022 ACC = 0.0765
Norm: tensor(6.6037, device='cuda:1')
Round: 1 User: 0 Train Loss: 747.719
Norm: tensor(6.4041, device='cuda:1')
Round: 1 User: 1 Train Loss: 756.220
Norm: tensor(5.5809, device='cuda:1')
Round: 1 User: 2 Train Loss: 652.955
Norm: tensor(6.4674, device='cuda:1')
Round: 1 User: 3 Train Loss: 735.953
Norm: tensor(6.6885, device='cuda:1')
Round: 1 User: 4 Train Loss: 753.171
Norm: tensor(6.1014, device='cuda:1')
Round: 1 User: 5 Train Loss: 698.320
Norm: tensor(6.2867, device='cuda:1')
Round: 1 User: 6 Train Loss: 742.941
Norm: tensor(6.4676, device='cuda:1')
Round: 1 User: 7 Train Loss: 770.469
Norm: tensor(6.5894, device='cuda:1')
Round: 1 User: 8 Train Loss: 749.977
Norm: tensor(5.7286, device='cuda:1')
Round: 1 User: 9 Train Loss: 663.647
Norm: tensor(6.5219, device='cuda:1')
Round: 1 User: 10 Train Loss: 745.642
Norm: tensor(5.9421, device='cuda:1')
Round: 1 User: 11 Train Loss: 703.344
Norm: tensor(5.8596, device='cuda:1')
Round: 1 User: 12 Train Loss: 696.384
Norm: tensor(6.0632, device='cuda:1')
Round: 1 User: 13 Train Loss: 722.690
Norm: tensor(6.3830, device='cuda:1')
Round: 1 User: 14 Train Loss: 724.953
Norm: tensor(5.6495, device='cuda:1')
Round: 1 User: 15 Train Loss: 686.592
Norm: tensor(6.1416, device='cuda:1')
Round: 1 User: 16 Train Loss: 707.260
Norm: tensor(7.1045, device='cuda:1')
Round: 1 User: 17 Train Loss: 795.714
Norm: tensor(6.0948, device='cuda:1')
Round: 1 User: 18 Train Loss: 689.315
Norm: tensor(6.1543, device='cuda:1')
Round: 1 User: 19 Train Loss: 728.970
Norm: tensor(6.2756, device='cuda:1')
Round: 1 User: 20 Train Loss: 731.909
Norm: tensor(6.2622, device='cuda:1')
Round: 1 User: 21 Train Loss: 712.013
Norm: tensor(5.8359, device='cuda:1')
Round: 1 User: 22 Train Loss: 689.304
Norm: tensor(5.5924, device='cuda:1')
Round: 1 User: 23 Train Loss: 681.500
Norm: tensor(6.9691, device='cuda:1')
Round: 1 User: 24 Train Loss: 775.153
Norm: tensor(6.1710, device='cuda:1')
Round: 1 User: 25 Train Loss: 728.147
Norm: tensor(5.8020, device='cuda:1')
Round: 1 User: 26 Train Loss: 671.416
Norm: tensor(6.7176, device='cuda:1')
Round: 1 User: 27 Train Loss: 770.720
Norm: tensor(6.2114, device='cuda:1')
Round: 1 User: 28 Train Loss: 743.341
Norm: tensor(6.4576, device='cuda:1')
Round: 1 User: 29 Train Loss: 724.141
Norm: tensor(5.5081, device='cuda:1')
Round: 1 User: 30 Train Loss: 660.687
Norm: tensor(6.6616, device='cuda:1')
Round: 1 User: 31 Train Loss: 755.999
Norm: tensor(6.2204, device='cuda:1')
Round: 1 User: 32 Train Loss: 724.058
Norm: tensor(6.7269, device='cuda:1')
Round: 1 User: 33 Train Loss: 773.452
Norm: tensor(6.3567, device='cuda:1')
Round: 1 User: 34 Train Loss: 730.730
Norm: tensor(5.9668, device='cuda:1')
Round: 1 User: 35 Train Loss: 709.767
Norm: tensor(6.3681, device='cuda:1')
Round: 1 User: 36 Train Loss: 744.418
Norm: tensor(6.1544, device='cuda:1')
Round: 1 User: 37 Train Loss: 711.439
Norm: tensor(5.8364, device='cuda:1')
Round: 1 User: 38 Train Loss: 715.096
Norm: tensor(6.3632, device='cuda:1')
Round: 1 User: 39 Train Loss: 714.436
Norm: tensor(6.2399, device='cuda:1')
Round: 1 User: 40 Train Loss: 727.183
Norm: tensor(6.1151, device='cuda:1')
Round: 1 User: 41 Train Loss: 723.248
Norm: tensor(6.3047, device='cuda:1')
Round: 1 User: 42 Train Loss: 720.471
Norm: tensor(6.3437, device='cuda:1')
Round: 1 User: 43 Train Loss: 752.505
Norm: tensor(5.9956, device='cuda:1')
Round: 1 User: 44 Train Loss: 687.069
Norm: tensor(6.5044, device='cuda:1')
Round: 1 User: 45 Train Loss: 742.503
Norm: tensor(6.6670, device='cuda:1')
Round: 1 User: 46 Train Loss: 753.596
Norm: tensor(5.7667, device='cuda:1')
Round: 1 User: 47 Train Loss: 670.926
Norm: tensor(6.3535, device='cuda:1')
Round: 1 User: 48 Train Loss: 737.721
Norm: tensor(6.1351, device='cuda:1')
Round: 1 User: 49 Train Loss: 735.857
Norm: tensor(5.8569, device='cuda:1')
Round: 1 User: 50 Train Loss: 704.820
Norm: tensor(6.4883, device='cuda:1')
Round: 1 User: 51 Train Loss: 753.995
Norm: tensor(6.4027, device='cuda:1')
Round: 1 User: 52 Train Loss: 736.337
Norm: tensor(6.1818, device='cuda:1')
Round: 1 User: 53 Train Loss: 720.657
Norm: tensor(6.1430, device='cuda:1')
Round: 1 User: 54 Train Loss: 720.268
Norm: tensor(6.2940, device='cuda:1')
Round: 1 User: 55 Train Loss: 744.824
Norm: tensor(5.4736, device='cuda:1')
Round: 1 User: 56 Train Loss: 643.382
Norm: tensor(6.1428, device='cuda:1')
Round: 1 User: 57 Train Loss: 716.929
Norm: tensor(5.7884, device='cuda:1')
Round: 1 User: 58 Train Loss: 689.189
Norm: tensor(6.7806, device='cuda:1')
Round: 1 User: 59 Train Loss: 772.434
Norm: tensor(6.5215, device='cuda:1')
Round: 1 User: 60 Train Loss: 744.446
Norm: tensor(5.8164, device='cuda:1')
Round: 1 User: 61 Train Loss: 689.436
Norm: tensor(6.6510, device='cuda:1')
Round: 1 User: 62 Train Loss: 739.648
Norm: tensor(6.3357, device='cuda:1')
Round: 1 User: 63 Train Loss: 743.668
Norm: tensor(5.7545, device='cuda:1')
Round: 1 User: 64 Train Loss: 668.334
Norm: tensor(5.9852, device='cuda:1')
Round: 1 User: 65 Train Loss: 705.461
Norm: tensor(6.6763, device='cuda:1')
Round: 1 User: 66 Train Loss: 756.427
Norm: tensor(5.7300, device='cuda:1')
Round: 1 User: 67 Train Loss: 683.710
Norm: tensor(6.4663, device='cuda:1')
Round: 1 User: 68 Train Loss: 732.596
Norm: tensor(6.1630, device='cuda:1')
Round: 1 User: 69 Train Loss: 723.600
Norm: tensor(6.7728, device='cuda:1')
Round: 1 User: 70 Train Loss: 769.207
Norm: tensor(5.8702, device='cuda:1')
Round: 1 User: 71 Train Loss: 694.768
Norm: tensor(5.8757, device='cuda:1')
Round: 1 User: 72 Train Loss: 703.521
Norm: tensor(6.2310, device='cuda:1')
Round: 1 User: 73 Train Loss: 723.174
Norm: tensor(6.2383, device='cuda:1')
Round: 1 User: 74 Train Loss: 720.626
Norm: tensor(5.9110, device='cuda:1')
Round: 1 User: 75 Train Loss: 694.202
Norm: tensor(6.0779, device='cuda:1')
Round: 1 User: 76 Train Loss: 701.531
Norm: tensor(6.2067, device='cuda:1')
Round: 1 User: 77 Train Loss: 736.651
Norm: tensor(6.6070, device='cuda:1')
Round: 1 User: 78 Train Loss: 751.407
Norm: tensor(6.0528, device='cuda:1')
Round: 1 User: 79 Train Loss: 700.913
Norm: tensor(6.9827, device='cuda:1')
Round: 1 User: 80 Train Loss: 790.535
Norm: tensor(5.9181, device='cuda:1')
Round: 1 User: 81 Train Loss: 711.088
Norm: tensor(6.1294, device='cuda:1')
Round: 1 User: 82 Train Loss: 706.252
Norm: tensor(6.0020, device='cuda:1')
Round: 1 User: 83 Train Loss: 692.009
Norm: tensor(6.4628, device='cuda:1')
Round: 1 User: 84 Train Loss: 745.696
Norm: tensor(6.3604, device='cuda:1')
Round: 1 User: 85 Train Loss: 735.041
Norm: tensor(6.1633, device='cuda:1')
Round: 1 User: 86 Train Loss: 707.157
Norm: tensor(6.1640, device='cuda:1')
Round: 1 User: 87 Train Loss: 736.813
Norm: tensor(6.2060, device='cuda:1')
Round: 1 User: 88 Train Loss: 731.309
Norm: tensor(6.1383, device='cuda:1')
Round: 1 User: 89 Train Loss: 695.784
Norm: tensor(5.7801, device='cuda:1')
Round: 1 User: 90 Train Loss: 680.937
Norm: tensor(6.1313, device='cuda:1')
Round: 1 User: 91 Train Loss: 704.849
Norm: tensor(6.1672, device='cuda:1')
Round: 1 User: 92 Train Loss: 715.599
Norm: tensor(6.4405, device='cuda:1')
Round: 1 User: 93 Train Loss: 748.095